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title: 'Medication Regimen Complexity Index Score at Admission as a Predictor of Inpatient
Outcomes: A Machine Learning Approach'
authors:
- Yves Paul Vincent Mbous
- Todd Brothers
- Mohammad A. Al-Mamun
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967355
doi: 10.3390/ijerph20043760
license: CC BY 4.0
---
# Medication Regimen Complexity Index Score at Admission as a Predictor of Inpatient Outcomes: A Machine Learning Approach
## Abstract
Background: In the intensive care unit, traditional scoring systems use illness severity and/or organ failure to determine prognosis, and this usually rests on the patient’s condition at admission. In spite of the importance of medication reconciliation, the usefulness of home medication histories as predictors of clinical outcomes remains unexplored. Methods: A retrospective cohort study was conducted using the medical records of 322 intensive care unit (ICU) patients. The predictors of interest included the medication regimen complexity index (MRCI) at admission, the Acute Physiology and Chronic Health Evaluation (APACHE) II, the Sequential Organ Failure Assessment (SOFA) score, or a combination thereof. Outcomes included mortality, length of stay, and the need for mechanical ventilation. Machine learning algorithms were used for outcome classification after correcting for class imbalances in the general population and across the racial continuum. Results: The home medication model could predict all clinical outcomes accurately $70\%$ of the time. Among Whites, it improved to $80\%$, whereas among non-Whites it remained at $70\%$. The addition of SOFA and APACHE II yielded the best models among non-Whites and Whites, respectively. SHapley Additive exPlanations (SHAP) values showed that low MRCI scores were associated with reduced mortality and LOS, yet an increased need for mechanical ventilation. Conclusion: Home medication histories represent a viable addition to traditional predictors of health outcomes.
## 1. Introduction
Obtaining an initial medication history at admission can significantly influence clinical outcomes [1], yet traditional scoring systems, such as APACHE or SOFA, remain the preferred prognostic tools [2,3,4]. Indeed, medication reconciliation informs on the negative consequences of medication list discrepancies [5]. Complete medication histories can help prevent medication errors and adverse drug events (ADEs) [6,7], which are more common among intensive care unit (ICU) patients than hospitalized patients [8].
Estimates of the clinical significance of medical histories in terms of medication errors range between $11\%$ and $59\%$ [9]. Medication errors are the third leading cause of hospital readmissions in the United States [10] and a significant cause of morbidity and mortality [11]. One hundred thousand people die each year as a result of medication errors in hospitals and clinics [12]. The incidence of adverse drug events is 6.5 per 100 admissions, with $28\%$ of them judged preventable [13]. About 100,000 people die each year as a result of medication errors in hospitals and clinics. Moreover, medication errors cost approximately USD 20 billion each year [12]. The stratification of these costs per race remains unknown to the best of our knowledge; a curious fact in light of extant racial health disparities in the US. As minorities incur more medication errors and adverse drug events than Whites in the US [14,15,16], it stands to reason that they should also bear higher costs.
To reduce the burden of medication errors and ADEs and their costs, the assessment of accurate medication histories is essential. For this purpose, pharmacists capture medication regimen complexity, which encompasses medication dosage, frequency, and route [17]. In clinical pharmacy practice, the most commonly used tool for the assessment of medication regimen complexity is the Medication Regimen Complexity Index (MRCI) [18]. Although initially developed and validated in outpatient settings [19,20], the MRCI has been validated across various other medical settings and populations, thus making it a gold standard for assessing medication regimen complexity [18]. Previous findings show that MRCI is correlated with health outcomes, specifically prognosis (of diabetes and hepatocellular carcinoma) but also mortality [21]. Two different studies utilized registry data and hospital records to show that high MRCI scores were associated with higher 4-year mortality, and higher odds of mortality (adjusted odds ratio = 1.12) [22,23], respectively. A recent study showed that higher MRCI was associated with increased mortality, a longer ICU length of stay (LOS), and the need for mechanical ventilation (MV) [17]. As the literature suggests that medication complexity scores are higher among Blacks compared to Whites [24], it is highly probable that the clinical burden exacted on minorities is also higher. This, however, remains to be explored.
When taken at admission, MRCI scores, which reflect patient medication histories, could help better predict outcomes of importance, especially among critically ill patients, who are subject to far more intense treatment. In clinical settings, traditional scoring systems, such as SOFA and APACHE II remain the primary indicators of disease severity [2]. In the ICU, the ratio of critical care pharmacists to patients is sub-optimal (the median number of day shift critical care pharmacists per ICU was one), and higher ratios are associated with unsafe patient care [25]. The potential usefulness of MRCI at admission for a critical care pharmacist is thus threefold: [1] to serve as a guide to reduce drug errors and adverse events by facilitating reconciliation; [2] to provide an indication of the potential outcome of hospital stay; and [3] to help mitigate the effects of the ICU pharmacist-to-patient ratio in a cost-effective manner. In the present study, we hypothesized that home MRCI can effectively predict ICU outcomes at admission. We developed machine learning (ML) algorithms to assess this hypothesis across three health outcomes (ICU mortality, LOS, and the need for MV) among critically ill patients. We also evaluated the racial disparities that stem from using MRCI for the foregoing clinical outcomes. Finally, we tested MRCI in combination with either APACHE II or SOFA as joint predictors for these outcomes, given the possibility of a synergistic predictive effect stemming from medication histories, physiological states, and organ failure assessments.
## 2.1. Study Design
This was a single-center, STROBE-compliant retrospective cohort study of 322 patients enrolled in the ICU of a 220-bed community hospital in Providence, Rhode Island, USA, between 1 February 2020 and 30 August 2020. Due to the retrospective nature of the data, informed consent was not deemed necessary, as all patient data were de-identified prior to use. The study was a granted exemption by the Human Research Review Committee Roger Williams Medical Center (RWMC) Institutional Review Board (IRB: 00000058) and the University of Rhode Island Institutional Review Board (IRB: 00000559). The data were curated and reviewed for accuracy by the RWMC data-extraction team.
## 2.2. Data Sources
Patient-level data were extracted from the electronic medical record system of a medical ICU. The total of 322 patients aged at least 18 years included demographics, comorbidity scores, outcomes, medication counts, and individual medication components of the MRCI tool. Patients were excluded if they had an ICU LOS of less than 24 h, active transfer, or change in code status to hospice at 24 h.
## 2.3.1. MRCI Score: Key Independent Variable
As medication regimen complexity is associated with several health outcomes, various tools have been developed to assess medication regimen complexity (Medication Complexity Index—MCI, the patient-level Medication Complexity Index—pMRCI, or the modified Medication Regimen Complexity Index—mMRCI) [26]. The MRCI is deemed the most reliable and valid of the currently available selection, in light of its good interrater and test–retest reliability [20,27]. The MRCI was calculated at the time of admission. The MRCI is a 65-item instrument divided into the following three sections: section A (32 items) for ascertaining dosage form; section B (23 items) for assessing dosing frequency, and section C (10 items) for evaluating additional directions (Supplemental S1, Table S1) [28]. Each prescription drug, over-the-counter drug (orally or not orally taken) was weighted according to these three components [28]. The total score is the sum of the individual sections’ scores, and the higher the score, the more complex the medication regimen [26]. MRCI scores were manually calculated by an independent coder, and validated by Todd Brothers, using a random sample of the extracted data ($20\%$).
## 2.3.2. Outcomes
Three outcomes were evaluated: ICU mortality, LOS, and the need for MV. LOS was stratified into a categorical variable of two levels: those with LOS < 3 days and ≥3 days. The threshold of three days was taken from the mean average length of patients in the literature (~3.4 days) [29]. The need for MV (MV) was classified into two categories, namely, those that used MV and those that did not. Missing data were excluded ($$n = 3$$).
## 2.3.3. Covariates
Variables of interest included age, Charlson comorbidity index score, gender, race, BMI, health insurance (public and private insurance), MRCI scores at admission, SOFA scores at admission, and APACHE II scores. With the exception of age, APACHE II scores, MRCI scores, and BMI, the remaining aforementioned independent variables were categorical. Race was stratified into Whites and non-Whites. Non-Whites or minorities encompassed Blacks, Asians, Hispanics, and unknown races; they were categorized as a single group because of their low sample size. Gender was recorded as “1” or “0”, for males and females, respectively.
## 2.3.4. Machine Learning Models
Five machine learning models were designed, and each dependent variable was fitted to all models. The home medication model included age, gender, Charlson score, BMI, race, health insurance, and MRCI at admission. The MRCI was calculated using the information on the medications the patient was taking at home. The admission model substituted MRCI for APACHE II. The MRCI/APACHE model included APACHE II and MRCI as well as the demographics of the previous models. The SOFA model included SOFA and demographics. The MRCI/SOFA model included SOFA, MRCI, and demographics. Each model was evaluated across all cohorts and across the defined racial continuum (White and non-Whites). A detailed description of each model is available in Supplemental S1, Table S2.
## 2.4. Model Development and Statistical Analysis
For descriptive statistics, the threshold of MRCI (low to high) was set at the third quartile value of MRCI scores. Classification learning algorithms build classifiers from a set of training data, and their performance is assessed based on how well they can predict unseen test data [30]. In the present work, four supervised classifiers were developed and tested for each model: logistic classifier (LC) [31], naïve Bayes (NB) [32], random forest (RF) [33], and extreme gradient boosting (XGB) [34]. The LC is a discriminative model that uses maximum likelihood parameter estimation, wherein a probability distribution is assumed about the data. The NB model uses the Bayes’ rule, which is a probability statement and simplifies the probabilities of the predictor values by assuming that all the predictors are independent of one another [32]. RF, a tree-based model, is an extension of the bagging method, which adds randomness to create an uncorrelated forest of decision trees with a random subset of features, thereby essentially ensuring low correlation among trees [33]. XGB is an implementation of Friedman’s stochastic gradient boosting algorithm, which encompasses classification and regression. Herein, weak classifiers are combined to produce an ensemble classifier with a superior generalized misclassification rate, while minimizing the loss function over numerous iterations [2,35,36].
The relative frequencies of classes may have a significant impact on the effectiveness of different models. In terms of our outcomes, there was an imbalance with regards to the proportion of dead/alive patients (alive: $76.1\%$, dead: $23\%$) and also between the racial groups (Whites: $64\%$, non-Whites: $35.1\%$). Practical approaches used to counter the influence of class imbalance on model output include model tuning, alternate cut-offs, and sampling methods, among other things [35]. In this study, we used sampling methods and model tuning to readjust sample sizes and improve model performances, respectively. The sampling method we used is termed the Synthetic Minority Oversampling Technique (SMOTE). SMOTE is an over-sampling approach in which the minority class is over-sampled by creating synthetic examples rather than by over-sampling with replacement [37]. Over-sampling of the minority class is performed by introducing synthetic examples along the line segments joining any of the k minority class nearest neighbors [37]. In this study, we used the five nearest neighbors. SMOTE was applied at a percentage of $400\%$ to generate synthetic data with 1276 data points (from the original 319 instances) consisting of 786 Whites and 490 non-Whites. SMOTE interpolation was conducted prior to splitting the data into train and test sets. SMOTE was also applied after subsuming race into two major groups (White and non-White). We did not interpolate the original synthetic data based on race because, based on the initial sample size, we could not safely conclude that these were representative enough to create a synthetic dataset of such diversity.
Measures of association (correlation) were assessed using the Goodman–Kruskal test to account for factor and categorical variables [38]. Significant associations between age and BMI (r = −0.180), age and Charlson score ($r = 0.341$), and pre-admission MRCI and Charlson score (r = −0.279) were observed. However, as these were weak, no measures were taken to curb their potential yet unlikely influence on results. The data was partitioned into training ($80\%$ of the data) and test ($20\%$ of the data) sets.
To determine optimal classification results, a k-fold cross-validation for 100 repetitions was estimated. An automatic grid search algorithm was used to find the tuning parameters for the best ML algorithm [39]. For RF, this entailed selecting the mtry, the minimum node size, and the sample fraction. In XGB, variations in randomly selected hyperparameters (max_depth, eta, subsample, colsample_by_tree, and min_child_weight) allowed us to create 10,000 models to choose from. After using the XGB algorithm, we plotted the SHapley Additive exPlanations (SHAP) summary to help us interpret the findings. The SHAP or Shapley values method is a feature attribution technique that assigns to each feature a particular value for a particular prediction to assist with interpretability. As the Shapley value method utilizes features in every possible order to arrive at values, this allows for an unbiased interpretation of predictions [40]. The SHAP values were plotted for the entire sample and not across the racial divide.
Selected metrics for overall performance included the area under the receiver operator characteristic curve (AUC), the sensitivity (Se), the specificity (Sp), the positive predictive value (PPV), and the negative predictive value (NPV). Ninety-five percent confidence intervals (CI) were provided alongside these metrics. The area under the receiver operating characteristic (ROC) curve, or AUC, measures the predictive ability of learning algorithms’ ROCs. Sensitivity refers to true positives that are correctly predicted by the model, while specificity refers to true negatives that are correctly predicted by the model. Results are shown for the general population and across the racial divide. Only the best ML algorithm results are shown; the remainder is provided in the Supplemental Files. All analyses were performed using R (R Core Team, 2019). R packages Caret (for LC), e1071 (for NB), Ranger (for RF), and XGBoost (for XGB) were used for ML algorithms. Multicollinearity was assessed mathematically using package performance and graphically using the package ggally. SMOTE implementation used the package smotefamily, whereas graphs were produced using ggplot2.
## 3.1. Descriptive Analysis
In total, data from 319 patients were included in the analysis (Table 1). The median age was 62 years and similar between low and high MRCI groups. There was no significant difference between the low and high MRCIs for BMI. No significant differences were detected between MRCI groups for APACHE II, the Glasgow Coma Scale (GCS), or the Simplified Acute Physiology Score (SAPS) II. The top conditions at admission included hypertension, acute renal failure, myocardial infarction, and metabolic encephalopathy (Table 1). The high MRCI group had the highest proportions of patients with these conditions, although the difference with the low MRCI group was not significant (Supplemental S2: Figures S6–S10). The proportion of patients who died in the ICU was higher among the high-MRCI compared to the low-MRCI patients ($26\%$ vs. $22\%$). Supplemental S2, Figure S1 shows that those with a high MRCI took more medications at home than those with low medications. Among those with high MRCI who survived, the distribution was broader compared to those who died. In Table 1, those with a low MRCI had a longer length of stay (113.2 h vs. 106.5 h) and needed more MV (65 h vs. 47.9 h) than those in the high MRCI group. This difference was not significant as emphasized (Supplemental S2, Figure S3). A heatmap (Supplemental S2, Figure S4) of the various medications taken at home by all patients shows that diuretics, genitourinary, and paralytic agents were highly used by those with low MRCI. Among those with high MRCI, IV fluids appeared to be slightly more predominant. Non-Whites had higher representation among those with high MRCI ($31.9\%$ vs. $21.4\%$) than Whites (Supplemental S2, Figure S5).
## 3.2.1. ICU Mortality
Table 2 presents the performance measures for the best model using the best ML algorithm. The best ML algorithm throughout was XGB, and the best model was the MRCI/SOFA model. The performances across the remaining ML algorithms for all models can be found in Supplemental S3, Table S3. For mortality, the predictive positive value (PPV) was defined as the percentage of patients predicted to die who in fact did die during their hospitalization. The home medication model showed a precision of ~$60\%$, a prediction accuracy for patient death of ~$70\%$ and could accurately classify $73\%$ of the time (Se) patients who had died. In this model, MRCI was the third-most important variable featured (Supplemental S3, Figure S11). Upon inclusion of SOFA, the MRCI/SOFA model outperformed all other models across all metrics with a precision of $100\%$ and an overall prediction accuracy for patient death of $98\%$. Using this model, patients who died were correctly classified $96\%$ (Se) of the time (Table 2 and Figure 1).
Despite the fact that SOFA drove the model and scored the highest on the variable importance chart, MRCI was the fourth most important variable, only outdone by age and BMI (Supplemental S3, Figure S11). The SHAP summary for the MRCI/SOFA model (Supplemental S3, Figure S12) showed that low scores of the MRCI were associated with remaining alive during an inpatient ICU stay.
## 3.2.2. ICU Length of Stay
For LOS, the precision of the home medication model was $76\%$, whereas the prediction accuracy for patient LOS of less than 72 h was $68\%$ (Table 2 and Figure 1). This model could accurately classify $64\%$ of patients who were hospitalized for less than 72 h. As with mortality, the addition of SOFA (MRCI/SOFA model) provided the best results in terms of precision ($95\%$ CI: 74–$83\%$), prediction accuracy ($95\%$ CI: 76–$82\%$), and Se ($95\%$ CI: 79–$83\%$). Variable importance featured MRCI in first and fourth place, across the home medication and the MRCI/SOFA models, respectively (Supplemental S3, Figure S13). SHAP values obtained for the MRCI/SOFA model showed that low values of MRCI were mostly consistent with a hospital LOS of less the 72 h (Supplemental S3, Figure S14).
## 3.2.3. ICU Need for Mechanical Ventilation
Across all outcomes, the home medication model performed best for the need for the MV outcome. Accounting for a precision of $72\%$, a prediction accuracy of $75\%$, and a classification accuracy for patients that need MV of $78\%$ (Table 2 and Figure 1), this model was not widely dissimilar in performance compared to the admission model or the MRCI/APACHE II model. Only the substitution/addition of SOFA in the SOFA and MRCI/SOFA models yielded far better outcomes. The MRCI/SOFA model had a precision of $84\%$ ($95\%$ CI: 79–$87\%$), a prediction ability of $87\%$ ($95\%$ CI: 85–$90\%$), and could accurately classify $90\%$ ($95\%$ CI: 86–$93\%$) of the time patients were in need for MV. In the home medication and the MRCI/SOFA models, MRCI was respectively the first and second-most important feature (Supplemental S3, Figure S15). Interestingly, the SHAP plot (Supplemental S3, Figure S16) showed that patients with low MRCI needed more MV.
## 3.3. Model Performance: Racial Continuum
Algorithm performance results for Whites are shown in Table 3, and for minorities in Table 4. Only the results for the best algorithms per model are presented in these tables; the remainder can be found in Supplemental S3, Table S3. The home medication model performed worse for minorities than it did for Whites. For mortality, the home medication model performed better among Whites compared to the mixed population. It correctly classified patients who died $83\%$ of the time, with a prediction accuracy of $81\%$ and a precision of $78\%$. Among minorities, this model’s prediction accuracy was $73\%$. The home medication model was the second-best model among Whites after the MRCI&SOFA model, which yielded increased $95\%$ CI for prediction accuracy ($95\%$ CI: 0.85–0.90), Se ($95\%$ CI: 0.82–0.93), Sp ($95\%$ CI: 0.86–0.93), PPV ($95\%$ CI: 0.87–0.93), and NPV ($95\%$ CI: 0.78–0.86).
For minorities, the SOFA and MRCI/SOFA models were the best in terms of Se and PPV, respectively. The best models among minorities were obtained using LC as opposed to XGB for Whites.
For LOS, the home medication model performed better among Whites with higher precision accuracy ($77\%$), Se ($72\%$), and PPV ($82\%$). However, the best algorithm for this model was XGB for Whites and naïve Bayes for minorities. Among Whites, the best models were the MRCI/APACHE II, SOFA, and MRCI/SOFA models, in terms of precision ($82\%$), precision accuracy ($83\%$), and classification accuracy ($90\%$), respectively. Thus, the inclusion of APACHE II improved the Se, whereas the inclusion of SOFA improved the PPV. Across minorities, the SOFA model was the most balanced model with a precision accuracy of $91\%$, a Se of $100\%$, and a precision of $82\%$. The addition of APACHE or SOFA to the home medication model improved the PPV ($95\%$: 0.75–0.84; $95\%$ CI: 0.82–0.89).
The home medication model performed better for the need for MV outcomes than for LOS, although it showed better metrics among Whites than among non-Whites. Indeed, precision accuracy reached $79\%$, Se, $78\%$, and precision, $82\%$, among Whites (Table 3). Among minorities, accuracy was $74\%$, Se was $74\%$, and precision was $76\%$. The contrast between the two understudied racial groups could not be more apparent than when the best models were examined. Among Whites, the MRCI/APACHE II outperformed with a precision accuracy of $91\%$, a Se of $89\%$, and a precision of $94\%$. However, among non-Whites, the SOFA and MRCI/SOFA models were the best.
## 4.1. Key Findings
In the present study, we hypothesized that home medications could serve as predictors of health outcomes, either as a single factor (MRCI) or in combination with traditional scoring systems (APACHE II or SOFA). We also investigated the differential in predictive capabilities across races for these predictors. Our findings show that the home medication model predicts on average accurately ~$70\%$ of the time all three outcomes: ICU mortality, LOS, and need for MV. Along with SOFA, the MRCI model outperforms in predicting all three outcomes. In other words, without knowing the subsequent status of an ICU admitted patient, by just using the calculated MRCI (home medications) at admission one can predict with $70\%$ accuracy mortality, LOS, and the need for MV. The combination of SOFA and MRCI vastly improved predictive accuracy among the general population. Moreover, another major finding of our study is that the MRCI was a better predictor of all three outcomes among Whites than it was among non-Whites. Among Whites, the predictive clinical accuracy of home MRCI reached $80\%$, while remaining at $70\%$ for non-Whites for all outcomes. These findings provide justification to include home medication histories in the list of existing patient equity scoring systems such as APACHE II, SOFA, etc.
The SHAP values showed that low values of MRCI were associated with reduced mortality and LOS but an increased need for MV. Past research has corroborated our findings [41]. Herein, higher values of MRCI increased the odds of hospital mortality, as those with MRCI values above 14 were at least 1.84 times more likely to die during their hospital stay compared to those with MRCI values less than 5 [41]. A meta-analysis also found that high MRCI scores were associated with increased hospitalization hazards (hazard ratio = 1.20; $95\%$ CI = 1.14 to 1.27) [42]. Across eight residential age care facilities in Australia, MRCI scores were shown to be positively correlated with LOS [18].
## 4.2. MRCI at Admission in Different Races
Interestingly, MRCI was a better predictor among Whites than it was among non-Whites. This could be due to a host of reasons, such as medication adherence and inaccurate medication history record, source of medication history record, class/covariate imbalance, and low sample size. There is a dearth of data on the variation of MRCI among racial groups, and whenever available, this evidence appears to be stratified by disease or confined to medication use. For example, past research in systemic lupus erythematosus showed that Blacks typically have higher medication regimen complexity scores compared to Whites [24]. Among Blacks, high MRCI scores are correlated with non-adherence to drug regimens [43]. This non-adherence may be due to a greater propensity for “pharmacy deserts” in low-income communities or medically underserved areas where minorities typically reside [44]. Geographical access to pharmacists’ services to manage regimens is thus not readily available for minorities [44,45]. As adherence/non-adherence may reflect MRCI scores [26,46], it may explain why Whites adhere more to drug regimens, and why this index is more reliable in predicting inpatient outcomes in this subpopulation.
## 4.3. Role of Critical Care Pharmacist
In the acute care setting, clinical pharmacists are considered medication experts and have extensive training in pharmacotherapeutics to provide comprehensive medication management to both patients and members of the interdisciplinary care team. It has been well documented that the addition of pharmacists providing direct patient care has led to a reduction in preventable adverse drug events, fewer transfers to the intensive care unit (ICU), and a reduction in length of stay (LOS) [47,48]. Additionally, the incorporation of critical care pharmacists within the interdisciplinary care team has led to improved patient outcomes, including mortality, ICU length of stay in mixed ICUs, and preventable/nonpreventable adverse drug events [49]. Clinical pharmacists play an essential role in evaluating home medication regimens for complexity in terms of appropriateness of use, safety of continuation during hospitalization, and frequent regimen modifications (i.e., dose reduction) during transitions of care. A 2017 study highlighted the importance of pharmacist intervention and communication during transitions of care from hospitalization to the community by demonstrating a $36\%$ reduction in medication-related hospitalizations among the elderly population [50]. Therefore, the use of an MRCI scoring system by clinical pharmacists remains essential to improving the quality of pharmaceutical care delivered.
## 4.4. Different Biases in Predicting Clinical Outcomes
Racial bias, often encountered in data-driven algorithms for healthcare, remains a known challenge to delivering equitable, high-quality healthcare. Label choice-induced bias has been widely documented and has been well described noting the discrepancy between unobserved optimal prediction and a prediction trained on an observed label [51]. This type of bias typically springs from mismeasurement and human judgment/interpretation [52]. Data obtained from electronic health records (EHR) or claims databases reflect unaccounted clinical errors, which can lead to mismeasurement and bias in predictions. In this study, the measurements of MRCI were obtained using EHR data. However, a more informative score would be a version of the MRCI calculated using pharmacy insurance claims. A recent study examined the correlation between an EHR-based MRCI and a pharmacy claims-based medication complexity tool [53]. The authors claimed that the claims-based tool would better capture all pharmacy encounters compared to the EHR, which reflected mostly provider interactions. The association between the EHR and claims data was significantly higher among a subset of patients with similar counts of records between the EHR and claims. The association was lower for patients with large discrepancies between medication orders captured in the EHR and pharmacy claims. It is thus possible that patients with better access to care may have more reliable counts of EHR records, which when considered may closely reflect MRCI scores at home, than patients who mostly utilize medical services sporadically and mostly through emergency services (minorities) [54].
Other sources of racial bias include demographics, comorbidity imbalances in the dataset, and other societal and systemic sources [55]. A significant statistical disproportion was found with Blacks in our study making up $35.4\%$ of the sample. Research has also shown that minorities are often, compared to Whites, at increased risk for chronic diseases [56]. Societal and systemic sources describe the unequal probability of having members of a specific racial group as a patient in our sample, perhaps due to strict patient selection or assessment of patient compliance, baseline health status, and comorbidities [55]. The mistrust of minorities with respect to medical providers could also play a crucial role here [57].
In the present study, the SOFA model was the best for Whites (mortality outcome), whereas the MRCI/APACHE II model had a better predictive ability for LOS and the need for MV outcomes. Among non-Whites, the SOFA and MRCI/SOFA models were the best models across all outcomes. Thus, for Whites, the addition of APACHE II to the base model seemed to enhance the predictive ability of the algorithm, whereas for non-Whites, the same effect was observed following the inclusion of SOFA scores. APACHE II is a disease severity classification system that focuses on the severity of disease based on physiological values. SOFA is an organ failure score based on the degree of dysfunction of six critical organs, and it is directly related to inpatient outcomes in critically ill patients. We hypothesize that SOFA is a better predictor among minorities because of the latter’s propensity to use emergency rooms as a primary resort for medical services [58], as a result of critical/worse (than Whites) health status. This is then better reflected across SOFA than APACHE II scores.
## 4.5. Implications of the Study
The present study highlights the benefits and advantages of using home medication histories for determining prognosis among a critically ill population. Identifying high-risk patients using this tool could substantially reduce the demand for critical care pharmacists, lower the overall costs of medical procedures, and also improve patient outcomes. As study strengths, this work helped set MRCI as a single or composite-value predictor for mortality, LOS, and the need for MV among hospitalized patients. Our results highlight the importance of critically evaluating home medication use to accurately and swiftly depict the prognosis to assist family members in making the challenging decision(s) to escalate care for their loved ones. Despite the widespread use of MRCI scores, researchers have yet to incorporate home medication use in a predictive model to forecast relevant outcomes. In terms of real-world implications, the bedside clinician is encouraged to evaluate the patient specific MRCI profile prior to making medical decisions. This in turn will positively impact patient safety and mitigate unnecessary risks. Incorporation of the MRCI has the potential to reinforce the current, yet not widely adopted, effort toward improved medication reconciliation, particularly upon transitions of care where most medication errors occur. Further, for critical care pharmacists, this tool could also serve to clearly identify the patients at the highest risk of treatment failure (patient readmission), in need of intense follow-up post-ICU admission, and equitably distribute future resources necessary to improve post-ICU and long-term care [59,60].
This study also promotes the use of explainable machine learning to investigate ICU outcomes, as informed by past research [61]. Further, it also emphasized the utility of the SMOTE technique in helping overcome class imbalance and producing robust results. It also highlighted the proficiency of several algorithms, specifically XGB, as well-suited to predict inpatient outcomes. XGB is a scalable and accurate implementation of gradient-boosting machines specifically designed to push the limits of boosted tree algorithms. XGB often produces the best predictive performances and processing times across several algorithms, and it has also been shown to work well in small samples.
## 4.6. Limitations
A few notable limitations are worth noting. First, we acknowledge that MRCI may be described as a surrogate index for disease severity. Second, racial bias on the basis of statistical disproportions limited the use of non-augmented (SMOTE) data in our algorithm. Despite the prowess of SMOTE, one of its major drawbacks is overfitting through the random synthesis of minority data while taking little to no account of the significance of the majority class [62]. Further, we were limited in the use of other covariates of importance in the dataset. Although MRCI alone could predict $70\%$ of the time, typically the best predictors record accuracies of $90\%$. Perhaps a larger data set would yield better results. This study’s findings are also limited in their generalizability, as the data were obtained from a single medical center and may not be representative of the general population.
## 5. Conclusions
Home medication history is a robust predictor of ICU mortality, LOS, and the need for MV. The predictive capabilities of traditional patient acuity scoring systems improve with the addition of MRCI scores at admission. Racial attributes appear to determine the degree of importance that medication regimen complexity occupies with respect to clinical outcomes. In spite of our encouraging findings, future research should aim to validate these findings not only across larger samples but across subpopulations of varying demographic characteristics. Indeed, incorporating strategies to mitigate racial bias and introduce fairness in predictive algorithms could help pharmacists better attend to patients and, in turn, improve outcomes and reduce overall healthcare costs.
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|
---
title: 'The Complexities of Managing Gestational Diabetes in Women of Culturally and
Linguistically Diverse Backgrounds: A Qualitative Study of Women’s Experiences'
authors:
- Melissa Oxlad
- Sharni Whitburn
- Jessica A. Grieger
journal: Nutrients
year: 2023
pmcid: PMC9967365
doi: 10.3390/nu15041053
license: CC BY 4.0
---
# The Complexities of Managing Gestational Diabetes in Women of Culturally and Linguistically Diverse Backgrounds: A Qualitative Study of Women’s Experiences
## Abstract
Aim: This study aimed to explore women’s perspectives and experiences concerning how culture impacts the lifestyle management of gestational diabetes mellitus (GDM) in women of culturally and linguistically diverse (CALD) backgrounds. Methods: Women of any cultural background diagnosed with GDM within the previous 12 months were purposively recruited from two Australian metropolitan hospitals. Data collected using semi-structured interviews ($$n = 18$$) and focus groups ($$n = 15$$ women in three groups) were analysed using reflexive thematic analysis. Results: Three themes were generated: “cultural beliefs and obligations impact lifestyle management of gestational diabetes”, which describes how some cultures lack awareness about GDM, and modifications or restrictions were viewed as depriving the infant, but sometimes adaptions could be made so that a culturally appropriate meal was suitable for GDM management; “the relationship between cultural foods and gestational diabetes management”, which discusses how important cultural foods may be incompatible with appropriate GDM management, so women worked to find solutions; “gestational diabetes education lacks cultural awareness and sensitivity”, which illustrates how current education fails to address differences in cultural beliefs, language and eating practices. Conclusion: Cultural beliefs, obligations and food practices must be considered when assisting women of CALD backgrounds using lifestyle modification to manage GDM. GDM education must be culturally sensitive and competent and, where possible, be delivered by health professionals of a shared cultural group.
## 1. Introduction
Gestational diabetes mellitus (GDM) is the onset or first recognition of glucose intolerance during pregnancy, mostly in the second or third trimester [1]. The prevalence of GDM in Australia has tripled over the last 15 years and has now reached $15\%$ [2]. Women with GDM are at a 10 times higher risk of developing type 2 diabetes 5–10 years post-partum [3] and are 2–3 times more likely to develop ischemic heart disease and hypertension up to 25 years after birth [4]. In addition, the offspring of women with GDM are more likely to be born large for gestational age, have a higher body mass index in childhood [5] and be more insulin resistant in adolescence [6].
Current first-line clinical management of GDM is a healthy diet and exercise; however, there are no universal guidelines for its management [7]. Although diabetes educators and dietitians demonstrate consistent knowledge of nutritional management for GDM and uniform delivery methods, concerns exist that women with GDM struggle to follow nutritional advice and often disengage from services [8]. In a systematic review of 10 studies, He et al. [ 9] noted that women with GDM had difficulty in changing their eating habits because the recommended eating plan differed significantly from their previous dietary habits. In a review among Black, Asian and minority ethnic populations, the nutritional education provided was seen to contradict traditional beliefs about pregnancy, contributing to anxiety, psychological distress and potentially exacerbating underlying health fears associated with race [10]. These findings highlight the disconnection between the delivery of recommendations for GDM by health professionals and the uptake of nutritional advice by women who have GDM.
Culture offers a potential explanation for some of this difficulty, with a person’s diet being culturally situated. Each culture has norms about foods and eating practices. Adhering to a prescribed nutrition regimen may be more difficult for women from minority ethnic groups than for women from the ethnic majority. In 2019, in Australia, $4.8\%$ of women were Aboriginal or Torres Strait Islander, and $36\%$ of women who gave birth were not born in Australia [11]. Such diversity brings different expectations, knowledge and practices about antenatal care. Immigrant women in Australia reported that the dietary advice they received about GDM was challenging [12], there was difficulty in meeting the demands to change the diet [13], and the dietary advice lacked cultural relevance [14]. Yet, other cultural groups identified GDM as an opportunity to improve their health [15]. In some cultures, GDM is unheard of or goes unspoken. Therefore, when diagnosed, women experience a sense of isolation [16], are often left to do their own research and may seek advice within their communities [16,17], or the advice they receive conflicts with their cultural practices and beliefs regarding pregnancy [12].
There is a growing body of literature concerning White and culturally and linguistically diverse (CALD) women’s GDM experiences in Australia, but it is currently insufficient to offer effective culturally responsive communication and care. Furthermore, there is far less information on how culture impacts the lifestyle management of GDM in women of CALD backgrounds in Australia. Therefore, barriers to dietary adherence and the influence of cultural diversity need to be identified to support implementation, aid practical resources and increase dietary adherence. Thus, we aimed to explore women’s perspectives and experiences concerning how culture impacts the lifestyle management of GDM in women of CALD backgrounds.
## 2.1. Design, Setting and Sample Recruitment
We employed a qualitative design using focus groups and semi-structured interviews. Participants were recruited using purposeful selection from two large metropolitan hospitals in Adelaide, Australia. A research nurse employed at each hospital identified potentially eligible women from hospital records; women required a GDM diagnosis within the past 12 months and the ability to speak and understand English. The research nurse telephoned potential participants to describe the study, and interested women gave verbal consent to be sent an information sheet and consent form. We used face-to-face focus groups and semi-structured telephone interviews as many women could not attend focus groups due to lack of transport or their husbands’ preference. Written consent was obtained before the commencement of the focus groups and was verbally recorded at the start of individual interviews. Interviews and focus groups were conducted between November 2021 and June 2022. The University of Adelaide Human Research Ethics Committee approved this study (2021/HRE00128).
Focus groups and interviews were guided by an open-ended question interview guide informed by previous literature studies. The topics covered included demographic information and women’s perspectives about managing GDM. Example questions included ”Can you tell us briefly about how you managed or aimed to manage your GDM?”, ” What were the greatest difficulties or barriers that you encountered when diagnosed with GDM?“ and ”Can you please describe your experience with the food guidance that you were provided following the diagnosis of GDM? Were there any issues in relation to your culture/food preference or food availability that made following these guidelines difficult?” Focus groups were facilitated by a research fellow with a nutrition background, while a paediatric diabetes nurse educator or a midwife conducted the interviews. With the participants’ consent, focus groups and interviews were audio-recorded and transcribed verbatim, with identifying information being removed from transcripts. Participants received AUD 50 gift cards as a sign of gratitude for their involvement.
In line with best-practice qualitative research involving ”member reflections” [18], all women were offered the opportunity to review their focus group/interview transcript and/or a summary of the themes; none chose to do so. We did not seek data saturation, as this concept does not align with the values and assumptions of reflexive thematic analysis [19]. Rather, Braun and Clarke [19] recommend that data collection continues until sufficient meaning can be generated. All authors felt that this was achieved in our sample.
In line with best-practice qualitative research, we recognised the researchers’ potential to influence the research process, including data collection, analysis and interpretation, so we engaged in self-reflexivity throughout the research project [18,20]. We are a team of women researchers with experience in conducting reproductive health-related research. The first and third authors are mothers; the first author has experience with GDM.
## 2.2. Data Analysis
Data were analysed using six-step reflexive thematic analysis [20]. That is, the analysis involved [1] data familiarization by reading the transcripts multiple times; [2] generating initial codes relevant to the research aims; [3] collating related codes to generate potential themes; [4] reviewing potential themes in relation to the research aims and ensuring they accurately reflected the data; [5] refining and naming themes; and [6] selecting extracts to illustrate the themes and writing up the results. Given the study’s exploratory nature, we employed an inductive approach. The first and second authors independently familiarized themselves with the data and undertook initial coding. After discussing coding, the first author developed the initial themes, which all authors then reviewed and refined. All authors agreed on the final themes.
## 3.1. Participants
The participants were 33 post-partum women (18 individual interviewees and 15 focus group participants) aged 20–42 years ($M = 32.09$, SD = 4.67). Focus groups ran for 59–71 min ($M = 65.33$ min), while interviews ranged from 10 to 28 min ($M = 14.39$ min). Women represented multiple ethnicities: Indian ($$n = 11$$), Australian ($$n = 6$$), Caucasian ($$n = 4$$), English ($$n = 2$$), Pakistani ($$n = 2$$) Aboriginal ($$n = 1$$), Bangladeshi ($$n = 1$$), Colombian ($$n = 1$$), Filipino/Italian ($$n = 1$$), Filipino/Spanish ($$n = 1$$), Iranian ($$n = 1$$), Iraqi ($$n = 1$$) and Nepalese ($$n = 1$$). Parity ranged between primiparous and four; three women had had GDM in two pregnancies.
## 3.2. Themes
*We* generated three themes that demonstrate how culture adds complexity to the lifestyle management of GDM.
## 3.2.1. Cultural Beliefs and Obligations Impact Lifestyle Management of Gestational Diabetes
Women were very motivated to follow lifestyle advice for their health and that of their baby; however, culture was an important influence on efforts to manage GDM with lifestyle change. Women described how cultural knowledge, beliefs and obligations were integral to understanding and managing GDM. They noted that GDM is not something people in all cultures are aware of; further, rates of GDM in some cultures were low, meaning that women often had to educate themselves and their families about the condition. In some cases, women also questioned whether countries have different approaches to pregnancy care.
Additionally, cultural views about the importance of food in general and the role of food in pregnancy and infant health were also expressed. For example, women described how family members valued eating during pregnancy and questioned the need to restrict foods, seeing eating as beneficial to the child and pregnancy as a time to eat freely.
In addition, when women tried to modify their diet to manage their GDM, this was not always met with understanding. Instead, family members who lacked awareness of or who had not been screened for GDM during their pregnancies did not see a need for lifestyle changes and encouraged women to continue eating whatever they wanted.
Additionally, any dietary modifications or restrictions were viewed as depriving the infant. Women articulated that they needed to educate family members about the need for lifestyle changes.
In making necessary dietary changes, women also spoke of how this impacted family eating practices, with meal preparation often being framed as challenging. In some instances, women could make adaptations, so a culturally appropriate meal could also be suitable for GDM management. For example, avoiding breads or using homemade breads, substitutions or eating smaller portions.
In other instances, women prepared their own meal or needed to make one meal for themselves and a separate meal for other family members—this arose due to food preferences or cultural expectations about supplying a culturally appropriate meal.
In contrast, some women prepared the meal best suited to them for their immediate family. However, one woman noted that while her husband was supportive, this approach would not have been acceptable if family were visiting.
Culture and its influence on diet, eating practices and family obligations is an important consideration in the lifestyle management of GDM in women from CALD backgrounds. However, while culture governs attitudes towards food and eating practices in pregnancy, culturally important foods also have a significant role in the lifestyle management of GDM.
## 3.2.2. The Relationship between Cultural Foods and Gestational Diabetes Management
Women described how important cultural foods may be incompatible with appropriate GDM management and how they worked to find solutions. Many important and frequently eaten foods were incompatible with optimal management. For example, one woman of Indian culture noted that in “a lot of food that we eat at home, and not just Indian culture, but a lot of traditional cultures of food is very, very carb-rich and carb-dense”, and that for her culture, “the food that we eat, the Indian food, it just doesn’t work with GDM”. In Indian culture, while many people are vegetarian, there is also a heavy reliance on flatbreads (i.e., roti and chapati) containing sugar and high-carbohydrate white rice, lentils and dahl. Women described receiving varying information about consuming cultural foods, with some women reporting being advised to avoid certain cultural foods.
In contrast, other women reported receiving advice that some cultural foods could still be eaten after consideration of portion size and timing. For example, “the intake and the time and how much we take that’s the main thing”. Women found creative ways to navigate potential incompatibilities between cultural foods and GDM management, including preparing meals in a way that is “respecting the culture”; cooking differently (i.e., more stir-frying, boiling and grilling), “so, the cooking—the preparation and the method was really different”; substituting foods (i.e., multi-grain flour instead of wheat flour, sweet potatoes instead of potatoes, and brown rice instead of white rice); eating small amounts more frequently; and reducing quantities and portion sizes.
The strategy of reducing quantities and portion sizes was also used as a means to minimize dietary changes and hold on to pre-diagnosis eating practices.
While many women used food substitutions and reduced consumption to manage their GDM, others significantly changed their food practices. For instance, some vegetarians chose to add meat to reduce carbohydrate intake.
However, the pull of culture can be very strong, with some women retaining cultural eating practices, viewing these as important for their child, even if inconsistent with scientific evidence.
Specific foods and ways of preparing food are highly valued aspects of culture. While women are highly motivated to make lifestyle modifications to manage their GDM, health professionals must recognize that important cultural foods may be incompatible with GDM management. For the most part, women from CALD backgrounds are willing to make changes regarding their cultural foods. However, the need for and challenge in making these changes should be recognised in culturally competent GDM education.
## 3.2.3. Gestational Diabetes Education Lacks Cultural Awareness and Sensitivity
Women described how GDM education did not address differences in cultural beliefs, language and eating practices; rather, women were educated on foods they could not eat, were unsure how recommendations would fit with their cultural eating practices, noting “I think from our culture it’s really difficult for us to just go on that one [recommended diet]…because our food is a lot more different from Australian”, and were often provided with limited or inappropriate alternatives.
Such an approach made it particularly difficult for women whose staple foods consisted of white rice and flatbread, since these are foods to avoid when managing GDM.
The education sessions were only offered in English, which sometimes made it challenging for women when English was not their first language. One woman reflected, “when you think it’s hard for us, imagine that being your second language… a lot of people who experience GDM are people from culturally and linguistically diverse backgrounds. So, it’s so important to tailor for them”. Encouragingly, women of CALD backgrounds described how the support from health professionals allowed them to overcome language barriers.
Women often highlighted the importance of individualized education not just in terms of language but in terms of diet and food practices. Women recognized that even within the same culture, regional differences exist. For example, one woman explained, “I’m from the northern part of India, salt is different in the east, we are different—every state is different”, while another stated, “I’m from India and specifically I’m from the southern part of India. So, if it is from northern part of India they will eat more of wheat, but we normally eat more of the rice.” Women expressed that such differences should be considered in education.
Some women described attending education sessions alongside women who may have a different diet to themselves as daunting and suggested one-on-one support as a valuable alternative.
In addition to one-on-one support, women suggested that it would be useful to have someone to relate to in the education sessions who understood their challenges. Women described this person as an advocate or “someone who has had GDM before, from a different background”. Women also emphasized the importance of including their partner in education sessions to assist couples in implementing the suggested recommendations.
The clear benefits of having a partner who is willing to learn and also implement changes was illustrated by one woman.
Women highlighted the importance of individualized education that addresses potential language barriers, and cultural beliefs and practices surrounding food. Partners and support people being included in education was also valued.
## 4. Discussion
This study aimed to explore women’s perspectives and experiences concerning how culture impacts the lifestyle management of GDM in women of CALD backgrounds. Women reported that testing and treatment for GDM were low in some countries, resulting in limited understanding and awareness. Additionally, cultural beliefs showed that families value eating during pregnancy, with diet modifications perceived as depriving the baby. This finding concurs with a recent study in South Asian immigrant women in Australia, where women were shocked when advised to decrease their food intake, as this goes against norms such as gaining weight and eating for two [12]. In contrast, a prior study in women who were currently or previously diagnosed with GDM found that when women visit family and friends, they feel obliged to eat the food prepared for them [21] which can potentially compromise their GDM management if the food is of poor diet quality. Some women in our study made a GDM-appropriate meal for themselves and a separate meal for family members to meet cultural obligations. While this may enable GDM management, it may still pose cultural issues and creates extra work for women.
Consistent with previous studies, revealing that it is difficult for women to implement dietary changes when staple cultural foods are ”carbohydrate heavy” [16,21], the women in our study described how common cultural foods were incompatible with their GDM management. Nutritional advice varied, with some women having been advised to avoid these cultural foods completely, while others were informed to eat their cultural foods in smaller portions or at certain times. Conflicting advice such as this occurs when dietitians lack education about variations in cultural cuisines, resulting in women sacrificing these dishes [17,21]. As a result, women undertook research and sought advice within their communities to make substitutions that better replicate their usual diet [16,17]. We observed this solution focus in our sample, where women substituted foods (multi-grain flour instead of wheat flour) and employed alternative cooking methods (boiling and grilling) to enable them to continue eating cultural foods while managing their GDM.
While women identified solutions, the education provided focused on foods to avoid and offered limited alternatives or substitutions and was reported to be only offered in English. Some past literature studies have found that language barriers sometimes lead women to misunderstand information, resulting in problems in following dietary advice and monitoring blood glucose levels [22,23]. However, in our study and a study in local and immigrant women in Norway [23], women with an immigrant background did not report challenges in understanding and following advice. Despite this, health professionals have noted challenges when educating women of CALD backgrounds, attributed to language, culture and religion [12] or a lack of resources for CALD women [8]. Women in our study recommended one-on-one individualized education and advice that was culturally sensitive. They also highlighted that having a support person attend education sessions may increase the support person’s understanding and the likelihood of support in lifestyle changes. This is in line with previous studies that have described the need to include partners, emphasizing difficulties for women in implementing lifestyle changes when their partner is unwilling to participate in any changes [22,24]. We build on these studies, with women in our study expressing a desire to include an advocate or someone who has experienced GDM from their culture.
Culture itself does not appear to influence the ability to benefit from GDM education and manage GDM with lifestyle modifications. Several studies show that women of different ethnicities can effectively manage GDM, for example, Chinese women with GDM living in China [25] and Thai women living in Thailand [26], or where the population was specifically recruited, such as African born [27] or Aboriginal born [28], to understand the experiences and perceptions of a largely homogenous group of women with GDM. In such study, the health professional who provided GDM education was of the same ethnicity as the women participating. Contrastingly, in Australia, GDM education for women of CALD backgrounds is typically provided by White women. This cultural incongruence cannot be overcome through interpreters, as language alone is not the only barrier to suitable education; health professionals also require cultural knowledge and understanding to provide culturally sensitive and competent care. Therefore, it is essential to have health professionals of diverse cultural backgrounds providing GDM education, and in their absence, for White health professionals to be culturally competent.
This study has important implications for policy and practice. In Australia and internationally, the prevalence of GDM is rising. The increased prevalence of GDM poses an increasing public health burden, given the intergenerational cycle that GDM perpetuates [29]. Additionally, in Australia, the population is increasingly comprising more women of reproductive age who are of ethnic minority backgrounds [30]. We have recently highlighted the lack of cultural resources for nutritional management of GDM in women of ethnic minority backgrounds [8], which is consistent with other studies [12,31,32] and demonstrates the ongoing need to consult women of CALD backgrounds about their views, experiences and needs, so that appropriate, evidence-informed health education prevention and management resources, as well as culturally sensitive and appropriate interventions and support, can be offered. Co-developing nutritional management plans that are tailored to the cultural context and that are emphasized by trained diabetes educators and dietitians would enhance current GDM care for women of CALD backgrounds. Recommendations also include training staff to be mindful and sensitive to culture and to consider the importance of cultural obligations and food practices in women’s lives and how such cultural factors impact women’s abilities to manage their GDM. Such training may enable staff to provide quality nutrition education and GDM management strategies that are considerate of and, when supported by medical evidence, compatible with cultural beliefs and practices. In turn, women of CALD backgrounds with GDM who receive education and guidance from culturally competent staff are likely to follow care recommendations and to be more satisfied with their care. Finally, to further enhance the likelihood of optimal GDM management in women of CALD backgrounds, partner and/or family engagement is also recommended; increasing family members’ knowledge about GDM and the changes needed to optimise the health of women and their babies is likely to improve the sustainability and success of well-integrated, culturally appropriate nutrition.
A strength of our study is the cultural diversity of our sample, providing important information on women’s experiences of how culture impacts awareness of and lifestyle management in GDM. The use of focus groups and interviews conducted in multiple locations somewhat mitigated selection bias. This approach also provided the capacity to access marginalized groups who may otherwise be unable to participate using traditional research methods and to gather in-depth accounts and views. Despite the strengths of our study, it is not without limitations. For example, although we recruited women with suitable English proficiency across two major public hospitals in Adelaide, Australia, our findings may not represent the views and experiences of all women diagnosed with GDM in Australia. The need for a degree of English proficiency may have excluded some potential participants and conducting the research in English (not all participants’ first language) may have hampered some participants’ ability to fully articulate their experiences, thereby leaving us with an incomplete understanding of the complexities of managing GDM in women of CALD backgrounds. Although challenging, where possible, it may be beneficial to offer participation in women’s first language. In addition, all women in our study were post-partum and may reflect differently on their experiences than women interviewed when newly diagnosed or actively managing a pregnancy with GDM. Finally, all women were from one Australian metropolitan area, and although women of several ethnicities were included, we cannot know whether women of ethnicities that were not included may have shared similar or disparate views and experiences regarding management of GDM. Therefore, as our findings may not be generalizable to all women of CALD backgrounds in Australia, we recommend that future research seeks the views of women of diverse sociocultural backgrounds, including women of under-represented cultural groups, varying socio-economic and education levels, residing in other Australian cities and rural communities where access to GDM support may vary and at varying stages of pregnancy. And if possible, that such research offers women the opportunity to participate in their first language. This could enable researchers and clinicians to generate a more complete understanding of women’s experiences and to develop evidence-informed resources and support.
## 5. Conclusions
Managing GDM with lifestyle modification can be effective, but culture must be considered, as it adds complexity. Health professionals need to recognise cultural beliefs, obligations, language and cultural eating practices. GDM education must be culturally sensitive and competent and, where possible, be delivered by health professionals of a shared cultural group. It is also essential to include women’s partners or families in education to enhance the understanding of why lifestyle modifications are needed and to increase the likelihood of them being effectively implemented.
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|
---
title: Frequency of Convenience Cooking Product Use Is Associated with Cooking Confidence,
Creativity, and Markers of Vegetable Intake
authors:
- Natasha Brasington
- Tamara Bucher
- Emma L. Beckett
journal: Nutrients
year: 2023
pmcid: PMC9967409
doi: 10.3390/nu15040966
license: CC BY 4.0
---
# Frequency of Convenience Cooking Product Use Is Associated with Cooking Confidence, Creativity, and Markers of Vegetable Intake
## Abstract
Low levels of cooking skills, confidence and home cooking are related to poorer dietary outcomes and are a common barrier to adequate vegetable consumption. Convenience cooking products may play a role in lowering the levels of confidence and creativity required to prepare home-cooked meals. It has previously been reported that those who use convenience cooking products have lower levels of cooking confidence and creativity and lower vegetable intakes compared to those who do not use these products. However, the relationship between these outcomes and the frequency of use of convenience cooking products has not been assessed. Therefore, a balanced demographic panel of Australian adults ($$n = 1034$$) was surveyed on the frequency of convenience cooking product use, vegetable intake and variety, and opinions and habits regarding vegetable intake. Those who used the products more regularly had higher cooking confidence and creativity, and higher vegetable variety scores, compared to less regular users ($p \leq 0.05$). However, the frequency of use of convenience cooking products was not associated with higher vegetable intake and did not influence views around the ease of eating vegetables. Therefore, these products may be a tool for assisting those with lower levels of cooking skills in accessing a higher variety of vegetables, but vegetable quantity in these products may need to be revised to assist consumers in better meeting intake recommendations.
## 1. Introduction
Cooking skills and the facilitation of home cooking are important contributors to balanced diets [1,2]. However, there are numerous barriers to home cooking from basic or core food ingredients, including cooking skills, confidence and knowledge, time, costs, convenience, attitudes, mood and health [3]. Pressures such as both parties in households tending to work full-time hours [4], the ready availability and marketing of foods cooked out of the home [5] and a reduced emphasis on home economics training in education curricula are contributing to low levels of cooking skills and home cooking in many populations [6,7,8,9,10]. Low levels of cooking skills and home cooking are related to poorer dietary outcomes, with those who cook more often at home being more likely to consume healthy foods more often [11,12,13], and those who tend to have a high level of nutrition knowledge and cooking skills are more likely to achieve the recommended consumption amounts of fruit and vegetables daily [14].
Vegetable consumption is a crucial component, and a marker of, a healthy balanced diet. Vegetables typically require cooking skills to facilitate consumption and enhance palatability. When cooking skills and confidence are low, individuals are more susceptible to using and consuming convenience and commercial foods (takeaway/takeout, fast foods and ready-to-heat meals). Consumer behaviour models also show other attitudinal drivers of convenience food consumption such as guilt [15], moral motivations [16], “convenience orientation” towards time and energy savings [17,18] and time and budget perceptions. Conversely, health consciousness and enjoyment reduce engagement with convenience foods [18]. Recent trends demonstrate the normalisation of convenience foods and thus their importance in dietary patterns [15,19]. While convenience and commercial food products require little or no preparation, reducing the time needed to prepare meals [6], they are typically lower in nutritional quality and are more energy-dense [2,20].
However, some convenience food products are used to reduce the burden of barriers such time, skills and costs, while encouraging and facilitating cooking. These “convenience cooking products” are distinct from other convenience food products in that they are used as ingredients in cooking and can facilitate cooking, as they include back-of-pack recipes with suggested ingredients. This lowers the skill threshold, as well as reducing meal preparation and cooking times. Common convenience cooking products include meal and recipe bases (in liquid or powder form, commonly sold in retort pouches and typically including complete meal recipes), simmer sauces (sold in retort pouches or jars, typically including recipes for complete meals or meal components and serving suggestions) and pasta sauces (sold in jars with recipes or preparation instructions specifically to serve with pasta). Due to the natural comparison to the healthfulness of meals prepared from basic, core and whole ingredients (i.e., cooking from “scratch”), and their often concentrated form, they may be regarded as processed foods and therefore perceived as non-healthful [21,22,23]. However, it is possible that through the inclusion of healthful back-of-pack recipes (e.g., proposing the addition of vegetables), these products may have a positive impact on nutritional intakes and cooking skills.
We have previously reported, using a convenience sample of 842 Australians, that those who reported using convenience cooking products had lower scores for cooking confidence and cooking creativity than those who do not use them [24], suggesting that these products might be a tool to facilitate home cooking in those with low levels of confidence and skills, as users reported typically following the back-of-pack recipes. However, users also typically had lower vegetable intakes [25], and an audit of meal and recipe base products available in Australian supermarkets revealed low vegetable variety in the back-of-pack recipes [26], potentially suggesting that improvements in product design are needed to allow these products to be regarded as tools for facilitating healthy eating.
However, the sample previously studied was obtained via a snowball recruitment technique and, as such, was limited in size and scope, with a skewed demographic profile, without clear findings on frequency of use. Although users of these products may have lower cooking confidence and creativity than those who do not use them, these attributes may vary within users by frequency of use. We hypothesised that a more regular user would have higher confidence and creativity than those who used the same products but less frequently. Understanding these relationships will help better design recommendations and tools for people who opt for convenience cooking over more involved home cooking methods. Therefore, we surveyed a larger, representative (based on Australian national census data [27]) and balanced sample of Australians who were self-reported consumers of convenience cooking products on their usage habits, cooking confidence and creativity and markers of their vegetable intake to assess the relationships in users of key convenience cooking products (meal/recipe bases, simmer sauces and pasta sauces).
## 2.1. Study Design and Recruitment
This study was granted ethical approval (Human Research Ethics Committee, the University of Newcastle, Reference H-2020-0119). A cross-sectional survey was conducted during November 2020 utilising an online market research panel recruited via Qualtrics, (SAP, Provo, UT, USA) using probability sampling. during November 2020. Questions were organised thematically into blocks including questions on convenience cooking product usage habits, cooking skills (confidence and creativity), vegetable intake (serves per day and variety scores) and demographics. For inclusion, participants were required to be living in Australia, over 18 years of age and self-reported users of convenience cooking products (used any meal/recipe base, or commercially available cooking or simmer sauce, at least once a month). As the survey was in English, English comprehension skills were a practical inclusion requirement.
## 2.2. Frequency of Use
Current frequency of use of the convenience cooking products in the major categories of meal and recipe bases (or concentrates), simmer sauces and pasta sauces was recorded. Options for selection were “multiple times a week”, “once a week”, “once a month” and “less than once a month”. However, these responses were subsequently collapsed into 3 categories (>weekly, weekly and <weekly) for analysis.
## 2.3. Cooking Confidence Scores and Cooking Creativity Scores
Scores for cooking confidence and creativity were calculated using questions based on cooking identity and food creativity scales previously published [24]. The presented statements were rated on 5-point Likert scales ranging from strongly disagree [1] to strongly agree [5]. Ratings were summed to calculate scores for cooking confidence (out of 35) and cooking creativity (out of 30). Reversed phrasing questions in these scales were used as attention checks, and those who failed were excluded from the analysis. Internal validity was assessed using Cronbach’s Alpha calculations.
## 2.4. Vegetable Intake and Variety Scores
Typical daily vegetable consumption (serves per day with a guide provided to assist with estimation) was self-reported. These data were then categorised into meeting or not meeting the recommendations for daily consumption of vegetables based on the Australian Guide to Healthy Eating. Vegetable variety scores were calculated based on the frequency of consumption of vegetables commonly consumed by the Australian population [24], with 1 point scored for each listed vegetable eaten at a frequency of one serve per week or more. Fourteen vegetables were listed, resulting in a maximum score of 14.
## 2.5. Vegetable Opinions, Behaviour and Knowledge
Participants were asked to rate how much they agree (5-point Likert scale from strongly disagree to strongly agree) with 3 statements regarding perceptions of vegetable eating (1. Eating 5 serves of vegetables each day is easy; 2. Eating a variety of vegetables each day is easy; 3. I like vegetables.). Participants were also asked to select how many serves or vegetables per day were recommended for good health (numeric scale), and they were asked how likely they were to follow recommendations such as serving with a side salad/vegetables or adding optional vegetable ingredients if recommended on the pack (5-point Likert scale from definitely not to definitely [18]).
## 2.6. Statistical Analysis
Data were analysed using JMP (Pro 14; SAS Institute Inc., Cary, NC, USA). Both categorical and continuous data were used. A p-value threshold of <0.05 was utilised for assessing statistical significance. Contingency tables (Pearson χ2) were used to investigate the relationships between categorical variables. Standard least squares regression was used to compare adjusted means by category with Tukey’s HSD post hoc tests. Analyses were also adjusted for age, sex, income, education, working hours and nights per week cooking at home.
## 3.1. Participants and Demographics
After exclusions for incomplete responses, failure of attention checks and removal of those who completed the survey in less than half the median completion time, 1034 complete and valid responses were included in the present analyses. Participant age ranged from 18 to 88 years, with a median age of 43 years, and participants were relatively evenly distributed across age groups, education levels and income levels (Table 1). Participants were $52.8\%$ females. The majority of participants were working 30 h or less per week (noting that this survey was conducted while Australia was impacted by the COVID-19 pandemic; Table 1). The majority of participants reported cooking dinner at home 5 days a week or more (Table 1).
## 3.2. Frequency of Use
The most common frequency of use was weekly for each convenience cooking product class assessed (meal and recipe bases, simmer sauce and pasta sauces; Table 2). Income, working hours, education level, frequency of cooking dinner at home, and age distributions varied by the frequency of use for each convenience cooking product class (Supplementary Table S1).
## 3.3. Cooking Confidence and Creativity
High internal reliability of the scales used for cooking confidence and creativity was found, with calculations returning Cronbach’s Alpha scores of 0.90 and 0.88, respectively. Scores for cooking confidence ranged from 7 (the minimum possible score) to 35 (the maximum possible score) with a mean of 25.1 (standard deviation 5.6). Scores for cooking creativity ranged from 6 (the minimum possible score) to 30 (the maximum possible score), with a mean of 18.5 (standard deviation 4.9).
Mean cooking confidence scores were higher in those who used each of the convenience cooking products most regularly (Figure 1A–C) compared to those who used them less frequently. These results remained significant when analyses were conducted with adjustments for age, sex, income, education, work hours and cooking frequency applied (Supplementary Figure S1A–C). Mean cooking creativity scores were higher in those who used each of the convenience cooking products most regularly compared to those who used them less frequently (Figure 1D–F). These results remained significant when adjustments for age, sex, income, education, work hours and cooking frequency were applied to analyses (Supplementary Figure S1A–F).
When analyses were stratified by sex, confidence scores by frequency of meal and recipe base use differed only in males, with the exception of the use of meal and recipe bases, which showed similar patterns in males and females (Figure 2). Interaction terms for sex and frequency of use were significant for meal and recipe bases ($$p \leq 0.02$$), simmer sauces ($$p \leq 0.008$$) and pasta sauces ($$p \leq 0.01$$) in predicting confidence scores. Mean confidence scores did not differ ($$p \leq 0.6$$) between males (mean 25.3, standard deviation 5.7) and females (mean 25.1, standard deviation 5.5). The results remained similar when adjustments for age, sex, income, education, work hours and cooking frequency were applied (Supplementary Figure S2).
Creativity scores were higher in males (mean 19.1 standard deviation 4.8) than in females (mean 18.1 standard deviation, 4.9, $$p \leq 0.002$$). When analyses were stratified by sex, creativity scores by frequency of meal and recipe base use differed only in males, with the exception of the use of simmer sauces, which showed similar patterns in males and females (Figure 2). Interaction terms for sex and frequency of use were significant for meal and recipe bases ($$p \leq 0.04$$) and pasta sauces ($$p \leq 0.04$$) in predicting confidence scores, but not for simmer sauces ($$p \leq 0.09$$). These results remained similar when adjustments were applied for age, sex, income, education, work hours and cooking frequency (Supplementary Figure S2).
## 3.4. Vegetable Intake
The consumption of five or more serves of vegetables per day was reported by $5.4\%$ of the sample. Frequencies of use of meal and recipe bases (χ2 = 0.7, $$p \leq 0.7$$), simmer sauces (χ2 = 0.7, $$p \leq 0.7$$) and pasta sauces (χ2 = 0.4, $$p \leq 0.8$$) were not associated with differences in the proportion of participants eating at least five serves of vegetables per day. However, vegetable variety scores were associated with frequency of use, with vegetable variety score increasing with frequency of use in all product categories (Figure 3). There was no interaction between sex and frequency of use in predicting vegetable variety score for meal and recipe bases ($$p \leq 0.8$$), simmer sauces ($$p \leq 0.7$$) or pasta sauces ($$p \leq 0.6$$). These results remained similar when analyses were stratified by sex and were adjusted for age, sex, income, education, work hours and cooking frequency (Supplementary Figures S3 and S4). In a multifactorial model, frequencies of use of each of the convenience cooking products (meal/recipe bases, simmer sauces and pasta sauces) were significant predictors of vegetable variety scores (Standardised Beta = 0.1, 0.04, 0.06, respectively, $p \leq 0.05$), along with age (0.1), income (0.1) and frequency of cooking (−0.08).
The largest proportion ($33.0\%$ and $31.5\%$) of respondents gave a neutral rating to the statements “Eating 5 serves of vegetables each day is easy” and “*Eating a* variety of vegetables each day is easy”. Strongly agree ($40.0\%$) was the most common response to “I like vegetables”. Convenience cooking product frequency of use was not related to any of these self-reported opinions on vegetable intake (Table 3, all $p \leq 0.05$).
When asked how many serves of vegetables per day were recommended for good health, $33.1\%$ responded correctly (approximately five serves), $22.1\%$ overestimated requirements and $44.8\%$ underestimated requirements. Those who use meal and recipe bases more than weekly were more likely (χ2 = 14.2, $$p \leq 0.0007$$) to overestimate needs ($31.1\%$) compared to those who used them weekly ($16.9\%$) or less than weekly ($21.2\%$). Distributions did not vary by frequency of use of simmer sauces or pasta sauces ($p \leq 0.05$).
When asked if participants follow serving suggestions such as “serve with salad” or “serve with vegetables” when using convenience cooking products “might or might not” was the most common response at $46\%$. Thirty-eight percent were “likely” to follow serving suggestions ($28\%$ probably, $10\%$ definitely), and only $17\%$ were “not likely” to ($3\%$ definitely not, $14\%$ probably not). When asked if they would add optional extra ingredients if suggested on the pack, “might or might not” was the most common response at $50\%$. Thirty-eight percent were “likely” to include optional ingredients ($31\%$ probably, $7\%$ definitely), and only $11\%$ were “not likely” to ($2\%$ definitely not, $9\%$ probably not). These distributions did not vary by frequency of use of any convenience cooking product category.
## 4. Discussion
This study is the first to investigate the relationship between the frequency of convenience cooking product use and outcomes related to cooking confidence, cooking creativity and vegetable intakes. These findings extend upon previous research studying users of these products, compared to non-users, without consideration of the frequency of use [25]. The findings here regarding cooking creativity and confidence complement the earlier findings that found use was linked to higher cooking confidence and creativity, with more regular use of convenience cooking products (meal/recipe bases, simmer sauces and pasta sauces) being associated with higher scores. Here, the frequency of use correlated with vegetable variety scores, with more frequent use linked to higher variety, which is interesting given there was no difference in variety scores between users and non-users previously [25]. However, this did not result in a higher overall vegetable consumption level.
This suggests that these convenience cooking products may be vehicles for enhancing cooking skills and, either directly or indirectly, introducing vegetable variety into the diet through encouraging a wider variety of recipe use and meal creation or through increasing the confidence and creativity required to incorporate vegetables. Research suggests that consuming a wide variety of plant-based foods daily will provide health benefits [28]. Different sources of vegetables provide the body with a variety of sources of micronutrients and phytochemicals for health [29]. However, the low overall vegetable intake across all frequency-of-use groups may suggest that these products do not contain sufficient serves of vegetables in their back-of-pack recipes [26]. Only $5.4\%$ of the total cohort reported consuming five or more serves of vegetables per day. This reflects the findings of the 2018 Australian National Health Survey which found that $95\%$ of Australians do not consume the recommended five or more serves of vegetables daily [30]. This suggests that the following study is likely to be a good sample of the Australian adult population.
The findings regarding opinions on vegetable intake suggest that convenience cooking products may be influencing vegetable consumption and confidence, directly leading people to consider the challenges associated with vegetable consumption, as opinions on the ease of eating enough and a variety of vegetables and whether participants reported liking vegetables did not vary by frequency of convenience cooking product use. Regular meal/recipe base users were more likely to overestimate how many vegetables are recommended for health; this may be due to higher exposure to back-of-pack recipes or may be a variable that encourages higher use of these products.
The relationships for cooking confidence and creativity and frequency of convenience cooking product use were due to significant relationships in males, with limited relationships found in females. While women are more likely to take responsibility for home cooking [31], men’s motivation for cooking more highly correlates with cooking enjoyment [31], with men likely to acquire cooking skills when cooking is considered to be an enjoyable activity, in comparison to females whose familiar roles are mostly characterised by their task as the main food provider and for whom cooking tends to be an obligation. Convenience cooking products may assist with skill development by lowering the threshold of effort required, which may make cooking a more enjoyable activity. Older, single men have previously been found to consume fewer fruits and vegetables than married men, and men were also less likely to cook a range of meals and more likely to choose foods that were easy to prepare than women of the same age group [32]. Therefore, these products may have specific appeal to males who have lower cooking skills and creativity.
Importantly patterns were generally the same across each subcategory of convenience cooking products. This may indicate high concurrent use or may indicate that these product categories fulfil similar roles for users. While there are likely variations in the vegetable contents of these products and their back-of-pack recipes, empirical data on these differences are needed to further understand these relationships.
Limitations of this study and other directly related studies are that data have been collected by self-reported survey means, and only in a cross-sectional manner. Therefore, no causal insights can be gained into relationships with health status or into how confidence, creativity or vegetable variety would vary when these products are introduced or removed from the diet. It is possible that convenience cooking products reduce the need for pre-prepared convenience foods and take-away products. However, it is also possible that these products displace cooking from core ingredients. Strengths of this study include the utilisation of a market research panel to obtain a large sample with key demographics representative of the broader Australian population as per Australian Census data. This is the first study regarding convenience cooking product use in a representative sample, and these data are important for addressing the information gap on these frequently consumed products.
## 5. Conclusions
The objective of this study was to assess the relationships between convenience cooking product usage habits, cooking confidence and creativity, vegetable intake and attitudes. The findings presented here describe a nascent research field in convenience cooking products and suggest that rather than convenience cooking products being unhealthy processed foods, they may have a role as a public health tool. Furthermore, this research has a practical utility in that these products have the potential to be recommended by dietitians and other health professionals for consumers to utilise their current cooking skills and confidence when cooking in the kitchen. The knowledge generated here may also inform the future design of these products to appeal to both consumer needs and nutritional needs. More frequent use is associated with higher confidence, creativity and vegetable variety, so despite being potentially viewed as processed and not as good as cooking from core food ingredients, convenience cooking products might be beneficial tools for those with low skills and other barriers such as time and costs. More research is needed into the role convenience cooking products do and may be able to play in encouraging higher vegetable intakes for health, including longitudinal research and intervention trials to demonstrate causation.
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|
---
title: 'Nutritional Composition and Antioxidant Activity of Gonostegia hirta: An Underexploited,
Potentially Edible, Wild Plant'
authors:
- Yaochen Li
- Zheng Hu
- Xiaoqi Chen
- Biao Zhu
- Tingfu Liu
- Jing Yang
journal: Plants
year: 2023
pmcid: PMC9967410
doi: 10.3390/plants12040875
license: CC BY 4.0
---
# Nutritional Composition and Antioxidant Activity of Gonostegia hirta: An Underexploited, Potentially Edible, Wild Plant
## Abstract
Wild, edible plants have received increasing attention as an important complement to cultivate vegetables, as they represent an easily accessible source of nutrients, mineral elements, and antioxidants. In this study, the tender stems and leaves of Gonostegia hirta, an edible species for which only scarce data are available in the literature, are thoroughly evaluated for their nutritional profile, chemical characterization, and antioxidant activity. Being considered as an underexploited, potentially edible plant, the nutritional composition of *Gonostegia hirta* was identified, and several beneficial compounds were highlighted: sugars, potassium, calcium, organic acids, fatty acids, phenolics, and flavonoids. A total of 418 compounds were identified by metabolomic analysis, including phenolic acids, flavonoids, amino acids, lipids, organic acids, terpenoids, alkaloids, nucleotides, tannins, lignans, and coumarin. The plant sample was found to have good antioxidant capacities, presented by DPPH, FRAP, ABTS+, hydroxyl radical scavenging capacity, and its resistance to the superoxide anion radical test. *In* general, *Gonostegia hirta* has a good nutritional and phytochemical composition. The health benefits of *Gonostegia hirta* as a vegetable and herbal medicine is important for both a modern diet and use in medication.
## 1. Introduction
Wild, edible plants are an important plant resource, not only as an inexpensive source of nutrients, vitamins, antioxidants, and functional ingredients because of their nutritional potential, but also as a cultural heritage practice that should be preserved. In some less-developed regions and economically disadvantaged areas in the world, wild, edible plants are still traditionally consumed and play an important role in the diet of local populations.
Globally, about 30,000 edible plant species are recorded at present; however, only about $0.5\%$ of them are widely grown [1]. The disappearance of many wild, edible plant species has been exacerbated by an over-reliance on high-yielding and genetically consistent crops. This has led to a monoculture of edible plants that can be grown on a large scale and can be put into production [2]. To date, global agriculture products do not seem to be sufficient enough to meet human’s nutritional needs. Meanwhile, wild, edible plant species that can be collected from the wild or grown using traditional methods can potentially play a role in diversifying diets and combating “hidden hunger” caused by micronutrient deficiencies [3]. In recent years, wild, edible plants have not only received further attention from the scientific community, with many wild, edible plants being discovered, documented, and studied for their chemical and functional properties, but also from the food industry and consumers, who are increasingly interested in sustainable and healthy foods. In addition, in some countries and regions, such as Europe, Japan, and China, local-specialty wild plants are transformed into various products, dishes, and skin care products as cultural promotion and exchange practices, while also seeking their health benefits.
Gonostegia hirta is a perennial herb of the family Urticaceae, and is a common Chinese medicinal product and wild, edible vegetable. On the one hand, *Gonostegia hirta* is an ethnic medicine commonly used in the treatment of stomachaches, bleeding, and mastitis [4]. A few studies have shown that *Gonostegia hirta* contains flavonoids, phenols, organic acids, polysaccharides, and other bioactive substances, while flavonoids, phenols, and organic acids have strong antioxidant properties [5,6]. An ethnobotanical survey of wild plants was conducted by Hong et al. [ 7] and indicted that *Gonostegia hirta* is useful as a traditional medicinal herb, and it also can be consumed as herbal tea after being dried, which has the effect of clearing heat and detoxifying the body, spleen tonic, digestion, and removing dampness.
On the other hand, *Gonostegia hirta* is also often used as an edible, wild plant. Of the different parts of *Gonostegia hirta* that may have a nutritional value (the leaves, young stems, and roots), the leaves and young stems are the most frequently consumed parts. These leaves and young stems can be eaten in stir-fries, cooked in soups, or made into dumplings. Although it is worthy of being noticed as both a nutritional source and traditional medicine plant, the relevant research focusing on the chemical characterization of *Gonostegia hirta* is still inadequate, and few reports have been conducted on its nutritional composition. The present study has four main objectives concerning the nutritional value and chemical characteristics of Gonostegia hirta: [1] to characterize the main nutritional values obtained from moisture, crude fat, soluble sugars, fatty acids, amino acids, minerals, and organic acids; [2] to evaluate the safety concerning the total content of potentially toxic and toxic elements and total saponins; [3] to evaluate antioxidant and potential functional properties through chemical content and metabolomics analysis; and [4] to comprehensively evaluate the nutritional, flavor, and functional values to meet the needs of healthy, vegetable diets to provide a basis for the development and utilization of Gonostegia hirta.
## 2.1.1. Moisture and Crude Fat
Table 1 shows that the moisture content of Gonostegia hirta, $50.84\%$, and its crude fat content, $2.57\%$. The fat content of vegetables is usually very low; therefore, the low-fat content observed in *Gonostegia hirta* supports this fact.
## 2.1.2. Minerals and Potentially Toxic Elements
As shown in Table 1, the highest amounts of minerals observed in *Gonostegia hirta* are potassium (K), calcium (Ca), phosphorus (P), and magnesium (Mg). Their contents were 3855.22, 1352.49, 569.51, and 284.35 mg/100 g of dry weight (DW), respectively. K is an essential nutrient that contributes to maintain total body fluid, acid and electrolyte balance, and normal cell function. Increasing K intake may be beneficial for most people in preventing and controlling elevated blood pressure levels and strokes [8]. Ca is also important for controlling blood pressure and promoting bone and tooth growth [9]. P plays a vital role in energy generation, human growth and development, and also provides the structural framework for DNA and RNA [10]. It also functions in regulating blood sugar levels [11]. Mg has numerous functions, including cell signaling and energy production, and it is also an important mineral in bones, cell membranes, and chromosomes [9]. The content of Ca and Mg in *Gonostegia hirta* is much higher than in some cultivated vegetables. For example, the Ca content in *Gonostegia hirta* was 5.12- and 22.24-times higher than in cassava leaves and chicory [12,13], respectively, and the Mg content in *Gonostegia hirta* was 7.10-, 5.10-, and 9.38-times higher than in chicory, green lettuce, and Swiss chard, respectively [13]. It has been suggested that *Gonostegia hirta* could act as an important supplement for calcium and magnesium. Zinc (Zn) has many roles in the body, including immune function, growth and development, nerve function, vision, and fertility [9]. Compared to spinach (7.95 mg/100 g DW) [14] and amaranth (3.7 mg/100 g DW) [12], *Gonostegia hirta* also has a higher Zn content (10.47 mg/100 g DW). However, it is important to note that the excessive consumption of zinc (estimated dose of 325–650 mg) is dangerous to human health [15]. Minerals, such as K, Ca, Mg, P, and Zn, are crucial for normal body development and maintenance. The results indicate that *Gonostegia hirta* is rich in these essential minerals, of which Fe, Zn, Ca, Mg, and Cu are some of the most commonly deficient mineral elements in the human diet [11]; thus, *Gonostegia hirta* seems to be a multifaceted supplement for these elements in the human body.
The contents of cadmium (Cd), lead (Pb), and chromium (Cr) were also measured to evaluate the safety of Gonostegia hirta, and the results show the Cd, Pb, and Cr contents in *Gonostegia hirta* are within the safe range, according to the Commission Regulation (EU) $\frac{2021}{1317}$, Commission Regulation (EC) No $\frac{1881}{2006}$, and Chinese National Food Safety Standard for Maximum Levels of Contaminants in Foods (GB 2762-2017). *In* general, *Gonostegia hirta* is less contaminated by potentially toxic and toxic elements; however, it might also be associated with the local climate, soil, and ecological environment, and should not be picked in contaminated areas, such as areas with developed industries, high traffic pollution, and high sewage discharge [16].
## 2.1.3. Soluble Sugars and Organic Acids
*In* general, monosaccharides are easily digested and absorbed by the human body; therefore, they are thought to have a high nutritional value [17]. Three types of soluble sugars were measured in Gonostegia hirta, namely, sucrose, glucose, and fructose. Among these, fructose has the highest value, accounting for $46.71\%$ of the total (Table 1), and is sweeter and tastier than sucrose and glucose [18]. The total soluble sugar content of *Gonostegia hirta* is 87.03 mg/g, which higher than lettuce (7.72 to 16.24 mg/g DW) [19] and very close to soybean (84.70 to 140.91 mg/g) [20].
Organic acids affect a number of characteristics of vegetables, such as flavor, aroma, and appearance [21]. The most abundant organic acid detected in *Gonostegia hirta* was citric acid (22.5 mg/g DW), followed by tartaric (10.68 mg/g DW), oxalic (3.4 mg/g DW), and ascorbic (1.30 mg/g DW) acids (Table 1). Among these, citric acid is an important organic acid with a strong, sour taste, is easily soluble in water, and is a natural preservative [22], while tartaric acid is a natural antioxidant and flavorant in foods [23]. Moreover, oxalic acid easily combines with mineral elements to form insoluble oxalate, and vegetables with a high oxalic acid content can be consumed in large quantities with a distinct bitter taste and may cause hyperoxaluria and kidney stones [24,25]. Gonostegia hirta contains slightly higher oxalic acid levels than lettuce (1.16 to 1.67 mg/g DW) [18], but less than conventional spinach (about 8 to 12.5 mg/g) [26]. Thus, it is recommended to blanch *Gonostegia hirta* to reduce the bitterness caused by oxalic acid when consuming it. In addition, *Gonostegia hirta* has a higher ascorbic acid content compared to spinach and chicory, and the ascorbic acid levels are 0.52 mg/g of fresh weight (FW) and 0.30 mg/g FW [13]. Ascorbic acid (vitamin C) is considered one of the most powerful and least toxic, natural antioxidants, which has been shown to be effective against superoxide radical anions, H2O2, hydroxyl radicals, and singlet oxygen [27].
In total, 27 organic acid species were detected by Ultra Performance Liquid Chromatography (UPLC)—tandem mass spectrometry (MS/MS), accounting for $6.46\%$ of 418 metabolites in total (Figure 1 and Table S1). Some of these organic acids are thought to have unique functions, such as succinic acid (SA), mangiferic acid, and kynurenic acid (KYNA). SA is an important metabolite that has been shown to be involved in promoting energy expenditure and fighting obesity [28]. Mangiferic acid can promote human skin regeneration, and it is expected to be used as a new material in skin regeneration biotherapy or cosmetics in the future [29]. KYNA is a metabolite of kynurenine, which has anti-inflammatory, antioxidant, and pain-relieving properties [30].
## 2.1.4. Amino Acid
Amino acid (AA) composition is a reliable indicator of the nutritional value of food and is traditionally classified as essential amino acids (EAAs) and non-essential amino acids (NEAAs). As shown in Table 2 and Figure 2, 17 amino acids were detected in Gonostegia hirta, and 8 of them present EAAs, namely, isoleucine (Ile), leucine (Leu), methionine (Met), lysine (Lys), valine (Val), threonine (Thr), phenylalanine (Phe), and histidine (His), which have an important effect on the nutritional quality of plant-based products. His has the highest content (0.091 mg/g DW), followed by Thr (0.033 mg/g) and Val (0.020 mg/g DW). The content of Met in *Gonostegia hirta* is 0.015 mg/g DW, and it is a sulfur-containing amino acid that is essential for cellular metabolism and protein uptake. In addition, aspartic acid (Asp) is the most abundant of all 17 amino acids, which may contribute to the fresh taste of Gonostegia hirta.
The content and ratio of individual amino acids are also related to the flavor of the plant. For example, Asp and glutamic acid (Glu) are thought to be significant contributors to the fresh flavor [30], which accounts for $32.06\%$ of total amino acids in Gonostegia hirta. At the same time, the proportion of sweet amino acids (Thr + Ser + Gly + Ala + Lys + Pro) [31] was $26.22\%$; the proportion of bitter amino acids (Val + Met + Ile + Leu + Phe + His + Arg) [31] was $20.63\%$. The results show that the content of bitter amino acids is lower than sweet and fresh amino acids, indicating that the palatability of *Gonostegia hirta* might be relatively good. In addition, some amino acids are considered as medicinal amino acids, including Asp, Glu, Gly, Met, Leu, Tyr, Phe, Lys, and Arg [31], which account for $62.19\%$ of the total amino acids in Gonostegia hirta. For example, Tyr may improve cognitive ability for human adults, while Arg has a beneficial effect on the regulation of nutrient metabolism to enhance lean tissue deposition and insulin resistance in humans [32,33]. Additionally, those two compounds had the highest levels of all medicinal amino acids.
Some amino acid derivatives were also detected by UPLC-MS/MS, such as trans-4-hydroxy-l-proline (Hyp), N-Acetylneuraminic acid (NANA), L-theanine, proline betaine, and pipecolic acid (Table S1). These amino acid derivatives have different roles in the growth and metabolism of plants, medicinal functions, etc. For example, *Hyp is* a useful chiral building block for the production of many nutritional supplements and drugs [34]. NANA consumes toxic hydrogen peroxide under physiological conditions and may serve as an intrinsic antioxidant in the future [35]. L-theanine is known to be an amino acid unique to tea, and has positive effects on relaxation, cognitive performance, emotional state, sleep quality, cancer, cardiovascular disease, obesity, and the common cold [36].
## 2.1.5. Fatty Acid
The composition of fatty acids has a significant impact on mammalian health. For example, some saturated fatty acids (SFAs) have been reported to exhibit deleterious effects, while the intake of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) reduced the risk of cardiovascular and other metabolic diseases, thereby improving one’s lifespan [37]. Therefore, lipid composition is critical for evaluating the quality of wild, edible plants. The fatty acid profile of *Gonostegia hirta* is shown in Table 3, evidencing that a total of 16 fatty acids can be identified (Figure 3). The two major compounds are the essential fatty acids linolenic and linoleic acids, with SFAs accounting for about $27.4\%$ and PUFAs accounting for about $72.6\%$. In the samples, PUFAs were the major group, with ω-3 fatty acids accounting for $31\%$ of total fatty acids. Previous studies suggested that a higher intake of ω-3 may protect us from inflammatory diseases, cancer, cardiovascular disease, and other chronic diseases [38]. It has been reported that the optimal intake ratio of ω-6 to ω-3 fatty acids is 1~$\frac{2}{1}$ [39], and the ratio of ω-6 and ω-3 fatty acids in *Gonostegia hirta* is $\frac{1.32}{1}$, which means the consumption of *Gonostegia hirta* could possibly be beneficial for our health.
Except for the 16 fatty acids mentioned above, more fatty acids were detected by UPLC-MS/MS, and some of them, such as elaidic and punic acids, serve many important roles. Ohmori et al. observed that elaidic acid may provide significant metastatic potential for colorectal cancer (CRC) cells, which has important implications for the treatment of CRC [40]. Punicic acid has great potential as an antioxidant, anti-diabetic, and natural healing agent for inflammatory diseases [41]. In addition to these fatty acids, we also found a phosphatidylcholine called choline alfoscerate; it is a common choline compound and acetylcholine precursor in the brain that has been shown to be effective in the treatment of Alzheimer’s disease and dementia [42].
## 2.1.6. TP (Total Phenols), TF (Total Flavonoids), and TS (Total Saponins)
Phenols are widely distributed in nature and their anti-microbial, anti-bacterial, antioxidant, pharmacological, and nutritional properties have been widely recognized [43]. The TP content of *Gonostegia hirta* was determined (Table 4). The result indicates that *Gonostegia hirta* is a good source of phenolics (TP: 1.20 ± 0.10 mg GAE/g DW), with an amount 2.43-times higher than spinach (0.493 mg GAE/g DW) and 5.53-times higher than green lettuce (0.217 mg GAE/g) [13]. However, the result in this study is lower than that of Wong et al. ( 5.6 and 5.3 mg GAE/g DW for leaves and stems, respectively) [5]. The reason for the discrepancy may be due to the plant development stage, picking regions, and extraction methods. In addition, 47 phenolic acid compounds were found by UPLC-MS/MS, accounting for $11.24\%$ of the total (Figure 1). p-Coumaric, ferulic, caffeic, chlorogenic, and coumaric acids were included, which received a lot of attention in the previous study, and are considered to have a variety of active functions [44]. For example, extensive studies have shown that p-Coumaric acid (especially the p-CA adduct) presents a variety of biological activities, including antioxidant, anti-inflammatory, anti-platelet, and anti-cancer activities, as well as reducing atherosclerosis, various tissue damage, neuronal damage, gout, and diabetes [45]. Ferulic acid has a good antioxidant capacity due to the presence of phenolic hydroxyl groups with a hydrogen-donating capacity [46]. The synergistic effect of these substances provides a certain basis for the potential biological activity of Gonostegia hirta.
The TF content in *Gonostegia hirta* was also measured in the present study, and a value of 76.49 ± 5.58 mg/g was obtained, which is 2.85-times higher than that of *Brassica juncea* [47]. To date, more than 6000 flavonoids have been identified, and their basic functions in plants include regulating growth and providing protection against pathogens. Because of their antioxidant, antitumor, anti-inflammatory, antibacterial, and antiviral activities, they have attracted considerable interest [48]. Flavonoids were the most diverse of the 418 identified metabolites, accounting for $31.58\%$ (Figure 1). The flavonoids identified can be divided into ten main groups, as shown in Figure 1. Quercetin, kaempferol, popcornin, apigenin, and lignan are the five most prevalent plant flavonoids, which were all detected in Gonostegia hirta. Apigenin has low toxicity and multiple beneficial bioactivities, such as anti-cancer and antibacterial effects [49,50], and received a considerable attention. Lignans, quercetin, prunetin, and kaempferol have also shown strong anti-cancer effects in various tests [51,52]. In this study, kaempferol, quercetin, isorhamnetin-3-O-rutinoside, and kaempferol 3-O-rutinoside were detected, and this is consistent with the results of Lei et al. [ 53].
Saponins are sugar-conjugated natural compounds with a variety of biological properties, such as anti-inflammatory, anticancer, antioxidant, and immunomodulatory [54]. Nevertheless, it has been shown that high doses of saponins can cause damage to the liver [55]. A TS content of 60.30 ± 0.66 mg/g was detected in Gonostegia hirta, and suggested that the value was within the range compared to *Aralia elata* (38.37 to 104.31 mg/g DW) [56]. The metabolites of *Gonostegia hirta* were detected by UPLC-MS/MS and three terpenoids were identified, including soyasapogenol B, 3, 24-Dihydroxy-17, 21-semiacetal-12[13], oleanolic fruit, and 2-Hydroxyoleanolic acid (Table S1). Of the abovementioned compounds, only soyasapogenol B belongs to triterpene saponins, which have also been shown to have a good ability to inhibit the proliferation of human liver cancer cells [57].
## 2.1.7. Alkaloids
Alkaloids are the main chemical constituents and the basis of medicinal substances in many medicinal plants, and some alkaloid components are also the main substance basis for the toxicity of plants [58]. The present study detected 23 alkaloids (Table S1), among which trigonelline, betaine, and caffeine are thought to be the most important substances. Trigonelline has a bitter taste and has been reported to have hypolipidemic, antiviral, central nervous system therapeutic, and memory-retention effects [59,60]. Although some studies suggest it has low toxicity levels, Mishkinsky et al. reported that oral and subcutaneous LD50 of trigonelline in rats of was ≈ 5000 mg/kg, and no mice died during the experiment, even when 50 mg/kg of fenugreek was fed to them for 21 days. Therefore, it is safe to consume vegetables that contain trigonelline, such as Gonostegia hirta, in moderation [61]. Some studies have shown that betaine has anti-inflammatory and antioxidant properties, and is also beneficial to alleviates endoplasmic reticulum stress, and therefore contributes to improve insulin sensitivity and better glucose clearance, with a greater potential to fight diabetes [62]. Caffeine is naturally found in various foods, such as coffee, tea, and cocoa, and has also been detected in Gonostegia hirta. Caffeine is used in cosmetics for its high antioxidant capacity and ability to penetrate the skin barrier [63], and it is often used as a stimulant [64]. An allergen was also detected, namely, cocamidopropyl betaine, which is mainly used as a surfactant in cosmetics, and it may cause a skin allergy on the head and neck. Thus, the subsequent use of *Gonostegia hirta* requires attention [65,66]. The types of alkaloids present in *Gonostegia hirta* can also be divided into phenolamine and indole alkaloids, the more useful of which is spermine, which has been shown to be associated with the development of various human cancers and can be used as a diagnostic, prognostic, and therapeutic tool for various cancers [67].
## 2.2. Antioxidation Capacity Analysis
To date, only a few studies have been conducted on the antioxidant properties of Gonostegia hirta. The values of the DPPH and ABTS+ scavenging capacities of *Gonostegia hirta* were 5.92 and 68.82 mg/g, respectively (Table 5). Additionally, the values are much higher than for cabbage (1.04 mg/g DW and 0.28 mg/g FW) [68,69]. However, the ferric-reducing power (62.23 μmol/L) of *Gonostegia hirta* is less than for cabbage (53.01 μmol/g) [68]. This may be due to the differences in antioxidant capacity-determination methods. The scavenging ability of DPPH and ABTS radicals is based on a combination of hydrogen atom transfer (HAT) and single electron transfer (SET) mechanisms, whereas FRAP is based on a SET mechanism, and the whole reaction does not involve free radicals, but only electron transfer ability. This may lead to the difference in the ability reflected by FRAP, compared to the other two components [70].
In addition, ABTS radicals are soluble in water, and organic solvents and are mainly used to determine the antioxidant capacity of lipophilic and hydrophilic compounds (e.g., vitamin C, vitamin E, phenolic compounds, and anthocyanins). However, DPPH radicals are insoluble in water and are usually soluble in methanol, ethanol, or their aqueous mixtures (water content should not exceed $60\%$), and the antioxidant capacity of scavenging DPPH radicals is correlated with phenolic acids and flavonoids [70].
Therefore, we speculated that the DPPH and ABTS+ scavenging abilities of *Gonostegia hirta* may be related to the abundant phenolic substances, such as caffeic acid, ferulic acid, p-coumarins, and quercetin, which are thought to have high free-radical scavenging capacities, all of which were detected in *Gonostegia hirta* [71,72,73]. Compared to some common vegetables [13,47], *Gonostegia hirta* has higher TP and TF levels. *In* general, the higher the content of TP and TF, the greater the antioxidant activity shown by the plant [74], which may also indicate its good antioxidant capacity. In addition, the presence of ascorbic acid also significantly contributes to the antioxidant capacity of plants. We can also observe, compared to other studies, the ascorbic acid content of *Gonostegia hirta* is also much higher than that of some other vegetables, such as spanich, chicory, and green lettuce [13,26]. It is suggested that the antioxidant capacity of *Gonostegia hirta* might be better and could contain more substances with an antioxidant activity. The chemical composition of the plant significantly changes with its growth and development, which can be some of the reasons for the difference in its chemical composition, compared to other vegetables.
## 3.1. Plant Material
Gonostegia hirta was obtained from Li Shui, Zhejiang province (27°25′ N~28°57′ N, 118°41′ E~120°26′ E) on 19 July 2019. Fresh stems and leaves were washed with ionized water, freeze-dried, crushed, and then stored at −20 °C until further analysis.
## 3.2.1. Moisture
The samples were cleaned and weighed (W1), then freeze-dried for 72 h and weighed again (W2), and the moisture percentage was calculated as:Moisure %=W1−W2W1×100
## 3.2.2. Crude Fat
Crude fat was determined as previously described by Xu. [ 75]. Fatty acids in the sample were extracted with 10 mL of hexane (1.0 g sample) (W1). The leaves were sonicated in a water bath at 42 °C for 10 min, centrifuged, and filtered. A total of 3 extractions were performed. The combined extracts were rotary evaporated and oven dried at 60 °C to a constant weight (W2), and the crude fat percentage was calculated as:Crude fat %=W2W1×100
## 3.2.3. Minerals and Potentially Toxic Elements
The elements were determined as previously described by Yang et al. [ 76]. Briefly, the freeze-dried powder (0.50 g) was digested with concentrated HNO3, fixed with water to 50 mL, and analyzed for minerals with a Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). We used an IRIS/AP-ICP (TJA, Dartmouth, MA, USA) instrument and the ICP-OES procedure mainly referenced the “Food National Standard for Determination of Multi-element in Food” (GB 5009. 268-2016).
## 3.2.4. Soluble Sugar
Soluble sugars were determined by high-performance liquid chromatography coupled to a refraction index detector (HPLC–RID), mainly referring to the method of Yao [77]. The samples were extracted (0.1000 g) with 6 mL of ultrapure water in a water bath at 65 °C for 20 min. The extraction solution was filtered by a 0.45 μm microporous filter prior for analysis.
A sample of 5 μL was analyzed in an Agilent 1200 HPLC system equipped with a differential refractive index detector, using a Waters sugar-Pak I column WAT084038 (6.5 × 300 mm, 10 µm). The column temperature was maintained at 85 °C at a rate of 0.8 mL/min, and the mobile phase was ultrapure water. The contents of glucose, sucrose, and fructose in the samples were calculated according to the standard curves drawn from the results of the injection.
## 3.2.5. Organic Acid
Reducing the organic acid was determined according to the method described by Song et al. [ 78]. The extract was obtained by passing 0.2000 g of sample and 10 mL of KH2PO4-H3PO4 buffer solution (0.02 mol/L, pH = 2.9) in a water bath at 75 °C for 1 h. The extraction solution was filtered by a 0.45 μm microporous filter prior for analysis. The results are expressed as mg per g of plant DW.
The samples were analyzed on an Agilent 1200 HPLC system equipped with a DAD detector using column InertSustain C18 (4.6 mm × 250 mm, 5 μm). The mobile phase was KH2PO4-H3PO4 at a rate of 0.8 mL/min. The contents of oxalic, tartaric, ascorbic, and citric acids in the samples were calculated from the standard curves drawn from the injection results.
## 3.2.6. Amino Acid
The extracts were prepared using 0.1000 g of sample and 5 mL of ultrapure water. The samples were extracted in an ultrasonic bath at room temperature for 60 min. The extract was filtered through a 0.22 μm filter, and then stored at 4 °C prior to analysis.
A total of 10 μL of sample solution, 70 μL of AccQ buffer, and 20 μL of derivatives were mixed for 15 s and heated in an oven at 55 °C for 10 min. The samples were then analyzed using the AccQ Tag system (Waters, Milford, MA, USA) by Waters Arc HPLC with an AccQ TagTM amino acid column (100 mm × 2.1 mm, 1.7 μm, Waters Corporation, Milford, MA, USA). The rate was 1 mL/min. Mobile phase A was AccQ-Tag A solution diluted at 1:10 (v/v) with ultrapure water, mobile phase B was acetonitrile, and mobile phase C was ultrapure water. The content of each amino acid quantity in the sample was calculated from the standard curve drawn from the injection results.
## 3.2.7. Fatty Acid
Fatty acids were determined as previously described by Xu. [ 75], and GC-MS methods mainly referenced the “Food National Standard for Safety Determination of Fatty Acids in Foods” (GB 5009.168-2016). The extracts (Section 3.2.2) were 2 mL of hexane and 20 μL of undecanoic acid standard (1 mg/mL), mixed and analyzed by GC-MS (GCMS-QP2010 SE, SHIMADZU) after methylation with the KOH-CH3OH and H2SO4—CH3OH solutions.
## 3.2.8. Total Phenolic Content (TPC), Flavonoid Content (TFC), and Saponins (TS)
The total phenol content was determined using the Folin–Ciocalteau method, according to Colonna et al. [ 13], with some modifications. The extracts were prepared using 0.1000 g of dry, raw material and 10 mL of $80\%$ methanol. In a test tube, 0.6 mL of extract, 3 mL of Folin–Ciocalteu reagent, and 2.0 mL of Na2CO3 $7.5\%$ were added. After the mixture was vortexed, it was allowed to react for 60 min in the dark. Finally, the absorbance at 765 nm was measured with a spectrophotometer (UV-2600, SHIMADZU, Tokyo, Japan) using distilled water as a blank. The content of total phenols was expressed as equivalent mg of gallic acid per g of the dry sample.
Total flavonoid content was estimated by the AlCl3 colorimetric method [47]. Briefly, 20 mg/mL of the extract was prepared using $60\%$ ethanol. The extract of 2 mL was used with 0.4 mL of a $10\%$ (p/v) aluminum trichloride (AlCl3) solution and 0.4 mL of $5\%$ sodium nitrate (NaNO2). Subsequently, the mixture was vortexed and incubated for 6 min. Then, 4 mL of NaOH ($4\%$) was added to stop the reaction. Finally, the absorbance at 510 nm was measured with a spectrophotometer (UV-2600, SHIMADZU) using $60\%$ ethanol as a blank. The total flavonoid content was expressed as equivalent mg of rutin per g of the dry sample.
Total saponins (TSs) were quantified by the colorimetric method according to Le et al. [ 17], with some modifications. The extracts were prepared using 0.1000 g of dried plant tissue and 7 mL of $70\%$ (v/v) ethanol, and sonicated at 55 °C for 40 min. In a test tube, evaporate 0.2 mL of the extract in a water bath at a temperature of 70 °C and add 0.1 mL of $5\%$ vanillin reagent and 0.4 mL of perchloric acid. The reaction was heated in a water bath at 60 °C for 15 min, and ethyl acetate (4 mL) was added for 10 min. Finally, the absorbance at 560 nm was measured with a spectrophotometer (UV-2600, SHIMADZU, Tokyo, Japan) using $70\%$ ethanol as a blank. The total saponin content was expressed as equivalent mg of oleanolic acid per g of the dry sample.
## 3.3. Metabolite Composition Identification
The metabolite components were identified using the UPLC-ESI-MS/MS method, mainly based on Chen et al. ’s study [79], with some modifications. A total of 100 mg of powder ground from each lyophilized leaf was weighed and extracted overnight at 4 °C with 0.6 mL of extracting solution. After centrifugation at 10,000× g for 10 min, the supernatant was aspirated. Samples were analyzed using a Waters ACQUITY UPLC HSS T3 C18 (1.8 μm, 2.1 mm × 100 mm) by a UPLC-ESI-MS/MS system (UPLC, Shim-pack UFLC CBM30A system, SHIMADZU; MS, 4500 Q TRAP, Applied Biosystems, Waltham, MA, USA) to analyze 4 μL samples. The mobile-phase solvent A was ultrapure water (containing $0.04\%$ acetic acid) and solvent B was acetonitrile (containing $0.04\%$ acetic acid). The column temperature was 40 °C and a gradient procedure was used for sample measurements. The effluent was alternately connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS. The ESI source operating parameters were set as follows: electrospray ion source temperature, 550 °C; mass spectrometry voltage, 5500 V; curtain gas set to 30.0 psi; and collision-activated dissociation (CAD) high. Raw files generated from UPLC-ESI-MS/MS analysis were analyzed with Analyst 1.6.3 software. Q3 was used for metabolite quantification, while Q1, Q3, RT (retention time), DP (declustering potential), and CE (collision energy) were used for metabolite identification.
## 3.4. Antioxidant Activity Evaluation
The antioxidant activity of methanolic extracts was measured in vitro and included the following assays: DPPH radical scavenging activity, ABTS+ scavenging capacity, iron ion-reducing capacity, hydroxyl radical scavenging capacity, and anti-superoxide anion capacity. DPPH radical scavenging activity, ABTS+ scavenging capacity, and ferric ion-reduction capacity refer to Jia et al. [ 80] with slight modifications. Hydroxyl radical scavenging capacity and resistance to the superoxide anion radical (O2−) test were conducted with a hydroxyl free-radical assay kit and inhibition and production superoxide anion assay kit (Nanjing Jiancheng Bioengineering Research Institute).
DPPH radical scavenging activity: 2.7 mL of DPPH methanol solution (0.1 mmol/L) was added to the methanol extract (0.3 mL), as presented in Section 3.2.8, and the reaction was monitored at 517 nm until the absorbance was constant. Measurements were repeated three times for each sample. DPPH radical scavenging capacity was expressed as the equivalent amount of ascorbic acid (vitamin C) per gram of sample.
ABTS+ scavenging capacity combined 3.8 mL of ABTS+ working solution and extract (0.2 mL) and monitored the reaction at 734 nm. The ABTS+ radical scavenging capacity was expressed as the amount of ascorbic acid (vitamin C) equivalent per gram of sample.
Iron ion-reducing capacity: 1.8 mL of TPTZ working solution (100 mL of 0.3 mol/L acetate buffer; 10 mL of 10 mmol/L TPTZ solution and 10 mL of 20 mmol/L FeCl3 solution, a mixture of the three solutions) was added to 3.1 mL of ultrapure water and 0.1 mL of the extract to be tested, and the absorbance of the mixture was measured at 593 nm. All analyses were performed in triplicate. The millimolarity of FeSO4 was expressed as its reducing power.
## 3.5. Statistical Analysis
The values of all indexes determined in the experiment were recorded in triplicate and were expressed as the mean ± standard deviation. SPSS Software (version 26.0) was used to apply these statistical tools.
## 4. Conclusions
The nutritional composition of *Gonostegia hirta* was evaluated and we concluded that it can be an important nutrient supplement, K, Ca, soluble sugars, organic acids, Asp, and omega-3 fatty acids. Moreover, the low content of potentially toxic and toxic metals (Pb, Cd, and Cr) indicated that the area from which the plant was removed was not contaminated. Additionally, *Gonostegia hirta* presented a high content of TP, TF, and TS, and contained a variety of health-promoting phytochemicals, such as rutin, caffeic acid, ferulic acid, vitamin C, vitamin E, etc, which proves that it can be an important source of natural antioxidants and has great potential to become a functional ingredient in the future. Furthermore, its methanol extract showed that it exhibited very good antioxidant abilities in DPPH, ABTS+, FRAP, hydroxyl radial scavenging capacity, and resistance to superoxide anion radical assays. In summary, a comprehensive analysis of *Gonostegia hirta* will help us to strengthen the protection and understanding of underexploited, edible, wild plants, and promote their growth, while simultaneously highlighting the interest in this edible, wild plant as a healthy dietary supplement.
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|
---
title: Untargeted Metabolomics Based Prediction of Therapeutic Potential for Apigenin
and Chrysin
authors:
- Cole Cochran
- Katelyn Martin
- Daniel Rafferty
- Jennifer Choi
- Angela Leontyev
- Akanksh Shetty
- Sonali Kurup
- Prasanth Puthanveetil
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967419
doi: 10.3390/ijms24044066
license: CC BY 4.0
---
# Untargeted Metabolomics Based Prediction of Therapeutic Potential for Apigenin and Chrysin
## Abstract
The prominent flavonoids apigenin and chrysin have been demonstrated to have systemic benefits. Our previous work was first to establish the impact of apigenin and chrysin on cellular transcriptome. In the current study, we have revealed the ability of apigenin and chrysin to alter the cellular metabolome based on our untargeted metabolomics. Based on our metabolomics data, both these structurally related flavonoids demonstrate diverging and converging properties. Apigenin demonstrated the potential to possess anti-inflammatory and vasorelaxant properties through the upregulation of intermediate metabolites of alpha-linolenic acid and linoleic acid pathways. Chrysin, on the other hand, exhibited abilities to inhibit protein and pyrimidine synthesis along with downregulation of gluconeogenesis pathways based on the altered metabolites detected. Chrysin-mediated metabolite changes are mostly due to its ability to modulate L-alanine metabolism and the urea cycle. On the other hand, both the flavonoids also demonstrated converging properties. Apigenin and chrysin were able to downregulate metabolites involved in cholesterol biosynthesis and uric acid synthesis, namely 7-dehydrocholesterol and xanthosine, respectively. This work will provide understanding regarding the diverse therapeutic potential of these naturally occurring flavonoids and help us in curbing an array of metabolic complications.
## 1. Introduction
Foods are a direct link to our environment. The global population relies mostly on naturally available foods from plant and animal sources [1,2,3]. Polyphenols are naturally occurring bioactive compounds presents in vegetables, fruits, and other plant parts that humans have been consuming for years [4,5]. In recent decades, chemists have developed strategies and tools to isolate the pure individual bioactive component from a plant part or the whole plant. This is important for understanding the physiological impact of that individual component. Apigenin and chrysin are two structurally related polyphenols belonging to the flavonoid family that are present in fruits, leaves, and vegetables [6,7]. In the available literature, the medical benefits of apigenin and chrysin are well described [4,5,6,8]. The rationale for using these agents in the available reports published to date has been more of a “pick and choose” strategy. Most of the published work has only portrayed the beneficial effects associated with apigenin and/or chrysin in the area of cardiovascular disease, cancer, or neurodegeneration [4,5,6,8]. From a pharmacological perspective, it is very crucial to remember that these natural agents are not specific ligands and could regulate an array of targets, resulting in a landscape shift in cellular signaling and function. When we consume these agents through foods, we cannot tightly control the dose. There are dose-specific and dose-dependent pharmacological and toxicological effects that are entirely unknown and need to be identified.
In our previous work, using a transcriptomic approach, we identified that both apigenin and chrysin were able to downregulate transcripts involved in the cholesterol biosynthesis pathway while promoting the ketogenic pathway [7]. In our current work using an untargeted metabolomics approach, we have corroborated our past findings, and have demonstrated that a penultimate metabolite in the cholesterol biosynthesis pathway is downregulated. Simultaneously, the compounds also exhibited some diverse features as demonstrated by the altered metabolite levels. Apigenin was able to upregulate alpha-linolenic acid and linoleic acid pathways, whereas chrysin was able to downregulate nucleic acid, and protein biosynthesis and gluconeogenesis pathways. Enhanced alpha-linolenic and linoleic acid pathways could lead improvement of cardiovascular and cerebrovascular function [9,10,11,12,13]. Apigenin could potentially serve as an ideal agent to treat cardiovascular and cerebrovascular potential due to this reason. Dysregulated transcription and translational processes contribute towards tumor progression, and inhibitors of both transcription and translation have been a major highlight in developing cancer therapeutics [14,15]. Gluconeogenesis is a major contributing factor for hyperglycemia in type 2 diabetes, and downregulators of gluconeogenesis pathways are being studied [16,17,18,19,20,21]. In our study, chrysin has demonstrated the dual potential of downregulating pathways of gluconeogenesis with transcription and translation, making it a potential therapeutic agent for treating complications associated with type 2 diabetes and cancer.
Based on our current omics-based approach, we were able to predict the potential application for these two beneficial flavonoids. Our study will not only reveal the potential benefits but also the associated risks, which could help us in the judicious use of these bioactive agents. This work will reveal a plethora of information regarding these two polyphenols and will help us in determining the therapeutic relevance of these agents along with revealing their suitability for specific indications.
## 2.1. Apigenin and Chrysin Treatment Altered the Whole Cell Metabolome in MEF Cells
The two closely related flavonoids, apigenin and chrysin (Figure 1A), altered the cellular metabolome in MEFs. Metabolites obtained from both negative and positive ion mode (ESI− and ESI+) were analyzed using principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) or orthogonal partial least squares discriminant analysis (OPLS-DA) to reveal the different metabolites formed following apigenin and chrysin treatments in comparison with the control treatment. A clear distinction was evident between the cluster of formed metabolites in the apigenin- and chrysin-treated groups in comparison with the control groups in both ESI− (Supplementary Figure S1) and ESI+ mode (Supplementary Figure S3). A volcanic plot of metabolite data sets validated the findings that apigenin and chrysin can make that clear-cut distinction in the metabolite changes. Univariate analysis of volcanic plot of metabolite sets when expressed as a log2 fold change revealed that apigenin was able to upregulate and chrysin was able to downregulate some of the major metabolite markers within the fibroblast cells, as exhibited by data sets from both negative (Supplementary Figure S2) and positive (Supplementary Figure S4) ion modes. The increase or decrease in metabolite levels, as depicted by data points in the volcanic plot, (colored) pink, is in the significant range. These data sets reveal the ability of these closely related flavonoids in regulating cellular metabolome.
## 2.2. Alpha-Linolenic Acid and Linoleic Acid Metabolism Emerged as the Major Metabolic Pathways Specifically Regulated by Apigenin
Pathway enrichment analysis of altered metabolites revealed that the alpha-linolenic and linoleic acid pathways were the prominently regulated pathways by apigenin unanimously in both negative and positive ion mode, as depicted in Figure 2 and Figure 3, respectively. The enrichment ratio, along with the p-value reached at significant levels for the metabolites, were selected. Specific analysis of metabolites belonging to these two major pathways regulated by apigenin revealed that eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid were the major ones. When comparing metabolites, the parameters were set to a limit of >±1.5 fold change (increase/decrease) as per the log2 fold change values, with a statistical significance set at $p \leq 0.05.$ Eicosapentaenoic acid levels in apigenin-treated MEFs showed a significant increase, with log2 fold change values >1.7 fold compared with control groups and even chrysin-treated groups based on the values from the negative ion mode (Figure 4A). Docosapentaenoic acid and docosahexaenoic acid exhibited only >1.3 and >1.04, respectively, as per the log2 fold change expressed in negative ion mode in comparison with both control and chrysin treatment groups (Figure 4B,C) and did not fulfill the selection criteria. For metabolites in the linoleic acid pathway, the metabolites that appeared in the list were arachidonic acid and adrenic acid. The changes in arachidonic levels were statistically significant ($p \leq 0.05$) but the log2 fold change did not reach 1.5 fold, rather it was a 0.671 fold increase (Figure 5A). Interestingly, adrenic acid reached a > 2.88 log2 fold change (increase) along with the statistical significance ($p \leq 0.05$) compared with both the control and chrysin-treated groups (Figure 5B). The original peak values for the metabolites are available as upper inserts in these figures.
## 2.3. Alanine Metabolism and Urea Cycle Are the Major Metabolic Pathways Specifically Controlled by Chrysin
The metabolite sets that emerged as the top regulated ones by chrysin in negative (Figure 6) and positive (Figure 7), as revealed by pathway enrichment analysis, were the urea cycle and alanine metabolism, respectively. L-Alanine metabolism is tissue specifically regulated. In non-hepatic cells, such as in MEFs, L-alanine can be formed from pyruvate via glucose or lactate sources (Figure 8A). The formed L-alanine either can be released into the circulation, which can be taken up by the liver for the process of gluconeogenesis, or can be used for the synthesis of proteins. It can also serve as an amino acid source for ATP generation in normal tissues and also in cancerous tissues. When measured, L-alanine levels decreased >1.7 fold (−1.78) as expressed by the log2 fold change with the statistical significance in comparison with the control and apigenin-treated MEFs (Figure 8B). We also analyzed the levels of pyruvate and lactate. Pyruvate expressed in the protonated form as pyruvic acid did not reach the cut-off criteria (< or >1.5 fold), but rather only demonstrated a 0.815-fold decrease (Figure 8C). Unlike pyruvic acid, lactic acid levels demonstrated >2.09 fold decrease (−2.09) as expressed by log2 fold change levels in comparison with the control and apigenin-treated groups (Figure 8D). The levels of L-alanine, pyruvic acid, and lactic acid correlated well, demonstrating the channelization of this metabolic pathway. Regarding the urea cycle, the intermediates within the urea cycle, L-arginine and D-ornithine, did not exhibit major change compared with the control or apigenin-treated groups (Figure 9B,C). A major precursor or substrate provider for the urea cycle is carbamoyl phosphate, which has two major fates—either helping in the formation of citrulline or taking an alternative path, forming orotidine, as shown in Figure 9A. Carbamoyl phosphate is formed from N-acetyl glutamate in the presence of carbon dioxide, ammonium ion, and ATP. N-acetyl glutamate is formed by the combination of glutamate and acetyl coA (Figure 9A). In the absence of any change in the metabolites/substrates of urea cycle, we measured the levels of orotidine, N-acetyl glutamic acid, and glutamic acid; the protonated forms of N-acetyl glutamate and glutamate were the ones that appeared in the metabolite list. Interestingly, there was over a 2.457 fold level decrease in orotidine (>−2.457 fold, Figure 9D), which correlated well with over a 1.52 decrease (>−1.52 fold, Figure 9E) for N-acetyl glutamine and over a 2.30 fold decrease (>−2.30 fold, Figure 9F) for L-glutamic acid, which are the upstream metabolites of orotidine as expressed by log2 fold change values. Orotidine is a major precursor for pyrimidine synthesis and is known to generate pyrimidine bases. In our metabolite list the downstream metabolite of orotidine and a pyrimidine base, uracil, demonstrated a significant change, with a log2 fold change over −2.675 (Supplementary Figure S7). The nucleotide form of uracil and cytosine, uridine monophosphate and cytidine monophosphate, also demonstrated significant changes with log2 fold change values of >−2.17 and >−1.89, respectively (decrease) (Supplementary Figure S8).
The peak/raw values for the metabolites belonging to different groups are represented as upper inserts in each figure.
## 2.4. Apigenin and Chrysin Demonstrated Similarity in Downregulating Metabolites Involved in Cholesterol and Uric Acid Biosynthesis Pathways
Along with the divergent properties demonstrated by both flavonoids, apigenin and chrysin, in regulating specific metabolites, they both also exhibited some commonality. Major metabolites that were regulated in a similar manner by both apigenin and chrysin were 7-dehydrocholesterol and xanthosine. Both 7-dehydrocholesterol and xanthosine are the major intermediate substrates/metabolites in cholesterol and uric acid biosynthesis pathways. 7-Dehydrocholesterol demonstrated over a 1.618 fold (>−1.618) and 2.605 fold (>−2.605) decrease as expressed by the log2 fold change values for apigenin and chrysin, respectively (Figure 10A). Xanthosine demonstrated a decrease of over 2.23 fold (>−2.23) and over 5.963 fold (>−5.963) for apigenin and chrysin, respectively, as expressed by the log2 fold change values (Figure 10B). The original peak values for the metabolites are expressed as upper inserts inside the figures.
## 3. Discussion
There is not much known about the impact of apigenin and chrysin on the cellular metabolome. Rather than directly advocating for the natural compounds of interest in treating a specific disease, it is important to understand in depth the overall impact of using these flavonoids at the cellular level. Our previous work demonstrated the influence of apigenin and chrysin at the cellular transcriptome level [7]. Current work has furthered the information by revealing the impact these compounds have on the cellular metabolome. Along with their ability to turn on or off certain transcripts, as demonstrated by our previous work, this study with the application of untargeted metabolomics revealed their ability to change the metabolite levels inside the cell. The data have revealed an in-depth knowledge regarding how these compounds could influence cellular function by altering various metabolic pathways. In addition, it is crucial to consider the pros and cons for these agents before we advocate them for specific conditions. Apigenin and chrysin are structurally similar and related flavonoids but differ in chemical structure by having one 4-hydroxyl group in the 2-phenyl for apigenin compared with chrysin as, described in Figure 1.
Even with a difference of just one hydroxyl group (Figure 1), there is a major divergence in the metabolic properties possessed and the metabolites regulated by these two compounds (Supplementary Figure S5). Interestingly, in both negative and positive ion mode metabolite detection, the alpha-linolenic acid and linoleic acid metabolic pathways are the crucial ones regulated by apigenin in a significant manner, with a high enrichment ratio (Figure 2 and Figure 3). This was a notable observation not only against the control group but also against the chrysin-treated groups (Supplementary Figure S6). Based on these observations we could deduce that apigenin could be an ideal agent for activating the alpha-linolenic acid and linoleic acid pathways. The protective role of alpha-linolenic acid and linoleic acid in cardiovascular diseases and neurodegenerative diseases is well established but we have rarely perceived agents that can channelize the intracellular lipid metabolism [22,23,24,25,26,27,28,29,30]. Among the metabolites regulated in these pathways, EPA, DPA, and DHA demonstrated changes, but only EPA levels were significant with a >1.5 fold change as expressed by log2 FC values. EPA levels increased >1.7 fold, whereas DPA and DHA levels only increased > 1.3 and >1.04 fold, respectively. It is a clinically proven fact based on data from numerous studies that a prolonged DHA increase could enhance the LDL-cholesterol (which is considered the bad cholesterol) levels in subjects [31,32]. In contrast, EPA provision is known to decrease the total cholesterol and triglyceride concentrations and improve cardiovascular health. In recent years, the only EPA-containing FDA-approved drug (Vascepa) has demonstrated incredible cardiovascular benefits, which reaffirms this claim [33,34]. The uniqueness about our findings is that apigenin can trigger the biochemical pathways involving the alpha-linolenic acid pathway, leading to more EPA than any other metabolites, which could be protective not only for the cardiovascular system but also for systemic health. The other metabolic pathway top regulated by apigenin is the linoleic acid pathway, as per our findings. In this pathway, both arachidonic acid and adrenic acid were upregulated, but adrenic acid was the only metabolite that demonstrated a log2 FC of > 1.5 (> 2.88) in comparison with arachidonic acid, which also changed > 0.671 (log2 FC). Adrenic acid is also known as 7,10,13,16-docosatetraenoic acid, which is an omega (ώ)-6 polyunsaturated fatty acid [35]. The protective roles for adrenic acid include endothelial-derived relaxation factor, as demonstrated in the bovine coronary artery model and adrenal cortical arteries, and as an anti-inflammatory agent inhibiting leukotriene synthesis (LTB4) in neutrophils using the murine model of peritonitis and arthritis [35,36,37]. Apigenin, by enhancing endogenous adrenic levels without significantly elevating arachidonic acid, could potentially enhance vasorelaxant and anti-inflammatory effects in cardiovascular and other systems but it needs further testing in vivo. These findings for the first time provide a clear insight into the multiple protective signaling networks turned on by the apigenin-mediated major metabolites EPA and adrenic acid.
With regard to chrysin, L-alanine metabolism was the most regulated pathway in negative ion mode and the urea cycle in positive ion mode. Hepatic tissue assimilates alanine secreted by other tissues into the circulation and converts it into glucose through the process of gluconeogenesis and make use of excess alanine as the raw material for the synthesis of proteins [38,39,40]. When there is an upregulation of L-alanine metabolism, it could potentially lead to enhanced gluconeogenesis, as seen during insulin resistance, cancer [39,41], and diabetes [41,42,43]. In addition, excess protein biosynthesis is another hallmark of metabolic syndrome and cancer [42,43]. By curbing L-alanine provision to the liver, we could limit the upregulation of gluconeogenesis and the trigger to synthesis excess proteins by the liver, therefore reducing hepatic stress. These phenomena (excess gluconeogenesis and excess protein synthesis) are very prevalent in insulin resistance, diabetes, and cancer. By curbing these pathways, we could potentially limit metabolic complications associated with diabetes and cancer. Besides L-alanine, the other top major metabolic pathway regulated by chrysin in positive ion mode was the urea cycle. Interestingly, as mentioned in our results section, no significant changes were noted in the levels of intermediate metabolites in the urea cycle, which came up in our analyte list, arginine and ornithine. An alternative fate for carbamoyl phosphate, the precursor for intermediates in the urea cycle, is to form orotidine, which is a known precursor for pyrimidine nucleotides [44,45]. Most malignancies have been associated with excess pyrimidine nucleotide synthesis, and inhibiting this biochemical process has been considered a major strategy to combat malignancies [46,47,48]. Both orotidine and its predecessor, N-acetyl glutamate, have been demonstrated to be downregulated by chrysin treatment not only in comparison with the control group but even with the apigenin-treated groups. We also evaluated the levels of downstream metabolites of orotidine, the pyrimidine base, uracil (Supplementary Figure S7), and its nucleotide form, uridine monophosphate, along with another pyrimidine nucleotide analog, cytidine monophosphate (Supplementary Figure S8). These downstream effects confirm chrysin’s ability to regulate pyrimidine biosynthesis. The unique ability of chrysin to downregulate orotidine, a pyrimidine precursor, demarcates it from its flavonoid counterpart in the treatment of cancer and associated complications. By influencing both L-alanine- and orotidine-mediated pyrimidine nucleotide synthesis pathways, chrysin emerges as an ideal candidate that could curb gluconeogenesis, and prevent excess protein and pyrimidine synthesis, as seen with cancer [42,47,48].
Even with the existing divergence, we have observed some converging features in these structurally related flavonoids. Our previous work, based on transcriptomic analysis, was the first to show that both apigenin and chrysin possess hypocholesterolemic properties by downregulating multiple enzymes in the mevalonate pathway [7]. In the current work, we observed consolidating evidence that both apigenin and chrysin were able to downregulate 7-dehydrocholesterol, the penultimate metabolite in the cholesterol biosynthesis pathway. Based on the observed results, chrysin was able to downregulate in a robust manner, even compared with apigenin (−2.6 vs. −1.6). Interestingly, another novel target that was downregulated by both apigenin and chrysin was xanthosine (−2.23 and −5.9) in comparison with the control. Both cholesterol and uric-acid accumulation has been reported to be an initiator of metabolic complications in cardiovascular pathologies and cancer [49,50,51]. Uric acid is also the biochemical end product of purine metabolism, which is elevated during both cancer and cardiovascular complications [52,53]. Agents to lower hypocholesterolemia have been considered a major therapeutic strategy for treating cardiovascular complications and have been studied for over a decade [54,55]. Recently, NIH-funded clinical trials—the Colchicine Cardiovascular Outcomes Trial (COLCOT) and Low-Dose Colchicine (LoDoCo) —have brought to light the significance of inhibiting uric acid using colchicine following cardiac ischemic conditions [56,57]. Apigenin and chrysin, with their ability to simultaneously inhibit cholesterol and uric acid, could serve as ideal agents to curb metabolic complications found during cancer and cardiovascular diseases (Figure 11).
## 4.1. Cell Culture and Treatments
Mouse embryonic fibroblasts (MEFs) purchased from Lonza, Inc. (Walkersville MD, USA) with Cat#M-FB-481 were employed for our experiments. Healthy passages from 2 to 5 were used for the different treatment groups. The cells were cultured and passaged in Dulbecco’s modification of Eagle’s Medium (DMEM) (Corning®, USA, Manassas, VA). DMEM comprising high glucose (4.5 g/L) was filtered along with $10\%$ fetal bovine serum (FBS00), 500 mL, USDA-Origin, Neuromics, MN, USA, and $1.5\%$ penicillin/streptomycin and amphotericin from VWR, Avantor, USA. During treatment, the serum-containing medium was replaced with a serum-free 1g/L glucose-containing (DMEM) medium supplied with only $1.5\%$ penicillin/streptomycin and amphotericin. The cells were subjected to only serum-free 1g/L glucose containing (DMEM) medium (controls) or incubated with 25 μM apigenin in 1 g/l glucose containing DMEM or 25 μM chrysin in 1 g/L glucose containing DMEM for 24 h before they were pelleted, and shipped at freezing temperatures using dry ice to perform untargeted metabolomics. Each group had $$n = 3$$ replicates.
## 4.2. Sample Preparation
The untargeted metabolomics service was performed at our outsourcing facility (Creative Proteomics, NY, USA). In brief, the shipped cell pellets were thawed, and 80–$85\%$ methanol was added to cover the pellets (750–1000 µL). These sample sets were subjected to ultrasound-based extraction at a steady temperature set at 4 °C for approximately 30 min. Following ultrasound exposure, samples were kept at −40 °C for at least an hour. After the cold exposure, samples were removed, vortexed well for 30 s, and then centrifuged at a speed of over 12000 rpm at 4 °C for at least 12–15 min. A clear supernatant from the top layer of approximately 200µL and DL-O-Chloro-phenylalanine at a concentration of 140 μg/mL made into 2–5 µL was transferred to a vial for LC-MS analysis.
## 4.3. Chemical Structures
The chemical structures with the IUPAC names were generated using the software ChemDraw Prime v19.1 from Perkin Elmer.
## 4.4. UPLC-TOF-MS Technology
Ultra performance liquid chromatography (UPLC) with time-of-flight mass spectrometry (ESI-TOF-MS) was performed at our outsourcing facility by a well-established method [58,59]. In brief, the sample separation was performed using UltiMate 3000LC combined with Q Exactive mass spectrometry (Thermo) followed by screening with ESI-MS. The LC system is a combination of a two-system unit with Thermo hyper gold C18 (100×2.1mm 1.9 μm) combined with the UltiMate 3000LC system. The mobile phase comprises two solvents—solvent A and solvent B. Solvent A comprises $0.1\%$ formic acid, $5\%$ acetonitrile, and water, and solvent B is a mixture of $0.1\%$ formic acid and acetonitrile with a gradient elution of 0–1.5 min, 0–$20\%$ B; 1.5–9.5 min, 20–$100\%$ B; 9.5–14.5 min, $100\%$ B; 14.5–14.6 min, 100–$0\%$ B; 14.6–18.0 min, $0\%$ B. The flow rate for the mobile phase was fixed at 0.3 mL/min. The column temperature was maintained at 40°C, and the sample manager temperature was set at 4 °C. Mass spectrometry parameters in ESI+ and ESI- modes were set. For positive ion mode (ESI+), the experimental parameters were the following: heater temperature set at 300 °C, flow rate of the sheath gas set at 45 arb, auxiliary gas flow rate set at 15 arb, sweep gas flow rate set at 1 arb with a spray voltage of 3.0 kV, capillary temperature set at 350 °C, and the S-Lens RF level adjusted to $30\%$.
## 4.5. Statistical Analysis
The analysis was performed using a well-established previously published statistical method [59,60]. Following the acquisition of the raw data, these data are aligned with the aid of Compound Discover using the 3.0 system from Thermo based on their m/z ratio and the retention times of ion signals. The emerging ions from both the positive (ESI+) and negative (ESI-) ion modes are fused before importing into the SIMCA-P program (version 14.1) for multivariate analysis. A preliminary unsupervised method is employed for principal components analysis (PCA) for visualization of data and for the identification of outliers. The data sets are then subjected to a supervised version of regression modeling using partial least squares discriminant analysis (PLS-DA) or orthogonal partial least squares discriminant analysis (OPLS-DA) to identify the target metabolites. The filtered-out metabolites are confirmed by combining the obtained results with those of variable importance in projection (VIP) values. The VIP values > 1.5 and p values < 0.05 based on the t-test are taken into consideration. The quality of data fit is then explained with the help of R2 and Q2 values. R2 indicates the variance and denotes the quality of the fit explained in the model. Q2 indicates the variance in the data with the model’s predictability.
From the obtained raw values from three replicates for each group, average values were calculated, and then fold change and log2 fold change were calculated. A log2 fold change of > +/−1.5 with a statistical significance as indicated by $p \leq 0.05$ was considered as a significant change. The calculated values were analyzed using GraphPad Prism software to evaluate the statistical significance of the test and difference between groups and plotted.
## 5. Conclusions
To conclude, our work based on an untargeted metabolomics approach reveals the unique properties of two closely related flavonoids. Currently we do not have much information on how these agents act at the cellular level, dissecting their effects on the cellular metabolome. This work will lay the foundation for future studies involving apigenin and chrysin in understanding the pharmacological properties and specific influence of these agents on the cellular metabolic landscape. As far as the limitations of this study are concerned, our predictions are based on untargeted metabolomics from an in vitro model system, and the predictions on the systemic effects are based on extrapolations. We recommend that this work should be followed up with studies involving in vivo model systems to identify the correct dose and toxicity when treating metabolic complications associated with cardiovascular disease or cancer. Both apigenin and chrysin have demonstrated high potential to emerge as therapeutic agents that can help in curbing metabolic diseases with feasibility, and with predictable and minimal adverse effects.
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|
---
title: Activation of MyD88-Dependent TLR Signaling Modulates Immune Response of the
Mouse Heart during Pasteurella multocida Infection
authors:
- Qiaoyu Fu
- Junming Jiang
- Xubo Li
- Zhe Zhai
- Xuemei Wang
- Chongrui Li
- Qiaoling Chen
- Churiga Man
- Li Du
- Fengyang Wang
- Si Chen
journal: Microorganisms
year: 2023
pmcid: PMC9967429
doi: 10.3390/microorganisms11020400
license: CC BY 4.0
---
# Activation of MyD88-Dependent TLR Signaling Modulates Immune Response of the Mouse Heart during Pasteurella multocida Infection
## Abstract
Pasteurella multocida (P. multocida) is an important zoonotic pathogen. In addition to lung lesions, necropsies have revealed macroscopic lesions in the heart in clinical cases. However, most previous studies focused on lung lesions while ignoring heart lesions. Therefore, to investigate the immune response of the P. multocida-infected heart, two murine infection models were established by using P. multocida serotype A (Pm HN02) and D (Pm HN01) strains. Histopathological examination revealed heterogeneous inflammatory responses, including immune cell infiltration in the epicardial and myocardial areas of the heart. Transcriptome sequencing was performed on infected cardiac tissues. To explore the traits of immune responses, we performed the functional enrichment analysis of differentially expressed genes, gene set enrichment analysis and gene set variation analysis. The results showed that the innate immune pathways were significantly regulated in both groups, including the NOD-like receptor signaling pathway, the complement and coagulation cascade and cytokine–cytokine receptor interaction. The Toll-like receptor signaling pathway was only significantly activated in the Pm HN02 group. For the Pm HN02 group, immunohistochemistry analysis further verified the significant upregulation of the hub component MyD88 at the protein level. In conclusion, this study reveals critical pathways for host heart recognition and defense against P. multocida serotypes A and D. Moreover, MyD88 was upregulated by P. multocida serotype A in the heart, providing a theoretical basis for future prevention, diagnosis and treatment research.
## 1. Introduction
The Hainan black goat is an indigenous goat that evolved under tropical climatic conditions of high humidity and temperature [1]. It is also an economically important livestock species for local animal husbandry. Goat hemorrhagic septicemia (HS) is an acutely fatal infectious disease resulting from *Pasteurella multocida* (P. multocida) [2], causing serious economic losses in many countries. Based on its capsular antigen, P. multocida is grouped into five serotypes: A, B, D, E and F [3]. Goats are the preferred hosts for P. multocida serotype A and D strains [4]. The capsular antigen of serotype A, mainly composed of hyaluronic acid, promotes the colonization of P. multocida in the mucosa of the lower respiratory tract [5]. Thus, the P. multocida strain of serotype A usually causes respiratory diseases. The main component of the serotype D capsule is heparosan [6]. The P. multocida strain of serotype D is usually associated with HS and pneumonia [7]. Our previous study demonstrated that P. multocida strains of serotypes A (Pm HN02) and D (Pm HN01) led to different cellular morphologies in goat bronchial epithelial cells [8]. Whether the host immune responses induced by these two strains are different has not been reported.
Ordinarily, P. multocida results in pneumonia and HS [9]. There are many studies regarding the lung [10,11] but fewer about the heart, despite reports of heart lesions caused by P. multocida [12]. Weise et al. demonstrated that P. multocida toxin aggravated cardiac hypertrophy and fibrosis in mice [13]. Clinically, cardiac damage caused by P. multocida also includes hemorrhages in subepicardial and subserosal areas [14], endocarditis [15], chronic fibrous pericarditis [16] and congestion with hemorrhages in necropsy hearts [17,18]. Moreover, Pors, Susanne E. detected and cultivated P. multocida from the pericardial sacs of 40 pigs [16]. The P. multocida burden was detected in mice heart after 12 h of P. multocida infection [19]. Bacterial virulence factors (LPS, etc.) are known to induce cardiac inflammation and myocardial cell death [20]. In conclusion, P. multocida invades the heart and causes pathological changes. We therefore focus on the immune mechanisms behind pathological changes in the heart caused by Pm HN01 and Pm HN02.
Previous study indicated that the mouse, being highly sensitive and susceptible to P. multocida, could serve as a useful model for pathogenesis studies, such as challenge studies, including for the development of vaccines against HS [21]. Therefore, we conducted subsequent in vivo experiments in mice infected with P. multocida. In order to systematically evaluate the pathological damage to the heart caused by the two strains and explore the immune response during the infection, Pm HN01 and Pm HN02 strains preserved in our laboratory were used to construct models of P. multocida infection by intraperitoneal injection. Firstly, a histopathological examination of heart tissues was performed. Subsequently, the analysis of transcriptome sequencing data was used to explore the immune response of mouse heart tissues. Additionally, functional enrichment analyses were performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Finally, quantitative real-time PCR (RT-qPCR) was performed to check the expression of 10 immune-related differentially expressed genes (DEGs). One of the hub genes, myeloid differentiation factor 88 (Myd88), was identified by immunohistochemistry (IHC) staining at the protein level. This paper reveals the critical pathways of host heart recognition and defense against P. multocida serotypes A and D. These pathways and genes provide potential targets for therapeutic interventions of Pasteurellosis.
## 2.1. Animals
A total of 24 eight-week-old, specific-pathogen-free (SPF), male KM mice (weight: 36 ± 2 g) were purchased from HUNAN SJA LABORATORY ANIMAL CO., LTD (Hunan, China). The mice were fed sterilized food and water for 3 days and were randomly divided into 3 groups: the control group (control group, $$n = 9$$), the infected group challenged with Pm HN01 (Pm HN01 group, $$n = 6$$) and the infected group challenged with Pm HN02 (Pm HN02 group, $$n = 9$$). Of the 24 mice, 9 mice (3 in each group) were examined using histological staining, another 9 mice (3 in each group) were used for transcriptome sequencing, and the remaining 6 mice (3 in the control group and 3 in the Pm HN02 group) were used for immunohistochemistry staining. Accordingly, there were 3 biological replicates for each experiment.
## 2.2. P. multocida Challenge Experiments
The bacterial strains used in this study were previously isolated in our laboratory. Specifically, Pm HN01 (GenBank Accession No. Cp037861.1) and Pm HN02 (GenBank Accession No. Cp037865.1) were isolated from lung tissues of a Hainan black goat and a sheep, respectively. The bacterial strains were routinely cultured in tryptic soy broth (Hopebio, Qingdao, China) containing $5\%$ (v/v) newborn bovine serum (Sijiqing, Beijing, China). According to our previous research, the challenge doses for each mouse in the Pm HN01 and Pm HN02 groups were 1.58 × 106 Colony-Forming Units (CFU) and 1.58 × 107 CFU at 100 µL by intraperitoneal injection, with an equal volume of sterile phosphate-buffered saline (PBS) for the control group. Moribund mice were immediately euthanized by cervical dislocation. The heart tissues were collected and stored in liquid nitrogen for RNA extraction to perform transcriptome sequencing or in $4\%$ paraformaldehyde for the other two experiment.
## 2.3. Histopathological Examination
Hematoxylin and eosin (HE) staining was conducted according to routine protocols [22]. Briefly, paraffin-embedded hearts were cut into 4 μm thick sections using LEICA RM2016 (LEICA, Wetzlar, Germany). Next, sections were dewaxed in xylene, dehydrated using gradient alcohol and stained by the HE dye solution set (Servicebio, Wuhan, China). Finally, the tissue was sealed with neutral gum (SCRC, Shanghai, China) and directly observed with a microscope (Nikon, Tokyo, Japan).
## 2.4. RNA Extraction and Transcriptome Sequencing
Total RNA was extracted from heart tissues using the TRIzol (TIANGEN, Beijing, China). Subsequently, the RNA concentration and purity were determined by NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA). The integrity of RNA was assessed using the RNA Nano 6000 Assay Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). According to the manufacturer’s procedure, the sequencing library was generated using the NEBNext UltraTM RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA) and evaluated for library quality on the Agilent Bioanalyzer 2100 system. The libraries were sequenced on the Illumina platform. The raw data were filtered to obtain clean data. HISAT2 (Version 2.0) was used to map the reference genome (GenBank Assembly ID: GCA_000001635.8). Fragments Per Kilobase of transcript per Million fragments mapped (FPKM) reads were used to quantify gene expression levels obtained using StringTie (Version 1.3.0). The repeatability among samples was evaluated by Spearman’s correlation coefficient.
## 2.5. Bioinformatics Analysis of Sequence Data
Deseq2 was used to analyze DEGs by Fold Change (FC) and p value between the infected group and the control group. The screening conditions were |log2 FC| ≥ 1.5 and $p \leq 0.05.$ The DEGs were analyzed using DiVenn software [23] (Version 2.0), GO and KEGG databases. Additionally, the KEGG database was predefined as the background gene set. GSEA [24] was used for all expressed genes to evaluate the expression of pathways. Thresholds of $p \leq 0.05$, False Discovery Rate < 0.25 and | Normalized Enrichment Score | > 1 were the screening criteria. Subsequently, GSVA [25] was used to further screen immune pathways with significant expression differences according to the threshold of |FC| > 1.
## 2.6. Quantitative Real-Time PCR
Based on the transcriptome data, ten immune- and inflammation-related DEGs were selected for RT-qPCR verification. Specific primers were designed according to the reference sequences in Genebank with Primer (Version 5.0), and the primer sequences are listed in Supplementary Table S1. The total RNA was reverse-transcribed into cDNA using FastKing gDNA Dispelling RT SuperMix (TIANGEN, Beijing, China). RT-qPCR was performed on QuantStudio™ 6 Flex (ABI, Los Angeles, CA, USA) with SuperReal PreMix Plus (SYBR Green) (TIANGEN, Beijing, China). Relative expression analysis was performed using the formula 2−ΔΔCt [ΔΔCt = (Ct of the target gene – Ct of the β-actin gene) in the treatment group – (Ct of the target gene – Ct of the β-actin gene) in the control group].
## 2.7. Immunohistochemistry Staining
Immunohistochemistry staining was conducted using 4 μm paraffin-embedded heart tissue ($$n = 6$$) sections. The primary antibodies against MyD88 (GB11269, Wuhan Servicebio Biotechnology Co., Ltd., Wuhan, China) were diluted 1:400 and then incubated at 4 °C overnight in a humidified container. After three washes with PBS, we added horseradish peroxidase (HRP)-labeled Goat Anti-Rabbit IgG (GB23303, Wuhan Servicebio Biotechnology Co., Ltd., Wuhan, China), which was diluted 1:200 and incubated at room temperature for 50 min. After three more washings with PBS, a chromogenic solution was added, and chromogenesis was terminated with tap water. Nuclei were then stained with hematoxylin. Finally, the slices were dehydrated and sealed, and the results were interpreted under a white-light microscope. Twelve fields of view were randomly selected from 400-fold fields (Supplementary Figure S2). The quantification of staining intensity was analyzed using the Image Pro Plus software (Version 6.0).
## 2.8. Statistical Analysis
All data are depicted as means ± SEM, and error bars in graphs indicate SEM. Results are representative of three independent experiments. Statistical significance was analyzed using using two-tailed unpaired Student’s t-test in GraphPad Prism (Version 8.0).
## 3.1. Pm HN01 and Pm HN02 Cause Different Pathological Changes in the Heart
The histopathological examination was performed to evaluate the effect of P. multocida infection on the murine heart. In the control group, cardiomyocytes were neatly arranged (Figure 1A). The nuclei were oval in shape and centrally located. Neither tissue degeneration nor inflammatory cell infiltration was observed. In the Pm HN01 group, myocardial hyperemia can be seen. Myocardial fibers were disorderly arranged, and the intercellular space was widened. The heart tissue showed extensive degeneration and necrosis. Inflammatory cells were aggregated under the epicardium. Multiple focal inflammatory cell aggregates were observed in the myocardium (Figure 1B). As for the Pm HN02 group, myocardial hyperemia and myocardial disarray were evident. The intercellular space was slightly widened. Additionally, mild degeneration and necrosis were observed in the tissue, and inflammatory cell infiltrates were scattered in the myocardium (Figure 1C). In contrast, mice challenged with Pm HN01 presented more serious pathological damage.
## 3.2. Pm HN01 and Pm HN02 Induce Unique and Common DEGs
Because of the immune cells observed in the histopathological examination, we intended to explore the immune pathways therein. Hence, transcriptome sequencing was performed on the murine heart. The quality of sequencing data was assessed. The transcript abundance was estimated based on FPKM, and all samples showed more upregulated transcripts than downregulated transcripts (Supplementary Figure S1A). The Spearman correlation matrix analysis of all nine samples showed that the measurements in each group were highly consistent and reproducible (Supplement Figure S1B). DEGs were screened from transcriptome sequencing data to further determine the effect of P. multocida on host cardiac tissues.
The results of DEG analysis in DiVenn software identified 2243 common DEGs in the differential expression gene sets of the Pm HN01 and Pm HN02 groups (Figure 2). Among them, the number of upregulated and downregulated genes was 1242 and 998, respectively. Additionally, the expression of these genes in both groups showed similar tendencies. These results indicated that the host response to Pm HN01 exhibited certain similarities to that to Pm HN02. In addition, the Pm HN01 group had 1107 unique DEGs, while the Pm HN02 group had 849. These unique DEGs imply the specificity of the two strains to the host.
## 3.3. Common DEGs Regulated by Pm HN01 and Pm HN02 Are Mainly Related to Innate Immunity
To explore the interactions between the host and the two different P. multocida, GO enrichment analysis was implemented on the common DEGs in the Pm HN02 and Pm HN01 groups (Figure 3A). In the biological process (BP) category, DEGs were mainly enriched in the regulation of biological process and regulation of response to stimulus (Figure 3B). In the molecular function (MF) category, binding was the most significant function, such as protein binding and cell adhesion molecule binding (Figure 3C). In the cellular component (CC) category, the intracellular part was the top GO term (Figure 3D). The DEGs were further annotated from the KEGG database to assess the critical signaling pathways (Figure 4). A total of 2709 DEGs were enriched in KEGG pathways involved in metabolism (global and overview maps), environmental information processing (signal transduction), organismal systems (immune system) and human diseases (infectious diseases) (Figure 4A). The top 20 KEGG pathways were mainly enriched in immune-related pathways, such as the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway, the complement and coagulation cascade and cytokine–cytokine receptor interaction (Figure 4B).
## 3.4. Unique DEGs Caused by Pm HN01 and Pm HN02 Are Functionally Distinct
Unique DEGs from the Pm HN01 and Pm HN02 groups were selected according to the DiVenn analysis (Figure 2) for GO and KEGG analyses (Figure 5). Unique DEGs in the Pm HN01 group were annotated to 58 GO terms, including 27 BPs, 13 CCs and 17 MFs. Comparatively, unique DEGs in the Pm HN02 group were annotated to 53 GO terms, including 26 BPs, 11 CCs and 15 MFs. Subsequently, the top 20 GO terms were screened for further analysis based on the p values. The results showed that unique DEGs in the Pm HN01 group were mainly enriched in protein binding (Figure 5A), while cytoplasm was the most significant GO term in the Pm HN02 group (Figure 5B).
This study focused on the immune-related pathways enriched in KEGG. Among them, unique DEGs in the Pm HN01 group were mostly enriched in the mitogen-activated protein kinase (MAPK) signaling pathway, followed by the chemokine signaling pathway (Figure 5C). The unique DEGs in the Pm HN02 group were mostly enriched in endocytosis, adherens junction, bacterial invasion of epithelial cells and the Toll-like receptor signaling pathway (Figure 5D). Therefore, it was speculated that the differences between the pathogenesis of Pm HN01 and Pm HN02 were related to these signaling pathways.
## 3.5. Toll-like Receptor Signaling Pathway Significantly Activated by Pm HN02
GSEA is a powerful analytical method that focuses on gene sets, which share common biological functions, chromosomal locations or regulatory mechanisms. The results of GSEA (Figure 6A,B) revealed that all genes in the Pm HN01 group were enriched in 316 pathways, while those in the Pm HN02 group were enriched in 314 pathways that were also in the Pm HN01 group. Among them, 16 immune-related pathways were found in the DEG enrichment analysis. They were the NOD-like receptor signaling pathway, cell adhesion molecules, MAPK signaling pathway, Nuclear Factor κB (NF-κB) signaling pathway, phagosome, Janus kinases (JAK) and signal transducers and activators of transcription (STAT) pathways (JAK-STAT) signaling pathway, Tumor Necrosis Factor (TNF) signaling pathway, chemokine signaling pathway, Toll-like receptor signaling pathway, complement and coagulation cascades, Interleukin (IL)-17 signaling pathway, cytokine–cytokine receptor interaction, leukocyte transendothelial migration, B-cell receptor signaling pathway, ferroptosis and C-type lectin receptor signaling pathway. Meanwhile, these pathways were activated in both the Pm HN01 and Pm HN02 groups.
GSVA is a method that builds on GSEA and is better than GSEA for characterizing pathways from the data obtained. GSVA can be used to compare differences in pathways between control and infected groups to better determine the activity of each pathway. According to the results of GSVA, the pathways shared by the Pm HN01 and Pm HN02 groups were the NOD-like receptor signaling pathway, the complement and coagulation cascade and cytokine–cytokine receptor interaction. Although there was no marked activation of the Toll-like receptor signaling pathway in the Pm HN01 group, it was significantly activated in the Pm HN02 group (Figure 7A,B).
## 3.6. Pm HN02 Induced the Activation of Myd88 at Transcription and Protein Levels
Five DEGs (Junb, Iigp1, Gadd45g, C3 and Il4ra) in common pathways, including the TNF and MAPK signaling pathway, the complement and coagulation cascade and cytokine–cytokine receptor interaction, were verified by RT-qPCR to check the accuracy of the transcriptome sequencing results. RT-qPCR verification demonstrated consistent results with RNA-seq (Figure 8). Due to the different activation statuses of the Toll-like receptor signaling pathway in the two challenge groups, we selected a hub gene (Myd88) and other related DEGs in the pathway to determine their expression trends at the transcriptional level. All of the selected genes showed upregulation in RT-qPCR and RNA-seq. Moreover, the MyD88 signal was detected in the cytoplasm by immunohistochemistry (Figure 9A). We found that the levels of Myd88 in the hearts of Pm HN02-infected mice were significantly higher than that in control mice (Figure 9B).
## 4. Discussion
Previous reports indicated that P. multocida led to pathological changes in cardiac inflammation in heart tissue. Nevertheless, little is known about the interaction between the host heart and P. multocida. As previously reported, the mouse is a useful animal model for studying P. multocida infection [26,27,28]. We constructed the murine infection model via intraperitoneal injection [29] of Pm HN01 and Pm HN02 strains to explore the immune response in the heart. In order to study the host’s recognition and defense against these two different serotype strains, the two strains were required to maintain the same lethal effect, so different challenge doses were selected for the two strains based on Lethal Dose 50. In this study, P. multocida-infected mice showed similar clinical symptoms to those of P. multocida-infected Hainan black goats, such as appetite loss, messy fur and depression [30]. Additionally, it showed heterogeneous myocardial damage and myocardial congestion. The histopathological examination revealed the infiltration of immune cells, including monocytes and lymphocytes, in epicardial and myocardial areas. However, the immune responses induced by cardiac injury are still largely unknown. Therefore, we analyzed the immune DEGs and signaling pathways to preliminarily characterize the changes at the transcript level and the similarities and differences in host immune responses to the two strains.
In bacterial myocarditis, numerous immune cells play critical roles [30], such as neutrophils, lymphocytes and macrophages [31]. In the present study, macrophages were detected by histopathological examination. Meanwhile, the expression of genetic markers of macrophages (Cd14, Chil3, Cd274, Cd163, Il-1β, Ccl5, Ccl2, Cd14, Cd80, etc.) was significantly upregulated at the genetic level. Additionally, histopathological examination showed myocardial infarction, which was supported by the transcriptome data. Cardiomyocyte marker genes (Hand2, Vcam1, Gja1, Actc1, etc.) were significantly downregulated. Furthermore, the functional investigation indicated that NF-κB inhibitor alpha (Nfkbia) [32] inhibited cell proliferation and promoted cell apoptosis. In this study, the expression of the *Nfkbia* gene was significantly increased. Hence, myocardial infarction may involve cardiomyocyte apoptosis [33]. Through damaged endothelial cells, intraperitoneally injected bacteria may have entered the blood circulation, adhering to heart tissue. Subsequently, the bacteria were transported to cardiomyocytes and caused heart injury. To sum up, we speculate that the innate immune system may play an essential role in the P. multocida-infected murine model. We next investigated key genes and their related pathways.
As the first line of host defense against bacterial infections [34], the innate immune system mainly relies on pattern recognition receptors (PRRs) [35] to recognize pathogen-associated molecular patterns (PAMPs), such as LPS [36]. Nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) are intracellular receptors in the PRR family [37]. As a vital member of the NLR family, NOD2 is a sensor of bacterial peptidoglycan (PGN) recognition [38]. Previous studies have shown that the basal expression of Nod2 is low, which is consistent with our control group results. However, after infection with Pm HN01 and Pm HN02, the expression of Nod2 was significantly upregulated, which may be attributed to the PGN fragment in the P. multocida periplasmic space [39]. NLRC5, a member of the NLR family, is a negative regulator of the inflammatory pathway. Its expression level was significantly upregulated after LPS stimulation [40]. The expression of Nlrc5 was significantly upregulated after PmHN01 and PmHN02 infection in our study, which indicated that the body inhibited the inflammatory response to P. multocida infection by enhancing the expression of Nlrc5. In summary, during infection with Pm HN01 and Pm HN02, genes related to immune inflammation, such as Nod2 and Nlrc5, were generally upregulated and significantly activated the NOD-like receptor signaling pathway. Taken together, the NOD-like receptor signaling pathway is essential for the recognition of Pm HN01 and Pm HN02.
As downstream pathways of PRRs, complement and coagulation and cytokine–cytokine receptor interaction were significantly activated in this study. Complement and coagulation are pivotal factors contributing to inflammation [41] and the core of innate immune mechanisms against extracellular bacteria. In this study, the complement and coagulation cascade was significantly upregulated in the Pm HN01 and Pm HN02 groups, which was an essential manifestation of host heart tissue participating in P. multocida infection. Moreover, we detected that the hub gene (C3) of the complement and coagulation cascade was upregulated. Thus, these results further indicate that P. multocida activated the complement and coagulation cascade. Inflammation stimulates the high expression of various pro-inflammatory mediators and cytokines in the tissue, which is consistent with the activation of cytokine–cytokine receptor interactions in this study. The increased expression of a cytokine (Il-1β) and cytokine receptor (Il4ra) was validated by RT-qPCR analysis. According to the histopathological examination, inflammatory cell infiltrates were scattered in the myocardium. IL-1β is the central mediator of inflammation [42] and is crucial for the body’s defense against infection. It is possible that Il-1β acts on macrophages through cell surface receptors and induces the expression of certain chemokines and adhesion molecules, thus recruiting and activating immune cells such as neutrophils. In this study, the expression levels of Il-1β, Il4ra, Il-6, Myd88, Nek7 and Nlrp3 were significantly upregulated and significantly activated complement and coagulation and cytokine–cytokine receptor interaction, suggesting that they are crucial for host defense mechanisms to both Pm HN01 and Pm HN02.
Toll-like receptors (TLRs) are transmembrane signal transduction receptors, which activate the innate immune response of the host through PAMPs, thus eliminating pathogens and playing an essential role in immune defense [43]. This study found that the Toll-like receptor signaling pathway was significantly upregulated during Pm HN02 infection, which is consistent with our in vitro experiment [8]. Lipoprotein on the surface of bacteria and LPS on the outermost layer of the cell wall are essential virulence factors of P. multocida [2]. They are also potent agonists that give rise to inflammatory responses. Among TLRs, TLR2 plays a vital role in the early innate immune response to bacterial infection by initiating the release of pro-inflammatory cytokines and influencing the downstream immune response [44]. LPS triggers the primary immune response and finally humoral immunity through TLR4 on the cell surface [45]. In this study, the expression levels of Tlr2 and Tlr4 were significantly upregulated after Pm HN01 and Pm HN02 infection, which was consistent with previous test results of P. multocida infection [46,47]. The TLR4-mediated signaling pathway of MyD88 activates NF-κB and initiates the production of a series of inflammatory cytokines, such as IL-6 [48]. In addition, TLR4 activates NLRP3 inflammatory bodies [49] through a non-classical pathway by recognizing extracellular LPS, which is pivotal in the host defense against pathogen infection and the regulation of inflammatory responses. Nek7 directly combines with NLRP3 receptor molecules [50], which promotes the assembly of NLRP3 inflammatory bodies. Moreover, the Toll-like receptor signaling pathway was only significantly upregulated in the Pm HN02 group, and no significant difference was observed in the Pm HN01 group in this study, which implies that the Toll-like receptor signaling pathway was stronger in the Pm HN02 group compared to the Pm HN01 group. Then, we focused on the Toll-like receptor signaling pathway in the Pm HN02 group without the Pm HN01 group. Previous studies demonstrated that LPS recognition results in the activation of the MyD88-dependent signaling pathway [51]. Moreover, the increased expression of Myd88 (the hub gene of the Toll-like receptor signaling pathway in the Pm HN02 group) was verified at both the transcription and protein levels. It has been suggested that *Pasteurella multocida* toxin-induced G protein signaling regulates TLR4-mediated immune responses [52]. Given the results presented here, we can speculate that the key difference in the host defense against the two strains is the Toll-like receptor signaling pathway. Perhaps Pm HN01 evades the immune system by avoiding recognition by TLRs, thereby reducing the innate immune response. This perhaps explains previous studies that suggested that Pm HN02 is less virulent than Pm HN01 [8]. To demonstrate this, further systematic explorations are needed.
## 5. Conclusions
To our knowledge, this study is the first to reveal vital pathways by which the heart recognizes and defends against P. multocida serotypes A and D. In addition, the significant activation of the NOD-like receptor signaling pathway suggests the importance for the heart recognition of P. multocida. As downstream pathways of PRRs, the significantly activated complement and coagulation cascade and cytokine–cytokine receptor interaction were crucial for the heart innate immune response during P. multocida infection. Moreover, P. multocida serotype A significantly activated the Toll-like receptor signaling pathway and upregulated the expression of MyD88 in the heart. These signaling pathways can be used as prognostic and diagnostic markers. Additionally, signaling pathway inhibitors or activators can be used as therapeutic targets. Together, these findings provide a molecular basis for the prevention and control of Pasteurellosis.
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|
---
title: 'The Ketogenic Diet and Neuroinflammation: The Action of Beta-Hydroxybutyrate
in a Microglial Cell Line'
authors:
- Rita Polito
- Maria Ester La Torre
- Fiorenzo Moscatelli
- Giuseppe Cibelli
- Anna Valenzano
- Maria Antonietta Panaro
- Marcellino Monda
- Antonietta Messina
- Vincenzo Monda
- Daniela Pisanelli
- Francesco Sessa
- Giovanni Messina
- Chiara Porro
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967444
doi: 10.3390/ijms24043102
license: CC BY 4.0
---
# The Ketogenic Diet and Neuroinflammation: The Action of Beta-Hydroxybutyrate in a Microglial Cell Line
## Abstract
The ketogenic diet (KD), a diet high in fat and protein but low in carbohydrates, is gaining much interest due to its positive effects, especially in neurodegenerative diseases. Beta-hydroxybutyrate (BHB), the major ketone body produced during the carbohydrate deprivation that occurs in KD, is assumed to have neuroprotective effects, although the molecular mechanisms responsible for these effects are still unclear. Microglial cell activation plays a key role in the development of neurodegenerative diseases, resulting in the production of several proinflammatory secondary metabolites. The following study aimed to investigate the mechanisms by which BHB determines the activation processes of BV2 microglial cells, such as polarization, cell migration and expression of pro- and anti-inflammatory cytokines, in the absence or in the presence of lipopolysaccharide (LPS) as a proinflammatory stimulus. The results showed that BHB has a neuroprotective effect in BV2 cells, inducing both microglial polarization towards an M2 anti-inflammatory phenotype and reducing migratory capacity following LPS stimulation. Furthermore, BHB significantly reduced expression levels of the proinflammatory cytokine IL-17 and increased levels of the anti-inflammatory cytokine IL-10. From this study, it can be concluded that BHB, and consequently the KD, has a fundamental role in neuroprotection and prevention in neurodegenerative diseases, presenting new therapeutic targets.
## 1. Introduction
The ketogenic diet (KD), a diet characterized by low levels of carbohydrates and proteins [1] but a high intake of fat, was initially used mainly for the treatment of drug-resistant epilepsy in humans, precisely in children, from the beginning of the 20th century [2]. In recent years, KD has been the subject of further studies, as it has been increasingly confirmed that diet and health are closely related and that different distributions of macronutrients, especially in the case of KD, could have positive effects, especially in some pathologies [3]. For example, numerous studies have reported that KD improves obesity [4], diabetes [5], polycystic ovary syndrome (PCOS) [6] and other conditions [7]. KD has been recognized as a neuroprotective factor, especially in cases of brain injury and neurodegenerative diseases [8,9]. Neurodegenerative diseases, such as Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), Alzheimer’s (AD) and Huntington’s disease (HD), are closely linked to a progressive loss of neuronal material and function [10]. The causes are to be attributed to infections and mutations, and therefore to genetic predispositions, as well as protein aggregates [11], which lead to chronic activation of the central nervous system (CNS) and consequently to high levels of inflammatory mediators [12]. The main cause of the probability of developing neurodegenerative diseases could be microglial activation [13]. Microglia, macrophages resident in the central nervous system, represent the first cell line that determines immune surveillance and host defense [14]. Cerebral microglia turn out to be very sensitive in perceiving the slightest variations in the surrounding environment, which variations determine their cellular activation [15]. Once activated, microglia are responsible for the phagocytosis of cellular debris and the production of proinflammatory mediators, reactive oxygen species (ROS), nitric oxide (NO), interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) [16,17]. Unstimulated microglia are in a “resting” state, with a branched morphology and reduced cytoplasm [18]. This state contributes to brain homeostasis by regulating synaptic remodeling and neurotransmission [19]. Activated microglial cells polarize into the M1 proinflammatory phenotype (classical activation) [15,20]. This phenotype is induced by interferon-γ (IFN-γ) and lipopolysaccharide (LPS) [21] and is characterized by a larger soma and reduced ramifications, typically of amoeboid form [22]. The M1 phenotype releases inflammatory cytokines and chemokines, determining inflammation and neuronal death [23]. The polarization of microglia in the M2 phenotype (alternative activation) is characterized by a branched morphology and a small body [18] and is induced by anti-inflammatory cytokines, such as IL-4 and IL-13, and characterized by the production of anti-inflammatory cytokines and secondary metabolites, such as IL-10, transforming growth factor TGF-β, and insulin-like growth factor-1 (IGF-1), which are involved in tissue maintenance and repair [24]. Persistent activation of microglia in the M1-type proinflammatory state results in the transition of microglia to an amoeboid morphology associated with neuronal damage and overproduction of proinflammatory cytokines [25], the main factors responsible for an increased likelihood of developing neurodegenerative diseases, such as PD, AD and ALS [26,27]. Recently identified among the new therapeutic strategies that could benefit microglia and consequently reduce the onset of neurodegenerative diseases is the KD [28]. The KD may exert neuroprotective effects by modulating numerous inflammatory patterns [29]. It is assumed that this neuroprotective effect is determined by the presence of secondary metabolites, acetoacetate (AcAc) and, in greater quantities, β-hydroxybutyrate (BHB), produced by hepatic mitochondria [30], which are the main ketone bodies consumed by the organism, especially by the brain, to compensate for the lack of energy as alternative substrates for the Krebs cycle [31] when glucose levels drop, especially during fasting or as a result of the mechanisms induced by the ketogenic diet [32]. These mechanisms occur because the total amount of carbohydrates provided by the KD is about 20–50 g per day (5–$10\%$ of total daily energy) [33]. The restriction of the amount of carbohydrates decreases the production of insulin, which promotes lipolysis [34] and therefore the conversion of fatty acids into ketone bodies. Ketone bodies can easily cross the blood–brain barrier by simple diffusion or through certain transporters [32]. For this reason, they can exert beneficial effects in the CNS, including the modulation of neurotransmitter concentrations, the modulation of synaptic transmission or, at the same time, the improvement of mitochondrial function [35]. Among ketone bodies, BHB has a predominantly neuroprotective role, even at the microglial level [36], by modulating the response of immune cells, such as by inhibiting the activation of the NLRP3 inflammasome [37], with decreased levels of IL-1β and caspase-1, decreased ROS production, and reduced cell death observed in vitro and in vivo [38]. Furthermore, BHB is associated with greater oxidation of NADH [8], which raises levels of glutathione, the main intercellular antioxidant capable of preventing possible damage caused by ROS [39]. Reduced glutathione levels are associated with increased cognitive impairment, as occurs in Alzheimer’s disease and epilepsy [40]. There are some studies that have reported that microglial activation is a key event in neuroinflammation, which, in turn, is a central process in neurological disorders. As reported in the literature, in in vivo models, BHB, acting as an anti-inflammatory mediator, inhibited IL-6 and TNF-α generation and promoted BDNF and TGF-β production in the brain of LPS-treated mice. In vitro, BHB inhibited IL-6 and TNF-α generation, increased BDNF and TGF-β production, reducing oxidative stress and ameliorating morphological changes, and elevated the viability of LPS-stimulated BV2 cells [41,42].
Considering this evidence, the aim of this study was to evaluate the effects of the KD by studying the effect of BHB in BV2 cells of murine microglia in order to better understand the molecular mechanisms involved in neuroprotection. The results of the studies that have been completed up to now are unclear and limited. The primary objective of this study was to investigate the possible neuroprotective effects of BHB, and indirectly that of the KD, on BV2 cells stimulated by LPS, a proinflammatory molecule which determines the typical phenomenon of microglial activation.
## 2.1. Influence of β-Hydroxybutyrate on BV2 Cell Viability
The results of the cell viability analysis (MTT) regarding the concentrations of BHB and their effects on BV2 cells in the presence or absence of LPS (1 µg/mL) are shown in Figure 1 below.
The data in Figure 1, Panel A show the dose–response curves in relation to BHB concentrations. As reported in previous studies in the literature, BHB did not significantly interfere with cell viability at a concentration of 5 mM [41]. Meanwhile, as shown in Figure 1, Panel B, pre-treatment of BV2 cells with BHB co-administered with LPS showed a significant ability to reverse the increase in LPS-induced cell proliferation.
## 2.2. Analysis of the Effect of β-Hydroxybutyrate on BV2 Cell Morphology
The results concerning the morphological analysis of the BV2 cells following the administration of BHB in the presence or absence of LPS (1 µg/mL) are shown in Figure 2, below.
As shown in Figure 2, the control BV2 cells (Panel A) show the classic morphology of microglia in a “resting state”, characterized by ramifications and small cell bodies [43]. Following proinflammatory or anti-inflammatory stimuli, microglia can assume either the M1 phenotype or the M2 phenotype, mediating functions to maintain the homeostasis of tissues [44]. The M1 phenotype, which is characterized by the absence of branches and an increased cell soma, as confirmed by various studies [12], can be induced by proinflammatory stimuli, such as LPS, as shown in Panel B. The M2 phenotype (alternative or anti-inflammatory activation) occurred after treatment with BHB and is characterized by significantly elongated branches as compared to the control and a reduced soma (Panel C). The results show that the same condition obtained after pretreatment with BHB with the addition of LPS (Panel D). It was therefore observed that BHB had an anti-inflammatory effect against the microglial BV2 cells, restoring the anti-inflammatory phenotype. The results were also confirmed by the morphological analysis (Panel E): BHB was able to significantly reduce the increase in cellular area induced by the LPS condition, causing the microglial cells to maintain their initial morphology towards an anti-inflammatory state.
## 2.3. β-Hydroxybutyrate and Cell Wound-Closure Assay
The results of the cell wound assay for BV2 cells following the administration of BHB in the presence or absence of LPS (1 µg/mL) are shown in Figure 3, below.
An increased migration capacity of microglial cells, as demonstrated, is mainly associated with inflammatory responses [45,46], as documented by several studies in the literature [47]. The results confirm that stimulation with LPS determines a greater migration of BV2 cells, as can be seen in Figure 3 (Panel C), which significantly reduced the free cell area of the cell monolayer after 24 h of incubation (Panel F). The application of BHB alone (Panel D) did not cause an increase in the migratory capacity of BV2 cells, while the pre-treatment with BHB with the addition of LPS (Panel E) significantly reduced wound closure by reversing the proinflammatory effect of LPS (Panel E). BHB co-administered with LPS has a protective effect in microglial cells by reducing the migratory capacity induced by a proinflammatory stimulus.
## 2.4. β-Hydroxybutyrate and Microglial Cytokine Expression
The results of the ELISA tests of the expression levels of IL-17 and IL-10 by BV2 cells are presented in Figure 4.
Figure 4 (Panel A) shows the expression of IL-17, a proinflammatory cytokine, which was statistically higher in the condition of the cells treated with LPS than in the control condition. The BV2 cells treated with BHB + LPS, on the other hand, showed a significant decrease in the expression of IL-17 compared to the cells treated with LPS. Figure 4 (Panel B) shows the production of IL-10, an anti-inflammatory cytokine, which was significantly higher in BV2 cells treated with only BHB administration. Similarly, the expression of IL-10 in the condition of BV2 cells treated with BHB + LPS was found to be significantly higher than in the LPS condition.
## 3. Discussion
In recent years, interest in the neuroinflammatory processes involved in neurodegenerative diseases has been increasing. The ketogenic diet, being rich in fats but low in carbohydrates and proteins [48], determines a reduced intake of carbohydrate [49], with consequent production of ketone bodies in the liver, including acetone, acetoacetate (AcAc) and, in greater quantities, β-hydroxybutyrate (BHB) [50]. These are used as an energy substrate to provide energy to body cells and to the brain [51], as they are able to easily cross the blood–brain barrier and capillary cell walls [51]. The ketogenic diet, already known as a treatment for drug-resistant epilepsy [52], shows potential for microglial activation [32]. As reported in numerous studies, microglia, immune cells resident in the CNS, are activated in response to stimuli from the surrounding brain environment [53] which modify their phenotypes towards the proinflammatory M1 type, characterized by an amoeboid form with increased cytoplasm and reduced branching [54], or the anti-inflammatory M2 phenotype [55], with elongated cellular processes and a reduced body. Excessive activation of microglia in a proinflammatory state contributes to neuronal damage, the leading cause of cognitive impairment [56,57]. When activated in an M1 state, the expression of the proinflammatory enzymes iNOS and COX-2 is increased, along with increased production of proinflammatory cytokines, such as TNF-α, IL-1β and IL-6 [58], and a marked migratory capacity induced by Akt/STAT3 signaling pathways [45]. These factors appear to be the main factors contributing to a higher probability of neuronal degeneration [59]. On the contrary, M2-type activation is mediated by interleukins, such as IL-4 and IL-13 [60], and results in the expression of cytokines and receptors involved in the inhibition of microglial inflammation and in the restoration of homeostasis in the cerebral environment [58]. This includes the production of anti-inflammatory interleukins, such as IL-10, or the factors TGF-β, VEGF, EGF and Arg1 [61], and a reduced migratory capacity [62]. Therefore, the inhibition of microglial activation could be a key therapeutic strategy to improve cellular states and reduce the senescence processes in neuronal cells [63] that are defining characteristics of neurodegenerative diseases. Research in recent years has shown how BHB can modulate the microglial inflammatory response [41], reducing the likelihood of developing neurodegenerative pathologies [36], improving body composition in the same way [64], improving metabolic health [65,66] and presenting anti-aging potential [67,68]. These results were also confirmed by this study: it was observed that BHB exerted anti-inflammatory power in the BV2 microglial cells by modulating the inflammatory response induced by the proinflammatory stimulus, LPS, indicating its possible neuroprotective role in relation to the reactive microglia induced by LPS. The results confirm that BHB can modulate the polarization of BV2 from an M1 (proinflammatory) phenotype towards an M2 (proinflammatory) phenotype, reducing the migratory capacity and the production of proinflammatory cytokines, such as IL-17, associated with causes of chronic inflammation and neuronal damage [69]. Similarly, BHB contributes to raising the levels of proinflammatory cytokines, such as IL-10, a key factor in maintaining the microglia in an anti-inflammatory state. It can therefore be stated that the pretreatment with BHB before stimulation with LPS prevented the retraction of microglial cellular processes, resulting in the acquisition by the microglia of a branched morphology typical of the M2 inflammatory state [70], reduction in migratory capacity and the modulation of cytokine production in the LPS-induced BV2 cells [71,72]. The mechanisms of action remain unclear; however, previous research has shown that BHB can inhibit the expression of the NLR family, in particular, the NLRP3 inflammasome, which is involved in microglial inflammation processes [73], resulting in decreased production of proinflammatory secondary metabolites, such as cytokines IL-1β, TNF-α, ROS, iNOS and COX-2 [46]. BHB suppresses LPS-induced inflammation in BV2 cells by inhibiting NF-κB activation and subsequent increases in glutathione synthesis [32] caused by increased NADH oxidation [8]. As regards migratory capacity, in some studies in the literature it has been hypothesized that cells stimulated by LPS undergo increased levels of proinflammatory cytokines and/or AKT/STAT3 signaling, while, on the contrary, antioxidant compounds, including BHB, on account of their anti-inflammatory effects, strongly inhibit LPS-induced BV2 cell migration by inhibiting NF-κB/STAT3, as summarized in Figure 5 [74]. Furthermore, other studies have suggested, as one of the possible molecular mechanisms involved in neuroprotection, that BHB is capable of modulating dopaminergic neurons by inhibiting LPS-induced microglial activation, both in vitro and in vivo, by mediating the GPR109A signaling pathway [74]. Although the molecular mechanisms are still to be explored, it can be deduced, as one of the results of this study, that BHB, and therefore indirectly the ketogenic diet, has therapeutic potential against neurodegenerative pathologies. That having been said, although it was confirmed with respect to the cellular bases involved in neuroprotection mechanisms that BHB has a therapeutic role in microglial cells, this being a preliminary study, further studies are needed to provide further insight into the molecular mechanisms involved.
## 4.1. Cell Culture and Treatment
The immortalized mouse microglial cell line BV2 cells (American Type Culture Collection, Manassas, VA, USA) were cultured and maintained in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with $10\%$ Fetal Bovine Serum (FBS, Euroclone, Milan, Italy), $1\%$ penicillin–streptomycin solution (Penicillin–Streptomycin, Euroclone, Milan, Italy) and $1\%$ glutamine (Glutamine, Euroclone, Milan, Italy) at 37 °C in a $5\%$ CO2 atmosphere and subsequently plated in appropriate numbers and densities on the basis of subsequent experimental tests after trypsinization using Trypsin-EDTA (Trypsin-EDTA 1X in PBS). For the next experimental phase, two cell groups were treated with 5 mM BHB (Sigma, St. Louis, MO, USA) and 1 μg/mL LPS (lipopolysaccharides from *Escherichia coli* O128: B12; Sigma-Aldrich, St. Louis, MO, USA), respectively, and another group was treated with 5 mM BHB with LPS (1 μg/mL) after 1 h. The cells were stimulated and analyzed after 24 h.
## 4.2. Preparation of β-Hydroxybutyrate Solution
β-hydroxybutyrate (BHB) (DL-β-Hydroxybutyric acid sodium salt, ~$98\%$; Sigma-Aldrich) was initially diluted in sterile PBS (Dulbecco’s Phosphate-Buffered Saline w/o Calcium, Euroclone, Milan, Italy) in a 1M concentration solution. Subsequently, the final concentrations were created from the stock solution and diluted in the DMEM in which the cells were plated. Cells were incubated with BHB for 24 h before each treatment.
## 4.3. Cell Viability Assay
The concentration of BHB utilized was tested by the MTT test (0.5 mg/mL; Thiazolil Blue Tetrazolium Bromide, Sigma-Aldrich, CAS: 298-93-1). Briefly, cells were plated in 24-well plates, at a density of 2 × 105, and incubated at 37 °C with $5\%$ CO2 for 24 h, initially with concentrations of 5 mM, 10 mM, 20 mM and 100 mM, in order to study the cytotoxicity induced by BHB concentrations and its possible neuroprotective effect. A 5 mM concentration was chosen for the subsequent experimental tests, as this did not affect the BV2 cells’ viabilities. An MTT assay was performed with 5 mM BHB in the presence or absence of LPS (1 µg/mL) for 24 h. The absorbance was read with a spectrophotometer (Filter Max F5 Multi-Mode Microplate Reader, Molecular Devices, San Jose, CA, USA) at a wavelength of 595 nm. The results are expressed as cell viabilities (%) based on the control condition.
## 4.4. Cell Morphology Assay
The morphologies of the BV2 microglial cells were evaluated by means of a morphological image test to analyze the effect of BHB at a concentration of 5 mM in the absence or with the addition of the proinflammatory LPS stimulus (1 µg/mL). Approximately 5 × 105 cells were plated on a 6-well plate and incubated at 37 °C with $5\%$ CO2 for 24 h. All morphological tests were performed in triplicate. Cell morphology was evaluated by photography with Leica Microscopy (DM IRB Leica Microsystems GmbH, Wetzlar, German), with 10× and 20× magnifications. Cellular areas (µm2) were quantified using ImageJ software.
## 4.5. Cell Wound-Closure Assay
Cell migration was assessed using the cell wound-closure assay, with a total of 1 × 106 BV2 cells added to the wells of a 6-well plate and incubated at 37 °C with $5\%$ CO2 until a confluence sufficient to create a cellular layer over the entire plate was reached. Confluent monolayers were wounded using a scraper. Subsequently, after washing, with PBS and DMEM change, the remaining cells were incubated for 24 h with the respective stimuli, i.e., 5 mM BHB in the absence or presence of LPS (1 µg/mL). All migration assays were performed in triplicate. Wound closure was documented after 24 h with photomicrographs of the various conditions analyzed. The wound closures were analyzed using ImageJ software and expressed as averages of the percentages of the areas covered by the cells from the time-zero condition after 24 h.
## 4.6. ELISA Test
BHB, at a concentration of 5 mM with or without LPS (1 µg/mL), was added to BV2 cells plated for 24 h and incubated at 37 °C with $5\%$ CO2. After 24 h, the culture medium was collected and used for the evaluation of IL-17 and IL-10 cytokines, as producers of proinflammatory and anti-inflammatory patterns, with commercially available ELISA kits (R&D Systems, Minneapolis, MN, USA). Cytokine determinations were performed in triplicate, in accordance with the protocol and the manufacturers’ instructions. The cytokine concentrations (pg/mL) in the medium were determined by referring to standard curves obtained with known quantities (pg/mL).
## 4.7. Statistical Analysis
All data are plotted as the means of three independent experiments ± SDs. Statistical analyses were conducted by one-way ANOVA testing, using Graph Prism 9 software (GraphPAD Software, San Diego, CA, USA). Statistical significance was assessed with a p-value < 0.05.
## 5. Conclusions
The ketone body BHB is generally regarded as an energy source for tissues during periods of calorie deprivation and/or adherence to a low-carbohydrate diet, such as the ketogenic diet. In fact, in addition to being a caloric source, BHB has many beneficial effects, especially at the brain level. In this study, we have demonstrated that BHB could act as an anti-inflammatory agent at the microglial level and that it may be involved in neuroinflammation and neuroprotective action, although the mechanisms are still partially unknown. We postulate that BHB could be a key molecule in the prevention of neurodegenerative diseases. In addition, BHB is a product of a ketogenic diet, such that, indirectly, we have provided evidence for the potential role of the ketogenic diet in neuroinflammation and neuroprotection, though further studies are needed to clarify the molecular mechanisms involved.
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|
---
title: Heterogeneity of Ocular Hemodynamic Biomarkers among Open Angle Glaucoma Patients
of African and European Descent
authors:
- Brent Siesky
- Alon Harris
- Alice Verticchio Vercellin
- Julia Arciero
- Brendan Fry
- George Eckert
- Giovanna Guidoboni
- Francesco Oddone
- Gal Antman
journal: Journal of Clinical Medicine
year: 2023
pmcid: PMC9967448
doi: 10.3390/jcm12041287
license: CC BY 4.0
---
# Heterogeneity of Ocular Hemodynamic Biomarkers among Open Angle Glaucoma Patients of African and European Descent
## Abstract
This study investigated the heterogeneity of ocular hemodynamic biomarkers in early open angle glaucoma (OAG) patients and healthy controls of African (AD) and European descent (ED). Sixty OAG patients (38 ED, 22 AD) and 65 healthy controls (47 ED, 18 AD) participated in a prospective, cross-sectional study assessing: intraocular pressure (IOP), blood pressure (BP), ocular perfusion pressure (OPP), visual field (VF) and vascular densities (VD) via optical coherence tomography angiography (OCTA). Comparisons between outcomes were adjusted for age, diabetes status and BP. VF, IOP, BP and OPP were not significantly different between OAG subgroups or controls. Multiple VD biomarkers were significantly lower in OAG patients of ED ($p \leq 0.05$) while central macular VD was lower in OAG patients of AD vs. OAG patients of ED ($$p \leq 0.024$$). Macular and parafoveal thickness were significantly lower in AD OAG patients compared to those of ED ($$p \leq 0.006$$–0.049). OAG patients of AD had a negative correlation between IOP and VF index (r = −0.86) while ED patients had a slightly positive relationship ($r = 0.26$); difference between groups ($p \leq 0.001$). Age-adjusted OCTA biomarkers exhibit significant variation in early OAG patients of AD and ED.
## 1. Introduction
The onset and progression of open angle glaucoma (OAG) in many persons, despite significant intraocular pressure (IOP) reduction, motivates the need for evolved approaches to individualize patient care. Among IOP-independent risk factors, impaired vascular regulation and ocular tissue ischemia have been well documented [1]. Over time, technological advancements in optical imaging have allowed for more specific and detailed quantification of various vascular elements within the eye. Translating these diverse vascular biomarkers into an effective tool to assist clinicians in glaucoma management, however, remains a significant challenge due to their inaccessibility and complexity in analysis and clinical application. Precision in ocular vascular data is also often lacking, with many custom imaging modalities and analysis approaches producing unique, limited and often difficult-to-reproduce aspects of ocular hemodynamics and metabolism [1]. In addition, retinal vascular network heterogeneity across glaucomatous populations is relatively unknown and shared vascular comorbidities including hypertension and diabetes are significantly higher in certain demographic groups, all of which may alter vascular imaging biomarkers and overall risk modeling. Further, differences in tissue pigmentation among subjects may alter or prohibit optical imaging biomarker comparability.
Optical coherence tomography angiography (OCTA) allows simultaneous assessments of retinal and optic nerve head (ONH) structure and vascular densities (VD), providing clinicians an improved user interface for the potential inclusion of vascular biomarkers [2]. Since its introduction, OCTA data from a wide range of studies have suggested a significant reduction in the mean peripapillary VD in glaucoma patients, as well as marked reduction in VD in the ONH and parafoveal regions [3]. The associations of OCTA VD outcomes and OAG are generally strong, suggesting lower VD of the peripapillary retina, ONH and macular regions in glaucoma patients when compared to healthy controls [2,3]. A recent study in a Chinese population found that significant microvascular damage assessed by OCTA was present in both macular and peripapillary regions in early OAG patients, with VD loss highest in peripheral regions [4]. Despite these demonstrated associations of OCTA VD biomarkers and OAG, there is still a lack of understanding of retina, macula and ONH VD loss in early glaucomatous disease. Further, little is known regarding retinal vascular networks and associated biomarkers across different patient populations, limiting comparative analysis of the earliest microvascular changes in OAG prior to detectible visual field loss.
OCTA VD biomarkers have demonstrated acceptable test–retest variability as well as the potential to differentiate glaucomatous from normal eyes [5]. However, OCTA biomarker data and truncated normative data available for cross-subject analysis may not be robust enough to ensure sufficient rigor for all demographic comparisons. The African American Eye Disease Study found age, sex and diabetes status must be considered when assessing changes in radial peripapillary capillary VD in glaucoma [6]. While identifying consistently lower VD in glaucoma patients across multiple studies, a recent study also concluded that a well-controlled meta-analysis of OCTA and glaucoma was not possible due to the wide variation in utilized methods, measurement approaches and selected regions of VD [7]. Therefore, although evidence supporting OCTA biomarker utility in OAG is fairly strong, the unknown heterogeneity of OCTA data and lack of population-based longitudinal studies currently limits its full applicability.
The principles of operation for OCTA involve utilization of ocular structures, light dynamics and tissue pigment levels, all of which may differ between persons with OAG and therefore bias device outcomes [1,2,3,5,7,8,9]. Mitigating potential bias in ophthalmic diagnostic utilities is essential to reduce disparities in treatment outcomes currently experienced by OAG patients of African descent (AD) [10]. Specifically, a broad array of cross-sectional VD data is available in Asian descent and European descent (ED) populations, but little to no comparative data is available on OCTA VD biomarkers in early OAG patients of AD who may have higher vascular impairment in their disease process [11]. This pilot study therefore first investigates the heterogeneity and variability in OCTA-assessed retinal, ONH and macular VD and ocular structure biomarkers and then analyzes their relationships to IOP, blood pressure (BP) and ocular perfusion pressures (OPP) in early stage OAG patients of AD and ED and age-adjusted healthy controls.
## 2. Materials and Methods
Sixty OAG patients (38 ED, 22 AD) exhibiting early structural glaucomatous changes and 65 healthy controls (47 ED, 18 AD) participated in a prospective, cross-sectional, observational study conducted at the Icahn School of Medicine at Mount Sinai, New York, NY. Healthy subjects were free from OAG and any other eye disease (i.e., age-related macular degeneration, diabetic retinopathy) while OAG subjects only had OAG disease as confirmed by a board-certified glaucoma specialist. OAG patients with early structural glaucomatous changes presented evidence of the following: ONH or RNFL structural abnormalities as defined by the 2020 American Academy of Ophthalmology Primary Open-Angle Glaucoma Preferred Practice pattern [12]: diffuse or focal narrowing, or notching, of the optic disc rim, especially at the inferior or superior poles; progressive narrowing of the neuro-retinal rim with an associated increase in cupping of the optic disc; diffuse or localized thinning of the parapapillary RNFL, especially at the inferior or superior poles; optic disc hemorrhages involving the disc rim, parapapillary RNFL, or lamina cribrosa; optic disc neural rim asymmetry of the two eyes consistent with loss of neural tissue; beta-zone parapapillary atrophy; thinning of the RNFL and/or macula on imaging. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Icahn School of Medicine at Mount Sinai, New York, NY (protocol code: Study-20-00198; date of approval: 17 November 2021). Written informed consent was obtained from all subjects involved in the study.
All participants were required to meet the following inclusion criteria: age 21 years or older, healthy eyes without OAG and any other eye disease and/ or patients with confirmed early OAG in at least one eye by a glaucoma specialist with no other eye disease. Patients were excluded for the following reasons: refractive error >+9 Diopters and <−9 Diopters in spherical equivalent; evidence of exfoliation or pigment dispersion; eye disease other than glaucoma or other eye health concerns; use of eye medications (other than IOP lowering medications for glaucoma or eye lubricants for dry eye); neurological disease (Alzheimer’s disease, Parkinson’s disease, multiple sclerosis); psychosis or neurological diseases that could prevent reliable eye exams; severe, unstable or uncontrolled cardiovascular, renal, or pulmonary disease.
One qualified study eye was randomly (coin flip) selected for each subject and patients were seen during a single two-hour study visit undergoing assessment for: IOP via Goldmann applanation, systolic and diastolic blood pressure (BP) (ambulatory, at rest), ocular perfusion pressure (OPP = $\frac{2}{3}$*mean arterial pressure-IOP) and visual field index (VFI), mean deviation (MD) and pattern standard deviation (PSD) via Humphrey field analyzer II using the 24-2 Swedish interactive threshold algorithm standard (white III stimulus) V.4.1 (Carl Zeiss Mediatec, Dublin, CA, USA).
OCTA (Optovue Inc, Avanti Angiovue, Fremont, CA, USA) was used to acquire structural elements, including RNFL thickness, cup-to-disc (C/D) ratio, ganglion cell complex (GCC) thickness and VD of the retina, ONH and macular regions. In brief, the Optovue OCTA provides a non-invasive three-dimensional visualization of the retinal microvasculature and OCT-assessed structural elements of the retina, ONH and macula regions. The device uses consecutive scans to calculate motion contrast and translates initial tissue reflectance into flow signals; details on principles of OCTA are available elsewhere [5,8,9]. In our study, we utilized the AngioAnalyticsTM licensed upgrade present in the Avanti Optovue device that enables the automatic assessment of the retinal and ONH VD computed as percentage of area occupied by OCTA detected vasculature in the areas of interest [13]. In detail, the ONH VD were assessed via the 4.5 mm HD Angio Disc scan and the percentage of area occupied by OCTA detected vasculature was detected for the radial peripapillary capillary (RPC) slab (from the internal limiting membrane to the nerve fiber layer). The ONH vessel density measurements are provided from three regions: peripapillary region (defined by two rings of 2 mm and 4 mm centered on disc center); inside the optic disc; entire region. The VD are measured for the small vessels (SV) (i.e., with large vessel masking) and for all vessels (ALL); the application of large vessel mask has threshold of ≥3 pixels (approximately ≥33 μm). The ONH vessels density information included were the RPC slab density parameters (global and peripapillary hemispheric for both the small vessels and all vessels) and the regional vessel density parameters (small vessels only) for the superior, temporal, nasal and inferior quadrants). The central macular vessel density was assessed via the 6.0 mm HD AngioRetina scan in the 1-mm central ring of the ETDRS grid centered on the fovea [13].
Healthy subjects were free from eye disease other than mild myopia and well-controlled hypertension. Subject demographics, including age, self-reported race and sex, height, weight, diabetic status, hypertensive status and medication use, were also recorded.
Nonparametric analysis of covariance was used to compare race/ethnic groups in OAG patients and healthy controls for differences in biomarkers, with demographics as covariates in the analyses including sex, age, hypertension and diabetes. Spearman correlations were used to test associations between biomarkers, with adjustment for demographics. A $5\%$ significance level was used. Statistical analyses were performed using SAS (SAS Institute Inc., Cary, NC, USA).
## 3. Results
Ocular and systemic characteristics for OAG patients and healthy controls are shown in Table 1. VF parameters, IOP, BP and OPP were not significantly different ($p \leq 0.05$) between OAG or healthy subgroups except for BP systolic between OAG patients and controls of ED ($$p \leq 0.000$$) and VF PSD between OAG patients and controls of AD ($$p \leq 0.036$$), as showed in Table 1.
When assessing ocular structure outcomes between heathy and OAG patients, average RNFL thickness was identified to be significantly thinner in early OAG patients of AD ($$p \leq 0.007$$) and ED ($$p \leq 0.000$$) as shown in Table 2. RNFL thickness in the superior and inferior hemispheres were also statistically significantly different between OAG patient groups and controls ($p \leq 0.05$). C/D area ratio ($$p \leq 0.023$$) and disc area ($$p \leq 0.028$$) were significantly different in OAG patients of ED versus controls.
Macular and parafoveal thicknesses were significantly lower in AD OAG patients compared to those of ED ($$p \leq 0.006$$–0.049). No other significant differences were found in the structure of the macular regions for OAG patient groups or between OAG patients and controls.
Multiple radial peripapillary capillary VD biomarkers were significantly lower only in OAG patients of ED compared to controls ($$p \leq 0.000$$–0.013) while central macular VD was lower only in OAG patients of AD compared to OAG patients of ED ($$p \leq 0.024$$). Table 3 show the OCTA parameters in OAG patients and healthy subjects of AD and ED.
In examination of the relationships between biomarkers, several significant differences in correlations were found between OAG patients of AD versus OAG patients of ED (Table 4). Regarding the relationship between IOP and VF parameters, OAG patients of AD had a negative correlation between IOP and VF index (r = −0.86) while ED patients had a slightly positive relationship ($r = 0.26$) leading to a statistically significant difference between groups ($p \leq 0.001$), see Table 4.
The differences in correlations between IOP and structural or VD outcomes for any control groups of AD and ED are shown in Table 5.
## 4. Discussion
This pilot analysis examined the heterogeneity of OCTA hemodynamic biomarkers of VD in the retina, macula and ONH in early stage OAG patients exhibiting structural changes and healthy controls of AD and ED. While a wealth of data supports OCTA-measured VD biomarkers being associated with OAG, little data is currently available on VD loss in early stage OAG across differing population groups. Early capillary loss prior to detectible VF damage may indicate a primary vascular dysfunction in the OAG disease process and such impaired vascular regulation may be more prevalent in persons of AD [11,14]. The shared and elevated rates of vascular comorbidities in AD populations may indicate higher vascular involvement in the glaucomatous disease process and OCTA VD may therefore have higher utility in AD disease management compared to other population groups.
Understanding variability within populations is especially important since glaucoma is multifactorial and may represent a collection of diseases that involve higher vascular insult in certain persons. Specifically, persons of AD are known to have significantly higher rates of systemic vascular health disease, including stroke, hypertension and diabetes [15,16] and these translate into poor autoregulatory ability for microvascular tissues. We previously identified retinal and retrobulbar blood flow deficits in glaucoma patients of AD compared to those of ED [14] and linked these lower vascular biomarkers to elevated levels of structural disease progression in AD OAG patents over a four-year period [11]. Of significant importance, it is not currently known if OAG patients with higher systemic vascular disease experience more significant retinal, macular and/or ONH VD capillary prior to detectable visual field loss. In addition, scarce information is currently available on OCTA VD biomarkers in persons of Hispanic descent, who along with persons of AD may experience elevated levels of both systemic vascular disease and glaucomatous disease burden. As these and other imaging biomarkers are utilized in clinical management, understanding bias in access, utilization and application of data is critical to eliminate bias and subsequent OAG disease and treatment disparities, including those currently experienced by patients of AD [10].
In our pilot analysis, IOP, BP and OPP were not significantly different between OAG or healthy subgroups. VF outcomes were also not different between OAG subgroups or OAG and controls, with the exception of VF PSD between OAG patients (3.24) and controls (2.10) of AD ($$p \leq 0.036$$). These data confirm our OAG groups (based upon changes to the ONH and retina) were relatively early in stage and examined prior to significant perimetric defect(s) and significant tissue atrophy. Specifically, average RNFL thickness was significantly lower in OAG patients of AD and ED compared to controls. Superior and inferior hemispheres RNFL thickness were also statistically significantly different between OAG patient groups and controls. Average GCC thickness was significantly lower in OAG patients of AD versus controls (80.1 vs 93.1) while trending (non-significantly) lower in those of ED (mean: 88.5 vs 95.3). A larger sample size would increase statistical power and likely result in more significant differences in each group, although the power of sensitivity for OCTA RNFL thickness and GCC thickness appears to vary with higher sensitivity in OAG patients of ED. It is important to note, however, that determining OAG early prior to significant visual field loss is challenging and lack of exact uniformity in early OAG structural changes may limit applicability of comparisons to other groups.
Macular and parafoveal thickness were significantly lower in AD OAG patients compared to those of ED. This finding in early AD OAG patients is interesting as early OAG structural changes have been previously reported in pilot work via OCTA that include reduction in the superficial VD of the macular regions [5]. This pilot data may indicate OAG patients of AD exhibit earlier, vascular-related changes to the macular region of the eye prior to or just at detectable visual field loss. Improvement in modeling outcomes for OAG patients where VD and structure are combined has been previously reported utilizing specific OCTA VD biomarkers [17]. Taken together with earlier pilot data [11,14], these data suggest modeling for OAG risk in persons of AD should include vascular elements where possible, including assessment of macular regions in early OAG.
Multiple VD biomarkers were significantly lower in OAG patients of ED while central macular VD was lower only in OAG patients of AD. This suggests OCTA VD biomarkers, similar to structural elements in the study, may have higher sensitivity in discriminating early OAG patients of ED than in those of AD. This may be due to more robust use of ED eyes for OCTA development compared to those of AD or a result of elevated levels of pigmentation altering light-based OCTA comparative outcomes. Differences in pigmentation of tissue affecting ocular imagery is an established limitation of optical imaging modalities including photographic retinal oximetry, where retinal oxygen levels often exceed $100\%$, including in persons of AD with higher levels of pigmentation [1,18].
Interestingly, our exploratory analysis showed that OAG patients of AD had a negative correlation between IOP and VF index (r = -0.86) compared to those of ED, who had a slightly positive relationship ($r = 0.26$), with a significant difference between groups ($p \leq 0.001$). While pilot data on differences in ocular structure, IOP, disease burden and therapeutic outcomes between OAG patients of AD and ED are available [10], little is known about differences in the relationships between risk factors. The strong negative relationship seen in our data between VFI and IOP in OAG subjects of AD agrees with several previous studies reporting higher IOP levels associated with increased OAG disease persons of AD [10]. Previously, higher levels of vascular dysfunction were also found in OAG patents of AD compared to ED, regardless of similar IOP and disease status [11,14]. Together these data suggest that OAG patients have both IOP and significant vascular mechanisms involved in their disease process, with some level of variability. While a higher sample size may reduce the magnitude of observed differences, these data suggest that traditional risk metrics using IOP alone may not best capture risk for all individuals of AD and ED. Differences in relationships between physiological biomarkers may also help explain why similar therapeutic IOP reduction results in significantly difference disease and visual field outcomes [10] for OAG patients of AD. Together, these data point to the need to model for multi-input risk in OAG to account for differential risk and individualization in disease management plans tailored to preservation of visual function and not considering only the level of IOP reduction achieved.
Our pilot study has several significant limitations to acknowledge. First, our patient population was considered early-stage OAG in nature; the structural diagnostic elements (ONH, CD ratio, RNFL) and diabetic and/or hypertensive status were not uniform across all subjects. These differences in potential approach and difficulty in consensus of determining early glaucoma may also limit applicability of comparisons to other patient samples. While out study was indented to be pilot in nature, the sample size, while informative, is small and a larger sample would likely reduce the magnitude of observed differences. In addition, healthy subjects were significantly younger than OAG subjects, although results were statistically adjusted for age to limit impact on the samples. Finally, our analysis was cross-sectional; longitudinal glaucomatous changes in outcomes were not assessed and are required for determining influence on predictability of disease progression.
In this analysis, age-adjusted OCTA hemodynamic and structural factors exhibit significant variation in OAG patients of AD and ED. For any measured outcome, use of normative data and disease group comparisons require careful consideration of potential biases including: limited access, non-inclusive principles of device operation (i.e., not accounting for differences in patient pigmentation) and bias in data utilization and modeling. To uncover the best approach for each patient, an inclusive model of risk is needed that accounts for potential modifiers and bias in patient data. Data rigor from ocular imaging is important to address in order to reduce disparities in current and future applications. Efforts to account for heterogeneity in OCTA hemodynamic data may be especially important in persons with elevated vascular disease including persons of AD. Properly designed longitudinal studies that target AD outcomes as primary endpoints are needed to confirm these findings and understand the impact of OCTA biomarker heterogeneity on glaucoma progression and disease management.
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---
title: Selective Transcription Factor Blockade Reduces Human Retinal Endothelial Cell
Expression of Intercellular Adhesion Molecule-1 and Leukocyte Binding
authors:
- Yuefang Ma
- Liam M. Ashander
- Binoy Appukuttan
- Feargal J. Ryan
- Alwin C. R. Tan
- Janet M. Matthews
- Michael Z. Michael
- David J. Lynn
- Justine R. Smith
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967456
doi: 10.3390/ijms24043304
license: CC BY 4.0
---
# Selective Transcription Factor Blockade Reduces Human Retinal Endothelial Cell Expression of Intercellular Adhesion Molecule-1 and Leukocyte Binding
## Abstract
The interaction between leukocytes and cytokine-activated retinal endothelium is an initiating step in non-infectious uveitis involving the posterior eye, mediated by cell adhesion molecules. However, because cell adhesion molecules are required for immune surveillance, therapeutic interventions would ideally be employed indirectly. Using 28 primary human retinal endothelial cell isolates, this study sought to identify transcription factor targets for reducing levels of the key retinal endothelial cell adhesion molecule, intercellular adhesion molecule (ICAM)-1, and limiting leukocyte binding to the retinal endothelium. Five candidate transcription factors—C2CD4B, EGR3, FOSB, IRF1, and JUNB—were identified by differential expression analysis of a transcriptome generated from IL-1β- or TNF-α-stimulated human retinal endothelial cells, interpreted in the context of the published literature. Further filtering involved molecular studies: of the five candidates, C2CD4B and IRF1 consistently demonstrated extended induction in IL-1β- or TNF-α-activated retinal endothelial cells and demonstrated a significant decrease in both ICAM-1 transcript and ICAM-1 membrane-bound protein expression by cytokine-activated retinal endothelial cells following treatment with small interfering RNA. RNA interference of C2CD4B or IRF1 significantly reduced leukocyte binding in a majority of human retinal endothelial cell isolates stimulated by IL-1β or TNF-α. Our observations suggest that the transcription factors C2CD4B and IRF1 may be potential drug targets for limiting leukocyte–retinal endothelial cell interactions in non-infectious uveitis involving the posterior eye.
## 1. Introduction
Non-infectious uveitis is a group of autoimmune and autoinflammatory eye diseases [1]. Although it is uncommon, non-infectious uveitis often impacts the vision, particularly when the inflammation involves the posterior segment of the eye: approximately $70\%$ of patients with uveitis suffer vision loss to $\frac{20}{60}$ or greater [2]. Most patients with intermediate, posterior, and pan non-infectious uveitis are initially treated with systemically administered corticosteroid and subsequently transitioned onto immunomodulatory drugs. Conventional drugs—such as anti-metabolites—plus low-dose prednisolone control the inflammation in just 24–$65\%$ of patients [3,4,5,6], and biologic drugs are increasingly being used, often targeting inflammatory cytokines such as tumor necrosis factor (TNF)-α and interleukin (IL)-1β [7].
Cell adhesion molecules are another potential biologic drug target in non-infectious uveitis involving the posterior eye. These molecules are expressed on endothelial cells that line tissue vasculature and on circulating leucocytes, and their interactions control the migration of the leukocytes across the endothelium into the tissue for homeostatic immune surveillance and during inflammation [8]. The migration process is often described as the ‘leukocyte adhesion cascade’, beginning with rolling of the leukocyte across the endothelium, followed by arrest and spreading of the leukocyte over the endothelium, and finally movement of the leukocyte through the endothelium. Endothelial selectins participate in the earliest stages, while immunoglobulin (Ig) superfamily members become the predominant players as migration proceeds. Drugs that block cell adhesion molecules have been used to treat inflammatory diseases, including non-infectious uveitis [9,10], but recognition of an association with progressive multifocal leukoencephalopathy has led to strict restrictions on their use [11]. This fatal disease is caused by reactivation of latent human polyomavirus 2 within the central nervous system (CNS); blocking leukocyte trafficking into the CNS, thus limiting immune surveillance, may break latency of the virus [12].
During inflammation, cell adhesion molecules are upregulated on the activated endothelium, promoting extravasation of large numbers of leukocytes into the tissue [8]. This suggests the opportunity for an alternative drugging approach for non-infectious uveitis: targeting the induction of endothelial cell adhesion molecules. Leukocytes enter the posterior eye across the retinal endothelium [13]. Intercellular adhesion molecule (ICAM)-1—a member of the immunoglobulin (Ig) superfamily—is expressed at relatively high levels by human retinal endothelial cells [14,15], and it is upregulated by inflammatory stimuli [13]. Expression of ICAM-1 is regulated primarily at transcription [16]. In a proof-of-concept study using a human retinal endothelial cell line, we showed that ICAM-1 levels could be controlled by manipulation at the transcriptional level [17]. In this work, we investigate the effect on ICAM-1 expression and leukocyte-endothelial interactions of targeting candidate transcription factors in multiple human retinal endothelial cell isolates.
## 2.1. Candidate Transcription Factors Induced in Cytokine-Activated Human Retinal Endothelial Cells: C2CD4B, EGR3, FOSB, IRF1, and JUNB
To identify transcription factors that might promote leukocyte interactions with activated human retinal endothelial cells, we interrogated a previously published transcriptomic dataset generated from cell isolates that had been activated by brief exposure to inflammatory cytokines [18]. Differential expression analysis comparing five primary human retinal endothelial cell isolates, treated with IL-1β or TNF-α versus no cytokine for 60 min, demonstrated a 2-fold or more increase in expression of 87 genes by IL-1β and 68 genes by TNF-α at a false discovery rate (FDR) of less than 0.05 (Supplementary Table S1). Overlay of the two lists of up-regulated molecules showed 66 were common, including 12 transcription factors (Table 1). Review of the activity of these transcription factors, as reported in the published literature, identified five candidates with the potential to induce expression of human retinal endothelial cell ICAM-1, a central cell adhesion molecule coordinating leukocyte interactions in non-infectious posterior uveitis: C2CD4B, EGR3, FOSB, IRF1, and JUNB [17,19,20,21].
## 2.2. Priority Candidate Transcription Factor Targets for Drugging Leukocyte Interactions with Activated Human Retinal Endothelial Cells: C2CD4B and IRF1
Candidate transcription factors—C2CD4B, EGR3, FOSB, IRF1, and JUNB—were further evaluated for a potential role in leukocyte–retinal endothelial cell interactions in a series of molecular studies. These studies made use of 28 primary cell isolates that were sourced from eyes of 12 men and 16 women cadaveric donors aged 35 to 77 years at death (median = 61.5 years). Time from death to cell isolation ranged from 11 to 67 h (median = 31.5 h).
First, to assess induction of the transcription factors in human retinal endothelial cells over an extended interval, confluent primary cell isolates were treated with IL-1β or TNF-α, or fresh medium alone as control ($$n = 5$$ isolates for each cytokine comparison) for 4 h, and gene expression levels were evaluated by reverse transcription (RT)-polymerase chain reaction (PCR). As shown in Figure 1, the expression of C2CD4B, IRF1, and JUNB was significantly increased (p ≤ 0.009) by treatment with IL-1β (Figure 1A,G,I) or TNF-α (Figure 1B,H,J). In contrast, there was no significant change in expression for EGR3 (Figure 1C,D) or FOSB (Figure 1E,F) in cells treated with either cytokine ($p \leq 0.05$).
Second, the effect of transcription factor blockade on ICAM-1 transcript expression was evaluated in a characterized human retinal endothelial cell line generated in-house. The cell line was used due to the large number of cells that were needed for the assays. As presented in Figure 2, a 24 h stimulation with either IL-1β and TNF-α, following on from a 48 h treatment with small interfering (si)RNA, increased ICAM-1 transcript expression in retinal endothelial cells. There was no significant change ($p \leq 0.05$) in the expression of ICAM-1 transcript in unstimulated human retinal endothelial cells following silencing of any of the five transcription factors. However, targeted siRNA knockdown of C2CD4B (Figure 2A,B) and IRF1 (Figure 2G,H) significantly decreased (p ≤ 0.001) the level of ICAM-1 transcript compared to non-targeted siRNA treatment under both IL-1β- and TNF-α-stimulated conditions. Knockdown of FOSB (Figure 2E,F) significantly reduced expression of ICAM-1 after TNF-α, but not IL-1β exposure, in comparison to control ($p \leq 0.007$ and $p \leq 0.05$, respectively). Expression of ICAM-1 was either unchanged ($p \leq 0.05$) or significantly up-regulated (p ≤ 0.0171) compared to non-targeted siRNA treatment when EGFR3 (Figure 2C,D) or JUNB (Figure 2I,J) were targeted under IL-1β- and TNF-α-stimulated conditions.
Third, the effect of transcription factor blockade on expression levels of ICAM-1 protein on the cell membrane, representing adhesion molecule available for leukocyte binding, was measured in primary human retinal endothelial cell isolates. Cells were treated with siRNA for 48 h and subsequently stimulated for 24 h with either IL-1β or TNF-α, or fresh medium only. At the end of the assay, membrane-bound ICAM-1 was labeled by indirect immunofluorescence and measured with adjustment for cell number. Membrane-bound ICAM-1 expression was induced under IL-1β- and TNF-α-stimulated conditions, compared with the medium control, and as illustrated in Figure 3, silencing of C2CD4B, FOSB, and IRF1 significantly decreased (p ≤ 0.001) the level of membrane-bound ICAM-1 compared to non-targeted siRNA under all conditions (Figure 3A–C). For reduced EGFR3 and JUNB, expression of membrane-bound ICAM-1 was unchanged ($p \leq 0.05$) under the control condition (Figure 3A) and significantly up-regulated ($p \leq 0.0001$) under IL-1β- and TNF-α-stimulated conditions (Figure 3B,C).
In summary, C2CD4B and IRF1 consistently demonstrated: [1] extended cytokine-induced gene expression in activated human retinal endothelial cells; [2] decrease in cellular ICAM-1 transcript expression when silenced under cytokine-activated conditions; and [3] decrease in membrane-bound ICAM-1 protein when targeted. Thus, these two transcription factors were priority candidates for evaluating the impact of transcription factor blockade on leukocyte–retinal endothelial cell interactions.
## 2.3. Effect of C2CD4B and IRF1 Targeting on Leukocyte Interactions with Human Retinal Endothelial Cells
The effect of C2CD4B and IRF1 blockade on leukocyte interactions with human retinal endothelial cells was studied in a binding assay conducted under simulated flow conditions. After a 48 h treatment with targeted or control non-targeted siRNA, and a 24 h stimulation with IL-1β or TNF-α, or medium alone, individual human retinal endothelial cell isolates were rotated briefly with CFSE-labeled THP-1 leukocytes. Leukocyte binding was measured as fluorescence of the co-cultures. As shown in Figure 4, targeted knockdown of C2CD4B led to significant reduction in THP-1 leukocyte binding across five individual human retinal endothelial cell isolates stimulated by IL-1β or TNF-α, in comparison to the non-targeted siRNA control treatment. For IRF1, the same result was observed in four of five isolates. In assays performed with non-activated endothelial cells treated with a fresh medium without cytokine, there was no significant change ($p \leq 0.05$) in THP-1 leukocyte binding for three of five isolates when C2CD4B was targeted and for two of five isolates when IRF1 was targeted. These results suggest that blockade of C2CD4B or IRF1 in cytokine-activated human retinal endothelial cells inhibits leukocyte binding for a majority of donors.
## 3. Discussion
The central role of transcription factors in cell identity and activity, and in the development and progression of diverse diseases including uveitis [22], led to early enthusiasm around therapeutic targeting of gene transcription [23]. However, features of transcription factor interactions with DNA and co-factors—elements of disorder or ‘fuzziness’ without structured binding pockets [24,25]—limited progress in the field for decades, and there was a general consensus that transcription was undruggable. Recent developments that promise to reverse this perspective include new knowledge of intrinsically disordered proteins, cellular thermal shift assays to interrogate target engagement, binding-focused drug screening methodologies, proteolysis targeting chimera-based therapeutics, and CRISPR-directed transcriptional interventions [26,27]. In the area of medical oncology in particular, numerous therapeutics that target transcription factor activity are currently under development or have already entered clinical trials [28]. In this work, we show that targeting the transcription factors, C2CD4B, and IRF1, limits interactions between human retinal endothelial cells and leukocytes, which is a key initiating step in non-infectious uveitis involving the posterior eye.
At the time of writing, C2CD4B remains quite poorly characterized among transcription factors, with less than 30 peer-reviewed articles published on this molecule, and no articles reporting its activity in retinal endothelial cells from humans or any other mammalian species. Originally described in 2004 and named nuclear localized factor (NFL)2, C2CD4B was measured at relatively high levels in human endothelial cells in comparison to epithelial cells, smooth muscle cells, fibroblasts, and monocytes, and was found to be induced by IL-1β and TNF-α [19]. *Subsequent* genetics-focused research has linked C2CD4B to glucose homeostasis, with increased activity promoting the development of type 2 diabetes mellitus by mechanisms that may be sexually dimorphic [29,30,31], and to regulation of coagulation factor VII and von Willebrand factor, with a potential causal role in vascular occlusive disease [32]. Interestingly, although most studied in relation to non-infectious uveitis, interactions between leukocytes and the retinal endothelium also occur in diabetic retinopathy and retinal vein occlusion [33,34], suggesting a role for C2CD4B beyond immune-mediated eye disease.
In contrast to C2CD4B, IRF1 has been extensively researched, regulating expression of multiple genes involved in adaptive and/or innate immunity, as well as inflammatory diseases [35]. Polymorphisms in the IRF1 gene have been associated with Behçet disease, which often presents with uveitis [36]. Consistent with our results, Guo and colleagues showed parallel up-regulation of both IRF1 and ICAM-1 in rat retinal endothelial cells activated by mitochondrial DNA, which is a damage-associated molecular pattern (DAMP) [37]. Although they did not examine the regulatory relationship or leukocyte binding, there is evidence of IRF1 promoting ICAM-1-mediated leukocyte-endothelial cell interactions in other experimental systems, for example, cerebral malaria in *Irf1* gene-deficient mice [38]. However, there is also evidence of vascular endothelial cell heterogeneity in relation to IRF1-mediated effects on interactions with leukocytes: in a study involving human umbilical vein endothelial cells, Yan and co-workers found that IRF1 silencing reduced the expression of vascular cell adhesion molecule (VCAM)-1 but did not alter the expression of ICAM-1 [39].
Unexpectedly, ICAM-1 was induced in cytokine-activated human retinal endothelial cells after knockdown of EGR3 and JUNB. We speculate that loss of the effect of these transcription factors may trigger a feedback mechanism, whereby other activators over-compensate for the change. It is also possible that EGFR3 and JUNB have human retinal endothelial cell-specific repressive activity. Further molecular analyses would be required to characterize this phenomenon. Since our interest was the blockade of the interaction between leukocytes and retinal endothelium, these transcription factors were not studied in the leukocyte binding assay.
A major strength of this work is the use of multiple human retinal endothelial cell isolates. The mouse is commonly employed in research on retinal diseases. Detailed comparisons of the transcriptomes of mouse and human tissues have revealed considerable differences between the two species, leading to the conclusion that “regulatory information in general, such as transcription factor binding, is highly diverged” [40]. Thus, for valid translation, it was important we employed a human system, although this necessarily required in vitro assays. *In* general, published research with human retinal endothelial cells uses a single isolate [18]. However, interindividual variation is an important consideration: for one of five human retinal endothelial cell isolates we studied, IRF1 silencing did not significantly reduce leukocyte binding, even while C2CD4B silencing did. Across this work, we used 28 human retinal endothelial cell isolates generated from women and men donors, to ensure consistent results.
Our approach to identifying priority target transcription factors involved an initial in silico analysis, follow-up molecular studies focused on ICAM-1 expression, and final cellular assays. Thus, from numerous potential targets, we identified two key transcription factors that clearly impacted leukocyte binding to activated human retinal endothelial cells. Notably, for three or two of these five isolates, respectively, targeting C2CD4B or IRF1 did not impact binding under non-activated basal conditions. This observation implies that it may be possible to limit leukocyte binding in the diseased condition primarily, without impacting homeostatic leukocyte trafficking and immune surveillance. Consistently, C2CD4B and IRF1 silencing had limited or no impact on baseline retinal endothelial cell ICAM-1 expression in the molecular studies. There are several ICAM-1 targeted therapeutics that have either been trialed in humans (e.g., alicaforsen, an ICAM-1 anti-sense oligonucleotide [41], and BI-505, an anti-ICAM-1 monoclonal antibody [42]) or are being evaluated in pre-clinical studies (e.g., ICAM-1-specific chimeric antigen receptor T cell therapy [43] and 3DNA nanocarrier-conjugated anti-ICAM-1 antibody [44]); however, these differ from the transcription factor-directed drugging strategy proposed here.
The goal of our research was to identify transcription factors that impacted leukocyte binding to human retinal endothelium and therefore might represent attractive drug targets for non-infectious uveitis involving the posterior segment of the eye. Members of the Ig superfamily coordinate leukocyte firm adhesion to endothelium, as well as initiation of leukocyte diapedesis [45]. Previous research has identified ICAM-1 as the dominant Ig superfamily member for migration of lymphocyte subsets involved in non-infectious uveitis across human retinal endothelium: ICAM-1 blocking antibody reduces human retinal endothelial transmigration of Th1 cells, Th17 cells, and B cells in most humans [46,47]. We have also observed a key role for ICAM-1 in human retinal endothelial cell-monocyte interactions (unpublished data). Therefore, our molecular studies focused on ICAM-1. It is possible that C2CD4B and/or IRF-1 also influence the expression of other retinal endothelial cell adhesion molecules. The Ig superfamily members, VCAM-1 and activated leukocyte cell adhesion molecule (ALCAM), are expressed by human retinal endothelial cells and may be induced by inflammatory cytokines [13,48]. However, transendothelial migration studies show no role for VCAM-1 and ALCAM in lymphocyte migration into the retina in most individuals [46,47].
In summary, we have demonstrated that silencing C2CD4B or IRF1 reduces ICAM-1 expression by cytokine-activated human retinal endothelial cells and decreases leukocyte binding to these endothelial cells. Our observations suggest the possibility of developing therapeutics directed against C2CD4B or IRF1 for non-infectious uveitis involving the posterior eye. Drug formulation remains a challenge, but the eye lends itself to local drug delivery due to physical accessibility and compartmentalization, and there are numerous innovations beyond simple intraocular drug injection [46]. While non-infectious uveitis is our primary interest, the cellular interaction that we have studied occurs in several other retinal diseases—diabetic retinopathy, retinal vein occlusion, and ocular toxoplasmosis [32,33,45]—suggesting broader potential application of our findings.
## 4.1. Selection of Transcription Factor Candidates
An RNA-sequencing dataset that represented the transcriptome of human retinal endothelial cells in resting state, and TNF-α- and IL-1β-activated states (Gene Expression Omnibus, National Center for Biotechnology Information Series link: GSE144785) [18] was the source of transcription factor candidates. Using the normalized read counts, adjusted for donor effect as presented in the description of this dataset, differential gene expression analysis was performed in the EdgeR v3.26.5 package [49]. Differentially expressed genes were defined by a fold-change of at least 2, plus an FDR of less than 0.05 [50]. Cross-referencing these lists identified all transcripts that were up-regulated by both TNF-α and IL-1β at 60 min. The National Library of Medicine (NLM) National Center for Biotechnology Information (NCBI) Gene database [51] and the Johns Hopkins University Online Mendelian Inheritance in Man (OMIM) catalog [52] were used to interrogate this transcript subset to identify those that encoded transcription factors. The NLM NCBI Pubmed bibliographic search engine [51] was then used to locate peer-reviewed published evidence of an association between any of these transcription factors and the induction of ICAM-1 during inflammation. This search used the transcription factor names and ICAM-1 as search terms.
## 4.2. Human Retinal Endothelial Cells
Human retinal endothelial cell isolates were prepared from paired posterior eyecups obtained from the Eye Bank of South Australia (Adelaide, Australia), after removal of the cornea for use in transplantation. None of the donors had a history of uveitis or any other retinal disease. The isolation method, as well as phenotypic descriptions of these cells, has been detailed in previous publications [13,14,15,53]. In brief, the retina was dissected free from the posterior eyecup and digested with collagenase II in varying concentrations (Thermo Fisher Scientific-Gibco, Grand Island, NY, USA). Endothelial cells were purified from the digested tissue by magnetic selection, using Dynabeads M-450 Epoxy magnetic beads (Thermo Fisher Scientific-DYNAL, Oslo, Norway) conjugated to anti-human CD31 antibody (BD Biosciences-Pharmingen, San Diego, CA, USA). The retinal endothelial cells used in the gene expression studies were previously transduced with the LXSN16E6E7 retrovirus (gifted by Denise A. Galloway, Fred Hutchinson Cancer Institute, Seattle, WA, USA) [54], which provided the necessary numbers of cells for those studies; these cells retain an endothelial cell phenotype [13]. Unless otherwise stated, the endothelial cells were cultured in a modified MCDB-131 medium (Merck-Sigma Aldrich, St. Louis, MO, USA) that had been supplemented with $10\%$ fetal bovine serum (FBS) (Thermo Fisher Scientific-Gibco or GE Healthcare-Hyclone, Logan, UT, USA) and endothelial growth factors (EGM-2 SingleQuots supplement, omitting FBS, hydrocortisone and gentamicin; Clonetics, Lonza, Walkersville, MD, USA) at 37 °C and $5\%$ CO2 in air.
## 4.3. Small Interfering RNA, Recombinant Cytokines and Monoclonal Antibodies
The siRNAs were selected from the Silencer Select range produced by Thermo Fisher Scientific-Ambion (Austin, TX, USA): C2CD4B (siRNA ID = s229328), EGR3 (siRNA ID = s4545), FOSB (siRNA ID = s5343), IRF1 (siRNA ID = s7501), JUNB (siRNA ID = s7661), NFKB1 (siRNA ID = s9504), and Negative Control No. 1 siRNA. The GeneID [55] and sequences of the targeted siRNA are presented in Table 2. Human recombinant TNF-α and IL-1β were purchased from R&D Systems (Minneapolis, MN, USA), and used in experiments at a concentration of 5 or 10 ng/mL. Mouse monoclonal anti-human ICAM-1 antibody (clone LB-2) and mouse IgG2bκ isotype negative control primary antibody (clone 27–35) were purchased from BD Biosciences-BD Pharmingen (San Jose, CA, USA), and used at a working concentration of 1 μg/mL.
## 4.4. RNA Silencing
Human retinal endothelial cells were plated for confluence in 12-well (growth area = 3.8 cm2) or 96-well (growth area = 0.32 cm2) multi-well plates in modified MCDB-131 medium, and incubated for 24 h at 37 °C and $5\%$ CO2 in air. The medium was refreshed, and cells were treated with targeted or control siRNA. For each well of the 12-well plates, 1 mL of fresh medium was combined with a transfection mixture, produced by combining 12 pmol of siRNA diluted in 100 μL of Opti-MEM I Reduced Serum Medium (Thermo Fisher Scientific-Gibco) with 100 μL of Opti-MEM I containing 2 μL of Lipofectamine RNAiMAX Transfection Reagent (Thermo Fisher Scientific-Invitrogen, Carlsbad, CA, USA). For each well of the 96-well plates, 90 μL of fresh medium was combined with a transfection mixture, produced by combining 1 pmol of of siRNA diluted in 5 μL of Opti-MEM I Reduced Serum Medium with 5 μL of Opti-MEM I containing 0.3 μL of Lipofectamine RNAiMAX Transfection Reagent. Cell monolayers were incubated for 48 h at 37 °C and $5\%$ CO2 in air, with a change of medium after 24 h, and subsequently treated for 24 h with an MCDB-131 medium with $10\%$ FBS, endothelial growth factors, and either TNF-α or IL-1β, or fresh medium without cytokine as control. Effect of the Silencer Select siRNA on expression of transcription factors was confirmed by RT-PCR (Figure S1). At the end of the treatment period, the medium was removed from cell monolayers in the 12-well plates, and RLT lysis buffer (Qiagen, Hilden, Germany) containing 2-mercaptoethanol was added to each well. The plates were frozen immediately at −80 °C in preparation for RNA extraction. Cell monolayers in the 96-well plates were either used immediately for leukocyte binding assays or washed twice in phosphate-buffered saline with divalent cations (PBS), fixed in $1\%$ paraformaldehyde for 30 min at room temperature, washed again with PBS, and stored under PBS at 4 °C for the membrane ICAM-1 immunoassay. We performed the RNA silencing step prior to the cytokine treatment to provide the cleanest assessment of transcription factor targeting, since we sought to test a therapeutic approach and not to develop a therapeutic agent. This also avoided unnecessary additional manipulations, such as the need to replenish the cytokine multiple times over the course of an experiment.
## 4.5. RNA Extraction and Reverse Transcription
RNA was extracted from the human retinal endothelial cell monolayers using the RNeasy Mini Kit (Qiagen) with optional on-column DNase I digest or TRIzol Reagent (Thermo Fisher Scientific-Ambion) and stored at −80 °C. Nucleic acid concentrations were determined by spectrophotometry on a Nanodrop 2000 (Thermo Fisher Scientific, Wilmington, DE, USA). The cDNA synthesis was performed using the iScript Reverse Transcription Supermix for RT-qPCR (Bio-Rad Laboratories, Hercules, CA, USA), with 100 ng minimum RNA input per reaction. Duplicate reactions were prepared for each sample, and the resulting cDNA was pooled for use in the PCR.
## 4.6. Real-Time Polymerase Chain Reaction
Relative quantitation real-time PCR was performed on a CFX Connect Real-Time PCR System (Bio-Rad Laboratories). In addition to SsoAdvanced Universal SYBR Green Supermix (Bio-Rad Laboratories) and nuclease-free water, each reaction contained 750 nM of the forward and the reverse primer and 2 µL of cDNA, used at up to 1:10 dilution. Cycling conditions included a pre-amplification hold of 95 °C for 30 s, followed by 40 cycles of denaturation at 95 °C for 30 s, annealing at 60 °C for 30 s, and extension and fluorescence reading at 72 °C for 30 s. Melting curves from 70 °C to 95 °C were performed for each run to confirm a single peak was produced for all primer sets, and amplicon sizes were confirmed by agarose gel electrophoresis. Relative expression of the transcripts of interest, normalized to stable reference genes (coefficient of variation less than 0.25)—5′-aminolevulinate synthase 1 (ALAS1), peptidylprolyl isomerase A (PPIA), or ribosomal protein lateral stalk subunit 0 (RPLP0)—was determined by the Pfaffl method [56]. Primer efficiency was greater than $85\%$ for all primer sets, as determined by CFX Manager software v3.0 (Bio-Rad Laboratories) using standard curves generated by serial dilution of purified PCR products. Primer sequences and expected product sizes are shown in Table 3.
## 4.7. Membrane-Bound Intercellular Adhesion Molecule-1 Immunoassay
Fixed human retinal endothelial cell monolayers were washed twice in PBS with $0.1\%$ Tween-20 (PBS-T) for 5 min each. The cell monolayers were blocked in $5\%$ skim milk (Coles, Hawthorn East, Australia) in PBS for 30 min, and incubated with mouse anti-human ICAM-1 or negative control primary antibody in blocking solution for 45 min. After 3 washes in PBS-T, the cell monolayers were incubated with goat anti-mouse IgG (H + L) Alexa Fluor 488-conjugated secondary antibody (Thermo Fisher Scientific-Molecular Probes, Eugene, OR, USA) diluted to 2.5 μg/mL in blocking solution for 30 min, washed 3 times in PBS-T, and counterstained with 300 nM 4′6-diamidino-2-phenylindole-dihydrochloride (Merck-Sigma Aldrich) in PBS for 5 min. All incubations and washes were conducted at room temperature on an OM5 orbital shaker (Ratek, Boronia, Australia; 60 rpm setting). Membrane labeling and nuclear staining were measured on the VICTOR X3 microplate reader (PerkinElmer, Waltham, MA, USA) using 485 nm excitation/535 emission and 355 nm excitation/460 emission filter sets, respectively. Membrane-bound ICAM-1 protein expression was expressed as fluorescence units, adjusted for background immunolabeling detected in wells incubated with negative control primary antibody and corrected for cell number based on the measurement of nuclear staining.
## 4.8. Leukocyte Binding Assay
THP-1 leukocytes (American Type Culture Collection, Manassas, VA, USA) were labeled with 5 µM carboxyfluorescein succinimidyl ester (CFSE, Thermo Fisher Scientific-Invitrogen) in an RPMI-1640 medium (Thermo Fisher Scientific-Gibco), supplemented with $10\%$ FBS and 0.05 mM 2-mercaptoethanol, in complete darkness at 37 °C and $5\%$ CO2 in air for 20 min, followed by an additional 5 min after 1:5 dilution in PBS. The labeled THP-1 leukocytes were resuspended in a modified MCDB-131 medium, held for a minimum of 10 min, and subsequently added to human retinal endothelial cell monolayers in 96-well multi-well plates at 105 cells (100 µL) per well. The plates were rotated for 30 min at room temperature on an OM5 orbital shaker (60 rpm setting). After careful removal of any non-bound THP-1 leukocytes, cell monolayers were washed gently 4 times with PBS and fixed with $10\%$ neutral buffered formalin for 10 min. The formalin was replaced with PBS, and well fluorescence was read on the VICTOR X3 microplate reader using a 485 nm excitation/535 emission filter set. We developed this methodology, involving CFSE staining of leukocytes and measurement of fluorescence by microplate reader, to ensure objective quantitation that reflected leukocyte binding across the entire endothelial cell monolayer and to facilitate high throughput for large numbers of replicate wells (Figure S2).
## 4.9. Statistical Analysis
Data were analyzed in GraphPad Prism (GraphPad Software, La Jolla, CA, USA). Groups were compared by Student’s t-test or one-way or two-way analysis of variance (ANOVA) with Dunnett’s or Tukey’s multiple comparisons test as appropriate to the comparison, implementing pairing when isolates from multiple human donors were involved. In all testing, a statistically significant difference was defined on the basis of a p-value less than 0.05.
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|
---
title: 'Distance to Natural Environments, Physical Activity, Sleep, and Body Composition
in Women: An Exploratory Analysis'
authors:
- Andreia Teixeira
- Ronaldo Gabriel
- José Martinho
- Irene Oliveira
- Mário Santos
- Graça Pinto
- Helena Moreira
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967458
doi: 10.3390/ijerph20043647
license: CC BY 4.0
---
# Distance to Natural Environments, Physical Activity, Sleep, and Body Composition in Women: An Exploratory Analysis
## Abstract
A growing body of evidence indicates that living close to nature is associated with better health and well-being. However, the literature still lacks studies analyzing the benefits of this proximity for sleep and obesity, particularly in women. The purpose of this study was to explore how distance to natural spaces is reflected in women’s physical activity, sleep, and adiposity levels. The sample consisted of 111 adult women (37.78 ± 14.70). Accessibility to green and blue spaces was assessed using a geographic-information-system-based method. Physical activity and sleep parameters were measured using ActiGraph accelerometers (wGT3X-BT), and body composition was assessed using octopolar bioimpedance (InBody 720). Nonlinear canonical correlation analysis was used to analyze the data. Our findings reveal that women living in green spaces close to their homes had lower levels of obesity and intra-abdominal adiposity. We also demonstrated that a shorter distance to green spaces seemed to correlate with better sleep onset latency. However, no relationship was found between physical activity and sleep duration. In relation to blue spaces, the distance to these environments was not related to any health indicator analyzed in this study.
## 1. Introduction
Women play crucial roles within families and society as caregivers, educators, wives, mothers, and members of the community [1]. Despite their important contributions, women often face worse health outcomes than men, which highlights their status as a marginalized and vulnerable group in society. According to Eurostat [2] and the data published by the European Institute for Gender Equality (EIGE), Portuguese women have a higher average life expectancy than men (84.1 years vs. 78 years, respectively), but they also have a lower estimated life quality (2.1 years less) compared to men. The fact that women in Portugal have a longer life expectancy than men does not necessarily mean that their overall health is better. The reason for the difference in life expectancy could be due to a variety of factors, including biological differences, access to healthcare, and lifestyle factors. For example, women may be more likely to experience certain conditions, such as osteoporosis, and may face unique health challenges related to pregnancy, childbirth, and menopause. Women also experience higher rates of depression, anxiety, and other mental health conditions [3,4,5].
Women’s health and well-being also correlate with factors such as physical activity, sleep, and adiposity levels, which are of critical importance to study. According to the latest Eurobarometer on Sport and Physical Activity [6], only $20\%$ of women in Portugal engage in physical exercise or sports activities, and these rates decline with age, particularly among women over 55. As reported by Rossi, et al. [ 7], postmenopausal women tend to have lower levels of moderate- and vigorous-intensity physical activity (PA) and higher levels of light-intensity PA.
In relation to sleep, women typically report poorer quality and more disrupted sleep across various stages of life [8]. Regarding sleep duration, men tend to sleep less than women on average in all age groups, and this difference is based on both biological and social factors [9]. In fact, physiological and hormonal changes that occur during puberty, the menstrual cycle, pregnancy, and menopause can impact women’s sleep architecture and quality [8,10]. Sleep is vital for health and well-being in all age groups and both sexes [11]. It is important for cognitive function, mood, mental health, and cardiovascular, cerebrovascular, and metabolic health [12]. However, there is currently limited knowledge on the association between sleep patterns and living near natural spaces [13,14] and for that reason, we objectively assessed this variable in the present study.
Regarding body composition, in the literature, the differences between genders are well established [15,16]. Women tend to have a higher percentage of fat mass and a lower muscular condition compared to men. Despite the fact that total and central adiposity peaks are reached after the age of 50 years and 60 years in women and men, respectively [17], this increase is especially evident in women due to menopause [18]. Depletion of estrogen during menopause generates an increase in fat mass, resulting in the extravasation of excessive lipid quantities and production of inflammatory cytokines [19], promoting the ectopic deposition of fat in the muscle and various organs.
Regarding the benefits of natural environments, numerous studies have emphasized their significance in improving health outcomes [20,21]. Green spaces, defined as areas dominated by vegetation such as grass, trees, shrubs, and more, including urban and suburban forests, parks, community gardens, and even school yards, have been found to have a positive impact on health [22]. Blue spaces, also referred to as blue infrastructure, consist of all areas dominated by surface water bodies or watercourses [22].
The mechanisms behind the benefits of natural environments include increasing physical activity, reducing psychological stress, promoting social cohesion and interaction, and reducing exposure to urban environmental hazards such as air pollution, noise, and heat islands [23,24,25]. These positive effects are known to contribute to a healthy weight [24,26], as well as to improving sleep duration and quality [27]. It can be speculated that individuals with access to more natural spaces are more likely to exhibit better health outcomes as a result of these positive drivers.
Another important aspect of natural spaces is the presence of biodiversity. The level of biodiversity can serve as an indicator of environmental quality and has been linked to improved health outcomes [28], increased psychological well-being [29], and positive emotions [30].
Many studies from which current research evidence is drawn have several important limitations. *In* general, objective measures of physical activity and sleep are not included and these variables are typically assessed through questionnaires [27,31,32,33]. In the vast majority of past studies, the assessment of total adiposity levels was performed mainly through self-reported weight and height values [34]. Additionally, few studies have differentiated between green and blue spaces. Völker and Kistemann [35] state that the term "blue space" summarizes all visible surface waters in the environment as an analogy to green spaces, rather than as a sub-category. They argue that while green spaces provide diverse forms of perception, such as changes in seasons and the variety of flora and fauna, they cannot attain the same symbolic semantic influence as water. The authors also note that contemplation in green spaces is not as pronounced as in blue spaces, making it important to consider these environments separately.
Several reasons support the relevance of developing studies in the field of natural spaces that involve women exclusively. Firstly, differences in physiology, psychology, nurturing styles, and thinking styles between men and women may impact the aspects of the residential environment that they focus on [36]. Secondly, women experience worse health outcomes than men, often report chronic pain [37], and face more barriers to weight loss [38]. The results of Hologic Global Women’s Health Index [39] show that women in Portugal have a lower overall health and well-being score of 58 points. This index is a comprehensive measure that takes into account key indicators such as access to preventive care, emotional well-being, perceptions of health and safety, and basic needs and personal health. In Portugal, the scores of the five individual indicators range from 37 points for preventive care to 84 points for perceptions of health and safety. The index is scored on a scale of 0 to 100, with a higher score indicating a better overall experience for women in these areas. Additionally, women continue to be responsible for most household chores, childcare, and caregiving, and thus spend more time in the residential environment [40,41]. Furthermore, as reported by Loarne-Lemaire, et al. [ 42], women are also more vulnerable to climate problems due to social, economic, and cultural factors, making them more sensitive to environmental challenges. Lastly, despite not always having easy access to green spaces, living in close proximity to green spaces, having green spaces with features or amenities that are particularly appealing to their needs and preferences, or feeling safe while using them, women still tend to benefit from natural environments more than men [43,44].
Thus, the aim of this study was to investigate the association between the distance to natural spaces, physical activity, sleep, and adiposity levels in adult women.
## 2.1. Study Area
This study was carried out in north Portugal, within the county of Vila Real (Figure 1). The study area presents a Csb type of climate, i.e., a temperate climate with a dry or temperate summer [45]. The landscape is characterized by continuous and discontinuous urban areas intercalated with agricultural patches, forests, and semi-natural vegetation.
Blue spaces, mostly lotic environments, belong to the Corgo River Basin, a tributary on the right bank of the Douro River, which has the largest river catchment in the Iberian Peninsula. The riparian forests of blue spaces, associated with alder (Alnus glutinosa), ash (Fraxinus angustifolia), willow (Salix sp.), and thickets and nettle (Celtis australis), encompass several uncommon and confined plant species [46]. Additionally, these habitats are particularly biodiverse and important for the conservation of endangered endemic aquatic animals. Concerning green spaces, remnant oak forests (Quercus sp.) and heathlands (Erica sp. and Calluna sp.) are particularly relevant for their floristic biodiversity and the occurrence of species of conservation concern (e.g., Veronica micrantha). Anyhow, in the location of the study area, which is in the transition from the “Atlantic” to the “Mediterranean” biogeographic regions, even highly humanized areas such as planted forests, vineyards, pastures, cropland, and vegetable and public gardens contain a diversity of intermingled species and habitats [47].
## 2.2. Ethics Statement
This research was approved by the Ethics Committee of the University of Trás-os-Montes and Alto Douro (Reference No.: Doc51A-CE-UTAD-2020) and adhered to the guidelines set forth in the Declaration of Helsinki. Measures were taken to prevent the transmission of COVID-19 during the study. Participants were fully informed of the purpose, benefits, and potential risks of the study and provided written informed consent.
## 2.3. Study Design and Sample
This cross-sectional study was conducted between December 2020 and February 2021 and included a sample of 111 adult women with an average age of 37.78 ± 14.70 years. The participants were not using any medication that could impact their sleep.
## 2.4. Exposure Assessment
Distance to natural spaces: “Green space” included open, accessible, available recreational and sustainable spaces, in the form of parks, wetlands, conservation reserves, and sports fields, and could comprise forestland, pastureland, or other natural areas at least 1 ha in size. Both public and private gardens were considered green space areas [48,49,50]. Agricultural land was not included because it is not freely accessible. Green space was considered accessible when there is a road, footpaths, trails, walkways, within or near the area (no more than 25 m). Regarding “blue space”, this was defined as an outdoor environment—either natural or manmade—that prominently featured water and was accessible to humans either proximally (being in, on, or near water) or distally/virtually (being able to see, hear, or otherwise sense water) [51]. Addresses were geocoded using the Geocode figure tool with the Esri World Geocoder (ArcGIS Pro). The road network used was the Open Street Map for Portugal, after updating it. The street network was constructed using the Create Network Dataset with the Road Centerlines tool (ESRI, 2022). The green areas were converted to a 5 m pixel raster. These images were later converted into points (at the center of the pixel) to allow the calculation of the distances between points along a street network. Distances were calculated using the Closest Facility tool (Version 3.0, ArcGIS Pro, ESRI, Redlands, CA, USA). In this study, distances of less than 300 m to green spaces and less than 500 m to blue spaces were considered indicative of good access to these environments, based on recommendations from the United Nations [52] and other studies [53,54,55,56].
## 2.5. Health Measures
Body composition: Body height (BH) was measured using a stadiometer (SECA 220, Seca Corporation, Hamburg, Germany). Body mass (BM, kg), fat mass (FM, kg and %), visceral fat area (VFA, cm2), and appendicular skeletal muscle mass (ASMM, kg) were evaluated using the octopolar bioimpedance InBody 720 (Biospace, Seoul, South Korea), with an alternating multifrequency of 1, 5, 50, 250, 500, and 1000 kHz.
This technology employs eight contact electrodes; two are positioned on the palm and thumb of each hand and the other is placed on the front part of the feet and on the heels. According to the criteria specified in the equipment manual [57,58], participants were instructed to [1] not eat food for at least 4 h; [2] not perform moderate-to-vigorous physical activity 12 h before the evaluation; [3] use the bathroom 30 min before the test (to reduce the volume of urine and feces); [4] not consume alcoholic beverages for at least 48 h; and [5] not wear metal jewelry. Before contact with the electrodes, the participants cleaned their hands and feet with antibacterial tissue obtained from the manufacturer. The data were electronically imported into spreadsheets using the software Lookin’Body 120 (Biospace, Seoul, South Korea).
The appendicular skeletal muscle mass index (ASMMI = ASMM/BH2, kg/m2) was used to categorize the muscle condition, and the cut-off value for low muscle mass was <5.7 kg/m2 [59]. The cut-off points for elevated visceral fat area and obesity were as follows: VFA ≥ 100 cm2 [60] and FM ≥ $35\%$ in women [61].
Considering dual-energy X-ray absorptiometry as a reference method, several studies have documented the validity of this equipment in assessing FM (kg and %) and ASMM in adults and older people [62,63,64,65,66]. Several authors have also reported a significant association between VFA estimated using the equipment and that measured using computerized axial tomography [67,68].
Physical activity and sleep: A triaxial accelerometer (ActiGraph GT3X, Actigraph Inc., Pensacola, FL, USA) was used to assess bodily movements 24 h per day for four consecutive days (two weekdays and weekends), including sleep outcomes, and was worn on the non-dominant wrist. Each participant was instructed to remove the device only when engaging in water-based activities (e.g., showering/bathing or swimming). All participants who agreed to wear the accelerometer received standardized oral and written information about using the equipment on the study days. The subjects also filled out a record sheet where they reported their sleep time and non-wear time.
We used a sampling rate of 100 Hz and a 1 min epoch setting. A valid wear day consisted of a device wear time of at least 600 min. The start of the devices was programmed for 6 am on the first day of evaluation and the physical activity records considered 15 s periods. Non-wear time was defined as 90 consecutive minutes of zero counts, with an allowance of 2 min of nonzero counts, provided there were 30 min of consecutive zero-count windows up- and downstream [69].
Activity intensities were then classified using counts per minute (CPM) thresholds: moderate: 1952–5724 CPM and vigorous: ≥5725 CPM [70]. The recommended PA level was at least 150–300 min/week of moderate intensity activity [71]. The number of daily steps was also retrieved from the accelerometer. Sleep patterns were assessed using a previously validated software algorithm based on the Cole–Kripke scoring method [72]. For this study, we describe the following objective sleep measures: total sleep time (TST, hours), sleep onset latency (SOL, min), sleep efficiency (SE, %), fragmentation (SFI, %), sleep onset time, sleep offset time, and sleep midpoint time. The TST is the amount of sleep obtained at night as identified by ActiLife software (hours/night). Sleep duration was categorized into sufficient sleep (≥7 h/night) versus insufficient sleep (<7 h/night), based on the study of Watson et al. [ 12]. The SOL is the duration of the time between when the lights are turned off and the individual tries to sleep until the moment he/she actually falls asleep and was determined by the ActiLife software. The cut-off points considered for SOL was 30 min [73]. SE is the percentage of the sleep period spent sleeping (duration of sleep/duration of time in bed) in percentage format. SE was categorized into low (<$85\%$) or high efficiency (≥$85\%$) [74]. Sleep fragmentation was evaluated as an index that tabulates the frequency of mobility episodes and short sleep bouts between sleep onset time and sleep offset time. It is calculated as the sum of percent mobile and percent 1 min immobile bouts divided by the number of immobile bouts [75].The higher the SFI, the more sleep is disrupted [76]. The sleep onset time and sleep offset time correspond to the first and the last epoch scored, respectively, as sleep in clock time format (HH:MM). The sleep midpoint is clock time that represents the midpoint between the clock time of sleep onset and clock time of sleep offset and was calculated as sleep onset time + ((wake up time-sleep onset time)/2) [77]. Based on a cut-off point for healthy sleep timing per published data, the sleep midpoint variable was then dichotomized as healthy (occurring between 2:00 and 4:00 AM) or early/late (outside of 2:00–4:00 AM) [78,79]. Data were evaluated with ActiLife software (Version 6.13.4, Pensacola, CA, USA).
## 2.6. Demographic Characteristics
According to a prior literature review, we evaluated several demographic variables including age, marital status, and employment status. We also gathered information about the consumption of alcohol and tobacco, as well as the intake of coffee, tea, and caffeine-containing beverages, since these have an impact on sleep.
## 2.7. Statistical Analyses
The numeric data were presented as mean ± standard deviation and qualitative variables were presented as absolute frequencies and percentages. To assess the relative contributions of the accessibility of green and blue spaces, nonlinear canonical correlation analysis (OVERALLS) was used. The OVERALS technique is a nonlinear multivariate exploratory analysis used to deal with variables with different levels of measurement, such as numerical, ordinal, and nominal levels, and that are defined by at least one set of variables. The purpose is to determine how similar these sets of variables are and how the projection of the data in a low-dimensional space can be achieved, accounting, as much as possible, for the variance in the relationships among the sets, and at same time to establish the similarities between the sets. In OVERALS, as in principal component analysis (PCA), eigenvalues are associated with each dimension and indicate to what extent every single dimension accounts for a good fit of data in a low-dimension space and, in a centroid plot, score objects for categories of each variable that are nearest to each other, indicating a higher degree of similarity [80]. We used 13 variables and classified them into 3 sets: [1] distance to green and blue space; [2] accelerometry variables (MVPA and sleep); and [3] body composition variables (%FM and VFA). The labels of the sets, variables, and categories in data, and the symbols that represent the categories in the graphics, are given in Table S1. All analyses were carried out using IBM SPSS, version 27.0 (Chicago, IL, USA).
## 3. Results
A data description is presented in Table 1 and Table 2. The mean age of the sample was 37.78 ± 14.70 years. A total of $0.52.3\%$ of the participants were single and $61.3\%$ were employed. Regarding the factors that influence sleep, $53.2\%$ of the women drank between 1 and 2 cups of coffee a day, some drank alcohol sometimes ($65.8\%$), and most of them did not have a smoking habit ($87.4\%$).
Overall, the majority of respondents had good access to green space and blue space, with $40.5\%$ and $67.6\%$ of people living within 300 m of green and 500 m of blue space, respectively.
Regarding body composition, $39.6\%$ of the women were classified as obese, with over $25\%$ of the sample revealing high levels of intra-abdominal adiposity. Based on the ASMMI values, low muscle mass was identified only in 10 women. The mean MVPA (188.03 ± 118.99 min/week) and steps-per-day values (12712.98 ± 3816.90 steps) identified were within the values recommended in the literature, with about half of the women ($55.9\%$) being classified as physically active. Additionally, $58.6\%$ of the sample had a sleep duration within the recommended range of 7 to 8 h [73,81]. Concerning sleep quality, the sample exhibited efficient sleep, $48.6\%$ took less than 30 min to fall asleep (latency), and $82.9\%$ showed reduced values of the sleep fragmentation index. The average sleep midpoint was 4:19 AM ± 2 h, representative of late sleep chronotypes.
As shown in Figure 2, about half of the women ($51.1\%$) who lived within 300 m of green spaces did not reach the recommended levels of MVPA. For blue spaces, the prevalence of recommended and non-recommended levels of MVPA was similar for both distances analyzed. A large percentage ($68.9\%$) of women living near green spaces exhibited normal total adiposity values. In contrast, a high proportion ($69.4\%$) of obese women were registered as living less than 500 m from blue spaces. Concerning intra-abdominal adiposity levels, a higher percentage ($75.6\%$) of women with normal VFA levels were observed to live close to green spaces compared to those living further away ($68.2\%$). In opposition, there was a higher prevalence of women with high central adiposity levels living closer to blue spaces ($83.3\%$). Of the women who lived closer to green spaces, $47\%$ slept at least 7 h per night, while among those who lived further away, $66.7\%$ exhibited non-recommended hours of sleep. For blue spaces, there was an equitable distribution of recommended and non-recommended TST. A higher prevalence of women living within 300 m of green spaces had recommended sleep onset latency levels compared to women who lived the farthest away ($54.5\%$ vs. $45.5\%$). Those living closer to blue spaces took longer to fall asleep compared to those with recommended levels of sleep onset latency ($53.3\%$ vs. $46.7\%$).
We consider that distance to natural spaces is not an isolated factor that can influence the duration and quality of sleep. Sleep is affected by various social, psychosocial, and environmental factors. Stress [82], socioeconomic status [83], cell phone habits [84], and distance to workplace [85], for example, are known contributors to poor sleep, but these were not the subject of the current study.
Loss values, eigenvalues, and fit values to show the similarities among sets are presented in Table 3. The eigenvalues obtained from this study were 0.427 (first dimension) and 0.403 (second dimension). The eigenvalues of the two dimensions add up to a fit of 0.830, and they can be interpreted as a proportion of explained variance. The fit shows to what extent the nonlinear canonical correlation analysis solution fits the optimally quantified data in regard to the association between the sets. We used two-dimensional solutions, so $\frac{0.830}{2}$ = $41.5\%$ of the variation was calculated in the analysis.
The component loadings presented in Figure 3 give the correlations between object scores and optimally scaled variables, and display the coordinates of the variable points on the graph. Component loadings indicated that visceral fat area and sleep onset latency were the most effective variables in relationships among variable sets, because they were positioned far away from the origin. The other variables (FM, MVPA, and TST) had no intense effect on relationships, because they were positioned close to the origin.
The plot of centroids, labeled by categories, is presented in Figure 4. The results show that living within 300 m of green spaces was associated with recommended levels of sleep onset latency (SOL_R) and lower levels of fat mass (FM_L). Women who lived closer to green spaces tended to have a shorter time transitioning from wakefulness to sleep and lower levels of total body fat. On the other hand, the results show that living near blue spaces (within 500 m) was associated with non-recommended levels of physical activity (MVPA_NR) and sleep duration (TST_NR). This suggests that proximity to blue spaces does not necessarily lead to adequate levels of physical activity and sleep duration.
## 4. Discussion
The purpose of this study was to explore the association between the distance to natural spaces and levels of physical activity, sleep duration and quality, and adiposity levels. According to the last Eurobarometer on Sport and Physical Activity [6], for most European Union countries ($47\%$), including Portugal ($52\%$), natural environments are valued for practicing physical activity (PA), and one of the main reasons reported by Europeans for practicing PA is to improve health. These results support the importance of studying the distance to these natural environments as an indication of health.
Our findings reveal that women with green spaces near their homes showed lower levels of total and intra-abdominal adiposity and better sleep onset latency values. However, we found no relationship between green space with physical activity and sleep time. Regarding blue spaces, the distance to these environments did not relate to any health indicator analyzed in this study (Figure 5).
The methods used to assess exposure to nature vary widely, and typically can be broadly classified into three categories: availability, distance, and visibility [86]. The measurement of proximity to natural environments is often assessed through geographical information systems (GIS), which correspond to the distance by road from the residential location to the nearest natural area [87]. This technology makes it possible to assess the quantity and quality of environments through remote sensing images. There are already recommendations for the distance between homes and the nearest open public space. Nonetheless, these are still not widely accepted. According to the European Commission [88], the currently recommended distance between a residence and the nearest open public space is 300 m. This recommendation might be supported by the fact that 300–400 m is the threshold after which the use of green spaces starts to decline [89]. Konijnendijk [90] recommends that every citizen be able to see three trees, live in a $30\%$ green-covered neighborhood, and be within 300 m of a park. As reported by the same author, benefits thus appear to result from both a combination of the provision in terms of proximity and size or coverage of natural environments. A better understanding of the minimum distance to consider in analyzing green space would help urban planners and public health professionals to improve the way they design green spaces close to the community [91].
In our study, we found that distance to green or blue spaces was not related to levels of moderate-to-vigorous physical activity (MVPA), which contradicts results from previous studies [56,92,93,94,95,96]. It is important to note that in our research, both MVPA and distance to natural spaces were objectively measured, while in prior studies, the distance was typically self-reported. According to Schipperijn, et al. [ 97], self-reported distances tend to be better predictors of the frequency of use of natural spaces than objectively measured distances, which may bias results. In addition, in the studies developed for several authors [56,93,94,95]. the levels of physical activity were self-reported, which is often considered as an important limitation. Additionally, many of the previous studies analyzed both genders without differentiating between the physical activity levels of men and women.
Our contrasting findings could also be related to the fact that previous studies used various definitions of green and blue spaces (as seen in Table S2) and employed different methods to evaluate accessibility to these environments, such as Euclidean or network buffers, average distances, or the distance to the nearest natural environment from a residence. These differences make it difficult to compare results across studies [97,98,99]. Additionally, in our study, we considered a green space to be accessible if there was a road, footpath, trail, or walkway within or near (no further than 25 m) the area. However, this type of public accessibility is not always ensured in other studies.
On the other hand, our results may suggest that living close to natural spaces is not enough to influence levels of physical activity; perhaps it is the enjoyment of these spaces that increases these levels. Russell, et al. [ 100] propose that benefits derived from interactions with natural environments may be obtained through four different channels of human experience: knowing (metaphysical interactions that arise through thinking about an ecosystem, its components, or the concept of an ideal ecosystem, in the absence of immediate sensory inputs); perceiving (remote interactions with ecosystem components, often associated with visual information alone; interacting (physical, active, direct multisensory interactions with ecosystem components that may be cursory and may involve other people); and living within (the everyday, repetitive, pervasive, voluntary, or involuntary interaction with the ecosystem in which one lives).
The lack of associations may be due to the fact that women lack opportunities or feel unsafe accessing green and blue space. Several investigations document that women attribute a higher value to quality and security features of green spaces than men, leading to increased use by women in safer and higher-quality natural environments [101]. In our study the predominant green spaces were forestland, pastureland, and similar green areas, which may possibly not be safe for women to use. Braçe et al. [ 40] highlight that the main differences in men’s and women’s perception of natural environments include lighting, safety, cleanliness, walking routes, bike lanes, shaded areas, recreational areas, off-leash dog areas, playgrounds, drinking fountains, and pleasant views.
When we investigated the relationship between distance to natural spaces and body composition, particularly total and central adiposity levels, we identified numerous gaps in the literature. Firstly, there are limited studies on blue spaces [102,103]. Secondly, many studies do not differentiate between green and blue spaces, often including both in their definition of green spaces. Thirdly, most studies on this topic define obesity by using total adiposity levels. We only found one study that evaluated central adiposity using waist circumference [104]. Despite a growing body of literature on the topic, the relationship between neighborhood greenery and body weight is inconsistent due to the variety of systems used to evaluate green space and health status and the inconsistent results obtained from different evaluation criteria in different research areas [34].
Some studies have found that living closer to green environments is associated with recommended body mass index (BMI) values [55,56,95]. In regard to blue spaces, an 8-year study by Halonen, et al. [ 105] found that living further from waterfronts in urban areas increases the risk of overweight. However, other investigations found no such association [49,106,107]. Most of these studies assessed adiposity levels through self-reported BMI, weight, and height. To the best of our knowledge, there are few studies on this topic that only focus on women. It is important to note that some studies have shown that self-reported BMI and measured BMI have a good correlation [108], with individuals generally overestimating their height and underestimating their weight. Thus, it is not appropriate to use cut-off scores for obesity based on self-reported data, but rather raw BMI scores. This may partially explain the inconsistent results in previous studies.
According to data from the World Obesity Federation Global Obesity Observatory (accessed on 20 December 2022)), approximately $32\%$ of adult women in Portugal are considered obese. In our study, most of the participants had normal levels of total and central adiposity, which might be due to the fact that a large percentage of the women were under the age of 45. Menopause typically occurs between the ages of 45 and 55, and, regardless of age, estrogen depletion is associated with an increase in fat mass, especially in the abdominal region [18].
In our research, total and central adiposity levels were assessed considering octopolar bioimpedance, and we found that women who lived closer to green spaces exhibited better levels of total and intra-abdominal adiposity. As in the present investigation, no association was identified between distance to green spaces and the levels of physical activity, we cannot assume these as mediators of the relationship. We therefore hypothesize that our results may be related to specific environmental factors that may have contributed to normal weight values, such as the diversity of fauna and flora in the study area. In line with some previous research, the presence of native plants [109], a variety of plant species [110,111], and grasslands [112] contribute to the control of adiposity levels.
Furthermore, the existence of wildlife—fish, birds, horses, butterflies, and others—also contributes to normal values of weight [109]. Additionally, within this domain, natural spaces that provide room and infrastructure for the practice of equestrian [113] and/or aquatic activities [109], cycling [114], or running [115] and the existence of outdoor recreation resources [116,117] are also some of the factors that contribute to better weight control. These factors, although not directly measured in our research, could potentially explain our results. Some studies, e.g., [118], have suggested that contact with natural environments, such as forests, increases adiponectin levels and reduces the risk of inflammation and atherosclerosis. It would have been valuable to collect information on the duration and frequency of exposure to nature in our research.
In relation to blue spaces, no association was recorded between living close to them and body fat levels. The limited availability of blue spaces in the study area, and the lack of opportunities for physical activity, could explain the lack of association recorded between living close to them and body fat levels. Elliot et al. [ 102] suggest that individuals living near the coast are healthier than those living inland, showing that the coastal environment may not only offer better opportunities for its inhabitants to be active, but also provide significant benefits in terms of stress reduction.
Another health outcome that has been associated with the residential environment is sleep. An Australian study found that people who live near green spaces exhibited better sleep quality [27]. Similarly, Grigsby-Toussaint, et al. [ 119] reported that access to green spaces has health benefits through increased exposure to natural daylight patterns, helping to maintain circadian rhythms. Triguero-Mas, et al. [ 120] also documented that the methods of global position system (GPS) trajectory measurement, which capture the actual daily green space exposure, had a positive association with sleep quality, while the residential-area-based measurement method does not always have a statistically significant association. In our research, we had no data related with the use of green space, which could have been interesting. In a review conducted by Shin, et al. [ 121], associations of green space with improved sleep outcomes were shown for studies in which participants’ use of green space (gardening or walking) was assessed as well as in studies that only evaluated study participant surroundings (accessibility and availably). In our study, women who lived closer to green environments (and not blue spaces) had shorter periods of sleep onset latency, which is a parameter of sleep quality. Surprisingly, the distance from natural environments was not related to sleep duration.
In our research, sleep was objectively measured using accelerometers. Although there have been validation studies of accelerometers in the assessment of sleep [122], questionnaires are the most commonly used method for measuring sleep quality and quantity [121]. In a systematic review of thirteen studies conducted by Shin, Parab, An and Grigsby-Toussaint [121], only two evaluated sleep patterns using accelerometry. We therefore consider that the variables effectively measured and self-reported may contribute to the differences found in the results.
Another explanation for our findings regarding sleep onset latency is related to the effect of green spaces on mood and mental health and the reduction in noise pollution [123,124]. The latter may contribute to a delay in sleep onset latency and has been associated with nocturnal awakenings [125].
The literature suggests a strong link between stress levels and adiposity levels [126,127], and it is known that high levels of intra-abdominal adiposity can lead to poor sleep quality. Our study found that most of the women had normal levels of total and central adiposity, which may help to explain the positive results we observed regarding sleep onset latency. However, we did not measure stress levels in our research.
We anticipate different outcomes would result if we were to differentiate between women based on their age and reproductive stage. According to some authors [128,129], sleep patterns are known to vary with age due to changes in circadian and homeostatic processes, as well as normal physiological and psychosocial changes. The reproductive aging stage, especially the transition to menopause, also has an impact on women’s sleep. The presence of vasomotor symptoms (such as hot flashes and night sweats) resulting from estrogenic depletion, commonly in conjunction with low mood and anxiety, leads to sleep difficulties [130,131,132]. Our hypothesis is that if we account for these variables, we may be able to identify correlations between sleep duration and other factors.
Our findings can also be attributed to the fact that the women in our study, with an average age of 37.78 ± 14.70 years, were still able to produce recommended levels of melatonin for the regulation of circadian rhythms. According to Karasek [133], melatonin secretion generally decreases with age and becomes significantly lower in most people by the sixth or seventh decade of life [134]. This could be another reason why exposure to green spaces did not have a positive effect on sleep duration in our study.
The lack of a correlation between blue spaces and sleep duration in our study may be due to the fact that the study area consists of rivers with low flow. According to Liu, et al. [ 135], the positive impact of blue spaces on sleep duration and quality is more prominent in coastal areas, which are considered restorative due to the high concentration of negative ions. In a meta-analysis conducted by Georgiou, et al. [ 136], the authors found that proximity to blue spaces or a higher concentration of blue spaces generally had a positive effect on restoration in adult populations, compared to living further away or in areas with a lower concentration of blue spaces. The restorative process triggered by blue spaces could be a key factor in promoting better sleep patterns.
The absence of a connection between distance to green and blue spaces, physical activity levels, and sleep duration in our study could also be due to the fact that people who live in these environments are already physically active and have good sleep habits. According to Goldenberg et al. [ 137], people with higher incomes tend to have greater access to nearby green and blue spaces that are within walking distance of their homes. Furthermore, wealthy residential areas tend to have abundant high-quality green spaces, while lower-income neighborhoods often lack such spaces [138]. According to Markevych et al. [ 23], the health benefits from green spaces can be even more crucial for people with lower socioeconomic status (SES) and those who live in more deprived neighborhoods. People with a lower SES typically have poorer baseline health, limited mobility, and live in areas with higher pollution, which can be addressed through experimental studies, although these are challenging to implement in practice.
The strengths of this study include the use of geocoding to accurately determine individuals’ proximity to natural environments, the use of objectively measured body composition to avoid potential biases associated with self-reported anthropometric measures, and the use of triaxial accelerometers to objectively measure physical activity levels. Additionally, the study sample was limited to women, which is another strength.
Despite the strengths explained previously, several limitations of this study need to be acknowledged. First, our sample size was relatively small, which limits our ability to make inferences and extrapolate our results. It would have been beneficial to have a larger sample size, which would have allowed us to analyze results between groups based on factors such as age or reproductive stage. Second, this study could have also benefited from a more equally adjusted number of demographic variables, such as marital status. Third, the study did not evaluate the use of natural spaces for activities such as gardening, physical activity, or relaxation. Additionally, the proximity to natural environments was assessed without considering differences in the types, sizes, or qualities of these spaces, which could result in a substantial degree of heterogeneity in exposure to recreational opportunities. To better understand the characteristics of these environments that can encourage physical activity and improve sleep and body composition, future research could assess cognitive variables such as knowledge about different species. According to Vanhöfen et al. [ 139], it is important to understand how people perceive their natural surroundings.
## 5. Conclusions
To the best of our knowledge, this study is unique in that it is the first to examine the relationship between physical activity, sleep, body composition, and proximity to natural spaces specifically in women. Our findings suggest that proximity to green spaces is associated with more favorable levels of total and central adiposity and lower sleep onset latency in adult women. However, we did not observe any relationships with health indicators and proximity to blue spaces. Further research is needed to better understand the nature of this relationship, particularly by exploring different metrics of nature exposure. Additionally, future studies should consider analyzing the specific characteristics of these natural environments to inform their design and optimize their use.
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|
---
title: Fat Loss in Patients with Metastatic Clear Cell Renal Cell Carcinoma Treated
with Immune Checkpoint Inhibitors
authors:
- Ji Hyun Lee
- Soohyun Hwang
- ByulA Jee
- Jae-Hun Kim
- Jihwan Lee
- Jae Hoon Chung
- Wan Song
- Hyun Hwan Sung
- Hwang Gyun Jeon
- Byong Chang Jeong
- Seong Il Seo
- Seong Soo Jeon
- Hyun Moo Lee
- Se Hoon Park
- Ghee Young Kwon
- Minyong Kang
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967473
doi: 10.3390/ijms24043994
license: CC BY 4.0
---
# Fat Loss in Patients with Metastatic Clear Cell Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors
## Abstract
The purpose of this study was to determine the prognostic impact of fat loss after immune checkpoint inhibitor (ICI) treatment in patients with metastatic clear cell renal cell carcinoma (ccRCC). Data from 60 patients treated with ICI therapy for metastatic ccRCC were retrospectively analyzed. Changes in cross-sectional areas of subcutaneous fat (SF) between the pre-treatment and post-treatment abdominal computed tomography (CT) images were expressed as percentages and were divided by the interval between the CT scans to calculate ΔSF (%/month). SF loss was defined as ΔSF < −$5\%$/month. Survival analyses for overall survival (OS) and progression-free survival (PFS) were performed. Patients with SF loss had shorter OS (median, 9.5 months vs. not reached; $p \leq 0.001$) and PFS (median, 2.6 months vs. 33.5 months; $p \leq 0.001$) than patients without SF loss. ΔSF was independently associated with OS (adjusted hazard ratio (HR), 1.49; $95\%$ confidence interval (CI), 1.07–2.07; $$p \leq 0.020$$) and PFS (adjusted HR, 1.57; $95\%$ CI, 1.17–2.12; $$p \leq 0.003$$), with a $5\%$/month decrease in SF increasing the risk of death and progression by $49\%$ and $57\%$, respectively. In conclusion, Loss of SF after treatment initiation is a significant and independent poor prognostic factor for OS and PFS in patients with metastatic ccRCC who receive ICI therapy.
## 1. Introduction
While the treatment paradigm for metastatic clear cell renal cell carcinoma (ccRCC) has undergone rapid evolution in the previous three decades, immune checkpoint inhibitors (ICIs) that target and block programmed death 1 (PD-1) or programmed death-ligand 1 (PD-L1) have resulted in further drastic shifts. Despite emerging treatment agents, a large percentage of patients do not respond, leading to early progression and poor prognosis [1]. Although PD-L1 expression, tumor mutational burden, and CD8+ tumor-infiltrating lymphocytes have been recognized as prognostic factors for ICI therapy, several studies on metastatic ccRCC have demonstrated conflicting results [2,3,4,5]. Thus, further studies are warranted to identify prognostic biomarkers and determine which patients are likely to respond.
Renal cell carcinoma (RCC) is a known malignancy in terms of the association between body mass index (BMI), adiposity, and prognosis, showing overall survival (OS) improvement in obese patients [6]. Despite the growing interest in this unexpected survival benefit of obesity, referred to as the “obesity paradox” [7,8], previous studies have focused on baseline features without considering their changes. Given that these changes, especially the rapid loss of adipose tissue, are also reported to have prognostic value in cancer patients [9,10,11], and that ICI therapy can lead to substantial changes in body composition [11], it may be reasonable to assume that these changes are also associated with patient prognoses. However, its prognostic impact in patients with metastatic ccRCC undergoing ICI therapy has not yet been established.
In this study, we aimed to determine the prognostic impact of fat loss determined using cross-sectional imaging after ICI treatment in patients with metastatic ccRCC. We also investigated the association between these changes and molecular features using targeted sequencing and RNA sequencing of tumor samples to understand the underlying biology.
## 2. Results
The study cohort consisted of 44 men and 16 women with a median age of 58 years (interquartile range (IQR), 52–65 years). The median intervals between the pre-treatment CT examination and treatment initiation, and that between the treatment initiation and post-treatment CT were 15.0 days (IQR, 7.0–28.5 days) and 61 days (IQR, 48.5–78.0 days), respectively. During the follow-up period, with a median of 14.1 months (IQR, 7.6–23.3 months), 26 patients ($43.3\%$) died.
The median ΔSF, ΔVF, and ΔTF were −$2.1\%$/month (IQR, −8.8–$2.7\%$/month), $0.2\%$/month (−10.8–$6.7\%$/month), and −$0.4\%$/month (−6.7–$3.5\%$/month), respectively. The optimal cut-off and corresponding log-rank p values for ΔSF, ΔVF, and ΔTF were −$5\%$/month and <0.001, −$8\%$/month and 0.056, and −$10\%$/month and 0.003, respectively, defining SF loss, VF loss, and TF loss as ΔSF < −$5\%$/month, ΔVF < −$8\%$/month, and ΔTF < −$10\%$/month, respectively. According to these criteria, the number of patients exhibiting SF loss, VF loss, and TF loss was 20 ($33.3\%$), 46 ($76.7\%$), and 13 ($21.7\%$), respectively (Figure S1). From SF, VF, and TF, we adopted SF loss to stratify the patients, given that it had the lowest log-rank p value.
The baseline patient characteristics are shown in Table 1, which provides a comparison between patients with and without SF loss. Patients with SF loss were significantly younger (median, 53.5 years vs. 58.5 years, $$p \leq 0.031$$), had lower BMI (median, 21.9 kg/m2 vs. 24.0 kg/m2, $$p \leq 0.003$$) with higher prevalence of underweight ($15.0\%$ vs. $0.0\%$, $$p \leq 0.033$$) and lower prevalence of obesity ($5.0\%$ vs. $32.5\%$, $$p \leq 0.023$$), lower VFI (median, 23.1 cm2/m2 vs. 38.2 cm2/m2, $$p \leq 0.017$$) and TFI (median, 57.8 cm2/m2 vs. 87.7 cm2/m2, $$p \leq 0.042$$), compared with patients without SF loss. There were no other significant differences between the two groups, including the performance status and distribution of the IMDC risk criteria.
## 2.1. Overall Survival
In all patients, the median OS was 24.2 months ($95\%$ CI, 15.9–32.3 months). The OS was significantly shorter in patients with SF loss (median OS, 9.5 months; $95\%$ CI, 7.2–15.9 months) and TF loss (median OS, 12.7 months; $95\%$ CI, 3.6–15.9 months), compared with patients without SF loss (median OS, not reached; $95\%$ CI, not estimated) (log-rank $p \leq 0.001$) or TF loss (median OS, 32.3 months; $95\%$ CI, 17.3–32.3 months) (log-rank $$p \leq 0.003$$), respectively. Patients with VF loss (median OS, 12.7 months; $95\%$ CI, 3.6–17.3 months) numerically showed a shorter OS compared to patients without VF loss that was not statistically significant (median OS, 32.3 months; $95\%$ CI, 16.7–32.3 months) (log-rank $$p \leq 0.056$$) (Figure 1).
In univariable Cox proportional analysis, fat loss in terms of ΔSF, ΔVF, and ΔTF was significantly associated with poor OS. The association remained after adjustment for covariates, demonstrating a $49\%$, $15\%$, and $37\%$ increased risk of death as SF, VF, and TF decreased by $5\%$/month. None of the baseline body composition features or ΔVSR were significantly associated with OS (Table 2).
## 2.2. Progression-Free Survival
In all patients, the median PFS was 9.4 months ($95\%$ CI, 3.3–23.8 months). PFS was significantly shorter in patients with SF loss (median PFS, 2.6 months; $95\%$ CI, 1.7–4.4 months), VF loss (median PFS, 3.3 months; $95\%$ CI, 2.1–9.4 months), and TF loss (median OS, 2.9 months; $95\%$ CI, 1.8–4.4 months) compared with that in patients without SF loss (median PFS, 33.5 months; $95\%$ CI, 9.5–37.7 months) (log-rank $p \leq 0.001$), VF loss (median PFS, 12.7 months; $95\%$ CI, 3.7–33.9 months) (log-rank $$p \leq 0.034$$), or TF loss (median PFS, 12.9 months; $95\%$ CI, 4.6–33.9 months) (log-rank $p \leq 0.001$) (Figure 2).
Univariable Cox proportional analysis showed that fat loss in terms of ΔSF and ΔTF was significantly associated with poor PFS. The association remained after adjustment for covariates, demonstrating a $57\%$ and $36\%$ increased risk of death as SF and TF decreased by $5\%$/month. However, the ΔVF, ΔVSR, and baseline body composition were not significantly associated with PFS (Table 3).
## 2.3. Response to Treatment
Treatment response was evaluable in 59 of the 60 patients. Complete response was achieved in six ($10\%$) patients, partial response in 21 ($35.0\%$) patients, and stable disease in nine ($15.0\%$) patients, resulting in an ORR of $45.0\%$ ($95\%$ CI, 32.1–$58.4\%$). The number of patients achieving complete response, partial response, and stable disease in the first line ICI therapy group was four ($15.4\%$), thirteen ($50.0\%$), and three ($11.5\%$), respectively, whereas in the subsequent nivolumab monotherapy group it was two ($5.9\%$), eight ($23.5\%$), and six ($17.6\%$), respectively. Patients with SF loss had significantly lower ORR to ICI therapy compared to those without SF loss ($10.0\%$ vs. $62.5\%$, $p \leq 0.001$). This association was significant in both the first line ($28.6\%$ vs. $78.9\%$, $$p \leq 0.028$$) and subsequent therapy ($0.0\%$ vs. $47.6\%$, $$p \leq 0.005$$) subgroups. The best overall response differed between patients with and without SF loss, with patients with SF loss showing a lower partial response rate ($10.0\%$ vs. $47.5\%$, $$p \leq 0.004$$) and a higher progressive disease rate ($75.0\%$ vs. $20.0\%$, $p \leq 0.001$). Similarly, a significant difference in response observed between patients with and without SF loss, with patients with SF loss showing a lower rate of clinical benefit ($10.0\%$ vs. $62.5\%$, $p \leq 0.001$) and a higher rate of no clinical benefit ($75.0\%$ vs. $25.0\%$, $p \leq 0.001$) (Table S1).
## 2.4. Interactions of Fat Loss with Line of Treatment and IMDC Risk Criteria
The association between fat loss in terms of ΔSF, ΔVF, ΔTF, and OS was not statistically significantly different between the first-line and subsequent therapy groups or between patients with favorable/intermediate and poor risk groups (p for interaction >0.05). Likewise, the association of fat loss with PFS did not significantly differ between the first-line and subsequent therapy groups, or between patients in the favorable/intermediate and poor risk groups (p for interaction >0.05) (Table S2).
## 2.5. Characteristics of Genomic Alterations and Transcriptomes between Patients with and without SF Loss
In 42 patients for whom targeted sequencing data were available, we identified 17 recurrently altered genes. The most commonly altered genes in this cohort were VHL ($$n = 24$$, $57.1\%$), PBRM1 ($$n = 14$$, $33.3\%$), SETD2 ($$n = 11$$, $26.2\%$), and BAP1 ($$n = 11$$, $26.2\%$), which are generally similar to those previously reported for ccRCC (Figure S2) [12,13]. There was no significant difference in recurrently mutated genes between samples with and without SF loss ($p \leq 0.05$). In addition, tumor mutational burden (TMB) and total indel count were similar between samples from patients with and without SF loss ($p \leq 0.05$) (Figure S3). Among the 60 patients in our study cohort, RNA sequencing data were available for 57. We identified 637 DEGs between patients with ($$n = 19$$) and without SF loss ($$n = 38$$) (Figure 3a, left). *Upregulated* genes in patients with SF loss were associated with cytokinesis and urogenital system development, whereas upregulated genes in patients without SF loss were associated with response to hypoxia, angiogenesis, and cytokine production (Figure 3a, right).
The proportion of immune cells calculated using CIBERSORTx is shown in Figure 3b. Notably, we found that the proportions of CD8 T cells and M1 macrophages were significantly lower in patients with SF loss than in those without SF loss (Figure 3c and Figure S4). We also observed that patients without SF loss had a higher proportion of active immune types, whereas patients with SF loss had higher rates of exhausted immune types (Figure 3d). Consistent with these findings, ssGSEA showed that angiogenesis ($$p \leq 0.003$$) and T-effector ($$p \leq 0.023$$) signatures from the IMmotion150 study [5] were downregulated in patients with SF loss compared with those without SF loss (Figure 4a,b). Moreover, immune-related gene signatures, including T cells ($$p \leq 0.039$$), NK cells ($$p \leq 0.045$$), and chemokines ($$p \leq 0.015$$), from the Javelin101 study [14] were downregulated in patients with SF loss compared to those without SF loss (Figure 4c,d). Additionally, the Th1 score, indicating anti-tumor-associated immunity, was also significantly decreased in patients with SF loss ($p \leq 0.001$) (Figure S5). IHC analysis of representative samples of patients with or without SF loss ($$n = 5$$ for each group) also demonstrated decreased number of CD8+ cells and granzyme B+ cells and lower PD-L1 CPS in patients with SF loss compared to those in patients without SF loss. However, no significant difference was observed in the CD68+ macrophage (pan-macrophage) count or PD-L1 TPS (Figures S6 and S7).
## 3. Discussion
Our analysis of patients with metastatic ccRCC treated with ICI therapy demonstrated that early fat loss after treatment is a significant prognostic factor affecting both OS and PFS. In addition, the associations between fat loss, OS, and PFS were independent of covariates and did not vary according to the line of treatment or the IMDC risk criteria. Although our results regarding the association between fat loss and poor prognosis are comparable to those of previous studies on patients undergoing ICI therapy [9,11], the strength of our study was that it showed that the transcriptomic features of the primary tumor samples differed according to fat loss, which may expand the understanding of the biological perspectives linking fat loss and poor prognosis. Transcriptomic features of primary tumor samples showed that patients with SF loss had an immune-suppressive tumor microenvironment (TME), including fewer CD8 T cells and M1 macrophage cells, a higher proportion of exhausted immune types, and downregulation of the immune-related gene signatures from the IMmotion150 [5] and Javelin101 studies [14] as well as anti-tumor immunity-related Th1 scores compared to those without SF loss.
Our study results also imply that the prognostic effect of subcutaneous and visceral fat differs and that loss of subcutaneous fat is more closely associated with poor prognosis. Since loss of subcutaneous fat could stratify patients according to OS, our analyses of transcriptomic features focused on its relationship with loss of subcutaneous fat. Although Han et al. [ 15] suggested different prognostic impacts of subcutaneous and visceral fat in patients with gastric cancer and cachexia by reporting that low subcutaneous fat was predictive of poor survival, whereas low visceral fat was not, the prognostic value of depletion of these two adipose tissues, their mechanisms, and whether they differ is not clear. In patients with non-small cell lung cancer, Degens et al. [ 9] argued that loss of subcutaneous and visceral fat is predictive of poor prognosis after nivolumab therapy. In a cohort of patients treated with ICI for various cancers, Crombe et al. [ 11] reported that the occurrence of subcutaneous adipopenia after treatment was correlated with a higher risk of progression. Similarly, Imai et al. [ 10] also reported that rapid depletion of subcutaneous fat indicates poor prognosis in hepatocellular carcinoma patients treated with sorafenib. Regarding the prognostic value of SF loss, our results are partially comparable to those of these previous studies. Given that subcutaneous fat is regarded as beneficial for lipid and glucose metabolism [16], depletion of energy reserves with exhaustion induced by cachexia may be a possible explanation for the worse prognosis in patients with SF loss. However, the association of SF loss with PFS and tumor response, as well as OS, indicates that factors other than nutritional or metabolic aspects, such as fat-tumor interaction, may be involved. Meanwhile, the time point at which post-treatment fat loss was evaluated in our study was similar to or earlier than in previous studies [10,11]. However, significant fat loss associated with poor prognosis has been reported to occur even at week 6 of treatment [9]. Therefore, further research is called for to find the ideal and earliest time to detect fat loss, and to elucidate how to improve the prognosis in patients showing early fat loss.
With growing interest in the obesity paradox, accumulating evidence suggests that the TME and its immunological perspective could play a critical role in this phenomenon. Obesity leads to T-cell modulation [17] and affects the balance between macrophage subtypes [18] that interact with tumor cells within the TME. In addition, obesity leads to T-cell dysfunction that is associated with enhanced antitumor efficacy [17] possibly through transcriptional and metabolic reprogramming [19], which has been considered convincing among several suggested hypotheses to address the obesity paradox in patients receiving ICI therapy. Obesity is believed to interact with immune checkpoint receptors in the TME, enhancing the response to ICI therapy and immune cell-mediated tumor regression through increased adipokine secretion from adipose tissue [17]. Notably, the proportional characteristics of immune cells observed in our patients without SF loss were similar to the results of previous studies that reported an increased CD8/CD4 ratio and favored the M1 over the M2 macrophage subtype in obesity [17,18]. Given that CD8 T cells have been recognized to contribute to antitumor immunity in patients with metastatic ccRCC undergoing nivolumab treatment [20] and that the high M2 macrophage subtype is associated with worse prognosis in patients with ccRCC [21], we believe that these different immune cell characteristics may explain why clinical outcomes differed between patients with and without SF loss in the present study. Future studies using imaging mass cytometry, which provides integrated spatial tissue analysis, may help to better understand tumor-immune interactions.
Our finding that patients without SF loss exhibit enrichment of angiogenesis signatures and upregulation of genes associated with response to hypoxia is also in line with a previous study by Sanchez et al. [ 8] which showed that obese patients harbor tumors with greater angiogenesis and peritumoral fat hypoxia. They also suggested that adipocyte hypertrophy leads to hypoxia and subsequent angiogenesis, simultaneously promoting tumor growth and tumor susceptibility to therapy. Although angiogenesis may explain the favorable outcomes in patients without SF loss in this study, there is still no conclusive evidence that angiogenesis is related to improved prognosis when ICI therapy is administered. Enhanced local delivery resulting from increased angiogenesis may be one possible explanation [8] and requires further investigation. Enrichment of chemokines in patients without SF loss may also explain the improved prognosis in these patients, as chemokines are known to participate in the anticancer immune response and inhibit cancer cell proliferation [22].
While the baseline body composition features were not significantly associated with prognosis in our study, patients who lost SF after treatment had a lower BMI and less adipose tissue at baseline. Therefore, the prognostic value of fat loss may be attributed to these baseline characteristics. However, considering that the baseline body composition features were not significantly associated with prognosis in our study, our results imply that their changes may have more prognostic value or at least partly affect prognosis. We also attempted to minimize the effect of reverse causality by adjusting for other relevant covariates. Nonetheless, since patients with SF loss had clinical features and TME status based on RNA sequencing data opposite to those of obese patients in previous studies [17,18], we presume that they may have already been associated with poor prognosis before they lost subcutaneous fat. Considering that obesity is related to TME modulation, the aforementioned association of baseline characteristics raises the suspicion that fat loss after treatment may also have further modulated the TME toward immune exhaustion and downregulation of immune-related signatures, leading to poorer prognosis. However, this causal relationship could not be determined in our study and remains a question as RNA sequencing data after treatment were not available. In this context, evaluating changes in TME status using post-treatment biopsies would also be an interesting topic worth investigating. Proteomic analysis of human blood-derived samples, which can be readily obtained before and after treatment, could be another attractive method to elucidate potential metabolic pathways.
Our study has some limitations. First, it was retrospectively conducted with a relatively small number of patients, which limits the power of the study. In addition, our study cohort was inhomogeneous and comprised both first-line ICI therapy and subsequent nivolumab monotherapy groups. Second, the causal relationship between fat loss and transcriptional characteristics could not be clearly determined. Third, residual confounding, despite multivariable analyses or unmeasured confounding factors, may also be possible. Fourth, the interval between pre-treatment and post-treatment cross-sectional imaging was inconsistent among patients. Fifth, in addition to the fact that RNA sequencing data were only available before treatment, our analysis of TME was based on bulk RNA sequencing, which may have obscured cell-specific transcriptomic features. Further studies using comprehensive single-cell profiling may provide a high-resolution view of cell-specific features, revealing novel TME characteristics [23].
Fat loss after ICI therapy was an independent prognostic factor for poor OS and PFS in patients with metastatic ccRCC. In particular, loss of subcutaneous fat, rather than visceral fat, is associated with poor prognosis. The transcriptomic characteristics, particularly immune-related features of the TME, significantly differed between patients with and without SF loss, implying that it may have the potential to link loss of fat and poor clinical outcomes in these patients. Further investigations are warranted to determine the causal relationship between fat loss and transcriptomic features to unravel how they affect patient survival.
## 4.1. Patients
This study was approved by our institutional review board (Samsung Medical Center, IRB file No. 2021-12-109). This study was conducted in accordance with the principles of the Declaration of Helsinki. We reviewed the electronic medical records of 84 consecutive patients with metastatic ccRCC, who received ICI therapy between November 2016 and April 2021. Among them, 76 patients with available pre-treatment abdominal computed tomography (CT) data were enrolled. After excluding patients with an interval between pre-treatment CT examination and treatment initiation exceeding 90 days ($$n = 4$$) and those who had not undergone post-treatment CT within 150 days after treatment initiation ($$n = 12$$), a total of 60 patients (33 treated with nivolumab monotherapy as a subsequent treatment after first-line tyrosine kinase inhibitor treatment, 27 treated with ICI-based therapy as a first-line treatment, 17 with nivolumab plus ipilimumab, 7 with pembrolizumab plus axitinib, and 3 with avelumab plus axitinib) were finally included in the analysis.
All patients received one of the following treatments: (i) nivolumab monotherapy (3 mg/kg intravenously, every 2 weeks, or 480 mg monthly); (ii) nivolumab (3 mg/kg) plus ipilimumab (1 mg/kg) every 3 weeks intravenously for four cycles, followed by nivolumab monotherapy (3 mg/kg every 2 weeks); (iii) pembrolizumab (200 mg intravenously, every 3 weeks) plus axitinib (5 mg orally, twice daily); or (iv) avelumab (10 mg/kg intravenously, every 2 weeks) plus axitinib (5 mg, orally, twice daily).
Patients continued to receive treatment until disease progression according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria [24] was reached, or toxicity was unacceptable. Computed tomography (CT) or magnetic resonance imaging (MRI) examinations were performed every 3 or 4 months for tumor assessment.
## 4.2. Image Analysis
A board-certified radiologist (JHL) with seven years of experience in musculoskeletal imaging evaluated the body composition features, blinded to patient information. Pre- and post-treatment abdominal CT studies were analyzed using open-source semi-automated software (BMI_CT, version 1.0, Seoul, Republic of Korea; available at https://sourceforge.net/projects/muscle-fat-area-measurement/, accessed on 6 March 2022) based on MATLAB version R2010a (Mathworks Inc., Natick, MA, USA). At the level of the third lumbar vertebra [25], cross-sectional areas (cm2) of skeletal muscle (including the rectus, transverse and oblique abdominal muscles, psoas muscles, and paraspinal muscles), subcutaneous fat, and visceral fat were measured using a semiautomated method [26]. The total fat area was defined as the sum of the areas of subcutaneous and visceral fat. The visceral-to-subcutaneous fat ratio (VSR) was calculated by dividing the area of visceral fat by that of subcutaneous fat. The patients’ body composition areas (cm2) were normalized by dividing by the square of the height (m2) of the patient to calculate the skeletal muscle index (SMI) [27], subcutaneous fat index (SFI), visceral fat index (VFI), and total fat index (TFI) (cm2/m2). Changes in the cross-sectional areas of subcutaneous fat, visceral fat, total fat, and VSR between the pre-treatment and post-treatment CT images were expressed as percentages relative to the baseline measurements and were divided by the interval between the CT scans to calculate ΔSF, ΔVF, ΔTF, and ΔVSR (%/month), respectively.
## 4.3. Clinical Data Collection
Electronic medical records were reviewed to collect baseline demographic, clinical, and laboratory data at the time of starting the therapy of interest. Patients were characterized according to the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk criteria (anemia, thrombocytosis, neutrophilia, Karnofsky performance status <$80\%$, time from diagnosis to treatment <1 year), categorizing them into favorable (score of 0), intermediate (score of 1–2), or poor (score of 3–6) groups [28]. BMI was calculated as the body weight (BW) divided by height squared (kg/m2) and categorized according to criteria for Asia–Pacific classification of underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), or obese (≥25.0 kg/m2) [29]. ΔBW (%/month) was defined as change in BW between the pre-treatment and post-treatment CT divided by the interval between the CT scans.
The primary outcome was OS, which was calculated from the date of treatment initiation to death from any cause. Secondary outcomes included progression-free survival (PFS), objective response rate (ORR), and clinical benefits. PFS was defined as the time from the date of treatment initiation to the date of disease progression or death due to any cause. The ORR was defined as the proportion of patients who achieved partial or complete response. To assess clinical benefit, the response group was defined as follows: (i) clinical benefit: patients with complete response, partial response, or stable disease, if they had any objective reduction in tumor burden lasting at least 6 months; (ii) no clinical benefit: patients with progressive disease within 3 months; and (iii) intermediate benefit: all patients who do not fit into either clinical benefit or no clinical benefit [13]. Tumor response was assessed according to the RECIST Criteria 1.1 [24].
## 4.4. Targeted Sequencing and RNA Sequencing Preprocesses
Targeted sequencing and RNA sequencing data from primary tumor specimens were collected with the patients’ written informed consent as part of another study approved by the Institutional Review Board (Samsung Medical Center, IRB file No. 2020-03-063).
To characterize the genomic landscape of metastatic ccRCC, we used targeted sequencing data to identify recurrently mutated genes in our cohort. Targeted sequencing of 380 cancer-related genes (CancerSCAN version 3.1, Seoul, Republic of Korea, a targeted-sequencing platform designed at Samsung Medical Center) was performed by extraction from formalin-fixed paraffin-embedded (FFPE) pre-treatment tumor tissues. Most samples had a mean coverage of ~900×, with coverage at hotspots well above the mean. Paired-end reads were aligned to the human reference genome (hg19) using BWA (v.0.7.5). SAMTOOLS (v0.1.18), GATK (v3.1-1), and Picard (v1.93) were used for file handling, local realignment, and the removal of duplicate reads, respectively. We recalibrated the base quality scores using GATK BaseRecalibrator based on known single-nucleotide polymorphisms (SNPs) and indels from dbSNP138.
Thereafter, we performed RNA sequencing to evaluate the transcriptome changes. Total RNA from FFPE pre-treatment tumor tissues was extracted using an RNA extraction kit (RNeasy Mini Kit, QIAGEN, Germantown, MD, USA), and RNA integrity was verified using a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). Libraries for sequencing were generated using the QuantSeq 3′ Library Prep Kit (Lexogen Inc., Vienna, Austria) according to the manufacturer’s instructions and sequenced on a HiSeq 2000 system (Illumina, San Diego, CA, USA). The reads were mapped to the hg19 human reference genome using STAR with the default parameters. The number of reads mapped to each gene was calculated using RSEM. Data processing and analysis were performed using R/Bioconductor libraries. We analyzed gene ontology terms to characterize the biological roles of differentially expressed genes (DEGs) using the DAVID website.
## 4.5. Immune Cell Type, Immune Type, and ssGSEA (Single-Sample Gene Set Enrichment Test)
To evaluate immune-related characteristics, the proportion of immune cell types was calculated using CIBERSORTx [30]. Additionally, we evaluated immune types by classifying them into the active immune type and exhausted immune type, considering cancer progression and the patient’s clinical outcomes [31,32,33], using the Nearest Template Prediction (NTP) algorithm based on the expression of active stroma and normal stroma signatures [33]. To perform ssGSEA, we evaluated the association between published immune-related gene signatures and fat loss and identified overall expression patterns of immune-related gene signatures from IMmotion150 [5] and Javelin101 [14] studies. ssGSEA was computed using the “GSVA” package [34]. Additionally, the gene signatures of Th1 and Th2 were derived from Bindea et al. ’s study [35].
## 4.6. Immunohistochemistry
Immunohistochemical (IHC) staining using whole section FFPE tissues was performed with the following primary antibodies: CD8 (clone 4B11, 1:400, Cat#NCL-L-CD8-4B11, Leica Biosystems, Newcastle, UK), Granzyme B (clone 11F1, 1:128, Cat#NCL-L-GRAN-B, Leica Biosystems, Newcastle, UK), CD68 (clone KP1, 1:2000, Cat#M0814, Dako, Glostrup, Denmark), and PD-L1 (clone 22C3, 1:50, Cat#M3653, Dako, Glostrup, Denmark). PD-L1 expression was evaluated as the tumor proportion score (TPS), which was defined as the percentage of tumor cells with PD-L1 expression, and the combined positive score (CPS), which was defined as the number of PD-L1-expressing tumors and immune cells (lymphocytes and macrophages) divided by the number of all tumor cells and multiplied by 100. To quantify CD8-, CD68-, and granzyme B-positive immune cells, up to 10 representative images of each IHC slide were acquired and analyzed by two expert genitourinary pathologists (S.H. and G.Y.K.) using the inForm 2.6 software (Akoya Biosciences, Marlborough, MA, USA). Positive cells were scored out of the total number of cells counted in representative images.
## 4.7. Statistical Analysis
Data are presented as absolute frequencies and percentages for categorical variables and medians and interquartile ranges for continuous variables. The optimal cut-off values to dichotomize ΔSF, ΔVF, and ΔTF were determined at the point that maximized the difference between OS in the two groups identified using the minimum log-rank p value approach [36]. Patients with ΔSF, ΔVF, and ΔTF below the cutoff values were regarded as having SF loss, VF loss, and TF loss, respectively. Patient characteristics were compared between subgroups stratified by fat loss; continuous variables were compared using the Mann–Whitney test, and categorical variables were compared using Fisher’s exact test.
The Kaplan–Meier method with the log-rank test was used to characterize the event-time distributions. A Cox proportional hazards regression model was used to explore whether changes in adiposity or baseline body composition features were associated with survival outcomes. Factors with $p \leq 0.05$ in the univariable tests were adjusted for age (≥65 years/<65 years), sex (male/female), ΔBW (continuously, per $1\%$/month), line of treatment (first line/non-first line), prior nephrectomy (yes/no), Eastern Cooperative Oncology Group (ECOG) performance status (≥$\frac{1}{0}$), IMDC risk criteria (favorable/intermediate/poor), and number of metastases (≥$\frac{2}{1}$) to determine whether their prognostic value was independent of these clinical covariates. The ORR, proportions of each best overall response, and response group according to changes in adiposity were compared using Fisher’s exact test. The interaction term in the Cox proportional hazard regression model was used to determine whether the association between the change in adiposity and OS or PFS differed across the line of treatment and IMDC risk criteria. Fisher’s exact test was used to evaluate whether gene-specific alterations, characteristics of genomic alterations, transcriptomes, and IHC results differed according to fat loss. DEGs were calculated by t-test between samples stratified by fat loss, and cut-off options were $p \leq 0.05$, and fold differences >1.0. Student’s t-test was performed for both groups.
All statistical analyses were performed using SPSS Statistics (version 27.0; SPSS Inc., Chicago, IL, USA), MedCalc® Statistical Software (version 20.023; MedCalc Software Ltd., Ostend, Belgium), and R software (version 4.1.3; The R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at $p \leq 0.05.$
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---
title: Inhibition of Sphingosine-1-Phosphate Receptor 2 by JTE013 Enhanced Alveolar
Bone Regeneration by Promoting Angiogenesis
authors:
- William Lory
- Bridgette Wellslager
- Chao Sun
- Özlem Yilmaz
- Hong Yu
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967474
doi: 10.3390/ijms24043401
license: CC BY 4.0
---
# Inhibition of Sphingosine-1-Phosphate Receptor 2 by JTE013 Enhanced Alveolar Bone Regeneration by Promoting Angiogenesis
## Abstract
Sphingosine-1-phosphate receptor 2 (S1PR2) is a G protein-coupled receptor that regulates various immune responses. Herein, we report the effects of a S1PR2 antagonist (JTE013) on bone regeneration. Murine bone marrow stromal cells (BMSCs) were treated with dimethylsulfoxide (DMSO) or JTE013 with or without infection by an oral bacterial pathogen Aggregatibacter actinomycetemcomitans. Treatment with JTE013 enhanced vascular endothelial growth factor A (VEGFA), platelet derived growth factor subunit A (PDGFA), and growth differentiation factor 15 (GDF15) gene expression and increased transforming growth factor beta (TGFβ)/Smad and Akt signaling. Eight-week-old male C57BL/6J mice were challenged with ligatures around the left maxillary 2nd molar for 15 days to induce inflammatory bone loss. After ligature removal, mice were treated with diluted DMSO or JTE013 in the periodontal tissues 3 times per week for 3 weeks. Calcein was also injected twice to measure bone regeneration. Micro-CT scanning of maxillary bone tissues and calcein imaging revealed that treatment with JTE013 enhanced alveolar bone regeneration. JTE013 also increased VEGFA, PDGFA, osteocalcin, and osterix gene expressions in the periodontal tissues compared to control. Histological examination of periodontal tissues revealed that JTE013 promoted angiogenesis in the periodontal tissues compared to control. Our findings support that inhibition of S1PR2 by JTE013 increased TGFβ/Smad and Akt signaling; enhanced VEGFA, PDGFA, and GDF15 gene expression; and subsequently promoted angiogenesis and alveolar bone regeneration.
## 1. Introduction
Sphingosine-1-phosphate receptor 2 (S1PR2) is one of the five G protein-coupled S1P receptors (S1PR1–5). S1PR2 couples with heterotrimeric Gi, Gq, and G$\frac{12}{13}$ proteins and regulates various cellular signaling pathways, including adenylate cyclase (AC), phospholipase C (PLC), phosphoinositide-3 kinase (PI3K), nuclear kappa-B (NF-κB), mitogen-activated kinases (MAPKs), and the small G proteins Rac and Rho (Figure 1) [1,2,3,4]. Previous studies demonstrated that S1PR2 not only controls S1P signaling, but also regulates inflammatory responses induced by various stimuli [5,6,7,8,9]. Moreover, inhibition of S1PR2 by a S1PR2-specific antagonist (JTE013) reduced serum IL-1β and IL-18 levels in mice when challenged by bacterial lipopolysaccharide (LPS) [5]. Additionally, treatment with JTE013 in mice alleviated colitis induced by deoxycholic acid and dextran sulfate sodium [6] and attenuated lung inflammation stimulated by ovalbumin [7]. In our previous studies using murine bone marrow-derived monocytes and macrophages (BMMs), knockdown of S1PR2 by a S1PR2 shRNA or pharmacological inhibition of S1PR2 by JTE013 decreased the levels of IL-1β, IL-6, and TNF-α inflammatory cytokines induced by the oral bacterial pathogen Aggregatibacter actinomycetemcomitans (Aa) via attenuating bacteria-induced PI3K, NF-κB, and MAPKs signaling [8,9]. Additionally, we demonstrated that treatment with the S1PR2 shRNA or JTE013 suppressed osteoclastogenesis induced by RANKL by down-regulating podosome components (basic cell adhesive units, including PI3K, Pyk2, Src, F-actin, integrin β3, and paxillin levels) [8,9]. In a ligature-induced periodontitis animal model, we also demonstrated that treatment with JTE013 alleviated periodontal inflammation and osteoclastogenesis, subsequently reducing alveolar bone loss compared to vehicle (diluted DMOS) treatment [10]. Furthermore, in an in vitro osteogenesis study, we demonstrated that JTE013 treatment enhanced osteogenesis by promoting vesicle trafficking, Wnt /Ca2+, and bone morphogenetic protein (BMP)/Smad signaling in murine BMSCs cultured in osteogenic media [11]. However, it is unknown if inhibition of S1PR2 by JTE013 can promote bone regeneration in animals following inflammatory bone loss.
Bones are highly vascularized organs with blood vessels that provide oxygen, nutrients, minerals, and secreted factors required for bone formation [12]. Many growth factors are involved in resolving inflammation, repairing tissues, and regenerating bone. These growth factors include vascular endothelial growth factor (VEGF) [12], platelet-derived growth factor (PDGF) [13], and growth differentiation factor 15 (GDF15) [14]. Because osteogenesis is coupled with angiogenesis, VEGF promotes bone repair [12] and delivery of exogenous VEGF promotes angiogenesis and the healing of bone defects [15,16]. In contrast, inhibition of VEGF activity by neutralizing VEGF receptor reduced angiogenesis, bone formation, and callus mineralization in femoral fractures [15]. PDGF is another growth factor expressed in tissues during bone fracture healing [17,18]. PDGF promotes bone healing because the growth factor is both chemotactic and mitogenic for osteoblast progenitor cells [19,20]; moreover, PDGF enhances angiogenesis [21]. Lastly, GDF15, a member of the transforming growth factor β (TGF-β) superfamily, promotes blood vessel growth by stimulating cell cycle progression, thus increasing bone healing [22]. In addition, GDF15 has an anti-inflammatory role [23,24]. In this study, using a ligature-induced, periodontitis model, we aimed to determine if inhibiting S1PR2 by JTE013 could increase gene expression for the growth factors (VEGF, GDF15, and PDGF), enhance angiogenesis, and promote alveolar bone regeneration following inflammatory bone loss.
## 2.1. Treatment with JTE013 Enhanced VEGFA, PDGFA, and GDF15 in Murine BMSCs with or without Aggregatibacter Actinomycetemcomitans Infection
To determine the effects of inhibition of S1PR2 by its specific inhibitor JTE013 on cell growth, we evaluated the mRNA levels of vascular endothelial growth factor A (VEGFA), platelet-derived growth factor subunit A (PDGFA), and GDF15 in murine bone marrow stromal cells (BMSCs) that were treated with vehicle (diluted DMSO) or JTE013 with or without 8 h Aggregatibacter actinomycetemcomitans (Aa) infection. When murine BMSCs were treated with JTE013 for 8 h without Aa infection, the mRNA levels of VEGFA, PDGFA, and GDF15 significantly increased by 2.4-fold, 2.0-fold, and 6.6-fold, respectively, when compared to vehicle controls (Figure 2A–C). In BMSCs treated with JTE013 and infected with Aa for 8 h, the mRNA levels of VEGFA, PDGFA, and GDF15 significantly increased by 13.0-fold, 2.2-fold, and 1.5-fold, respectively, when compared to controls. These findings support that treatment with JTE013 enhanced VEGFA, PDGFA, and GDF15 gene expression in BMSCs with or without Aa infection (Figure 2A–C).
To determine if treatment with JTE013 could potentially generate any off-target effects, murine BMSCs were treated with a S1PR2 shRNA or a control shRNA and the cells were either uninfected or infected with Aa for 8 h. In BMSCs without Aa infection, no significant differences of VEGFA mRNA levels were found between cells treated with the S1PR2 shRNA or the control shRNA (Figure 2D). However, treatment with the S1PR2 shRNA significantly increased PDGFA and GDF15 mRNA levels by 2.5-fold and 1.5-fold, respectively, compared to the control shRNA treatment (Figure 2E,F). In BMSCs infected with Aa for 8 h, treatment with the S1PR2 shRNA significantly increased VEGFA, PDGFA, and GDF15 mRNA levels by 1.2-fold, 3.7-fold, and 1.1-fold, respectively, when compared to controls (Figure 2D–F). The S1PR2 shRNA reduced the mRNA level of S1PR2 by $65.5\%$ in murine BMSC without Aa infection and by $48.0\%$ in murine BMSCs with Aa infection when compared to the control shRNA-treated BMSCs (Figure 2G). These results support that treatment with the S1PR2 shRNA caused effects similar to treatment with JTE013 by promoting gene expression of PDGFA and GDF15. However, the JTE013 treatment also exhibited off-target effects, impacting VEGFA expression in BMSCs without Aa infection when compared to the S1PR2 shRNA treatment.
## 2.2. Treatment with JTE013 Enhanced TGFβ/Smad and Akt Signaling in Murine BMSCs without Aggregatibacter Actinomycetemcomitans Infection
Many signaling pathways are involved in cell growth and bone regeneration, including TGFβ/Smad and PI3K/Akt signaling [25,26,27,28]. To determine which signaling pathways influence the release of growth factors in murine BMSCs, we evaluated p-TGFβ receptor 1 (p-TGFβR1), p-Smad3, p-PI3K, p-Akt, and control actin protein levels in murine BMSCs treated with vehicle or JTE013 with or without 8 h Aa infection. In uninfected murine BMSCs, treatment with JTE013 significantly increased p-TGFβR1 and p-Smad3 protein levels (Figure 3A–C). In murine BMSCs with Aa infection, treatment with JTE013 also increased p-TGFβR1 and significantly increased p-Smad3 levels compared to vehicle controls (Figure 3A–C). These findings support that JTE013 treatment promotes TGFβ/Smad signaling. In uninfected murine BMSCs, similar levels of p-PI3K were observed in murine BMSCs, regardless of treatment with vehicle or JTE013 (Figure 3A,D). Additionally, p-PI3K levels significantly decreased when JTE013-treated BMSCs were infected with Aa compared to vehicle controls (Figure 3A,D). In contrast, p-Akt protein levels significantly increased in uninfected murine BMSCs treated with JTE013 compared to controls (Figure 3A,E). Lastly, no significant differences of p-Akt levels were found in Aa-infected murine BMSCs treated with JTE013 or with vehicle (Figure 3A,E). These findings suggest that Akt signaling might be controlled by multiple signaling pathways. The interplay of PI3K and other signaling pathways perhaps affects p-Akt activity.
To determine if JTE013 treatment could generate off-target effects on TGFβ/Smad and PI3K/Akt signaling, we evaluated p-TGFβR1, p-Smad3, p-PI3K, p-Akt, and control actin protein levels in murine BMSCs treated with a S1PR2 shRNA or a control shRNA. Treatment with the S1PR2 shRNA significantly suppressed S1PR2 protein levels compared to control shRNA treatment (Figure 3G). In uninfected murine BMSCs, treatment with the S1PR2 shRNA significantly suppressed p-TGFβR1 and p-Smad3 protein levels compared to control shRNA treatment (Figure 3F,H,I). In shRNA-treated murine BMSCs that were infected with Aa, there was a reduction in p-TGFβR1 caused by the S1PR2 shRNA; the S1PR2 shRNA significantly suppressed p-Smad3 levels compared to control shRNA treatments (Figure 3F,H,I). These data suggest that JTE013 may have some off-target effects on TGFβ/Smad signaling compared to the S1PR2 shRNA treatment. Although p-PI3K was significantly suppressed by treatment with S1PR2 shRNA in murine BMSCs regardless of Aa infection (Figure 3J), the S1PR2 shRNA significantly enhanced p-Akt in uninfected cells and increased p-Akt in Aa infected cells (Figure 3K). These results support that multiple signaling pathways might regulate Akt signaling in addition to PI3K.
## 2.3. Treatment with JTE013 Enhanced Alveolar Bone Regeneration following Inflammatory Bone Loss Induced by Ligature Placement in Mice
To determine if treatment with JTE013 could promote alveolar bone regeneration following inflammatory bone loss, we placed ligatures around the left maxillary 2nd molar for 15 days in C57BL/6J mice to induce alveolar bone loss. As expected, ligature placement caused severe alveolar bone loss in the distal aspect of the 1st molar, the mesial aspect of the 2nd molar, the distal aspect of the 2nd molar, and the mesial aspect of the 3rd molar areas compared to the right side maxilla without ligature placement (Figure 4B). After the ligatures were removed, mice were treated with JTE013 or vehicle (diluted DMSO) in the periodontal tissues 3 times/week for 3 weeks. Treatment with JTE013 significantly reduced alveolar bone loss, as measured by the distance from cementoenamel junction (CEJ) to alveolar bone crest (ABC), in the distal aspect of the 1st molar, the mesial aspect of the 2nd molar, and the distal aspect of the 2nd molar areas compared to DMSO treatment (Figure 4B,C). We also injected calcein (a fluorochrome that binds to calcium and can be incorporated at sites of mineralization [29]) twice (on day 15 and day 36) to measure bone regeneration after treating with JTE013 or vehicle. Calcein imaging in the periodontal tissues (Figure 4D) shows double calcein signaling, which reflected the two calcein injections during the 3-week interval. Treatment with JTE013 significantly increased calcein width (the distance between the two calcein signals in the periodontal tissues) compared to control (Figure 4D,E). These results support that treatment with JTE013 promoted alveolar bone regeneration following inflammatory bone loss.
## 2.4. Treatment with JTE013 Increased VEGFA, PDGFA, Osteocalcin, and Osterix mRNA Levels in Murine Gingival Tissues and Enhanced Angiogenesis in the Periodontal Tissues
In JTE013-treated periodontal tissues, we observed a 2.8-fold increase in VEGFA and a 2.4-fold increase in PDGFA mRNA levels compared to vehicle-treated controls (Figure 5A). However, no significant differences in GDF15 mRNA levels were found between JTE013-treated animals and DMSO-treated animals. Because our previous study showed that JTE013 increased osteogenic genes, including alkaline phosphatase (ALPL), RUNX Family Transcription Factor 2 (RUNX2), osteocalcin (OCN), and osterix (OSX) in murine BMSCs cultured in osteogenic media [11], we also quantified these osteogenic gene mRNA levels in the periodontal tissues. In JTE013-treated oral mucosa, OCN and OSX mRNA levels were significantly enhanced compared to controls (Figure 5A). However, no significant differences in ALPL and RUNX2 mRNA levels were observed between JTE013-treated group and DMSO-treated group. Hematoxylin & eosin (H&E) staining of periodontal tissues revealed that no inflammation was present in the periodontal tissues (Figure 5B). However, more dilated capillary-like structures were found around alveolar bone tissues in animals treated with JTE013 compared to animals treated with DMSO (Figure 5B). Additionally, immunohistochemical staining of CD31 (a marker of endothelial cells) in the periodontal tissues confirmed that treatment with JTE013 increased the presence of dilated CD31-staining positive capillaries around alveolar bone tissues when compared to animals treated with DMSO (which showed only small capillaries around alveolar bone tissues) (Figure 5C). Overall, our findings support that treatment with JTE013 enhanced VEGFA, PDGFA, OCN, and OSX gene expression and promoted angiogenesis in the periodontal tissues.
## 3. Discussion
In this study, we are the first to demonstrate that inhibition of S1PR2 by JTE013 increased TGFβ/Smad and Akt signaling and significantly enhanced the mRNA levels of VEGFA, PDGFA, and GDF15 in murine BMSCs. Using the ligature-induced periodontitis animal model, we are also the first to demonstrate that treatment with JTE013 enhanced VEGFA, PDGFA, OCN, and OSX mRNA levels; increased angiogenesis in the periodontal tissues; and promoted alveolar bone regeneration when compared to treatment with the control vehicle.
Previously, conflicting results were reported about how S1PR2 regulates VEGF expression and angiogenesis. Inoki et al. [ 30] showed that both S1P and endothelial growth factor (EGF) stimulated the cell migration and the formation of capillary tube-like structures on the Matrigel using mouse vascular endothelial cells. The addition of the S1PR2 specific antagonist (JTE013) further stimulated S1P and EGF-induced migration and capillary tube-like structure formation on the Matrigel [30]. Mechanistically, Inoki et al. [ 30] demonstrated that S1P and EGF enhanced Rac-GTP levels, and the addition of JTE013 further increased the Rac-GTP levels [30]. By implanting Matrigel in the subcutaneous tissues of mice, the researchers also demonstrated that treatment with JTE013 and S1P increased the number of infiltrating cells and the formation of blood vessels in mice [30]. In another preeclampsia (a pregnancy-induced hypertensive disorder) study, Zhang et al. [ 31] showed that treatment with JTE013 reduced blood pressure, attenuated inflammatory cytokines (TNF-α, IL-1β, and IL-6) in placental tissues, and significantly enhanced VEGF levels. However, Chumanevich et al. [ 32] reported that S1PR2 knockout mice or treatment with JTE013 in cells (mouse bone marrow-derived mast cells and human skin mast cells) attenuated S1P-induced VEGFA levels. In another neuroblastoma study, Li et al. [ 33] showed that treatment with JTE013 inhibited tumor growth and VEGF mRNA expression. These differences might arise from the different type of cells being treated with JTE013. Different cells may express different levels of S1P receptors. We previously showed that JTE013 affected the protein expressions of multiple S1P receptors (S1PR1-S1PR5) [11]. Additionally, S1P receptors couple with multiple G proteins and influence multiple signaling pathways. The angiogenesis reaction might depend on the cell type, location of the receptors, and specific signaling pathways that are involved. Previously, we have showed that S1PR2 is highly expressed in murine BMSCs, and treatment with JTE013 enhanced Rac1-GTP level compared to vehicle control [11]. In murine BMMs, treatment with JTE013 also significantly increased VEGFA, PDGFA, and GDF15 compared with vehicle treatment regardless of Aa infection/ Our results are congruent with Inoki et al. [ 30] and Zhang et al. [ 31]’s studies [31] and support that JTE013 treatment promoted VEGF expression and angiogenesis. In the present study, we observed an increase in p-Akt in uninfected murine BMSCs treated with JTE013. Future studies are required to determine if Rac-GTP or other signaling pathways may also be involved in the activation of Akt.
In this study, we showed that treatment with JTE013 had some off-target effects via promoting TGFβ/Smad signaling and enhancing VEGFA expression in murine BMSCs even without Aa infection (Figure 2 and Figure 3). In contrast, treatment with the S1PR2 shRNA in murine BMSCs suppressed TGFβ/Smad signaling and had no significant difference on VEGFA expression in uninfected BMSCs when compared to cells treated with the control shRNA (Figure 2 and Figure 3). The enhanced VEGFA in JTE013-treated cells might be associated with the increased TGFβ/Smad signaling. These results are consistent with our previous study [11], which showed that treatment with JTE013 increased BMP/Smad signaling (a member of TGFβ/Smad signaling), and treatment with the S1PR2 shRNA in murine BMSCs inhibited BMP/Smad signaling.
Previous studies [34,35] demonstrated that activation of Smad signaling is affected by phosphorylation of MAPKs and glycogen synthase kinase-3 (GSK-3). This finding is significant because phosphorylation of MAPKs and GSK-3 can cause ubiquitination and proteasome-dependent degradation of regulatory Smad (R-Smad) [34,35]. We observed a reduction in p-Smad3 in murine BMSCs treated with JTE013 or the S1PR2 shRNA and infected with Aa (Figure 3A,F) compared to JTE013 or the S1PR2 shRNA-treated BMSCs without Aa infection. Perhaps this reduction in p-*Smad is* associated with enhanced phosphorylation of MAPKs induced by Aa, resulting in ubiquitination and degradation of R-Smad. We previously showed that treatment with JTE013 or S1PR2 shRNA suppressed the phosphorylation of MAPKs induced by Aa [8]. Although treatment with S1PR2 shRNA did not increase VEGFA in uninfected murine BMSCs, S1PR2 shRNA did enhance VEGFA in BMSCs with Aa infection (Figure 2D). This result may have been caused by the down-regulation of phosphorylation of MAPKs by the S1PR2 shRNA, perhaps reducing the degradation of R-Smad, thus subsequently increasing VEGFA expression.
Bone regeneration undergoes three continuing and overlapping phases, including inflammation, regeneration, and remodeling [36]. The resolution of inflammation involves recruiting neutrophils and macrophages/monocytes to the injury sites to remove tissue debris and microbial pathogens. VEGF plays an important role in the inflammation phase during bone repair by attracting neutrophils and macrophages [37,38,39], facilitating the resolution of inflammation (Figure 6). During bone regeneration phase, both VEGF and PDGF regulate the migration and proliferation of endothelial cells, and control blood vessel permeability [19,37]. Additionally, VEGF and PDGF stimulate the migration and proliferation of osteoblast progenitors, and promote the differentiation of osteoblasts [19,37]. Furthermore, the increased angiogenesis subsequently provides osteoblast progenitors, nutrients, oxygen, and minerals required for bone mineralization [37]. A previous study [15] demonstrated that VEGF is critical for bone repair because mice treated with a neutralizing VEGF receptor antibody reduced angiogenesis, bone formation, and callus mineralization [15]. In contrast, treatment with an exogenous VEGF enhanced blood vessel formation, ossification, and new bone maturation in animals [15]. In the bone remodeling phase, VEGF and PDGF influence the function of both osteoclasts and osteoblasts, coordinating them to replace woven bone (characterized by a haphazard organization of collagen and mechanically weak) with lamellar bone (characterized by parallel alignment of collagen into sheets and mechanically strong) [21,37]. Thus, VEGF and PDGF play essential roles in the inflammation resolution phase, bone regeneration phase, and bone remodeling phase (Figure 6). GDF15 is another cytokine that promotes angiogenesis as demonstrated by Wang et al. [ 22]. GDF15 enhanced the expression of cyclins D1 and E and promoted the proliferation of human umbilical vein endothelial cells (HUVECs) [22]. Akt was also identified as one of the signaling pathways that induces the production of GDF15 [22]. Treatment with GDF15 promoted neovascularization in the critical-sized calvarial defects of mice compared to sterile saline treatment [22]. In this study, although JTE013 significantly enhanced GDF15 in vitro compared to vehicle treatment in murine BMSCs (Figure 2C), no significant differences of GDF15 mRNA levels were found in the oral mucosa between JTE013-treatment animals and DMSO-treated animals (Figure 5A). Perhaps this finding can be attributed to the different harvest time of cells between the in vitro study (8 h after treatment) and the in vivo study (2 days after JTE013 treatment). Future studies are required to determine if treatment with JTE013 could increase GDF15 mRNA levels within 8 h of treatment.
We previously showed that murine BMSCs treated with JTE013 increased vehicle trafficking when cultured in osteogenic media [11]. Treatment with JTE013 also enhanced the mRNA levels of osteogenic genes (ALPL, RUNX2, OCN, and OSX) in murine BMSCs cultured in osteogenic media [11]. The increases of these osteogenic genes were associated with the enhanced intracellular vesicle trafficking in BMSCs cultured in osteogenic media [11]. In murine BMSCs cultured in DMEM media, JTE013 did not enhance vehicle trafficking when compared to DMSO-treated controls. Because the osteogenic media are a DMEM media supplemented with β-glycerophosphate, dexamethasone, and ascorbic acid, the enhanced vesicle trafficking in JTE013-treated cells might be associated with S1PR2 in response to stimulation with β-glycerophosphate, dexamethasone, or ascorbic acid. In the current study, we only observed a significant increase in OCN and OSX mRNA levels in the periodontal tissues (Figure 5A), which was potentially associated with increased angiogenesis in periodontal tissues, and subsequently promoting bone matrix regeneration and calcification. In the periodontal tissues, we also observed significant increases in VEGFA and PDGFA mRNA levels in mice treated with JTE013. Because VEGF and PDGF promote the resolution of inflammation, angiogenesis, bone regeneration, and the bone remodeling process (Figure 6), treatment with JTE013 increased alveolar bone regeneration following ligature removal.
The following limitations occurred in the present study. First, we only harvested periodontal oral mucosa to analyze the mRNA levels of VEGFA, PDGFA, GDF15, ALPL, RUNX2, OCN, and OSX. Because oral mucosa is the top layer of periodontal tissues, it may not reflect overall gene expression in the entire periodontal tissues. Future studies are needed to determine if treatment with JTE013 could increase these gene expressions in the entire periodontal tissues. Second, because S1PR2 couples with multiple G proteins, we could not determine which G proteins are associated with the activation of TGFβ/Smad and Akt signaling. Future studies are required to determine which G proteins are involved in the activation of TGFβ/Smad and Akt signaling. Finally, images of H&E staining of periodontal tissue sections revealed similar alveolar bone morphology between JTE013-treated mice and vehicle-treated mice. Future studies using an electronic microscope are needed to display more detailed structures of regenerated bone tissues.
In summary, the present study is the first to demonstrate that treatment with the S1PR2 antagonist (JTE013) enhanced TGFβ/Smad and Akt signaling and increased VEGFA, PDGFA, and GDF15 gene expressions in murine BMSCs with or without bacterial infection. Using a ligature-induced periodontitis animal model, we are the first to demonstrate that treatment with JTE013 promoted angiogenesis and alveolar bone regeneration following inflammatory bone loss. Because treatment with JTE013 inhibited inflammation, attenuated osteoclastogenesis, promoted angiogenesis, and induced bone healing, inhibition of S1PR2 by JTE013 may potentially serve as a therapeutic strategy to treat inflammatory bone loss diseases, including periodontitis.
## 4.1. Animals, Cells, and Reagents
Eight-week-old male C57BL/6J mice were purchased from Jackson Laboratory (Bar Harbor, ME, USA). Mice were housed under a 12 h light/12 h dark cycle in specific pathogen-free conditions and had free access to food and water. All animal-related work was conducted in accordance with the guidelines laid down by the National Institute of Health (NIH) in the United States regarding the usage of animals for experimental procedures and approved by the Institutional Animal Care and Use Committee at the Medical University of South Carolina. The murine BMSCs were harvested from 8-week-old C57BL/6J mice by flushing bone marrow cells from femur and tibia. To separate BMMs from BMSCs, bone marrow cells were plated in 15 cm cell culture dishes and incubated at 37 °C with $5\%$ CO2 for 3 days. The suspended BMMs were removed and discarded. After washing plate with PBS, the attached murine BMSCs were cultured in Dulbecco’s Modified Eagle Medium (DMEM) and supplemented with $10\%$ fetal bovine serum (FBS), 100 U/mL penicillin, and streptomycin. JTE013 was purchased from Cayman Chemical (Ann Arbor, MI, USA) and dissolved in DMSO as 20 mM stock solution. DMEM, FBS, penicillin, and streptomycin were purchased from Fisher Scientific (Suwanee, GA, USA). Calcein was obtained from Sigma Aldrich (St. Louis, MO, USA) and dissolved in $2\%$ bicarbonate as 4 mg/mL stock solution.
## 4.2. Generation of ShRNA Lentivirus
The S1PR2 shRNA and control shRNA were generated as previously described [8]. Briefly, human embryonic kidney (HEK) 293 cells were co-transfected with S1PR2 shRNA plasmid DNA or control shRNA plasmid DNA along with lentiviral packaging plasmids pCMV-VSV-G and pCMV-dR8.2 dvpr (Addgene, Cambridge, MA, USA) using lipofectamine 2000 (Life Technologies). Furthermore, 3 days after transfection, the supernatant was collected and ultracentrifuged at 25,000 rpm for 1.5 h at 4 °C using a Beckman Ultracentrifuge (Beckman Coulter, Indianapolis, IN, USA). The viral pellet was resuspended in serum-free DMEM medium, and viral titer was determined with a HIV-1 p24 Antigen ELISA kit (Zeptometrix, Buffalo, NY, USA).
## 4.3. Infection with Aggregatibacter Actinomycetemcomitans
Aggregatibacter actinomycetemcomitans (Aa, ATCC 43718) was purchased from American Type Culture Collection (Manassas, VA, USA), grown on DifcoTM brain heart infusion agar plates (BD Biosciences, Sparks, MD, USA), and cultured in BactoTM brain heart infusion broth (BD Biosciences) for 24 h at 37 °C with $10\%$ CO2. The bacteria were centrifuged, washed with PBS with $5\%$ glycerol, and resuspended in PBS with $5\%$ glycerol. We determined the bacterial concentration by measuring bacterial optical density and by bacterial plating on brain heart infusion agar plates (OD600 = 1, about 3 × 107 colony forming unit, CFU/mL). Murine BMSCs were pre-treated with DMSO or JTE013 (10 μM) for 30 min, and then the BMSCs were either uninfected or infected with Aa (1 CFU/cell) for 8 h.
## 4.4. RNA Extraction, Reverse Transcription, and Quantitative Polymerase Chain Reaction (RT-qPCR)
Total RNA was isolated from cells using TRIzol (Life Technologies, Carlsbad, CA, USA), according to the manufacturer’s instructions. The complementary DNA was synthesized with a TaqMan reverse transcription kit (Life Technologies) using the total RNA (1 μg). Real-time PCR was performed using a StepOnePlus Real-Time PCR System (Life Technologies) as previously described [8]. The following amplicon primers were obtained from Life Technologies: VEGFA (Mm00437306_m1), PDGFA (Mm01205760_m1), GDF15 (Mm00442228_m1), ALPL (Mm00475834_m1), RUNX2 (Mm00501584_m1), OCN (also called bone gamma carboxyglutamate protein BGLAP, Mm03413826_mH), OSX (also called Sp7 transcription factor, Mm04209856_m1), S1PR2 (ARFVPA4), and GAPDH (Mm99999915_g1). Amplicon concentration was determined using threshold cycle values compared with standard curves for each primer. Sample mRNA levels were normalized to control GAPDH expression and expressed as fold changes as compared to control groups.
## 4.5. Protein Isolation and Western Blot Analysis
Proteins were extracted using RIPA cell lysis buffer (Cell signaling Technology, Danvers, MA, USA). The protein concentration was determined with a DCTM protein assay kit (Bio-Rad Laboratories, Hercules, CA, USA). Proteins were loaded on $10\%$ Tris-HCl gels and electro-transferred to nitrocellulose membranes. Membranes were blocked with milk for 1 h at RT and incubated with primary antibody overnight at 4 °C. The p-TGFβR1 (PA5-40298) antibody was obtained from Thermo Fisher Scientific (Waltham, MA, USA). The antibodies to p-Smad3, p-PI3K, p-Akt, p-38, and pan-actin were purchased from Cell Signaling Technology (Danvers, MA, USA). The S1PR2 antibody (SAB4503614) was purchased from Sigma Aldrich (St. Louis, MO, USA). All primary antibodies were incubated at 1:500 or 1:1000 dilution overnight at 4 °C. After washing, the nitrocellulose membranes were incubated at room temperature (RT) for 1 h with horseradish peroxidase-conjugated secondary antibodies (Cell Signaling Technology) and developed using SuperSignal West Pico Chemiluminescent Substrate (Life Technologies Grand Island, NY, USA). Digital images were recorded with a G-BOX chemiluminescence imaging system (Syngene, Frederick, MD, USA). Protein densitometry was analyzed with the GeneTools software (Syngene).
## 4.6. Animal Treatment
To induce inflammatory bone loss, 8-week-old male C57BL/6J mice ($$n = 30$$) were placed with 5.0 silk sutures (Roboz Surgical Instrument Co., MD, USA) around the cervical region of left maxillary second molars under isoflurane anesthesia. The right maxillary teeth were untreated to serve as a baseline control. The ligatures were checked daily and remained in place in all mice during the experimental period. All the ligatures were replaced on day 4 and day 9 to induce minor tissue injury, bacterial colonization, and persistent inflammatory bone loss response. The animals were divided into 3 groups (10 mice/group). The first group of mice were sacrificed on day 15 after ligature placement and both sides of maxillary tissues were harvested to evaluate alveolar bone loss. The ligatures were removed on day 15 for the remaining mice and calcein (20 mg/kg) was injected intraperitoneally (i.p.). The remaining 2 groups of mice were injected with either 8 μL of diluted DMSO ($$n = 10$$) or 8 μL of JTE013 (20 μM, $$n = 10$$) in the lingual periodontal mucosal tissues 3 times/week for 3 weeks. Three weeks after JTE013 or DMSO treatment, the mice were injected with calcein again. Two days after calcein injection, the mice were euthanized. Left lingual oral mucosal tissues (5 mice/group) were harvested and stored in TRIzol reagent (ThermoFisher Scientific, Waltham, MA, USA). Tissues were then homogenized in TRIzol by a bullet blender tissue homogenizer (Next Advance, Inc. Troy, NY, USA) with RNase-free stainless steel beads. Both sides of maxillary tissues (10 mice/group) were fixed in $10\%$ buffered formalin solution for 48 h and later stored in $70\%$ ethanol.
## 4.7. Micro-Computed Tomography (Micro-CT) Scanning and Alveolar Bone Loss Assessment
Maxillary tissues were scanned with a cone-beam µ-CT40 system (Scanco Medical AG, Switzerland). Three dimensional micro-CT images were visualized with the GE Healthcare MicroView software using the isosurface function (with image threshold 7000 and surface quality factor 0.5). The alveolar bone loss was assessed by measuring the distance from cementoenamel junction (CEJ) to alveolar bone crest (ABC) using Adobe Photoshop CS5.1 software. The distance was calibrated by the height of second crown.
## 4.8. Tissue Processing and Staining
Half of the maxillary bone tissues (5/group) were decalcified in a $20\%$ EDTA solution for 4 weeks followed by paraffin embedding. Five µm sagittal paraffin tissue sections were cut, stained with hematoxylin and eosin (H&E) for general histology, and evaluated by an experienced pathologist. The other half of the maxillary tissues (5/group) were processed for methyl methacrylate embedding and ground sectioning to evaluate calcein signaling in the tissues. For immunochemical staining of CD31, the 5 μm paraffin sections were deparaffinized in xylene and rehydrated in graded alcohol series. The sections were incubated in Tris-EDTA buffer for epitope retrieval. After washing with TBST solution 3 times, the slides were blocked with $10\%$ goat serum for 1 h. Then, the slides were incubated with anti-CD31 rabbit monoclonal antibody (Abcam EPR17259, 1:2000) overnight at 4 °C. After washing, the slides were incubated with $3\%$ H2O2 for 15 min at RT to inhibit endogenous peroxidase. After washing, the slides were incubated with goat anti-rabbit biotinylated 2nd antibody (Vector Laboratories, Newark CA, USA, 1:200) for 1 h at RT. The slides were washed and incubated with standard avidin–biotin complex (Vector Laboratories) for 30 min at RT. Antibody binding was revealed using H2O2 as a substrate and diaminobenzidine as chromogen (Vector Laboratories). Counterstaining was performed with hematoxylin. H&E and CD31 images were recorded with an Olympus BX43 microscope and calcein images were recorded with a Zeiss Axio Imager A1 Epifluorescence microscope.
## 4.9. Statistical Analysis
Data were analyzed by unpaired t-test with Welch’s correction. All statistical tests were performed using GraphPad Prism software (GraphPad Software Inc., La Jolla, CA, USA). Values are expressed as means ± standard error of the means (SEM) of 3 independent experiments. A p value of 0.05 or less was considered significant.
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|
---
title: Abalone Viscera Fermented with Aspergillus oryzae 001 Prevents Pressure Elevation
by Inhibiting Angiotensin Converting Enzyme
authors:
- Natsumi Iwamoto
- Asahi Sasaki
- Tomoaki Maizawa
- Naoko Hamada-Sato
journal: Nutrients
year: 2023
pmcid: PMC9967480
doi: 10.3390/nu15040947
license: CC BY 4.0
---
# Abalone Viscera Fermented with Aspergillus oryzae 001 Prevents Pressure Elevation by Inhibiting Angiotensin Converting Enzyme
## Abstract
Abalone viscera, which accounts for more than $20\%$ of the total weight of abalone, is generally regarded as waste in the food industry, and effective methods are required to utilize it productively. In this study, the viscera were fermented with *Aspergillus oryzae* 001 to add functionality. Fermented abalone viscera exhibited increased angiotensin I-converting enzyme (ACE) inhibitory activity and enhanced inhibition of blood pressure elevation in spontaneously hypertensive rats (SHRs). Abalone viscera administration had no significant effect on body weight, food intake, liver and kidney weights, or serum components in SHRs. ACE inhibitors specific to fermented abalone viscera were identified through extraction, fractionation, purification, and analysis. The identified substance was L-m-tyrosine, which non-competitively inhibited ACE and, in a single oral administration, significantly reduced blood pressure in SHRs compared to that in the control. This study identified that abalone viscera fermented by A. oryzae 001 has an inhibitory effect on blood pressure elevation, suggesting its potential use as a functional food. In addition, L-m-tyrosine, a unique substance in fermented abalone viscera, was isolated for the first time as a single ACE-inhibitory amino acid.
## 1. Introduction
The food processing industry produces enormous amounts of organic residues and wastewater, most of which is left unused or untreated [1]. Because waste is detrimental to the environment and human and animal health, various effective ways of using it are being explored [1]. Abalone is one of the most popular and economically important seafood species [2]. Therefore, abalone aquaculture has been increasing worldwide, reaching 190,000 tons per year in 2019 [2,3]. Abalone viscera, which accounts for 15–$25\%$ of the total weight, is usually not considered edible and is discarded, contributing to environmental pollution [4,5]. Therefore, effective ways to utilize it are being explored, including the purification of sulfated polysaccharides and antioxidant peptides with bioactive properties from the viscera [6,7]. In addition, silage made from abalone viscera is rich in protein and promotes growth in animals that consume it [8].
Aspergillus oryzae, one of the koji molds, has been used for over 2000 years for food fermentation and for over 50 years for the production of food enzymes [9]. Therefore, A. oryzae is enlisted in the U.S. Food and Drug Administration’s (FDAs) “Generally Recognized as Safe (GRAS)” list [10]. It produces a variety of enzymes, including proteases and amylases that digest proteins and starch, respectively [11]. The fermented food idli increases gamma-aminobutyric acid content, angiotensin I-converting enzyme (ACE) inhibitory activity, and antioxidant activity through koji mold fermentation [12]. The in vivo evaluation of spontaneously hypertensive rats (SHR) with koji mold fermented idli has confirmed its blood pressure-lowering effect [12]. Koji mold is also used for effective utilization of waste and the residue generated when walnut oil is extracted (walnut meal) has similarly been reported to enhance ACE inhibitory and antioxidant activities via koji molds fermentation [13].
Hypertension is a major risk factor for cardiovascular disease, including coronary artery disease, left ventricular hypertrophy, valvular heart disease, and arrhythmias, such as atrial fibrillation, stroke, and renal failure [14]. It is estimated that 1.4 billion people worldwide have hypertension, but only $14\%$ have it controlled [15]. Angiotensin-converting enzyme (ACE) catalyzes the conversion of angiotensin I to the vasoconstrictor angiotensin II [16]. Synthetic ACE inhibitors, such as captopril, lisinopril and enalapril are currently used to treat hypertension but have significant side effects including taste abnormalities, rash, cough, hypotension, renal failure, and hyperkalemia [17,18]. By contrast, naturally occurring ACE inhibitors are considered safe [19]. To date, ACE inhibitors have been found in fermented milk [20] and fish surimi [21], rabbit meat [19], and ACE inhibitory peptides have been isolated from those foods and other sources.
With the increase in abalone production, the amount of abalone viscera that is discarded is expected to increase in the future. Therefore, more effective ways to utilize abalone viscera will be required than those at present. In previous studies, abalone viscera fermented with the lactic acid bacteria Lacticaseibacillus casei 001 and *Lactiplantibacillus pentosus* SN001 showed ACE-inhibitory activity [22,23]. In addition, single and long-term administration of the fermented products reduced SHR blood pressure and growth inhibition was also not observed. Koji mold, such as lactic acid bacteria, has been traditionally used to ferment foods. In the present study, abalone viscera were fermented with A. oryzae 001, and the inhibitory effect of the fermented product on elevated blood pressure was evaluated.
## 2.1. Material and Reagents
Abalone viscera were sourced from Australian farmed blacklip abalone (Haliotis ruber) and transported frozen. A. oryzae 001 is a proprietary fungus owned by the laboratory. L-tyrosine, soybean oil, isoflurane, tert-butylhydroquinone (TBHQ), L-cysteine, trifluoroacetic acid, sodium hydroxide, o-phthalaldehyde solution, phosphorus acid and kits for cholesterol, HDL-cholesterol, and triglyceride E tests as well as glucose and transaminase CII tests, were purchased from Wako Pure Chemical Industries (Osaka, Japan). Potato dextrose broth (PDB) was purchased from Funakoshi Co., Ltd. (Tokyo, Japan). The ACE Kit-WST was purchased from Dojindo Laboratories (Kumamoto, Japan). β-corn starch, casein, α-corn starch, sucrose, AIN76 mineral mixture, AIN76A vitamin mixture without choline deuterium tartrate, and cellulose were purchased from Oriental Yeast Co., Ltd. (Tokyo, Japan). Acetonitrile and distilled water were purchased from KOKUSAN CHEMICAL Co., Ltd. (Tokyo, Japan). ACE from rabbit lung was purchased from Sigma–Aldrich (St. Louis, MO, USA), and D-tyrosine was purchased from NACALAI TESQUE, Inc. (Kyoto, Japan). DL-o-tyrosine was purchased from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan). L-m-tyrosine was purchased from Cosmo Bio Co., Ltd. (Tokyo, Japan); D-m-tyrosine was purchased from Santa Cruz Biotechnology, Inc. (Dallas, TX, USA), Hip-His-Leu was purchased from Bachem AG (Bubendorf, Switzerland), and His-Leu was purchased from Peptide Institute (Osaka, Japan).
## 2.2. Fermentation by A. oryzae 001
Abalone viscera were lyophilized, ground with a mixer, and sieved through a 500-mesh sieve. The abalone viscera powder was stored at −20 °C until use. A. oryzae 001 was activated from −80 °C storage by pre-culturing with shaking (28 °C, 160 rpm for 24 h) in PDB medium. For fermentation, 1 mL of the pre-cultured bacterial solution was added to 100 mL of distilled water with 1 g of abalone viscera powder, and cultured with shaking (28 °C, 160 rpm, 6 d). The culture supernatant of the ferment was subjected to measurement of ACE inhibitory activity. The ACE-inhibitory activity was determined using the ACE Kit-WST according to the manufacturer’s instructions.
## 2.3. Long-Term Administration Study
Eighteen 14-week-old male SHR/Izm rats (Sankyo Lab Service, Tokyo, Japan) were housed in a room at 25 ± 3 °C, with a humidity of 45 ± $5\%$, and a 12 h light/dark cycle (8:00–20:00 light period). Water (tap water) and feed were provided ad libitum. The rats were pre-reared for 1 week to acclimatize them to the environment. During the pre-rearing period, all rats were fed the same diet. The pre-reared rats were divided into control, fermented, and unfermented groups of 6 rats each and were fed the diets listed in Table 1. The diets for the fermented and unfermented groups contained $5\%$ fermented and unfermented abalone viscera, respectively. Blood pressure was monitored twice a week using a non-observational blood pressure monitor for mice and rats (Blood Pressure Monitor For Mice & Rat Model MK-2000, Muromachi Kikai Co., Tokyo, Japan) six times per animal. Body weight and food intake were also measured on the same day as the blood pressure measurements. Food intake was measured from the difference between the amount fed and the amount remaining. Blood samples were collected under isoflurane anesthesia after one night of fasting, from day 49. After the rats were euthanized, their kidneys and livers were removed for observation and weighing. Blood tests included serum total cholesterol, HDL-cholesterol, glucose, triglyceride, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) activity, as measured using kits (Cholesterol E Test, HDL-cholesterol E Test, Glucose CII Test, Triglyceride E Test, and Transaminase CII Test).
## 2.4. Purification of ACE Inhibitor Components
Fermented and unfermented abalone viscera were extracted with water (50 °C, 125 spm, 60 min) and centrifuged (13,000× g, 10 min). The aqueous extract was ultrafiltered using a centrifugal ultrafiltration unit Vivaspin 20 (Sartorius Stedim Biotech GmbH, Göttingen, Germany) with molecular mass cut-off (MWCO) values of 3, 10, 30, and 100 kDa. Each fraction (<3 kDa, 3~10 kDa, 10~30 kDa, 30~100 kDa, >100 kDa) was concentrated in a rotary evaporator, lyophilized, and measured for ACE-inhibitory activity. The fraction with high ACE-inhibitory activity was dissolved in distilled water, filtered through a 0.22 μm filter, and analyzed using reversed-phase high-performance liquid chromatography (RP-HPLC). ODS-120T (4.6 × 250 mm; Tosoh Bioscience, Tokyo, Japan), and liquid A ($0.1\%$ trifluoroacetic acid solution) and liquid B ($0.1\%$ trifluoroacetic acid solution/acetonitrile = 3:7 mixture) were used as the column and mobile phase, respectively. For elution, a concentration gradient of 0–$50\%$ ratio of solution B was applied over 40 min. The flow rate was set at 1.0 mL/min, and the detector at 220 nm. The peak with high ACE-inhibitory activity, unique to aqueous extracts of fermented abalone viscera, was collected and purified repeatedly. The peak with high ACE-inhibitory activity was subjected to a concentration gradient from $7\%$ to $7.7\%$ acetonitrile, and ACE-inhibitory activity was determined according to the manufacturer’s protocol for the ACE Kit-WST, and IC50 was calculated.
## 2.5. Identification of ACE Inhibitors
The purified fractions were subjected to Edman degradation, and the purified products were identified using mass spectrometry. Phenylthiohydantoin derivatives produced by Edman degradation were separated and analyzed using RP-HPLC using Zaplous alpha, Pep C18 120A (0.1 × 150 mm; AMR, Inc., Tokyo, Japan). The molecular weights of the purified materials were determined using an LTQ-Orbitrap XL mass spectrometer (Thermo Fisher Scientific K.K., Tokyo, Japan). The ACE-inhibitory activities of various isomers (L-tyrosine, D-tyrosine, DL-o-tyrosine, L-m-tyrosine, and D-m-tyrosine) of the purified substance were determined, and the IC50 values were calculated. The structure of the purified product was determined by comparing the IC50 of the purified product with those of the various isomers. To eliminate foreign substances in the reagents, standards of all isomers were purified using HPLC and used for the measurement of ACE-inhibitory activity. HPLC conditions were the same as those used for the purification of ACE inhibitory components.
## 2.6. Estimation of Mode of Inhibition
The mode of inhibition was determined using Lineweaver–Burk plots [19,24]. Briefly, 50 μL of L-m-tyrosine (0, 0.28, and 0.57 mM) and 100 μL of ACE (10 mU/mL) were mixed and incubated at 37 °C for 10 min. After incubation, 25 μL of Hip-His-Leu (2.5, 5.0, 12.5, and 25 mM) was added, and the mixture was incubated at 37 °C for 40 min. Then, 50 μL of 1N NaOH was added, and after the reaction was stopped, 10 μL of $0.2\%$ o-phthalaldehyde solution was added, and the reaction was carried out at room temperature for 15 min under light-shielding conditions. Then, 15 μL of 3.6 M phosphoric acid solution was added, and fluorescence intensity was measured at excitation and emission wavelengths of 360 and 460 nm, respectively. The Michaelis–Menten constant (Km) and the maximum reaction rate (Vmax) were calculated according to the Michaelis–Menten kinetic equation from the Lineweaver–Burk plot.
## 2.7. Single-Dose ACE Inhibitor Study
Male SHRs/Izm rats were purchased and housed as described in Section 2.3. Water (tap water) and feed were provided ad libitum, and the rats were pre-reared for at least 1 week to acclimatize to the environment. L-m-tyrosine solution (pH 3, 10 mg/kg body weight) or water (pH 3) was orally administered to each rat. The pH was adjusted to 3 because L-m-tyrosine is insoluble in water under neutral pH. Blood pressure was measured 6 times per animal before and 2, 4, 6, 8, and 24 h after administration using a non-observational blood pressure monitor.
## 2.8. Statistical Analysis
The blood pressure measurements and weight changes are expressed as mean ± standard error, and other results are expressed as mean ± standard deviation. Rejection was performed using the Smirnov–Grubbs test. Multiple comparisons were performed using the Steel–Dwass test, and comparisons between two test intervals were performed using the t-test. Statistical significance was set at $p \leq 0.05.$
## 3.1. Long-Term Dosing Study
The ACE-inhibitory activity of abalone viscera fermented with A. oryzae 001 was $56.9\%$. Fermentation of abalone viscera using lactic acid bacteria requires the addition of glucose [22,23], while the addition of nutrients was not necessary because koji mold has a variety of enzymes. The results of A. oryzae 001 fermented and unfermented abalone viscera administered to SHRs are shown in Figure 1. No significant differences in food intake were observed between the test groups during the study period (data not shown). The blood pressure of the fermented group was always lower than that of the control group from day 6 onward. The fermented group always had lower blood pressure than the control and unfermented groups from day 12 onward. Blood pressure was significantly lower in the fermented group than in the control group on days 22, 26, 29, 33, 36, and 43, and significantly different from the unfermented group on days 26, 33, and 36. The results of body weight changes are shown in Figure 2. There were no significant differences in the body weights of SHRs between the test groups during the study period. The average kidney and liver weights are shown in Table 2, and the blood test results are shown in Table 3. The control group was reduced to $$n = 5$$ due to hemolysis in the serum of one animal in the control group. There were no significant differences in kidney and liver weights between the study groups and no differences in appearance. Serum total cholesterol, HDL-cholesterol, glucose, triglyceride, ALT, and AST levels were also not significantly different between the groups. Rodents are commonly used as animal models of hypertension, with SHRs being the most commonly used model in studies of essential hypertension in humans [25,26,27]. In the present study, the group treated with fermented abalone viscera had consistently lower blood pressure than the other groups after 12 days of treatment. Thus, fermentation with A. oryzae 001 imparted an antihypertensive effect to abalone viscera, and the fermented viscera was shown to suppress blood pressure elevation in vivo over the long term. In a previous study, L. casei 001 fermented abalone viscera mixed feed suppressed blood pressure elevation of SHRs after 28 days of administration [22], but A. oryzae 001 fermented abalone viscera mixed feed suppressed blood-pressure elevation from day 12 of administration. Therefore, it was suggested that in A. oryzae 001 fermented abalone viscera suppressed blood pressure elevation more rapidly than L. casei 001 fermented abalone viscera in vivo. In a study on L. pentosus SN001 fermented abalone viscera, SHRs were reared for 9 weeks and L. pentosus SN001 fermented abalone viscera mixed feed suppressed blood pressure elevation from week 8 of rearing [23], and no significant differences occurred between the fermented and unfermented groups [23]. The fermented group showed significantly lower blood pressure than the unfermented group during approximately 7 weeks three times (on days 26, 33, and 36) in this experiment. Therefore, A. oryzae 001 fermentation may have greatly enhanced the inhibition of blood pressure elevation in abalone viscera compared to L. pentosus SN001 fermentation. These results suggest that A. oryzae 001 fermentation enhanced the inhibition of blood pressure elevation in abalone viscera, and that the in vivo effect was stronger than that of lactic-acid fermentation. Significant differences in food intake and body weight between test groups have been used as an indicator of growth inhibition in rats [23,28]. Administration of the abalone viscera mixture did not affect food intake or body weight, suggesting that A. oryzae 001 fermented and unfermented abalone viscera did not inhibit SHR growth. Hypertensive patients tend to have lower HDL cholesterol levels and higher triglyceride levels, and total cholesterol levels above a certain level induce a greater increase in blood pressure [29]. Triglyceride and total cholesterol levels in the unfermented group tended to be higher than in the control group. The fermented group tended to have lower total cholesterol than the unfermented group. Abalone viscera contains about $10\%$ lipids in its dried state, and a diet high in lipids increases cholesterol and triglyceride levels [23,30]. A. oryzae has lipolytic enzymes and has used fatty acids as a carbon source in previous reports [31]. Therefore, A. oryzae 001 may be degraded and reduced lipids in abalone viscera, resulting in lower total cholesterol levels in the fermented group than in the unfermented group. Hyperglycemia occurs due to abnormalities in glucose regulation, such as decreased glucose utilization, increased glucose production, and insulin secretion [32]. Since there were no significant differences in glucose concentrations among the study groups, it appears that abalone viscera consumption does not induce hyperglycemia. The reason for the highest glucose concentration in the fermented group may be due to the high carbohydrate-degrading enzyme activity of the fermented abalone viscera, since A. oryzae produces α-amylase and glucoamylase [11]. ALT and AST activities are indicators of liver health [33]. These values and liver appearance and weight displayed no significant differences between the test groups and suggested that abalone viscera consumption does not affect the liver. Long-term administration of feed mixed with idli fermented with A. oryzae suppressed the increase in blood pressure in SHRs from at least day 14, and ALT and AST activities remained normal with no significant difference from control or unfermented for 10 weeks [12]. Thus, it was suggested that fermentation with A. oryzae did not affect ALT and AST activities.
## 3.2. Purification of ACE inhibitors
The IC50 values of each fraction separated by ultrafiltration are listed in Table 4. The fermentation products showed maximum ACE-inhibitory activity and a weight of <3 kDa. Therefore, the <3 kDa fraction was further analyzed. The results of RP-HPLC analysis of the <3 kDa of fermented and unfermented products are shown in Figure 3. The peaks of the fermented and unfermented products were designated as (F1–F7) and (N1–N2), respectively, with larger peaks detected in F1 and F4. F1 was similar in retention time and size to N1, so F4 was considered to be the fermentation product-specific peak; F4 was further purified using RP-HPLC to yield three peaks (F’1–F’3). The ACE-inhibitory activity was not observed in F’1 and F’2, but high ACE-inhibitory activity was observed in F’3 and it was subjected to Edman degradation and mass spectrometry. Protease activity involved in protein degradation was found to be enhanced during fermentation (Data not shown). Abalone viscera is rich in protein and fermentation is used as an effective means of protein hydrolysis [34]. Fermented camel and bovine milk showed maximum ACE-inhibitory activity in the <3 kDa and <5 kDa fractions, respectively [35,36]. Fermented soybean showed strong ACE-inhibitory activity in the lower molecular weight fraction, with maximum activity in the <2 kDa fraction [37]. Those ferments showed higher ACE-inhibitory activity in the smaller molecular weight fractions, consistent with the results of the present study. Previous studies have confirmed that the smaller the molecular weight of a bioactive substance, the easier it passes through the intestinal wall and the more likely it is to exert its effect in vivo [38,39]. Thus, A. oryzae 001 fermented abalone viscera had high ACE-inhibitory activity in the low molecular weight fraction, suggesting that it is effective in vivo.
## 3.3. Identification of ACE Inhibitors
Edman degradation analysis showed that only one tyrosine residue was present in the purified substance. Mass spectrometry results showed an m/z of 182.08122 and a composition of C9H12O3N. Thus, it was clear that the purified product was tyrosine. Since tyrosine has many isomers, the structure was determined by measuring the ACE-inhibitory activity of the various isomers and comparing the IC50 with that of the purified product. The IC50 values for each isomer were as follows: L-tyrosine and D-tyrosine showed less than $50\%$ ACE inhibition at all concentrations. The IC50 values for the ACE inhibition of DL-o-tyrosine, L-m-tyrosine, and D-m-tyrosine were 0.62 mg/mL, 0.31 mg/mL, and 0.96 mg/mL, respectively. L-m-tyrosine was the most potent ACE inhibitor, with an IC50 value comparable to that of the isolated peak. Therefore, F’3 was determined to be L-m-tyrosine. Tyrosine is effective for mental health, and dietary tyrosine intake has been found to improve cognitive performance and physical performance tasks that are sensitive to it [40]. ACE inhibitors of natural origin were present in carp scales, salmon processing by-products, and aosa-derived substances [41,42,43]. Previous studies have reported tyrosine-containing dipeptides [39,44,45] and tripeptides over [46,47] ACE inhibitory peptides. Inhibitory dipeptides with a tyrosine residue at the C-terminus are effective [48,49]. Tyrosine-containing peptides may also be effective because of the high ACE-inhibitory activity of tyrosine. Since the amount of tyrosine contained in abalone viscera is not high [50], it is assumed that it was purified by fermentation.
## 3.4. Estimation of Mode of Inhibition
In previous studies, ACE-inhibitory activity and the mode of inhibition of peptides containing tyrosine were measured [44,51], but the mode of inhibition of tyrosine alone or L-m-tyrosine was not determined. This study is the first to investigate the ACE-inhibitory activity of L-m-tyrosine. Lineweaver–Burk plots of ACE activity at various concentrations of L-m-tyrosine (0, 0.28, 0.57 mM) are shown in Figure 4. Vmax was 5.56, 2.20, and 0.78 mM/min, respectively, and was concentration dependent. Km was similar at 8.15, 8.24, and 8.14 mM, respectively. From the slope and y-axis intercept, Ki was 0.12 mM. Vmax was concentration-dependent while Km was relatively constant suggesting that ACE inhibition by L-m-tyrosine is a non-competitive inhibition. Similar to the present study, several tyrosine-containing dipeptides noncompetitively inhibited ACE [44]. In previous reports, ACE inhibitors obtained by hydrolysis of marine products, such as squid and tuna noncompetitively inhibited ACE [52,53]. However, the ACE inhibitory sites of these substances were not identified [52,53]. In most cases, binding of the inhibitor to the allosteric site of the enzyme results in a pattern of noncompetitive inhibition, but there are exceptions. Because ACE inhibitors from different foods are not identical, detailed inhibition methods require further investigation [54].
## 3.5. Single-Dose Study of ACE Inhibitors in SHRs
The effect of L-m-tyrosine administration on the blood pressure of SHRs is shown in Figure 5. From 4 h after administration, the tyrosine group showed lower blood pressure than the control group. Six and eight hours after administration, the blood pressure of the tyrosine group was significantly lower than that of the control group. In vivo studies indicate that L-tyrosine-supplemented diets prevent blood pressure elevation and tyrosine-containing peptides reduce blood pressure in SHRs in the short term [55,56]. However, there are no reported studies of L-m-tyrosine. L-m-tyrosine was identified as the active component that acted as the ACE inhibitor in this study. Tyrosine isomers differ in structure, resulting in differences in ACE-inhibitory activity, behavior in the body, and digestibility [57]. The smaller the molecular weight of a bioactive substance, the faster it is digested and absorbed, and the more rapidly it exerts its effects in vivo [38,39]; therefore, among the isomers of L-tyrosine, L-m-tyrosine may be the most potent inhibitor of elevated blood pressure in vivo.
## 4. Conclusions
In this study, abalone viscera, an underutilized resource, was fermented with A. oryzae 001, its ACE-inhibitory activity was enhanced, and its inhibition of blood pressure elevation in vivo was confirmed. The ACE inhibitor unique to fermented abalone viscera was identified as L-m-tyrosine, which was found to inhibit ACE in a non-competitive manner. Furthermore, L-m-tyrosine showed antihypertensive effects in vivo. These results revealed that the fermentation of abalone viscera by A. oryzae 001 enhanced the antihypertensive effect of abalone viscera, suggesting that fermented abalone viscera can be utilized as a functional material to inhibit elevated blood pressure. In addition, L-m-tyrosine was found, for the first time, to be an amino acid with high ACE-inhibitory activity.
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|
---
title: Multi-Modal Stacking Ensemble for the Diagnosis of Cardiovascular Diseases
authors:
- Taeyoung Yoon
- Daesung Kang
journal: Journal of Personalized Medicine
year: 2023
pmcid: PMC9967487
doi: 10.3390/jpm13020373
license: CC BY 4.0
---
# Multi-Modal Stacking Ensemble for the Diagnosis of Cardiovascular Diseases
## Abstract
Background: Cardiovascular diseases (CVDs) are a leading cause of death worldwide. Deep learning methods have been widely used in the field of medical image analysis and have shown promising results in the diagnosis of CVDs. Methods: Experiments were performed on 12-lead electrocardiogram (ECG) databases collected by Chapman University and Shaoxing People’s Hospital. The ECG signal of each lead was converted into a scalogram image and an ECG grayscale image and used to fine-tune the pretrained ResNet-50 model of each lead. The ResNet-50 model was used as a base learner for the stacking ensemble method. Logistic regression, support vector machine, random forest, and XGBoost were used as a meta learner by combining the predictions of the base learner. The study introduced a method called multi-modal stacking ensemble, which involves training a meta learner through a stacking ensemble that combines predictions from two modalities: scalogram images and ECG grayscale images. Results: The multi-modal stacking ensemble with a combination of ResNet-50 and logistic regression achieved an AUC of 0.995, an accuracy of $93.97\%$, a sensitivity of 0.940, a precision of 0.937, and an F1-score of 0.936, which are higher than those of LSTM, BiLSTM, individual base learners, simple averaging ensemble, and single-modal stacking ensemble methods. Conclusion: The proposed multi-modal stacking ensemble approach showed effectiveness for diagnosing CVDs.
## 1. Introduction
Cardiovascular diseases (CVDs) are a global public health problem and result from a variety of causes. Since CVDs are a disease of multifactorial origin, it is not easy to accurately and timely diagnose the disease [1]. Early and accurate diagnosis and treatment of CVDs can significantly reduce the risk of morbidity and mortality, making rapid and accurate CVDs prediction a crucial task in healthcare. Cardiologists use various tools to diagnose cardiovascular diseases, and one commonly used tool is the electrocardiogram (ECG). It enables quick detection of abnormal heart rhythms and potential heart disease signs without any intervention [2,3]. In particular, the most frequently used complementary exam for cardiac evaluation is a standard short-duration 12-lead ECG (S12L-ECG) since it can provide a comprehensive evaluation of the heart’s electrical activity. Therefore, the S12L-ECG system is used in various medical environments, ranging from primary care centers to intensive care units [4,5].
However, the ECG signal is complex and can be affected by various factors, such as noises and motion artifacts [6]. This makes it challenging to accurately diagnose CVDs. One way to overcome this limitation is to apply deep learning methods. Deep learning methods have been used to improve the accuracy of CVDs diagnosis by automatically learning features from the ECG signal that are relevant to the CVDs. When it comes to deep learning techniques utilized in detecting CVDs, recurrent neural networks (RNN), long short-term memory (LSTM), and gated recurrent units (GRU) have been extensively employed [7,8,9]. Faust et al. used a bidirectional LSTM (BiLSTM) to identify atrial fibrillation beats in heart rate signals, while Gao et al. proposed an LSTM that incorporated focal loss to address the imbalance of ECG beats [7,8].
Convolutional neural networks (CNN) are also widely used for diagnosing CVDs [10,11,12,13,14,15]. The one-dimensional CNN (1D CNN) model exploits the one-dimensional (1D) structure of the signal, so it can be used on these ECG data without transformation. The 1D CNN models, which are popular representation learning methods of 1D signals, can learn distinguishing hierarchical features when applying 1D convolution to 1D signals. The 1D CNN models hierarchically learn primitive features from the lower layers and complex features through consecutive higher layers [11]. Yildirim et al. constructed a 1D CNN and LSTM combination model to detect four and seven rhythm classes [11]. Mousavi et al. proposed a deep learning architecture that comprises the CNN layers, attention mechanism, and LSTM units to mitigate the occurrence of false alarms for arrhythmia detection in intensive care units [12].
Recently, there have been numerous studies conducted to detect CVDs using two-dimensional CNN (2D CNN) with ECG signals [14,15,16,17,18]. In order to apply a 1D ECG signal to a 2D CNN, the 1D signal needs to be transformed into a two-dimensional (2D) image. Jun et al. obtained 2D ECG images from 1D ECG signals by plotting each ECG beat as a grayscale image to classify eight rhythms [16]. In this study, we refer to the transformed 2D image as an ECG grayscale image. As another method, we can convert the 1D ECG signal into a spectrogram through a short-time Fourier transform (STFT) or a scalogram using wavelet transform. Yildirim et al. fine-tuned 2D CNN models (AlexNet, VGGNet, ResNet, and DenseNet) with spectrogram images to identify diabetes mellitus and Yoon et al. applied a pretrained ResNet-50 model to the ECG scalograms to classify four rhythms [14,15]. We refer to the converted scalograms as scalogram images. As another method, Zhai et al. used a 2D CNN architecture with a dual beat coupling matrix to identify supraventricular ectopic beats and ventricular ectopic beats [17]. 2D CNN has the advantage of utilizing pretrained models that were trained with a large number of images, such as the ImageNet database. In addition, there are several established 2D CNN architectures that have demonstrated good performance, so there is no need to design a new 2D CNN architecture by modifying layers and filters. To take advantage of the 2D CNN mentioned above, we aim to diagnose CVDs by fine-tuning a pretrained ResNet-50 model with scalogram images and ECG gray-scale images.
However, a single CNN model may not be sufficient to accurately predict CVDs, as it may suffer from high bias or high variance [19]. One way to address this problem is through ensemble methods, which combine the predictions of multiple single CNN models. Ensemble methods can lead to an improvement in performance by combining the strengths of multiple models and reducing the influence of their individual weaknesses. Ensemble models can also be used to reduce overfitting and improve generalization [20]. In this study, we aim to reduce the weakness of 12 individual ResNet-50 models for 12 ECG leads and enhance the strengths of those models using a simple averaging ensemble and stacking ensemble with two kinds of input modalities: scalogram image and ECG grayscale image. The two types of input images exhibit different characteristics. To obtain the characteristics of each image, we propose a multi-modal stacking ensemble that can utilize information obtained from different input modalities.
The major contributions of the study are outlined in the following manner: [1] for each lead, the performances of ResNet-50 based on scalogram images was compared to the performance of ResNet-50 based on ECG grayscale images; [2] we demonstrated that the diagnostic performance of the single-modal stacked ensemble was superior to that of the 12 individual base learners and single-modal simple averaging ensemble for both scalogram images and ECG grayscale images; [3] we proposed a multi-modal stacking ensemble that combines base learner predictions obtained from scalogram images and ECG grayscale images and then fed them as inputs to a meta learner; [4] the proposed multi-modal stacking ensemble demonstrated superior performance compared to LSTM, BiLSTM, 12 individual base learners, simple averaging ensemble, and the single-modal stacking ensemble.
## 2.1. Dataset and Preprocessing
The dataset used in this research was a 12-lead ECG database that was collected by Chapman University and Shaoxing People’s Hospital in China [6]. The 12-lead ECG database, which was recorded at a sampling frequency of 500 Hz, consisted of 10,646 patients (including 5956 males) and each recording lasted for 10 s. The ECG database contained 11 different heart rhythms labelled by professional physicians. Since raw ECG signals contain unwanted noise, the following three preprocessing steps were sequentially applied: Butterworth low-pass filter (LPF), local polynomial regression smoother (LOESS) curve fitting, and non-local means (NLM) technique [21,22,23]. The Butterworth LPF was used to remove signals with frequencies above the typical frequency range of a normal ECG (0.5 Hz to 50 Hz). To eliminate the baseline wandering effect that can be caused by respiration, the LOESS curve fitting method was used. The NLM technique was employed to reduce residual noises. Of the ECG data, 58 ECG recordings were excluded from the study since they either only had zeros or some of their channel values were incomplete. Among the remaining 10,588 data, the number of ECG samples with atrial tachycardia (AT), atrioventricular node reentry tachycardia (AVNRT), atrioventricular reentry tachycardia (AVRT), and sinus atrial-to-atrial wander rhythm (SAAWR) categories was only 121, 16, 8 and 7, respectively. The number of samples belonging to the four categories mentioned above was extremely small and hence excluded from this study. Finally, a sum of 10,436 ECG recordings belonging to 7 ECG rhythms were used in this study. Table 1 provides a comprehensive description of 7 distinct ECG rhythms along with the corresponding number of subjects.
## 2.2. Data Transformation
To utilize the 2D CNN model, it is necessary to transform the 1D ECG signal into a 2D image. Among the various methods of converting to a 2D image, we adopted a method of converting to a scalogram and a method of plotting a 1D ECG signal as it is in two dimensions. In this study, we refer to the former image as a scalogram image and the latter image as an ECG grayscale image. An ECG scalogram image is a visual representation of the time-frequency composition of the ECG signal that can reveal important information about the frequency characteristics of the ECG over time. Scalogram images were generated by applying the continuous wavelet transform (CWT) to the ECG recordings. An analytic Morse wavelet with a symmetry parameter of 3 (γ = 3) and a time-bandwidth product of 60 (P2=60) was used to obtain the CWT. The Morse wavelet is perfectly symmetric in the frequency domain and has zero skewness when γ equals 3. The CWT was calculated using 10 voices per octave, a 500 Hz sampling frequency, and a signal length of 5000. The minimum and maximum scales were determined automatically based on the wavelet’s energy spread in time and frequency [24]. In this study, we used the cwt.m function provided by Wavelet Toolbox in Matlab 2020a (https://www.mathworks.com/help/wavelet/ref/cwt.html, accessed on 13 February 2023). The converted scalogram images were saved as 300 × 300 pixel RGB images. For ECG grayscale images, 1D ECG recordings were plotted as grayscale images with a white ECG signal against a black background. The ECG grayscale images were saved as 300 × 300 pixels. Examples of scalogram images and ECG grayscale images for the 7 groups (AFIB, AF, ST, SVT, SB, SR, and SI) are shown in Figure 1.
## 2.3. Ensemble Methods
Ensemble methods are a group of techniques that combine the predictions of multiple models to improve performance. There are many ensemble methods, but this study adopts simple averaging ensemble and stacking ensemble. Simple averaging ensemble obtains the output by averaging the predictions of individual learners directly. Owing to its simplicity and effectiveness, the method is popular in many real applications. The stacking ensemble consists of multiple base learners and a meta-learner. In stacking ensemble, each base learner trains with the original training dataset and then generates new datasets for training a meta learner, where the outputs of the base learner are regarded as input features of the meta learner. The stacking ensemble is powerful because it can combine the strengths of different models to produce a more accurate prediction [20].
Since we propose a multi-modal stacking ensemble method for diagnosing CVDs, we focus on a stacking ensemble. In this study, we use two types of image modalities: scalogram images and ECG grayscale images. The single-modal stacking ensemble refers to the stacking ensemble that utilizes only one image modality, whereas the multi-modal stacking ensemble refers to the stacking ensemble that incorporates two image modalities. We first explain the single modal stacking ensemble, and, to ensure clear understanding, we specifically describe the scenario where the input is a scalogram image. As shown in Figure 2, scalogram images are fed to a pretrained ResNet-50 model to be fine-tuned for each lead. Since we have 12 leads, 12 ResNet-50 base learners are fine-tuned with scalogram images. We can then obtain 12 predictions from 12 individual base learners. Each base learner’s prediction is a 7-dimensional probabilities vector. Considering 12 leads, we can obtain 12 predictions that consist of 7-dimensional probability vectors. Simple averaging ensemble averages the predictions of 12 single-lead ResNet-50 models that were independently trained. On the other hand, the stacking ensemble combines the predictions of the 12 base learners. That is, the 7-dimensional output probability vector from each lead is concatenated to make an 84-dimensional vector. Then the 84-dimensional vector is fed into a meta learner that outputs prediction values for the 7 ECG rhythms. As the meta learner, logistic regression, support vector machines (SVM), random forest, and XGBoost were employed in this study [25,26,27,28]. The single-modal stacking ensemble architecture for ECG grayscale images is the same as described above, except that the input image is an ECG grayscale image instead of a scalogram image.
Single-modal stacking ensemble considers only one input modality, whereas multi-modal stacking ensemble methods take multiple input modalities into account. A detailed description of the multi-modal stacking ensemble is depicted in Figure 3. In this study, scalogram images and ECG grayscale images are used as two input modalities. In the proposed multi-modal stacking ensemble, we combine an 84-dimensional vector obtained from 12 individual base learners using scalogram images and another 84-dimensional vector attained from 12 individual base learners using ECG grayscale images. Combining the vectors obtained from the two modalities results in a 168-dimensional vector. The concatenated 168-dimensional vector contains the characteristics of a scalogram image and an ECG grayscale image. The 168-dimensional vector becomes the new input vector for the meta learner. Similar to the single-modal stacking ensemble, the multi-modal stacking ensemble employed logistic regression, SVM, random forest, and XGBoost as meta learners in this study.
## 2.4. LSTM
LSTM is a type of recurrent neural network and a powerful method for the diagnosis of CVDs. By training an LSTM model on labeled ECG recordings, the model can learn to detect patterns and features that are indicative of CVDs. Due to the sequential nature of ECG recordings, LSTM is well-suited for this task as it can capture long-term and temporal dependencies between individual ECG recordings. In this study, LSTM was applied to the same ECG dataset to demonstrate the effectiveness of the proposed multi-modal stacking ensemble method. In experiment settings, LSTM has numerous hyperparameters; however, this study chose to set the batch size, hidden size, dropout, and number of epochs to fixed values of 128, 128, 0.2, and 100, respectively. The Adam optimizer was used with β1 set to 0.9 and β2 set to 0.999 to optimize the LSTM model. To determine the learning rate and number of layers, a grid search was performed where the learning rates were evaluated over the range of (1e-3, 1e-4, 5e-5, 1e-5), and the number of layers was tested within the range of [2, 3, 4]. The best hyperparameter was chosen by selecting the one with the highest accuracy on the validation dataset. To prevent the vanishing gradient problem, the ECG signal sampled at 500 Hz was downsampled to 250 Hz. LSTM was trained for all 12 leads at the same time since a 12-lead ECG signal can be represented as a sequence of a 12-dimensional vector with a length of T time sample. On the other hand, ResNet-50 was trained individually for each lead. BiLSTM can be seen as a variation of LSTM. Unlike LSTM, BiLSTM can analyze input sequences both forward and backward, which gives it the ability to comprehend information from past and future time-steps and identify complex inter-dependencies in the data. BiLSTM was also experimented under the same conditions.
## 2.5. ResNet-50 Model and Machine Learning Algorithms
ResNet is a deep neural network architecture introduced in 2015. It was developed to address the issue of vanishing gradients that arises in deep networks. This problem is resolved by adding skip connections between the layers. The skip connection is a type of feedforward network that involves a shortcut connection. It adds new inputs to the network and yields new outputs, enabling the network to learn the residual mapping instead of the original mapping. ResNet has achieved state-of-the-art accuracy in a variety of computer vision tasks and became one of the most popular architectures for image classification and computer vision tasks [29]. For this reason, we used a pretrained ResNet-50 model as a base learner. To fine-tune the ResNet-50 model, we utilized the Adam optimizer with β1=0.9 and β2=0.999. The experiments were conducted with three initial learning rates (1e-4, 5e-5, 1e-5) of the Adam optimizer. Of the three learning rates, 5e-5 was adopted as the most accurate in the validation set among individual base learners. We fixed the mini-batch size at 32 and the number of epochs at 30. The ResNet-50 model was developed with a PyTorch framework [30]. The computer specifications used in the experiments are as follows: Intel Core i7-9700K 3.60GHz CPU, 64GB memory, and a 12GB NVIDIA GeForce GTX 2080 Ti graphics card. In this study, we considered four machine learning classifiers as a meta learner of the stacking ensemble: logistic regression, SVM, random forest, and XGBoost. We employed Scikit-learn library (https://scikit-learn.org/stable/index.html, accessed on 30 January 2023) to implement logistic regression, SVM, and random forest classifiers, while XGBoost was implemented using XGBoost Python Package (https://xgboost.ai/, accessed on 30 January 2023). Optimal hyperparameters for the meta learner were chosen by performing a thorough grid search and evaluating the accuracy of the validation set. The details of the hyperparameters which were tuned using the grid search are described in Table 2. The code for training and evaluating the proposed multi-modal stacking ensemble model is available at: https://github.com/xodud5654/MMSE (accessed on 17 February 2023).
## 3. Results
We evaluated the individual base learner, simple averaging ensemble, and stacking ensemble methods on the publicly available Chapman University and Shaoxing People’s Hospital dataset. The data was split into three parts: $80\%$ for training, $10\%$ for validation, and $10\%$ for testing. As represented in Table 1, the samples of each class are imbalanced. Therefore, we considered a weighted averaging technique instead of a macroscopic averaging technique when evaluating the performance measures such as the area under the ROC curve (AUC), sensitivity, precision, and F1-score. The weighted averaging calculates a measure of performance for each class and then calculates a weighted mean. The weight is determined by the number of samples in each class relative to the total number of samples.
In Table 3, the performances of ResNet-50 based on scalogram images were compared to the performance of ResNet-50 based on ECG grayscale images for each lead. For scalogram images, Lead II demonstrated the highest accuracy ($92.24\%$), AUC (0.991), sensitivity (0.922), precision (0.916), and F1-score (0.916) among the 12 leads. On the other hand, for ECG grayscale images, the aVR lead achieved the highest accuracy ($90.90\%$), sensitivity (0.909), precision (0.911), and F1-score (0.909), while the V1 lead obtained the highest AUC (0.989). Comparing the performance of individual ResNet-50 models for each lead, the model based on scalogram images generally exhibited superior performance.
For the single-modal ensemble methods, single-modal stacking ensemble methods achieved better results than the single-modal simple averaging ensemble and 12 individual base learners for both scalogram images and ECG grayscale images, as described in Table 4. For scalogram images, single-modal stacking ensembles with four machine learning algorithms showed the following diagnostic performance: AUC (ranging from 0.993 to 0.995), accuracy (ranging from 92.34 to 93.01), sensitivity (ranging from 0.923 to 0.930), precision (ranging from 0.915 to 0.925), and F1-score (ranging from 0.913 to 0.925). For ECG grayscale images, single-modal stacking ensembles with four machine learning algorithms achieved the following: AUC (0.993), accuracy (ranging from 92.34 to 93.01), sensitivity (ranging from 0.923 to 0.930), precision (ranging from 0.918 to 0.925), and F1-score (ranging from 0.917 to 0.924). Comparing the scalogram image and the ECG grayscale image, both single-modal stacking ensemble methods showed similar performance. However, random forest and XGBoost showed better results in scalogram images, and logistic regression showed better results in ECG grayscale images.
For the multi-modal stacking ensemble method, the best accuracy ($93.97\%$), sensitivity (0.940), precision (0.937), and F1-score (0.936) were obtained when logistic regression was used as a meta learner as shown in Table 5. In addition, we could obtain the best AUC (0.996) when XGBoost was used as a meta learner. Compared with LSTM, BiLSTM, individual base learners, and single-modal ensemble methods, the proposed multi-modal ensemble methods showed better diagnostic performances. In Figure 4, we represented confusion matrices of two individual leads, a single-modal stacking ensemble with random forest for scalogram images, a single-modal stacking ensemble with logistic regression for ECG grayscale images, multi-modal simple averaging ensemble, and a multi-modal stacking ensemble with logistic regression for comparison.
## 4. Discussion
In this study, we proposed a multi-modal stacking ensemble which combines information from different two modalities, scalogram images and ECG grayscale images. The ResNet-50 model was used as the individual base learner of the stacking ensemble, and one of the machine learning algorithms, logistic regression, SVM, random forest, and XGBoost was utilized as the meta learner. Logistic regression exhibited the highest accuracy, sensitivity, precision, and F1-score and XGBoost achieved the best AUC among the four machine learning algorithms when employed as a meta learner.
The proposed multi-modal stacking ensemble relies on the predictions obtained from both the ECG grayscale image and the scalogram image to generate final predictions. The ECG grayscale image provides cardiologists with information similar to a patient’s ECG graph displayed on a monitor, while the scalogram image offers information about the time-frequency relationship of the ECG signals. In other words, the proposed model has the advantage of collecting multi-modal information potentially contained in the ECG grayscale image and the scalogram image, thereby enabling more accurate predictions of CVDs. From a practical perspective, the utilization of multi-modal information can be crucial for improving the accuracy of predictions in medical environments where accuracy is of utmost importance.
There are many studies that have applied ensemble algorithms to the healthcare field. Kang et al. improved the AUC by simply averaging the predictions from five CNN algorithms (ResNet-101, Xception, Inception-v3, InceptionResNet-v2, DenseNet-201) in classifying breast microcalcification in screening mammograms [31]. Abdar et al. introduced a two-layer nested ensemble method that employed stacking and voting as the classifier to identify benign breast tumors from malignant cancers. Their results indicated that the proposed ensemble algorithms achieved higher performance than single classifiers and most of the previous works [32]. Rao et el. proposed an ensemble model, which integrates three CNNs (DenseNet-121, Inception-v3, and InceptionResnet-v2) in a novel way. The proposed ensemble model showed better performance than the traditional ensemble technique in predicting the recurrence of odontogenic keratocysts (OKCs) on a small chunk of biopsy [33].
There are various public ECG databases on the problem of arrhythmia classification: MIT-BIH arrhythmia database, CinC/Physionet Challenge 2017 database (CinC2017), China Physiological Signal Challenge 2018 database (CPSC2018), PTB-XL database, and Chapman University and Shaoxing People’s *Hospital arrhythmia* database [6,34,35,36,37]. Among these databases, some of the researchers employed the same database, the Chapman University and Shaoxing People’s *Hospital arrhythmia* database, that we analyzed. Yildirim et al. constructed an efficient DNN model combining 1D CNN and LSTM and achieved a $92.24\%$ accuracy [11]. Merdjanovska et al. adopted the CPSCWinnerNet model, the winning model of the 2018 China Physiological Signal Challenge, consisting of convolutional blocks, GRUs, and an attention layer. They achieved an accuracy of $94.00\%$ [38]. Baygin et al. proposed a novel classification model which generated 16,384 multilevel features using homeomorphically irreducible tree and maximum absolute pooling. The Chi2 feature selector was used to select the 1000 most informative features, which were subsequently classified using the SVM classifier. The model showed a $92.95\%$ accuracy despite being a feature-based method rather than an end-to-end method [39]. Guan et al. presented a new approach called the hidden attention residual network (HA-ResNet) for the automated classification of arrhythmia. They used three different images, Recurrence Plot, Gramian Angular Field, and Markov Transition Field, as input images which were converted from 1D ECG. The Ha-ResNet algorithm achieved an F1-score of 0.876, a sensitivity of 0.882, and a precision of 0.876 [40]. It is prudent to be careful when comparing directly to the studies mentioned above due to differences in the test data. However, our proposed multi-modal stacking ensemble achieved comparable performance.
Despite demonstrating reasonable performance, this study has some limitations. First, with the exception of LSTM and BiLSTM, the majority of the experiments covered in the study are based on 2D CNNs. We compared the proposed method with base learners and single-modal ensemble methods to show the effectiveness of the proposed multi-modal stacking ensemble. However, it would also be worthwhile to compare the proposed method with feature-based machine learning algorithms or 1D CNN models. The second limitation pertains to the dataset utilized in this study. The 12-lead ECG arrhythmia database collected by Chapman University and Shaoxing People’s *Hospital is* based on severely imbalanced data. As described in Table 1, the SB category has 3888 samples, while the SI category only contains 397 samples. In order to alleviate this problem, we evaluated the performance measures with a weighted averaging technique instead of a macroscopic averaging technique. To address this issue, one could consider using several large publicly available ECG data sets, such as the recently published PTB-XL [37]. Third, when constructing the stacking ensemble, only one 2D CNN algorithm, ResNet-50, was used as the base learner. It would be necessary to optimize the architecture of the proposed model with a variety of combinations of deep learning and machine learning algorithms.
## 5. Conclusions
In this study, we proposed the use of a multi-modal stacking ensemble for the prediction of CVDs. The proposed method achieved superior performance compared to LSTM, BiLSTM, individual base learner, simple averaging ensemble, and single-modal stacking ensemble methods. These results suggest that a multi-modal stacking ensemble may be a promising approach for improving the accuracy of CVD prediction. Further research is needed to explore the use of multi-modal stacking ensemble methods with large ECG datasets and other combinations of 2D CNNs and machine learning algorithms.
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|
---
title: 'Front-of-Pack Nutrition Labels: Comparing the Nordic Keyhole and Nutri-Score
in a Swedish Context'
authors:
- Stephanie Pitt
- Bettina Julin
- Bente Øvrebø
- Alicja Wolk
journal: Nutrients
year: 2023
pmcid: PMC9967491
doi: 10.3390/nu15040873
license: CC BY 4.0
---
# Front-of-Pack Nutrition Labels: Comparing the Nordic Keyhole and Nutri-Score in a Swedish Context
## Abstract
The extent to which different front-of-pack nutrition labels (FOPNLs) agree or contradict each other has been insufficiently investigated. Considering the 2020 proposal from the European Commission to create a harmonized FOPNL, the aim of this study was to assess agreements and disagreements between two FOPNL schemes—the Keyhole and the Nutri-Score—in a Swedish context. The current *Keyhole criteria* and the updated Nutri-Score 2022 algorithm were applied to 984 food items and their nutrient compositions, obtained from the food database of the Swedish Food Agency. Agreements (Keyhole-eligible and Nutri-Score A or B; or not Keyhole-eligible and Nutri-Score C, D, or E) and disagreements (Keyhole-eligible and Nutri-Score C, D, or E, or not Keyhole-eligible and Nutri-Score A or B) were calculated as percentages for all items and by food group. An agreement was found for $81\%$ of included items. The lowest level of agreement was found for the groups of flour, grains, and rice ($62\%$ agreement) and for plant-based meat and fish analogues ($33\%$ agreement). There is generally a good level of agreement between the Keyhole and the Nutri-Score for food items on the Swedish market. Large disagreements found for plant-based meat and fish analogues, and products based on cereals/grains, highlight important considerations for the development of a harmonized FOPNL within Europe.
## 1. Introduction
Western diets—predominant across parts of Europe and North America—are typically characterized by a low intake of fruit, vegetables, and whole grains, and a high intake of processed foods, refined grains, salt, sugar, and saturated fats. The increased consumption of such foods in the diet, combined with low levels of physical activity, is associated with the increasing prevalence of overweight and obesity [1] which is an established risk factor for the development of non-communicable diseases [2]. Approaches to generating both population- and individual-level transitions toward healthier diets are therefore necessary.
Providing nutritional information on food packaging is an example of a macro-level measure that aims to improve population-level diet. Front-of-pack nutrition labels (FOPNLs) have been identified by the World Health Organization (WHO) as an important policy tool to guide consumers towards making healthier food choices [3], whilst also encouraging manufacturer-led product reformulation. The overall goal of an FOPNL is to provide at-a-glance nutritional information at the point of purchase, thus enabling consumers with different health literacy [4] to better distinguish between food products with high or low nutritional value.
Pre-packed foods sold within the European Union (EU) are required to display a nutrient declaration, usually found on the back of the pack [5]. However, as of today, there is no harmonized approach to front-of-pack nutrition labelling within the EU. As such, considerable variations in both labelling schemes and the associated terminology exist [6]. Generally, FOPNLs fall into one of two categories—”nutrient-specific” (e.g., reference intake labels) or “summary indicators”, which can be further divided into:i.Positive endorsement labels (e.g., the Nordic Keyhole);ii. Warning labels (e.g., the Chilean warning label);iii. Graded indicator labels (e.g., the Nutri-Score).
Despite there being multiple forms, there is limited evidence on the effects of FOPNLs on purchasing behaviours and improvements in dietary intake and health outcomes [6], particularly for some groups, such as people suffering from eating disorders [7]. However, within EU countries, FOPNLs are generally appreciated by consumers, and, in comparison to no label, most have been found to have a positive influence on the ability of consumers to identify the healthier food choice [6,8]. Therefore, as part of the Farm to Fork strategy adopted by the European Commission in 2020, the introduction of an EU-wide harmonized and mandatory FOPNL has been proposed [9]. Further details on the proposal were expected by the end of 2022, although there has been no confirmation as of January 2023.
## 1.1. Nordic Keyhole
The proposal is supported by the Nordic countries [10], in four of which the Nordic Keyhole (hereafter, Keyhole) is the adopted FOPNL (excluding Finland). Criteria for determining which food items are eligible to display the Keyhole are based on the Nordic Nutritional Recommendations, which constitutes the scientific basis for national nutrient recommendations and food-based dietary guidelines in the Nordic countries [11,12]. The *Keyhole is* a positive endorsement logo (Figure 1), meaning that it indicates when a food item or product is a healthier option in comparison to other products in the same category (e.g., less salt, lower in sugars, contains more fibre and whole grains, or contains healthier or less fat). One study found that by replacing some non-eligible food items with equivalent food items eligible to be labelled with the Keyhole, an improvement in meeting nutritional recommendations was achieved [13]. Furthermore, consumer awareness in *Sweden is* estimated to be high, with $97\%$ of 18–80-year-olds reporting being familiar with the Keyhole symbol [14]. However, it is also reported that few consumers have a deeper insight or understanding of what the Keyhole symbol represents in practice [15].
The Keyhole was introduced as an FOPNL in Sweden in 1989, and it has been adopted by five other countries as of January 2023: Denmark, Iceland, Lithuania, Norway, and North Macedonia [16]. The Swedish Food Agency (Livsmedelsverket in Swedish) is a government agency that is the brand owner of the Keyhole, although the use of the *Keyhole is* voluntary and at the discretion of the food manufacturer. However, products with a low nutritional value (e.g., salted or sweet snacks and pastries), or those containing artificial sweeteners, plant sterols, or more than $2\%$ industrially produced trans fatty acids cannot be labelled with the Keyhole. No registration is necessary for the use of the Keyhole and in Sweden, eligibility must be determined by the manufacturer with support offered by the Swedish Food Agency. Use of the *Keyhole is* then controlled by the responsible authority, usually at the municipality level.
## 1.2. Nutri-Score
More recently, several European countries have adopted the Nutri-Score FOPNL (Figure 1): a coloured five-letter grading system used to demonstrate the overall nutritional value of any given product, excluding unprocessed products comprising of a single ingredient (e.g., a piece of fruit or cut of raw meat) [17,18]. Originally adapted from the nutrient profiling system developed by the British Food Standards Agency, it was introduced in France in 2017. Since 2017, the Nutri-Score has been adopted by Belgium, Germany, Luxembourg, the Netherlands, Spain, and Switzerland. Similarly to the Keyhole, the Nutri-*Score is* a voluntary FOPNL. In contrast to the Keyhole, the use of the Nutri-Score label requires manufacturers to register their brand, with all products under the brand also required to use the Nutri-Score label. At present, the available literature suggests that the Nutri-Score (or a similar five-colour nutrition label) may be the most effective FOPNL for improving consumer behaviour, by guiding consumers toward healthier food choices [6], improving the identification of healthier foods [19,20,21] and, as it is a highly interpretative label, requiring the lowest cognitive workload [22]. Furthermore, in comparison to less interpretative labels, one study found the Nutri-Score could improve the understanding of the nutritional value of foods across income levels, thus indicating it is an equitable label [23]. However, the scientific committee of the Nutri-Score identified potential improvements to the algorithm behind the Nutri-Score, enabling it to better align with food-based dietary guidelines. An update of the Nutri-Score algorithm was thus published in 2022 [24], although as of January 2023, it remains under review with the original algorithm [17] currently implemented.
## 1.3. Research Gap and Aim
The Keyhole and the Nutri-Score represent two FOPNLs in use throughout Europe at present. However, the extent to which the labels agree or contradict each other (in terms of how food products are labelled by either scheme) has been insufficiently investigated, particularly for the Nutri-Score 2022 algorithm. Therefore, the aim of this study is to assess the extent of agreement and disagreement between the Keyhole and the Nutri-Score when applied to food items available in Sweden. Assessing the agreements and disagreements between the two schemes could be useful for a better understanding of how an EU-wide harmonized label could be achieved, what challenges may exist, and how this may impact the current labelling scheme in any given context.
## 2.1. Data on Food Items
The Swedish Food Agency food database (version 2022-05-24) was used as a source of food items and their nutritional composition (e.g., saturated fat, protein, and salt) per 100 g [25]. The food database consists of over 2000 food items—most of which are generic, but some are brand-specific—and aims to represent food items available on the Swedish market. Both whole foods (e.g., a piece of fruit) and composite foods (e.g., manufactured products), as well as cooked dishes, are included in the food database. Some food items in the database could not be included in this study. All home-cooked items (e.g., pasta boiled with salt) were excluded, as such items are not representative of what is found on supermarket shelves. Beverages and other drinks (including milk and plant-based alternatives) were also excluded, as the Nutri-Score 2022 algorithm had not been updated to include such items at the time of conducting this study [24]. Items for children under 36 months (e.g., baby food) were excluded as these items are not eligible for either the Keyhole or Nutri-Score FOPNL.
The remaining items were then grouped into one of 11 main food groups, as specified in the current Keyhole eligibility criteria (Livsmedelsverkets föreskrifter om användning av symbolen Nyckelhålet (LIVSFS) 2005:9) [11,12]. Since milk and yoghurt-based drinks were excluded, the group containing milk (group 4) was re-named in this study to avoid confusion. Any items that were not included in one of the 11 groups specified by the Keyhole eligibility criteria (e.g., jam and marmalade, pastries, biscuits, and cakes) were placed in an additional group (group 12, “other”), so as to include a wider range of items in the assessment. The 12 food groups were thus as follows:1Vegetables, fruits, berries, and nuts;2Flour, grains, and rice;3Porridge, bread, and pasta;4Milk, fermented products, and related plant-based products—hereafter referred to as fermented products and related plant-based products, since milk- and yoghurt-based drinks and related plant-based milk products were excluded from the assessment;5Cheese and related plant-based products;6Fats, oils, and spreads;7Fish, shellfish, and derivative products;8Meat and meat products;9Plant-based products—with the same range of use as meat or fish in group 7 or 8, hereafter referred to as plant-based meat and fish analogues;10Ready meals;11Dressings and sauces;12Other—this group is not included in the current Keyhole eligibility criteria.
The aim was to include approximately 100 items for each of the groups. However, for some groups, data were available for fewer than 100 items. Overall, 984 items were included in the assessment, covering most of the non-excluded items available from the food database. A second database (referred to as the ingredient database) containing ingredients (i.e., recipes) and their proportions (in percentage) for each item in the food database was provided by the Swedish Food Agency and linked via a unique number to each of the included items. The Keyhole eligibility for each item was subsequently determined, using the current criteria (LIVSFS 2005:9) [11,12], along with the corresponding Nutri-Score, using the updated Nutri-Score 2022 algorithm [24]. Each is described in turn, below.
## 2.2. Application of the Keyhole Eligibility Criteria
Prior to applying the Keyhole eligibility criteria, some minor adjustments or calculations were required. For vegetable items, a criterion is given for added fat; however, the amount of added fat was not available from the food database. Therefore, this criterion was only applied to the vegetable items that had oil/fat listed as an ingredient, as this indicated that fat was added to the item. In all other cases, the items were either $100\%$ vegetable (i.e., had no added fat), or consisted of water (e.g., for canned vegetables) or salt. For items in the groups of flour, grains, and rice; porridge, bread, and pasta; plant-based meat and fish analogues; and ready meals, the amount of whole grain was calculated as a percentage of the dry matter content or as a percentage of total cereal content, whichever was specified by the criteria for the group. For fish items, the proportion of non-fish fat was determined by subtracting polyunsaturated fats from total fat. Where necessary, the proportion of fish and meat in food items was also determined using the ingredient database. The total fruit, vegetable (excluding potato), legume (excluding peanut), and grain (when required by the Keyhole criteria) percentage for all items were determined by summing up the percentages of relevant ingredients.
Items eligible for the Keyhole were required to fit into one of the 11 food groups, as specified by the current Keyhole eligibility criteria, listed above. These items were then further subdivided into one of 32 categories (Table A1 in Appendix A). Products were eligible to be marked with the Keyhole provided the criteria were met (e.g., amount of fibre, whole grain, fat, saturated fat, sugar, and salt). The criteria vary between each of the 32 food categories. The criteria for each category are provided in the Supplementary Material (File S1), with the official criteria reported in detail elsewhere [11,12].
## 2.3. Application of the Nutri-Score 2022 Algorithm
The Nutri-Score 2022 algorithm was applied to all items. More detail on the 2022 algorithm can be found in the Supplementary Material (File S2), with the official report found elsewhere [24]. A brief overview is provided herein. Items were first placed into one of two groups: solid food or fats, oils, nuts, and seeds (including cream products). Within the solid food group, cheese products and red meats were identified, as specific considerations are given to these items in the final calculation. The proportion of fruit, vegetable (excluding potato), and legume (FVL) for each item was determined using the ingredient database. For the fats, oils, nuts, and seeds category, oils derived from vegetables or fruits (e.g., olive or avocado oil) were also identified. In practice, the Nutri-*Score is* not applied to unpackaged items without a nutrient declaration (e.g., an apple, or a cut of raw meat). However, for the purposes of comparison in this study, the Nutri-Score 2022 algorithm was applied to such items.
In accordance with the Nutri-Score 2022 algorithm, points were given for “favourable” and “unfavourable” elements [24] for each item. The elements comprising favourable and unfavourable elements are shown in Table 1, separately for the two groups (solid foods and fats, oils, nuts, and seeds) with more information on point allocation for each element provided in the Supplementary Material (File S2). Note that for red meat items, the maximum number of points that the protein element can receive is 2. Together, the points for the favourable elements form the C component, and the points for the unfavourable elements form the A component. The Nutri-Score for each item was then calculated by applying one of the formulas listed below.
For items in the solid food group If the A Component was ≥11 points, then: Formula i.Nutri-Score=A Component−Points FVL+Points Fibre (not including points for protein) If the A Component was <11 points or if calculating for cheese, then:Formula ii. Nutri-Score=A Component−C Component For items in the fats, oils, nuts, and seeds group
If the A Component was ≥7 points, then: Formula iii. Nutri-Score=A Component−Points FVL+Points Fibre (not including points for protein) If the A Component was <7 points, then: Formula iv. Nutri-Score=A Component−C Component The final number of points determined the Nutri-Score letter and colour, ranging from the highest nutritional quality labelled with the letter “A” (dark green); to the lowest nutritional quality labelled with the letter “E” (dark orange) (Table 2).
## 2.4. Assessment of Agreement and Disagreement
The number of items (n) and percentage of items (%) with Keyhole eligibility (yes/no) and Nutri-Score (A or B/C, D, or E) were determined overall, and within each food group. To equate Keyhole eligibility and the Nutri-Score, an agreement was determined as being Keyhole-eligible and having a Nutri-Score of A or B, or not Keyhole-eligible and having a Nutri-Score of C, D, or E (Table 2). A disagreement between the two was determined as being Keyhole-eligible and having a Nutri-Score of C, D, or E, or not being Keyhole-eligible and having a Nutri-Score of A or B. Descriptive statistics (%) were used to assess the extent of agreement and disagreement overall, and within each group. The percentage of agreement within each group was determined, as well as the percentage of disagreement, separated by the reason for disagreement (i.e., not Keyhole-eligible, but with a Nutri-Score of A or B, or Keyhole-eligible, but with a Nutri-Score of C, D, or E). Stata 16.1 was used for all statistical calculations. Five items in which a disagreement was found were selected across the food groups to further assess how the application of the *Keyhole criteria* and updated Nutri-Score 2022 algorithm may have led to the observed disagreement. Both the requirements for Keyhole eligibility and whether the specific criterion was met are reported, as well as the Nutri-Score points for each element. Further information on all food items assessed and their corresponding Keyhole eligibility and Nutri-Score are presented in the Supplementary Material (File S3). For each item, nutrient quantities are presented that are relevant to determining Keyhole eligibility and/or the Nutri-Score. In addition, the individual Nutri-Score points given for both the favourable and unfavourable elements are shown.
## 3. Results
Across the 984 items that the current *Keyhole criteria* and Nutri-Score 2022 algorithm were applied to, $36\%$ were found to be Keyhole-eligible. For the Nutri-Score, $48\%$ of items received a score of A or B (Table 3). The group of vegetables, fruits, berries, and nuts had the highest percentage of items eligible for the Keyhole ($76\%$), as well as the highest percentage of items with a Nutri-Score of A or B ($90\%$). For three groups—fats, oils, and spreads; fish, shellfish, and derived products; and meat and meat products—a higher percentage of items were found to be Keyhole-eligible, compared to items that received a Nutri-Score of A or B. For one group—cheese and related plant-based products—the number of items eligible for the Keyhole was the same as the number of items with a Nutri-Score of A or B. For the remaining eight groups, a higher percentage of items were found to have a Nutri-Score of A or B, compared to the proportion of items that were Keyhole-eligible.
An agreement between the two FOPNLs was found for $81\%$ of items ($$n = 799$$) whereas a disagreement was found for $19\%$ ($$n = 185$$) (Table 4). Of the 799 items for which an agreement was found, $40\%$ was due to being Keyhole-eligible and having a Nutri-Score of A or B. Therefore, $60\%$ of items for which an agreement was found were not Keyhole-eligible and had a Nutri-Score of C, D, or E. Of the 185 items for which a disagreement was found, $83\%$ was due to being not Keyhole-eligible, but having a Nutri-Score of A or B. Thus, $17\%$ of items for which a disagreement was found were Keyhole-eligible, but had a Nutri-Score of C, D, or E.
Within 8 of the 12 food groups, an agreement between the Keyhole and Nutri-Score was found for at least $80\%$ of all items (Table 4). The greatest agreement between the two schemes was found for the following groups (% agreement): dressings and sauces ($97\%$); meat and meat products ($90\%$); fish, shellfish, and derived products ($88\%$); cheese and related plant-based products ($88\%$); vegetables, fruits, berries, and nuts ($85\%$); ready meals ($81\%$); and fats, oils and spreads ($80\%$). In addition, a high level of agreement ($97\%$) was found within the “other” group, which includes items such as salted and sweet snacks and pastries. The lowest level of agreement between the Keyhole and the Nutri-Score was found for the following groups (% agreement): porridge, bread, and pasta ($70\%$); fermented products and related plant-based products ($63\%$); flour, grains, and rice ($62\%$); plant-based meat and fish analogues ($33\%$).
Details of why there are differences between some items are shown for the examples provided in Table A2 (see Appendix B). For instance, for the group of plant-based meat and fish analogues—for which there was least agreement—the item soy protein kebab was not eligible for the Keyhole due to its high salt content. However, in the application of the Nutri-Score, the points resulting from the high salt content were balanced out by highly favourable elements of protein and fibre, and thus the item received a Nutri-Score of A. Additionally, in the group of porridge, bread, and pasta, the item wholegrain bread, rye unsweetened was not eligible for the Keyhole due to the proportion of whole grain based on dry matter content being less than $30\%$, but the item received a Nutri-Score of B. For the group of cheese and related plant-based products, a disagreement was also found for hard cheese, $17\%$ fat. In this case, the item was eligible for the Keyhole, despite the highly unfavourable elements of saturated fat and salt, which were not outweighed by a favourable protein content, and resulted in a Nutri-Score of D.
## 4. Discussion
The aim of this study was to identify the extent to which the Keyhole and the Nutri-Score were in agreement or disagreement when applied to food items in the Swedish context. Of the 984 items included in the assessment, $36\%$ were found to be eligible for the Keyhole, whilst $48\%$ were able to receive a Nutri-Score of A or B. Of the 984 items, an agreement between the Keyhole and Nutri-Score (i.e., Keyhole-eligible and a Nutri-Score of A or B, or not Keyhole-eligible and a Nutri-Score of C, D, or E) was found for $81\%$ of items. Of the items for which a disagreement was found, the Keyhole appeared to be more restrictive, with $83\%$ of disagreements due to not being Keyhole-eligible, but having a Nutri-Score of A or B. The least agreement was found for the groups of fermented products and related plant-based products; flour, grains, and rice; and plant-based meat and fish analogues.
## 4.1. Interpretation of Results
Overall, there appears to be a good agreement between the current *Keyhole criteria* and the updated Nutri-Score 2022 algorithm, when applied to food items on the Swedish market. This is particularly true for food groups at either end of the scale from low to high nutritional value. For instance, a high level of agreement was found for fruits and vegetables (generally high in nutritional value) and for pre-packaged dressings and sauces (generally low in nutritional value). Based on these findings, for most items on the Swedish market, a hypothetical introduction of the Nutri-*Score is* unlikely to generate profound changes to the indicated healthfulness of a large number of products.
In terms of which items could be labelled as a healthier option, the findings from the presented study indicate that the Keyhole appears to be more restrictive compared to the Nutri-Score. One explanation for this could be the category-specific criteria for determining Keyhole eligibility, as opposed to an across-the-board application (as utilized in the Nutri-Score algorithm). Therefore, for some items on the Swedish market, a hypothetical introduction of the Nutri-Score 2022 algorithm would result in some currently not Keyhole-eligible items receiving a Nutri-Score of A or B. This highlights a difference in the aim of each label. While both provide an at-a-glance indication of nutritional quality, the primary aim of the *Keyhole is* to enable consumers to identify items with a higher nutritional quality in comparison to other products of the same category (which are usually placed on the same shelf). Conversely, the Nutri-Score aims to provide an overall indication of the nutritional quality of an item. In practice, though, the Nutri-*Score is* also applied within categories (e.g., when choosing among cereals, the label guides consumers towards choosing the item with a better Nutri-Score).
In terms of the application of both FOPNLs, the *Keyhole is* applicable only to items that can fit into the pre-determined 11 food groups, whereas the Nutri-*Score is* (in practice) applied only to pre-packaged items with a nutrient declaration, thus excluding unprocessed fruits, vegetables, meat, and fish. Despite this difference in application, a general agreement in the Keyhole eligibility and Nutri-Score across these food items was found, as shown by the high percentage of agreement in the groups containing fruit and vegetables, meat, and fish.
However, a lack of agreement between the schemes in certain groups indicates two differences. First, the perceived healthfulness of plant-based meat and fish analogues currently differs, since this was the group with the least agreement found. Plant-based meat and fish analogues can be challenging to generalize from a health perspective since their nutritional compositions can vary substantially between products [26] and certain properties, such as reduced bioavailability of iron, have only recently been explored [27,28]. Nonetheless, increased consumption of plant-based proteins at the expense of animal-based proteins has been suggested to improve longevity [29] and reduce climate impact [30]. Thus, improved coherence with regard to the labelling of this food group is important, as well as the ability of consumers to identify healthier plant-based meat and fish analogues, particularly considering their increasing sales [31]. This is also relevant from a sustainability perspective since plant-based foods generally carry a lower environmental impact in comparison to animal products [32]. Second, the use of whole grain or fibre as an indicator of healthfulness differs, since less agreement was found for groups in which Keyhole eligibility is in part determined by the whole grain content (e.g., flour, grains, and rice, as well as porridge, bread, and pasta). This finding was expected, since the Keyhole has certain requirements for whole grain and fibre in some instances, whereas the Nutri-Score does not have a whole grain requirement but rather uses fibre content as a proxy. This is further exemplified in Table A2 (see Appendix B), for the wholegrain bread item in which a disagreement between the two FOPNLs is found based only on the whole grain requirement (or lack thereof). Since the consumption of whole grains is recommended in many food-based dietary guidelines in Europe [33], including whole grain composition in an assessment of the healthfulness of a food item appears important. Given that the definition of whole grain can differ between the EU and its constituent countries [34], this may present a potential challenge to the development of a harmonized label.
## 4.2. Strengths and Limitations
Several strengths of this study have been identified. First, the updated version of the Nutri-Score algorithm, published in 2022, was applied, and thus the findings from this study can provide both relevant and timely points for discussion. Second, an exact assessment (rather than an estimation) of applying both FOPNLs was carried out, including a large number of items, thus maximizing the accuracy of the findings. Third, the use of the food database from the Swedish Food Agency as a source of food items, their composition, and nutritional content, ensures the reproducibility of this study upon data or criteria updates, or to answer future research questions. Fourth, the findings are generalizable to food items not included in the study but belonging to one of the food groups explored. However, although the vast majority of items assessed are common across supermarkets in Europe, some items are local to Sweden, which should be taken into consideration when generalizing the results outside of Sweden.
Despite the strengths of this study, the following limitations should be acknowledged. First, for some food groups only a small number of items were included. For instance, some plant-based meat and fish analogues are relatively new to the market, and thus fewer items than are currently available were included in the food database. This is unlikely to significantly impact the overall findings but does reduce the reliability of the findings for smaller groups. Second, some items in the database are outdated (e.g., analysed in 2012), and other items listed are an average of several similar products. Therefore, the items included in this study may not exactly match the nutritional composition of some items currently on the market. However, the impact on the findings and conclusions drawn is limited, since both the Keyhole and the Nutri-Score were applied to the same items. Third, a limitation may exist in the attempt to equate the two FOPNLs as the interpretation of Keyhole eligibility may not perfectly match with a Nutri-Score of A or B. For the purposes of this study, this was necessary to enable an appropriate comparison.
## 4.3. Similar Studies in the Literature
There is currently limited published literature assessing the extent of agreement and disagreement between applying the Keyhole and the Nutri-Score 2022 algorithm to food items. A Danish report directly compared some aspects of the Keyhole and the Nutri-Score algorithm and provides a useful overview of practical differences [35]. However, this study did not assess the application of either scheme to food items on the market. In addition, the authors did not utilize the Nutri-Score 2022 algorithm. A 2022 study by Konings et al. [ 36] compared how well two FOPNLs—the Choices five-level criteria, and the Nutri-Score—aligned to current Dutch food-based dietary guidelines. The authors found that the Choices five-level criteria aligned more closely with the food-based dietary guidelines, noting that many discrepancies were found between the Nutri-Score and the guidelines. However, since the updated Nutri-Score 2022 algorithm was not applied, it is challenging to draw comparisons. Söderlund et al. [ 37] compared two FOPNLs—the Australasian Health Star Rating and the Chilean warning labels—when applied to 13,000+ food items on the market in New Zealand. Whilst the compared FOPNLs differ from those compared in the presented study, the authors found comparable results, with a good level of agreement found in general between the two labelling schemes, but higher levels of disagreement for specific food categories, including cereals and cereal products. The similarity between the studies on this matter supports the interpretation that improved coherence between different FOPNLs may be necessary.
## 4.4. Further Implications
The presented study is theoretical, only considering if an item would be eligible for the Keyhole and which Nutri-Score it could receive. Using these findings as a starting point, further investigation into the uptake of both FOPNLs in different countries, as well as further investigation into the impact on consumer behaviour, could provide an indication of the current situation in different contexts. In addition, broader questions, such as the implication of harmonized FOPNLs on imports/exports are also brought to light. For instance, it is likely that, at present, some Keyhole-eligible food items which are imported to Sweden from within the EU may not display the Keyhole FOPNL, thus potentially limiting the effect of the label. This highlights one benefit of the development of an EU-wide harmonized label.
In the process of conducting this study, some potential points for discussion on how to achieve a successful EU-wide FOPNL have been generated. Alongside promoting healthier diets at the consumer level, FOPNLs can also encourage manufacturer-led product reformulation. For instance, with respect to the Keyhole criteria, concrete cut-off values are given for each element within a category, thus providing specific reasons for a product to be eligible or not. As such, for manufacturers, the *Keyhole criteria* can serve as a benchmark by providing clear areas for improvement. By contrast, Nutri-Score points are awarded the same way within a group (with special considerations given to cheese and red meat). Therefore, when applying the Nutri-Score, it is more challenging to determine a specific element that results in the final score. For some items, such as the soy protein kebab (see Table A2 in Appendix B), a relatively unfavourable salt content (which is a factor resulting in the item not being eligible for the Keyhole) is “offset” by favourable protein and fibre, resulting in a Nutri-Score of A. Consequently, there may be little motivation for manufacturers to reduce the high salt content. This example illustrates a possible benefit of a more granular approach to labelling criteria, as different components are necessary for different micro- and macro-nutrients, and hence may be more or less important depending on the food category. However, the motivation for product reformulation may also vary depending on the food item. For instance, for snack items (e.g., biscuits) there are no criteria to serve as a benchmark, since these items are not eligible for the Keyhole. By contrast, the manufacturer of a food item with a Nutri-Score of D or E could be encouraged to reformulate several aspects of the product to achieve a higher Nutri-Score grading, since points in the Nutri-Score algorithm are given across the board. An improved understanding of the effects of different types of FOPNLs on both manufacturer and consumer behaviour is thus necessary. Overall, this highlights that the discussion on FOPNLs within *Europe is* not a matter of public health alone, but it involves a geopolitical debate and is also closely coupled with the operation of industry.
## 5. Conclusions
This study aimed to compare the application of two FOPNLs—the Keyhole and the Nutri-Score—to determine to what extent the two schemes agreed or disagreed with respect to the scores given for the nutritional quality of food items available on the Swedish market. The results indicate a generally good level of agreement between the application of the two FOPNLs in most food groups, particularly with respect to items that are known to be high or low in nutritional value. However, disagreements exist within some food groups, particularly plant-based meat and fish analogues, and products based on cereals/grains, in which the discrepancies between whole grain and fibre requirements of the two FOPNLs can be observed. Areas of agreement, and particularly disagreement, are important for discussion when considering a harmonized FOPNL across Europe.
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|
---
title: The APC/C Activator Cdh1p Plays a Role in Mitochondrial Metabolic Remodelling
in Yeast
authors:
- Ana Cláudia Leite
- Maria Barbedo
- Vítor Costa
- Clara Pereira
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967508
doi: 10.3390/ijms24044111
license: CC BY 4.0
---
# The APC/C Activator Cdh1p Plays a Role in Mitochondrial Metabolic Remodelling in Yeast
## Abstract
Cdh1p is one of the two substrate adaptor proteins of the anaphase promoting complex/cyclosome (APC/C), a ubiquitin ligase that regulates proteolysis during cell cycle. In this work, using a proteomic approach, we found 135 mitochondrial proteins whose abundance was significantly altered in the cdh1Δ mutant, with 43 up-regulated proteins and 92 down-regulated proteins. The group of significantly up-regulated proteins included subunits of the mitochondrial respiratory chain, enzymes from the tricarboxylic acid cycle and regulators of mitochondrial organization, suggesting a metabolic remodelling towards an increase in mitochondrial respiration. In accordance, mitochondrial oxygen consumption and Cytochrome c oxidase activity increased in Cdh1p-deficient cells. These effects seem to be mediated by the transcriptional activator Yap1p, a major regulator of the yeast oxidative stress response. YAP1 deletion suppressed the increased Cyc1p levels and mitochondrial respiration in cdh1Δ cells. In agreement, Yap1p is transcriptionally more active in cdh1Δ cells and responsible for the higher oxidative stress tolerance of cdh1Δ mutant cells. Overall, our results unveil a new role for APC/C-Cdh1p in the regulation of the mitochondrial metabolic remodelling through Yap1p activity.
## 1. Introduction
Mitochondria are essential organelles that play a critical role in several cellular functions including ATP synthesis by the oxidative phosphorylation system (OXPHOS). The biogenesis of the OXPHOS system requires the concerted expression of the nuclear and the mitochondrial genomes [1]. In yeast, the mitochondrial proteome is largely dependent on substrate availability. The presence of glucose induces the catabolite repression of mitochondrial function [1,2]. The transition from fermentative to respiratory metabolism (known as diauxic shift) and shift to nonfermentable carbon sources trigger a major metabolic reorganization with the transcriptional up-regulation of many genes required to promote not only an increase in mitochondrial biogenesis and mitochondrial mass, but also a remodelling of mitochondria function towards a more respiratory mode, with an increase in OXPHOS complexes and tricarboxylic acid (TCA) enzymes [3,4,5]. The mitochondrial regulation is achieved mainly at the transcriptional level by the concerted regulation of multiple transcription factors by glucose-sensing signaling pathways (reviewed in [6]). Signaling pathways also seem to impact on mitochondrial metabolic reprogramming independently of the carbon source. By modulating the transcription of nuclear-encoded mitochondrial proteins, the cAMP-dependent protein kinase A (PKA) pathway regulates the mitochondrial enzyme content, and not the total mass, increasing the oxidative phosphorylation capacity of the cells [7,8]. Likewise, reduced TOR signaling increases mitochondrial oxygen consumption, in part, by up-regulating the translation of mitochondrial genome-encoded OXPHOS subunits, enhancing the density of OXPHOS complexes [9,10]. The type 2A-related serine-threonine phosphatase Sit4p is one of the TOR complex 1 (TORC1) downstream effectors that plays a role in mitochondrial glucose repression [11] and impacts on OXPHOS activity. Sit4p modulates the phosphorylation status of several mitochondrial proteins, including the ATP synthase catalytic beta subunit (Atp2p in yeast) [12]. In the absence of Sit4p, the phosphorylation of Atp2p leads to an increase in the ATP synthase levels, impacting the activity of the respiratory chain complexes and enhancing overall mitochondrial respiration [12].
We recently reported that the Atp2p levels increase in the absence of the anaphase-promoting complex/cyclosome (APC/C) activator Cdh1p [13]. APC/C is an E3 ubiquitin ligase responsible for the ubiquitin-dependent degradation of many cell cycle regulators [14,15], and its activity is primarily regulated through the temporal activation of two cofactors, Cdc20p and Cdh1p (also known as Hct1p) [16,17]. Cdc20p and Cdh1p carry conserved receptor domains to recognize specific sequence signals such as the destruction box and the KEN box that provide substrate selectivity [18]. Unlike Cdc20p, Cdh1p is not essential in yeast, though cdh1Δ cells exhibit a prolonged cell cycle and are sensitive to different types of stress, such as caffeine, alkalinity and hyperosmotic stress [19]. In addition to targeting mitotic regulators, emerging evidence suggests that Cdh1p has cell cycle-independent functions both in yeast [20] and mammals [21]. Although Atp2p is not an APC/C-Cdh1p direct target [13], the fact that its protein abundance is affected in cells lacking Cdh1p raises the question of whether Cdh1p may play a role in the regulation of mitochondrial function.
In the current study we performed a mitochondrial proteomic analysis and found that deletion of CDH1 impacts on the abundance of many mitochondrial proteins in yeast. Overall, absence of Cdh1p promotes a shift towards a higher mitochondrial respiratory metabolism, which is dependent on the basic leucine zipper (bZIP) transcription factor Yap1p.
## 2.1. CDH1 Deletion Leads to a Remodelling of the Mitochondrial Proteome and Promotes Mitochondrial Respiration
To evaluate the impact of APC/C-Cdh1p activity on yeast mitochondria, the mitochondrial proteome of wild type (wt) and CDH1-deleted cells was analysed by high-resolution mass spectrometry (HPLC-MS/MS). Quantification of mitochondrial proteins was performed with normalization based on total peptide amount. Cells were grown to mid-log phase under semi-respiratory conditions using galactose as a carbon source to obtain a higher mitochondrial mass, and mitochondria were then isolated by differential centrifugation. The proteomic data obtained gave a high level of replicate reproducibility with a total of 922 proteins previously reported as mitochondrial, representing a coverage of 90–$100\%$ depending on the reference proteome used [22,23]. Only these proteins were used for further data treatment.
To evaluate overall changes in the mitochondrial proteome upon CDH1 deletion, we used biological triplicate proteomic data for significance testing of the protein abundance changes in a pairwise manner. Student’s t test was used to identify differential protein expression between wt and cdh1Δ cells and represented in a volcano plot (Figure 1A). To analyse changes in protein abundance, a cut-off of p-value < 0.05 and an absolute log2 fold change (log2 FC) > 0.3 were applied. A total of 135 proteins exhibited altered protein abundance in the absence of Cdh1p activity, with 43 up-regulated and 92 down-regulated proteins (Figure 1B). Dataset S1 list the top up- and down-regulated mitochondrial proteins.
The proteins that increased the most in cdh1Δ cells are four succinate dehydrogenase subunits (Complex II), Sdh1p, Sdh3p, Sdh4p and Sdh6p. Among the most abundant proteins are also two Cytochrome c oxidase (Complex IV; Cox2p, Cox5p) subunits, two subunits of Cytochrome bc1 complex (Complex III; Qcr2p and Rip1p) as well as the NADH:ubiquinone oxidoreductase (equivalent to mammalian Complex I; Ndi1p). This shows that deletion of CDH1 increases the abundance of proteins from all respiratory chain complexes. Among the most overrepresented proteins are also the respiratory chain soluble carrier Cytochrome c isoform 1 (Cyc1p), Aconitase (Aco1p) and the ADP/ATP translocator isoform (Aac1p), also involved in the respiratory metabolism. As we previously found, Atp2p was statistically significantly up-regulated in cdh1Δ cells, but stayed below our defined threshold.
To identify the biological processes most impacted in cdh1Δ cells, a gene ontology (GO)-term enrichment analysis on biological processes was run using STRING v11.0 database [24]. This analysis showed that among the 43 up-regulated mitochondrial proteins the TCA cycle and mitochondrial respiration were the most represented processes (Figure 2A). Our results are consistent with the mitochondrial proteome analysis of yeast grown in respiratory conditions (versus fermentative) in which an overrepresentation of proteins associated to these processes have been reported [3,5,25]. We also found that proteins associated with mitochondrial protein synthesis and mitochondrial organization are enriched in the cdh1Δ mutant, namely several proteins involved in respiratory complexes assembly and two proteins involved in mitochondrial morphology, Fis1p and Dnm1p. Since both proteins are involved in fission, we analysed the mitochondrial network morphology in the cdh1Δ mutant but found no alterations in mitochondrial morphology (Figure S1). However, this was not entirely unexpected as increased Fis1p and Dnm1p abundance are also associated to the proteome remodelling that occurs upon the transition to a respiration metabolism, and this is not associated to mitochondrial fragmentation [3,25].
On the other hand, the 92 down-regulated proteins include proteins from diverse functional categories, with fatty acid metabolism (Cat2p and Oar1p among the most abundant in this category) and amino acid metabolism (glycine catabolism and aspartate synthesis) as the most relevant down-regulated biological process in the cdh1Δ mutant.
These results suggest that deletion of CDH1 promotes a metabolic remodelling towards an increased respiratory metabolism, demonstrated by the up-regulation of proteins involved in energy generation. An increase in the abundance of proteins associated with the respiratory chain and TCA cycle are hallmarks in the transition from fermentative to respiratory growth conditions [3]. To confirm these results, oxygen consumption in the cdh1Δ mutant was evaluated in whole cells in the conditions used for the proteomic analysis. In accordance, the results showed a 1.8-fold increase in mitochondrial respiration in cdh1Δ cells compared to wt cells (Figure 2B). We also assessed the oxygen consumption rate of cdh1Δ cells from post-diauxic shift (PDS) cells when yeast switch their growth from fermentation to mitochondrial respiration. At PDS, the oxygen consumption rate in cdh1Δ cells was similar to that in wt cells (Figure 2B), indicating that Cdh1p does not regulate the normal derepression of respiratory genes at the diauxic shift. This suggests that either Cdh1p plays a role in mitochondrial function only in proliferating cells, or that it exhibits an early catabolite derepression.
The increase in mitochondrial respiration in mid-log cdh1Δ cells was further supported by the increased activity of the respiratory complex cytochrome c oxidase (COX) (from 0.22 U/mg protein in wt to 0.59 U/mg protein in cdh1Δ mutant; Figure 2C). Since the remodelling towards a more respiratory metabolism is often accompanied by an increase in mitochondrial biogenesis, we performed in vivo measurements of mitochondrial mass using nonyl acridine orange (NAO) fluorescence. We found that the mitochondrial mass is mildly increased in cdh1Δ cells when compared to wt cells, but the difference was not statistically significant (7.9 × 105 ± 1.2 × 105 to 9.4 × 105 ± 1.5 × 105, mean ± SD, Figure 2D). This indicates that the increased mitochondrial respiration in cdh1Δ cells is mostly due to an increase in the respiratory capacity of mitochondria than to an increase in mitochondrial mass. Furthermore, overexpression of a constitutively active Cdh1-m11 form (lacking the 11 Cdk inhibitory-phosphorylation sites) [26] results in a decrease in mitochondrial respiration compared to wt cells expressing the empty vector (Figure 2E).
## 2.2. The Transcription Factors Yap1p and Rpn4p Mediate the Induction of Mitochondrial Respiration in cdh1Δ Cells
Since Cdh1p is part of an E3 ubiquitin ligase complex, it is possible that part of the mitochondrial proteins could be regulated by Cdh1p-mediated proteolysis. However, given the high number of altered proteins, with a high proportion of down-regulated proteins, it is most likely that Cdh1p is impacting on mitochondrial proteins indirectly, possibly through the modulation of transcription factor(s). The repository YEASTRACT+ (Yeast Search for Transcriptionally Regulators And Consensus Tracking) [27] was used to predict the transcription factors that might be responsible for the protein expression patterns in cdh1Δ cells. This led to the identification of four transcription factors as possibly regulating the adaptive responses to CDH1 deletion (Figure 3A). This list includes Pdr3p (regulator of the pleiotropic drug resistance), Gcn4p (regulator of amino acid biosynthetic genes in response to amino acid starvation), Yap1p (regulator of the oxidative stress response) and Rpn4p (regulator of the proteasome). To investigate whether these transcription factors mediate the effects of CDH1 deletion on mitochondrial function, double mutant strains deleted both in CDH1 and in the individual transcription factors were constructed. The absence of the selected transcription factors on the cdh1Δ mitochondrial phenotype was first evaluated by measuring oxygen consumption rate. Our results show that deletion of PDR3 and GCN4 did not significantly affect cdh1Δ high oxygen consumption. On the other hand, both YAP1 and RPN4 deletion restored cdh1Δ respiration to wt levels (Figure 3B). We also assessed the impact of the transcription factors deletion on cell growth by measuring optical density (OD) over time (Figure 3C). For quantitative evaluation of growth and statistical analysis purposes, the area under each growth curve was also calculated (AUC; values in Figure S2). Cells lacking Cdh1p exhibited a significant growth delay when compared to wt cells, which can be attributed to the accumulation of cell cycle progression substrates like Clb2p and Ase1p [16]. Deletion of PDR3, RPN4 and YAP1 improved the growth of cdh1Δ cells. This effect was more significant for YAP1 deletion which, despite not reverting cdh1Δ growth to wt levels (AUC of 19.4), almost doubled the AUC from 6.7 in cdh1Δ cells to 12.5 in yap1Δcdh1Δ cells. This suggests that YAP1 genetically interacts with CDH1 and contributes to the cdh1Δ mutant slow growth phenotype.
To further evaluate this functional relationship, we assessed how the deletion of RPN4 and YAP1 affected the expression of mitochondrial proteins previously identified as up-regulated (Cyc1p and Cox2p) in cdh1Δ cells. Cyc1p and Cox2p were among the proteins identified by YEASTRACT+ as potentially transcriptionally regulated by Yap1p and Rpn4p. Tim22p, which was found unaltered cdh1Δ cells, was also analysed as a control of mitochondrial mass. Accordingly, we found Cyc1p and Cox2p, but not Tim22p, accumulated at higher levels in proliferating cdh1Δ cells (Figure 4). Our results also show that Cyc1p levels were significantly decreased after deletion of both YAP1 and RPN4 in cdh1Δ cells. Cox2p levels also decreased in the double mutants when compared with cdh1Δ cells, but the difference was not statistically significant (Figure 4).
Overall, these results suggest that transcription factors Yap1p and Rpn4p function as Cdh1p downstream effectors in the regulation of mitochondrial protein levels. Interestingly, Yap1p and Rpn4p are functionally related, as YAP1 itself contains a Proteasome Associated Control Elements (PACE) sequence in its promotor targeted by Rpn4p [28], while RPN4, in turn, can be transcriptionally regulated by Yap1p [29].
## 2.3. CDH1 Deletion Does Not Impact on Rpn4p Activity
Yeast Rpn4p is a C2H2 zinc finger transcription factor that is responsible for the expression of genes associated with proteasome biogenesis and activity and with ubiquitin-dependent proteolysis [30,31]. Inhibition of proteasome activity results in a Rpn4p stabilization, which binds to PACE sequences found in Rpn4p-recognized promotors, up-regulating its target genes [30].
We next investigated the hypothesis that the direct targeting of Rpn4p by APC/C-Cdh1p may account for the mitochondrial alterations induced by CDH1 deletion. For that, the levels of Rpn4p were evaluated by Western blot, in cells expressing HA-tagged endogenous Rpn4p. We found that Rpn4p stability was not increased by CDH1 deletion (Figure 5A), suggesting that Rpn4p is not a direct substrate of APC/C-Cdh1p. In addition, it suggests that Rpn4p is not more active in cdh1Δ cells as Rpn4p stabilization is associated to its activity [32]. To confirm this, we assessed Rpn4p transcriptionally activity using a Rpn4p-driven GFP reporter [33]. As a positive control, wt cells were incubated with 60 μM of the proteasome inhibitor MG132 for 2 h. As shown in Figure 5B, GFP fluorescence was significantly elevated in MG132-treated cells while RPN4-deleted cells showed a strong decrease, validating the reporter specificity. However, loss of Cdh1p did not affect Rpn4p transcriptional activity, supporting the hypothesis that Rpn4p is not more active in CDH1 deleted cells. These results suggest that Rpn4p activation is not the primary cause leading to Cdh1p-mediated up-regulation of mitochondrial respiration.
## 2.4. Yap1p Is More Active in cdh1∆ Cells
Yeast Yap1p is a leucine zipper (bZIP) transcription factor that activates the expression of genes encoding several antioxidant proteins [34]. Yap1p is activated in response to different reactive oxygen species (ROS), such as hydrogen peroxide (H2O2), by a mechanism that inhibits its nuclear export, thus promoting Yap1p nuclear accumulation and activation [35,36,37]. In addition to its well-known role in the oxidative stress response, Yap1p is also involved in the yeast response to metals and unrelated drugs [35] and seems to play a role in mitochondrial regulation [38,39,40].
We next investigated the hypothesis that the direct targeting of Yap1p by APC/C-Cdh1p may account for the mitochondrial alterations induced by CDH1 deletion. For that, we compared the steady-state level of the Yap1p protein in wt and cdh1Δ cells. The Yap1-9Myc protein was expressed from a vector under the regulation of its native promoter in the yap1Δ and yap1Δcdh1Δ mutants. As shown in Figure 6A, no difference was detected in the protein levels of Yap1p at OD600nm 0.5 suggesting Yap1p is not a Cdh1p direct substrate. In addition, the levels of Yap1p were also not affected by expression of a constitutively active Cdh1-m11 form (lacking the 11 Cdk inhibitory-phosphorylation sites) [26] or after mutation in a potential APC/C recognition motif predicted using GPS-ARM 1.0 (Figure S3). Intriguingly, at OD600nm 1.0 Yap1p levels were even decreased in cells lacking Cdh1p (Figure 6A). It was previously reported that Yap1p activity is mostly controlled by the disruption of Yap1p nuclear export without affecting protein levels [35,41]. However, a decrease in Yap1p protein levels is often observed following its activation [35,41,42]. Therefore, our results suggest that Yap1p is not a direct Cdh1p target, but its transcriptional activity might be indirectly regulated by Cdh1p. To investigate this hypothesis we monitored Yap1p transcriptional activity in cdh1Δ cells, using a Yap1p-dependent lacZ reporter (pRS415-AP-1-CYC-LacZ) [41]. As a positive control, wt cells were treated with 5 mM H2O2 for 1.5h, which triggered a significant increase in β-Galactosidase activity (Figure 6B). On the other hand, the Yap1p-dependent β-Galactosidase activity in yap1Δ cells was dramatically decreased, confirming the reporter specificity. Notably, the results showed a 1.7-fold increase in β-Galactosidase activity in cdh1Δ cells compared to wt cells, indicating that Yap1p transcriptional activity is increased in cells lacking Cdh1p.
## 2.5. Yap1p Mediate the Oxidative Stress Resistance of cdh1∆ Cells
Since Yap1p is a major oxidative stress response regulator in yeast, we asked whether its increased transcriptional activity in cdh1Δ cells led to an increase in oxidative stress resistance. To test this hypothesis cells were grown in solid media in the presence of H2O2. As expected, deletion of YAP1 dramatically increases the H2O2 sensitivity (Figure 7A). In contrast, cells lacking Cdh1p presented a higher oxidative stress resistance compared to wt cells, particularly evident at the higher H2O2 concentration used. The increase in H2O2 resistance was dependent on Yap1p since its deletion in cdh1Δ cells restored oxidative stress sensitivity (Figure 7A). In contrast, cdh1Δ cells, but not yap1Δ cells, were more sensitive to methyl methanesulfonate (MMS) comparing to wt (Figure 7A), as reported for several other stressors [19]. These findings indicate that cdh1Δ cells are unexpectedly resistant to oxidative stress, and that this occurs due to Yap1p activation.
Under physiological conditions, mitochondria serve a major source of ROS that are mainly generated from the mitochondrial respiratory chain as a normal consequence of aerobic respiration [43,44]. Since CDH1 deletion led to an up-regulation of mitochondrial respiration, we investigated its effect on ROS levels using dihydroethidium (DHE) as a probe that becomes fluorescent upon oxidation by superoxide radicals and hydrogen peroxide. At early-log phase, approximately $1\%$ of wt cells exhibited ROS accumulation, whereas $10\%$ of cdh1Δ cells displayed DHE staining (Figure 7B). ROS levels in the cdh1Δyap1Δ double mutant were similar to those in cdh1Δ cells (Figure 7B). Since YAP1 deletion lowered the increase in mitochondrial respiration in cdh1Δ cells, but not the ROS levels, we questioned whether the higher ROS levels in cdh1Δ cells may underlie Yap1p activation in these cells and precede the mitochondrial remodelling. To test this hypothesis, we analysed Yap1p transcriptional activity in cdh1Δ cells after overexpression of the mitochondrial superoxide dismutase (Sod2p) using Yep352-SOD2 plasmid [45]. Overexpression of SOD2 decreased the Yap1p-dependent β-Galactosidase activity in cdh1Δ cells comparing to cells expressing the empty-vector (Figure 7C). However, SOD2 overexpression did not fully lower the Yap1p activity in the cdh1Δ mutant to the levels observed in wt cells overexpressing SOD2. This result led us to hypothesize that in cdh1Δ cells Yap1p is transcriptionally more active, leading to an increase in mitochondrial respiration, which results in higher mitochondrial ROS production. This in turn, in a positive feedback loop, further favours Yap1p activation in these cells.
## 3. Discussion
In this work we investigated the role of Cdh1p in the control of mitochondrial function using a proteomic approach. Cdh1p has a well-known role in ubiquitination of cell cycle substrates, regulating cell cycle processes such as G1/S transition and mitotic exit [17]. This study provides for the first time evidence that Cdh1p also plays a role in the regulation of mitochondrial functional remodelling and provides a global overview of the specific mitochondrial changes elicited by CDH1 deletion. We found that deletion of CDH1 causes a shift in mitochondrial proteome composition to promote a more respiratory mode, which was confirmed by measuring oxygen consumption and COX activity. Besides the canonical functions of APC/C, some studies in mammalian cells point to a role for Cdh1p in the regulation of metabolism and mitochondrial morphology [46,47]. APC/C-Cdh1 impacts on mitochondrial morphology by ubiquitinating Drp1 (the Dnm1p homologue), contributing to the maintenance of a dynamic balance between mitochondrial fission and fusion during mitotic exit [46]. Though we also found an increase in Dnm1p levels in cells lacking Cdh1p, due to the high number of mitochondrial proteins altered in the cdh1Δ mutant [135], with about two-thirds being down-regulated, it is more likely these are indirect effects. However, we cannot discard the hypothesis that among the up-regulated proteins some might be direct targets and subject to Cdh1p-regulated proteolysis. In fact, many mitochondrial proteins have potential Cdh1p canonical recognition motifs. However, the APC/C motifs are very common in the proteome [48] and, thus, are not strong substrate predictors and need to be experimentally validated.
The up-regulation of mitochondrial respiration in cdh1Δ mutant was suppressed upon deletion of genes encoding the transcription factors Yap1p or Rpn4p, supporting an indirect regulation of mitochondrial function. Though both Yap1p and Rpn4p, a downstream target of Yap1p [49], were required for mitochondrial functional remodelling in the cdh1Δ mutant, only Yap1p was found to be more active in these cells. Due to the functional relation between Yap1p and Rpn4p, Rpn4p may contribute to Yap1p effects, but the up-regulation of Yap1p function is likely the main trigger for the mitochondrial alterations in cdh1Δ cells. Yap1p is the main oxidative stress response regulator in yeast, but several works point for a potential role for Yap1p in mitochondrial function. Indeed, it was demonstrated that the transcription factor Yap1p is directly involved in the regulation of iron export from the mitochondria [38] and plays a role in the mitochondrion-to-nucleus signaling during growth on ethanol [39]. Importantly, Yap1p overexpression leads to an increase in the abundance of mitochondrial proteins associated to respiration [39], supporting our observations that increased Yap1p activity can lead to an enhancement in mitochondrial respiration in cdh1Δ cells. Interestingly, in the same study, authors also report Yap1p overexpression triggers alterations in proteins associated with cell cycle and growth regulation. Though Cdh1p can have cell cycle-independent functions, its main role is the regulation of cell cycle progression. Since we and others have found a synchronization between cell cycle progression and mitochondrial respiration in yeast [13,50], it will be interesting to assess if the role of Cdh1p in the regulation of mitochondrial function is cell cycle-independent or occurs during cell cycle progression. In fact, the oxygen consumption during cell cycle progression in lowest in G1, the phase in which Cdh1p is more active [13,50]. Likewise, the lower effect in the mitochondrial proteome remodelling in the cdh1Δ mutant compared to the transition to growth in respiratory substrates fits well with the maximum oscillations found in mitochondrial respiration during cell cycle progression (about 1.3 fold) [13]. In addition, Cdh1p does not seem to play a role in the traditional diauxic shift transition to respiration, as it did not affect the yeast respiration in PDS phase. In addition, Yap1p and Rpn4p are not important players in mitochondrial transcriptional regulation at this phase, with Msn2p and Msn4p [51], Cat8p [52] and Sip4p [53] as the main transcriptional factors involved in mitochondrial derepression. This suggests that Cdh1p impacts on mitochondrial respiration in proliferating cells independently of the canonical carbon source-responsive pathways.
A remaining question Is also how APC/C-Cdh1p regulates the activity of Yap1p to promote the induction of mitochondrial respiration. We provide evidence that CDH1 deletion affects Yap1p activity, but not its protein levels. It is therefore possible that Cdh1p may regulated the proteins involved in the regulation of Yap1p activity/nuclear export. Since we found that cdh1Δ cells exhibit higher ROS levels than wt cells, it is also possible that Yap1p is being activated by the oxidative environment of cdh1Δ cells. Curiously, though Yap1p seem involved in the up-regulation of respiration in cdh1Δ cells, Yap1p transcriptional activity has been described to be also induced by mitochondrial respiration [54,55]. The mitochondria respiratory chain is the major source of endogenous ROS [44], and therefore transition to mitochondrial respiratory growth is accompanied by the induction of cellular antioxidant defences, which allows the cells to become intrinsically more tolerant to oxidants than fermenting grown yeast [54,55]. Activation of Yap1p in cdh1Δ cells may allow the coordination of mitochondrial respiration with oxidant resistance, particularly vital if the regulation of mitochondrial function by Cdh1p occurs during cell division, as ROS are particularly harmful to replicating DNA [56] and can lead to cell cycle arrest [57]. Interestingly, two additional transcription factors, Tos4p and Pdr3p, implicated in the DNA damage response were reported to be positively regulated by Cdh1p [58]. Together with our results, this suggests Cdh1p may play a broader role than believed in the cellular transcriptional responses to different environmental stresses.
In conclusion, our study reveals a novel role for Cdh1p in the regulation of mitochondrial metabolic remodelling contributing to our understanding of the signalling pathways controlling cellular energy homeostasis. Regulation of mitochondrial metabolism occurs after glucose exhaustion, in the presence of alternative respiratory carbon sources and even during cell cycle progression [13,50]. Mitochondrial metabolic remodelling also occurs in response to diverse signalling pathways [7,8,9,10,11] reinforcing the importance of fine-tuning mitochondrial function with energetic demands. We also report that Cdh1p impacts on Yap1p transcriptional activity, which underlies both the cdh1Δ mutant resistance to oxidative stress and the up-regulated mitochondrial respiration. The integration of mitochondrial function with the induction of antioxidant defences through Yap1p may be important to maintain the cellular redox balance in cdh1Δ cells.
## 4.1. Yeast Strains and Growth Conditions
The *Saccharomyces cerevisiae* strains used are all BY4741 derivative and are listed in Table S1. *To* generate cdh1∆::HIS3 strain, cdh1∆::KanMX4 was transformed with a DNA fragment containing HIS3MX. To construct double mutant strains, the DNA fragment containing cdh1∆::HIS3 was amplified and transformed in the deletion strains. *To* generate Rpn4-HAcdh1Δ::kan strain, Rpn4-HA:HIS3 was transformed with a DNA fragment containing cdh1∆::KanMX4. Strains were transformed by the standard lithium acetate procedure [59]. Gene deletion was confirmed by PCR. For overexpression of Cdh1-m11 and Sod2p, cells were transformed with the plasmids pRS416-GALL-3HA-Cdh1-m11 [26] and Yep352-SOD2 [45], respectively.
Cells were grown in rich medium [YPGal: $2\%$ (w/v) galactose, $1\%$ (w/v) yeast extract, $2\%$ (w/v) bactopeptone] or synthetic complete medium [SC: $0.67\%$ (w/v) Bacto-yeast nitrogen base w/o amino acids, $2\%$ (w/v) glucose and $0.2\%$ (w/v) Dropout mix] lacking uracil/leucine, as appropriate. For Cdh1-m11 overexpression, cells were grown in YPRaff medium [$2\%$ (w/v) raffinose, $1\%$ (w/v) yeast extract, $2\%$ (w/v) bactopeptone] overnight until mid-log phase and cultured with $4\%$ galactose for 3h before oxygen consumption analysis. Cultures were routinely grown at 26 °C in an orbital shaker at 140 r.p.m.
## 4.2. Mitochondrial Isolation
For isolation of an enriched mitochondrial fraction, wt and cdh1Δ cells were grown to mid-log phase (OD600nm = 1.4) in YPGal medium and digested enzymatically with zymolyase (5 mg/g of cells) at 37 °C for 30 min. The homogenized spheroplasts were subjected to differential centrifugation basically as described in [60].
## 4.3. Protein Identification by HPLC-MS/MS
Biological triplicates from wt and cdh1Δ cells were solubilized with 100 mM Tris pH 8.5, $1\%$ (w/v) sodium deoxycholate, 10 mM tris(2-carboxyethyl) phosphine (TCEP) and 40 mM chloroacetamide for 10 min at 95 °C at 1000 r.p.m. Each sample was processed for proteomics analysis following the solid-phase-enhanced sample-preparation (SP3) protocol as described in [61]. Enzymatic digestion was performed with Trypsin/LysC (2 μg) overnight. Protein identification and quantitation was performed by nanoLC-MS/MS composed by an Ultimate 3000 liquid chromatography system coupled to a Q-Exactive Hybrid Quadrupole-Orbitrap mass spectrometer (ThermoFisher Scientific, Waltham, MA, USA), as previously described [62]. This equipment is composed of an Ultimate 3000 liquid chromatography system coupled to a Q-Exactive Hybrid Quadrupole-Orbitrap mass spectrometer (ThermoFisher Scientific, Waltham, MA, USA).
The raw data were processed using Proteome Discoverer 2.5.0.400 software (ThermoFisher Scientific, Waltham, MA, USA) and searched against the UniProt database for the *Saccharomyces cerevisiae* Proteome 2020_03 together with a common contaminant database from MaxQuant (version 1.6.2.6, Max Planck Institute of Biochemistry, Martinsried, Germany). The Sequest HT search engine was used to identify tryptic peptides. Peptide confidence was set to high. The processing node Percolator was enabled with the following settings: maximum delta Cn 0.05; decoy database search target FDR $1\%$, validation based on q-value. Protein label free quantitation was performed with the Minora feature detector node at the processing step. Precursor ions quantification was performing at the processing step with the following parameters: Peptides to use unique plus razor, precursor abundance based on intensity and normalization based on total peptide amount.
## 4.4. Mitochondrial Mass Analysis
The total mitochondrial mass was determined using 10-N-Nonyl acridine orange (NAO, Invitrogen, Waltham, MA, USA), a dye that binds to cardiolipin present specifically on the mitochondrial membrane [63]. Briefly, wt and cdh1Δ cells were grown to mid-log phase in YPGal medium and incubated in culture medium containing 10 μM NAO for 30 min. Fluorescence intensity measured using the BD Accuri C6 flow cytometer. Data were analysed with FlowJo v10 software version.
## 4.5. Oxygen Consumption Rate and COX Activity
The oxygen consumption was measured polarographically in whole cells resuspended in PBS buffer, from cultures grown in YPGal medium to mid-log or PDS phase, using a Clark-type oxygen electrode coupled to an *Oxygraph plus* system (Hansatech, King’s Lynn, United Kingdom).
Data were analysed using the OxyTrace+ software. The respiratory rate was obtained by dividing the oxygen consumed per min by the number of cells used in the experiment.
Cytochrome c oxidase activity was determined by measuring cytochrome c oxidation as previously described [64].
## 4.6. SDS-PAGE and Western Blot
For immunoblotting, yeast cell extracts were resuspended at identical cell densities in sodium dodecyl sulphate (SDS) loading dye and lysed by boiling for 6 min and vortexing for 5 min with glass beads. Protein samples were separated into 7.5–$10\%$ SDS-PAGE gels and transferred to nitrocellulose membranes (Hybond-C, GE Healthcare).
The primary antibodies used were raised against yeast Tim22p (1:500, sc-14042, Santa Cruz Biotechnology, Dallas, TX, USA), yeast Cox2p (1:6000, 4B12A5, ThermoFisher Scientific, Waltham, MA, USA), yeast Cytochrome c (1:10,000, Davids Biotechnologie, Regensburg, Germany), yeast Pgk1p (1:30,000, 22C5D8, ThermoFisher Scientific, Waltham, MA, USA), HA (1:1000, Y-p11, Santa Cruz Biotechnology, Dallas, TX, USA) and c-Myc (1:1000, ThermoFisher Scientific, Waltham, MA, USA).
Secondary antibodies used were anti-goat IgG-HRP (1:5000), anti-mouse IgG-HRP (1:10,000, Molecular probes, Eugene, OR, USA) and anti-rabbit IgG-HRP (1:10,000, Sigma, St. Louis, MO, USA).
Membranes were incubated with WesternBright ECL (Advansta, San Jose, CA, USA), exposed to LucentBlue X-ray film (Advansta), scanned on a Molecular Imager GS900, and quantified using Image Lab Software version 6.1 (Bio-Rad, Hercules, CA, USA).
Full-length blots corresponding to the blots displayed in various figures and used for data quantification are provided in Figures S4–S6.
## 4.7. Fluorescent Reporter Assay Measurements
Cells harbouring a GFP reporter for Rpn4p activity [33] were grown in YPGal until early-log phase. To assess Rpn4 activity under proteasomal stress conditions, wt cells were treated with 60 μM of MG132 (Merck, Darmstadt, Germany) for 2 h. Cells were then centrifuged, washed and resuspended in PBS buffer. Cells were acquired using the FL1 detector in a BD Accuri C6 Flow cytometer and data were analysed with FlowJo v10 software version.
## 4.8. β-Galactosidase Assay
Cells harbouring pRS415-AP-1-CYC1-LacZ plasmid [41] were grown in YPGal until mid-log phase. To assess Yap1p activity under oxidative stress conditions, wt cells were treated with 3 mM H2O2 (Merck, Darmstadt, Germany) for 1.5 h. The β-galactosidase activity was measured in a liquid assay using o-nitrophenyl-β-D-galactoside (ONPG; Merck, Darmstadt, Germany) as previously described [65] using 60 μg of total protein.
## 4.9. Oxidative Stress and DNA Damage Sensitivity
Wt, cdh1Δ, yap1Δ and yap1Δcdh1Δ strains were grown overnight at 26 °C in YPGal medium until mid-log phase. Each culture was then diluted to OD600nm = 0.1 and ten-fold dilutions were performed using PBS buffer. Cells were spotted in YPGal plates, used within 48h of preparation, supplemented with 0, 2.5 and 5 mM of H2O2 (Merck, Darmstadt, Germany) and $0.05\%$ (v/v) of methyl methanesulfonate (MMS, ThermoFisher Scientific, Waltham, MA, USA). Cells were incubated for 2 days at 26 °C.
## 4.10. ROS Levels
Cells were grown overnight at 26 °C in YPGal medium until mid-log phase and incubated with 5 μg/ml dihydroethidium (DHE, Invitrogen, Waltham, MA, USA) for 30 min at room temperature in the dark. Cells were then centrifuged, washed and resuspended in PBS buffer. Cells were acquired using the FL3 detector in a BD Accuri C6 Flow cytometer (BD Biosciences, San Jose, CA, USA) sand data were analysed with FlowJo v10 software version.
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|
---
title: 'Synthetic Cinnamides and Cinnamates: Antimicrobial Activity, Mechanism of
Action, and In Silico Study'
authors:
- Mayara Castro de Morais
- Edeltrudes de Oliveira Lima
- Yunierkis Perez-Castillo
- Damião Pergentino de Sousa
journal: Molecules
year: 2023
pmcid: PMC9967511
doi: 10.3390/molecules28041918
license: CC BY 4.0
---
# Synthetic Cinnamides and Cinnamates: Antimicrobial Activity, Mechanism of Action, and In Silico Study
## Abstract
The severity of infectious diseases associated with the resistance of microorganisms to drugs highlights the importance of investigating bioactive compounds with antimicrobial potential. Therefore, nineteen synthetic cinnamides and cinnamates having a cinnamoyl nucleus were prepared and submitted for the evaluation of antimicrobial activity against pathogenic fungi and bacteria in this study. To determine the minimum inhibitory concentration (MIC) of the compounds, possible mechanisms of antifungal action, and synergistic effects, microdilution testing in broth was used. The structures of the synthesized products were characterized with FTIR spectroscopy, 1 H-NMR, 13 C-NMR, and HRMS. Derivative 6 presented the best antifungal profile, suggesting that the presence of the butyl substituent potentiates its biological response (MIC = 626.62 μM), followed by compound 4 (672.83 μM) and compound 3 (726.36 μM). All three compounds were fungicidal, with MFC/MIC ≤ 4. For mechanism of action, compounds 4 and 6 directly interacted with the ergosterol present in the fungal plasmatic membrane and with the cell wall. Compound 18 presented the best antibacterial profile (MIC = 458.15 μM), followed by compound 9 (550.96 μM) and compound 6 (626.62 μM), which suggested that the presence of an isopropyl group is important for antibacterial activity. The compounds were bactericidal, with MBC/MIC ≤ 4. Association tests were performed using the Checkerboard method to evaluate potential synergistic effects with nystatin (fungi) and amoxicillin (bacteria). Derivatives 6 and 18 presented additive effects. Molecular docking simulations suggested that the most likely targets of compound 6 in C. albicans were caHOS2 and caRPD3, while the most likely target of compound 18 in S. aureus was saFABH. Our results suggest that these compounds could be used as prototypes to obtain new antimicrobial drugs.
## 1. Introduction
Cinnamic acid (CA) [1] is a natural product that presents a low toxicity to most living organisms. It is found in plant species, mainly in Cinnamomum zeylanicum, which gives rise to the term “cinnamic”. Its structure is simple (Figure 1), but it is involved in many crucial systemic functions such as growth, development, reproduction, and defense in various plant species [1,2]. This acid comes from the biosynthetic pathway of shikimic acid, its precursor being phenylalanine, and participates in the synthesis of more complex secondary metabolites such as lignins, flavonoids, isoflavonoids, tannins, coumarins and anthocyanins, which play vital roles in plant physiology such as during growth, development, reproduction and disease resistance [3,4].
In the last 10 years, interest in CA and its derivatives (esters, amides, aldehydes and alcohols) [5] has increased because of its many pharmacological activities, such as antituberculosis [6,7,8,9], antiviral [10], anticancer [11,12,13,14,15,16], mammary (MCF-7) and prostate (PC-3) inhibition, neoplastic cell growth, apoptosis inducement [17,18,19], anticholesterolemic [20,21,22,23], cardioprotective [24], antioxidant [25,26,27,28], anti-inflammatory [2,29,30,31,32], hepatoprotective [33,34,35], antidiabetic [36,37,38], antimalarial [39], anxiolytic [40], central nervous system depressant [41], neuroprotective [42,43,44,45,46], larvicidal agent [47,48,49,50,51], anti-leishmania [52], cosmetic [17,53], and antimicrobial action [54,55,56,57,58,59,60,61,62,63,64,65,66] properties.
Infectious diseases caused by bacteria and fungi remain a major global health problem, especially in developing countries. Antibacterial and antifungal drugs, widely known as antimicrobials, began to be used in chemotherapy in the 1940s, and many new classes of antimicrobials were discovered in the period from 1940 to 1970 and successfully introduced into clinical practice [67]. However, as these new drugs were employed, drug-resistant strains began to appear [68]. The widespread use of antibiotics during the last forty years in animal feed and human consumption has only accelerated the emergence of resistance in various pathogenic organisms [69]. Infection with drug-resistant strains is typically associated with longer treatments, greater toxicity, and higher costs.
The CA skeleton is an interesting scaffold for the development of novel bioactive substances. CA derivatives are known for their antimicrobial activity [21]. Antimicrobial mechanism studies have reported that CA mainly exerts its activity through plasma membrane disruption, nucleic acid and protein damage, and the induction of intracellular reactive oxygen species [70,71]. The biological activities of CA can be explained through its interactions with the molecular targets present in a living organism. CA has three main reactive sites: the aromatic ring substituent, the carboxylic acid function, and the conjugated olefin (Figure 1) [72].
Therefore, the objectives of this study were to synthesize a series of cinnamic acid derivatives and to evaluate their antifungal and antibacterial activities to identify new antimicrobial drug candidates. An in silico approach was used to investigate the potential mechanisms of antimicrobial action.
## 2.1. Chemistry
Cinnamic acid [1] and cinnamoyl chloride were used as starting materials for the preparation of a series of nineteen compounds: via Fischer esterification reactions [51,73,74] (2–8), bimolecular nucleophilic substitution [51,73,75] (9 and 14), and Schotten–Baumann reactions [65] (10–13 and 15–20) (Scheme 1). The following reagents were used: methanol [2], ethanol [3], propanol [4], isopropanol [5], butanol [6], pentanol [7], iso-pentanol [8], bromodecane [9], benzyl alcohol [10], 4-methylbenzyl alcohol [11], 4-hydroxybenzyl alcohol [12], 4-nitrobenzyl alcohol [13], 4-chlorobenzyl chloride [14], piperonyl alcohol [15], benzyl amine [16], 4-chlorobenzyl amine [17], 4-isopropylbenzyl amine [18], piperonyl amine [19] and dibenzyl amine [20] (Figure 2). The compounds were structurally characterized using infrared (IR) spectroscopy, nuclear magnetic resonance (NMR), and high-resolution mass spectrometry.
The compounds were evaluated for in vitro antimicrobial activity against strains of Candida albicans (ATCC-76485), *Candida tropicalis* (ATCC-13803), *Candida glabrata* (ATCC-90030), *Aspergillus flavus* (LM-171), *Penicillium citrinum* (ATCC-4001), *Streptococcus aureus* (ATCC-35903), *Streptococcus epidermidis* (ATCC-12228), and *Pseudomonas aeruginosa* (ATCC-25853).
An analysis of the 1 H NMR spectra of the cinnamic derivatives showed seven hydrogens in common in the cinnamoyl substructure, five belonging to the aromatic ring and two olefinic hydrogens referring to the side carbon chain. In view of the common signals for all analogues, the most unprotected hydrogen signal in the spectrum was that of the olefinic hydrogen in the form of a doublet at about δH 7.60 ppm, which was coupled to the neighboring hydrogen that presented a signal in the form of doublet around δH 6.53 ppm, evidencing the configuration of the double bond is trans.
In the 13 C NMR spectra, chemical shifts indicated that the cinnamic derivatives had nine carbons in common. A signal close to δC 166.0 ppm was attributed to carbonyl; a signal around δC 141.3 ppm was attributed to olefinic carbon. A signal at δC 133.0 ppm was attributed to the aromatic carbon adjacent to the olefinic group. In addition, the signals at about δC 129.6 ppm and δC 128.8 ppm were attributed to meta carbons of the aromatic ring and to two ortho carbons, respectively, and another chemical shift of approximately δC 127.8 ppm indicated carbon in the para position. Furthermore, the presence of a signal close to δC 120.3 ppm was attributed to olefinic carbon.
The IR spectra showed absorption bands between 2850 and 3000 cm−1, indicating C-H sp3 stretching; signals between 3000 and 3100 cm−1 indicating C-H sp2 stretching; and C=O stretching bands in the range of 1750–1730 cm−1 characteristic of ester carbonyls or a strong signal around 1650 cm−1 belonging to the carbonyl stretch of the amides.
## 2.2. Evaluation of Antifungal Activity
Following the antifungal activity analysis of the nineteen cinnamic acid analogs against strains of C. albicans (ATCC-76485), C. tropicalis (ATCC-13803), C. glabrata (ATCC-90030), A. flavus (LM-171), and P. citrinum (ATCC-4001) (Table 1), it was verified that eleven were bioactive. Butyl cinnamate [6] was the most potent compound (MIC = 626.62 µM) against all tested strains. Ethyl cinnamate [3] and methyl cinnamate [2] were also bioactive, though with a lower potency, with MIC = 726.36 µM and 789.19 µM, respectively. *In* general, the ester derivatives were more bioactive than the amide derivatives.
## 2.2.1. Minimum Fungicidal Concentration (MFC)
One may analyze whether a substance is fungicidal or fungistatic by calculating its MFC to MIC ratio [76]. Therefore, MFC/MIC ratios were calculated to determine whether the substances presented fungistatic (MFC/MIC > 4) or fungicidal (MFC/MIC ≤ 4) activity. The MFC/MIC ratios were all less than 4 (Table 2), strongly suggesting that the compounds maintain antifungal activity with a fungicidal character.
## 2.2.2. Mechanism of Action
Sterols make up part of the constitution of all fungal cells. Ergosterol is a principal sterol and modulates membrane fluidity, cell growth, and proliferation [76]. In this study, tests to detect the biological targets of compounds 4 and 6 were performed by adding ergosterol to the medium. An increase in the MIC of the compounds was observed, indicating that the fungus likely acts by inhibiting ergosterol synthesis or directly binding to ergosterol. Azoles and polyenes are well-known classes of antifungal drugs that act on ergosterol to treat fungal infections [76] (Table 3 and Table 4).
When studying cell wall architecture, protoplasts stabilized with osmo-protectants are important biochemical tools [76]. Osmotic stability is used with C. albicans and other fungi to study antibiotic mechanisms of action [76,77,78]. Damage to essential components of the cell wall, caused by antifungal agents such as cell wall synthesis inhibitors, can lyse cells in the absence of an osmo-protectant. However, cells will continue to grow if an adequate stabilizer is present in the medium. In the sorbitol (osmotic protector) test, the MIC of compounds 3 and 6 increased with microbial growth, indicating interference in cellular functions that are involved the participation of the cell wall (Table 3 and Table 4).
## 2.2.3. Association Tests—Checkerboard Method
In the microdilution assays, compound 6 demonstrated the best antifungal activity, so it was tested in combination with nystatin using the Checkerboard method to analyze its synergistic effect. When tested alone, the compound presented an MIC of 626.62 µM and nystatin presented an MIC of 8.0 µM. When tested in combination, compound 6 presented an MIC of 313.31 µM and nystatin presented an MIC of 3.2 µM, thus demonstrating an additive effect (0.5 < FIC ≤ 1); see Table 5 [79].
## 2.3. Evaluation of the Antibacterial Activity of the Derivatives
According to the results shown in Table 6, when observing the antibacterial activity of the compounds against strains of S. aureus (ATCC-35903), S. epidermidis (ATCC-12228), and P. aeruginosa (ATCC-25853), it was verified that of the 20 tested compounds, 9 were bioactive. 4-isopropylbenzylcinnamide [18] was the most potent (MIC = 458.15 µM), followed by decyl cinnamate [9], which for all tested strains presented an MIC = 550.96 µM. Benzyl cinnamate [10] was equipotent (MIC = 537.81 μM) to compound 9 against S. aureus ATCC-35903 and S. epidermidis ATCC-12228, and it was less active (1075.63 µM) against P. aeruginosa ATCC-25853.
## 2.3.1. Minimum Bactericidal Concentration (MBC)
Antibacterial substances can be classified as bacteriostatic or bactericidal. This can be established by calculating the MBC/MIC ratio. A bactericidal effect is considered when the MBC/MIC ratio is ≤4, and a bacteriostatic effect is considered when the ratio is >4 [76]. In the present study, it was possible to determine that the compounds with better results against bacterial strains were also characterized as bactericidal (Table 7).
## 2.3.2. Association Test Using the Checkerboard Method
The best microdilution test results were obtained with compound 18 (for bacterial strains). This compound was then tested in combination with amoxicillin (an antimicrobial of first choice in the treatment of infections caused by S. aureus) to analyze its synergistic effect using the Checkerboard method.
When tested alone, the compound presented an MIC of 128.0 µg/mL. When tested alone, amoxicillin presented an MIC of 0.015 µg/mL. When tested in combination, the compound presented an MIC of 64.0 µg/mL and amoxicillin presented an MIC of 0.0005 µg/mL, demonstrating an additive effect (0.5 < FICI ≤ 1); see Table 8 [79].
## 2.4. Molecular Docking
Potential targets identified during the target docking predictions for compounds 6 and 18 in C. albicans and S. aureus, respectively, are reported in Table 9. The table contains the UniProt accessions for all predicted potential targets, the ID given to each target, the compound corresponding to each target, a brief functional description, and a column indicating whether the protein structure was retrieved from the Protein Data Bank database or obtained via homology modeling. In total, 18 potential targets were identified for compound 6 in C. albicans and 10 were predicted for compound 18 in S. aureus. In both cases, the potential targets of the chemicals covered a wide range of functions.
As described in the Methods section, the compounds were docked into the proteins listed in Table 9. The full results of the molecular docking calculations are given as Supporting Information in Table S1, and the scores of the top scored ligand conformers by target are presented in Table 10. For caTIM10, we were unable to obtain a complete homology model, and no valid docking pose was produced for caCDC42. However, three different docking conditions were explored for caTMP1: compound 6 in the absence of dUMP and 5,10-methylene tetrahydrofolate, docking in the dUMP-binding site in the presence of the cofactor, and docking in the 5,10-methylene tetrahydrofolate cavity with dUMP present.
The docking process produced 62 complexes fulfilling the selection criterion for additional analyses (aggregated Z-score larger than 1). Overall, these calculations showed that the best scored targets of compound 6 in C. albicans were RPD3, HOS2, and IMA1. The best docking scores in S. aureus were obtained for the complexes of compound 18 with FABH, MENB, and GAR. Despite being a widely used tool for computer-aided drug discovery, molecular docking tools employ very simple scoring functions. For this reason, all 62 selected complexes were subjected to MD simulations, and estimations of their free binding energies were performed based on these simulations. The use of MD simulations to refine molecular docking results has been shown to provide better estimates of free energy in ligand–receptor complex binding [80].
Of the predicted complexes, caUGA1 and caUGA11 were excluded from the MD simulation analyses because we could not find Amber parameters for the Fe2S2 cofactor coordinated by the aspartic acid residues present in these receptors. The MD simulations led to a total simulation time of 1.14 µs for all complexes. The predicted free binding energies and their components for the 57 investigated complexes are provided as Supporting Information in Table S2. The results for the best (lowest) energy conformer by target are presented in Figure 3. The results of the free binding energy predictions agreed with those obtained from molecular docking predictions regarding the best ranked molecular target in each microorganism. That is, the most probable targets of compound 6 in C. albicans were caHOS2 and caRPD3, while saFABH was the most likely target of 18 in S. aureus. Notably, for both microbes, the free binding energies derived from the MD simulations were able to separate the top ranked targets better than molecular docking. Based on these results, the predicted binding modes for compound 6 to caHOS2 and 18 to saFABH were analyzed in detail. The 6–caRPD3 complex was excluded from the analysis because all residues in the binding cavity of this receptor and caHOS2 were conserved. In addition, the orientation of the ligand in the predicted complex with caRPD3 overlapped with that predicted for caHOS2.
Figure 4 shows the complexes predicted for compound 6 with caHOS2 and compound 18 with saFABH. For depiction, the 100 ligand conformations present in the same number of MD snapshots employed for MM–PBSA calculations were clustered. The centroid of the most populated cluster was selected as the representative conformation of the complex. The residues labeled in Figure 4 are those interacting with the ligands in at least $50\%$ of the analyzed MD snapshots. The figure was prepared using UCSF Chimera [81], the frequencies of the compound–receptor interactions were analyzed with Cytoscape [82], and ligand–receptor interaction diagrams were obtained using LigPlot+ [83].
## 3. Discussion
Cinnamic acid [1] presented no activity against the studied strains. Compared with its derivative compound 2 (methyl cinnamate), it was observed that alteration of the carboxylic group to an ester function resulted in a bioactive derivative with an MIC of 789.19 μM against all tested Candida strains and an MIC of 1578.16 μM against A. flavus and P. citrinum.
The presence of the ethyl group in compound 3 potentiated its pharmacological response (MIC = 726.36 μM), possibly due to an increase in lipophilicity and greater penetration of the compound into biological membranes. Indeed, the increase in carbon chain length increased the antifungal action of compound 6 (butyl cinnamate, MIC = 626.62 μM). There are several studies and lipophilicity has been extensively studied and is considered one of the most important parameters influencing antifungal activity.
The compound propyl cinnamate [4] was bioactive against all tested strains, with an MIC = 672.83 μM. However, its isomer, compound 5 (R = isopropyl), was only bioactive against yeast strains (MIC = 672.83 µM).
Compounds 8 (R = isopentyl) and 7 (pentyl cinnamate) presented no activity against the tested Candida species. However, compound 7 was weakly bioactive against A. flavus and P. citrinum, with an MIC = 2345.39 μM. Interestingly, the higher alkyl volume at the terminal portion of compound 8 resulted in inactivity against both fungal species.
compound 9 (decyl cinnamate) was bioactive against all Candida strains, with an MIC = 1101.92 µM, corroborating the results of a previous study [78] that reported on decyl 4-chlorocinnamate with antifungal action against strains of C. albicans ATCC 90028, C. glabrata ATCC 90030, C. krusei ATCC 34125, and C. guilliermondii ATCC 22017 (MIC = 3.10 μmol/mL, 3.10 μmol/mL, 3.10 μmol/mL, and 1.15 μmol/mL, respectively), evidencing the contribution of the decyl group in cinnamate analogs to the antifungal action.
Reduced biological activity (MIC = 1075.63 µM and 2151.26 µM, respectively) was noticed in compound 10 (benzyl cinnamate) compared with compound 6. The introduction of an aromatic ring as a radical, with or without substituents, resulted in a loss of antifungal activity, except for compounds 17 and 18. The molecular volume of these groups may have influenced this change in biological potency.
Of the studied amides, only compounds 17 and 18 were bioactive. The activity of compound 17 (4-chlorobenzyl cinnamide) was weak (MIC = 2021.31 μM) and specific for filamentous fungal strains. compound 18 was bioactive against all studied fungal strains, with an MIC = 1832.62 μM for C. albicans (ATCC-76485) and C. tropicalis (ATCC-13803) strains and an MIC = 916.31 μM for C. glabrata (ATCC-90030), A. flavus (LM-171), and P. citrinum (ATCC-4001).
To better understand the mechanism of the antifungal action of the derivatives, compounds 4 and 6 were subjected to a test to verify the mode of action on the cell wall and plasmatic membrane of the fungus using strains of C. albicans ATCC-76485 and P. citrinum ATCC-4001. The test results (Table 3 and Table 4) showed that there was a direct interaction between the molecules and ergosterol, a component of the fungus cell membrane, and with sorbitol, an osmotic protector of the cell wall.
Antibacterial activity increased with the length of the carbonic radical chain in compound 2 (methyl cinnamate) with an MIC = 789.19 µM, in compound 3 (ethyl cinnamate) with an MIC = 726.36 µM, and in compounds 4 (propyl cinnamate), 6 (butyl cinnamate), and 9 (decyl cinnamate) with MIC = 672.83 µM, 672.83 µM, and 550.96 µM, respectively, against all studied bacteria. These results suggest an increase in the liposolubility-augmented passage through the biological membrane. compound 7 (pentyl cinnamate) with five carbons in the main chain was inactive against S. aureus ATCC-35903.
compound 5 (with an isopropyl group) was bioactive against all tested bacterial strains; however, compound 8 (with an isopentyl group) was inactive, confirming that a greater carbon chain length with a bulky terminal group can result in steric effects that influence bioactivity. In the aryl derivatives group, only compound 18 (4-isopropylbenzylcinnamide) was bioactive against the studied strains, with the best antibacterial profile of the entire collection (MIC = 458.15 µM). The presence of the isopropyl group attached to the aromatic ring was important for antibacterial activity of this compound. In the Checkerboard test, the compounds with the best results (6 and 18) both showed an additive effect when associated with the reference drug.
Subsequently, the antifungal and antibacterial activity of compounds 6 and 18 were investigated through a molecular modeling study. For caHOS2, as well as for caRPD3, the carbonyl oxygen in compound 6 directly points to the Zn2+ ion. Furthermore, the phenyl ring of the ligand was found to be positioned in parallel with F233 and F177 at the entrance of the binding cavity and to allow for π–π stacking with these residues. This moiety also interacts with D126. These stacking interactions, as well as the strong electrostatic interaction predicted with the metal ion at the active site, are likely to make the largest contributions towards complex stability. In addition, the central enoate group presents contacts with H167, H168, and H205. However, the butyl tail was found to occupy the bottom of the binding cavity, comprising a mostly hydrophobic tunnel flanked by M56, G165, C178, G328, and G329.
In the complex predicted for compound 18 with saFABH, the 4-isopropylbenzyl group occupies the entrance of the binding site and forms a large network of interactions that includes F157, M201, V206, H238, A240, I244, N268, and F298. Two hydrogen bonds contributing to the stability of the complex were predicted: carbonyl oxygen serves as an acceptor for the backbone of G300 and amide nitrogen acts as a donor to the F298 backbone. Finally, the other side of the compound accommodates a hydrophobic pocket formed by L119, L142 I145, T146, F157, and F400 of the second saFABH monomer. This phenyl ring orients favorable π–π stacking interactions with the latter two phenylalanine residues. These modeling results could explain both the antifungal activity of compound 6 and the antibacterial activity of compound 18. Furthermore, caHOS2 has been shown to be a regulator of the essential Hsp90 protein [84]. In antifungal agents, HOS2 inhibition has been demonstrated against C. albicans, and it can even overcome resistance to azole drugs in this fungus [85]. Our results suggest that HOS2 and other histone deacetylases (such as RPD3) are potential antifungal drug targets [86,87,88]. Additionally, FABH is an essential enzyme for the synthesis of fatty acids in bacteria, and it has been investigated for its potential as a drug target [89]. In the specific case of S. aureus, FABH has been validated as a target of many chemical compounds presenting antibacterial activity [90,91,92,93].
Altogether, these modeling predictions were consistent with the antifungal and antibacterial activities observed for compounds 6 and 18, respectively. Although target-specific experiments are required to test these hypotheses, the presented results will be useful in guiding future investigations of the mechanism of action of these compounds.
## 4. Conclusions
Nineteen compounds derived from cinnamic acid (2–20) were synthesized, and eight of them presented antimicrobial activity. Compounds 4 and 6 exhibited the best antifungal results, and compounds 9 and 18 presented the best antibacterial results. Compounds 6 and 18 presented an additive effect with differing antibiotics. Compounds 3 and 6 promoted antifungal activity, both acting on the cell membrane (sorbitol assay) and on the fungal cell wall (ergosterol assay). In the Checkerboard association test of the most bioactive compounds, 6 and 18 presented an additive effect towards inhibitory action. According to the computational results, the most likely targets of compound 6 in C. albicans were caHOS2 and caRPD3, while saFABH was the most likely target of compound 18 in S. aureus. For caHOS2, and for caRPD3, the carbonyl oxygen of compound 6 was found to directly point to the Zn2+ ion. Furthermore, the phenyl ring of the ligand was shown to be positioned parallel to F233 and F177 at the entrance of the binding cavity, thus allowing for π–π stacking with these residues. The central enoate group made contact with H167, H168, and H205, and the butyl tail occupied the bottom of the binding cavity, comprising a mostly hydrophobic tunnel flanked by M56, G165, C178, G328, and G329. In the complex predicted for compound 18 with saFABH, the 4-isopropylbenzyl group was shown to occupy the entry of the binding site and to form a large network of interactions that included F157, M201, V206, H238, A240, I244, N268, and F298. Two hydrogen bonds that contribute to the stability of the complex were predicted: carbonyl oxygen serves as an acceptor for the G300 backbone and amide nitrogen acts as a donor for the F298 backbone. compound 18 settles into a hydrophobic pocket formed by L119, L142, I145, T146, F157, and F400 of the second saFABH monomer. This phenyl ring is favorable for π–π stacking interactions with the last two phenylalanine residues. Our data indicate that these compounds can be used as prototypes to develop structural analogs with better antimicrobial profiles.
## 5.1. Chemistry
All the chemical products used during synthesis were from Sigma-Aldrich. The 400 1H-NMR (nuclear magnetic resonance) and 100 MHz 13 C-NMR, and 500 1H-NMR and 125 MHz 13 C-NMR spectra were recorded on VARIAN MERCURY, BRUKER-ASCEND, and VARIAN-RMN-SYSTEM spectrometers, respectively. Chemical shifts (δ) are expressed in parts per million (ppm) using TMS as an internal standard. Spin–spin multiplicities are given as s (singlet), brs (broad singlet), d (doublet), t (triplet), q (quartet), qu (quintet), sext (sextet), sept (septet), and m (multiplet). Column adsorption chromatography (CC) was performed on silica gel (Merck 60, 230–400 mesh); analytical TLC was performed on pre-coated silica gel plates (Merck 60 F254). Melting points were determined with a Microquímica apparatus (Microquímica equipamentos LTDA, Model MQAPF 302, Serial No.: $\frac{403}{18}$, Palhoça, Brazil) at a temperature measurement range of 10 °C to 350 °C. All reactions were monitored with analytical thin layer chromatography.
## 5.1.1. Synthesis of Compounds 2–8
To a 100 mL flask, cinnamic acid (0.25 g, 1.69 mmol) and alcohol (50 mL) were added in the presence of sulfuric acid (0.4 mL); this mixture was then heated under reflux until the completion of the reaction (5–24 h), which was verified with single-spot TLC [51]. Spectroscopic data for the compounds in this study are available in the Supplementary Materials.
## 5.1.2. Synthesis of compounds 9 and 14
A mixture of cinnamic acid (0.2 g, 1.35 mmol), triethylamine (0.73 mL), and halide (1.39 mmol) in acetone (16.4 mL) was heated under reflux until a complete reaction (24 h), which was verified with single-spot TLC [51]. Spectroscopic data for the compounds in this study are available in the Supplementary Materials.
## 5.1.3. Synthesis of Compounds 10–13 and 15–20
A mixture of cinnamoyl chloride (0.1 g, 0.6 mmol) and the corresponding alcohol or amine (0.6 mmol) in pyridine (1.0 mL) was heated under reflux until a complete reaction (3–24 h), which was verified with single-spot TLC [94]. Spectroscopic data for the compounds in this study are available in the Supplementary Materials.
## 5.2.1. Microorganisms
The 20 selected compounds were checked for antifungal activity against strains of C. albicans (ATCC-76485), C. tropicalis (ATCC-13803), C. glabrata (ATCC-90030), A. flavus (LM-171), and P. citrinum (ATCC-4001), and their antibacterial activity was evaluated against strains of S. aureus (ATCC-35903), S. epidermidis (ATCC-12228), and P. aeruginosa (ATCC-25853). The strains were acquired at the MICOTECA of the Mycology Laboratory, Department of Pharmaceutical Sciences (DCF), Health Science Center (CCS) of the Federal University of Paraíba. All strains were kept on Sabouraud dextrose agar (SDA) and in brain heart infusion broth (BHI) at a temperature of 4 °C, and they were used for the assays at 24–48 h in SDA/BHIA while incubated at 35 ± 2 °C. The microorganism suspension was prepared according to the 0.5 McFarland standard to obtain 1–5 × 106 CFU/mL. Standard drugs, nystatin (yeast) and amoxicillin, were used as controls.
## 5.2.2. Determination of Minimum Inhibitory Concentration (MIC)
MIC values were determined using the broth microdilution method and 96-well U-shaped plates. In each well, 100 µL of liquid medium from Roswell Park Memorial Institute (RPMI) doubly concentrated with 100 mL of product solution was added to the first row of plate wells. Through serial dilutions, concentrations of the evaluated compounds ranging from 1000 μg/mL to 2.0 μg/mL. Subsequently, 10 µL of inoculum was added to the wells in each column of the plate and the culture medium with nystatin. The plates were then incubated at 37 °C for 24–48 h. For each strain, the MIC was defined as the lowest concentration capable of inhibiting fungal growth in the wells, visually observed in comparison with the control. All tests were performed in duplicate, and the results are expressed as an arithmetic mean of the MIC values obtained in both tests [95].
## 5.2.3. Determination of Minimum Fungicidal Concentration (MFC)
After the MIC values were determined, 10 μL aliquots of the supernatant from the wells in which complete fungal growth inhibition (MIC, MIC × 2, and MIC × 4) was observed in the microdilution plates were added to 100 μL of RPMI broth contained in new culture plates. The plates were incubated for 24–48 h at 35 ± 2 °C. The minimum fungicidal concentration (MFC) was considered as the lowest concentration of the product that was able to inhibit the growth of microorganisms [96].
## 5.2.4. Determination of Minimum Bactericidal Concentration (MBC)
After the MIC values were determined, 10 μL aliquots of the supernatants were removed from the wells of the microdilution plates at concentrations of MIC, MIC × 2, and MIC × 4 for each strain and inoculated into new microdilution plates containing only a BHI medium. The assay was performed in triplicate. The plates were incubated at 35 ± 2 °C for 24 h, and bacterial growth was observed. The MBC was defined as the lowest concentration capable of causing the complete inhibition of bacterial growth [96,97].
## 5.2.5. Mechanism of Antifungal Action for Amides
[1] Sorbitol Assay: The microdilution technique was performed in the presence of sorbitol (anhydrous D-sorbitol) (INLAB laboratory) to determine the mode of action of the compounds on the cell wall of C. albicans CBS 562. For this test, the inoculum was prepared with sorbitol to a final concentration of 0.8 M. The plates were incubated, and readings were taken at 24 h and 48 h post-incubation. Caspofungin was used as a positive control at an initial concentration of 5 mg/mL [76,98].
[2] Ergosterol Test: This test was performed using the microdilution technique, as previously described, in the presence of exogenous ergosterol at 400 μg/mL. Nystatin was used as a positive control. The plates were incubated, and readings were taken at 24 and 48 h [76,98].
## 5.2.6. Association Study Using the Checkerboard Method
In a 96-well plate, all the wells were filled with 100 μL of SD broth. Compounds 6 and 18 were initially dissolved in DMSO and further diluted in SD broth Then, 100 μL of the compound was added to the initial column (wells A1 to H1) and serially diluted up to the 10th column. The 11th and 12th columns, respectively, served as a drug-only control and a growth control. Similarly, a drug control was initially dissolved in DMSO and diluted in broth to obtain a 4 × concentration of the desired drug concentration. It was separately prepared in each tube for the desired concentration. One hundred microliters of the first control drug concentration was added to the first row A wells A1 to A11 but not to A12 (the growth control). This process was repeated with the respective drug concentrations for rows B to G (but not for row H). All wells were thoroughly mixed by pipette aspiration to obtain proper drug dispersion. One hundred microliters (100 μL) of the contents of each well was transferred to another 96-well plate, which was marked as a replica plate. Finally, 100 μL of the inoculum (1 × 103 to 3 × 103 CFU/mL) was added to all wells, and the plates were incubated at 37 °C for 7 days [79].
## 5.3.1. Target Selection
The previously described homology-based target fishing approach was employed to identify potential targets for compounds 6 and 18, respectively, in C. albicans and S. aureus [74,98]. Potential targets for each compound were separately predicted using the Similarity Ensemble Approach (SEA) web server [99]. For each compound, the sequences of the targets provided by SEA were retrieved from the Uniprot database. The sequences of the targets predicted for compound 6 were then submitted to a Blast [100] search using the proteins from C. albicans (taxid 5476) included in the Reference Protein (refseq_protein) database using the NCBI web implementation of Blast [101]. The same process was repeated for compound 18 using proteins from S. aureus (taxid 1280). Two criteria were used to select the potential targets: the selected proteins had to have a shared identity of at least $45\%$ with the proteins identified during target fishing, and at least of $75\%$ of their sequences had to be covered by the alignment obtained from the Blast search. Proteins fulfilling the latter criteria were selected for modeling studies.
## 5.3.2. Molecular Docking
An initial three-dimensional (3D) conformation was generated for each compound with OpenEye’s Omega [102], and partial atomic charges of the am1bcc type were added to these with MolCharge [103]. The 3D structures of a few targets were available in the Protein Data Bank (database). These targets were ACPS (PDB code 5cxd), MEMB (PDB code 2uzf), FABH (PDB code 6kvs), and GBSA (PDB code 5eyu) from S. aureus and TDH3 (PDB code 7u4s) from C. albicans. The remaining targets predicted for compounds 6 and 18 had no available 3D structure, and homology models were generated for them on the SwissModel web server [104]. Various homology models were generated for each protein, and the highest QMEANDisCo global score by potential target was selected for molecular docking calculations.
For molecular docking, the previously reported procedure was followed [74,105]. The Gold software [106] was selected for docking calculations. The binding cavities were defined from either the co-crystallized ligands or the ligands present in the templates of the homology models. Functionally relevant cofactors or metal ions were maintained in the receptor in case they were already present or were transferred to it from the model’s templates. Hydrogen atoms were added to the receptors, and residues pointing to the binding cavity were set to be flexible. The PLP scoring function was selected for primary scoring. A total of 30 docking solutions were obtained and re-scored with the ChemScore, GoldScore, and ASP GoldScore scoring functions.
Considering the average and standard deviations of the scoring values, the scores obtained with each of the four scoring functions were converted to Z-scores at a scoring function level. The resulting Z-scores were then averaged. The ligand poses with aggregated Z-scores ˃ 1 were selected for additional studies. These selected potential complexes were further studied with molecular dynamics (MD) simulations, and free binding energies were predicted from the MD snapshots as described below.
## 5.3.3. Molecular Dynamics Simulations and Free Energy Calculations
MD simulations were carried out with Amber 20 [107] according to previously described methods [1,76]. The same protocol was applied to model all systems, parameterizing the ligands and amino acids with the gaff2 and ff19SB force fields, respectively. For cofactors, Amber parameters were obtained from the database provided by the Bryce Group at The University of Manchester: http://amber.manchester.ac.uk/index.html (accessed on 26 May 2022). Cofactors not included in the latter database such as dUMP and 5,10-methylene tetrahydrofolate were parameterized using the same approach followed for ligands. Parameters for the Zn2+ ion, as well as for its coordinating residues, were retrieved from the Yuan-Ping Pang lab web page: https://www.mayo.edu/research/labs/computer-aided-molecular-design/projects/zinc-protein-simulations-using-cationic-dummy-atom-cada-approach (accessed on 26 May 2022) [108].
Truncated octahedron boxes were generated to enclose the systems that were solvated with OPC water molecules. Systems were neutralized with the addition of Na+ and Cl− ions at a concentration of 0.15 M [109]. Two stages of energy minimization were performed, the first with restraints applied to everything except the solvent and counter ions and the second with no restraints. The systems were next heated from 0 K to 300 K (the temperature during the 20 ps production runs). The heated systems were subsequently equilibrated at constant temperature and pressure for 100 ps. The final system for each complex was used as input for five production runs, each initialized with differing random velocities to better explore each complex’s conformational space. Each production run lasted for 4 ns, totaling 20 ns per complex.
The MM–PBSA method, as implemented in the MMPBSA.py script of Amber 20, was used to estimate the free binding energies. Calculations proceeded with 100 MD snapshots evenly extracted from five production runs. To compute the free binding energies, 20 snapshots per production run were extracted. Only snapshots in the 1 ns to 4 ns time interval were considered for MM–PBSA calculations. The ionic strength for these calculations was set at 150 mM.
## Figures, Scheme and Tables
**Figure 1:** *Reactive sites in the CA structure.* **Figure 2:** *Chemical structures of the prepared compounds.* **Figure 3:** *Predicted free binding energies of compounds 6 (a) and 18 (b) with their predicted targets in C. albicans and S. aureus, respectively.* **Figure 4:** *Predicted binding modes of compounds 6 and 18 to caHOS2 (a) and saFABH (b) with diagrams of the predicted ligand–receptor interactions. The ligands are represented as orange balls and sticks. Labeled residues correspond to those interacting with the receptors in at least $50\%$ of the analyzed MD snapshots. Atoms are shown for residues either forming hydrogen bonds with the ligand or coordinating the Zn2+ ion.* **Scheme 1:** *Synthesis of cinnamic acid derivatives: (a) ROH, H2SO4, reflux; (b) Et3N, RX, acetone, reflux; (c) ROH, pyridine, reflux; (d) RNH2, pyridine, reflux.* TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 TABLE_PLACEHOLDER:Table 3 TABLE_PLACEHOLDER:Table 4 TABLE_PLACEHOLDER:Table 5 TABLE_PLACEHOLDER:Table 6 TABLE_PLACEHOLDER:Table 7 TABLE_PLACEHOLDER:Table 8 TABLE_PLACEHOLDER:Table 9 TABLE_PLACEHOLDER:Table 10
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---
title: Adrenomedullin Improves Hypertension and Vascular Remodeling partly through
the Receptor-Mediated AMPK Pathway in Rats with Obesity-Related Hypertension
authors:
- Hong-Yu Wang
- Fang-Zheng Wang
- Rui Chang
- Qian Wang
- Si-Yu Liu
- Ze-Xiong Cheng
- Qing Gao
- Hong Zhou
- Ye-Bo Zhou
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967515
doi: 10.3390/ijms24043943
license: CC BY 4.0
---
# Adrenomedullin Improves Hypertension and Vascular Remodeling partly through the Receptor-Mediated AMPK Pathway in Rats with Obesity-Related Hypertension
## Abstract
Adrenomedullin (ADM) is a novel cardiovascular peptide with anti-inflammatory and antioxidant properties. Chronic inflammation, oxidative stress and calcification play pivotal roles in the pathogenesis of vascular dysfunction in obesity-related hypertension (OH). Our study aimed to explore the effects of ADM on the vascular inflammation, oxidative stress and calcification in rats with OH. Eight-week-old Sprague Dawley male rats were fed with either a Control diet or a high fat diet (HFD) for 28 weeks. Next, the OH rats were randomly subdivided into two groups as follows: [1] HFD control group, and [2] HFD with ADM. A 4-week treatment with ADM (7.2 μg/kg/day, ip) not only improved hypertension and vascular remodeling, but also inhibited vascular inflammation, oxidative stress and calcification in aorta of rats with OH. In vitro experiments, ADM (10 nM) in A7r5 cells (rat thoracic aorta smooth muscle cells) attenuated palmitic acid (PA, 200 μM) or angiotensin II (Ang II, 10 nM) alone or their combination treatment-induced inflammation, oxidative stress and calcification, which were effectively inhibited by the ADM receptor antagonist ADM22-52 and AMP-activated protein kinase (AMPK) inhibitor Compound C, respectively. Moreover, ADM treatment significantly inhibited Ang II type 1 receptor (AT1R) protein expression in aorta of rats with OH or in PA-treated A7r5 cells. ADM improved hypertension, vascular remodeling and arterial stiffness, and attenuated inflammation, oxidative stress and calcification in OH state partially via receptor-mediated AMPK pathway. The results also raise the possibility that ADM will be considered for improving hypertension and vascular damage in patients with OH.
## 1. Introduction
Obesity is a major risk factor for cardiovascular diseases (CVD), which increased morbidity and mortality in the world [1]. Obesity-related hypertension (OH) is closely associated with chronic heart failure (CHF) and stroke partly due to vascular abnormalities such as vascular remodeling and the increased arterial stiffening [2]. Inflammation, oxidative stress and calcification have emerged as critical mediators of OH-associated vascular damage [2]. The atherogenic dyslipidemia, proinflammatory state and the overactivation of renin-angiotensin-aldosterone system (RAAS) have been linked to OH [3]. Therefore, the improvement of vascular abnormalities caused by OH may prevent the development of CVD associated with obesity.
Normal vascular smooth muscle cells (VSMCs) are highly differentiated cells within the medial layer of blood vessels. They perform a critical role in regulating blood pressure and vascular function, but their dysfunction contributes to vascular pathologies in OH [4]. The migration, proliferation and phenotype transition (from a contractile phenotype to a synthetic phenotype) of VSMCs are the core processes in vascular remodeling, which can be influenced by inflammation and oxidative stress. If this phenotypic switching is excessive, it will promote the increases of extracellular matrix synthesis and calcification of VSMCs that further participate in vascular remodeling and the increase in stiffness and reduce the elasticity of artery wall leading to the development of occlusive vascular diseases, such as postangioplasty restenosis, atherosclerosis, hypertension and aneurysm formation [4,5].
The cardiovascular risk factors RAAS and free fatty acids (FFAs), such as the main saturated fatty acid palmitic acid (PA), increase the incidence of vascular abnormalities in subjects with OH [4,6,7]. High levels of circulating angiotensin II (Ang II) and PA are known to be important triggers for vascular damage during the development of OH [4,5]. They can also promote oxidative stress, inflammation and calcification in VSMCs [8,9,10,11,12].
Adrenomedullin (ADM) is an endogenous active peptide with many functions, including tissue repair, anti-inflammatory and antioxidant effects, and organ protection [13,14,15]. It was expected to be a candidate therapeutic agent for CVD, including CHF [15]. ADM and ADM receptors are highly expressed in vascular tissues, and plasma ADM level is markedly increased in people with obesity [16,17,18] indicating that it may be critically involved in the pathogenesis of OH.
At present, the potential effects and mechanisms of ADM to treat OH, especially in blood vessels, have not been thoroughly explored. Our recent work has found that ADM could improve cardiac remodeling and function in rats with OH [19]. Therefore, it is better to explore the effects and molecular mechanisms linking ADM to vascular pathophysiology in OH, and to assess the therapeutic targets that may be of specific benefit in combating vascular diseases in OH.
## 2.1. Animals
Eight-week-old male Sprague Dawley rats (300~350 g) were randomly assigned to Control group ($$n = 8$$), fed a Control diet (fat provided $12\%$ kilocalories, TROPHIC Animal Feed High-tech Co Ltd., Nantong, China) and high fat diet (HFD, fat provided $45\%$ kilocalories, TROPHIC Animal Feed High-tech Co Ltd, Nantong, China) group ($$n = 37$$). Rats were housed and permitted access to tap water and diet (Control diet or HFD) ad libitum in a room with a 12 h light/dark cycle and controllable temperature and humidity for 28 weeks. The experiments were approved by the animal research ethics committee of Nanjing Medical University (1911016, 14 September 2020) and conformed to the Guidelines for the Care and Use of Laboratory Animals (NIH publication, eighth edition, 2011). The criterion for the OH rats was that the body weight (BW) was $120\%$ higher than that of the mean weight of control rats, and the systolic blood pressure (SBP) was more than or equal to 140 mmHg after 28-week HFD feeding. OH rats ($$n = 17$$) were further randomized into two groups and continued to receive the HFD for 4 weeks. The intraperitoneal injection of ADM (7.2 μg/kg/day) was applied to the OH rats ($$n = 9$$), and the remaining rats ($$n = 8$$) received an equal volume of saline. At the end of 32 weeks, the BW and SBP were measured in conscious state. The heart and visceral white adipose tissue (WAT) were removed under anesthesia by using sodium pentobarbital and then weighted.
## 2.2. Measurement of SBP and Heart Rate
The SBP of tail artery in waking state were measured by a computerized tail-cuff system (NIBP, ADInstruments, Sydney, NSW, Australia). The rat was trained for SBP detection to obtain a steady pulsation of tail artery before the formal experiment began as previously described [19]. In a rat, the obtained values were analyzed by averaging 10 measurements.
## 2.3. Aortic Samples Preparation
Under anesthesia, the whole aortic tissue of rat was removed quickly. One part of the aortic tissue was kept at −80 °C for further analysis, and the other was incubated in formalin for 8 h. The sections of aortic tissue slices (6~8 μm) were used for hematoxylin-eosin (H&E), dihydroethidium (DHE) and alizarin red staining, respectively.
## 2.4. Alizarin Red Staining
For evaluating calcification, aortic slides were dehydrated and rinsed in distilled water, and the cultured A7r5 cells (rat thoracic aorta smooth muscle cells) grown in 6-well plates were fixed in $4\%$ paraformaldehyde for 15 min after washing with PBS three times. The alizarin red solution (pH 4.2, $1\%$) was used to incubate the aortic slides or A7r5 cells for 3–5 min at room temperature and it was washed with distilled water. Finally, the staining was observed by microscopy.
## 2.5. Measurement of Plasma Insulin and Triglyceride
The tail vein blood was collected for the measurement of fasting insulin and triglyceride levels. Plasma was obtained by centrifugation of blood samples at 900× g for 10 min at 4 °C with a centrifuge (MicroCL 17R, Thermo Fisher Scientific Inc., Waltham, MA, USA). The plasma level of insulin was determined by Enzyme-linked immunosorbent assay (Elisa) by using a kit (USCN Business Co., Ltd., Wuhan, China) referring to the manufacturer’s instructions. The triglyceride level was detected by colorimetric assay with a kit (Jiancheng Bioengineering, Nanjing, China) according to the manufacturer’s descriptions. The optical density at a certain wavelength was measured by a microplate reader (ELX800, BioTek, Winooski, VT, USA).
## 2.6. Cell Culture and Treatment
A7r5 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) containing $10\%$ fetal bovine serum (FBS), 100 U/mL penicillin and 100 μg/mL streptomycin in a 37 °C incubator with $5\%$ CO2. For ADM treatment, the cells were treated with 10 nM ADM for 30 min, then treated with PA or Ang II alone or their combination for 24 h (for detection of inflammation and oxidative stress-related markers) or 7 days (for detection of calcification-related markers). For ADM receptors antagonizing or the inhibition of signaling pathway, 1 μM ADM22-52 or 10 μM AMPK inhibitor Compound C was added into the medium for 30 min before the ADM pretreatment, respectively.
## 2.7. Cell Viability Assay
The A7r5 cells suspension (100 μL) was added into a 96-well plate and cultured in a cell incubator at 37 °C for 24 h. The effect of PA (200 μM), Ang II (10 nM) or ADM (10 nM) alone on cell viability was detected by Cell Counting Kit-8 (CCK8) cell cytotoxicity test referring to the manufacturer’s instructions as previously described [19].
## 2.8. DHE Fluorescence Staining for ROS Level Assay
Reactive oxygen species (ROS) production in aortic tissue or A7r5 cells was detected with DHE staining as previously described [19]. Briefly, the tissue sections (7 μm) or the A7r5 cells (3 × 105 cells/mL) in six-well plates were incubated with 10 μM DHE in PBS for 30 min in a dark and humidified container at 37 °C. Then, they were rinsed with cold PBS for three times and were observed by a fluorescence microscopy (DP70, Olympus Optical, Tokyo, Japan).
## 2.9. Determination of ROS Level and NADPH Oxidase Activity
The enhanced lucigenin-derived chemiluminescence method was adopted to measure the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity and ROS level in aortic tissues or A7r5 cells. Both dark-adapted 100 μM NADPH and 5 μM lucigenin were used to trigger the photon emission and the background chemiluminescence was detected by a luminometer (Turner, CA, USA). The data were presented as the mean of light unit (MLU)/min/mg protein.
## 2.10. Measurement of Calcium Content
Calcium content of the aortic tissues or A7r5 cells was determined by O-cresolphthalein colorimetric (OCPC) method by using a kit (Nanjing Jiancheng Bioengineering, Nanjing, China). The aortic tissues or A7r5 cells were decalcified with HCl at 37 °C for 24 h. The mixed working reagent solution containing OCPC, 8-hydroxyquinoline and ethanolamine buffer were added into the supernatant fluid. The solutions were incubated at 30 °C for 5 min. The absorbance of the compound solution was determined at 600 nm wavelength.
## 2.11. Measurement of Alkaline Phosphatase (ALP) Activity
ALP activity was measured by using an ALP assay kit (Nanjing Jiancheng Bioengineering, Nanjing, China). The proteins were extracted from the aortic tissues or A7r5 cells in $0.05\%$ Triton X-100 in PBS and quantified using a bicinchoninic acid (BCA, ThermoFisher, Waltham, MA, USA) protein assay. The 5 μL supernatant of samples was mixed with reaction mixture including alkaline buffer solution 50 μL mainly containing disodium phenyl phosphate and substrate solution 50 μL mainly containing 4-aminoantipyrine and potassium cyanide. They were incubated at 37 °C for 15 min, then developer 150 μL was added into each well. The absorbance was detected at 520 nm wavelength and the results were normalized to the level of total protein.
## 2.12. Western Blot Analysis
Aortic tissues or A7r5 cells were homogenized in RIPA lysis buffer. After protein quantification, equal quantities of tissues or cells protein lysates were separated by polyacrylamide gel electrophoresis (PAGE) (Bio-Rad), then were electrotransferred to a nitrocellulose membrane as previously described [19]. The membrane was incubated with the primary antibody against α-actin (1:3000), Runt-related transcription factor 2 (Runx2, 1:1000), tumor necrosis factor-α (TNF-α, 1:1000), interleukin-1β (IL-1β, 1:1000), IL6 (1:1000), NOX2 (1:1000), NOX4 (1:1000), ADM (1:1000), calcitonin receptor-like receptor (CRLR, 1:1000), receptor activity modifying protein 2 (RAMP2, 1:1000), RAMP3 (1:1000) or GAPDH (1:3000), respectively, overnight at 4 °C, then secondary antibody (horseradish peroxidase-conjugated anti-rabbit or anti-mouse) for 1 h. The polyclonal antibodies against α-actin, Runx2, ADM, CRLR, RAMP2, RAMP3, IL-1β, IL6, NOX2 and NOX4 were generated by immunizing rabbits and GAPDH monoclonal antibody was generated by immunizing mouse. Band densities were captured by using Odyssey Imaging System (LI-COR Biosciences, Lincoln, Nebraska). Finally, the protein level was evaluated by Image J software and normalized to GAPDH protein expression level.
## 2.13. Reagents and Antibodies
Rat ADM (molecular formula: C242H381N77O75S5) was obtained from Bachem (Bubendorff, Switzerland). PA and Compound C were purchased from Sigma Aldrich (St. Louis, MO, USA). ADM22-52 was purchased from Anaspec (Fremont, CA, USA). DMEM, $0.25\%$ trypsin-EDTA, fetal bovine serum, trypsin and streptomycin/penicillin were from Thermo Fisher Scientific (Waltham, MA, USA). The primary antibodies against α-actin and Runx2 were purchased from Abcam (Burlingame, CA, USA). ADM, CRLR, RAMP2, RAMP3, TNF-α and IL6 were obtained from Affinity Biosciences (Pottstown, PA, USA). The antibodies of IL-1β, NOX2, NOX4 and GAPDH were from Proteintech (SANYING, Wuhan, China).
## 2.14. Statistics
The GraphPad Prism version 8.0.2 (San Diego, CA, USA) software was used in this study to analyze all data. Shapiro–Wilk test were used to evaluate normality of the data. Homogeneity of variances was assessed by the F test or Brown–Forsythe test. All data showed normal distribution and passed equal variance testing. Statistical analyses between two groups with normal distribution were performed using a two-tailed unpaired t-test as indicated in figure legends. One-way or two-way ANOVA followed by Bonferroni post hoc analysis was employed in the analyses of more than two groups with normal distribution as indicated in figure legends. The data were shown as mean ± SEM. Statistical significance was accepted at $p \leq 0.05.$
## 3.1. The Effects of ADM on Body Weight, Metabolic Parameters, Blood Pressure and Left Ventricular Mass in HFD-Induced OH Rats
In this study, we found that HFD feeding for 32 weeks significantly led to obesity, hypertension ($p \leq 0.0001$, Figure 1A,B,E,F), myocardial hypertrophy ($p \leq 0.0001$, Figure 1G) and the increases of plasma triglyceride and insulin levels ($p \leq 0.0001$, Figure 1C,D), which were effectively inhibited by exogenous ADM application for 4 weeks ($p \leq 0.0001$ for Figure 1A,B,E–G, $$p \leq 0.0065$$ for Figure 1D, $$p \leq 0.0201$$ for Figure 1D). HFD feeding also significantly increased vascular remodeling, ROS level and calcification as demonstrated by H&E staining (Figure 1H), DHE staining (Figure 1I) and alizarin red staining (Figure 1J), respectively, which were markedly alleviated by ADM application in HFD-fed rats. Taken together, these results indicate that ADM can improve HFD-induced hypertension, vascular remodeling and the increase in vascular stiffness in obese state.
## 3.2. The Endogenous Expression of ADM and Its Receptor System and The Effects of ADM on Aortic Inflammation, Oxidative Stress and Calcification in HFD-Induced OH Rats
Western blot results showed that the endogenous protein expressions of ADM and its receptor system including CRLR, RAMP2 and RAMP3 were significantly increased in the tunica media of aorta in OH rats when compared to the control rats ($$p \leq 0.0014$$, $p \leq 0.0001$, $$p \leq 0.0002$$, $p \leq 0.0001$, respectively. Figure 2A–D). The results suggest that ADM and its receptor system may play important roles in regulating the function of VSMCs under OH state. In the vasculature, OH is associated with substantial inflammatory and oxidative responses, which mediate the pathogenesis of vascular injury and remodeling [20]. We examined the protein expressions of pro-inflammatory cytokines in tunica media of aorta. The results in OH rats showed that TNF-α, IL-1β and IL6 protein levels were significantly up-regulated when compared to the control rats ($p \leq 0.0001$, $$p \leq 0.0065$$, $$p \leq 0.0011$$, respectively. Figure 2F–H), which were effectively reduced by ADM application when compared to OH rats ($p \leq 0.0001$, $$p \leq 0.0031$$, $$p \leq 0.0009$$, respectively. Figure 2F–H). NADPH oxidase is a dominant enzyme to catalyze the formation of ROS, which plays a role in the development of CVD [21]. In this study, we examined the ROS level (Figure 2K), NADPH oxidase activity (Figure 2L) and its two important catalytic subunits NOX2 and NOX4 protein expressions (Figure 2I,J) to reflect the oxidative stress state. They all had a significant increase in aorta of OH rats compared to the control rats (all $p \leq 0.0001$), and ADM administration significantly decreased their levels compared to OH rats ($p \leq 0.0001$, $$p \leq 0.0003$$, $$p \leq 0.0002$$, and $$p \leq 0.0003$$, respectively. Figure 2I–L). These results suggest that ADM is involved in the improvement of OH-induced vascular inflammation and oxidative stress. Both inflammation and oxidative stress can induce the osteogenic transition of VSMCs which promotes the occurrence of vascular calcification resulting in the increased vascular stiffness [22]. In this study, we also examined the calcification-related indicators, namely calcium content, ALP activity, protein expressions of Runx2, a transcription factor essential for bone formation and α-actin, a phenotypic marker of smooth muscle cells, in aorta of HFD-induced OH rats. Compared to the control rats, the results showed that there were marked increases in the calcium content, ALP activity and the protein expression of Runx2 ($p \leq 0.0001$, $p \leq 0.0001$, and $$p \leq 0.0483$$, respectively. Figure 2N–P), but the α-actin protein expression was significantly reduced ($$p \leq 0.0007.$$ Figure 2M). These changes were remarkably reversed by ADM administration compared to OH rats, ($p \leq 0.0001$, $p \leq 0.0001$, and $$p \leq 0.0175$$, respectively. Figure 2N–P; and $$p \leq 0.0023.$$ Figure 2M) suggesting that ADM can effectively improve vascular stiffness involving the inhibition of arterial medial calcification and osteoblastic phenotypic transition of VSMCs in OH state.
## 3.3. The Effects of Exogenous ADM Pretreatment on PA-Induced Cell Viability, Inflammation and Oxidative Stress in A7r5 Cells and Its Possible Mechanisms
Elevated FFAs levels are a common feature of obesity and perform an etiological role in the pathogenesis of some diseases. In particular, the saturated fatty acid PA, which makes up 30–$40\%$ of high plasma FFAs concentration, is a major contributor to vascular diseases. However, the roles and mechanisms of ADM in PA-induced damage in vascular smooth muscles cells (VSMCs) are not entirely clear. Therefore, PA was used in this study to mimic the high-saturated fatty acids environment of obesity. In A7r5 cells, the Western blotting results showed that PA (200 μM) treatment for 24 h induced the higher protein expressions of ADM, CRLR, RAMP2 and RAMP3 than those in the control group ($$p \leq 0.0119$$, $$p \leq 0.0054$$, $p \leq 0.0001$, and $$p \leq 0.0100$$, respectively. Figure 3A–D). CCK8 results showed that ADM alone did not produce significant changes in cell viability compared to the control group ($p \leq 0.9999$, Figure 3E), but PA alone significantly decreased it ($p \leq 0.0001$, Figure 3E) when compared to the control group. More importantly, ADM pretreatment obviously improved the cell viability in A7r5 cells ($p \leq 0.0001$, Figure 3E). We also observed that ADM in A7r5 cells significantly reduced the increased protein levels of PA-induced proinflammatory cytokines TNF-α, IL-1β and IL6 (all $p \leq 0.0001$, Figure 3F–H) and oxidative stress-related indicators, namely ROS level, NADPH activity, and NOX2 and NOX4 protein expressions ($p \leq 0.0001$, $$p \leq 0.0116$$, $$p \leq 0.0001$$, and $p \leq 0.0001$, respectively. Figure 3I–L) compared to the PA group. In order to explore the possible mechanisms of ADM’s action, we applied the ADM receptors antagonist ADM22-52 and AMP-activated protein kinase (AMPK) inhibitor Compound C in PA-treated cells, respectively. The results showed ADM22-52 or Compound C pretreatment could effectively attenuate the inhibitory roles of ADM in inflammation and oxidative stress caused by PA in A7r5 cells (Figure 4A–H. (ADM22-52: $$p \leq 0095$$, $p \leq 0.0001$, $$p \leq 0.0001$$, $p \leq 0.0001$, $$p \leq 0.0001$$, $p \leq 0.0001$, $p \leq 0.0001$, respectively. Figure 4A–G); (Compound C: $$p \leq 0040$$, $p \leq 0.0001$, $$p \leq 0002$$, $p \leq 0.0001$, $p \leq 0.0001$, $$p \leq 0004$$, and $p \leq 0.0001$, respectively. Figure 4A–G)) suggesting that ADM exerts anti-inflammatory and antioxidant effects in VSMCs under metabolic stress partly via receptor-mediated AMPK pathway.
## 3.4. The Effects of Exogenous ADM Pretreatment on PA Plus Ang II-Induced Inflammation and Oxidative Stress in A7r5 Cells and Its Possible Mechanisms
Among the potential underlying pathophysiologic mechanisms of OH, overactivation of the RAAS also performs an important role [23]. Increased Ang II level is a major causative factor for obesity-related diseases, such as hypertension, myocardial hypertrophy, chronic kidney disease and so on [23]. Ang II contributes to inflammation, oxidative stress and calcification in the VSMCs [8,9,10]. In this study, we also explored the effects of ADM on the combination of PA plus Ang II-induced inflammation, oxidative stress and calcification. In aorta of OH rats, we found the marked increase in Ang II type 1 receptor (AT1R) protein expression ($$p \leq 0.0027$$, Figure 2E) which in A7r5 cells was also increased in culture with PA for 24 h ($$p \leq 0.0011$$, Figure 5A) compared to the control group. The results indicate that metabolic stress, namely elevated plasma levels of saturated FFAs, promotes the AT1R expression to enhance the pathogenic effects of Ang II on vascular damage. ADM administration notably recovered the cell viability abnormity caused by PA or PA plus Ang II (10 nM) in A7r5 cells ($p \leq 0.0001$, and $$p \leq 0.0008$$, respectively. Figure 5B). Ang II increased cell activity that may be related to the pro-proliferative effect. As we expected, PA plus Ang II induced more significant inflammation, namely the increased protein expression of proinflammatory cytokines TNF-α, IL-1β and IL-6 (all $p \leq 0.0001$, Figure 5C–E), and oxidative stress, namely increased ROS level, NADPH activity and protein expression of NOX2 and NOX4 (all $p \leq 0.0001$, Figure 5F–I) compared to the control group. These above changes were effectively reversed by ADM application (all $p \leq 0.0001$). Moreover, ADM receptors antagonist ADM22-52 (1 μM) and AMPK inhibitor Compound C (10 μM) pretreatment could also significantly inhibit the protective effects of ADM on PA plus Ang II-induced inflammation ($$p \leq 0.0011$$ (IL6), Figure 6C); (all $p \leq 0.0001$, Figure 6A,B,D–G), and oxidative stress Figure 6D–H; (all $p \leq 0.0001$, Figure 6D–G). Furthermore, ADM administration also effectively inhibited PA plus Ang II induced-calcification, and which were significantly reversed by ADM22-52 or Compound C. (Figure 7A–E; all $p \leq 0.0001$, Figure 7A–D). These resuts suggests that receptor-mediated AMPK pathway may involve ADM’s anti-inflammatory, antioxidant and anti-calcification effects in OH state.
## 4. Discussion
In this study, the primary novel findings were that the exogenous ADM application contributed to the improvement of vascular remodeling and stiffness, and lowered blood pressure. ADM alleviated inflammation, oxidative stress and calcification not only in the tunica media of aorta in rats with OH, but also in A7r5 cells-treated by PA. More importantly, we found ADM significantly attenuated the synergistic effects of PA and Ang II-induced inflammation, oxidative stress and calcification, which were partially associated with the receptor-mediated AMPK pathway.
ADM can participate in the regulation of many physiological functions and pathophysiological process of some diseases, such as vasodilation, angiogenesis, organ protection and tissue repair [24,25,26,27,28,29]. In our previous studies, ADM improved cardiac remodeling and function in rats with OH [19]. These findings suggest that ADM may have protective roles in vascular damage in OH state. Indeed, our results confirmed our speculation that exogenous ADM administration improved vascular remodeling and stiffness and decreased blood pressure in rats with OH. It also effectively reduced the protein expressions of proinflammatory factors and the related indicators of oxidative stress and calcification. Therefore, it is speculated that ADM improves vascular remodeling and stiffness partly through its anti-inflammatory, antioxidant and anti-calcific effects in OH-induced vascular injury.
Metabolic stress in obesity state, especially excessive and saturated FFAs, such as PA, and the overactivity of the RAAS, specifically the vasoactive mediator Ang II, appear to be of particular importance in the genesis of vascular damage in OH [6,7,8,9,10,11,12]. In vitro, PA plus Ang II treatment induced more significant inflammation, oxidative stress and calcification. More importantly, ADM application could notably attenuate the synergistic pathogenic effects that suggests ADM may be a more effective peptide for the treatment of vascular diseases in people with OH.
Cardiovascular tissues have highest density of ADM receptors and binding sites [24,25]. In this study, we found that there were higher expression of ADM and its receptor system in aorta of OH rats and their expressions were also upregulated by PA in A7r5 cells. These results suggest that the changes of ADM and its receptor system may exert beneficial effects on blood vessels in OH state. RAMP2 and RAMP3 were the key determinants for biological activities of ADM. The CRLR combining with RAMP 2 or 3 confers specificity of the receptor for ADM [30]. In this study, we applied the ADM receptor antagonist and found that it markedly blocked the inhibitory effects of ADM on PA or PA plus Ang II-induced inflammation, oxidative stress and calcification in A7r5 cells suggesting that ADM may be through the receptor activation to exert its protective roles in vascular diseases in OH state.
AMP-activated protein kinase (AMPK), as a sensor of energy molecules, is closely associated with metabolic stress, diabetes and vascular disorders [31,32,33,34,35,36]. In VSMCs, AMPK activation also involves the improvement of oxidative stress, inflammation and calcification [37,38]. Both intermedin (IMD), also known as adrenomedullin 2 (ADM2), and ADM belong to the calcitonin/calcitonin gene-related peptide family and they exert some similar functions in some organs or cells through similar mechanisms [39]. IMD can activate AMPK to alleviate insulin resistance, vascular calcification and cardiac hypertrophy [40,41,42]. Thus, we speculate that the protective roles of ADM in this study may be through the activation of AMPK. In vitro experiments, we applied the AMPK inhibitor Compound C to confirm the hypothesis. The results showed that Compound C pretreatment indeed attenuated the protective roles of ADM in PA or PA plus Ang II-induced inflammation, oxidative stress and calcification in A7r5 cells indicating that AMPK activation may partly involve the beneficial roles of ADM in vascular diseases in OH state. In this study, the intracellular signaling pathway of ADM remains mostly to be specified. For instance, we can further measure cAMP level, a major intracellular messenger of ADM and apply the cAMP analogue to mimic ADM’s actions that further clarifies the mechanisms of ADM’s roles in OH.
Based on the results of the present study, we concluded that ADM could effectively improve hypertension, vascular remodeling and arterial stiffness in OH rats, which might be closely associated with the inhibition of inflammation, oxidative stress and calcification in VSMCs partially via the receptor-mediated AMPK pathway. However, the precise mechanism underlying ADM’s action in this study needs to be further investigated.
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|
---
title: GC-MS Analysis of Bioactive Compounds Extracted from Plant Rhazya stricta Using
Various Solvents
authors:
- Nabih A. Baeshen
- Yaaser Q. Almulaiky
- Mohamed Afifi
- Ammar Al-Farga
- Haytham A. Ali
- Naseebh N. Baeshen
- Mosleh M. Abomughaid
- Aaser M. Abdelazim
- Mohammed N. Baeshen
journal: Plants
year: 2023
pmcid: PMC9967519
doi: 10.3390/plants12040960
license: CC BY 4.0
---
# GC-MS Analysis of Bioactive Compounds Extracted from Plant Rhazya stricta Using Various Solvents
## Abstract
Worldwide, human beings have traditionally employed many folkloric herbal resources as complementary and alternative remedies, and these remedies have played a pivotal role in modern medicines for many decades, as scientists have used them to develop drugs. We studied the effects of employing solvents with varying polarity on the yields of phytochemical components extracted from the plant Rhazya stricta. We used chloroform–methanol (1:1), methanol, ethanol, diethyl ether, and ethyl acetate as extraction solvents. The results showed that the efficiencies of the solvents at extracting phytochemical compounds were in this order: chloroform–methanol < ethanol < methanol < diethyl ether < ethyl acetate extract. The chloroform–methanol extract produced the highest concentration of phenolic and flavonoid contents among the five solvents tested (13.3 mg GAE/g DM and 5.43 CE/g DM). The yields of the extracted phytochemical compounds ranged from 47.55 to $6.05\%$. The results revealed that the properties of the extraction solvents considerably impacted the extraction yield and the phytochemical components of the R. stricta extract. Furthermore, compared with the other solvents, the chloroform–methanol extraction led to the highest yield ($47.55\%$) and to more phytochemical substances being extracted. The aim of this study is to investigate the phytochemical compounds extracted from R. stricta with different solvents that have different polarities.
## 1. Introduction
People have used natural medicinal plants as self-medication to treat diseases for many decades; however, scholars have debated the biologically-active molecules, plant-derived molecules, and mechanisms of action occurring in natural medicines for years. It is believed that people commonly employ folkloric herbal remedies as a source of innovative medications in folk medicine, and they have used these remedies, which have shown promising potential, to treat various human and animal diseases [1,2]. On the Arabian Peninsula, Saudi Arabian plants have a rich biological diversity and represent a significant genetic resource for both agriculture and medicinal plants. Due to its geographic location and characteristically dry weather, a large number of these plants grow under adverse weather conditions, meaning that their genomes are remarkably unique; thus, individuals use them to treat various conditions [3,4].
Primary metabolites are found in all plants, while secondary metabolites help a particular plant species interact with its environment. Plant-specific and genetically determined, the contents of physiologically active substances are additionally influenced by cultivation practices, diseases and pests, climate, developmental stage, ecology, and the time of day that the material is gathered [5]. Saudi Arabia’s harsh environmental conditions have forced plants to evolve coping mechanisms. However, according to phytochemistry, this causes high quantities of secondary metabolites such as polyphenols, flavonoids, tannins, terpenes, alkaloids, and saponins and their glycosides [6].
Current pharmacology explains the importance of natural products for developing novel drugs. Many natural compounds have been utilized as the foundation for the creation of medications and are still in use today to treat various diseases. However, the use of modern drugs entails a multitude of challenges, including severe side effects and drug resistance to antibiotics or even anti-cancer medications, which requires the development of novel medications. For instance, typical NSAIDs are well-known for their side effects, which include gastrointestinal hemorrhage and cardiovascular events [7]. Therefore, it is necessary to develop new NSAIDs with fewer side effects. In addition to antibiotic side effects, unchecked use increases the chance that bacteria will evolve resistance, which raises the risk of fatal infections [8]. In Saudi Arabia, cancer incidence has increased in recent years; breast, uterine, bladder, and colon cancer rates have risen roughly 10 times. Thyroid cancer incidence has increased by a factor of 26. From $5\%$ in 1990 to $12\%$ in 2016 [9], Saudi Arabia had an increase in cancer-related fatalities. An analysis of the ethnopharmacology of Saudi Arabian plants revealed that Saudi residents depend on conventional and contemporary therapies [10]. However, there are no data on the phytochemical components derived from *Rhazya stricta* in SA, despite the fact that various articles discuss traditional medicines in Saudi Arabia [11,12]. Therefore, it is possible to discover innovative hits for medication development by fusing conventional wisdom with contemporary pharmacognostic research, leading to the evidence-based application of traditional medicines and novel drug development.
Rhazya stricta is a classic shrub that is toxic, low, erect, and glabrous. It is one of the most common medicinal shrubs in the desert of the Arab Peninsula, including Saudi Arabia, and is used in herbal medicines to treat various diseases [13]. Recently, scientists have used its extracted materials in the formulation of silver nanoparticles, which have a role in fighting mosquito vectors and multiple pathogens [14]. R. stricta contains glycosides, alkaloids, tannins, and triterpenes, which are considered to be a rich source of indole alkaloids [15,16]. Indole alkaloid compounds generally exhibit antinociceptive, antitumor, anti-inflammatory, antioxidant, and antimicrobial antihypertensive properties [17]. Scientists have identified more than 100 alkaloids from R. stricta using phytochemical analysis methods [18]. Based on these aforementioned facts, we aimed to investigate the phytochemical compounds that are extracted from R. stricta with different solvents (methanol–chloroform (1:1), diethyl ester, methanol, ethanol, and ethyl acetate) and the identification of bioactive compounds. Using multiple solvents to extract compounds from R. stricta will provide us with opportunities to discover various bioactive compounds with therapeutic potential.
## 2.1. Phenolic and Flavonoids Contents
Plant potential antioxidant activity is proportional to the amount of cell-reinforcing chemicals present, such as phenolic compounds that are capable of catalyzing free radical scavenging [19]. To extract phenolic and flavonoid chemicals, the appropriate solvent must be utilized. Table 1 shows the capacity of several solvents to extract phenolic and flavonoid compounds from R. stricta. We tested methanol, ethanol, ethyl acetate, diethyl ether, and chloroform–methanol (1:1) to determine the best solvent to extract phenolic and flavonoid chemicals. Chloroform–methanol produced the highest concentration of phenolic compounds among the five solvents tested (13.3 mg GAE/g DM), and it produced a higher flavonoid content concentration (5.43 CE/g DM). Chloroform–methanol was the best solvent for extracting polyphenolic chemicals from the plants due to its ability to inhibit polyphenol oxidase activity. This enzyme is responsible for polyphenols’ oxidation and dispersion efficiency [20]. In *Caesalpinia decapetala* [21], Portulacaceae [19], and *Morus nigra* and *Artocarpus heterophyllus* leaves [22], scientists have used methanol ($70\%$) extracts to investigate antioxidant properties and flavonoid components. We performed a correlation study on the phenolic and flavonoid content of R. stricta extracts. It was revealed that there was a 0.995 connection between the phenolic and flavonoid contents, suggesting that, in R. stricta, flavonoids are the predominant phenolic group. The results are comparable to the extraction of phenolics from Pisang Mas, Guava, and *Limnophila aromatica* [23,24].
## 2.2. Extraction with Ethanol Solvent and Identification of Compounds Using GC/MS
Table 2 and Figure 1 show 18 compounds found in R. stricta extract using an ethanol solvent. We used the peak area percentage to indicate the relative concentration of each compound. The main compounds identified based on the relative contents were Methyl octadeca-17-enoate ($46.32\%$), Methyl hexadecanoate (Methyl palmitate) ($24.22\%$), [-]-1,2-Didehydroaspidospermidine ($11.39\%$), and Strictamine ($3.44\%$). Most of the compounds extracted with ethanol were unsaturated fatty acids. Methyl hexadecanoate plays a vital role in modulating anti-inflammatory responses in macrophages [25]. Additionally, it affects human semen quality [26]. Further, 1,2-*Didehydroaspidospermidine is* a bioactive alkaloid extracted from many plants, and scientists have used it as a target for synthesis [27]. Finally, Strictamine has promising and significant antibacterial potential against *Acinetobacter baumannii* [28]. Our results are in accordance with previous reports showing the fatty acid profile of R. stricta [16]. These results suggest a positive biological effect of the bioactive materials extracted from R. stricta with an ethanol solvent. Similarly, the high fatty acid content extracted from R. stricta demonstrates its volatile flavors, which scholars have previously detected [29].
## 2.3. Extraction with Methanol Solvent and Identification of Compounds Using GC/MS
Table 3 and Figure 2 present the 18 compounds extracted from R. stricta with the methanol solvent. The main compounds identified based on relative contents were [-]-1,2-Didehydroaspidospermidine ($28.37\%$), Methyl aspidospermidine-3-carboxylate ($14.27\%$), quebrachamine ($11.96\%$), and 3-Ethylpiperidine ($5.63\%$). Most of the compounds extracted with methanol were alkaloids; similarly, previous data showed the existence of alkaloids in R. stricta [15,30]. Additionally, genetic diversity can affect the plant content of alkaloids [31]. Alkaloids are a rich source of the materials used for drug discovery and formulation; thus, scientists have examined various alkaloids for their anticancer and antiproliferative activities [32,33]. The results of another study elucidated their role in providing protection to animals subjected to UV radiation [34]. The results obtained in the present study emphasize the potential therapeutic use of R. stricta, especially as a potent source of alkaloids, and the potential for researchers to discover multiple bioactive materials with therapeutic properties against different malignancies.
## 2.4. Extraction with Diethyl Ether Solvent and Identification of Compounds Using GC/MS
Table 4 and Figure 3 show the 15 compounds found in R. stricta extract using the diethyl ether solvent. The main compounds identified based on the relative contents were [-]-1,2-Didehydroaspidospermidine ($26.76\%$), squalene ($22.49\%$), Di-n-2-propylpentylphthalate ($9.19\%$), and quebrachamine ($5.49\%$). Most of the compounds extracted with diethyl ether were alkaloids and triterpenes. Scientists have shown that triterpenes exist in R. stricta via cheminformatics studies that they performed to determine the bioactive molecules responsible for their therapeutic potential [35]. Scholars have revealed that triterpenes have various medicinal uses due to their antitumor activities [36], inhibitory effect on nitric oxide (NO) production [37], anti-inflammatory activities [38], and antineoplastic activities [39]. Although R. stricta has high therapeutic potential, its phthalic acid content has provoked discussions about the adverse effect of this bioactive compound [40,41].
Moreover, scientists have detected a high amount of squalene in R. stricta. Squalene is a polyunsaturated hydrocarbon with multiple bioactivities, including skin hydration, acting as an emollient agent and drug carrier, and having antioxidant and detoxification properties [42]. Recently, scholars discovered the important role of squalene as an adjuvant for influenza vaccines [43], and they determined its role in the treatment of cardiovascular disease through its statin-like action [44]. Quebrachamine, another indole alkaloid extracted from R. stricta, has blocking activities against the adrenergic nerves of urogenital tissues [45]. Our results are in accordance with previous reports that also detected quebrachamine in R. stricta [16]. The bioactive materials extracted from R. stricta with diethyl ester tended to have important activities for therapeutic uses; Sultana and Khalid, 2010, reported the same prospect [46]. All the previously-mentioned records emphasize the therapeutic potential of R. stricta regarding its isolated and extracted bioactive compounds.
## 2.5. Extraction with Chloroform–Methanol Solvent and Identification of Compounds Using GC/MS
Table 5 and Figure 4 show the 10 compounds that we found in R. stricta via extraction with the chloroform–methanol solvent. The compounds identified based on the relative contents were methyl stearate ($47.55\%$), Methyl palmitate ($35.23\%$), methyl tetradecanoate ($6.03\%$), [-]-1,2-Didehydroaspidospermidine ($1.53\%$), and Methyl laurate ($1.46\%$). Most of the compounds extracted with chloroform–methanol were fatty acids and alkaloids. Our study’s results are comparable to those of previous studies, whereby the authors extracted more than 100 alkaloid compounds from R. stricta [47]. We found that methyl stearate, the fatty acid that we extracted most often from R. stricta with chloroform–methanol, had a regulatory effect on the calcium-activated chloride channels, which has sparked debate on its use in drug synthesis and fabrication [48]. Additionally, it has anti-inflammatory activities through its ability to downregulate the proinflammatory response [49]. Moreover, methyl stearate has several uses in biological and medical research [50]. Another bioactive compound, methyl tetradecanoate, a fatty acid extracted from R. stricta, has contraceptive activities [51]. The previously-mentioned citations confirm the potential of the extracted R. stricta bioactive compounds to be a potent therapeutic compound.
## 2.6. Extraction with Ethyl Acetate Solvent and Identification of Compounds Using GC/MS
Table 6 and Figure 5 show the 10 compounds extracted from R. stricta using the ethyl acetate solvent. The main compounds identified based on the relative contents were [-]-1,2-Didehydroaspidospermidine ($6.05\%$), 3-ethylpyridine ($4.01\%$), N-ethyl-desoxy-veratramine ($3.11\%$), aR-Turmerone ($2.10\%$), oleic acid ($2.16\%$), and vitamin E ($1.94\%$). The R. stricta extraction with the ethyl acetate solvent resulted in a higher oleic acid content. The results are comparable to those of previous studies that showed the existence of oleic acid in R. stricta [52]. As an omega-9 unsaturated fatty acid, oleic acid regulates female fertility and is involved in germ cell growth and development. It contributes to oocyte preimplementation and embryo growth [53].
Moreover, it plays a beneficial role in diminishing the incidence of cardiovascular disorders, carcinogenesis, liver dysfunctions, and intestinal inflammations [54]. Additionally, it has a potent ability to mitigate inflammatory responses in sepsis, has antioxidant power, takes antiparasitic action against *Acanthamoeba castellanii* trophozoites, and promotes the differentiation of neural cells in human endometrial stem cells [55,56]. Furthermore, oleic acid ameliorates induced hepatocellular lipotoxicity [57], acts as a carrier for anticancer drugs [58], upregulates myosin heavy chain-1 expression, and elevates the mitochondrial mass in myoblasts [59]. Its high oleic acid content makes R. stricta a possible medicinal plant for many diseases. Also, we extracted vitamin E from R. stricta; the biological activities and the importance of vitamin E are well known, and researcher studies have recently and extensively shown its antioxidant power [60,61]. Recently, scholars have found that lower serum levels of α-tocopherol and lycopene are more associated with high pain and disability in osteoarthritis patients than in healthy controls [62]. Moreover, its administration after surgical operations enhances the osseointegration of stainless-steel implants in vivo [63]. The obtained results show that R. stricta is a potent source of vitamin E and, thus, can be a powerful source of antioxidants.
## 2.7. Comparison between Extraction Percentage of the Phytochemical Compounds Using Different Solvents
The results shown in Table 7 indicate that the main bioactive compounds extracted by different solvents belong to families of alkaloids, fatty acids, triterpene, antimicrobials, vitamin E, and antibiotics. These bioactive compounds could open new horizons to more in-depth studies to evaluate the mode of action of the compounds that are necessary to pave the way for clinical trials. The isolation and purification of these compounds are needed to assess their mode of action with in vitro studies to better understand their activities. The discrepancies in the RT that are obvious for bioactive compounds extracted using different solvents could be attributed to variances in the polarity of various plant chemicals, as described by Jayaprakasha et al. [ 64]. As a result of this variation, the solubility of the solvent that was employed differed, and the RT of the bioactive compounds which were extracted varied depending on the kind of solvent used [65]. These results agree with Swamy et al. [ 66], who used different solvents (methanol, acetone, and hexane) to extract *Plectranthus amboinicus* leaves. They revealed that the retention time of the same compound might vary in the same column under the same analytical conditions with a different solvent. For instance, tetrapentacontane appears in the methanol extract at Rt 72.63 min and in the hexane extract at Rt 92.76 min. Pentaconsane appears in the ethanol extract at Rt 75.78 min and in the hexane extract at Rt 81.95 min. Squalane appears in the methanol extract at Rt 86.54 min and in the hexane extract at Rt 75.43 min [66].
## 3.1. Collection of Plant Samples and Preparation
We collected R. stricta plant materials from the *Ghola area* at Osfan with the coordinates N: 21.935.1966 and E: 39.305869. We brought the collected samples to the laboratory, separated the leaves from the stems, washed them with running tap water, and left them to dry in the shade at the laboratory for three days. When the leaves were completely dehydrated, we placed them in a blender, ground them to a fine powder, and kept them at room temperature for further use.
## 3.2. Sample Extraction
We extracted 100 g of fine powder using 500 mL of absolute ethanol, methanol, diethyl ether, a chloroform–methanol mixture (1:1, v/v), or ethyl acetate. We ultrasonicated all the samples in a water bath at 40 °C for three hours, soaked them in a shaking water bath at 70 °C for 24 h until the solvent became colorless, filtered them through Whatman filter paper No.2, and analyzed them with GC-MS.
## 3.3. Total Phenolic Content
We used the method explained by [67] to determine the total phenolic content of the plant. Firstly, we introduced 100 μL of the Folin–Ciocalteu reagent to 100 μL of the plant extract and 800 μL of distilled water, and left the solution for 5 min at room temperature. We then added 500 μL of sodium carbonate ($15\%$, w/v) to the reaction mixture. Finally, we measured the absorbance at 750 nm after 30 min. The results are represented in mg gallic acid equivalent per gram of dry matter (mg GAE/g DM).
## 3.4. Total Flavonoid Content
We used the method described by [68] to determine the flavonoid content. Firstly, we combined 250 μL of plant extract, 1.25 μL of distilled water, and 75 μL of NaNO2 solution ($5\%$, w/v) in a reaction mixture and allowed it to stand for 6 min. Then, we added 150 μL of an AlCl3 solution ($10\%$, w/v), 0.5 mL of 1 M NaOH, and 275 μL of distilled water to the reaction mixture and allowed it to stand for 5 min. Finally, we recorded the absorbance at 510 nm. Then, we calculated the results as mg catechin equivalent/g dry matter (mg CE/g DM) and used a catechin solution as the standard.
## 3.5. Gas Chromatography-Mass Spectrometry (GC-MS) Analysis
We determined the chemical compositions of the samples using a Thermo Scientific Trace GC1310-ISQ mass spectrometer with a direct capillary column TG–5MS (30 m × 0.25 mm × 0.25 m film thickness). Initially, we maintained the column oven at 50 °C; then, we increased the temperature by 5 °C/min to 230 °C, which we held for 2 min, and then by 30 °C/min to 290 °C, which we also maintained for 2 min. Next, we held the temperature of the injector and MS transfer lines at 250 and 260 °C, respectively. We used helium as a carrier gas at a constant flow rate of 1 mL/min. The solvent delay was 3 min, and we automatically injected 1 μL of the diluted samples using Autosampler AS1300 coupled with GC in the split mode. We collected EI mass spectra at 70 eV ionization voltages over the range of m/z 40–1000 in full scan mode. Next, we set the ion source temperature to 200 °C. Finally, we identified the components by comparing the components’ retention times and mass spectra to those of the WILEY 09 and NIST 11 mass spectral databases.
## 4. Conclusions
This study investigated the effects of solvents with different polarities on the phytochemical compounds derived from R. stricta. The solvents that were used included chloroform–methanol, ethanol, methanol, diethyl ether, and ethyl acetate. The results revealed that chloroform–methanol use resulted in a high extraction yield of extracted phytochemical compounds (13.3 ± 0.86 mg/g phenolic content and 5.43 ± 0.89 mg/g flavonoid content). The majority of the compounds extracted with chloroform–methanol were Methyl stearate ($47.55\%$), which plays a regulatory role in the calcium-activated chloride channels and has anti-inflammatory activities through its ability to downregulate the proinflammatory response, and hexadecanoic acid ($35.23\%$), which has a vital role in modulating anti-inflammatory reactions in macrophages and affects human semen quality. Therefore, the properties of the extraction solvents play an important role in determining the effectiveness of phytochemical compound extraction. Furthermore, the extracted bioactive compounds revealed the medicinal potential of R. stricta for female reproduction disorders, cardiovascular disease, obesity, inflammatory conditions, and hepatic disorders. Moreover, it is a rich source of antioxidants, alkaloids, and beneficial unsaturated fatty acids. Therefore, it is possible to separate, isolate, and characterize all of the phytocomponents found in R. stricta in order to identify novel drugs and study their therapeutic benefits. Future studies will concentrate on separating and characterizing particular compounds from R. stricta crude extracts and testing them in living organisms to better understand their activities.
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|
---
title: Antibacterial Activity and Mechanism of Madecassic Acid against Staphylococcus
aureus
authors:
- Chunling Wei
- Peiwu Cui
- Xiangqian Liu
journal: Molecules
year: 2023
pmcid: PMC9967526
doi: 10.3390/molecules28041895
license: CC BY 4.0
---
# Antibacterial Activity and Mechanism of Madecassic Acid against Staphylococcus aureus
## Abstract
Antibacterial resistance has become one of the most serious problems threating global health. To overcome this urgent problem, many scientists have paid great attention to developing new antibacterial drugs from natural products. Hence, for exploring new antibacterial drugs from Chinese medicine, a series of experiments were carried out for verifying and elucidating the antibacterial activity and mechanisms of madecassic acid (MA), which is an active triterpenoid compound isolated from the traditional Chinese medicine, Centella asiatica. The antibacterial activity was investigated through measuring the diameter of the inhibition zone, the minimum inhibitory concentration (MIC), the growth curve, and the effect on the bacterial biofilm, respectively. Meanwhile, the antibacterial mechanism was also discussed from the aspects of cell wall integrity variation, cell membrane permeability, and the activities of related enzymes in the respiratory metabolic pathway before and after the intervention by MA. The results showed that MA had an inhibitory effect on eight kinds of pathogenic bacteria, and the MIC values for Staphylococcus aureus, Methicillin-resistant Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, and *Bacillus megaterium* were 31.25, 62.5, 250, 125, 62.5, and 62.5 µg/mL, respectively. For instance, 31.25 µg/mL MA could inhibit the growth of *Staphylococcus aureus* within 28 h. The antibacterial mechanism experiments confirmed that MA could destroy the integrity of the cell membrane and cell wall of Staphylococcus aureus, causing the leakage of macromolecular substances, inhibiting the synthesis of soluble proteins, reducing the activities of succinate dehydrogenase and malate dehydrogenase, and interacting with DNA, leading to the relaxation and ring opening of supercoiled DNA. Besides, the activities of DNA topoisomerase I and II were both inhibited by MA, which led to the cell growth of *Staphylococcus aureus* being repressed. This study provides a theoretical basis and reference for the application of MA in the control and inhibition of food-borne Staphylococcus aureus.
## 1. Introduction
As one of the most common causes responsible for infectious diseases and an important pathogen in clinical practice, *Staphylococcus aureus* (S. aureus) has contributed to a severe threat, involving mild skin infection, severe tissue infection, and sepsis to human health due to its widely distribution in human skin, especially in the nasopharynx [1]. In addition, S. aureus can also cause a variety of nosocomial infections derived from medical instruments and equipment pollution [2]. At present, the treatment of S. aureus infection mainly relies on antibiotics. However, repeated and excessive use of antibiotics has led to serious antibiotic residues and bacterial resistance, along with decreased therapeutic efficacy. Therefore, it has become an important and urgent task to explore natural products with low toxicity and high anti-microbial activity for treating the initial stage of infection, reducing the use of antibiotics, and limiting the development of drug resistance of pathogenic microorganisms. Besides, active natural compounds can also perform as adjuvants or bacterial resistance-modifying agents, which can enhance or restore the effectiveness of commercial drugs towards antibiotic-resistance bacteria, so it has drawn much awareness to mine potential natural compounds with significant antibacterial activity from pharmaceutical botany.
Centella asiatica (L.) *Urb is* a famous botanical drug, belonging to the umbrella family, recorded in the 2020 edition of the Chinese Pharmacopoeia [3], which is widely distributed in China, India, Malaysia, Indonesia, Oceania Islands, Japan, Australia, and Central Africa [4,5]. In China, the main producing area of *Centella asiatica* (L.) *Urb is* located in Anhui, Guangxi, Hunan, and other central south places. The dried whole of this plant can be drunk as herbal tea [6] due to its effects of clearing heat and dampness, detoxification and swelling [7], and showing cold and bitter taste. Relevant studies have also shown that *Centella asiatica* can exhibit antibacterial properties, liver injury protection, nerve protection, anti-tumor properties, wound healing properties, and other effects [8,9,10,11,12], indicating that *Centella asiatica* (L.) *Urb is* a good source for developing new antibacterial drugs. As one of the most active constituents in *Centella asiatica* (L.) Urb, asiatic acid can show significant broad-spectrum antibacterial activity on Escherichia coli, Salmonella typhimurium, Pseudomonas aeruginosa, Enterococcus faecalis, S. aureus, etc. [ 13,14,15,16]. However, our research confirmed that another main compound in *Centella asiatica* (L.) Urb, MA, also showed significant antibacterial activity. As MA has been reported to exhibit anti-cancer properties, cardiovascular protection, anti-diabetes properties, and anti-inflammatory activities in previous studies [17,18,19,20], it can be recognized as a competitive and promising candidate compound for drug development. Based on this, the antimicrobial activity and related mechanism of MA were systematically studied in this paper, which can provide an integrated experimental basis and reference for the development of low-toxicity and low-resistance antimicrobial drugs.
## 2.1.1. Diameter of Inhibition Zone
The inhibition zone of oxacillin (OXA) against S. aureus was the largest, and no antibacterial zone was formed in the dimethyl sulfoxide (DMSO, control) group. The inhibition effect of MA on S. aureus was better, and the diameters of inhibition zones of MA against S. aureus, methicillin-resistant *Staphylococcus aureus* (MRSA), Candida albicans (C. albicans), *Escherichia coli* (E. coli), *Pseudomonas aeruginosa* (P. aeruginosa), Gordinia sp., *Bacillus subtilis* (B. subtilis), and *Bacillus megaterium* (B. magaterium) were 13 mm, 14.5 mm, 14 mm, 10 mm, 11.5 mm, 13.5 mm, 10.5 mm, and 10.5 mm, respectively (Table 1), indicating that MA is a potential candidate compound for anti-pathogenic bacteria drug development.
## 2.1.2. Minimum Inhibitory Concentration (MIC)
The MIC values of MA against S. aureus, MRSA, E. coli, P. aeruginosa, B. subtilis, and B. magaterium were 31.25, 62.5, 250 and 125, 62.5, and 62.5 µg/mL, respectively (Table 1). The MIC of OXA (positive control) against S. aureus, MRSA, B. subtilis, and B. magaterium were 0.048, 7.8, 3.9, and 1.9 µg/mL, respectively. The experimental results showed that the antibacterial effect of MA against Gram-positive bacteria (S. aureus, MRSA) was better than that of Gram-negative bacteria (E. coli, P. aeruginosa). It was also found that the MIC of MA against MRSA was stronger than that of tormentic acid (128 μg/mL) [21], but lower than that of sanguisorbigenin (12.5–50 μg/mL) [22]. Even MA, tormentic acid and sanguisorbigenin all belong to ursane-type triterpenoids, and they exhibit different inhibition activity against MRSA, which may be caused by the different substituent group of different compounds.
## 2.2. Antibacterial Effect of MA on S. aureus
In comparison to the control group (DMSO), the treatment with 31.25 µg/mL and 62.5 µg/mL MA significantly inhibits the growth of S. aureus. The optical density (OD) value of the MA group was significantly lower than that of the control group. This further confirmed that MA had an obvious inhibitory effect on S. aureus, and 31.25 µg/mL MA could exhibit consistent growth inhibiting activity of S. aureus, up to 28 h, while 62.5 µg/mL MA could completely inhibit the growth of S. aureus within 32 h (Figure 1).
## 2.3. Effect of MA on Biofilm of S. aureus
A bacterial biofilm is an organized bacterial group formed by multiple bacteria adhering to non-biological or biological surfaces, secreting polymer matrix, and wrapping themselves in it [23]. The results of crystal violet staining showed that, when the concentration of MA was 31.25 µg/mL and 62.5 µg/mL, the inhibition rates of biofilm were $68.35\%$ and $72.73\%$, respectively, indicating higher concentration of MA, causing inhibiting rates of increasing biofilm (Figure 2). Therefore, MA had an inhibitory effect on the production of S. aureus biofilms.
## 2.4.1. Results of Changes in Conductivity in the Culture Medium after the Intervention of MA on S. aureus
The experimental group with MA showed a rapid growth trend of broth conductivity, and the percentage of electrical conductivity for the MIC group and the 2 MIC group reached $67.17\%$ and $76.79\%$, respectively, while the control group was only $36.32\%$ (Figure 3a). This result suggests that MA has a significant impact on the function of the cell membrane of S. aureus, which is the main barrier preventing the leakage of cell contents.
## 2.4.2. Effect of MA on Macromolecular Substances in Culture Medium of S. aureus
After 31.25 µg/mL and 62.5 µg/mL MA treatment, the nucleic acid leakage (OD260nm) and protein leakage (OD280nm) in the extracellular bacteria suspension were significantly increased (Figure 3b,c). The results also indicated that the permeability of the cell membrane increased after the action of MA, and the macromolecular substances in the cell were released into the extracellular broth.
## 2.4.3. Effect of MA on Cell Wall of S. aureus
The leakage amount of alkaline phosphatase in the experimental group containing MA was significantly higher than that in the control group (Figure 4), indicating that MA could increase the leakage amount of alkaline phosphatase (AKP) in S. aureus, and the integrity of the bacteria wall might be damaged, symbolizing that MA could damage the cell wall of S. aureus, causing the leakage of cell contents.
## 2.4.4. Effect of MA on β-Galactosidase Content
β-Galactosidase exists in the bacterial inner membrane. When the inner membrane is damaged, β-Galactosidase would leak out through the cytoplasmic membrane, and the change in extracellular β-galactosidase content could be used to predict the damage degree of bacterial inner membrane [24,25]. β-galactosidase content of the control group did not change significantly during the whole cultivation period, but β-galactosidase content of the MAs, 31.25 µg/mL and 62.5 µg/mL experimental groups, was significantly higher than that of the control group (Figure 5), indicating that MA destroyed the integrity of the inner membrane of S. aureus and caused the leakage of β-galactosidase to the extracellular surface, leading to an increase in extracellular β-galactosidase.
## 2.5. Effect of MA on Soluble Protein of S. aureus
The results shown in Figure 6, which were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) of soluble protein separated from the cells of S. aureus, the control group without MA treatment presented more and clearer protein bands than the two experimental group intervened by 31.25 µg/mL MA and 62.5 µg/mL MA, respectively. This result suggests that MA could exert its antibacterial effect through repressing the protein expression in S. aureus. The reason may be that MA affects the synthesis of nucleic acid and the expression of related genes of S. aureus, and then it blocks the synthesis of some proteins and enzymes, leading to a decrease in protein expression in the bacteria, thus exerting its bacteriostatic effect.
## 2.6.1. Changes of DNA Structures by Interaction of MA with DNA
Plasmid DNA was chosen to observe the MA effects on the superhelical structure of circled double-stranded DNA. The results of agarose gel electrophoresis are shown in Figure 7. When the concentration of MA was greater than 0.007812 mg/mL, Form I (supercoiled DNA) gradually decreased, and Form II (relaxation unwinding DNA) gradually increased, indicating that MA could cause relaxation and rang opening of super spiral DNA.
## 2.6.2. UV Spectral Study on the Binding of MA with DNA
Ultraviolet absorption spectroscopy is often used to study the interaction between compounds and DNA. Generally, red shift phenomenon and color reduction effect appeared after the interaction between compounds and DNA, indicating that the interaction between the compounds and DNA is intercalation binding [26]. With the increase in MA concentration, the maximum light absorption value of pET-28a DNA gradually decreased, and the color reduction effect occurred. The maximum adsorption wavelength of pET-28a DNA showed a red shift, which further proved that MA could bind pET-28A DNA, and DNA conformational changes were caused by the separation of DNA base pairs caused by MA insertion (Figure 8).
## 2.7. Effect of MA on the Morphology of S. aureus Cells
The results of transmission electron microscopy showed that MA had an obvious effect on the morphology of S. aureus. The untreated S. aureus had normal morphology and an intact membrane. However, compared with the untreated S. aureus, the cell plasma membrane of the S. aureus exposed to 31.25 µg/mL MA was damaged, and the surface was rougher. The cells of S. aureus exposed to 62.5 µg/mL MA were spited, and cytoplasmic contents were released (Figure 9).
## 2.8. Effect of MA on the Determination of Malate Dehydrogenase (MDH) and Succinate Dehydrogenase (SDH) Activities
MDH and SDH are the key enzymes in the tricarboxylic acid cycle. Detecting the activities of MDH and SDH can indirectly reflect the energy metabolism in bacteria. The activities of SDH and MDH in S. aureus were significantly decreased after exposure to 31.25 µg/mL and 62.5 µg/mL MA (Figure 10). This suggests that MA could inhibit the activities of MDH and SDH in S. aureus.
## 2.9.1. Purity Test Results of pET-28a
The agarose gel electrophoresis pattern is shown in Figure 11. pET-28a is a commonly used prokaryotic efficient expression vector of fusion protein type, the size of which is 5369 bp, containing kanamycin resistance gene. The electrophoresis bands showed that the size of purified plasmid DNA was between 5000 bp and 6000 bp coupled with a brighter band referred to the supercoiled pattern of target plasmid.
## 2.9.2. Determination of DNA Topoisomerase Activity in Crude Enzyme Extracts of S. aureus
The supercoiled pET-28a DNA can be uncoiled into open loop or linear DNA (Form II) by the crude enzyme isolated from the cells of S. aureus. With the increase in concentration of crude enzyme, Form II DNA gradually increased, along with a gradual decrease in supercoiled DNA (Form I), indicating that the DNA topoisomerase in the crude enzyme is effective and has strong unwinding activity (Figure 12).
## 2.9.3. Effects of MA on DNA Topoisomerase I Activity of S. aureus
DNA topoisomerase I is one of the key enzymes in nucleic acid metabolism in organism catalyzing transient DNA single-strand disconnection and reconnection related to DNA unwinding regulation occurring in the process of DNA replication, transcription, recombination, reparation, and other key reactions. This process does not require the participation of energy cofactor adenosine triphosphate (ATP). Under the catalysis of DNA topoisomerase I, pET-28a DNA was unscrewed into Form II. When the concentration of MA was greater than 1.25 mg/mL, the Form I gradually increased, and Form II gradually decreased with the increase in MA concentration, which indicated that MA could inhibit the activity of S. aureus topoisomerase I (Figure 13).
## 2.9.4. Effects of MA on DNA Topoisomerase II Activity of S. aureus
DNA topoisomerase II is another important target enzyme responsible for breaking two strands of a double helix of DNA. The role of topoisomerase II is to mediate the unwinding, breaking, and reconnecting of DNA double strands to affect the structure of DNA. When the concentration of MA was greater than 2.5 mg/mL, the Form I gradually increased, and the Form II gradually decreased with the increase in MA concentration, indicating that MA could inhibit the activity of topoisomerase II from S. aureus (Figure 14).
## 3. Discussion
S. aureus, a widely distributed pathogenic bacteria, can cause local suppurative infections generating blood infection, pneumonia, enteritis, and other suppurative inflammation related diseases in human. To cure these infections, many and excessive antibiotics and other drugs have been adopted to these patients, but the bacterial resistance has also been induced at the same time, which has become a new deep, challenging issue threating human health.
In order to slow down or repress the evolution of bacterial resistance, the development of new antibacterial Chinese herbal medicines and their preparations have become an important hotspot in the field of antibacterial drug research and development. For example, Zhang et al. [ 27] found that the aqueous extract of Artemisia argyi leaves could destroy the integrity of the cell wall of S. aureus and increase the permeability of the cell membrane at a certain concentration, but it could not kill S. aureus in a short time; Zhou et al. [ 28] found that a part of n-butanol and ethanol crude extract of the Dendrobium shell had strong antibacterial activity against *Salmonella paratyphimurium* and S. aureus, and the antibacterial mechanism might be related to the synthesis inhabitation of bacterial proteins. However, both Chinese herbal compound preparations and single Chinese herbal medicines all have complex chemical components, leading to unclear antibacterial mechanisms and lack of standard drug use specifications. Therefore, it is necessary to conduct in-depth research on the antibacterial activities and mechanisms of key components in Chinese herbal medicines. Relevant data will provide an important basis for the development of antibacterial drugs from Chinese herbal medicines and the formulation of clinical drug use specifications.
In this study, the filter paper method and the 2,3, 5-triphenyltetrazolium chloride (TTC) staining method were used to determine the antibacterial activity and MIC value of MA. The antibacterial activity of MA against eight common pathogenic bacteria (S. aureus, MRSA, C.albicans, E. coli, P. aeruginosa, Gordinia sp., B. subtilis, and B. magaterium) was determined. Results showed that the antibacterial effect of MA against Gram-positive bacteria was better than that of Gram-negative bacteria. The MIC of MA against S. aureus was 31.25 μg/mL. The growth curves of 31.25 µg/mL and 62.5 µg/mL MA against S. aureus were also determined. It was further confirmed that MA had a significant inhibitory effect on the growth of S. aureus and could inhibit the growth of S. aureus within 28 h. Meanwhile, 31.25 µg/mL and 62.5 µg/mL MA could significantly inhibit the formation of S. aureus biofilm. Bacteria cells are composed of cell membrane, cell wall, cytoplasm, and nucleoplast, among which cell membrane is an important medium for material and energy exchange between bacteria and the outside world. When the cell membrane permeability of pathogenic bacteria is destroyed, the electrolytes in the bacteria will leak into the culture medium, and the conductivity of the supernatant of the culture medium of S. aureus can indirectly reflect the permeability of the cell membrane of the bacteria. In this study, the change in the relative conductivity of the cell after the action of MA was detected. It was found that the relative electrical conductivity of the experimental group was significantly higher than that of the control group after 4 h of MA treatment, which indicated that the permeability of the cell membrane of S. aureus was changed after MA treatment, causing the leakage of small molecules, such as K+ and Na+ in the cells. Furthermore, OD values of nucleic acid leakage (OD260nm) and protein leakage (OD280nm) in extracellular bacterial suspensions were detected. It was found that the OD values of nucleic acid leakage and protein leakage of bacterial suspensions increased significantly after MA treatment. This further confirmed that the cell membrane of S. aureus was damaged after the action of MA, and the macromolecular substances, such as DNA and RNA in the cell, were released into the culture medium, thus leading to the death of S. aureus. At the same time, the effect of MA on β-galactosidase content was also measured, and it was found that the extracellular β-galactosidase content of MA treatment group was significantly higher than that of the control group, which fully confirmed that MA damaged the cell membrane of S. aureus. AKP is an enzyme that exists between cell walls. Under normal circumstances, the activity of AKP could not be detected outside the cell wall, but when the cell wall was damaged, AKP could be detected outside the cell wall, and the activity of AKP could also increase [29]. The experimental results showed that the content of AKP in the experimental group was significantly higher than that in the control group, indicating that MA could destroy the bacterial cell wall and increase the permeability of the bacterial cell wall. The experimental results showed that the content of AKP in the experimental group was significantly higher than that in the control group, indicating that MA could destroy the bacterial cell wall and increase the permeability of the bacterial cell wall. At the same time, MA could also inhibit the synthesis of soluble protein of S. aureus. Besides, the morphology of S. aureus cells treated with 31.25 µg/mL and 62.5 µg/mL MA was observed by transmission electron microscope. The result is consistent with the previous data on the effects of MA on the cell wall and the membrane showed above. SDH and MDH are the key metabolic enzymes in the tricarboxylic acid cycle of pathogenic bacteria. Detection of SDH and MDH activities in S. aureus can reflect the energy metabolism of S. aureus. In this study, the activities of SDH and MDH in S. aureus before and after MA intervening were detected, and it was found that MA could reduce the activities of SDH and MDH in S. aureus. This means that MA plays an antibacterial role by acting on metabolic enzymes in S. aureus. In addition, the method of interaction between MA and DNA was also tested to determine whether drugs could interact with DNA. Agarose gel electrophoresis results showed that the interaction between MA and DNA caused relaxation and looped opening of supercoiled DNA, and UV absorption spectroscopy further proved that MA could bind pET-28a DNA. The antibacterial mechanism of MA is from our research, as shown in Figure 15. As antibiotic resistance has become the global challenge threating people’s health, and many pathogenic bacteria export antibiotics from intracellular environment through developing their multidrug efflux pumps system, which can be induced or evolved under long term excessive drug stress by modifying or regulating relative genes in plasmids [30], it is very urgent to develop new drugs or adjuvants to overcome antibiotic resistance. In this study, the multi-mechanical actions against S. aureus by MA were systemically verified, indicating that MA is a promising natural compound for controlling S. aureus infection. In further study, how MA regulates or interacts with the multidrug efflux pump system of pathogenic bacteria is also a very important issue. So, this research can also provide a basic reference for further elucidating the molecular mechanism of MA against pathogenic bacteria.
## 4.1. Bacterial Strains and Bacterial Culture
S. aureus, CMCC (B) 26003 (Shanghai Luwei Technology Co., Ltd.), MRSA ATCC 43300 (BeiJing Microbiological Culture Collection Center (BJMCC)), and other strains, including *Escherichia coli* (E. coli) ATCC 25922, *Pseudomonas aeruginosa* (P. aeruginosa) ATCC 27853, Candida albicans (C. albicans) CMCC (F) 98001, *Bacillus megaterium* (B. magaterium) ATCC35985, and *Bacillus subtilis* (B. subtilis), were all purchased from Shanghai Bioresource Collection Center, and the strain Gordinia sp. JD-4 was isolated from the local soil by our lab and identified by the 16s rDNA sequence. For Madecassic acid (Figure 16), the purity by HPLC analysis was more than $98\%$. Lot number: J12HB184580, Shanghai Yuanye Biotechnology Co., Ltd.; Luria Bertani (LB) agar medium, LB liquid medium, yeast extract peptone dextrose (YPD) agar medium, and YPD liquid medium, Guangdong Huankai Microbiology Technology Co., Ltd.
## 4.2. Determination of Diameter of Inhibition Zone of MA
The paper diffusion method [31] was employed to evaluate the antibacterial activity of MA. Briefly, the strains were firstly, respectively, activated on the ultraclean table, and they were uniformly coated on the LB medium plate with sterile coating rods. On the plate, 6 mm filter paper sheets soaked with MA solution of certain concentration were placed, respectively; another solvent-only sample was selected as the control group. After inoculation and filter paper plating, the plates were cultured in the biochemical incubator at 37 °C for 12–18 h. Finally, the antibacterial effect was calculated through measuring the diameter of the inhibition zone by Vernier caliper, which is a measuring tool for measuring length, inner and outer diameter, and depth accurately.
## 4.3. Determination of Minimum Inhibitory Concentration (MIC)
The MIC values of MA against six strains (S. aureus, MRSA, E. coli, P. aeruginosa, B. subtilis and B. magnatum) were determined by the TTC staining method [32]. After dilution of the bacterial suspension in the logarithmic phase to the concentration of 106–107 cfu/mL by liquid medium, 180μL bacterial suspension and 20μL MA solution of different concentrations were added to the 96-well plate to ensure the final concentrations of 500, 250, 125, 62.5, 31.25, 15.625, 7.8, and 3.9 µg/mL, respectively. DMSO was chosen as the control group, and the plate was incubated at 37 °C for 12–16 h. After incubation, TTC solution was added to each experimental well, and the plate was incubated at 37 °C for another 4 h in the dark for observing the color change. The experiment was repeated three times, and the average value was calculated.
## 4.4. Antibacterial Curve of MA against S. aureus
Different volumes of MA solution were added into 107–108 cfu/mL S. aureus suspension to reach the final concentrations of 31.25 µg/mL and 62.5 µg/mL. The control group was added DMSO. Then, all the culture tubes were transferred to a constant temperature culture oscillator with parameter settings at 37 °C and 120 rpm. During the cultivation period, OD at 600 nm was measured every 4 h. Finally, the growth curves of S. aureus with or without MA treatment was drawn to show the relationship between the culture time (t) and the OD value [33]. The experiment was repeated thrice, and the average value was taken.
## 4.5. Inhibitory Effect of MA on the Production of S. aureus Biofilm
S. aureus was inoculated into LB medium and incubated at 37 °C, 120 rpm for about 24 h. When the OD600nm of the bacteria broth reached about 0.3, the MA solution of different concentrations was added to the bacteria broth and mixed thoroughly to reach the final MA concentration of 31.25 µg/mL and 62.5 µg/mL, respectively. In the control group, equal volume of DMSO was added to the broth. After 24 h cultivation at 37 °C, the planktonic cells were removed and washed by phosphate buffered saline (PBS) thrice. Subsequently, the samples were dyed with $1\%$ crystal violet for 10 min at room temperature, then washed for three times by sterile water. Finally, the stained biofilm was dissolved in 200 μL absolute ethanol, and the OD value at 570 nm was measured [34].
## 4.6. Transmission Electron Microscope (TEM) Analysis of the Effect of MA on the Morphology of S. aureus Cells
TEM observation was employed to analyze the effect of MA on the morphology of S. aureus cells. Firstly, S. aureus cells were cultivated to the exponential phase to prepare the bacterial suspensions. Then, MA was added to reach the final concentration of 31.25 µg/mL and 62.5 µg/mL, and the obtained bacterial suspensions were incubated for another 6 h at 37 °C. The control group was treated with equivalent DMSO. After incubation, the cells were washed with sterilized PBS, processed with $2.5\%$ glutaraldehyde, and fixed with $1\%$ osmium tetroxide for 24 h, and then they were dehydrated with a gradient ethanol concentration. Finally, the cells were embedded in resin for ultrathin sections, and the samples were observed and photographed with a transmission electron microscope for analyzing the changes in intracellular structure of S. aureus [35].
## 4.7. Determination of Electrical Conductivity, DNA, RNA, and Other Macromolecular Substances Extravasation and Alkaline Phosphatase in Bacterial Liquid Phase
The electrical conductivity was measured according to the methods reported previously [36]. The suspension of S. aureus in the logarithmic growth phase was centrifuged for 10 min and washed with $5\%$ glucose until it reached to isotonic concentration, and the conductivity of the solution was determined by sterilized water in $5\%$ glucose as the control, and it was marked as L1, and different volumes of MA solution were added into S. aureus suspension to reach the final concentrations of 31.25 µg/mL and 62.5 µg/mL. Then, the mixture was mixed and incubated at 37 °C, and the conductivity of the mixture was measured every 2 h and labeled as L2. The electrical conductivity of $5\%$ glucose bacterial mixture was treated with boiling water for 5 min and marked as L0, and the relative electrical conductivity was calculated as = (L2−L1)/L0 × $100\%$. The suspension of S. aureus in the logarithmic growth phase was centrifuged for 10 min, and then the cells were resuspended and washed twice with PBS. Later, the concentration was adjusted to 107 cfu/mL, and MA was added to reach the final concentration of 31.25 µg/mL and 62.5 µg/mL, but, for the control group, nothing was added. All the treated suspensions were incubated at 37 °C, and the bacterial solution was taken every 2 h for detecting the OD value in the medium supernatant at 260 nm and 280 nm and analyzing the content of AKP in the supernatant by AKP kit [37,38].
## 4.8. Effect of MA on Bacteria β- Determination of Galactosidase Content
For normal bacterial cells, β-galactosidase could not pass through the cell membrane, and, if the cell membrane was damaged, β-galactosidase could leak through the damaged membrane, and it could be detected in the cytoplasm [39]. The bacterial solution in the logarithmic growth period was centrifuged, resuspended by sterile M9 lactose induction medium, and incubated at 37 °C for another 8 h. After centrifugation, the cell pellets were resuspended by β-galactosidase reaction buffer, and 2-Nitrophenyl β-D-galactopyranoside (ONPG) was added and mixed thoroughly. Subsequently, MA was added to the suspension to reach the final concentrations of 31.25 µg/mL and 62.5 µg/mL, and nothing was added to the control group. All samples were incubated at 37 °C, and the cell suspensions were removed every 2 h for measuring OD values at 420 nm.
## 4.9. Effect of MA on Soluble Protein Content of S. aureus Detected by SDS-PAGE
The bacterial cells in the logarithmic phase were harvested by centrifugation at 5000× g for 10 min. and diluted by fresh sterilized LB medium to OD value of 0.5. Then, MA was added to the suspension for final concentrations of 31.25 µg/mL or 62.5 µg/mL, and the following incubation was set at 37 °C for 16 h. Subsequently, cells were harvested by centrifugation at 5000 r/min for 10 min and subjected to be disrupted by sonification on ice. Later, the cell lysates were centrifuged at 10,000× g and 4 °C for 10 min to collect the soluble fraction. The supernatants were finally subjected to $15\%$ SDS-PAGE analysis, and the gels were stained with Coomassie brilliant blue R-250 and observed and imaged under the gel imaging system [34].
## 4.10. Determination of SDH and MDH Activities
Firstly, S. aureus cells that were intervened were 31.25 µg/mL or 62.5 µg/mL MA, marked as experimentational groups, and then they were intervened by DMSO, marked as a control group, which was then incubated, harvested, and disrupted by methods mentioned above. After sonification and incubation at 37 °C for 20 h, and centrifuging at 5000 r/min for 10 min, the activities of SDH and MDH in the supernatants were detected by the SDH and MDH activity detection kit [40].
## 4.11.1. Agarose Gel Electrophoresis Was Used to Determine the Interaction Mechanism between MA and DNA
A prokaryotic plasmid pET-28a DNA was intervened by added MA to the final concentrations of 0.003906, 0.007812, 0.15625l, 0.3125, 0.625, 1.25, and 2.5 mg/mL, respectively. For the control group, absolute alcohol was added to the system. All tubes were supplemented with buffer solution to reach 1.5 mL and subjected to constant temperature incubation at 37 °C for 30 min. Finally, the reaction system was terminated by adding 1 μL $10\%$ SDS and 1 μL 10 mg/mL proteinase K. A further incubation was carried out at 37 °C for another 30 min, and then the samples were electrophoresed in $0.8\%$ agarose gel electrophoresis for 20 min at 150 V, and then they were observed and photographed by a gel imaging system [41].
## 4.11.2. The Interaction Mode between MA and DNA was Determined by UV Absorption Spectrometry
The reaction was carried out in the quartz cuvette. The pET-28a DNA was intervened by adding MA to the final concentrations of 31.25 µg/mL and 62.5 µg/mL and incubated at 37 °C for 30 min. Finally, the UV absorption spectrum was detected by a UV spectrophotometer at 240–300 nm. For the control group, absolute alcohol was added to the system [42].
## 4.12. Determination Method of the Influence of MA on DNA Topoisomerase Activity
The effect of MA on the activity of DNA topoisomerase was detected by gel electrophoresis [42]. The reaction system consisted of DNA unwinding buffer I/II,d superhelix pET-28a DNA, crude enzyme extract, and different concentrations of MA solution. DMSO was used to replace MA in the control group. After incubation at 37 °C for 30 min, the reaction was terminated by adding $10\%$ SDS and 10 mg/mL proteinase K 1 μL, and a further incubation was carried out at 37 °C for 30 min. The samples were electrophoresed in $0.8\%$ agarose gel electrophoresis for 20 min at 150 V. The gel was observed and photographed by gel imaging system.
## 4.13. Statistical Analysis
SPSS 22.0 statistical software was used to analyze the experimental data, and analysis of variance was used for pairwise comparison between groups. $p \leq 0.05$ was considered as significant correlation, and $p \leq 0.01$ was considered as extremely significant correlation.
## 5. Conclusions
MA plays a significant inhibitory role on S. aureus through destroying the integrity of cell membrane and cell wall integrity, affecting the changes of energy metabolism, inhibiting protein synthesis, interacting with DNA, and inhibiting the activities of DNA topoisomerase I and II. As a highly active antibacterial natural product with multiple targets to interfere with bacterial proliferation, metabolism, and cell integrity, it is very suitable for the development of low-resistance antibacterial drugs and can be used as a candidate molecule for the development of new antibacterial drugs. This study provides an important reference and basis for the follow-up treatment of S. aureus and other pathogenic bacteria infection and the development of low-resistance, multi-target antimicrobial drugs.
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|
---
title: Intravesical Injection of Botulinum Toxin Type A in Patients with Refractory
Overactive Bladder—Results between Young and Elderly Populations, and Factors Associated
with Unfavorable Outcomes
authors:
- Yin-Chien Ou
- Yao-Lin Kao
- Yi-Hui Ho
- Kuan-Yu Wu
- Hann-Chorng Kuo
journal: Toxins
year: 2023
pmcid: PMC9967532
doi: 10.3390/toxins15020095
license: CC BY 4.0
---
# Intravesical Injection of Botulinum Toxin Type A in Patients with Refractory Overactive Bladder—Results between Young and Elderly Populations, and Factors Associated with Unfavorable Outcomes
## Abstract
Intravesical botulinum toxin type A (BoNT-A) injection has been recognized as the standard treatment for refractory overactive bladder (OAB). However, its therapeutic efficacy and safety have not been thoroughly reviewed in elderly patients. This study aims to provide treatment outcomes for patients aged ≥75 years, and to identify factors associated with unfavorable outcomes. Patients receiving intradetrusor injections of 100 U onabotulinumtoxinA for refractory OAB between 2011 and 2021 were retrospectively reviewed. Urodynamic parameters, underlying comorbidities, subjective success, and unfavorable outcomes were assessed. A total of 192 patients were included, and 65 of them were classified into the elderly group. For the elderly group, $60.0\%$ experienced subjective dryness, and $84.6\%$ remained subjective success at 6 months after the injections. The prevalence rates of common unfavorable outcomes, including urinary tract infections, large post-void residual urine volume, and urinary retention, were $9.2\%$, $27.7\%$, and $12.3\%$, respectively. Multivariate analysis revealed that female, baseline urodynamic parameters, and diabetes mellitus were associated with unfavorable outcomes in the elderly group. Intravesical BoNT-A injections provide comparable therapeutic efficacy and safety concerns in elderly patients with refractory OAB. A thorough consultation for treatment benefits and possible adverse events is mandatory before the procedure.
## 1. Introduction
Overactive bladder (OAB) is a syndrome defined by the International Continence Society and is characterized by urinary urgency, with or without urgency urinary incontinence, and usually accompanied by frequency and nocturia [1,2]. Large population-based surveys revealed that the prevalence of OAB increases with age, and is slightly higher for elderly males over females [3,4]. Many studies have described the negative influence of OAB on health-related quality of life, including anxiety, depression, sleep disorder, social withdrawal, and sexual life impairment [5,6,7,8,9,10]. Likewise, urinary incontinence is known to negatively affect the quality of life in the elderly population [11] and is also responsible for low self-esteem and depression [12]. To treat the bothersome storage symptoms of OAB, antimuscarinic agents have been developed to inhibit spontaneous detrusor smooth muscle contractions and reduce afferent signals during bladder filling [13]. The therapeutic effect of antimuscarinic agents has been proven; however, insufficient symptom relief and concomitant adverse events cause poor medication persistence and adherence [14]. Solifenacin and fesoterodine have been shown to have limited impact on cognitive function and few central nervous system adverse events for patients ≥65 years after short-term exposure [15,16,17]. Even though, uncertainty regarding cognitive decline after long-term cumulative anticholinergic exposure still limits their use in the elderly population [18,19]. On the other hand, β3-adrenoceptor agonists facilitate relaxation of the detrusor muscle during bladder filling. Both mirabegron and vibegron have been confirmed to be effective and well-tolerated in the elderly population [20,21,22,23,24,25]. However, most participants in the clinical trials were relatively healthy and did not have uncontrolled cardiovascular diseases. The long-term application of these pharmacological agents in the elderly population remains questionable.
The efficacy of intravesical injection of botulinum toxin type A (BoNT-A) has been established for patients with OAB who have an insufficient response to first-line pharmacological agents [26,27]. However, most of these published data did not focus on the elderly population, and only a handful of studies included a population with a mean age of ≥65 years old [28,29,30,31,32,33,34,35]. In addition, 75 years of age has been proposed as a new cutoff value to redefine the elderly because of the global extension of life expectancy [36]. Exploring the therapeutic outcomes and adverse events associated with BoNT-A injections in this vulnerable population is urgently necessary [37]. The commonly reported adverse events after BoNT-A injection include large post-void residual urine volume (PVR), urinary retention, and urinary tract infection (UTI) [38]. However, factors that can help identify patients at risk of these unfavorable outcomes are still limited, especially in the elderly population. Therefore, the primary aim of our study is to retrospectively evaluate the therapeutic efficacy of intravesical BoNT-A injection for refractory OAB, and the secondary aim is to investigate the factors associated with unfavorable outcomes in an elderly population aged ≥75 years.
## 2. Results
In total, 192 patients received intravesical BoNT-A injections for refractory OAB symptoms during the study period. During the administration of injections, 65 ($33.9\%$) patients were classified into the elderly group (≥75 years old), and the remaining 127 ($66.1\%$) patients were classified into the young group. For the young and elderly groups, the mean age was 58.8 ± 11.9 and 82.0 ± 4.6 years old, respectively. A higher percentage of males was found in the elderly group compared to the young group ($75.5\%$ and $34.6\%$, respectively). More comorbidities were found in the elderly group, including hypertension, diabetes mellitus (DM), dementia, coronary artery disease, and chronic kidney disease. The multichannel urodynamic parameters for baseline bladder function prior to BoNT-A injection are listed in Table 1. For the filling phase parameters, the elderly bladders are more sensitive to filling, and have a smaller cystometric bladder capacity (CBC) compared to those of the young. For the voiding phase parameters, a higher detrusor pressure at the maximal flow rate (PdetQmax), a slower maximum flow rate (Qmax), and a smaller voided volume (VV) were found for the elderly group compared to the young group.
Primary outcomes after intravesical BoNT-A injections are shown in Table 2. At 6 months after the injection, $77.2\%$ and $84.6\%$ of patients in the young and elderly group remained subjective success, respectively. The subjective success rate was comparable in both groups at 3, 6, and 12 months after the injections. Additionally, more than $60\%$ of patients in both groups experienced a certain period of subjective dryness without any urge incontinence. Compared to the baseline uroflowmetry parameters, the CBC and PVR were significantly increased, and the voiding efficiency was significantly decreased in both groups three months postoperatively. In addition, the postoperative CBC and VV were smaller, and Qmax was slower (265.8 ± 126.0 vs. 332.5 ± 158.1 mL, $$p \leq 0.010$$; 156.9 ± 106.1 vs. 220.4 ± 139.6 mL, $$p \leq 0.007$$; and 11.0 ± 7.3 vs. 15.5 ± 10.7 mL/s, $$p \leq 0.007$$, respectively) in the elderly group than in the young group. The prevalence of unfavorable outcomes such as a large PVR, urinary retention, and UTI did not vary between groups. For the young and elderly group, 29 ($22.8\%$) and 18 ($27.7\%$) patients were found to have large PVR, and 11 ($8.7\%$) and 8 ($12.3\%$) patients eventually experienced urinary retention and required catheterization to empty the bladder, respectively. Indwelling Foley catheters were used for all the 11 patients in the elderly group and 4 patients in the young group. Clean intermittent catheterization was used by the other 4 patients in the young group. The catheterization period persisted within one week for 7 patients, between one week to one month for 5 patients, and up to two months for 7 patients. Additionally, 18 ($14.2\%$) and 6 ($9.2\%$) patients in the young and elderly group experienced UTI, respectively.
Table 3 shows the baseline clinical characteristics and multichannel urodynamic parameters of elderly patients with or without postoperative unfavorable outcomes: 6 ($9.2\%$), 18 ($27.7\%$), and 8 ($12.3\%$) patients in the elderly group had postoperative UTI, large PVR, and urinary retention, respectively. For baseline multichannel urodynamic parameters, patients with postoperative UTI tended to have lower bladder compliance (19.7 ± 12.5 vs. 61.0 ± 67.3 mL/cmH2O, $$p \leq 0.014$$) and a higher PdetQmax (56.2 ± 33.2 vs. 29.0 ± 17.4 cmH2O, $$p \leq 0.013$$) compared to those without UTI, whereas patients with postoperative large PVR or with urinary retention tended to have higher PdetQmax (40.1 ± 23.4 vs. 28.3 ± 18.6 cmH2O, $$p \leq 0.029$$; 55.5 ± 27.1 vs. 28.2 ± 17.3 cmH2O, $$p \leq 0.001$$, respectively) compared to those with normal PVR or without urinary retention. Regarding underlying comorbidities, patients with postoperative UTI had a higher prevalence of dementia, while patients suffering postoperative urinary retention had a greater prevalence of DM and cerebrovascular accidents.
For the elderly population, multivariate analysis revealed that female, lower baseline bladder compliance, and higher PdetQmax were significantly associated with postoperative UTI. In addition, a higher baseline PdetQmax and a history of DM were associated with urinary retention. However, the association between higher baseline PdetQmax and postoperative large PVR failed to achieve significance (OR: 1.027, $$p \leq 0.075$$) after adjusting for age and gender (Table 4).
Forty-three ($33.9\%$) patients in the young group and 14 ($21.5\%$) patients in the elderly group received subsequent injection cycles after the initial BoNT-A effect vanished, whereas the other 135 ($70.4\%$) patients received only one episode of BoNT-A injection. The injection cycles between young and old patient groups are shown in Table 5.
## 3. Discussion
The role of BoNT-A in treating refractory OAB is well established in both sexes [26,27]. However, studies focusing on efficacy and adverse events in the elderly population are limited [38]. In addition, with the extension of life expectancy, “75 years of age and over” is increasingly being used to define the elderly population [36]. Hence, our study defined the elderly population as patients aged 75 years or older. We aimed to determine the therapeutic outcome of intravesical BoNT-A in this population and identify valuable factors associated with adverse events. Our results revealed that although elderly bladders were more sensitive at baseline compared to young bladders, BoNT-A intravesical injection was equally effective for OAB symptom control. In addition, the prevalence of adverse events was equal in both age groups. Female sex, lower bladder compliance, and higher PdetQmax were associated with postoperative UTI, while DM and higher PdetQmax were associated with postoperative urinary retention in the elderly population.
Several possible pathophysiologies have been proposed to explain refractory OAB [39], including urothelial dysfunction with aging [40], undetected bladder outlet obstruction (BOO), chronic bladder ischemia or inflammation [41,42], and central sensitization [43,44]. These conditions are commonly found in the elderly population owing to aging-induced changes from the brain to the bladder itself [45,46,47]. In our study, more than $75\%$ of patients in the elderly group were men, a proportion much higher than that in the young group. This may further emphasize the importance of chronic undetected BOO in bladder remodeling [48]. It is well-documented that the presence of BOO will result in large PVR and could be a risk of urinary retention after the intravesical BoNT-A injection, especially in the elderly [29,30]. Therefore, in our clinical practice, we will investigate patients with refractory OAB by video-urodynamic study to find if there is BOO, and the BoNT-A injection can only be performed in patients without BOO, or if their BOO has been well-treated. In addition, our findings of the preoperative multichannel urodynamic study in these elderly bladders, including increased bladder sensation and reduction in bladder capacity, were consistent with the known changes in the aging bladder [46]. Intravesical BoNT-A injection provides sensory blockade in addition to chemo-denervation of the bladder detrusor muscle [49,50]. This may explain why patients who are refractory to conventional OAB medications can be successfully treated with BoNT-A.
To the best of our knowledge, no case-control study has compared the therapeutic efficacy of BoNT-A between patients aged ≥75 years and those aged <75 years. White et al. [ 34] reported a case series of 21 refractory OAB patients aged 75 years and older and concluded that BoNT-A injection is efficacious, durable, and has a low incidence of adverse events in the short term. Frailty has been proposed as a negative factor for long-term treatment success, but this study used “age greater than 65 years” as the definition of elderly [29]. Our study demonstrated that the elderly population (≥75 years old) had similar subjective success rates at 3, 6, and 12 months postoperatively compared with the young population. Furthermore, with no between-group differences, >$60\%$ of patients in both groups eventually experienced a certain period of subjective dryness without urge incontinence. This highlights that age itself is not a direct factor that affects the bladder response to BoNT-A. Instead, the underlying pathophysiologies that develop during the aging process to induce refractory OAB are key factors in determining therapeutic outcomes.
Considering the direct chemo-denervation effect on the bladder detrusor muscle, PVR elevation and urinary retention are common concerns after intravesical BoNT-A injections [51]. A large PVR is commonly defined as a PVR greater than 150 or 200 mL, and approximately 6–$61\%$ of patients with a mean age > 65 years have been reported to experience a large PVR after receiving injections [28,29,30,35]. Miotla et al. reported that female patients with PVR > 200 mL or retention after injections were older than those with PVR < 200 mL [52]. Liao and Kuo proposed that instead of age, frailty was associated with post-injection PVR > 150 mL [29]. In our elderly population (≥75 years old), 18 ($27.7\%$) patients were found to have a large PVR > 200 ml after BoNT-A intravesical injection, and eight ($12.3\%$) patients eventually experienced urinary retention and needed temporary Foley catheter indwelling. There was no difference in the prevalence of a large PVR and urinary retention between the elderly and young populations. Although no valuable factor could be found to be associated with large postoperative PVR in our elderly population, a higher baseline PdetQmax and a history of DM were identified as factors associated with postoperative urinary retention. DM is a well-known factor that induces overactive bladder and affects detrusor contractility during the voiding phase [53]. Wang et al. reported that intravesical BoNT-A successfully managed detrusor overactivity and achieved a similar treatment success rate in both DM and non-DM patients but with a higher risk of large PVR and general weakness in DM patients [54]. In elderly patients with DM, detailed consultation and close follow-up for postoperative PVR are necessary.
UTI is another common but frustrating unfavorable outcome after intravesical BoNT-A injections [55]. A recent systemic review revealed that the prevalence rate of UTI after intravesical BoNT-A injection for treating OAB is approximately $29.8\%$ [56]. Both storage and emptying dysfunction have been proposed to impact UTI recurrence [57,58]. In our study, we found that female sex, lower bladder compliance, and a higher PdetQmax were associated with postoperative UTI in the elderly population. Lower bladder compliance and higher PdetQmax are common bladder dysfunctions that increase intravesical pressure during both the storage and emptying phases. Increased intravesical pressure is known to cause bladder ischemia, which may predispose the bladder to infection because of a delayed or insufficient immune response [59,60].
Although the present study successfully demonstrated the therapeutic outcomes and adverse events of intravesical BoNT-A injections in a population older than most of the published data, some limitations still exist. First, its retrospective design made it possible to involve biases during patient selection, data collection, and statistical analysis. Moreover, we could not further define ‘frailty’ by retrospectively reviewing the medical records. Instead, we believe that using 75 years as the cutoff value would be indeed a reasonable choice. Second, the small sample size in the elderly group limited the statistical power in multivariate logistic regression analyses, and also hindered the subgroup analysis for different sexes. Third, no postoperative multichannel urodynamic data were available to provide detailed bladder storage function after BoNT-A injection. Considering the invasiveness of the test, a simple uroflowmetry with PVR is commonly used to represent postoperative bladder function. Finally, in the long-term follow-up, we found only $29.7\%$ of refractory OAB patients received subsequent BoNT-A injection in our hospital. This result indicates that the patients might not be satisfied with the unfavorable treatment outcome after the first BoNT-A injection and would choose medical therapy for their bothersome OAB symptoms. However, understanding the treatment effect of BoNT-A on the sensory blockade in the elderly population remains limited. Prospective case-control studies are necessary to evaluate treatment outcomes and outcome predictors in this population in detail.
## 4. Conclusions
Intravesical BoNT-A injections provided equally effective and durable therapeutic outcomes in both young and elderly patients (≥75 years old) with refractory OAB. The prevalence rates of common unfavorable outcomes were equal between the two age groups. For elderly patients receiving intravesical BoNT-A injection, female, lower bladder compliance, and higher PdetQmax were associated with postoperative UTI, whereas a history of DM and higher PdetQmax were associated with urinary retention postoperatively. A thorough consultation for possible benefits and adverse events is mandatory, especially in elderly patients with certain risk factors.
## 5. Materials and Methods
We retrospectively reviewed patients with idiopathic OAB symptoms refractory to conventional medications who received intravesical injections of BoNT-A for the first time at a tertiary medical center in eastern Taiwan. All patients had persistent urgency urinary incontinence even with antimuscarinics, β3-adrenoceptor agonists, or a combination of both for more than three months. A multichannel urodynamic study, including cystometry and a pressure flow study, was performed preoperatively in accordance with the International Continence Society’s good urodynamic practice recommendations [61] to confirm the presence of detrusor overactivity. All patients have been proven to be non-BOO by the video-urodynamic study before receiving the intravesical BoNT-A injections. Patients with underlying neurological factors that may cause neurogenic detrusor overactivity, or intrinsic sphincter deficiency were excluded from this study. Patients who were ≥75 years old while receiving the injections were classified into the elderly group, whereas the others belonged to the young group.
Baseline lower urinary tract function was assessed for each patient using uroflowmetry, PVR, and a multichannel urodynamic study before BoNT-A injection. Parameters including the VV, Qmax, CBC, and voiding efficiency were collected from the uroflowmetry. CBC was defined as the sum of VV and PVR, and voiding efficiency was defined as VV divided by CBC. For the multichannel urodynamic study, bladder sensations, compliance, and the presence of detrusor overactivity were recorded as the filling phase parameters, whereas PdetQmax, Qmax, VV, CBC, and PVR were recorded as the voiding phase parameters. BOO was defined as BOO index >40 for men [62], and as PdetQmax > 35 cmH2O for women [63]. Bladder sensations were further classified as the first sensation of filling, full sensation, and urge sensation, according to the patients’ reports.
All patients were hospitalized and received intravesical injections of 100 units of Botox® (Allergan, Irvine, CA, USA), which is the standard dosage used to treat refractory OAB [26], under general anesthesia in the operating room. The injection method has been described previously [26]. Briefly, 10 mL normal saline was used to dilute each Botox vial. The injection needle was inserted into the posterior and lateral bladder walls under the guidance of rigid cystoscopy, and a total of 20 evenly distributed intradetrusor injections (0.5 mL for each injection) were performed while sparing the trigone area. A 14 Fr. urethral Foley catheter was placed and remained in place for one day after the Botox injection. Objective outcomes were assessed three months after the injections using uroflowmetry and PVR. Subjective treatment success and improvement of urge incontinence were reviewed according to the medical records at the out-patient department during serial follow-ups. As improvement of urinary incontinence and difficult urination might coexist after intravesical BoNT-A injection, patients might consider that they had unsuccessful treatment if they had severe difficulty in urination even though urinary incontinence had improved. Therefore, a subjective success was defined by having a Global Response Assessment (scoring from −3 to +3, indicating markedly worse to markedly improved after the treatment [64]) of +2 or +3. Underlying comorbidities and postoperative unfavorable outcomes, including a large PVR (defined as PVR >200 mL during the follow-up period), urinary retention, and UTI, were also collected from the patients’ medical records. All patients were followed up regularly at the out-patient clinic with or without OAB medication, and repeat BoNT-A injections were performed if patients had recurrence of OAB symptoms and requested for injection, otherwise they were continuously treated with oral medications.
Statistical analyses were performed using SPSS Statistics for Windows, Version 17.0. Chicago: SPSS Inc. Continuous and categorical variables are expressed as mean ± standard deviation and as numbers and percentages, respectively. Statistical comparisons between groups were performed using the Mann–Whitney U test for continuous variables and the chi-square test for categorical variables. Fisher’s exact test was applied when > $20\%$ of the expected frequencies were less than five. Comparisons between baseline and follow-up within-group differences were performed using the Wilcoxon signed-rank test. Age, gender, and variables demonstrating significant differences between patients with or without each unfavorable outcome were further analyzed with multivariate logistic regression analyses to identify factors associated with postoperative unfavorable outcomes in the elderly group. All statistical assessments were considered significant when the two-sided p-value was <0.05.
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|
---
title: Glucose-6-Phosphate Dehydrogenase Activity in Milk May Serve as a Non-Invasive
Metabolic Biomarker of Energy Balance in Postpartum Dairy Cows
authors:
- Ayelet Hod
- Jayasimha Rayalu Daddam
- Gitit Kra
- Hadar Kamer
- Yuri Portnick
- Uzi Moallem
- Maya Zachut
journal: Metabolites
year: 2023
pmcid: PMC9967546
doi: 10.3390/metabo13020312
license: CC BY 4.0
---
# Glucose-6-Phosphate Dehydrogenase Activity in Milk May Serve as a Non-Invasive Metabolic Biomarker of Energy Balance in Postpartum Dairy Cows
## Abstract
Negative energy balance (EB) postpartum is associated with adverse outcomes in dairy cows; therefore, non-invasive biomarkers to measure EB are of particular interest. We determined whether specific metabolites, oxidative stress indicators, enzyme activity, and fatty acid (FA) profiles in milk can serve as indicators of negative EB. Forty-two multiparous Holstein dairy cows were divided at calving into 2 groups: one was milked 3 times daily and the other, twice a day for the first 30 d in milk (DIM). Cows were classified retrospectively as being in either negative EB (NEB, $$n = 19$$; the mean EB during the first 21 DIM were less than the overall median of −2.8 Mcal/d), or in positive EB (PEB, $$n = 21$$; the mean EB was ≥−2.8 Mcal/d). The daily milk yield, feed intake, and body weight were recorded individually. Blood samples were analyzed for metabolites and stress biomarkers. Milk samples were taken twice weekly from 5 to 45 DIM to analyze the milk solids, the FA profile, glucose, glucose-6-P (G6P), G6P-dehydrogenase (G6PDH) activity, malic and lactic acids, malondialdehyde (MDA), and oxygen radical antioxidant capacity (ORAC). The NEB cows produced $10.5\%$ more milk, and consumed $7.6\%$ less dry matter than the PEB cows. The plasma glucose concentration was greater and β-hydroxybutyrate was lower in the PEB vs. the NEB cows. The average concentrations of milk glucose, G6P, malic and lactic acids, and MDA did not differ between groups; however, the G6PDH activity was higher and ORAC tended to be higher in the milk of NEB vs. the PEB cows. The correlation between milk G6PDH activity and EB was significant (r = −0.39). The percentages of oleic acid and total unsaturated FA in milk were higher for the NEB vs. the PEB cows. These findings indicate that G6PDH activity in milk is associated with NEB and that it can serve as a non-invasive candidate biomarker of NEB in postpartum cows, that should be validated in future studies.
## 1. Introduction
During the transition from late gestation to lactation, high-yielding dairy cows experience a sudden shift in their energy demand for milk production, which induces tissue mobilization and negative energy balance (NEB) [1,2]. Negative EB postpartum is associated with several adverse outcomes on cow health and performance [3,4,5]. Therefore, in recent years, there has been growing interest worldwide in establishing empirical non-invasive indicators of cow health and fitness [6]. Identifying biomarkers of NEB is of great importance to the dairy industry, since direct measurement of feed intake, which is required for calculating energy balance, is not feasible in a commercial setting. Xu et al. [ 7] used liquid chromatography-mass spectrometry and nuclear magnetic resonance techniques to identify metabolic changes in milk of early lactation cows. Importantly, they found that 15 metabolites were positively correlated with EB and 20 were negatively correlated with it, which could be attributed to the increased leakage of cellular content and the elevated synthesis and metabolism in epithelial cells during NEB.
Epithelial cells in the mammary gland do not synthesize glucose due to a lack of the enzyme glucose-6-phosphatase [8]. Therefore, milk glucose concentrations are dependent on glucose absorbed from the blood. Within the mammary gland, glucose is converted to glucose-6-phosphate (G6P), which is a central metabolite in the glycolytic pathway and is an intermediate compound during lactose synthesis; G6P participates in the initial steps of both glycolysis and the pentose phosphate pathway (PPP) [9]. The enzyme G6P-dehydrogenase (G6PDH) is the first enzyme in the PPP that converts G6P into 6-Phosphogluconolactone. In early lactation, milk glucose is first low and then gradually increases, whereas G6P in milk is high postpartum and then decreases in the milk of dairy cows [10,11]. Thus, in a study that involved a small number of cows, a significant correlation was found between G6PDH activity and G6P content in milk postpartum [11]. Based on these findings, we previously postulated that the balance between these biochemical pathways (glycolysis and PPP) within the mammary gland, which may be reflected in the concentrations of glucose, G6P, and G6PDH activity, is associated with the energetic and oxidative state of the cow, as a part of the homeostatic adaptation to NEB at the onset of lactation [11]. Therefore, these compounds could serve as biomarkers of cows’ physiological state postpartum [6]. Here, we aimed to validate and further examine several milk metabolites (glucose, G6P, malic acid, and lactic acid), G6PDH activity, markers of oxidative stress, and the fatty acid (FA) composition of milk in an intensive and comprehensive study with postpartum dairy cows, to determine the relationship between NEB and candidates for milk biomarkers in high-yielding dairy cows.
## 2.1. Cows and Experimental Procedures
The experimental protocol and procedures were approved by the Volcani Center Animal Care Committee (IL $\frac{637}{16}$). The study was conducted at the experimental dairy farm of the Volcani Center in Rishon LeZion, Israel. A detailed account of the study procedures was published [12]. Briefly, 42 multiparous high-yielding Holstein cows were divided into 2 subgroups: 21 cows were milked 3 times a day (at 05:00, 13:00, and 20:00 h), and 21 cows were milked twice a day (at 07:00 and 19:00 h) until 30 days in milk (DIM); from 30 DIM, all cows were housed together and milked 3 times a day. From day 5 postpartum until 30 DIM, milk samples were taken twice a week (Monday and Thursday) from 2 consecutive milkings for cows that were milked twice daily, or from 3 consecutive milkings for cows that were milked thrice daily. We assumed that the different milking frequencies would influence the milk yield and intake, and consequently, EB, resulting in postpartum cows with varied EB. From 30 to 45 DIM, milk samples were taken from 3 consecutive milkings twice a week. Milk samples were analyzed for milk fat, protein, and lactose by infrared analysis (standard IDF 141C: 2000). The milk fat FA profile was determined using a Fourier transform mid-infrared spectrometer (Bentley FTS, Bentley Instruments, Chaska, MN, USA) at the laboratories of the Israeli Cattle Breeders’ Association (Caesarea, Israel). This instrument was calibrated monthly by Secondary Reference Material (SRM) produced by Actalia (Poligny, France), and the FA profile in the reference material was determined by GC. The somatic cell counts (SCC) were determined in the same laboratory. Additional milk samples were collected on the same milk collection days; representative daily pools were prepared for each cow according to the milk production for each milking, and frozen at −20 °C, pending the analysis of milk metabolites, G6PDH activity, and indicators of oxidative stress. Postpartum, the cows were fed a standard Israeli milking cow ration. The composition and content of the diet are presented in Moallem et al. [ 12]. The diet was offered once daily at 10:00 h ad libitum to about $5\%$ orts. The individual amounts offered and the daily leftovers were recorded daily to calculate the individual feed intake.
The EB was calculated according to NRC [2001], as described in Moallem et al. [ 12] for the first 21 d of lactation, and the cows were divided post-factum into 2 groups. The median of the average EB during the first 21 DIM was calculated as −2.8 Mcal/d. Cows were classified as being in negative EB (NEB, $$n = 19$$) if the mean EB during the first 21 DIM was less than −2.8 Mcal/d, and as being in positive EB (PEB, $$n = 21$$) if the mean EB during the first 21 DIM was greater than or equal to −2.8 Mcal/d. Two cows were excluded from the analysis due to extreme EB values. As expected, among the NEB cows, 12 cows ($63\%$) were milked 3 times daily and 7 cows ($37\%$) were milked twice daily; among the PEB cows, 8 cows ($38\%$) were milked 3 times daily and 13 cows ($62\%$) were milked twice daily.
## 2.2. Blood Sampling and Analysis of Metabolites and Stress Biomarkers
Blood samples were taken 3 times weekly (on Sunday, Tuesday, and Thursday) from calving until 21 DIM. After the morning milking, the blood samples were collected by coccygeal venipuncture into vacuum tubes containing lithium heparin (Becton Dickinson System, Cowley, UK), and the tubes were immediately placed in ice. Plasma was separated by centrifugation for 15 min at 1000× g, divided into 4 tubes, and stored at −80 °C pending analysis. The concentrations of glucose, non-esterified fatty acids (NEFA), beta hydroxybutyrate (BHB), malondialdehyde (MDA), cortisol, and tumor necrosis factor alpha (TNF-α) were determined. The plasma glucose concentrations were analyzed using the Cobas C111 Autoanalyser (Roche Holding GmbH, Grenzach-Wyhlen, Germany). The concentrations of NEFA in the plasma were determined using a NEFA C Test Kit (Wako Chemicals GmbH, Neuss, Germany). The intra- and interassay coefficients of variation (CV) for the NEFA assay were 5.9 and $6.1\%$, respectively. The plasma BHB concentration was determined using a RANBUT D-3-Hydroxybutyrate kit (Randox, Crumlin, UK). The intra- and interassay CVs for the BHB assay were 1.3 and $1.6\%$, respectively. The plasma MDA concentration was measured by the thiobarbituric acid reactive substances (TBARS) fluorometric assay [13]; the intra- and interassay CVs were $9.4\%$ and $2.5\%$, respectively. The plasma cortisol concentrations were determined by ELISA (EIA1887, DRG International, Inc., Springfield, NJ, USA), and the TNF-α concentration was determined using a bovine TNF-α Duoset ELISA kit (R&D Systems, Inc., Minneapolis, MN); the intra- and interassay CVs were 9.3 and $6.1\%$, respectively.
## 2.3. Milk Metabolites and Indicators of Oxidative Stress
To determine the milk metabolites, G6PDH activity, and oxidative stress indices, we randomly selected 12 cows from each milking frequency group. Since the classification according to the calculated EB was done post-factum, the milk analyses were conducted in samples of 13 PEB and 11 NEB cows. Thawed milk samples were centrifuged at 3000× g for 20 min at 4 °C to remove the fat layer, and the skim milk was analyzed for milk glucose, G6P, as well as lactic and malic acid concentrations using a fluorometric assay via enzymatic reactions, and the activity of G6PDH in milk was analyzed by modifying a classical enzymatic assay procedure in which the reduction of NADP+ to NADPH is coupled to form a fluorometric chromophore [11]. In addition, the milk MDA concentration was measured according to the TBARS fluorometric assay and the oxygen radical antioxidant capacity (ORAC) in milk serum was analyzed by a fluorometric procedure as described previously [11].
## 2.4. Statistical Analysis
Continuous variables (milk, milk solids, DMI, EB, milk, and blood parameters) were analyzed as repeated measurements using the PROC MIXED procedure of SAS, version 9.2 [2002] (SAS Institute, Inc., Cary, NC, USA). When relevant, variables were analyzed using the specific previous lactation data as covariates.
The model was Yijkl = µ + Ti + Lj + C(T × L)ijk +DIMijkl + Eijklm, where µ = the overall mean; Ti = the treatment effect, $i = 1$ to 2; Lj = parity, $j = 2$ or >2; C(T × L)ijk = cow k nested in treatment i and parity j; DIMijkl = day in milk as a continuous variable; Eijklm = random residual.
The interaction treatment × DIM was tested and found to be non-significant; therefore, it was excluded from the model. Autoregressive order 1 was used as a covariance structure in the model because it resulted in the lowest Bayesian information criterion for most of the variables tested. To evaluate the relationship between EB and milk metabolites and FA, a linear regression analysis was performed for each treatment using the REG procedure of SAS (version 9.2). Least square means and adjusted SEM are presented; p ≤ 0.05 was accepted as significant.
## 3.1. Milk Production and Composition, Dry Matter Intake, and Energy Balance
In the present study, the NEB cows produced $10.5\%$ more milk than the PEB cows ($$p \leq 0.0001$$; Table 1). The ECM yield tended to be higher in the NEB cows ($$p \leq 0.06$$), with no difference between groups in $4\%$ FCM yield (Table 1). No differences were observed in the fat percentage or lactose percentage in milk; however, there was $6.3\%$ more protein in the PEB cow milk than in that of the NEB cows ($$p \leq 0.0006$$; Table 1). No differences were found in milk SCC between groups. During the first 21 d postpartum, DMI was $13.4\%$ lower for the NEB cows than for the PEB cows ($p \leq 0.0001$), and the average calculated EB until 21 DIM was −5.9 and 4.1 Mcal/d for the NEB and PEB cows, respectively ($p \leq 0.0001$; Table 1). In addition, the DMI from calving until 45 DIM was $7.6\%$ lower in the NEB cows vs. the PEB cows (26.6 vs. 28.9 kg/d, respectively, SEM = 0.3, $p \leq 0.0001$), and the average calculated EB until 45 DIM was −2.9 and 5.2 Mcal/d for the NEB and PEB cows, respectively (SEM = 0.5, $p \leq 0.0001$).
## 3.2. Plasma Concentrations of Metabolites and Stress Biomarkers
The average plasma glucose concentration during the first 21 DIM was $9.3\%$ greater in the PEB than in NEB cows ($$p \leq 0.002$$), and the average plasma BHB concentration was $23\%$ lower in the PEB vs. NEB cows ($p \leq 0.0001$; Table 2). The increased BHB and the lower glucose concentrations in the plasma of NEB cows were in agreement with our classification of the cows according to their calculated EB. No differences were observed between groups regarding the plasma concentrations of NEFA, malondialdehyde, cortisol, or TNF-α (Table 2).
## 3.3. Milk Metabolites and Markers of Oxidative Stress, and the Milk FA Profile
The average concentrations of the parameters examined in the milk are presented in Table 3. The average concentrations of milk glucose, G6P, malic acid, lactic acid, and MDA during weeks 1–7 in lactation did not differ between NEB and PEB cows. However, G6PDH activity was higher in the milk of NEB vs. PEB cows ($$p \leq 0.03$$), and the ORAC tended to be higher in NEB vs. PEB milk ($$p \leq 0.1$$; Table 3).
The milk FA profile differed in the NEB and PEB cows; the percentage of C18:1 was higher in the milk of NEB than in the milk of PEB ($$p \leq 0.001$$; Table 3); therefore, the total percentage of mono-unsaturated FA (MUFA) was higher in NEB ($$p \leq 0.01$$); in addition, the total percentage of unsaturated FA (UFA) was higher in NEB milk than in PEB milk. The percentage of C16:0 tended to be lower in NEB ($$p \leq 0.10$$); thus, the total percentage of saturated FA (SFA) tended to be lower in NEB vs. PEB milk ($$p \leq 0.10$$; Table 3).
As shown in, the concentrations of milk G6P (Figure 1A) during the first week postpartum were high and then declined until 7 weeks postpartum, and vice versa for the milk glucose concentration (Figure 1B). The activity of G6PDH was highest in week 1 and then declined until 7 weeks postpartum, and it was significantly higher in NEB than in PEB milk in weeks 2, 3, and 4 postpartum (Figure 1C).
## 3.4. Correlations between Milk Metabolites and the FA Profile and the Calculated EB
We tested the correlation between EB and the milk parameters; we found a negative correlation between milk G6PDH activity and the EB (r = −0.39, $p \leq 0.0001$). The milk G6P and the MDA contents were also significantly correlated with EB, but with small correlation coefficients (Table 4). In addition, the percentage of oleic acid tended to be negatively correlated with EB, and SFA in milk tended to be positively correlated with EB (Table 4).
## 4. Discussion
A severe magnitude or duration of NEB during the postpartum period raises the risk of metabolic diseases and is associated with reduced conception rates. Milk metabolites and components are desirable candidates to be biomarkers, since this medium is non-invasive and accessible in a commercial setting. Other fluids and tissues, such as hair samples [14], may potentially prove to be a valuable source of non-invasive metabolic biomarkers in the future. Currently, several blood metabolites, the calculated EB, and the body condition score are the traditional methods for detecting NEB; however, they require complex methods such as individual feed intake, body weight, time-consuming blood collection, and the need for trained staff [15,16]. Indeed, in the present study, we showed that plasma BHB levels increased in NEB vs. PEB dairy cows. Elevated blood levels of BHB are linked to an increased risk of infectious illnesses [17,18].
Glucose-6-phosphate-dehydrogenase (G6PDH), the first enzyme in the pentose phosphate pathway, has also been proposed as a candidate milk biomarker for NEB diagnosis in dairy cows, based on the relationship between milk G6P and EB. Few studies have examined the presence of G6PDH in cow milk. Zachut et al. [ 11] demonstrated that milk G6PDH activity in cows peaked during the first and second weeks of lactation before declining until the fifth week of lactation. This is similar to milk G6P concentrations. The patterns of the changes in the concentration of milk G6P and glucose are in agreement with others [10,11]. This supports our earlier hypothesis that elevated G6PDH activity in early lactation reflects increased shunting of G6P to the PPP [11]. However, in this study the average concentrations of G6P in milk did not differ in the milk of NEB vs. PEB; thus, we do not propose it as a candidate biomarker of NEB. On the other hand, there was an increase in G6PDH activity in cow milk with NEB, compared with cow milk with PEB, and together with the correlation between G6PDH activity and EB (r =−0.39), we propose that G6PDH activity can serve as an innovative candidate biomarker for EB in dairy cows for future validation studies, which is in agreement with our premise [6]. As stated above, others found higher concentrations of citrate, cis-aconitate, creatinine, glycine, phosphocreatine, galactose-1-phosphate, glucose-1-phosphate, UDP-N-acetyl-galactosamine, UDP-N-acetyl-glucosamine, and phosphocholine, but lower concentrations of choline, ethanolamine, fucose, N-acetyl-neuraminic acid, N-acetyl-glucosamine, and N-acetyl-galactosamine in milk of cows in NEB in early lactation [7]. Taken together, the strength of our data relies on the premise that various milk metabolites and enzyme activities indicate the cows’ EB during early lactation.
Changes in blood plasma lipidome are evident in postpartum compared with prepartum dairy cows [19]. In milk as well, changes in milk FA composition are known to be related to the metabolic status of dairy cows, because adipose tissue lipolysis during negative EB releases palmitic, stearic, and oleic acids, which are incorporated into the milk fat [20,21,22]. Indeed, an elevated proportion of oleic acid in milk fat during NEB postpartum was demonstrated by Gross et al. [ 23]. In our experiment, the composition of FA in milk was correlated with the EB of the cows: the ratio of oleic acid in milk was higher in cows with NEB than in cows with PEB. In addition, the proportion of MUFA and UFA was higher, whereas the SFA tended to be lower in cows with NEB. Our results support the relationship between oleic acid and NEB in the milk of postpartum dairy cows, although the correlation only tended toward significance. Moreover, since dietary composition affects milk FA composition and may change the oleic acid percentage in the milk, any changes in the milk FA composition should be interpreted carefully by considering the diet, as previously suggested [22]. Recently, when examining milk metabolites and FA profiles in both a restricted feed model and in postpartum cows, it was demonstrated that milk cis-9 C18:1 had a good single linear regression with energy balance, and that milk G6P was negatively correlated with EB [24], which is similar to our findings.
In conclusion, we found that G6PDH activity in milk is correlated with individual EB in postpartum cows, suggesting that it might serve as a candidate indicator of NEB in postpartum cows, that should be validated in future studies. Studies to determine more novel non-invasive biomarkers of NEB, such as metabolites or enzymatic activity in milk, in dairy cows are warranted.
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---
title: Identification of Bioactive Peptides from a Laminaria digitata Protein Hydrolysate
Using In Silico and In Vitro Methods to Identify Angiotensin-1-Converting Enzyme
(ACE-1) Inhibitory Peptides
authors:
- Diane Purcell
- Michael A. Packer
- Maria Hayes
journal: Marine Drugs
year: 2023
pmcid: PMC9967564
doi: 10.3390/md21020090
license: CC BY 4.0
---
# Identification of Bioactive Peptides from a Laminaria digitata Protein Hydrolysate Using In Silico and In Vitro Methods to Identify Angiotensin-1-Converting Enzyme (ACE-1) Inhibitory Peptides
## Abstract
Bioactive peptides range in size from 2–30 amino acids and may be derived from any protein-containing biomass using hydrolysis, fermentation or high-pressure processing. Pro-peptides or cryptides result in shorter peptide sequences following digestion and may have enhanced bioactivity. Previously, we identified a protein hydrolysate generated from *Laminaria digitata* that inhibited ACE-1 in vitro and had an ACE-1 IC50 value of 590 µg/mL compared to an ACE-1 IC50 value of 500 µg/mL (~2.3 µM) observed for the anti-hypertensive drug Captopril©. A number of peptide sequences (130 in total) were identified using mass spectrometry from a 3 kDa permeate of this hydrolysate. Predicted bioactivities for these peptides were determined using an in silico strategy previously published by this group utilizing available databases including Expasy peptide cutter, BIOPEP and Peptide Ranker. Peptide sequences YIGNNPAKGGLF and IGNNPAKGGLF had Peptide Ranker scores of 0.81 and 0.80, respectively, and were chemically synthesized. Synthesized peptides were evaluated for ACE-1 inhibitory activity in vitro and were found to inhibit ACE-1 by 80 ± $8\%$ and 91 ± $16\%$, respectively. The observed ACE-1 IC50 values for IGNNPAKGGLF and YIGNNPAKGGLF were determined as 174.4 µg/mL and 133.1 µg/mL. Both peptides produced sequences following simulated digestion with the potential to inhibit Dipeptidyl peptidase IV (DPP-IV).
## 1. Introduction
Bioactive peptides are sequences of amino acids ranging in size from 2–30 in length providing health benefits beyond basic nutrition when consumed [1]. Health benefits associated with bioactive peptides are extensive and include the reduction of hypertension and associated illnesses such as stroke and heart attack. The bioactive peptide activity pathway is thought to occur through the inhibition of enzymes within the Renin-Angiotensin-Aldosterone-System (RAAS) including Angiotensin-Converting-Enzyme-1 (ACE-1; EC3.4.15.1) and Renin (EC 3.4.23.15) [2,3,4,5]. In addition, other potential health benefits associated with bioactive peptides include anti-microbial and anti-inflammatory benefits, prevention of type 2 diabetes (T2D) through inhibition of alpha amylase (EC 3.2.1.1) and dipeptidyl peptidase IV (DPP-IV; EC 3.4.14.5) and inhibition of enzymes such as Prolyloligopeptidase (POP; EC 3.4.21.26) and BACE-1 that may result in mental health benefits. These peptides can be derived from any protein source including non-food sources such as natural protein produced in the gastrointestinal tract, but the most well-recognized sources are dairy, meat and fish [6,7].
Recently, we utilized enzymatic hydrolysis combining the enzymes Viscozyme® and Alcalase® as a method to extract protein from the brown seaweed *Laminaria digitata* [8]. Hydrolysis is a well-known strategy for the generation of bioactive peptides. Hydrolysis may increase the health benefits of protein hydrolysates. Several ACE-1 inhibitory peptides were identified to date from products including cheese, milk and yoghurt. ACE-1 is a zinc metallic protease, which converts Angiotensin I to the potent vasoconstrictor Angiotensin II, and enhances the degradation of the vasodilator Bradykinin [9]. Arterial Hypertension (AHT) is treated using drugs that inhibit the Angiotensin I-Converting Enzyme (ACE-1; EC 3.4.15.1) such as Enalapril® or Captopril© [10,11,12,13]. However, side effects associated with these drugs have prompted research for natural remedies that may also treat or prevent the development of high blood pressure [14,15,16,17]. Previous studies have shown the ACE-1 and anti-hypertensive activities of the brown seaweeds Undaria pinnatifida, *Sargassum siliquosum* and Sargassum polycystum, [18,19].
In silico analysis is a valuable technique for predicting the potential bioactivities of peptides [3,20,21,22]. In silico analysis was used recently to identify anti-thrombotic [23,24,25] peptides from a variety of sources including dairy, mealworms, plants, peas, canola, maize and, more recently, seaweeds [20,26,27,28]. This approach has not, to the best of the authors’ knowledge, been applied to the brown seaweed Laminaria digitata.
This paper details the identification of peptides generated through hydrolysis of *Laminaria digitata* protein using enzymes and the characterisation of peptide sequences using mass spectrometry (MS). Subsequently, identified peptide sequences were ranked for potential bioactivities using an in silico approach described herein. One hundred and thirty peptides were identified from the L. digitata permeates and two peptides were synthesized. The ACE-1 IC50 values of these peptides were subsequently determined.
## 2.1. Identification of Peptides Using Mass Spectrophometery and In Silico Analysis of Sequenced Peptides
A total of 130 peptides were identified from the 3-kDa permeate fraction using mass spectrometry (MS) as shown in Table 1 ($$n = 3$$). The identified peptide sequences had a >$95\%$ confidence level as being derived from the identified proteins listed in Table 2 and homology was confirmed using UniProt (https://www.uniprot.org/, accessed on 10 December 2022) [29]. Peptides had amino acid sequence homology with proteins from red seaweeds including Neopyriopia yezoensis, *Porphyra umbilicalis* and Sporolithon durum, and from the brown seaweeds including Laminaria digitata; Colpomenia wynnei; Dictyopteris divaricate; Fucus vesiculosus, Ascophyllum nodosum; Sargassum horneri; Ectocarpus siliculosus; Carpomitra costata; Coccophora langsdorfii, Asterocladon rhodochortonoides; Choristocarpus tenellus; Asteronema ferruginea, *Cladosiphon okamuranus* and *Tilopteris mertensii* as well as the red microalga Porphyridium purpureum, a marine bacterium Tamlana fucoidanivorans and the alpha proteobacteria Pseudooceanicola algae. The software programme Peptide Ranker (http://distilldeep.ucd.ie/PeptideRanker/, accessed on 10 December 2022) [30] identified peptides with potential bioactivities. Ten peptides including peptide IGNNPAKGGLF corresponding to amino acid peptide sequence f(315–326) of protein with accession number UniProtKB_Q1XDG4 (PBSS_NCOYE) derived from *Neopyriopia yezoensis* and peptide YIGNNPAKGGLF corresponding to f(314–326) of a protein with accession number UniProtKB_P51322 (PSBB_PORPU) from *Porphyra purpurea* were identified. Peptide DAALDFGPAL derived from the protein OX = 1537215 UniProt KB-A0A4185KT7_9RHOB and peptide AFYDYIGNNPAKGGLF from protein UniProtKB-Q1XDG4 (PSBB_NEOYE), and following peptides, SDGKIFDPL (UniProtKB_A0A6H5TY18 (A0A6H5J418_9PHAE); QGRVPGDIGFDPL (UniProtKB-A0A6HSJUW7_9PHAE); SMSGHPGAPM (UniProtKB_10A6H5L712_9PHAE); SEFIGFPIK (Uni-ProtKB-A0H6H5L026_9PHAE); and the final peptide GDFGNKDGKLTF (Uni-ProtKB-D8LG03) are all listed in Table 1, were identified. Identified peptides varied in length from 9–16 amino acids and had Peptide Ranker scores ranging from 0.64–0.82 (Table 1).
## 2.1.1. Peptide Ranker
Peptide Ranker (http://distilldeep.ucd.ie/PeptideRanker/, accessed on 24 November 2022) is an open source software resource, which can be used to predict the potential bioactivity of peptides based on a novel N-to-1 neural network. Any user can submit peptides to Peptide Ranker, which will be returned to the user ranked by the probability that the peptide will be bioactive. It is important to note that this is not a prediction of the probability that the peptide has bioactivity [30].
Identified peptide IGNNPAKGGLF had a Peptide Ranker score of 0.82 which was the highest value obtained for any peptide identified using MS from the L. digitata 3 kDa permeate. This indicates that this peptide likely has bioactivity. Acceptable probability values for bioactivity are between 1.0–0.5. The peptide YIGNNPAKGGLF had a Peptide Ranker score of 0.81, indicating high potential bioactivity (Table 1). Peptides DAALDFGPAL and AFYDYIGNNPAKGGLF had Peptide ranker scores of 0.78. Peptide SDGKIFDPL had a score of 0.74 (Table 1).
## 2.1.2. BIOPEP
A search of the BIOPEP database (https://biochemia.uwm.edu.pl/biopep-uwm/, accessed on 10 December 2022) [46] determined the novelty of the peptides identified and shown in Table 1. Of the ten peptides analyzed and listed in Table 2, their amino acid sequences were not identified in previously published papers concerning seaweed proteins and bioactive peptides [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45].
## 2.1.3. Simulated Digestion Using Peptide Cutter
Peptide cutter software (http://web.expasy.org/peptide_cutter/, accessed on 10 December 2022) [47] was used to determine if the identified peptides could potentially survive GI digestion. Peptides shown in Table 1 underwent simulated digestion using the GI tract enzymes, pepsin (pH 1.3), trypsin, and chymotrypsin. All peptides were cleaved into shorter peptide fragments that in some instances had known bioactivities and are found in BIOPEP (Table 2). Simulated GI digestion of the 10 peptides shown in Table 1 produced smaller peptides such as the active peptide GGL (derived following GI simulated digestion from YIGNNPAKGGLF). GGL is an active fragment, is a known anti-microbial peptide found in BIOPEP and it also has alpha-glucosidase inhibitory activities seen previously in Iberian dry-cured ham [31]. Peptides associated with other bioactivities include DPP-IV inhibition for monopeptides I, L; ACE-1 inhibition for dipeptides GD, TF, DP [35,36,43,44,45]. The monopeptide F, is a hydrophobic aromatic, amino acid, and it is thought, to enhance anti-oxidant activity [31]. Peptide IGNNPAKGGLF was digested into 3 peptides with sequences of IGNNPAK; GG and F. When comparing the first two peptides sequences listed in Table 2, the monopeptide Y, was one of two differing peptides. This monopeptide, Y, is hydrophobic, an aromatic amino acid, with anti-oxidant and anti-microbial bioactivity [31,32,33].
Several bioactive peptides also result from simulated GI digestion of the peptide DAALDFGPAL. Following simulated GI digestion the peptides DAA and GPAL result. DAA is a known antimicrobial peptide sequence found in the peptide tenecin 1, an insect defensin peptide [32]. The dipeptide DY results from simulated digestion of AFYDYIGNNPAKGGLF. This dipeptide is a known ACE-1 inhibitory peptide [34].
Simulated GI digestion of peptide SDGKIFDPL produces peptides SDGK and DP. The dipeptide DP identified previously from the dark muscle of tuna is a known ACE-1 inhibitor that also has anti-hypertensive activity shown in rat studies previously [36].
The peptide QGR occurs following simulated GI digestion of QGRVPGDIGFDPL. This tripeptide has known anti-microbial activity [37]. The peptide PL results following simulated GI digestion of YDYIGNNPAKGGLF. This tripeptide has known anti-microbial activity, and PL is also an ACE-1 inhibitor [37,38].
## 2.1.4. Toxicity Assessment Using In Silico Analysis
All 130 peptides identified using MS were assessed for their potential to be toxic using ToxinPred (https://webs.iiitd.edu.in/raghava/toxinpred2/batch.html, accessed on 10 December 2022) [48]. Of the 130 peptides, tested results indicate that no peptides have potential toxicity.
## 2.1.5. Peptide Synthesis and ACE-1 Inhibition
The peptides IGNNPAKGGLF and YIGNNPAKGGLF were synthesized and assessed in vitro for their ability to inhibit ACE-1. The peptide IGNNPAKGGLF was found to inhibit ACE-1 by $80\%$ and YIGNNPAKGGLF inhibited ACE-1 by $91\%$ when assayed at a concentration of 1 mg/mL compared to the control Captopril® assayed at a concentration of 0.05 mg/mL. The ACE-1 IC50 values determined for both peptides were 174.4 µg/mL and 133.1 µg/mL for IGNNPAKGGLF and YIGNNPAKGGLF, respectively.
## 3. Discussion
Ten different peptide sequences were identified from the L. digitata protein 3 kDa permeate using MS. The ACE-1 inhibitory activity of two of these peptides was confirmed using chemical synthesis and assessment in vitro for ACE-1 inhibition. Additionally, other bioactivities were predicted using in silico methods. The MS-sequenced peptides ranged in length from 9–15 amino acids. All identified peptides were novel based on a search of the BIOPEP database and the literature. Peptide Ranker values were obtained for all peptides and the peptides likely to have bioactivities are shown in Table 1. These peptides had Peptide Ranker values greater than 0.5.
Two peptides, with Peptide Ranker scores of 0.82 and 0.81 were selected for chemical synthesis. ACE-1 inhibition values were determined in vitro for these peptides with amino acid sequences IGNNPAKGGLF and YIGNNPAKGGLF. ACE-1 and IC50 results for these synthesized peptides were obtained. Peptide IGNNPAKGGLF inhibited ACE-1 by $80\%$ and YIHNNPAKGGLF inhibited ACE-1 by $91\%$ when assayed at 1 mg/mL. The ACE-1 IC50 value for IGNNPAKGGLF was 174.4 µg/mL (0.161 µM) ACE-1. Peptide YIGNNPAKGGLF had an IC50 value of 133.1 µg/mL (0.11 µM) compared to Captopril© with a documented ACE-1 IC50 value of 500 µg/mL (2.3 µM) [8]. Previous studies on marine cryptides, used Captopril© as a positive control with IC50 values of (1.79–15.1 nM) for ACE-1, and another drug Losartan was used as a negative control for ACE-II inhibition, and had IC50 values of (17.13–146 μM) [49]. The IC50 for Captopril© varies depending on application and extraction methods used, with an IC50 of 7.09 nM from visible spectrophotometric (VSP) and for high-performance liquid chromatography (HPLC), and an IC50 of 4.94 nM [50]. Common hypertensive drugs, using the ACE-1 mechanism of control include Captopril©, Enalapril, Tekturna and Rasilez [51].
Peptides with ACE-1 IC50 values ranging from 2.42–20.63 µM [52] were identified from protein hydrolysates generated from *Laminaria japonica* previously. The IC50 values obtained for our synthesized peptides are greater than ACE-1 IC50 values reported previously for peptides such as HR, extracted from a bovine hydrolysate with an ACE-1 IC50 of 0.19 mM [51]. The ACE-1 inhibitory activity of the synthesized peptides is greater than the value reported for the L. digitata hydrolysate and shows the potential of these peptides for potential use in the treatment of hypertension.
Simulated GI digestion increased the potential bioactivities of identified peptides and several peptides with alpha-glucosidase and anti-microbial activities were found. Inhibition of alpha-glucosidase reduces carbohydrate digestion, consequently decreasing carbohydrate content in blood, which improves human health outcomes regarding type 2 diabetes [31,53]. The dipeptide sequence SE, cleaved from the novel peptide SEFIGFPIK (shown in Table 2), has potential stimulating vasoactive substance release bioactivity, discovered in peptides sourced from casein and soy protein previously [43,53]. The anti-inflammatory peptide sequence IGF also results from the GI digestion of SEFIGFPIK. This tripeptide is found in the pepsin hydrolysis of hempseed protein [42]. The peptide GNK that is cleaved from sequenced peptide GDFGNKDGKLTF is found in the Arietin peptide-A known as Fibrinogen interaction inhibitor. The dipeptide TF is also cleaved from the same sequenced peptide and is a known ACE-1 inhibitor [43,44,45].
This work identified two novel ACE-1 inhibitory peptides with pharmaceutically relevant ACE-1 IC50 values. In addition, the array of bioactive peptides that result following simulated GI digestion demonstrates the potential bioactivities still to be harnessed from brown seaweed proteins in L. digitata.
Additional bioactivities were also identified from cryptides identified following simulated gastrointestinal (GI) digestion. These bioactivities included Dipeptidyl peptidase IV (DPP-IV) inhibition potential for peptide sequences SDGK and alpha-glucosidase inhibition potential of peptides GGL and IGNNPAK. Future work will involve the synthesis of these peptides and determination of their in vitro inhibitory activities as well as the determination of their relevant IC50 values. Inhibitors of DPP-IV and alpha-glucosidase enzymes are the key targets for the pharmaceutical sector for development of drugs to prevent or to control type 2 diabetes [T2D].
## 4.1. Mass Spectrophotometry (MS) Characterisation of 3kDa Permeates
Protein extraction and peptide enrichment using molecular weight cut-off (MWCO) filtration was performed prior to MS characterisation in accordance with the method outlined in [8].
Peptide fractions were prepared for MS characterisation using the Phoenix peptide clean-up kit 4X, manufactured by Peromics and following the clean-up method supplied by the manufacturer. Peptides were identified using a mass spectrometer nanoESI qQTOF (6600 plus TripleTOF, AB SCIEX, Framingham, MA, U.S.A.) using liquid chromatography and tandem mass spectrometry (LC–MS/MS). A total of 1 μL of microalgal permeate was loaded onto a trap column (3 μ C18-CL 120 Ᾰ, 350 μM × 0.5 mm; Eksigent) and desalted with $0.1\%$ TFA (trifluoroacetic acid) at 5 μL/min for 5 min. The peptides were then loaded onto an analytical column (3 μ C18-CL 120 Ᾰ, 0.075 × 150 mm; Eksigent) equilibrated in $5\%$ acetonitrile $0.1\%$ FA (formic acid). Elution was carried out with a linear gradient from 7 to $45\%$ B in A for 20 min, where solvent A was $0.1\%$ FA and solvent B was ACN (acetonitrile) with $0.1\%$ FA at a flow rate of 300 nL/min. The sample was ionized in an electrospray source Optiflow < 1 μL Nano applying 3.0 kV to the spray emitter at 200 °C. Analysis was carried out in a data-dependent mode. Survey MS1 scans were acquired from 350 to 1400 m/z for 250 ms. The quadrupole resolution was set to ‘LOW’ for MS2 experiments, which were acquired from 100 to 1500 m/z for 25 ms in ‘high sensitivity’ mode. Up to 50 ions were selected for fragmentation after each survey 400 scan. Dynamic exclusion was set to 15 s. The system sensitivity was controlled by analyz-401 ing 500 ng of K562 protein extract digest (SCIEX); in these conditions, 2260 proteins were identified (FDR < $1\%$) in a 45 min gradient. Peptides identified as having potential bioactivities were chemically synthesised by GenScript Biotech (Leiden, The Netherlands). GenScript also verified the purity of the peptides by analytical RP-HPLC–MS.
## 4.2. In Silico Analysis of MS Sequenced Peptides
Peptide Ranker was used to predict the bioactivity of peptide sequences and values of between 0.5 and 1 were taken as indicative of peptides having bioactivity.
Figure 1 shows the six steps used during in silico analysis. Of the 130 peptides identified using MS, only those with >$95\%$ confidence were selected for synthesis and in silico analysis. Selected peptides were input into the software programme Peptide Ranker (http://distilldeep.ucd.ie/PeptideRanker/, accessed on 15 December 2022). A value indicative of potential bioactivity was obtained for each peptide. Only peptides with Peptide Ranker scores greater than 0.5 were used in further analysis. Ten peptide sequences were identified as having potential bioactivities. The novelty of these peptides was determined following a search in the peptide database BIOPEP (http://www.uwm.edu.pl/biochemia/index.php/pl/biopep, accessed on 12 December 2022). Active peptides were further assessed for their ability to survive simulated GI digestion using Expasy peptide cutter (http://web.expasy.org/peptide_cutter/, accessed on 10 December 2022). The UniProt database was used to identify proteins containing the peptide sequences. Additionally, the potential toxicity of identified peptides was assessed using the software programme ToxinPred (https://webs.iiitd.edu.in/raghava/toxinpred2/batch.html, accessed on 10 December 2022).
## 4.3. ACE-1 Inhibitory Activity Assessment
The peptides with the highest Peptide Ranker scores IGNNPAKGGLF, with a peptide ranker value of 0.82, and YIGNNPAKGGLF, with a value of 0.81,were selected for synthesis. Once made, peptides were re-tested using in vitro screening assays. ACE-1 activity was tested using an assay kit supplied by Cambridge BioSciences (Cambridge, UK) as described previously. Captopril© (a known ACE-1 inhibitor) dissolved in distilled water was used as a positive control.
## 5. Conclusions
In silico and in vitro methods are useful tools for selection of enzymes to generate bioactive peptides from protein containing biomass. Moreover, they are useful to determine potential bioactivities of peptides prior to chemical synthesis and can save time and money prior to animal studies to determine potential health benefits. A combination of these methods was used previously to identify and confirm the bioactivity of peptides derived from blood proteins [51] and microalgae previously [54]. However, limitations of this approach exist and specifically include limits concerning the folding of protein, which has an impact on how enzymes cut the protein and which in turn can impact production of the resulting peptides. One of the main barriers for entering the human functional foods market is unknown and unstable peptide product qualities. It is required to have analytical methods for characterising the peptide fraction. Today, research groups are using Fourier-transform Infrared (FTIR) fingerprints to gain new insight in quality variations of peptide products. These fingerprints can be related to raw material composition and processing factors [55]. The method used in this study has advantages over in vitro only methods as it can help to predict the best enzymes to use to generate bioactive peptide containing hydrolysates and additionally can predict the most bioactive peptides and those that may be toxic before any in vitro assays are performed.
Two novel ACE-1 inhibitory peptides with amino acid sequences corresponding to IGNNPAKGGLF and YIGNNPAKGGLF were identified from a 3 kDa permeate of a protein hydrolysate generated from the brown seaweed L. digitata. In silico methods also predicted the potential of this seaweed as a source of novel, bioactive peptides that may impart additional health benefits to the consumer including prevention of T2D and antimicrobial activities following GI digestion. Identified, chemically synthesized peptides had ACE-1 inhibition IC50 values of 174.4 µg/mL (0.161 µM) for peptide IGNNPAKGGLF and 133.1 µg/mL (0.107 µM) for peptide YIGNNPAKGGLF and both peptides were similar in terms of bioactivity to other ACE-1 inhibitory peptides identified from tuna and meat muscle previously. This study highlights the potential bioactivity of this brown seaweed. However, future work is required to confirm an anti-hypertensive effect of the seaweed hydrolysate and synthesized peptides in vivo. This work will involve assessment of the L. digitata hydrolysate and synthesized peptides in spontaneously hypertensive rats (SHRs) to assess if the ACE-1 inhibitory peptides have an anti-hypertensive effect in vivo.
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|
---
title: Investigation of the Effects of Stress Hyperglycemia Ratio and Preoperative
Computed Tomographic Angiography on the Occurrence of Acute Kidney Injury in Diabetic
Patients following Surgical Thromboembolectomy
authors:
- Orhan Guvenc
- Mesut Engin
- Filiz Ata
- Senol Yavuz
journal: Tomography
year: 2023
pmcid: PMC9967571
doi: 10.3390/tomography9010020
license: CC BY 4.0
---
# Investigation of the Effects of Stress Hyperglycemia Ratio and Preoperative Computed Tomographic Angiography on the Occurrence of Acute Kidney Injury in Diabetic Patients following Surgical Thromboembolectomy
## Abstract
Acute lower extremity ischemia (ALI) is a cardiovascular emergency resulting from embolic and thrombotic causes. Although endovascular techniques have advanced, surgical thromboembolectomy is still the gold standard. Emergency thromboembolectomy surgery involves an ischemia-reperfusion injury, which also poses a risk for acute renal injury (AKI). The stress hyperglycemia rate (SHR) has recently emerged as an important prognostic value in emergency cardiovascular events. In the present study, we aimed to analyze the impact of preoperative contrast-enhanced tomographic angiography (CTA) and the SHR value on postoperative AKI in emergency thromboembolectomy procedures in patients with insulin-dependent diabetes mellitus (DM). In this retrospective analysis, patients with DM who received emergency surgical thromboembolectomy after being hospitalized at our hospital with ALI between 20 October 2015, and 10 September 2022, were included. Patients were classified into two groups: Group 1 ($$n = 159$$), who did not develop AKI, and Group 2 ($$n = 45$$), who did. The 45 patients in Group 2 and the 159 patients in Group 1 had median ages of 59 (39–90) and 66 (37–93), respectively ($$p \leq 0.008$$). The percentage of patients in Group 2 with Rutherford class IIB and admission times longer than 6 h was higher ($$p \leq 0.003$$, $$p \leq 0.027$$, respectively). To determine the variables affecting AKI after surgical embolectomy procedures, multivariate logistic regression analysis was used. In multivariate analysis Model 1, age > 65 years (odds ratio [OR]: 1.425, $95\%$ confidence interval [CI]: 1.230–1.980, $p \leq 0.001$), preoperative high creatinine (OR: 4.194, $95\%$ CI: 2.890–6.156, $$p \leq 0.003$$), and Rutherford class (OR: 0.874, $95\%$ CI: 0.692–0.990, $$p \leq 0.036$$) were determined as independent predictors for AKI. In Model 2, age > 65 years (OR: 1.224 CI: 1.090–1.679, $$p \leq 0.014$$), preoperative high creatinine (OR: 3.975, $95\%$ CI: 2.660–5.486, $$p \leq 0.007$$), and SHR (OR: 2.142, CI: 1.134–3.968, $$p \leq 0.003$$), were determined as independent predictors for amputation. In conclusion, when an emergency thromboembolectomy operation is planned in insulin-dependent DM patients, renal risky groups can be identified, and renal protective measures can be taken. In addition, to reduce the renal risk, according to the suitability of the clinical conditions of the patients, the decision to perform a CTA with contrast can be taken by looking at the SHR value.
## 1. Introduction
Acute lower extremity ischemia (ALI) is a cardiovascular emergency resulting from embolic and thrombotic causes. The diagnosis of acute extremity ischemia can be easily reached with a physical examination and a detailed anamnesis. According to the results of physical examination and Doppler ultrasonography, these patients can be operated on without angiography before ischemia [1]. When these patients are diagnosed, surgical or endovascular procedures should be scheduled immediately. Although endovascular techniques have advanced, surgical thromboembolectomy is still the gold standard [2].
Emergency thromboembolectomy surgery involves an ischemia-reperfusion injury, which also poses a risk for acute renal injury (AKI). In addition, the administration of iodinated contrast material before surgery may also pose a risk for renal damage. In one study, it was shown that angiography increases the risk of renal damage in emergency trauma patients [3]. In another study, it was concluded that the time of angiography before coronary bypass did not affect postoperative renal failure in diabetic patients [4].
The stress hyperglycemia rate (SHR) has recently emerged as an important prognostic value in emergency cardiovascular events [5]. Studies have shown that the blood glucose (ABG) value alone after coronary interventions is predictive for the risk of renal damage after the procedure in patients without DM [6]. Therefore, it was thought that SHR value might be more predictive in DM patients. In a study conducted in this direction, it was shown that the SHR value calculated before coronary intervention in patients with acute myocardial infarction was a good predictor of postprocedural AKI [7].
In the present study, we aimed to analyze the impact of preoperative contrast-enhanced tomographic angiography (CTA) and the SHR value, which was calculated at the time of admission, on postoperative AKI in emergency thromboembolectomy procedures in patients with insulin-dependent diabetes mellitus (DM).
## 2. Materials and Methods
In this retrospective analysis, patients with DM who received emergency surgical thromboembolectomy after being hospitalized at our hospital with ALI between 20 October 2015 and 10 September 2022, were included. The hospital registry system and patient files were used to gather the patient data. All patients’ demographic information, blood counts on admission, and postoperative problems were noted. Ultimately, after the exclusion criteria were met, 204 consecutive patients were enrolled in the research (Figure 1). After these procedures, patients were classified into two groups: Group 1 ($$n = 159$$), who did not develop AKI, and Group 2 ($$n = 45$$), who did.
## 2.1. Diagnosis and Treatment Strategy of ALI
A detailed history is taken, and a physical examination is performed on each patient who applies to our emergency department with a suspected ALI clinic. Doppler ultrasonography is also used to support the suspicion of ALI. As a result of these examinations, the diagnosis of ALI can be made, and surgical intervention can be planned [8]. However, there are also suggestions that surgery after CTA is beneficial by showing the thrombus location and arterial structure more objectively [9]. In our clinic, the rate of using CT imaging in patients with suspected ALI has increased approximately four times in the last four years.
After diagnosis, all patients were urgently hospitalized in our intensive care unit and taken into surgery. Local anesthetic and mild sedation were used during every procedure. After a linear incision in the femoral region, the common femoral, superficial femoral, and profunda femoral arteries were turned and suspended. After the arteriotomy to the common femoral artery, an embolectomy was performed with a Fogarty catheter (3–7 French). The procedure was continued until the thrombus material stopped coming forth, and the arteriotomy was primarily repaired when adequate distal and proximal flow was achieved. After the surgery, for at least one day, every patient was monitored in the intensive care unit under close monitoring. During this period, hourly heart rate examinations were performed. In medical treatments, after the heparin infusion (The activated clotting time stayed constant at 200–250 s) on the first day, a low molecular weight heparin (1 mg/kg, sc) treatment was applied for at least one week. In addition to these treatments, 100 mg/day of acetylsalicylic acid and clopidogrel 75 mg/day were given after the first day. In some patients, a re-embolectomy was determined according to the pulse findings in their close follow-up (a total of 12 patients).
## 2.2. Calculation of SHR
Blood samples drawn from peripheral venous structures during hospitalization were used to determine the blood parameters for each patient. The next step was to acquire SHR using the following formula [5]:[1]SHR=Admission blood glucose levels mg/dL28.7x glycosylared hemoglobin %−46.7
## 2.3. Diagnosis of AKI
In the postoperative period, creatinine assessments were performed for three days in all patients. The postoperative renal injury will be performed according to the Kidney Disease Improving Global Outcomes (KDIGO) classification [10].
Three categories are used to group this information: Stage 1: 1.5–1.9 times the baseline value or a rise of more than 0.3 mg/dL. Urine volume < 0.5 mL/kg/h for 6–12 h.
Stage 2: 2.0–2.9 times the initial value. Urine volume < 0.5 mL/kg/h for >12 h.
Stage 3: Three-fold rise from baseline, serum creatinine > 4.0 mg/dL, or the start of renal replacement treatment. Urine volume < 0.3 mL/kg/h for >24 h or anuria for >12 h.
## 2.4. Statistical Analysis
All data were evaluated using the SPSS program (IBM Corp., 2012, IBM SPSS Statistics for Windows, Version 21.0, Armonk, NY, USA: IBM Corp.). For categorical data, percentage and frequency values were determined; for continuous data, mean, standard deviation (SD), and median (minimum-maximum) values were computed. The Kolmogorov-Smirnov and Shapiro-Wilk tests were used to assess the distribution’s normality. Data that were not normally distributed were evaluated using the Mann-Whitney U test and the Student’s t-test, respectively. Nominal data were subjected to frequency and percentage analysis before the Chi-square test was used to compare them. To identify the predictors of postoperative renal injury, univariate logistic regression analysis was first performed. The multivariate logistic regression analysis included variables whose p-value fell below 0.25 in these assessments. Multivariate logistic regression analysis was carried out in two separate models; the model with the ABG value and the model with the SHR value. For the purpose of forecasting AKI, receiver-operating characteristic (ROC) curve analysis for ABG and SHR was carried out, and areas under the curve (AUC) were computed. The statistical significance of test results was defined as $p \leq 0.05.$
## 3. Results
Some 204 consecutive patients with insulin-dependent DM were included in the study. All patients underwent emergency surgical thromboembolectomy surgeries. The 45 patients in Group 2 and the 159 patients in Group 1 had median ages of 59 (39–90) and 66 (37–93), respectively ($$p \leq 0.008$$). The two groups shared similar characteristics with regard to the history of past cerebrovascular events, gender, hypertension, hyperlipidemia, rates of coronary artery disease and peripheral arterial disease, body mass index, and current smoking rates. The percentage of patients in Group 2 with Rutherford class IIB and admission times longer than 6 h was higher ($$p \leq 0.003$$, $$p \leq 0.027$$, respectively). Patients in the two groups also had similar vascular thrombus areas (Table 1).
White blood cell, platelet, hematocrit, urea, albumin, HbA1c, and eAG levels did not significantly differ across the groups. ABG and SHR were considerably greater in Group 2 than in Group 1 ($$p \leq 0.017$$ and P0.001, respectively). Re-embolectomy (first 24 h) rates ($3.1\%$ versus $15.6\%$) and preoperative CTA usage rates ($52.2\%$ versus $71.1\%$) were also significantly higher in Group 2 ($$p \leq 0.002$$, $$p \leq 0.024$$, respectively) (Table 2).
The correlation between CTA use and AKI was examined using subgroup analysis. According to the research, only Stage 1 AKI ($$p \leq 0.015$$) is correlated with the usage of CTA (Table 3).
To determine the variables affecting AKI after surgical embolectomy procedures, multivariate logistic regression analysis was used (Table 4). In multivariate analysis Model 1, age > 65 years (odds ratio [OR]: 1.425, $95\%$ confidence interval [CI]: 1.230–1.980, $p \leq 0.001$), preoperative high creatinine (OR: 4.194, $95\%$ CI: 2.890–6.156, $$p \leq 0.003$$), and Rutherford class (OR: 0.874, $95\%$ CI: 0.692–0.990, $$p \leq 0.036$$) were determined as independent predictors for AKI. In Model 2, age > 65 years (OR: 1.224 CI: 1.090–1.679, $$p \leq 0.014$$), preoperative high creatinine (OR: 3.975, $95\%$ CI: 2.660–5.486, $$p \leq 0.007$$), and SHR (OR: 2.142, CI: 1.134–3.968, $$p \leq 0.003$$), were determined as independent predictors for amputation.
The effectiveness of ABG and SHR in predicting AKI following surgical thromboembolectomy procedures was assessed using ROC analysis. The cut-off value of ABG was 265 (AUC: 0.763, $95\%$ CI: 0.680–0.846, $p \leq 0.001$, with $78.4\%$ sensitivity and $56.7\%$ specificity), and that of SHR was 1.89 (AUC: 0.849, $95\%$ CI: 0.790–0.908, $p \leq 0.001$, with $86.4\%$ sensitivity, $61.6\%$ specificity) (Figure 2)
## 4. Discussion
ALI is an important clinical condition with mortal and morbid consequences, and surgery should be performed urgently on patients that are deemed to require it. Although these patients can be operated on after physical examination and DUSG findings, the use of CTA/conventional angiography has now become widespread. In the present study, we demonstrated that preoperative use of CTA in insulin-dependent DM patients increases the risk of postoperative AKI. However, we also showed that this increased risk was significant exclusively in Stage 1 AKI. In addition, we recently found that SHR, which is a valuable prognostic parameter in acute clinical conditions, is an independent predictor of the development of AKI after surgical thromboembolectomy.
On the impact of employing imaging techniques that require contrast agents before interventional surgeries, numerous research has been carried out. What causes conflict-induced AKI is not entirely understood. It has been suggested that several different systems must interact for AKI to occur. Among these mechanisms, it is commonly acknowledged that toxic effects on the tubular cells and a decrease in renal perfusion brought on by the direct action of contrast agents on the kidney are significant. The pathophysiological significance of the contrast agent’s direct actions on tubular cells, as well as the other hypothesized causes [11]. In a study by Yamamoto et al., including a large patient population, the effect of imaging with contrast agents on the development of AKI in emergency trauma patients was investigated. As a result of the analyses performed in this study, it was revealed that performing angiography in the emergency department doubled the risk of AKI [3]. In another study conducted by Doğan et al., patients with DM who underwent coronary artery bypass graft (CABG) operation were included. In this study, which included 421 patients retrospectively, the effect of CABG surgery timing after the coronary angiography on AKI was investigated. The patients were split into three groups. According to the moment, the CABG operation after coronary angiography (zero-three days, four-seven days, and >seven days) was performed. In this study, the authors did not find a significant relationship between angiography time and the development of AKI [4]. In our study, we investigated the effect of preoperative CTA on postoperative AKI in patients with DM who underwent emergency thromboembolectomy. By performing subgroup analysis, we also showed that Stage 1, 2, and 3 AKI development rates were high in patients who underwent preoperative CTA, but only the Stage 1 AKI development rate was statistically high.
Hyperglycemia occurs as an endocrine and metabolic response to acutely developing clinical conditions. This situation is detected at a rate of up to $30\%$ in the hospitalized patient population, and this rate increases in elderly patients and patients with DM [12,13]. This condition, which occurs in response to acute events, increases oxidative stress and free radical production and leads to endothelial, vascular, and immune dysfunction [14]. In a study that included patients with DM with acute myocardial infarction (AMI), it was revealed that a high ABG value increased the risk of AKI [7]. In another study, it was revealed that hyperglycemia after coronary angiography increased the risk of AKI after the procedure [15]. In a study by Gorelik et al., the effect of ABG value on AKI in hospitalized patients was investigated. A significant relationship was shown between high ABG at admission and AKI and mortality in nondiabetic patients, and the authors concluded that this relationship decreased in DM patients [16]. In our study, the ABG value was higher in patients with AKI, nevertheless; multivariate analysis did not show that it was an independent predictor.
The ABG value is an important parameter as an indicator of the response to acute events in patients without DM. In a study conducted on intensive care patients, the SHR value was shown to be most useful in predicting poor outcomes in DM patients [17]. For this reason, studies investigating the predictive value of SHR value in DM patients have been conducted in the cardiovascular field. Accordingly, in a study conducted by Marenzi et al., the effect of acute and chronic glycemic status on AKI in AMI patients was investigated. This study included 474 consecutive diabetic AMI patients and showed that the SHR value was more reliable in predicting the risk of AKI than the ABG value alone [6]. In a study conducted by Ramon et al., 91 COVID-19 patients with DM who were hospitalized were included. The primary endpoints of the study were defined as the need for intensive care, the need for a mechanical ventilator, and mortality. Thirty-five ($38.4\%$) patients had a primary outcome and in the analysis performed, a significant relationship was revealed between the primary outcome and the SHR value (hazard ratio: 1.57 $95\%$ CI 1.14–2.15, $$p \leq 0.005$$) [18]. In a study by Gao et al., the effect of SHR value on postprocedural AKI in AMI patients with DM was investigated. As a result of the multivariate analysis performed in this study, the SHR value was shown as an independent forecaster in predicting the risk of AKI (OR: 3.18, $95\%$ CI: 1.99–5.09, $p \leq 0.001$) [7].
The Rutherford ALI classification is examined under four main headings according to the severity of ischemia (I, IIA, IIB, and III) [19]. In our study, we excluded patients who did not require emergency intervention (Rutherford I) and those with irreversible damage (Rutherford III). In the multivariate analysis Model 1 utilized in our study, we revealed that the severity of ischemia (Rutherford IIB versus IIA) increases the risk of postoperative AKI. As a result, the severity of ischemia may increase the risk of AKI, as it will increase oxidative stress due to ischemia-reperfusion [20]. In our study, being over the age of 65 was also shown as an independent predictor of AKI risk in both multivariate analysis models. Fibrosis in cardiovascular structures increases with increasing age [21], and this fact may also increase the risk of AKI [22].
Although our study reached important results, there are also some limitations. First, we included a limited population of insulin-dependent DM patients. In addition, we conducted a single-center study which was planned retrospectively. However, we believe that our study will be a source for future multicenter prospective studies.
## 5. Conclusions
Acute limb ischemia is an important clinical condition that can lead to the loss of limbs as well as involve vital risks. AKI that occurs after these surgeries is also an important problem, as in many diseases. Our study showed that preoperative use of CTA can increase the risk of Stage 1 AKI in insulin-dependent DM patients. In addition, we showed the SHR value calculated from the blood values at the time of admission as an independent predictor of the development of AKI. Accordingly, when an emergency thromboembolectomy operation is planned in insulin-dependent DM patients, renal risky groups can be identified, and renal protective measures can be taken. In addition, to reduce the renal risk, according to the suitability of the clinical conditions of the patients, the decision to perform a CTA with contrast can be taken by looking at the SHR value. The findings of our study require to be supported by prospective randomized controlled studies.
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---
title: Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites
in Brain
authors:
- Sungtak Hong
- Jun Shen
journal: Metabolites
year: 2023
pmcid: PMC9967573
doi: 10.3390/metabo13020211
license: CC BY 4.0
---
# Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites in Brain
## Abstract
Spectral correlations between metabolites in 31P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between 31P-containing metabolites arising from spectral overlap, and their downfield correlations are markedly altered by the background spectral baseline. Overall, the spectral correlations between 31P-containing metabolites are markedly reduced at 7 Tesla with the increased chemical shift dispersion and the decreased membrane phospholipid signal. The findings provide the quantitative landscape of pre-existing correlations in 31P MRS spectra due to overlapping signals. Detailed procedures for quantifying the pre-existing correlations between 31P-containing metabolites are presented to facilitate incorporation of spectral correlations into statistical modeling in clinical correlation studies.
## 1. Introduction
Phosphorous (31P) magnetic resonance spectroscopy (MRS) is an important technique enabling noninvasive assessment of many aspects of bioenergetics and metabolism in vivo [1]. 31P MRS has been widely used to study numerous diseases such as Parkinson’s disease [2], tumor [3], diabetes [4], stroke [5], hepatobiliary disease [6], and neuromuscular disorders [7]. In many clinical applications of 31P MRS, metabolite signals such as adenosine triphosphate (ATP), phosphocreatine (PCr), inorganic phosphate (Pi), and phosphoesters are measured in vivo and then correlated with clinical metrics such as disease severity and/or treatment. For example, the duration of illness was shown to be correlated with phosphoesters in patients with Wilson’s disease [8]. The phosphoesters were also found to correlate with the time of transplantation in kidney transplant patients [9]. Phosphocreatine levels in the brain were found to be reduced in cerebral creatine deficiency caused by guanidinoacetate methyltransferase deficiency [10]. After treatment by oral creatine supplementation, brain PCr level was restored [10].
At 3 Tesla or lower magnetic field strengths, there is severe spectral overlap between ATP and nicotinamide adenine dinucleotide (NAD) and among the signals downfield from PCr, which are phosphocholine (PC), glycerophosphocholine (GPC), intra- and extracellular inorganic phosphate (Piin, Piex), phosphoethanolamine (PE), and glycerophosphoethanolamine (GPE) [11]. In particular, the signals from macromolecule membrane phospholipids (MP) are highly prominent at low magnetic fields [12], overlapping with the downfield signals. At the high magnetic field strength of 7 Tesla, spectral overlap between 31P-containing metabolites is greatly reduced, as it is aided by the increased chemical shift dispersion and the large decrease in the signal intensity of MP. However, even at 7 Tesla, there is still severe spectral overlap among ATP, NAD, and uridine diphosphate glucose (UDPG) [11].
In the clinical 31P MRS literature, concentrations of 31P-contaning metabolites measured by 31P MRS have been treated as statistically independent variables in their correlations with clinical metrics. However, spectral overlap can present as an intervening variable that may unfortunately reduce the likelihood of the intended statistical precision and extrapolation of the clinical findings under investigation, unless correlations of metabolites can be parsed correctly [13,14]. When two peaks of the same polarity overlap each other, overdetermination (underdetermination) of one peak is correlated with the underdetermination (overdetermination) of the other, leading to a negative correlation between the two signals [13]. To the best of our knowledge, correlations originating from spectral overlap have not been taken into account in clinical MRS studies, including clinical studies using 31P MRS, although these spectral correlations may confound correlations of biological origins.
Monte *Carlo analysis* has been a standard tool to quantify correlations [13]. In this study, we use numerical Monte Carlo simulations to investigate and quantify spectral correlations between 31P-containing brain metabolites in the absence of any influence from biological correlations. To evaluate the effect of magnetic field strength on these spectral correlations, in vivo 31P MRS data measured at both 3 and 7 Tesla were analyzed. Highly significant spectral correlations were found between the oxidized and reduced forms of NAD at both 3 and 7 Tesla. Significant correlations were also found between many downfield 31P MRS signals, especially at 3 Tesla. In addition, although the background spectral baseline has little effect on correlations between the upfield signals, it plays a major role in downfield correlations. The complexity of the spectral correlations between 31P-containing metabolites underscores the importance of quantifying these correlations and incorporating them in statistical modeling of the correlations between overlapping 31P-containing metabolites and clinical metrics.
## 2.1. In Vivo 31P MRS Data
Ten in vivo 31P MRS datasets, which were acquired from five healthy participants (mean age 26.8 ± standard deviation 7.7 years) at 3 Tesla and five healthy participants (age 33.5 ± 10.3 years) at 7 Tesla [11], were analyzed in this study. The data acquisition procedures have been described previously [11]. Briefly, MRS measurements were performed on Siemens Skyra 3 Tesla and Magnetom 7 Tesla scanners (Siemens Healthcare, Erlangen, Germany) using home-built coil assemblies composed of a circular 31P coil with a 7.0 cm diameter and a quadrature half-volume 1H coil. In vivo 31P MRS spectra were acquired without 1H decoupling. Acquisition parameters at 3 Tesla were as follows: TR = 2 s; spectral width = 5 kHz; number of acquisitions = 128; number of data points = 1024. Identical parameters were used for 7 *Tesla data* acquisition, except that TR = 3 s.
## 2.2. In Vivo Data Processing and Quantification
Identical data processing procedures were used for MRS data acquired at both field strengths. The first two data points in FID were set to zero to suppress the baseline in the 31P MRS spectrum [15]. Subsequently, zero-filling, 1-Hz exponential line-broadening, Fourier transform, zero- and first-order phase corrections, and chemical shift referencing (by setting PCr to 0 ppm) were performed.
All spectra were quantified using an in-house-developed fitting program [16] implementing the linear combination model (LCM)-fitting algorithm [17]. Basis data, a prerequisite for LCM fitting, were generated with density matrix simulations [18]. The following 12 metabolites covering the spectral region between −20 to 10 ppm were included in the spectral model: PCr, ATP, the oxidized form of NAD (NAD+), the reduced form of NAD (NADH), UDPG, GPC, GPE, Piex, Piin, PC, PE, and MP. Both chemical shifts and coupling constants, which must be priorly known for density matrix simulation, were taken from the literature [19,20]. Due to the low sensitivity at 3 Tesla, UDPG was included only in the basis data of 7 Tesla. During the spectral fitting, the linewidths of NAD+ and NADH were constrained to the linewidth of α-ATP minus 1.5 Hz [21]. The background spectral baseline was modeled using a polynomial. The whole spectral region which covered −20 to 10 ppm was quantified at both field strengths. For calculating metabolite concentrations, total ATP (the sum of α-, β-, and γ-ATP) was used as an internal reference, and it was assumed to be 9 mM [22].
## 2.3. Monte Carlo Analysis of In Vivo Spectra
The first Monte *Carlo analysis* was performed to investigate the effects of field strengths and the background spectral baseline on metabolite–metabolite correlations. For each participant, two different datasets composed of metabolites only and metabolite + baseline were generated using fitted individual metabolites and the background spectral baseline derived from LCM fitting. Subsequently, random noise at the same level derived from the corresponding in vivo spectrum was added. A separate dataset excluding the spectral baseline was also generated using the same procedure to investigate the influence of the background spectral baseline on metabolite–metabolite correlations. For each dataset, 2000 different noise realizations were used, resulting in a total of 40,000 spectra (=2 field strengths × 5 participants × 2 baseline options × 2000 noise realizations).
The second Monte *Carlo analysis* was performed to investigate the effects of linewidth on metabolite–metabolite correlations at different field strengths. The mean linewidth and amplitude of each metabolite and the mean spectral baseline extracted from the LCM fitting of all participants were used to generate a noiseless synthetic spectrum for each field strength. For 3 Tesla, three different line-broadening factors of 0, 4, and 8 Hz were used to study the effect of linewidth variations. For 7 Tesla, the line-broadening factors were 0, 10, and 20 Hz. A separate dataset that excluded the spectral baseline was also generated for each field strength using the same procedure to investigate the influence of the spectral baseline on metabolite–metabolite correlations. For each dataset, random noise with 2000 different noise realizations at the corresponding mean in vivo noise level was added to each synthetic spectrum. A total of 24,000 spectra (=2 field strengths × 3 different line-broadening factors × 2 baseline options × 2000 noise realizations) were generated. All 24,000 spectra were quantified using the same LCM fitting procedure as described in Section 2.2.
## 2.4. Correlation Analysis
Pearson’s cross-correlation coefficients between pairs of 31P-containing metabolites + MP were calculated using the fitted concentrations of individual signals derived from Monte Carlo analysis. Then, the Pearson’s cross-correlation coefficients were used to investigate the influence of spectral baseline and linewidths at different field strengths.
All computational tasks, including density matrix simulation, data processing, Monte-Carlo analysis, and correlation analysis, were carried out with in-house software written in MATLAB (R2020b; MathWorks, Natick, MA, USA) on a personal laptop using an Intel CoreI i7-10850H CPU (2.7 GHz) with 32 GB RAM.
## 3. Results
LCM spectral fitting of a representative in vivo 31P MRS spectrum acquired from human brain at 3 *Tesla is* shown in Figure 1. The fitting result for a representative 7 *Tesla spectrum* is shown in Figure 2. Note that although UDPG was not detected in individual participants at 3 Tesla, the improved sensitivity at 7 Tesla allows the detection of UDPG indicated by an arrow in Figure 2. At 7 Tesla, the MP signal is greatly reduced, a reduction which is accompanied by substantially improved spectral resolution in the downfield region. The background spectral baseline is also significantly reduced at 7 Tesla. The PCr linewidth and SNR were found to be 6.3 ± 0.9 Hz and 82 ± 21 at 3 Tesla and 9.3 ± 2.1 Hz and 171 ± 27 at 7 Tesla, respectively. The means and standard deviations of metabolite concentrations found by LCM fitting are summarized in Supplementary Table S1. The results are in agreement with a previous study that used jMRUI [11].
The 3 Tesla spectral model contains 11 × $\frac{10}{2}$ = 55 pairs of 31P-containing metabolites + MP. From the Monte *Carlo analysis* of the 10,000 spectra without the background spectral baseline, Pearson’s correlation coefficients for each of the 55 pairs were computed. The results were depicted by the top-left correlation coefficient matrix in Figure 3. As seen in this matrix, there is a strong negative correlation between NAD+ and NADH. Without the spectral baseline, the correlation coefficient of the NAD+–NADH at 3 Tesla was found to be −0.72 ± 0.04 ($$n = 5$$). Except for NAD+–NADH, GPC–GPE, GPC–MP, Piex–Piin, and PC–PE, all other metabolite–metabolite pairs showed only minor correlations with Pearson’s correlation coefficients in the range of −0.1~0.1.
The effect of the background baseline at 3 *Tesla is* shown by the middle and the right matrices in the top row of Figure 3. These correlation coefficients were computed from the 10,000 spectra that include the background spectral baseline. As seen in these two matrices, the addition of the background spectral baseline has little effect on the upfield correlations at 3 Tesla. For example, the NAD+–NADH correlation coefficient was found to be −0.68 ± 0.05 ($$n = 5$$) with the background spectral baseline, which is comparable to the corresponding value in the absence of the background spectral baseline (−0.72 ± 0.04, $$n = 5$$; effect size = 0.94, $$p \leq 0.008$$). However, the background spectral baseline causes relatively large changes in the downfield correlations, as evidenced by the top right difference matrix.
The procedure for computing the correlation coefficients at 7 *Tesla is* similar. The results are shown by matrices in the bottom row of Figure 3. As expected, all correlations become weaker at 7 Tesla due to the increased spectral resolution. Note that the 7 Tesla spectral model includes UDPG; therefore, it contains 12 × $\frac{11}{2}$ = 66 pairs of 31P-containing metabolites + MP. The pair with the greatest correlation coefficient at 7 Tesla remains NAD+–NADH. However, the magnitude of their correlation becomes smaller than at 3 Tesla. Without the background spectral baseline, the NAD+–NADH correlation coefficient was found to be −0.56 ± 0.01 ($$n = 5$$) at 7 Tesla. With the background spectral baseline, this correlation is barely changed (−0.55 ± 0.01; $$n = 5$$; effect size = 0.73, $$p \leq 0.14$$). Similar to the 3 Tesla case, the background spectral baseline causes relatively large changes in the downfield correlations, although the overall change is much smaller than at 3 Tesla.
A more detailed comparison is shown in Figure 4, which demonstrates the complex effect of the background spectral baseline at both 3 and 7 Tesla. Notably, there are highly significant correlations between UDPG and NAD (both NAD+ and NADH) at 7 Tesla. Although the background spectral baseline has a relatively small effect on the UDPG–NAD correlations, the influence of the baseline is quite significant for the downfield correlations, especially at 3 Tesla. For example, the PC–PE correlations at 3 Tesla changed from −0.36 ± 0.03 ($$n = 5$$) without the baseline to 0.12 ± 0.03 ($$n = 5$$; effect size = 14.99, $p \leq 0.0005$) with the baseline.
Because spectral overlap becomes more prominent with broader lines, line-broadening is expected to increase cross-correlations in general. As described in the Materials and Methods, 4000 spectra were generated for each line-broadening factor at each field strength, with half of the spectra without the background spectral baseline. Figure 5 shows examples of the cross-correlation coefficients with different line-broadening factors. The numerical values of all correlation coefficients for characterizing the linewidth effect are provided in Supplementary Tables S2 and S3. As shown in Figure 5, there is a trend by which the magnitude of the cross-correlation coefficients becomes greater with broader linewidths at both field strengths. However, there are exceptions to this trend. For example, the Pearson’s correlations coefficients for the UDPG–NAD+ pair become smaller with greater line-broadening with and without the background spectral baseline over the linewidth range investigated here. Also shown by Figure 5, adding the background spectral baseline has a strong impact on cross-correlation coefficients for metabolite pairs such as GPC–GPE, GPC–MP, Piex–Piin, and PC–PE, which belong to the downfield spectral region. This strong impact disrupts the trend of shared directionality of correlation and linewidth.
A secondary effect of line-broadening is degraded measurement precision. Table 1 and Table 2 summarize the linewidth effect on coefficients of variation (CVs) of the 31P-containing metabolites at both 3 and 7 Tesla. As expected, the results demonstrate increased CVs when the linewidths are increased. Adding the background spectral baseline also increases CVs as the baseline contributes to the overall crowdedness.
## 4. Discussion
In this study, we have shown that many 31P-containing metabolites measured using in vivo 31P MRS are correlated due to spectral overlap. Like in the case of short echo time proton MRS these correlations are influenced by linewidth and interactions with the background spectral baseline [23,24], especially in the downfield region. Compared with 3 Tesla, metabolite–metabolite correlations are significantly reduced at 7 Tesla, highlighting a previously underappreciated benefit of high magnetic field MRS. Even at 7 Tesla, however, there remain significant metabolite–metabolite correlations due to the severe spectral overlap between NAD+, NADH, and UDPG, and, to a lesser extent, due to interactions with the background spectral baseline in the downfield region.
Correlation between two variables A and B can be distorted by their correlation with a potentially intervening variable C. The influence of variable C can be illustrated using partial correlations. Specifically, the partial correlation coefficient between A and B with the influence of C excluded (rAB|C) is defined as follows [24,25]:[1]rAB|C=rAB−rACrBC1−rAC21−rBC2 where rAB, rAC, and rBC are Pearson’s correlation coefficients measured experimentally. In the case of correlating a 31P-containing metabolite (A) with a clinical metric (B), the measured Pearson’s correlation coefficient rAB could be significantly influenced by another 31P MRS signal (C) overlapping with the 31P signal of interest (A). It is well known in statistics that if the rAB|C is much smaller than rAB, then the Pearson’s correlation between A and B is considered spurious, which would be caused by their correlations with C instead of by the genuine correlation between A and B [25,26].
In proton MRS, it is often possible to suppress the influence of overlapping signals by spectral editing or by altering the echo time [27]. Unfortunately, 31P signals generally have very short T2; therefore, it is difficult to spectroscopically suppress spectral overlap in 31P MRS. These considerations and the results of this study indicate that metabolite–metabolite correlations due to spectral overlap need to be considered in downstream statistical correlations between overlapping 31P-containing metabolites and clinical metrics. Furthermore, compared to the 3 Tesla results, the dramatic reduction in metabolite–metabolite correlations at 7 Tesla highlights the advantage of high magnetic field 31P MRS in avoiding or reducing the confounding spectral correlations.
ATP comprises three moieties that resonate at −7.56 ppm (α-ATP), −16.18 ppm (β-ATP), and −2.53 ppm (γ-ATP). Of them, the α-ATP peak overlaps strongly with both NAD+ and NADH. In contrast, β-ATP and γ-ATP are not affected by any spectral overlap. As such, ATP as a whole is well determined, even in the presence of significant spectral overlap between α-ATP and NAD. This de facto spectral separation between ATP and NAD is reflected by the negligible Pearson’s correlation coefficients for ATP–NAD+ and ATP–NADH, even at 3 Tesla.
It is well-known in the MRS literature that line-broadening due to poor shimming degrades measurement precision. This effect of line-broadening is reflected by the results of Table 1 and Table 2, which show increased metabolite CVs due to increased line-broadening with and without the background spectral baseline and at both field strengths. Note that the increased correlation between overlapping signals due to line-broadening also contributes to increased CVs because of the greater measurement uncertainty in the presence of spectral overlap. In contrast to the dependence of CVs on linewidth, the effects of line-broadening on metabolite–metabolite correlation are more nuanced. Although the general trend of correlation increasing with broader resonance lines is expected, it is noted that metabolite–metabolite correlations are also influenced by other overlapping resonances in a complex and often nonintuitive fashion. Equation [1] above provides an illustrating example for the simple case of three-way correlations. Therefore, it is not surprising that, over the range of 20 Hz, it was found that line-broadening reduces Pearson’s correlation between UDPG–NAD+, as shown in Figure 5.
## 5. Conclusions
Using Monte *Carlo analysis* with the exclusion of biological effects, the metabolite–metabolite correlations due to spectral overlap in the 31P MRS of human brain were systematically investigated. The results show the importance of high magnetic fields in reducing the confounding metabolite–metabolite correlations due to overlapping 31P MRS signals. The quantification of the pre-existing correlations between 31P-containing metabolites described in this work is expected to facilitate clinical studies that involve correlating overlapping 31P MRS signals with clinical metrics.
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|
---
title: 'Inositol in Disease and Development: Roles of Catabolism via myo-Inositol
Oxygenase in Drosophila melanogaster'
authors:
- Altagracia Contreras
- Melissa K. Jones
- Elizabeth D. Eldon
- Lisa S. Klig
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967586
doi: 10.3390/ijms24044185
license: CC BY 4.0
---
# Inositol in Disease and Development: Roles of Catabolism via myo-Inositol Oxygenase in Drosophila melanogaster
## Abstract
Inositol depletion has been associated with diabetes and related complications. Increased inositol catabolism, via myo-inositol oxygenase (MIOX), has been implicated in decreased renal function. This study demonstrates that the fruit fly Drosophila melanogaster catabolizes myo-inositol via MIOX. The levels of mRNA encoding MIOX and MIOX specific activity are increased when fruit flies are grown on a diet with inositol as the sole sugar. Inositol as the sole dietary sugar can support D. melanogaster survival, indicating that there is sufficient catabolism for basic energy requirements, allowing for adaptation to various environments. The elimination of MIOX activity, via a piggyBac WH-element inserted into the MIOX gene, results in developmental defects including pupal lethality and pharate flies without proboscises. In contrast, RNAi strains with reduced levels of mRNA encoding MIOX and reduced MIOX specific activity develop to become phenotypically wild-type-appearing adult flies. myo-Inositol levels in larval tissues are highest in the strain with this most extreme loss of myo-inositol catabolism. Larval tissues from the RNAi strains have inositol levels higher than wild-type larval tissues but lower levels than the piggyBac WH-element insertion strain. myo-Inositol supplementation of the diet further increases the myo-inositol levels in the larval tissues of all the strains, without any noticeable effects on development. Obesity and blood (hemolymph) glucose, two hallmarks of diabetes, were reduced in the RNAi strains and further reduced in the piggyBac WH-element insertion strain. Collectively, these data suggest that moderately increased myo-inositol levels do not cause developmental defects and directly correspond to reduced larval obesity and blood (hemolymph) glucose.
## 1. Introduction
Alterations in myo-inositol metabolism are often associated with human diseases including diabetes, cancer, reproductive defects, and neurological disorders [1,2,3,4,5,6,7,8]. The depletion of myo-inositol has been associated with diabetic complications such as nephropathies, cataracts, retinopathies, and neuropathies [9,10,11,12]. Inositol depletion could arise from increased myo-inositol catabolism. Rats with upregulated myo-inositol catabolism have increased blood glucose and related pathobiological stress [13,14,15]. In the fruit fly, Drosophila melanogaster, reduced myo-inositol synthesis was shown to cause defective spermatogenesis [16], and increased myo-inositol synthesis caused severe developmental defects [17]. This led to the current study investigating the role of myo-inositol catabolism in fruit fly development and metabolism.
Inositol is a six-carbon sugar alcohol found in all eukaryotes and some prokaryotes. It can serve as a precursor of the membrane lipid phosphatidylinositol, act as a second messenger in signal transduction pathways, aid in osmoregulation, mediate endoplasmic reticulum stress (unfolded protein response), affect nucleic acid synthesis, or function as a carbon and/or energy source [18,19,20,21,22,23]. myo-Inositol oxygenase (MIOX) catalyzes the first step of myo-inositol catabolism and is essential in the regulation of myo-inositol levels in vivo [24,25,26,27]. MIOX was first reported in rat kidney extracts, and later in oat seedlings, hog and human kidney, many plants, and yeast [13,25,28,29,30,31,32,33,34,35]. In most organisms, MIOX is an approximately 33 kDa monomeric single-domain protein [36,37]. This highly conserved enzyme catalyzes the ring cleavage of myo-inositol with the incorporation of oxygen, converting myo-inositol into D-glucuronic acid. D-glucuronic acid can enter in multiple metabolic pathways, including the step-wise conversion into D-xylulose-5-phosphate and then the pentose phosphate cycle, eventually producing nucleic acids and providing energy [25,26,28,29]. The glucuronate–xylulose pathway has been documented as the only myo-inositol catabolic pathway in eukaryotes [25].
In recent years, D. melanogaster has emerged as an ideal model organism for studying metabolic diseases including diabetes [38,39,40,41,42,43,44,45,46]. It has also been shown, via established assays, to display a wide array of diabetic-like traits similar to humans such as increased circulating glucose, insulin resistance, excess lipid storage, and decreased longevity [38,39,42,45,47,48,49,50,51,52,53,54,55,56]. The development of the fruit fly consists of gametic, embryonic, larval, pupal, and adult stages. During embryogenesis, the imaginal disc primordia are established, and head involution occurs. Head involution includes the rearrangement of lobes that form larval head structures, concurrent with the relocation of the imaginal disc primordia that later contribute to adult head structures, including the proboscis [57,58]. Rivera et al. [ 17] demonstrated that dietary myo-inositol and/or increasing myo-inositol synthesis via genetic manipulation alleviated obesity and high-hemolymph glucose; however, extremely high levels of constitutive myo-inositol synthesis resulted in pupal lethality and developmental defects (lacking proboscises and with structural alterations of the legs and wings).
In the current study, myo-inositol catabolism and its role in growth, development, and adaptation to varied environments were explored in the model organism D. melanogaster. D. melanogaster were shown to survive with myo-inositol as the sole dietary sugar. Moreover, this study seems to be the first demonstration in animals that MIOX mRNA levels and MIOX specific activity levels are regulated in response to dietary myo-inositol. A piggyBac WH-element insertion strain, with MIOX specific activity eliminated, displayed high levels of pupal lethality and pharate adult developmental defects (no proboscises). Third-instar larvae of three independent D. melanogaster strains with reduced MIOX mRNA levels and reduced MIOX specific activity levels were shown to have a dramatic reduction in obesity and high-hemolymph glucose. Lastly, genetic modifications cause high levels of myo-inositol mitigate diabetic traits but display developmental defects, while dietary myo-inositol supplementation mitigates diabetic traits without inducing developmental defects. These studies contribute to the understanding of the role of myo-inositol in metabolism and development.
## 2.1. MIOX Homolog Identified in D. melanogaster (CG6910) Is Regulated in Response to Dietary myo-Inositol
To identify myo-inositol oxygenase (MIOX) in Drosophila melanogaster, BLASTP was performed using the 285 amino acid human MIOX protein sequence as a query. This revealed one candidate (CG6910) with ~$55\%$ identity spanning the entire protein. Although there are two splice variants of CG6910, B and C, listed in Flybase [59], 5′RACE experiments previously performed in this lab did not detect the C variant in larvae or adults. Moreover, high-throughput expression data (RNA -Seq Signal by Region) and the G-browse visual display reveal that RNA transcripts unique to the C variant region are rare or undetectable in all stages of development and in all tissues examined [59]. To experimentally verify that CG6910 encoded the MIOX protein, three strains were obtained; two RNAi strains to reduce CG6910 transcript levels and one strain with a piggyBac WH-element inserted into CG6910 (Figure 1A).
To determine if the levels of CG6910 (MIOX) mRNA are regulated in response to myo-inositol, qRT-PCR experiments were performed. RNA was extracted from third-instar larvae and adults of five D. melanogaster strains. Two of the strains have different MIOX (CG6910) RNAi constructs with UASGAL4 sequences. Both are controlled by GAL4 driven by the Actin 5C (Act5C) promoter (MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3). Three control strains were also used (CS, ActGal4-3/Tb, and CyOGFP/+; ActGal4-3/Tb). The adults had slightly lower MIOX mRNA levels than the larvae. MIOX (CG6910) mRNA levels in MIOXi2/+; +/Act5Cgal4-3 and MIOXi3/Act5CGal4-3 were significantly lower than in the control strains. When larvae were grown on semi-defined food with myo-inositol as the sole sugar (CAA-I), the level of MIOX mRNA was significantly higher than when grown on semi-defined food with sucrose as the sole sugar (CAA-S) (Figure 1B).
To examine if dietary myo-inositol affected MIOX specific activity, the conversion of myo-inositol to glucuronic acid by crude lysates of third-instar larvae and adults was monitored in the strains described above. There was slightly less activity detectable in the adults than the larvae. MIOX specific activity in larvae was significantly higher for all the strains when grown on CAA-I. Moreover, the specific activity of MIOX in crude lysates of MIOXi2/+, +/Act5CGal4-3, and MIOXi3/Act5CGal4-3 larvae was significantly lower than that of the control larvae (Figure 1C). Even more striking is that there was no detectable MIOX activity in crude lysates of the homozygous piggyBac WH-element insertion strain (P-mioxf01770/P-mioxf01770).
## 2.2. Dietary myo-Inositol Supports Survival of Wild-Type (CS) D. melanogaster Adults but Not of MIOX Knockdown Strains
To determine if MIOX plays a role in fruit fly survival, pupae of MIOXi2/+; +/Act5CGal4-3, MIOXi3/Act5CGal4-3, and the wild-type control strain (CS) were transferred to tubes with semi-defined food containing sucrose (CAA-S) or myo-inositol as the sole sugar (CAA-I), or no sugar (CAA-0). It was exciting to note that wild-type (CS) adult flies survived equally well on semi-defined food with either myo-inositol or sucrose as the sole sugar, demonstrating that there is sufficient myo-inositol catabolism to support survival of D. melanogaster (Figure 2A).
Moreover, control, MIOXi2/+; +/Act5CGal4-3, and MIOXi3/Act5CGal4-3 adults survived comparably well on semi-defined food with sucrose (CAA-S). On semi-defined no-sugar food (CAA-0), all three strains died within ten days (Figure 2A–C). In contrast to wild-type flies, MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3 adults died by day 10 on semi-defined food with myo-inositol as the sole sugar (CAA-I). The survival of these two strains on CAA-I was similar to their survival on food with no-sugar (CAA-0) (Figure 2B,C).
## 2.3. Disruption of myo-Inositol Catabolism via Piggybac WH-Element Insertion in MIOX Results in Developmental Defects
The survival experiments described above did not include adult P-mioxf01770/P-mioxf01770 flies, because these homozygotes are not viable as adults. As displayed in Figure 3A, ~$16\%$ of the homozygous P-mioxf01770/P-mioxf01770 and ~$76\%$ of the control embryos developed to the pupal stage. Even more striking is that only ~$6\%$ of the homozygous P-mioxf01770/P-mioxf01770 pupae eclosed as adults, with most dying as pharate adults (not eclosing from the pupal case), in contrast to ~$96\%$ of the control strain eclosing as adults. The few P-mioxf01770/P-mioxf01770 adults that eclosed from the pupal case died within two days and exhibited severe head morphological defects, most noticeably the lack of a proboscis (Figure 3B). To confirm that the piggyBac WH-element in P-mioxf01770 caused the pupal lethality and morphological defect, heterozygous strains with the element excised were generated. All three independently obtained excision lines (eleven stocks), with TM6, Tb balancer chromosomes, produced viable homozygous progeny in the expected ratio. Of the 998 pupae examined (350 homozygotes; 648 heterozygotes (Tb)), the same percentage of homozygotes and heterozygotes eclosed. Neither pupal lethality nor morphological defects were observed in the homozygous excision progeny. The excision of the element reverted the phenotype.
## 2.4. Reduced myo-Inositol Catabolism Increases myo-Inositol Levels in Larvae
To assess if the developmental defect observed in the P-mioxf01770/P-mioxf01770 strain was due to reduced catabolism yielding increased myo-inositol levels, assays were performed using carcasses of third-instar larvae grown on rich food with 0 or 50 µM myo-inositol supplementation. Higher myo-inositol levels were observed in the tissues of larvae with decreased myo-inositol catabolism (Figure 4A). The highest level of myo-inositol is apparent in the P-mioxf01770/P-mioxf01770 larval tissues which had no detectable myo-inositol catabolic activity via MIOX. In all the strains, myo-inositol levels increased when the standard rich food was supplemented with 50 µM of myo-inositol (Figure 4A).
## 2.5. Increased myo-Inositol Decreases Larval Obesity and Hemolymph Glucose
To examine the relationship between MIOX and the diabetic hallmarks, obesity and high hemolymph glucose, third-instar larvae grown on standard rich food with 0 or 50 µM myo-inositol supplementation were assayed. Buoyancy, TAG, and glucose assays revealed that P-mioxf01770/P-mioxf01770 larvae were the least obese with the lowest levels of TAG and hemolymph glucose. In these assays, the two RNAi knockdown strains, MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3, had intermediate levels relative to the control and the P-mioxf01770/P-mioxf01770 strains (Figure 4B–D). Dietary myo-inositol supplementation (50 µM) further reduced the proportion of obese larvae, TAG, and hemolymph glucose in all strains (Figure 4B–D).
## 3. Discussion
This study examines the roles of myo-inositol catabolism using the model organism D. melanogaster. CG6910 was identified as the myo-inositol catabolic gene encoding myo-inositol oxygenase (MIOX), which is more than $55\%$ identical (>$70\%$ similar) to human MIOX. The high level of identity among these two evolutionarily distant organisms demonstrates the conservation of MIOX structures in eukaryotes. There are two splice variants, B and C, listed in Flybase [59]; however, multiple experiments suggest that RNA transcripts unique to the C variant region are rare or undetectable in all stages of development and in all tissues examined [59]. If the C variant exists in larvae and adults, it comprises a small proportion of the MIOX transcripts and protein. Developmental proteome experiments reveal high levels of MIOX expression in late third-instar larvae (wandering and prepupae) and adults [60]. Temporal microarray and RNAseq data have shown the peak expression of MIOX (CG6910) mRNA in late third-instar larvae and adults [61]; therefore, an emphasis has been placed on examining third-instar larvae and adults.
This appears to be the first report to examine MIOX (CG6910) mRNA levels in animals, D. melanogaster larvae and adults, in response to dietary myo-inositol (Figure 1B). A significantly higher level of MIOX mRNA is apparent in qRT-PCR experiments examining larvae fed myo-inositol as the sole sugar (CAA-I) compared to larvae fed sucrose as the sole sugar (CAA-S). MIOX mRNA levels were reduced in larvae and adults via two different RNAi constructs (MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3) (Figure 1B). Similar to the wild-type control, these strains have higher levels of MIOX mRNA when grown on CAA-I than when grown on CAA-S (Figure 1B). Increased myo-inositol catabolism, via MIOX, has been implicated in decreased renal function [62]. Decreased MIOX mRNA levels via siRNA in transgenic mice expressing high levels of MIOX mRNA has been shown to reduce renal damage and associated endoplasmic reticulum stressors [63]. Yet, in this study using D. melanogaster, neither the RNAi strain nor the wild-type controls exhibited any gross morphological abnormalities, even with increased levels of MIOX mRNA when fed CAA-I.
An assay to measure MIOX-specific activity in D. melanogaster was established based on previously existing protocols for rat kidneys, hog kidneys, and fungi [28,31,32] (Figure 1C). Similar to the mRNA levels, MIOX-specific activity levels in MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3 larvae and adults were lower than the control (CS) strain. Moreover, all the strains had increased levels of MIOX activity when fed CAA-I. Homozygous CG6910-MIOX (P-mioxf01770/P-mioxf01770) larvae with a 7.2 kb piggyBac WH-element insertion disrupting the MIOX gene had no detectable MIOX activity. The MIOX-specific activity in crude lysates of control D. melanogaster larvae is 5.2 µmol/30 mins/mg, slightly more than that observed in adults, much more than that in rat kidney [29], and similar to that in the fungus Cryptococcus neoformans [32].
Survival experiments revealed that adult D. melanogaster have sufficient myo-inositol catabolism and transport to remain viable on semi-defined food with myo-inositol as the sole sugar/energy source (CAA-I) (Figure 2). The statistically significant results of six independent trials also showed that a reduction in MIOX expression via RNAi diminishes viability on CAA-I, mimicking survival on food with no sugar. The identical loss of the viability of both fly strains, MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3, is particularly compelling, because the RNAi constructs are located on separate chromosomes and the strains were generated from two separate Vienna Drosophila Resource Center (VDRC) libraries (KK (phiC31) and GD (P-element), respectively). These libraries used different vectors and cloning methods and have been shown to have different off-target effects [64,65,66,67]. Since the two strains appeared phenotypically identical, the observed phenotypes in this study should be due to the decreased MIOX mRNA levels. Moreover, these results indicate that MIOX is a component of the primary myo-inositol catabolic pathway in D. melanogaster.
Adult P-mioxf01770/P-mioxf01770 were not included in experiments because they are rarely viable, with only ~$6\%$ of the pupae eclosing and the flies that eclose dying within two days (Figure 3A). These results are similar to previously published findings that highly upregulated myo-inositol synthesis reduces eclosion to ~$9\%$ [17]. As myo-inositol is a precursor of the phosphatidylinositol phosphates (PIPs), it is interesting to note that inositol phosphate kinase 2 (Ipk2) deletions and dysregulation of the expression of the phosphatidylinositol synthase gene (Pis) also cause pupal lethality [68,69]. Among the few P-mioxf01770/P-mioxf01770 adults, the most jarring morphological defect is the lack of proboscises (Figure 3B). This phenotype has been previously described when myo-inositol synthesis was highly upregulated [17]. The MIOX RNAi knockdown strains with intermediate levels of of myo-inositol in larval tissues did not display morphological abnormalities, paralleling previously published findings that lower but still elevated levels of myo-inositol synthesis did not produce the developmental defect [17]. Together, these data suggest that increased myo-inositol, not the process of synthesis or catabolism, contributes to or causes developmental defects. Deformities of fruit fly head structures have been observed with mutations disrupting the head involution defective (hid) [70,71] or the decapentaplegic (dpp) genes [72,73,74]. The morphological abnormalities observed in this study, however, seem to be unique to flies with elevated myo-inositol levels.
As could be predicted, less myo-inositol catabolism results in more myo-inositol in larval tissues, with the highest myo-inositol level observed in the strain with the lowest level of catabolism (P-mioxf01770/P-mioxf01770). Not surprisingly, the intermediate levels of myo-inositol catabolism in the two RNAi knockdown strains MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3 showed intermediate levels of myo-inositol in larval tissues (Figure 4A). When rich food was supplemented with 50 µM of myo-inositol, the myo-inositol levels in all the strains increased (Figure 4A). Interestingly, whole MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3 larvae fed rich food with 50 µM myo-inositol supplementation had more total myo-inositol than P-mioxf01770/P-mioxf01770 larvae fed rich food without myo-inositol supplementation, yet only P-mioxf01770/P-mioxf01770 displayed morphological defects (Figure 3B). Larvae with hemolymph removed (carcasses) of MIOXi2/+; +/Act5CGal4-3 and MIOXi3/Act5CGal4-3 fed rich food with 50 µM myo-inositol supplementation had lower total myo-inositol than carcasses of P-mioxf01770/P-mioxf01770 larvae fed rich food without myo-inositol supplementation (Figure 4A). Apparently, adding dietary myo-inositol, and by doing so increasing the circulating myo-inositol levels, does not affect development but does further reduce obesity (buoyancy and TAG) and hemolymph glucose levels in all the strains (Figure 4B,C). It is tantalizing to speculate that at least some of the developmental defects observed in P-mioxf01770/P-mioxf01770 stem from abnormally high myo-inositol levels during embryogenesis prior to the organism feeding. Notably, abnormally high myo-inositol levels contribute to the pathology of some human disorders of neurological development and dysfunction [6,7,75,76,77].
Alterations of myo-inositol metabolism been implicated in many human diseases and disorders including diabetes, obesity, and hyperglycemia. Low MIOX expression/activity, which should elevate myo-inositol levels, rescued mice and rats from renal injury and oxidative stress [27,62]. In this study, low MIOX levels were shown to reduce obesity and hyperglycemia in populations of D. melanogaster larvae. In addition, the supplementation of the rich food with 50 µM of myo-inositol further reduced obesity and hyperglycemia. In humans, dietary myo-inositol augmentation may mitigate obesity and hyperglycemia (high blood glucose) [4,7,78]. These results complement studies which established that reduction in the inositol 1,4,5-trisphosphate receptor (InsP3R), either by knockdown or mutation, resulted in obese adult fruit flies [79]. Moreover, these results are in agreement with studies demonstrating that an increase in myo-inositol, via the overexpression of the myo-inositol synthetic gene or the addition of dietary myo-inositol, decreased obesity and hyperglycemia in D. melanogaster [17]. In summary, increased myo-inositol, regardless of its source, can mitigate diabetes-associated obesity and hyperglycemia. This study, at the junction of metabolism and development, furthers the understanding of the importance of myo-inositol catabolism and the regulation of intracellular myo-inositol levels and may have implications for the treatment of diabetes and developmental disorders.
## 4.1. Fly Stocks and Maintenance
Stocks obtained from the Bloomington Drosophila Stock Center (Bloomington, IN, USA) include the Canton-S (#1, CS) strain, w [1118]; PBac{w[+mC] = WH}CG6910[f01770]/ TM6B, Tb[1] (#18471, hereafter identified as P-mioxf01770/Tb), y[1] w[*]; +;P(w[+mC] = Act5C-GAL4)17bFO1/TM6B, Tb[1] (#3954, hereafter identified as Act-Gal4-3/Tb), w[1118]; CyO, P{w[+mC] = FRT(w[+])Tub-PBac\T}2/wg[Sp-1] (#8283), w[*]; TM3, Sb [1] Ser [1]/TM6B, Tb[1] (#2537, hereafter identified as w[*]; Tb/Sb), and w[1118]; Df(3L) Ly, sens(Ly-1)/TM6B, P{w[+mW.hs]=Ubi-GFP.S65T}PAD2, Tb[1] (#4887) and w[1]; sna[Sco]/CyO, P{w[+mC] = GAL4-Hsp70.PB}TR1, P{w[+mC] = UAS-GFP.Y}TR1 (#5702) used to introduce GFP-marked chromosomes 3 and 2, respectively). The two RNAi strains P{KK102548}VIE-260B (#103766, hereafter identified as MIOXi2/MIOXi2) and w[1118]; P{GD12073} v22464/TM3, Tb (#22464, hereafter identified as MIOXi3/Tb) were obtained from the Vienna Drosophila Research Center (Vienna, Austria). The RNAi strain MIOXi2/MIOXi2 is homozygous for an RNAi construct complementary to the third exon of CG6910 that was inserted via P-element to chromosome 2. The other RNAi strain, MIOXi3/Tb, also containing sequences complementary to the third exon of CG6910, is heterozygous for a different RNAi construct that was inserted via a phiC31 sequence to chromosome 3. Both RNAi constructs contain UASGAL4 sequences controlled by GAL4 expression. MIOXi2/+; +/ActGal4-3 and MIOXi3/ActGal4-3 were generated by mating strains marked with GFP on corresponding balancer chromosomes. The third strain was generated by introducing a GFP-marked balancer third chromosome (TM6) into the P-mioxf01770/Tb, an existing strain with an approximately 7.2kb piggyBac WH-element inserted into the second intron of CG6910, and non-GFP non-tubby homozygotes (P-mioxf01770/ P-mioxf01770) were then readily identified. The piggyBac-element insertion in CG6910 was remapped and its location confirmed using flanking sequence data [80]. To create a double-marked (Tb/Sb) transposase strain, the strain harboring the transposase (#8283) was crossed to a third chromosome double balancer strain (#2537) introducing the Tb marked TM6B chromosome. These Tb marked flies were again crossed to the third chromosome double balancer strain (#2537) to introduce the Sb marked TM3 chromosome creating the double marked transposase strain w [1118]; CyO, P{w[+mC] = FRT(w[+])Tub-PBac\T}2; TM3, Sb [1] Ser [1]/TM6B, Tb [1] (hereafter identified as w[+]; piggyBac transposase; Tb/Sb). To excise the piggyBac WH-element inserted in the MIOX gene (CG6910), the w[+]; piggyBac transposase; Tb/Sb strain was crossed to P-mioxf01770/Tb (#18471). According to Thibault et al. 2004 [81], excisions of this piggyBac WH-element are precise. Seventy-two single Tubby (Tb) progeny with dark red eyes (double w[+mC]) with curly wings (CyO) harboring both the transposase and the piggyBac WH-element were individually mated with w[*]; Tb/Sb. Eight of the seventy-two crosses produced white-eyed, straight-winged progeny, carrying neither the piggyBac WH-element (chromosome 3, CG6910) nor the transposase (chromosome 2, CyO, P{w[+mC] = FRT(w[+])Tub-PBac\T}2). Of these eight, three produced multiple white-eyed, straight-winged progeny which were used to establish stocks. Three or four individuals from each of the three independent lines (eleven flies) with putative piggyBac WH excisions (from the MIOX gene (CG6910)) were individually crossed to w[*]; Tb/Sb, and Tb progeny were selected.
Flies were maintained in standard laboratory conditions at 25 °C and 70–$80\%$ humidity on a 12 h:12 h light–dark cycle. All fly stocks were grown on either rich food (BDSC cornmeal food, https://bdsc.indiana.edu/information/recipes/bloomfood.html (accessed on 29 April 2011)) or modified food (per liter, 10 g of agar (Fisher Scientific, Waltham, MA, USA), 80 g of brewer’s yeast (Genesee), 20 g of yeast extract (Fisher Scientific), 20 g of peptone (Fisher Scientific), and sucrose (Fisher Scientific) as indicated, [49]) with or without 50 µM of myo-inositol (Sigma, St. Louis, MO, USA) as indicated, which is sufficient to support growth of a homozygous Inos deletion mutant (inosΔDF/inosΔDF) [16]. Semi-defined food (casamino acids sucrose (CAA-S) and casamino acids myo-inositol (CAA-I)) was prepared essentially as described [82] with modifications [83]. Briefly, defined food contained 0.4 g of lecithin, 0.613 g of vitamin mix, 5.5 g of casamino acids, 3.15 g of agar, and 7.5 g of sugar (sucrose or myo-inositol) or no sugar per 100 mL. The vitamin mix was composed of 3 g of cholesterol, 0.02 g of thiamine, 0.01 g of riboflavin, 0.12 g of nicotinic acid, 0.16 g of calcium pantothenate, 0.25 g of pyridoxine, 0.016 g of biotin, 0.03 g of folic acid, 14 g of NaHCO3, 18.3 g of KH2PO4, 18.9 g of K2HPO4, and 6.2 g of MgSO4. Then, 350 μL of $30\%$ Tegosept was added to the 100 mL of food.
## 4.2. RNA Extraction and qRT-PCR
Total RNA was extracted from 10–20 third-instar larvae or adult flies grown on the food indicated using TrizolTM (Life Technologies, Carlsbad, CA, USA) [84]. Total RNA (1 µg) was DNase-treated using the DNA-free Kit (Ambion, Foster City, CA, USA) with inactivation buffer (DNA-free DNA Removal Kit, Invitrogen, Carlsbad, CA, USA). cDNAs were generated using oligo (dT) 18 primers (Eurofins, Luxembourg), dNTPs (ThermoFisher, Waltham, MA, USA), and Moloney Murine Leukemia Virus Reverse Transcriptase (M-MLV RT) (Fisher, Waltham, MA, USA). After amplification, the samples were treated with RNAse H (New England BioLabs, Ipswich, MA, USA). The cDNA was diluted in RNase/DNase-free water (ThermoFisher) (1:16), and qRT-PCR experiments were performed using ThermoScientific Absolute qPCR Mix, SYBR Green, ROX (Fisher) in an Applied Biosystems StepOnePlus System. Triplicate samples were used in all the experiments including linearizations and melt curves. All the experiments were performed at least three independent times (separate biological samples), as indicated in the figure legends. The results were normalized to the transcript levels of Drosophila melanogaster ribosomal protein L32 (RpL32). The following primers were used: MIOX exon 2-3 forward GACACCACCGATCCTCTAAAGG and reverse GGAAGGCGTGGATGATGT, RpL32 forward CCAGCATACAGGCCCAAGAT and reverse GCACTCTGTTGTCGATACCC.
## 4.3. Protein Extraction and the MIOX Activity Assay
The MIOX activity assays were established for D. melanogaster based on protocols for hog kidneys and fungi [31,32]. For each sample, ten flies or ten larvae were homogenized in 300 μL of 20 mM sodium acetate (pH 6.0), 2 mM L-cysteine (pH 4.5), 1 mM glutathione (pH 3.5), 1mM ferrous ammonium sulfate (pH 4.5), and 10 μL of protease inhibitor (Halt™ Protease Inhibitor Cocktail (100X), Thermo Scientific). Protein concentrations of the crude lysate cleared supernatants were determined using the Bradford Assay [85] with bovine serum albumin (Pierce™ Bovine Serum Albumin Standard, Thermo Scientific) and using a dye concentrate (5000006, Bio-Rad, Hercules, CA, USA) for the colorimetric analysis. myo-Inositol catabolism was assayed in 450 μL of 50 mM sodium acetate (pH 6.0), 2 mM L-cysteine (pH 3.5), 1 mM ferrous ammonium sulfate (pH 4.5), and 60 mM myo-inositol (or water) with 15 μg of crude lysate protein. The reactions were incubated at 30 °C. Then, 200 μL aliquots were removed at 0 and 30 min, immediately added to 55 μL of $30\%$ trichloroacetic acid (TCA), and incubated at 100 °C for two minutes. The glucuronic acid concentrations of the cleared supernatants were determined by adding 500 μL of orcinol reagent (0.08 g of orcinol, 0.018 g of FeCl3 and 20 mL of concentrated HCl) to 250 μL of the sample and were measured at 660 nm [28].
## 4.4. Survival Studies
Twenty CS or Act-Gal4-3/TbGFP virgin females and ten CS or MIOXi2/MIOXi2 or MIOXi3/TbGFP males were mated on rich food. For each of the six independent trials, twenty pupae from each cross were transferred onto rich food with 0 or 50 µM of myo-inositol added, CAA-S, CAA-I, or CAA-0 (no sugar added). Survival was monitored daily.
## 4.5. Pupariation and Eclosion
Female and male adults (2:1) were placed in vials of standard rich food in a 25 °C incubator at 70–$80\%$ humidity on a 12 h:12 h light–dark cycle. The progeny (embryos) were sorted using the GFP marker and reconfirmed as larvae. To allow sufficient time for genotypes with developmental delays to eclose, the vials were checked daily for up to 28 days. The number of pupae were recorded, as was the number of adults that eclosed.
## 4.6. Light Microscopy
Fifteen control CS and sixteen independent experimental P-mioxf01770/P-mioxf01770 specimens were viewed on a Nikon SMZ1500 microscope, and images were captured using a Micropublisher 6 color CCD camera system (Teledyne Q imaging, Surrey, BC, Canada).
## 4.7. myo-Inositol Assay
Five third-instar larval carcasses per sample were collected by puncturing five larvae and draining the hemolymph via centrifugation. The samples were homogenized in dH2O, and the Megazyme myo- inositol assay kit (K-INOSL) was used as per the manufacturer’s instructions. Three independent trials were performed.
## 4.8. Buoyancy Assay
Experiments were conducted essentially as described by Reis [48,54] using 20–30 3rd-instar larvae per sample, with initial results confirmed by the method of Hazegh and Reis [54]. A relationship between the percentage of larvae floating in a buoyancy assay and the percent body fat of the larvae has been established [48,86]. In this study, the relative obesity of a population of larvae is defined as the proportion of the larvae floating in the buoyancy assay.
## 4.9. Triacylglyceride (TAG) Assay
Experiments were performed essentially as previously described [39] and normalized to total protein (using the Bradford Assay described above). Six third-instar larvae per sample were homogenized in 1xPBS with $9.1\%$ Tween, and the Serum Triglyceride Determination Kit (TR0100, Sigma, St. Louis, MO, USA) and Triglyceride Reagent (T2449, Sigma) were used as per the manufacturer’s instructions for three independent trials.
## 4.10. Hemolymph Glucose Assay
Experiments were performed essentially as described by Tennessen et al. [ 39]. Hemolymph was collected by puncturing five third-instar larvae per replicate, and the Sigma Glucose (GO) Assay Kit GAGO-20 was used. Three independent trials were performed.
## 4.11. Computational Analyses
The National Center for Biotechnology Information’s (NCBI) Basic Local Alignment Search Tool (BLASTP) with default settings (BLOSSUM 62) was used to identify the MIOX homolog in D. melanogaster.
## 4.12. Statistical Analyses
Standard error was calculated for all experiments. Mantel–Cox (log rank) tests were performed to calculate significance in survival studies. The p-values of pairwise comparisons were determined using Student’s two-tailed t-test.
## 5. Conclusions
In the model organism Drosophila melanogaster, the elimination of myo-inositol catabolism and the associated high levels of myo-inositol cause severe developmental defects. A reduction in myo-inositol catabolism or dietary myo-inositol supplementation yields the beneficial effects of higher myo-inositol levels (reduced obesity and hemolymph (blood) glucose in Drosophila melanogaster third-instar larvae) without causing developmental defects. This suggests that dietary inositol supplementation may serve as a therapeutic agent.
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|
---
title: Predicting Hepatotoxicity Associated with Low-Dose Methotrexate Using Machine
Learning
authors:
- Qiaozhi Hu
- Hualing Wang
- Ting Xu
journal: Journal of Clinical Medicine
year: 2023
pmcid: PMC9967588
doi: 10.3390/jcm12041599
license: CC BY 4.0
---
# Predicting Hepatotoxicity Associated with Low-Dose Methotrexate Using Machine Learning
## Abstract
An accurate prediction of the hepatotoxicity associated with low-dose methotrexate can provide evidence for a reasonable treatment choice. This study aimed to develop a machine learning-based prediction model to predict hepatotoxicity associated with low-dose methotrexate and explore the associated risk factors. Eligible patients with immune system disorders, who received low-dose methotrexate at West China Hospital between 1 January 2018, and 31 December 2019, were enrolled. A retrospective review of the included patients was conducted. Risk factors were selected from multiple patient characteristics, including demographics, admissions, and treatments. Eight algorithms, including eXtreme Gradient Boosting (XGBoost), AdaBoost, CatBoost, Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LightGBM), Tree-based Pipeline Optimization Tool (TPOT), Random Forest (RF), and Artificial Neural Network (ANN), were used to establish the prediction model. A total of 782 patients were included, and hepatotoxicity was detected in $35.68\%$ ($\frac{279}{782}$) of the patients. The Random Forest model with the best predictive capacity was chosen to establish the prediction model (receiver operating characteristic curve 0.97, accuracy $64.33\%$, precision $50.00\%$, recall $32.14\%$, and F1 $39.13\%$). Among the 15 risk factors, the highest score was a body mass index of 0.237, followed by age (0.198), the number of drugs (0.151), and the number of comorbidities (0.144). These factors demonstrated their importance in predicting hepatotoxicity associated with low-dose methotrexate. Using machine learning, this novel study established a predictive model for low-dose methotrexate-related hepatotoxicity. The model can improve medication safety in patients taking methotrexate in clinical practice.
## 1. Introduction
Methotrexate (MTX), a folic acid antagonist that inhibits dihydrofolate reductase in the S-phase cell cycle, was first developed as an anticancer treatment in the 1940s [1,2]. Since the 1950s, MTX has been prescribed as an immunosuppressant for treating immune system disorders, including rheumatoid arthritis, psoriasis, psoriatic arthritis, and inflammatory bowel diseases [3]. The overall prevalence of rheumatoid arthritis is $0.24\%$ to $1.1\%$ [4,5,6]. Similarly, a population-based study in the United States found that psoriasis rates increased significantly from 50.8 cases per 100,000 (from 1970 to 1974) to 100.5 cases per 100,000 (from 1995 to 1999) [7]. A worldwide review showed that the prevalence of psoriasis ranged from 0.5 to $11.4\%$ in adults [8]. MTX is now recommended as a first- or second-line treatment for many immune system diseases [9,10,11,12,13,14,15]. Although several biological agents have emerged for immune system diseases in the last two decades, such as adalimumab [16], infliximab [17], canakinumab [18], ustekinumab [19], and secukinumab [19], MTX is still widely used due to its efficacy, low cost, and ease of administration. MTX can be administered orally or subcutaneously as a weekly treatment regimen [11].
Due to lower doses of MTX, life-threatening adverse drug effects (ADE) are rarely observed in MTX treatment for immune system diseases. However, severe ADEs can still occur, especially hepatotoxicity [20]. Abnormal serum levels of alanine aminotransferase (ALT) or aspartate aminotransferase (AST) occurred in $23.47\%$ ($\frac{315}{1342}$) of patients treated for MTX-treated rheumatoid arthritis [21]. Liver enzyme abnormalities are the leading cause of dose modification or discontinuation of MTX [22]. Furthermore, a systematic review indicated that $33\%$ of patients with psoriasis who received low-dose MTX had liver disease progression, such as liver fibrosis [23]. Therefore, it is crucial to clarify the incidence of liver ADE in MTX-treated patients. Risk factors can affect MTX therapies. These risk factors include alcohol use, history of liver disease, obesity, type 2 diabetes, history of significant exposure to hepatotoxic drugs or chemicals, lack of folate supplementation, and hyperlipidemia [24,25]. However, current research lacks an assessment of the impact of these risk factors. Furthermore, there is a lack of research exploring unknown risk factors and establishing predictive models for hepatotoxicity associated with low-dose MTX.
Machine learning is one of the fastest-growing technical fields [26] and has been widely used in medical fields, such as medical diagnosis and prediction of disease risks [27,28,29]. Machine learning can promote data-driven estimation when selecting multiple variables and processing complex nonlinear relationships among multidimensional variables [30]. Therefore, machine learning can increase the precision of prediction models, especially for analyzing large datasets with many variables [31,32]. The study aimed to compare eight machine learning methods to identify the most optimal model to predict hepatotoxicity and risk factors associated with low-dose MTX.
## 2.1. Study Setting and the Study Population
This retrospective study was conducted at the West China Hospital of Sichuan University, a large tertiary teaching hospital in China. This hospital uses an electronic medical record (EMR) and bar code systems to document medication administrations. The study inclusion criteria were [1] patients with immune system diseases and [2] treated with low-dose MTX (≤30 mg per week) [33] during hospital stays at the West China Hospital of Sichuan University. Patients who were treated with other doses of MTX were excluded. The study period was from 1 January 2018 to 31 December 2019.
## 2.2. Data Extraction
A two-stage review process for medical records was conducted to identify the presence of hepatotoxicity. In the first stage, two trained clinical pharmacists (Hu and Wang) independently reviewed each medical record for the presence of hepatotoxicity. The following sections of the charts were reviewed: basic patient information, diagnostic and progress notes, medication charts, laboratory data, surgical records, nursing flow sheets, and admission and discharge documents. In the second stage, a physician reviewed all medical records identified in the first stage to determine the presence of hepatotoxicity. Disagreements were resolved through a team discussion. Because the clinical interventions usually preceded patients reaching clinical diagnostic criteria of drug-induced liver injury [34], hepatotoxicity was defined as elevated liver enzymes > 1.25 of the upper limits of normal (ULN) and outcomes of liver failure, fibrosis, cirrhosis, or death. The hospital standard cut-off values for ALT are 40 IU/L for women and 50 IU/L for men. AST values are 35 IU/L for women and 40 IU/L for men. Alkaline phosphatase (ALP) values are 135 IU/L for women and 160 IU/L for men. Data collection was carried out from September 2020 to January 2021.
Based on data from included patients’ records, risk factors were screened from multiple patient characteristics to establish a prediction model. Specifically, the following variables were documented: age, gender, height, weight, alcohol use, history of liver diseases (hepatitis B, hepatitis C, and nonalcoholic fatty liver disease), admission, discharge, blood lipid level, antibiotics, other immunosuppressive agents, and Chinese patent medicines. The scores of all risk factors were calculated using the machine learning method and represented by a ranking figure. The factor with a higher score had a more significant impact on the occurrence of hepatotoxicity. Factors with a score of zero were removed because they did not affect the prediction. A Shapley Additive Explanations (SHAP) figure demonstrated the positive or negative correlations between risk factors and hepatotoxicity. Risk factors with a large sample size would affect their impact on the SHAP figure. The SHAP figure was developed by using Python software (version 3.7, Python Software Foundation, Wilmington, DE, USA)
## 2.3. Model Development
Missing data were imputed using the missForest method, and variables with more than $30\%$ missing data were discarded [35]. Patients included were randomly stratified (8:2) into the training set for modeling development and the testing set to evaluate the performance of the models. Using the selected risk factors as covariates, eight machine-learning models were established and analyzed using algorithms including eXtreme Gradient Boosting (XGBoost), AdaBoost, CatBoost, Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LightGBM), Tree-based Pipeline Optimization Tool (TPOT), Random Forest (RF), and Artificial Neural Network (ANN). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, representing the overall ability to classify and predict, is considered the primary metric for evaluating and comparing models. The accuracy, precision, sensitivity, specificity, recall, F1 scores, and average precision (AP) of precision-recall curve were also calculated. These metrics were used to assess the model performance comprehensively. The best-performing model was selected to establish a hepatotoxicity prediction model associated with low-dose MTX. The missForest method and machine learning models were developed and validated with open-source packages in Python software (version 3.7).
## 2.4. Statistical Analysis
Categorical variables were summarized using frequency counts and percentages, and continuous variables were presented as means with standard deviations (SD) or medians with ranges. Comparisons between the training set and the testing set were made using the nonparametric Mann–Whitney U test for continuous variables and the χ2 test for categorical variables. By convention, p values of less than 0.05 were considered statistically significant. These analyses were performed using the SPSS 25.0 software (IBM Information Management, Chicago, IL, USA).
## 3.1. Study Population
A total of 2080 medical records were registered in the cohort during the study period, and 782 patients were enrolled in this study. The following patients were excluded: 171 had duplicate records, 588 were on high-dose MTX, and 539 had low-dose MTX as discharge medication (Figure 1). Among the patients enrolled, the mean age was 47.85 ± 15.56 years (range from 10 to 87 years), and the females represented $54.99\%$ ($\frac{430}{782}$). The average body mass index (BMI) was 22.72 ± 3.91 kg/m2 (range from 13.27 to 41.14 kg/m2). A total of 279 ($35.68\%$) patients experienced hepatotoxicity. Among these variables analyzed, BMI had 53 missing data points ($6.78\%$) imputed using the missForest method. There was no significant difference between the processed data and the original data. The enrolled patients were divided into training and testing sets in a ratio of 8:2, with 625 and 157 patients, respectively. There were no significant differences in any variables between the training and testing sets ($p \leq 0.05$) (Table 1).
## 3.2. Model Performance
The visual comparisons of the eight models in the total population are shown in Figure 2, including the precision-recall and the ROC curves. Random Forest achieved the highest AUC of 0.97, followed by XGboost (AUC = 0.94), Catboost (AUC = 0.91), LightGBM (AUC = 0.87), and TPOT (AUC = 0.78). The ROC curves of Adaboost, ANN, and GBDT were low, only 0.69, 0.65, and 0.53, respectively. The precision, accuracy, sensitivity, specificity, recall, and F1 values of the eight models are shown in Table 2.
Adaboost and Random Forest had the highest accuracy ($64.33\%$). Adaboost had the highest precision value ($51.35\%$), followed by GBDT ($50.94\%$). GBDT had the highest sensitivity value ($41.07\%$), followed by Adaboost ($33.93\%$) and XGboost ($33.93\%$). GBDT had the highest specificity value ($30.69\%$), followed by XGboost ($24.75\%$). GBDT had the highest recall value ($41.07\%$), followed by Adboost ($33.93\%$) and XGboost ($33.93\%$). GBDT had the highest F1 value ($41.82\%$), followed by Adaboost ($40.86\%$). These results showed that Adaboost had slight advantages in precision and accuracy with good recall, sensitivity, and F1 values. Adaboost had a significantly lower AUC than Random Forest (0.69 versus 0.97). *After* general consideration of the prediction performance, Random Forest was selected to predict the hepatotoxicity associated with low-dose MTX.
## 3.3. Hepatotoxicity and Risk Factors
A total of 279 patients experienced hepatotoxicity, with an incidence rate of $35.68\%$. The importance score ranking in the Random Forest model is shown in Figure 3. Importance scores were above zero for all risk factors, indicating that they had a greater or lesser impact on prediction. Among risk factors, the highest score was BMI (0.237), followed by age (0.198), number of drugs (0.151), and number of comorbidities (0.144), demonstrating their importance in hepatotoxicity associated with low-dose MTX.
The SHAP values of the risk factors are shown in Figure 4. When analyzed by the following risk factors (the number of comorbidities, the number of drugs, the use of antibiotics, male gender, the use of alcohol, infectious liver disease, dyslipidemia, and the history of kidney disease). The color of the dot became redder as the SHAP value increased. The color was bluer when the SHAP value decreased. The color changes showed degrees of the positive impact of these factors on the risk of hepatotoxicity. In contrast, risk factors, including BMI and doses of folic acid, showed negative effects. Type 2 diabetes, taking MTX for the first time, other immunosuppressive agents, age, and Chinese patent medicines showed unclear influence.
## 4. Discussion
An effective prediction model is necessary to prevent the hepatotoxicity associated with low-dose MTX. In real-world studies, the variables are not independent but are related nonlinearly. Multivariate analysis methods are challenging for capturing complex relationships. Therefore, we innovatively attempted to apply machine-learning methods that can capture nonlinear relationships between variables. Machine learning can explore risk factors and establish a prediction model for hepatotoxicity associated with low-dose MTX through data learning. Our retrospective study analyzed 15 risk factors for hepatoxicity. The BMI with missing data was imputed using the missForest method, which has been shown to successfully handle missing values, particularly in data sets that include different variables [35]. The results did not show significant differences between the processed and original data.
The eight machine learning methods, including XGBoost, AdaBoost, CatBoost, GBDT, LightGBM, TPOT, RF, and ANN, were applied to establish a prediction model. In these methods, the XGBoost, AdaBoost, CatBoost, GBDT, and LightGBM are boosting algorithms in machine learning. GBDT can combine the predictions from multiple decision trees to generate the final predictions, while it can hardly be adapted to dynamic online data generation, and it tends to be ineffective when facing sparse categorical features [36]. The working procedure of XGBoost is the same as GBDT. XGBoost includes a variety of regularization techniques that can reduce overfitting and improve overall performance, which makes XGBoost slightly better than GBDT. LightGBM is a fast, distributed, high-performance gradient-boosting framework based on a decision tree algorithm. LightGBM uses a histogram-based algorithm, i.e., it buckets continuous feature values into discrete bins that fasten the training procedure [37]. CatBoost is also based on GBDT and has the following two innovations: ordered target statistics and ordered boosting [38]. Therefore, CatBoost works well with the default set of hyperparameters, and the users do not have to spend a lot of time tuning the hyperparameters [38]. Adaboost is relatively robust to overfitting in low-noise datasets. While it is easily defeated by noisy data, the efficiency of the algorithm is highly affected by outliers as the algorithm tries to fit every point perfectly [39]. Random *Forest is* a bagging algorithm that uses bootstrap aggregation of multiple regression trees to reduce the risk of overfitting and combine the predictions of many trees to produce more accurate predictions [40]. Therefore, Random Forest has a good classification effect for most data. TPOT can automatically optimize feature transformation, feature selection, feature construction, model selection, and parameter optimization via genetic programming using a tree-based structure [41]. The design of ANNs is based on the human brain’s neural network. Neurons in the different layers have their own missions to solve problems, which can be analogous to factory production lines [42]. As a type of parallel distributed system driven by mass data, ANNs are free from the requirements of logical or mathematical associations known beforehand [42].
The performance of different machine learning algorithms should be based on the characteristics of the dataset. Therefore, the choice of models should be based on the calculation results. The results showed that these machine algorithms performed well, especially the Random Forest. The Random Forest showed that its AUC was 0.97. The accuracy and precision were $64.33\%$ and $50.00\%$, respectively. Both the recall and the F1 scores were satisfactory. Random Forest outperformed other models selected to build the prediction model for hepatotoxicity associated with low-dose MTX.
Analysis of risk factors showed that all 15 variables helped predict low-dose MTX-related hepatotoxicity. The top ten significant risk factors included BMI, age, number of drugs and comorbidities, doses of folic acid, antibiotic use, gender, immunosuppressive agents, taking MTX for the first time, and alcohol use, suggesting physicians should pay more attention to these factors and take the corresponding prevention measures. BMI was considered the most critical risk factor, which had a negative relationship with hepatotoxicity, demonstrating that patients with lower BMI were more likely to experience hepatotoxicity. Therefore, the dose of MTX should be individualized based on height and weight to avoid hepatoxicity. Male gender was also identified as an important risk factor in our study. However, the causal relationship between gender and hepatotoxicity associated with low-dose MTX remains controversial [43,44] and requires further research.
The importance of the number of drugs, the number of comorbidities, and the use of antibiotics was also confirmed. As the primary organ for drug metabolism, the liver is more vulnerable to damage by drugs, active metabolites, or drug interactions [45,46,47]. Multiple drug treatments and comorbid diseases can increase the risks of polypharmacy, drug interactions, and even medication errors [48,49], increasing the risk of hepatotoxicity. Antibiotics are the most common cause of liver damage [50]. However, the potential for liver injury caused by antibacterial drugs was underestimated [51]. Several real-world studies showed that antibiotic-induced liver injury ranged from $13.5\%$ to $65\%$ [52,53,54]. Therefore, to avoid hepatotoxicity during MTX therapy, simplifying treatment regimens should be an important measure for the benefit of patients.
Alcohol consumption is well known to harm the liver, particularly in excess [55]. The American College of Rheumatology and the British Society of Rheumatology recommend limiting alcohol intake for patients on MTX treatment [56,57]. Similarly, we found a positive relationship between alcohol use and hepatotoxicity associated with low-dose MTX. Although the importance score for alcohol consumption was not high in this study due to the relatively small number of patients who drank alcohol, we still recommend limiting or avoiding alcohol intake.
Supplementation with folic or folinic acid during MTX treatment can ameliorate ADEs. Worldwide guidelines currently support the coadministration of folic acid with MTX. The recommended doses range from 0.5 to 2 mg per day [57,58]. However, several studies have suggested that high-dose folinic acid supplementation may reduce the beneficial effects of MTX [59,60,61]. In our study, patients taking high-dose folic acid had a high risk of liver injury. Among patients taking more than 15 mg of folic acid a week, the incidence of liver injury was $41.94\%$. In contrast, the incidence of liver injury in patients taking 5–10 mg/week was only $34.54\%$. Furthermore, 59 patients in this study did not take folic acid during MTX treatment, and their liver injury rate was up to $45.76\%$. Therefore, we recommend daily supplementation with folic acid during MTX treatment.
Metabolic syndrome is a biochemical and clinical condition characterized by visceral obesity, dyslipidemia, hyperglycemia, and hypertension [62,63]. Disorders associated with metabolic syndrome can be significant risk factors for fibrosis and the progression of liver damage. Type 2 diabetes contributed to the biological processes that drove the severity of nonalcoholic fatty liver disease, which was the leading cause of developing chronic liver diseases [64,65]. Several studies showed that nonalcoholic steatohepatitis and hyperlipidemia contributed to MTX hepatotoxicity in patients with psoriasis [43,66]. These were consistent with our results that type 2 diabetes and hyperlipidemia were significant risk factors for hepatotoxicity associated with low-dose MTX.
Hepatitis B and hepatitis C can cause liver damage, increasing the risk of liver toxicity and even liver fibrosis and cirrhosis in patients taking MTX [67]. Infectious liver disease was one of the important risk factors for hepatotoxicity in this study, while its importance score was not high. The reason might be that patients with infectious liver disease were only $4.1\%$ of the study sample. For health and safety reasons in China, many physicians choose other alternative treatments for patients with infectious liver disease instead of MTX. Similarly, only six patients had a history of kidney disease in this study. Therefore, the importance score for the history of kidney disease was low.
Our study has the following limitations [1] knowledge about specific risk factors is still lacking in this study. Although factors such as taking MTX for the first time, other immunosuppressive agents, age, and Chinese patent medicines affected the occurrence of hepatotoxicity, the direction of influence of these factors was unclear. These factors could be influenced by other factors, such as drug regimens (the number of drugs and drug interactions), gender, and BMI; [2] the sample size was small. Future studies should include more patient data from different health care centers; [3] long-term studies are required to verify the association of these risk factors with liver fibrosis or cirrhosis.
## 5. Conclusions
Machine learning can be applied to establish the prediction model for low-dose hepatotoxicity associated with MTX. The model can help to improve medication safety in patients taking methotrexate in clinical practice. However, due to the above limitations, further studies are required to test our findings.
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|
---
title: 'Artificial Intelligence Software for Diabetic Eye Screening: Diagnostic Performance
and Impact of Stratification'
authors:
- Freya Peeters
- Stef Rommes
- Bart Elen
- Nele Gerrits
- Ingeborg Stalmans
- Julie Jacob
- Patrick De Boever
journal: Journal of Clinical Medicine
year: 2023
pmcid: PMC9967595
doi: 10.3390/jcm12041408
license: CC BY 4.0
---
# Artificial Intelligence Software for Diabetic Eye Screening: Diagnostic Performance and Impact of Stratification
## Abstract
Aim: To evaluate the MONA.health artificial intelligence screening software for detecting referable diabetic retinopathy (DR) and diabetic macular edema (DME), including subgroup analysis. Methods: The algorithm’s threshold value was fixed at the $90\%$ sensitivity operating point on the receiver operating curve to perform the disease classification. Diagnostic performance was appraised on a private test set and publicly available datasets. Stratification analysis was executed on the private test set considering age, ethnicity, sex, insulin dependency, year of examination, camera type, image quality, and dilatation status. Results: The software displayed an area under the curve (AUC) of $97.28\%$ for DR and $98.08\%$ for DME on the private test set. The specificity and sensitivity for combined DR and DME predictions were 94.24 and $90.91\%$, respectively. The AUC ranged from 96.91 to $97.99\%$ on the publicly available datasets for DR. AUC values were above $95\%$ in all subgroups, with lower predictive values found for individuals above the age of 65 ($82.51\%$ sensitivity) and Caucasians ($84.03\%$ sensitivity). Conclusion: We report good overall performance of the MONA.health screening software for DR and DME. The software performance remains stable with no significant deterioration of the deep learning models in any studied strata.
## 1. Introduction
The number of people with diabetes mellitus (DM) is rapidly increasing, with up to 642 million cases expected by 2040 [1,2]. More than $40\%$ of these diagnosed persons will develop retinopathy. Diabetic retinopathy (DR) and diabetic macular edema (DME) are the main ophthalmological complications of DM, with DR being the leading cause of blindness and visual disability in the working-age population. The risk of such vision loss can be reduced by annual retinal screening and early retinopathy detection to refer cases for follow-up and treatment. The necessary fundus photographs for such screening can be easily obtained non-invasively in an outpatient setting. Implementing a nationwide screening program based on fundus photography resulted in DR no longer being the leading cause of blindness certification in the United Kingdom [3,4,5].
However, as long as an ophthalmologist interprets retinal images manually, this screening procedure will always be labor-intensive and expensive, thereby complicating large-scale accessible implementation in many countries. New technologies facilitate the development of care solutions that keep our health system manageable and affordable, especially for diseases of affluence such as DM and associated eye health complications. To realize this ambition, experts in technology and medicine collaborate on solutions to reduce the workload caused by manual grading, a task for which artificial intelligence (AI) is well suited [4,5].
AI research in healthcare accelerates with applications achieving human-level performance across various fields of medicine. The use of AI can range from organizational help to surgical applications, with image classification for diagnostic support being one of the main areas of interest [6,7]. IB Neuro™ (Imaging Biometrics, Elm Grove, WI, USA) was the first FDA-approved AI application in 2008 for detecting brain tumors on MRI images. Multiple applications have been approved since then, many in medical imaging domains such as radiology. Some applications go beyond diagnosis and enter therapeutic fields such as radiotherapy [7].
Deep learning, a subtype of AI, was introduced not so long ago for the automated analysis and classification of images. In 2016, Gulshan et al. published a landmark paper on a deep learning algorithm with high sensitivity and specificity to classify referable DR [8]. Later papers showed that deep learning algorithms’ diagnostic accuracy is at least comparable to the assessments done by clinicians [9,10,11,12]. Abràmoff and colleagues published their paper on an autonomous AI-based diagnostic system for detecting diabetic retinopathy in 2018 (IDx-DR (Digital Diagnostics, Coralville, IA, USA)). This work led to the first FDA-permitted marketing of an AI-based medical device for automated DR referral [13]. Since then, multiple AI devices have been developed around the world [14].
These developments are exciting, but the clinical community is not yet widely adopting the new tools. Several bottlenecks are at the basis of this hesitation. First, most algorithms are reported by the scientific community and have not been developed into easy-to-use software for primary or secondary care. Second, algorithms mostly report on DR performance, but when considering diabetic eye screening, both DR and DME are relevant. Third, the performance evaluation of the algorithms is done under limited test conditions. Finally, discussions are ongoing at different levels in the healthcare sector about the medico-legal position of AI-based screening and its integration into the patient care path.
AI accomplishes a specific task on previously curated data, typically from one setting. Ideally, datasets to develop an algorithm are sufficiently diverse to represent the population, with metadata such as age, ethnicity, and sex to allow for performance analysis. In reality, health data lack standardization and contain a bias due to variance in human grading. The actual patient populations are more diverse than those in commonly used datasets [15,16]. Medical data with high-quality labels is challenging to collect, and the General Data Protection Regulation (GDPR) and other privacy-preserving regulations restrict medical data usage. Therefore, most AI models are trained with datasets that have limited heterogeneity. Predictions often do not generalize to different populations or settings. Analyses on subpopulations (e.g., ethnicity) are seldom done, leaving uncertainty that model performance can be reliably extrapolated to new, unseen patient populations [17]. As a result, the performance promised in scientific publications is often not reached in clinical practice, and existing inequalities and biases in healthcare might be exacerbated [17]. Some of these problems can be overcome by executing a prospective clinical trial incorporating pre-chosen metadata and ensuring a relevant distribution amongst specific subpopulations [13]. However, this is a time-consuming and expensive solution, and this approach only allows model evaluation in a limited number of clinical centers.
International organizations such as the International Diabetes Federation, the International Council of Ophthalmology, the World Council of Optometry, and the International Agency for the Prevention of Blindness support the vast clinical need for widespread and convenient eye health screening tools for persons with diabetes as part of integrated diabetes care [18]. From this perspective, we present an evaluation of a diabetic eye screening software available as a certified medical device for automated DR and DME detection. We report the performance of the deep learning model underlying the software using private and publicly available datasets. Using stratification analyses, we studied the performance in predefined subgroups based on clinically relevant parameters, thereby taking an essential step toward improving the model evaluation process and its robustness during deployment.
## 2.1. MONA.health AI-Based Screening Software
The MONA.health diabetic eye screening software MONA DR DME (Version 1.0.0; MONA.health, Leuven, Belgium) (https://mona.health/, accessed on 31 January 2023) evaluated in this paper is commercially available as a Class 1 certified medical device under the European Union Medical Device Directive (MDD, Council Directive $\frac{93}{42}$/EEC of 14 June 1993 concerning medical devices, OJ No L $\frac{169}{1}$ of 7 December 1993). The software needs one fundus image per eye centered between the macula and optic disc for algorithmic processing and reporting three diabetic eye screening results per patient (DR, DME, and a combination of both). The essential processing steps are presented in Figure 1.
Before presenting the images to the models, they are preprocessed to increase uniformity. This consists mainly of resizing and contrast enhancements, thereby reducing the effects of illumination and fundus pigmentation. Next, the quality of an image is assessed by two models: a model analyzing whether the image is a fundus image or not and a second model evaluating the quality of the image. The second model is trained based on image quality labels according to the EyePACS protocol [19]. An image passing this quality control step is analyzed for referable DR and DME.
The core of the MONA.health screening software consists of two sets of deep learning models, a DR ensemble and a DME ensemble. Each ensemble is a set of models differing in model architecture and training details such as optimizer, learning rate, and the number of epochs trained. All models used are convolutional neural networks (CNN), with different architectures (ResNet, EfficientNet, Xception, InceptionV3, DenseNet, and VGG). More specifications can be found in Figure A1 [20,21,22,23,24,25]. The results of these individual models are averaged to generate a final output. The resulting output of each ensemble is fundamentally different: an estimation of grade by regression in the case of DR versus a probability of having the disease for DME. Therefore, the models run in parallel instead of having one model that makes all predictions.
A threshold value was computed for each ensemble to achieve an operating point on the receiver operating curve (ROC) with a sensitivity of $90\%$ for diagnosing referable DR or the presence of DME. These thresholds remained fixed for all subsequent analyses. If the maximal predicted value for at least one eye is higher than these fixed threshold values, the individual is marked for referral for one or both diseases.
## 2.2. Private Test Set for Algorithm Testing
The fundus images for evaluating the MONA.health diabetic eye screening software originates from the EyePACS telemedicine platform containing patient visits from screening centers in the USA. The characteristics are documented in Table 1. Note that the disease gradings originate from the telemedicine platform without regrading [26].
One fundus image per eye, centered between the optic disc and macula, was used for each patient encounter. Relevant metadata, such as age, sex, ethnicity, insulin dependency, and camera type, are available for stratification analysis. The DR grading is consistent with the internationally adopted International Clinical Diabetic Retinopathy (ICDR) severity level [20]. Macular thickening is used in ICDR and Early Treatment Diabetic Retinopathy Study (ETDRS) classification for DME, but cannot be appreciated on standard fundus photographs. Therefore, the presence of hard exudates within one disc diameter of the macula is the surrogate parameter for DME [27,28].
We implemented a filtering procedure to remove images from persons under 18 years, with laser scars, signs of vascular occlusion or cataracts, and images that the image quality models rejected. The image quality models reject poor-quality images for which no interpretation would be possible for a human or an algorithm. Examples of images of sufficient (adequate, good, and excellent) and insufficient quality can be found in Figure A1. The resulting test sets comprised 16,772 patient encounters suitable for DR evaluation (prevalence of referable DR: $48.8\%$) and 16,833 patient encounters for DME evaluation (prevalence of DME: $11.8\%$). A total of 16,733 patient encounters were suitable for both evaluations accounting for the large overlap between both datasets.
The MONA.health software performance was evaluated by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC). These values were calculated for DR, DME, and the combined prediction. The dataset of overlapping patient encounters was used for the combined analysis. Additional analyses were done on ICDR grade 3 and grade 4 retinopathy subgroups since these consist of patients with vision-threatening DR.
## 2.3. Publicly Available Datasets for Algorithm Testing
The second series of evaluations used publicly available datasets containing DR and DME labels at the level of the screened individual. The following datasets were available: the Kaggle DR test set (population: USA; $$n = 5000$$ patients; multiple cameras) [29], Messidor-2 (population: France; $$n = 874$$ patients; Topcon NW6) [30,31], and the Messidor-2 Iowa reference (population: France; $$n = 874$$ patients; Topcon NW6) [32]. The Messidor-2 and Messidor-2 Iowa references use the same image data set but a different grading protocol [32].
## 2.4. Stratification Analysis
We performed stratification analyses for patient-based detection of referable DR and DME. The subgroup investigations were done for ethnicity, age, sex, insulin dependency, dilatation status, year of examination, camera type, and image quality. The $95\%$ CIs were calculated via the Percentile Bootstrap Method. The dataset was sampled with replacement for 10,000 repetitions. The size of the sample was always the same size as the data sampled it was from. A sample size calculation was done for the stratified groups based on a pre-specified FDA inferiority hypothesis, namely $75\%$ sensitivity and $78\%$ specificity [13]. A one-sided hypothesis test with binomial distribution was carried out with an overall one-sided $5\%$ Type 1 error, $90\%$ power, and an effect size of $10\%$. A sample size of 541 evaluated subjects is needed, including 338 subjects with the disease and 203 subjects without the disease to ensure the calculated metrics represent the group. Results for stratified groups with a sample size lower than the computed sample size should be interpreted cautiously since this could be a chance finding. Computations were done in R with the pwr package [33].
## 3.1. Test Set and Public Datasets
The MONA.health diabetic eye screening software had an excellent performance on the private test set when predicting referable DR and the presence of DME. The area under the curve (AUC) was the primary metric to evaluate the diagnostic prediction, with a patient-based prediction of referable DR of $97.28\%$. A specificity of $94.62\%$, a sensitivity of $90.67\%$, a PPV of $94.14\%$, and an NPV of $91.40\%$ were recorded for the $90\%$ sensitivity setpoint. The sensitivity was 99.39 and $99.54\%$ when predicting DR grade 3 (severe non-proliferative DR) and grade 4 (proliferative DR), respectively. For DME prediction, the AUC was $98.08\%$ with a specificity of $94.53\%$, a sensitivity of $90.75\%$, a PPV of $68.57\%$, and an NPV of $98.71\%$. The specificity and sensitivity for the combined DR and DME predictions were 94.24 and $90.91\%$, respectively. An overview of the performance metrics can be found in Table 2.
The AUCs obtained on the public datasets were equally high. The values ranged from 96.91 to $97.99\%$ for referable DR. A minimal change in the operating point corresponding to the predefined threshold is noted, as can be observed by inspecting the sensitivity and specificity metrics in Table 2. Similar observations are made for DME on the Messidor-2 dataset. All results are above the proposed minimum requirements set by the FDA in the pre-specified inferiority hypothesis. The evaluation of DME classification could not be reported for the Kaggle test set and Messidor-2 Iowa’s reference because the relevant disease labels are unavailable for these datasets. The referable label in the Iowa reference was based on the assessment of DR and DME and only indicated being referable for either of these diseases. All publicly available datasets were used in their entirety without selection.
## 3.2. Stratification Analysis
We report the sensitivity and specificity for detecting referable DR (Figure 2) and DME (Figure 3) when dividing the private test set into subgroups according to attributes relevant to the persons with diabetes and the eye screening procedure. The results are for the model with the fixed threshold computed for the $90\%$ sensitivity setpoint. Detailed numerical values of the analysis are in Appendix A (Table A1, Table A2, Table A3, Table A4, Table A5, Table A6, Table A7 and Table A8).
A high sensitivity (exceeding $90\%$ on average) for detecting referable DR is obtained for most age groups, with only a decreased sensitivity of $82.51\%$ ($95\%$ confidence intervals can be found in Appendix A) in the 65+ age group. Specificity remained high at $94.24\%$ in this age group. No differences between the age groups are encountered for DME detection.
DR referral in the groups defined based on ethnicity (Figure 2B) had a high AUC of $96.38\%$ observed in the Caucasian group, with lower values in the Asian ($95.26\%$) and African ($94.80\%$) subpopulations. However, sensitivity values are lower in the Caucasian ($84.03\%$) and higher in the Latin American ($91.95\%$) populations. The AUC was high for all subgroups (range 96.67–$99.34\%$) for DME referral (Figure 3B). Decreased sensitivity and specificity are noted in the Asian population and lower specificity in the Latin American population.
The diabetic eye screening software showed excellent overall performance, without any relevant differences when the dataset was divided according to the sex or insulin dependency status of the patients. A difference in sensitivity/specificity division can be perceived at the $90\%$ sensitivity operating point in the latter group for DR. Considering DME, a lower specificity of $91.72\%$ was noted in the insulin-dependent group compared to $95.74\%$ in the non-insulin-dependent group. We refer the reader to Appendix A for detailed reports on this analysis.
Stratifying the data according to the year of examination showed good performances for DR referral, with a slight decrease in sensitivity to $89.32\%$ for the oldest images (Figure 2C). A high sensitivity but lower specificity is observed in this group for DME (Figure 3C). The dilatation status during fundus photographing did not affect the model performance (Appendix A).
The AUCs were comparable between the different fundus cameras, with values between 96.30 and $98.22\%$, except for the Optovue iCam 100 (Visionix, Pont-de-l’-Arche, France) ($94.46\%$). High sensitivity is observed for DME using the Canon CR-2 camera (Canon, Tokyo, Japan) ($96.84\%$), while the values for the other cameras ranged from 83.04 to $91.25\%$ (Figure 3D). Sensitivity for DME is lower for images obtained on the Canon CR-1 (Canon, Tokyo, Japan) ($83.04\%$) camera.
## 4. Discussion
We report a systematic retrospective evaluation of the MONA.health diabetic eye screening software that analyzes fundus images using artificial intelligence and summarizes DR and DME classification outputs as a single result to assess the patient referral status. Our investigations were performed on a large, multi-center, private test set from a US-based screening network and publicly available datasets regularly used to benchmark diabetic eye detection algorithms. The private test set reported $90.91\%$ sensitivity and $94.24\%$ specificity for referring a person because of DR or DME. These values are higher than the pre-specified superiority endpoints of $85\%$ sensitivity and $82.5\%$ specificity proposed in the work of Abràmoff and coworkers [13]. It is relevant to say that the latter values are for a prospective study while we performed a retrospective study. Nevertheless, our performances are comparable to previously published work [13,34,35,36,37,38,39,40,41]. Our study adds value to the research field by reporting the results of data stratification to study differences in model performance in subpopulations. Such an analysis is essential to assess the usability of the software in clinical practice, thereby providing a starting point for better insights into potential hurdles when incorporating AI-based decision support software in clinical practice.
All DR grades beyond mild DR are considered referable and justify a physical examination by an ophthalmologist. However, the higher the retinopathy grade, the higher the risk of vision loss and the more urgent the need for referral. Therefore, high sensitivities are even more critical for detecting severe non-proliferative DR and proliferative DR. Sensitivities of 99.39 and $99.54\%$ were obtained for these cases of vision-threatening DR, indicating that the vast majority of cases will be accurately referred by the software. A substantial difference in PPV, the probability that subjects with a positive screening test truly have the disease, is noted when considering the diagnosis of DME ($68.75\%$) compared to DR ($94.14\%$). This difference is likely attributed to the lower disease prevalence of DME ($11.76\%$) in the test set.
The performance was analyzed on the publicly available Kaggle, Messidor-2, and Messidor-2 Iowa reference datasets. The algorithm has a robust performance, with only slight decreases in AUC and sensitivity for DR on the publicly available Kaggle test set. This observation may be attributed to the fact that the Kaggle test set only contains images dating before 2015 [29]. We observed a comparable decrease in sensitivity in our test set for older images (Figure 2C). For the Messidor-2 dataset, AUC values are comparable to those reported on the test set for the regular and Iowa reference. However, a decrease in specificity and an increase in sensitivity are noted for DR. This rebalance between sensitivity and specificity indicates that the chosen threshold is suboptimal for this specific dataset. These findings are consistent with those of Gulshan et al. [ 8]. A possible explanation for this shift in operating point is the homogeneity of the dataset (one camera type and only patients from France with a less diverse ethnic mix) [30,31]. However, the chosen threshold might still result in a performance closer to the $90\%$ sensitivity operating point in a more variable real-life setting than shown on the Messidor-2 dataset. This hypothesis is supported by the analysis results on the more extensive test set. A decreased sensitivity for DME is observed on the Messidor-2 data compared to our own test set. A shift in operating point is the most likely explanation for this observation. This effect is larger in the Iowa reference labeling. This might be attributed to a difference in labeling between these two references. For the same images, the patient level prevalence is $21.7\%$ in the Iowa labeling [32] compared to $30.9\%$ in the standard labeling (calculated based on [8]).
The performance evaluations of AI algorithms detecting DR and DME can yield good results, but guaranteeing high model performance for all relevant subpopulations is still a significant challenge. We performed an extensive stratification analysis in the current study to investigate possible differences in performance. This evaluation has not been reported to our knowledge.
The algorithm’s performance for DR and DME classification was stable in the different age categories up to 65 years. Beyond the patient age of 65 years, a decrease in sensitivity for DR detection to $82.51\%$ was recorded. Acquiring high-quality fundus images can be more challenging in the elderly due to patient-related factors such as corneal changes, vitreous floaters, and cataract formation. However, the lower sensitivity in DR detection cannot be solely attributed to this factor since no remarkable differences were noted in the stratification analysis based on image quality. No alternative explanations could be found based on the performed stratifications.
The MONA.health software is registered as diabetic eye screening software in Europe. Of note, ethnicity distribution is different between the European and USA-based populations of the private test set. An ethnicity stratification was performed to aid the software performance evaluation. The biggest relevant deviations were found for sensitivity in the Caucasian subgroup ($84.03\%$) and specificity in the Latin American subgroup ($91.33\%$). A detailed analysis of the positive cases in this Caucasian group was done, showing that for Caucasians, $33.3\%$ of the referable cases are based on the presence of retinal hemorrhages with/without micro-aneurysms without any other lesion types (such as cotton wool spots, hard exudates, IRMA, venous beading, new vessels, fibrous proliferation, preretinal, or vitreous hemorrhage). By comparison, this is only the case in $23.5\%$ of all non-Caucasian cases and $22.2\%$ of Latin American cases (the largest subgroup amongst positive cases). We assume DR detection is more difficult in the Caucasian population due to a lower prevalence of other signs besides hemorrhages. Our medical retina experts’ analysis of all Caucasian false negatives revealed that dust spots and shadows had been mislabeled as hemorrhages. Previous research showed that artifacts might be an important reason for intra- and interobserver variability and mislabeling [15]. Nevertheless, the achieved performances remain above the non-inferiority hypothesis [13].
The prevalence of referable DR is higher in the Latin American population than in the Caucasian population [42]. Increased prevalence may be associated with a higher likelihood of more severe disease, which is more easily detected [43,44]. This might contribute to the observed differences. Furthermore, $30\%$ of patients are of “unspecified” ethnic origin, making many images unavailable for the stratification analysis. A drop in specificity for the Latin American subgroup is observed. Considering that the AUC remains high in this group, this observation may indicate that there is a more optimal threshold for this subgroup. The high disease prevalence might reinforce this effect in this subgroup. Sensitivity and specificity metrics for the Asian and African subgroups should be interpreted cautiously. The sample size of these two groups was under the minimal sample size of 541, making it hard to draw any meaningful conclusion.
Multiple parameters were explored to stratify the analysis for disease severity. Due to the low quality of specific labels such as HbA1c values and years since diagnosis (missing data, impossible values), these parameters were not kept for analysis. Therefore, insulin dependency was selected as a surrogate parameter for disease severity. This stratification showed a difference in sensitivity/specificity division for DR (93.94/$88.55\%$ vs. 87.81/$96.22\%$), meaning that the ideal operating point for $90\%$ sensitivity differs between the two groups. In real life, only one threshold can be used, and a mix between insulin-dependent and independent patients is expected, balancing the differences between both groups.
Considering the year of examination, intuitively, one would expect a lower performance when analyzing older images since image quality, resolution, and ease of use have increased over the years due to technological improvements. This statement appears to hold for DR. However, for DME, increased sensitivity and decreased specificity are seen for the older images. At the same time, the AUC remained high, indicating that older images might also benefit from a different threshold. No notable discrepancies between results were recorded when considering camera type. Regarding DME, a lower sensitivity was observed for the Canon CR-1 camera (Canon, Tokyo, Japan).
This study comes with strengths and limitations. We report the performance of the MONA.health software that uses one fundus image of the left eye and one of the right eye to generate a report about the patient’s referral status for DR and DME. One fundus image per eye results in higher patient comfort and lower operational costs, making the software easy to use. This software was developed explicitly for diabetic eye screening, and its operational settings balance sensitivity, specificity, and cost-effectiveness [45]. The referral threshold was computed and subsequently fixed for subsequent usage in the software [45]. An additional study strength is the evaluation of the software using a sizable private test set and publicly available datasets. Furthermore, the stratification analysis investigated the diagnostic performance of such an AI-based algorithm for the first time. Overall, we report stable high-performance results using widely used metrics such as AUC, sensitivity, and specificity. We highlight the importance of stratification from a research and clinical perspective by illustrating potential hurdles to overcome before implementing AI in daily practice. The stratification illustrates that comparisons based on AUC can be deceiving since most strata have a very high AUC, but the resulting performances for a predefined threshold may shift. In a production setting, one cannot tailor this threshold to the specific needs of the context since this would require a new and elaborate validation study to prove effectiveness [45].
The most critical limitation of stratification is that results depend on the initial label’s quality both for the ground truth of the diagnosis and for the metadata. Our research team obtained the private test set from the well-established EyePACS telemedicine platform. The EyePACS protocols for collecting fundus images and diabetic eye screening are reliable. However, the protocols were initially not designed to organize metadata for later use in a stratification analysis to assess AI-based image analysis. We noted several problems regarding this quality during our study, such as impossible numerical values and missing data. A more robust higher quality dataset would be necessary to further improve research on this subject. Nonetheless, patient consent and privacy issues limit obtaining such a dataset, and a post hoc curation of an existing dataset is extremely difficult. A second limitation is the difference between prevalence in the dataset ($48.8\%$) and real-life prevalence, of which reports vary but are considerably lower [46,47,48,49,50,51]. We considered correcting for this difference in our study, but it was decided not to rebalance the dataset to maintain a sufficient number of images. Finally, prospective studies and post-market clinical evaluations are needed to evaluate MONA-health software performance further and support our conclusions. Such studies are currently underway and indexed as clinical trials NCT05260281 and NCT05391659.
## 5. Conclusions
We present a detailed evaluation of the MONA.health AI screening software for detecting referable DR and DME using a single fundus image per eye. Performance analysis shows good overall results. An extensive stratification analysis considered patient characteristics and parameters related to eye screening. We observed variability between the results of the subgroups, but overall performance remained stable with no significant deterioration of the deep learning model in any of the studied strata. We advocate that reporting stratification performances is essential when envisioning a DR screening algorithm in clinical practice, but such results are typically not reported. Our research highlights the importance of high-quality data, thereby forming a basis for the improvement of future research in medical AI by bringing to attention some of its current shortcomings.
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|
---
title: 'Laboratory Findings and Clinical Outcomes of ICU-admitted COVID-19 Patients:
A Retrospective Assessment of Particularities Identified among Romanian Minorities'
authors:
- Alexandra Mocanu
- Voichita Elena Lazureanu
- Ruxandra Laza
- Adelina Raluca Marinescu
- Talida Georgiana Cut
- Suzana-Vasilica Sincaru
- Adina Maria Marza
- Irina-Maria Popescu
- Lucian-Flavius Herlo
- Andreea Nelson-Twakor
- Mircea Rivis
- Felix Bratosinand
- Tamara Mirela Porosnicu
- Alexandru Ovidiu Mederle
journal: Journal of Personalized Medicine
year: 2023
pmcid: PMC9967597
doi: 10.3390/jpm13020195
license: CC BY 4.0
---
# Laboratory Findings and Clinical Outcomes of ICU-admitted COVID-19 Patients: A Retrospective Assessment of Particularities Identified among Romanian Minorities
## Abstract
The Roma population accounts for over $3\%$ (approximately 10 to 15 million) of Romania’s permanent population, and it represents one of Europe’s most impoverished populations. Due to poverty and unemployment, Romania’s Roma minority may have diminished access to healthcare and preventive medicine. The limited existing evidence suggests that the European Roma group has been at a higher risk of becoming ill and dying during the pandemic owing to their lifestyle choices, socioeconomic circumstances, and genetic pathophysiological traits. As a result, the purpose of the present research was to investigate the link between the inflammatory markers implicated and the clinical progression of COVID-19 in Roma patients who were brought to the intensive care unit. We considered 71 Roma patients admitted to the ICU with SARS-CoV-2 infection and 213 controls from the general population with the same inclusion criteria. The body mass index of patients was statistically significantly higher among Roma patients, with more than $57\%$ being overweight, compared with $40.7\%$ in the control group. Frequent smoking was more prevalent in patients of Roma ethnicity admitted to the ICU and the number of comorbidities. We observed a significantly higher proportion of severe imaging features at admission in the group of cases, although this difference may have been associated with the higher prevalence of smoking in this group. The mean duration of hospitalization was longer by 1.8 days than the control group. Elevated ESR levels were observed in $54.0\%$ of Roma patients at admission, compared with $38.9\%$ in the control group. Similarly, $47.6\%$ of them had elevated CRP levels. IL-6 increased significantly at the time of ICU admission, similarly to the significant rise in the CRP levels, compared with the general population. However, the proportion of intubated patients and mortality did not differ significantly. On multivariate analysis, the Roma ethnicity significantly influenced the CRP (β = 1.93, p-value = 0.020) and IL-6 (β = 1.85, p-value = 0.044). It is necessary to plan different healthcare strategies aimed at special populations, such as the Roma ethnicity, to prevent the reduced disparities presented in in this study.
## 1. Introduction
In the majority of patients, SARS-CoV-2 causes no symptoms or only mild symptoms; it is less fatal than other viral infections, even though up to $20\%$ of cases, such as those involving older people and those with multiple comorbidities, may develop severe forms and overactivation of the immune system [1,2,3]. The most common symptoms of COVID-19 are generally nonspecific, including high prevalence rates of fever, tiredness, and a dry cough. On the other hand, interstitial pneumonia, thrombo-embolic events, and acute respiratory distress syndrome (ARDS) are all outcomes and possible severe manifestations of SARS-CoV-2 infection among populations at risk [4,5,6,7,8]. These forms of COVID-19 are likely to be triggered by an overactivation of the immune system, causing a cytokine storm [9,10,11,12].
The excessive inflammation seen in certain patients, particularly those who develop severe disease, is one of the most distinctive characteristics of COVID-19. An overactive immune response that is driven by several different cytokines is one factor that contributes to the development of severe illness [13]. In the research conducted so far, some immune cells and inflammatory mediators have been identified as being involved in the illness process. These markers include lymphokines, cytokines, monokines, tumor necrosis factors (TNF), and interferons, all with autocrine, paracrine, or endocrine effects [14,15]. In order to battle the potentially lethal inflammation, researchers from all over the globe have investigated a wide variety of pharmacotherapeutic medicines, including anti-inflammatory drugs and antivirals, although without any breakthrough discovery in COVID-19 treatment [16,17].
The cytokine storm syndrome is one of the most severe complications that can occur in COVID-19 patients, being triggered by the inflammatory cell infiltration in the lungs, activation of T-helper 1 reactions, and abundant release of proinflammatory cytokines into the circulation [18,19]. The systemic inflammation can cause multiple organ dysfunction syndromes (MODS) and disseminated intravascular coagulation (DIC). Therefore, the prompt treatment of this cytokine storm in its early stage, with the use of immunomodulators, corticosteroids, and cytokine antagonists, is suggested by some specialists to be the most important factor in lowering the death rate of these individuals and determining fewer admissions to intensive care units [20] This treatment can be accomplished by administering these medications when the cytokine storm is in its early stage.
Many COVID-19 patients who exhibit severe SARS-CoV-2 infection are admitted to critical care units and have very high concentrations of inflammatory markers and D-dimers in their serum samples [21]. When evaluating the results of blood tests on patients with severe SARS-CoV-2 infection, it was observed that a very large increase in cytokines, roughly equivalent to an increase of four times or more, is associated with an increased risk of mortality [22]. Additionally, the severity of COVID-19 may be impacted by a number of known and unknown variables, such as certain demographic features, racial disparities, the poverty status of the community, or an ethnic group such as the Roma population.
The findings of a few studies indicate that people of Roma ethnicity, also known as Romani in the European Union or Gypsies as a pejorative form, are likely to be at an increased risk of SARS-CoV-2 infection [23]. In addition, the Roma community is likely to suffer psychological, social, and economic repercussions directly from the pandemic. In addition, it seems that some racial and ethnic groups are more prone to comorbidities that predispose them to poorer COVID-19 results, as well as certain unique genetic characteristics that relate the severity of infection with the demographic profile of those groups. Similarly, it is expected that Roma patients are less likely to be vaccinated against COVID-19; therefore, they might have a more severe response to the viral infection [24,25,26]. To the best of our knowledge, however, there is a paucity of data about the dynamics of SARS-CoV-2 viral manifestations in the Roma population. As a consequence, the objective of this study was to explore the clinical development of COVID-19 in Roma patients concerning the laboratory findings and inflammatory markers that were involved.
## 2.1. Study Design and Ethics
Patients were eligible for participation in the present observational retrospective research provided it was determined that their hospital admission occurred between March 2020 and August 2022. This timeframe encompasses both the pre-COVID-19 vaccination phase and the post-COVID-19 vaccine period. The investigation was conducted at the “Victor Babes” University of Medicine and Pharmacy in Timisoara. More specifically, it took place in the “Victor Babes” Hospital for Infectious Disease and Pneumology under the Department of Infectious Disease. The purpose of this study was to conduct research in retrospect by collecting data from the paper records and digital records of patients diagnosed with COVID-19 who were admitted to the hospital throughout the time period of the study.
As an auxiliary of the “Victor Babes” Hospital for Infectious Disease and Pneumology in Timisoara, the infectious disease clinic affiliated with the “Victor Babes” University of Medicine and Pharmacy operates under the laws of the local commission of ethics that approves scientific research that operates following the International Conference on Harmonization from Helsinki regarding technical requirements for registration of pharmaceuticals for human use. Additionally, the infectious disease clinic is governed by the local commission of ethics laws that approve scientific studies. The research was conducted in a manner that accorded with the ethical standards of the university at which the study was conceived, as well as by the ethics committees of both institutions.
## 2.2. Inclusion Criteria and Variables
A database and patient paper record search were conducted to determine the number of adult Roma patients admitted to the ICU with a COVID-19 diagnosis. Patients were included if they matched the following criteria: [1] being older than 18 years; [2] if their paper records mentioned the Roma minority; [3] being vaccinated or unvaccinated against SARS-CoV-2; [4] having a SARS-CoV-2 infection confirmed by PCR test. According to existing guidelines, the SARS-CoV-2 infection was considered mild, moderate, or severe [27,28]. Severe imaging features were considered for ground-glass opacities involving more than $50\%$ of the lungs on chest X-ray or CT scan [6]. The COVID-19 status was defined by a positive polymerase chain reaction test (PCR) from oropharyngeal and nasal swabs, using a multiplex RT-PCR [29,30]. A predefined patient personal form was used to gather demographic, clinical, and outcome data from electronic medical records and identify the patients’ ethnicity.
Considering that, after January 2021, the COVID-19 vaccination campaign started in Romania, it was considered necessary to stratify the cohort of patients into vaccinated Roma, unvaccinated Roma, and a control group from the general population of patients with SARS-CoV-2 infection, excluding those of Roma ethnicity. Vaccination status was identified with the unique QR code of the European Union COVID-19 vaccination certificate. Patients were vaccinated with the available vaccines in Romania produced by Pfizer/BioNTech (Reinbek, Germany), AstraZeneca (Oxford, UK), Moderna (Norwood, MA, USA), and Johnson & Johnson (New Brunswick, NJ, USA).
Using a convenience sample method, we estimated that at least 27 patients of Roma minority should be included in the analysis to provide proper statistical power. The sample size was calculated for a proportion of Roma ethnicity in Romania of about $3.5\%$, according to the most recent census [31], and the rate of ICU admission of about one-third of the severe cases [32]. Other considerations for the sample size were a $99\%$ confidence level and a $5\%$ margin of error. A total of 71 patients from the Roma population that matched the inclusion criteria were included in the analysis. The control group from the general population was case-matched by age and COVID-19 vaccination status with the Roma group and included 213 patients.
The variables taken into consideration included background data (age, gender, area of residence, occupation, body mass index, smoking status, and alcohol use), the presence of chronic comorbidities (high blood pressure, lung disease, diabetes mellitus, cerebrovascular disease, digestive and liver problems, kidney disease, depression, and malignancy), and COVID-19 transmission source. COVID-19 data that were analyzed comprised signs and symptoms, COVID-19 patient outcomes, and COVID-19 treatment. Clinical presentation of the patients comprised their oxygen saturation on admission, respiratory rate, and heart rate. According to the existing national guidelines [33], clinical picture, and the number of comorbidities, COVID-19 patients received antiviral agents, broad-spectrum antibiotics, anticoagulant treatment, steroids, and immune modulators for the duration of hospital admission. Lastly, the laboratory data included the following inflammatory markers: procalcitonin, D-dimers, IL-6, TNF-alpha, ferritin, ESR, CRP, and fibrinogen.
## 2.3. Statistical Analysis
IBM SPSS v.27(IBM, Armonk, New York, USA) and MedCalc v.20 (MedCalc Software Ltd., Ostend, Belgium) were used for statistical analysis. We calculated the absolute (n) and relative (%) frequencies of categorical variables and compared their proportions using chi-square and Fisher’s exact test. After testing the available data for normality with the Shapiro–Wilk test, we used the Mann–Whitney test to compare non-Gaussian variables, and we reported them by the median and interquartile range (IQR). The mean and standard deviation of continuous variables with a normal distribution were compared using the Student’s t-test (unpaired, independent samples). A Kaplan–Meier probability plot was created to estimate mortality risk. A multivariate regression analysis was performed to determine the influence of patients’ ethnicity for elevated inflammatory markers at hospital admission. A significance level of 0.05 was chosen as the alpha value.
## Patients’ Background Characteristics
Table 1 presents a comparison of baseline characteristics between cases (patients of Roma ethnicity) and controls from the general population that were diagnosed with COVID-19 and required admission to the ICU. A total of 71 cases were included in the analysis, and 213 controls with a 1:3 ratio and case-matched by age and COVID-19 vaccination status. The majority of patients were at retirement age, over 65 years old (>$47\%$), being represented more often by the male gender (>$54\%$). The body mass index of patients was statistically significantly higher among Roma patients, with more than $57\%$ being overweight, compared with $40.7\%$ in the control group.
Other background characteristics of the study participants identified a higher prevalence of Roma patients residing in the rural regions of Romania, with significantly more of them being unemployed ($38.0\%$ vs. $25.8\%$, p-value = 0.049). Frequent smoking was also more prevalent in patients of Roma ethnicity ($38.0\%$ vs. $24.9\%$, p-value = 0.032). Another important finding was that Roma patients admitted to the ICU had more comorbidities, with $53.5\%$ having three or more comorbid conditions, compared with $34.7\%$ in the control group (p-value = 0.017). Moreover, $12.7\%$ of cases vs. $12.2\%$ of controls were immunized with COVID-19 vaccines.
Table 2 describes the SARS-CoV-2 infection signs, symptoms, and outcomes in Roma patients and the control group of patients admitted to the ICU. There were no statistically significant differences between the signs and symptoms of the studied patients and no differences in the COVID-19 treatment. However, we observed a significantly higher proportion of severe imaging features at admission in the group of cases ($40.8\%$ vs. $28.2\%$, p-value = 0.046), although this difference can be associated with the higher prevalence of smoking in the same group.
Data in Table 3 describe the comparison of COVID-19 outcomes between patients of cases and controls admitted to the ICU. It was observed that the mean duration of hospitalization was longer by 1.8 days than the control group (p-value = 0.027). The viral clearance had a significantly longer duration in the Roma ethnicity group, confirming the longer mean duration of hospitalization. The median duration from symptom onset to hospital admission was 1 day shorter in the group of Roma patients, although not statistically significant. Similarly, the median duration from hospital admission to ICU admission was also shorter in the cases group (p-value = 0.113). The SOFA score and proportion of severe in-hospital complications did not show significant differences between the study groups. However, the median duration of ICU stay was significantly longer in the Roma group (7 days vs. 5 days, p-value < 0.001), and the proportion of intubated patients and mortality did not differ significantly.
When examining the cytokines and inflammatory markers at hospital admission between cases and controls, it was observed that ESR and CRP levels were significantly increased in the Roma patient group, as presented in Table 4. Thus, elevated ESR levels were observed in $54.0\%$ of Roma patients at admission, compared with $38.9\%$ in the control group. The median ESR levels in the cases group was 26 mm/h, compared to 20 mm/h in the control group (p-value = 0.002). Similarly, $47.6\%$ patients from the cases group had elevated CRP levels, with a median value of 24 mg/dL, compared with 17 mg/dL among controls, (p-value < 0.001).
It was observed that, at the moment of ICU admission, the inflammatory markers worsened, increasing in a majority of patients, as seen in Table 5, as compared to the findings observed at admission. IL-6 levels increased significantly in both groups, although with a statistically significant difference between the cases and control groups (17 pg/mL vs. 11 pg/mL, p-value = 0.004). CRP levels that were increased since admission also remained significantly different between the two study groups, with $62.0\%$ of Roma ethnicity patients having elevated CRP at ICU admission, compared with $46.0\%$ in the general population group. The median CRP value among Roma patients was 27 mg/dL, compared with 21 mg/dL (p-value < 0.001), as seen in Figure 1. Lastly, the Kaplan–Meyer probability curve of mortality after ICU admission between patients of Roma ethnicity and the general population showed similar risks in both groups, with no significant differences (log-rank p-value = 0.426), as presented in Figure 2.
A multivariate regression analysis was performed to determine the influence of patients’ ethnicity for elevated inflammatory markers at hospital admission, presented in Table 6. The control group from the general population was considered as the reference group for risk analysis, while CRP, ESR, and IL-6 were considered the dependent variables potentially influenced by the ethnicity of the patients. Only these inflammatory markers were considered for inclusion in the regression analysis after previously determining a statistically significant difference between the cases and control groups regarding these three serum markers. The regression was performed using a threshold for the dependent variables as the upper value of the normal range, and two times the upper value of the normal range. It was observed that the general population did not influence significantly the variation of inflammatory markers above the normal range or two times above the normal range. On the other hand, Roma ethnicity did not have a significant influence on these markers elevated one time above the normal range; however, at two times the normal range, it was shown that it influenced significantly the CRP (β = 1.93, p-value = 0.020) and IL-6 (β = 1.85, p-value = 0.044).
## 4.1. Literature Findings
The current study identified several particularities that seem to affect more often or more severely the COVID-19 patients of Roma ethnicity. One of the minority groups that are the most disadvantaged and underdeveloped on the European continent is the Roma ethnicity [34]. Roma communities have drastically worse health outcomes, such as a far shorter life expectancy, an increased prevalence of both physical and mental health concerns, and larger adoption of risky health practices. Roma communities also have much higher rates of substance abuse, as observed in our study. Contagious diseases, including measles, hepatitis, and TB, disproportionately impact Roma communities due to their lifestyle pattern of living in close groups with many family members [35]. In addition, Roma ethnics are less likely to participate in healthcare services, including their reluctance to vaccination programs, child health, and maternal care, due to barriers such as culture, language, and health literacy, making it less likely for this minority to receive primary and preventive care [36].
According to the results of our research, the unemployment rate among Roma patients was much higher than the general population, and the majority of them lived in rural areas. In addition to these factors, the lifestyle conditions previously described that characterize people of Roma ethnicity might disproportionately expose them to higher risks of SARS-CoV-2 infection, as well as the risk of other contagious diseases due to a higher risk of viral transmission within their communities. It is also more difficult for disadvantaged groups to engage in mitigation activities such as frequently washing their hands, keeping a physical distance, and receiving access to medical care [37]. Therefore, the increased hazards presented by COVID-19 for these communities have the potential to make the health disparities that now exist among Roma groups considerably worse while also potentially having a negative impact on the health of the broader population.
Although no other researchers have reported similar particular results addressing the inflammatory markers in minorities, such as the Roma ethnicity, IL-6 levels have been linked to prolonged lung damage in SARS-CoV-2-infected individuals [38,39]. Notably, these studies described how individuals with persistent pulmonary lesions, as determined by high CT scores, had elevated IL-6 levels at discharge and during the follow-up period, which may also explain why our group of patients with higher IL-6 at admission had more ICU admissions and oxygen supplementation requirements [40]. Importantly, the peak expression of IL-6 prior to the worsening of lung damage was mostly seen in patients with persistent lesions, and multivariate analysis demonstrated that the IL-6 level at admission was an independent predictor of persistent pulmonary injury [41]. Consequently, this much greater percentage of Roma patients with severe COVID-19 who had increased IL-6 levels at admission might explain why these patients also had persistently elevated inflammatory markers, such as CRP and ESR, upon admission.
The elevated CRP levels seen in individuals with severe SARS-CoV-2 infection may be attributed to the overproduction of inflammatory cytokines. When the immune system is overactive, cytokines may cause irreparable lung tissue damage. Therefore, the production of CRP is enhanced by both inflammatory cytokines and the degradation of tissue in COVID-19-infected patients [42]. In conclusion, an elevated CRP level may be a valuable early marker for predicting the likelihood of disease development in COVID-19 patients with mild symptoms. This may allow medical personnel to identify such individuals at an early stage in order to initiate early treatment. In addition, COVID-19 patients with elevated CRP levels need continual monitoring and treatment, even if they did not develop symptoms consistent with a severe disease course [43]. In more than $70\%$ of the COVID-19 intubated patients from the Roma ethnicity, there was a significant increase in C-reactive protein levels. Moreover, severe cases of SARS-CoV-2 infection had higher C-reactive protein levels compared to moderate disease patients in most of the studies [44].
We observed that Roma patients were admitted to the ICU within 3.5 days from the initial hospitalization and 7 days from the onset of their symptoms, which is significantly lower than the general population. This length was, on average, 1 day shorter than the overall population, although this difference was not statistically significant, probably due to a much greater prevalence of comorbidities, such as diabetes mellitus, hypertension, heart disease, and dyslipidemia, among ethnic Roma. In this cohort study, patients of Roma ethnicity were observed to have several elevated inflammatory biomarkers that were significantly higher than in the general population, such as CRP, ESR, and IL-6. Certain inflammatory markers were significantly greater in Roma patients and were related to higher rates of ICU admission or illness severity, but a causative relationship could not be established. In addition, these individuals had a greater prevalence of comorbidities, such as obesity, which is linked with a more severe systemic inflammatory status. It can be hypothesized that these elements, together with a possible genetic predisposition, define greater risks. Although Roma patients had a higher mortality rate, the difference was not statistically significant. There is a good chance that stringent medical and therapeutic care in the ICU saved many lives and decreased the death rate in this demographic. Viral clearance and duration of hospitalization were significantly longer in the Roma population, likely correlated with the more elevated inflammatory markers.
The same Roma patients also had higher median SOFA scores upon admission to the ICU; however, the difference was not statistically significant. Similar studies reported the SOFA score as a strong predictor of mortality in patients with severe COVID-19 [45,46]. Other good predictors for mortality in SARS-CoV-2 infections were the increased circulating cytokines, mostly interleukins. However, one meta-analysis observed that people of Asian descent had lower levels of interleukins when compared to the European population [47], thus confirming that patients of Roma ethnicity might exhibit different pathophysiology during COVID-19, although future populational studies are recommended.
## 4.2. Study Limitations
Even though the selected cohort met the criteria for the sample size needed to achieve statistical power, the number of patients was still not large enough to find COVID-19 outcomes with a lower incidence. In a similar manner, the sample size might have affected the results found in this study, considering that Roma patients were admitted with significantly more elevated inflammatory markers, but the mortality rate was not significantly higher. Nevertheless, the supportive treatment received in the ICU could also help in lowering the mortality odds. Since all of the patients in this study were admitted to a tertiary hospital, it is important to point out the potential for bias in the patient selection that exists within this research, having a higher likelihood of admitting more severe cases requiring ICU admission. As a result, it is possible that the instances of COVID-19 that have been described might have a severity that is higher than the norm.
## 5. Conclusions
We believe that patients of Roma ethnicity exhibit particular population-specific features that manifest differently when facing a disease such as COVID-19. This study showed that Roma patients admitted to the ICU did not have more frequent first symptoms than the general population, such as fever, shortness of breath, and cough. However, they had more risk factors for mortality after intubation, which is likely to be influenced by a higher proportion of comorbid conditions and unhealthy behavior such as smoking, in this particular population. Some inflammatory markers such as ESR, CRP, and IL-6 were significantly more elevated in some of the cases, which could potentially increase the mortality rates. However, in reality, we did not observe a significantly higher rate of Roma patients being intubated or a higher mortality, which can be attributed to good, individualized treatment and management in the ICU. Additional prospective studies must be conducted in order to address more specific laboratory markers of the infected individuals that are highly correlated with a severe SARS-CoV-2 infection and to find the most effective therapy methods.
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|
---
title: Synthesis and Properties of Biodegradable Hydrogel Based on Polysaccharide
Wound Dressing
authors:
- Meiling Shao
- Zhan Shi
- Xiangfei Zhang
- Bin Zhai
- Jiashu Sun
journal: Materials
year: 2023
pmcid: PMC9967607
doi: 10.3390/ma16041358
license: CC BY 4.0
---
# Synthesis and Properties of Biodegradable Hydrogel Based on Polysaccharide Wound Dressing
## Abstract
The metabolic disorder of the wound microenvironment can lead to a series of serious symptoms, especially chronic wounds, which result in significant pain in patients. At present, there is no effective and widely used wound dressing. Therefore, it is important to develop new multifunctional wound dressings. Hydrogel is an ideal wound dressing for medical nursing because of its abilities to absorb exudate and maintain wound wetting, its excellent biocompatibility, and its ability to provide a moist environment for wound repair. Because of these features, hydrogel overcomes the shortcomings of traditional dressings. Therefore, hydrogel has high medical value and is widely studied. In this study, a biodegradable hydrogel based on polysaccharide was synthesized and used as a wound dressing. The swelling degree and degradability of hydrogel were characterized as the characteristics of the wound dressing. The results showed that the prepared hydrogel was degraded with trypsin and in the soil environment. Furthermore, the wound dressing can effectively inhibit the bacterial environment, promote the deposition of the collagen structure of the wound tissue, and accelerate the healing of the wound. The proposed hydrogel has value in practical medical nursing application.
## 1. Introduction
Hydrogel is a kind of hydrophilic three-dimensional network structure that has water as a dispersion medium, and is insoluble but can swell [1,2]. Under the influence of water, hydrogel can swell and handle large amounts of biological liquid, protecting the network structure within the cross-linked polymer chains and providing a springy effect for the hydrogel-treated objects [3]. A variety of hydrophilic groups are attached to the polymer side chain skeleton in the hydrogel, including –COOH, –OH, –SO3H, –NH2, and –CONH, which can maintain the water retention property of hydrogel [4]. As a kind of extracellular matrix (ECM) polymer, hydrogel has good biocompatibility, and has been widely used in biomedicine, tissue engineering, and other fields [5,6,7].
At present, wound dressings are mainly divided into traditional wound dressings and new wound dressings. Traditional wound dressings, including hemostatic gauze and bandages, are mainly used to keep the wound dry, absorb the wound exudate, and prevent wound infection [8,9]. However, they easily adhere to the wound and cause secondary damage without an antibacterial effect. In view of the deficiencies of traditional wound dressings, a new wound dressing was designed according to the theory of wet wound healing. Hydrogels have good toughness and can be tightly fitted to the skin as a wound barrier to prevent wound infection [10,11,12]. In addition, studies have shown that the hemostatic property of hydrogels is not only supported by the physical sealing, but also the enrichment of coagulation factors through the absorption of wound extract [13,14]. Hydrogels are used in the preparation of new wound dressings. With the development of preparation technology, biodegradable hydrogels have been developed and applied to wound excipients [15]. Polysaccharide-based hydrogels composed of chitosan and other natural biological polysaccharides (such as sodium alginate and cellulose) have been widely investigated due to their excellent functions [16]. Alginate and chitosan can form a polyelectrolyte complex through the interaction between the carboxyl group of alginate and the amino ions of chitosan. Chen et al. [ 17] prepared citric acid-modified chitosan hydrogels loaded with tetracycline hydrochloride by freeze–thaw treatment. Antibacterial experiments showed that the hydrogel had an obvious antibacterial effect on both Gram–negative bacteria (Escherichia coli) and Gram–positive bacteria (Staphylococcus aureus). In addition, the tensile strength of the hydrogel was 3 ± 1.5 MPa, the elastic modulus was 2.16 ± 0.1 MPa, and the hydrogel had good tensile properties and toughness. Wound healing experiments showed visible granulation tissue formation 12 days after covering the wound with the hydrogel. Ehteram et al. [ 18] prepared functional hydrogels loaded with A–tocopherol (vitamin E) by crosslinking chitosan and sodium alginate. The therapeutic effect of the developed hydrogel was studied in a full–layer skin wound model [19]. The experimental results showed that the prepared chitosan/sodium alginate hydrogel dressing had a higher wound healing rate than the wound treated with gauze. Khomsan et al. [ 20] used the freeze–thaw treatment in the preparation of chitosan/poly (vinyl alcohol)/ZnO hydrogels. The average aperture in the hydrogel was 13.7 ± 5.9 μm, the bibulous rate reached $850\%$, and the mechanical properties increased with the increase in the elongation of the break. The antibacterial experiment showed that the hydrogel had an excellent antibacterial effect against Gram–positive bacteria (Staphylococcus aureus). In vitro wound healing experiments showed that it had good biocompatibility and could effectively accelerate wound healing. Rezaei et al. [ 21] synthesized a heat–responsive chitosan (TCTS) hydrogel and loaded it with different concentrations of antimicrobial peptides to create an antibacterial wound dressing against drug–resistant bacteria. The physicochemical properties, release behavior, biocompatibility, and antibacterial activity of AMP–TCS hydrogel against standard strains and drug–resistant *Acinetobacter baumannii* were determined by in vitro antibacterial experiments. On day 1, AMP–TCTS AMP gel explosive released about $40\%$ of the water, which can occur within 7 days of controlled drug release. The hydrogel was observed to be extremely absorbent for the first 4 h, and absorbency then continued in a steady manner for 10 h. AMP–TCS hydrogel showed good biocompatibility with human fibroblasts. TCTS hydrogels showed no antibacterial activity against standard strains and clinical isolates. By comparison, AMP–TCTS hydrogels showed strong antibacterial activity against standard strains, but only 16 μg/mL hydrogels showed antibacterial activity against drug–resistant Baumanella. The experimental results showed that 16 μg/mL of AMP–TCTS hydrogel could be used as an excellent antibacterial wound dressing against resistant Baumanniella, and this hydrogel is expected to be further tested in clinical trials. Song et al. [ 22] developed a multifunctional adhesive biohydrogel consisting of 3, 4–dihydroxyphenylpropionic acid modified chitosan (DCS) and p–hydroxybenzaldehyde modified polyethylene glycol (PEGSH). The biohydrogel, which is a kind of hemostatic material having great potential, showed good tensile properties and coagulation, strong adhesion and self–healing properties, and good cytocompatibility and antibacterial properties. The hydrogel eliminates the need for any additional adhesives and antibacterial agents to overcome the shortcomings of traditional hemostatic agents, which have poor stretching ability and poor self–adhesion in humid environments. Kumar et al. [ 23] prepared chitosan–gellan hydrogel for drug delivery and tissue engineering. Controlled drug release at low pH can be achieved by adding gellan gum. The research of Lei H et al. [ 13] found that antioxidant hydrogels can remove excessive reactive oxygen species in chronic wounds to reduce oxidative stress, thus improving the wound microenvironment, promoting collagen synthesis and re–epithelialization, and reducing the pH value of the wound to accelerate healing and reduce infection.
Therefore, in this study, a biodegradable polysaccharide–based hydrogel was synthesized and applied as a wound dressing. Using polyurethane as the base material, the colloid surface is controlled by the amide reaction to ensure compatibility. The mechanism of the hydrogel on wound healing was extensively investigated and it was found that the hydrogel can effectively inhibit bacteria and accelerate wound healing.
## 2.1. Materials and Reagents
Hyaluronic acid (HA), sodium periodate, chitosan (CS), sodium alginate (SA), glycol, and dimethyl sulfoxide were purchased from Aladdin Reagent Co., Ltd., Shanghai, China. The cell culture media were purchased from Fuzhou Aoyan Experimental Equipment Co., Ltd., Fuzhou, China. The chemical structures of the purchased SA and CS are shown in Figure 1, and the molecular weight of CS ranged from 100,000 to 150,000.
## 2.2. Methods
SA and CS having the mass ratio of $\frac{2}{1}$ were dissolved in autoclaved deionized water to obtain a final concentration of 40 mg/mL. The solution was placed in a petri dish, kept at 60 °C, and stirred for 90 min. After centrifugation, the sediment was dispersed in the liquid, and sodium hydroxide with a mass concentration of 150 mg/mL was added to adjust the solvent to be alkaline. When the liquid turned yellow, the precipitation produced by repeated washing and centrifugation with acetone was treated by vacuum drying and dissolved in distilled water. Three grams of HA was weighed and placed in a reaction vessel, and 300 mL of deionized water was prepared. After the substance was completely dissolved, 1 g of sodium periodate was added and the reactive substance was continuously quenched with ethylene glycol. The SA, CS, HA, sodium periodate, and ethylene glycol mixture solution was introduced into the mold and polymerized to obtain polysaccharide–based degradable hydrogel. The diagram of the polysaccharide hydrogel synthesized by a crosslinking reaction is shown in Figure 2, in which both SA and CS are integrated into the structure of the polysaccharide–based hydrogel. Scanning electron microscopy was used to observe the polysaccharide–based degradable hydrogel and obtain SEM images of the hydrogel structure. The results are shown in Figure 3.
Figure 3 shows that the prepared uniform hydrogel structure is coated on the PE film with the hydrogel solution by the coater, and the medical polyurethane semi–permeable film containing wavy lines is placed on the other side. The coating thickness of the solution was controlled to be 2.5 mm; the coating component was controlled to be cooled naturally and formed, and then cut into rectangular specimens of the same size. The size of the internal holes was centrally distributed in a range of 5–10 μm. After sealing with a sealer, the sample of water coagulation dressing was prepared by irradiating 25 k Gy in a nuclear magnetic resonance spectrometer.
A sample of the hydrogel wound dressing prepared above was weighed and placed in PBS (pH 7.4) buffers, followed by a GX–2030–type high-temperature circulating chamber [24]. After 12 h of treatment at the constant temperatures of 20, 30, 40, 50, 60, and 70 °C, when the wound dressing reached the swelling equilibrium, the excess water on the surface was absorbed and the quality of the hydrogel wound dressing was determined.
## 3.1. Swelling Degree Analysis
The swelling rate of wound dressing was calculated, and the numerical relationship is expressed as:[1]R=Ds−DfDf×$100\%$ where R is the swelling rate of wound dressing; *Ds is* the swelling equilibrium mass of the wound dressing sample at corresponding temperature; and *Df is* the original quality of the wound dressing [7]. The corresponding swelling rates of wound dressings under different temperature conditions are shown in Table 1.
The test temperatures were selected in the ranges of 30 °C to 70 °C and 30 °C to 50 °C degrees, with an increment of 5 °C, and 50 °C to 70 °C degrees, with an increment of 10 °C. It can be seen from Table 1 that the prepared biodegradable polysaccharide–based hydrogel wound dressing has strong hydrophilicity. With the increase in ambient temperature, the swelling rate of wound dressing increased, indicating that the prepared hydrogel has strong absorbability and can meet the requirements of normal wound treatment.
## 3.2. Hydrogel Degradability
In order to investigate the biodegradability of polysaccharide–based biodegradable hydrogels, the mass loss of hydrogels under different concentrations of trypsin and in the soil environment was tested. In addition, the morphologies of the degraded hydrogel were observed by scanning electron microscope. Figure 4a shows the mass loss of hydrogel reduced by trypsin at concentrations of 0.1 and 0.2 mg/mL. It can be observed from Figure 4a that the hydrogel at the concentration of 0.2 mg/mL trypsin decreased the hydrolysis rate faster, and the mass loss rate was $68\%$ after 7 days. The results showed that part of the polymer chain segment of the hydrogel was firstly cut off due to the action of enzymes. The damaged part gradually separated from the structure of the hydrogel network and finally dispersed in the solution, resulting in the continuous reduction in the quality of the residual hydrogel. Figure 4b shows that the mass loss rate of the prepared hydrogel reached $61\%$ after 14 days in the soil environment, which indicates that the prepared hydrogel can also degrade in the soil environment.
The changes in hydrogel surface morphology caused by degradation were characterized by SEM, and the results are shown in Figure 5a–c. The biodegradable polysaccharide hydrogel was highly porous, but the degradation of the amide bond on the polypeptide–based vinyl cross–linking agent chain resulted in the destruction of the hydrogel network structure. As shown in Figure 5c, after degradation treatment for 7 days, the internal structure of the hydrogel wound dressing was decomposed into concave and convex structures by microorganisms in the soil. In addition, the surface of the film changed from smooth to rough, and there were holes of different sizes in the film structure. Microorganisms in the soil destroyed the structure of the dressing film, resulting in a compositional degradation process. These results indicate that the prepared biodegradable polysaccharide–based hydrogel is biodegradable and environmentally friendly, which is in line with the application requirements of medical dressings.
## 3.3. Bacteriostatic Performance
A test medium was prepared to test the bacteriostatic performance of the polysaccharide-based degradable hydrogel wound dressing. Nutrient AGAR medium was selected; 5 g of beef paste was prepared, to which 10 g peptone of was added, and the result was stirred evenly. Five grams of sodium chloride was added, followed by an appropriate amount of distilled water to dissolve into a 1000 mL solution. A concentration of 0.1 mol/L sodium peroxide was then added to adjust the pH of the solution to weak acid. The result was placed in a sterilization box and treated for 30 min. When configuring the buffer of the medium, 2.5 g disodium hydrogen phosphate and 1.3 g of potassium dihydrogen phosphate were added to 500 mL of distilled water. After it was fully dissolved, the pH value of the mixed solution was adjusted to about pH 7.4 with hydrochloric acid. After sterilization, the solution was fused with the medium with the above configuration, and *Escherichia coli* were inoculated on the inclined plane of the medium. The medium containing *Escherichia coli* was placed in a constant temperature biological culture cabinet and kept in an inverted state for 24 h. Colonies with good colony growth were selected and transplanted into the medium. The culture medium without transplanted colonies was irradiated and sterilized with a UV lamp for 12 h, and then sealed in a sub–packing bag as a blank control group.
In view of the difference in the properties of dressing-applied fiber materials, the bacterial colonies in the medium were diluted to 10−6, and, according to the actual reaction time, the growth in the number of colonies of staphylococcus units in the unit time was controlled to be 30 cfu. After the culture treatment was completed, the bacterial solution was evenly applied to the medium utensils with the coating rod. The colonies in the culture medium were used as the treatment object of the polysaccharide-based degradable hydrogel wound dressing, and the inhibitory rate of the wound dressing was measured according to the number of inhibited colonies within the cycle range. According to the colony medium prepared above, the bacteriostatic rate of hydrogel wound dressing was defined, and the numerical relationship is expressed as [25]:[2]Y=Wb−WcWb×$100\%$ where Y is the calculated bacteriostasis rate; *Wb is* the number of colonies implanted in the medium; and *Wc is* the number of colonies in the control group. According to the numerical relationship defined above, the bacteriostatic effect was tested in an *Escherichia coli* environment and a staphylobacter colony at 4 h intervals; the bacterial inhibition results of wound dressings were finally obtained, as shown in Figure 6.
As can be seen from the bacterial inhibition results of wound dressings in Figure 6a,b, the polysaccharide–based degradable hydrogel wound dressing has a better bacteriostatic effect in the environments of E. coli bacteria and staphylobacter. Figure 6c shows wound dressings can effectively inhibit $53\%$ of bacteria, and the bacterial inhibition effect of wound dressings is better. In the bacterial environment of Staphylococcus, the wound dressing can effectively inhibit $47\%$ of the bacteria, and the wound dressing has a better bacterial inhibition effect. In conclusion, the wound dressing produced has a better bacterial inhibition effect, and can be used in the process of wound care.
## 3.4. Tissue Collagen Deposition
MTT analysis was used to evaluate the application of the prepared wound dressings according to the bacteriological inhibition effect described above. A small number of EA.hy926 endothelial cells were taken and placed on the membrane dressing and cultured for 48 h. Under sterile conditions, a wound was manually marked on the mold setting, and the collagen distribution of the tissue on the wound was observed with an electron microscope, as shown in Figure 7.
As can be seen from the collagen distribution of the wound in Figure 7a, no bacterial toxicity was present on the surface of the wound, and no collagen proliferation occurred on the wound. After the prepared hydrogel wound dressing was placed on the wound, it was observed for 12 h. According to Figure 7b, part of the tissue collagen deposition was found in the epidermal structure. With the continuous enhancement of the bacterial inhibition effect of the hydrogel wound dressing, the wound epidermis can absorb protein, produce fibronectin in the tissue structure, promote the deposition of the collagen structure, and accelerate hemostasis and wound healing. After further collagen activity of the tissues, collagen deposition after 24 h of application of the wound dressing was observed, and the specific results are shown in Figure 7c. As shown in Figure 7c, as the treatment time of wound dressing increases, a phenolic substance is generated between the activated tissue collagen and the dressing, which promotes the regeneration of tissue collagen, activates the cells in the wound, and achieves the rapid deposition of the collagen structure. Therefore, the prepared polysaccharide–based degradable hydrogel wound dressing can effectively inhibit bacterial regeneration, promote collagen deposition on the wound surface, and accelerate wound healing. This has excellent clinical application in the course of medical nursing.
## 4. Conclusions
In this study, a polysaccharide–based biodegradable hydrogel was synthesized and applied to treat dermal wounds. In vivo results showed that the hydrogel can accelerate granulation tissue formation, increase collagen deposition, and thus promote the wound closure. The results show that the polysaccharide-based biodegradable hydrogel has degradability and excellent antibacterial properties. Furthermore, by simulating the wound environment, it was found that the synthetic hydrogel wound dressing can effectively inhibit bacteria and accelerate the healing of the wound surface.
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|
---
title: Design of TiO2-Based Hybrid Systems with Multifunctional Properties
authors:
- Simona Ortelli
- Maurizio Vespignani
- Ilaria Zanoni
- Magda Blosi
- Claudia Vineis
- Andreana Piancastelli
- Giovanni Baldi
- Valentina Dami
- Stefania Albonetti
- Anna Luisa Costa
journal: Molecules
year: 2023
pmcid: PMC9967613
doi: 10.3390/molecules28041863
license: CC BY 4.0
---
# Design of TiO2-Based Hybrid Systems with Multifunctional Properties
## Abstract
In recent years, multifunctional inorganic−organic hybrid materials have been widely investigated in order to determine their potential synergetic, antagonist, or independent effects in terms of reactivity. The aim of this study was to design and characterize a new hybrid material by coupling well-known photocatalytic TiO2 nanoparticles with a mixture of lipopeptides (LP), to exploit its high binding affinity for metal cations as well as the ability to interact with bacterial membranes and disrupt their integrity. We used both chemical and colloidal synthesis methodologies and investigated how different TiO2:LP weight ratios affected colloidal, physicochemical, and functional properties. We discovered a clear breaking point between TiO2 and LP single-component trends and identified different ranges of applicability by considering different functional properties such as photocatalytic, heavy metal sorption capacity, and antibacterial properties. At low LP contents, the photocatalytic properties of TiO2 are preserved (conversion of organic dye = $99\%$ after 40 min), and the hybrid system can be used in advanced oxidation processes, taking advantage of the additional antimicrobial LP properties. Around the breaking point (TiO2:LP 1:1), the hybrid material preserves the high surface area of TiO2 (specific surface area around 180 m2/g) and demonstrates NOx depletion of up to $100\%$ in 80 min, together with improved adhesion of hybrid antibacterial coating. The last design demonstrated the best results for the concurrent removal of inorganic, organic, and biological pollutants in water/soil remediation applications.
## 1. Introduction
Sustainable wastewater management has become the primary agenda of the sustainable development goals worldwide [1].
This challenge is addressed by technologies that promote a concurrent removal of organic (molecules, oils, microorganisms, etc.) and metal pollutants from contaminated sites (water or soil).
Nano-TiO2 offers low cost, high reactivity, and easy recovery of photocatalytic technology. Its light-activated capacity to oxidate/mineralize organic compounds is of great relevance and significance in advanced oxidation processes for water and air depollution [2,3,4,5]. The possibility of activation in the visible light region as a result of metal and nonmetal doping and the fabrication of composites has recently attracted increasing attention due to possible applications under outdoor solar or indoor LED-visible sources of irradiation. The design of TiO2 nanoparticles (NPs) strongly affects their efficiency. It is influenced by:[1] quantum size effects such as band gap energy and the light-induced charge transfer between the adsorbate molecules and the substrate; [2] surface area effects such as the light absorption efficiency and the consequent surface photocarrier concentration; and [3] carrier diffusion effects such as the recombination rate of photogenerated carriers.
Lipopeptides are a class of biosurfactants that have been widely studied and utilized for various biomedical and environmental applications due to their diverse properties, including antimicrobial, antiadhesive, antitumor, and bioremediation activities [6,7,8,9,10,11,12]. Lipopeptides possess surfactant properties due to their amphiphilic nature, having both hydrophilic (peptide) and hydrophobic (lipid) components. This allows them to interact with cell membranes, disrupting their structures and functions. As a result, lipopeptides can exhibit potent antimicrobial effects against a wide range of pathogens, including bacteria, fungi, and even some viruses [13,14].
Lipopeptides also exhibits good stabilizing properties used in the sol–gel synthesis of metal nanoparticles [15,16,17,18,19]. Thus, we decided to exploit the coupling between TiO2 NPs and a mixture of lipopeptides (LP), to investigate the physicochemical identity of the hybrid phase and the possible synergetic, antagonist, or independent effects in terms of functionality [20,21].
New inorganic−organic multicomponent materials based on TiO2 and LP were produced, characterized, and tested for their multifunction activity, as reported in Scheme 1.
Two synthesis design strategies, namely chemical sol–gel synthesis of TiO2 nanoparticles (NPs) nucleated over LP solution and colloidal heterocoagulation, exploiting the attraction between opposite charge TiO2 NPs and LP, were used to produce hybrid materials made by TiO2.
We tested the photocatalytic activity vs. the degradation of rhodamine B (RhB) in water, the abatement of NOx at gas phase, the sorption of Cu2+ ions, selected as probe metal, and the biocidal action following the ASTM E2149 procedure against Gram-positive bacteria Staphylococcus aureus.
## 2.1. Sol–Gel Synthesis (TiO2@LP_S)
Data from colloidal characterization of TiO2@LP_S samples, differing for the TiO2:LP weight ratio (details in Section 3.2.1), are reported in Table 1. We observed an increase in hydrodynamic diameters, determined by DLS analysis (Figure S1 and Table 1), as a function of the LP amount. This was justified by the increase in the steric hindrance of the LP shell and by the destabilization of colloidal dispersion, which were caused by free, non-adsorbing molecules in solution (depletion flocculation) [22]. The zeta-potential curves as a function of pH, reported in Figure 1, show an abrupt change in colloidal properties, passing from a 1:1 to 1:2 TiO2:LP ratio. Two populations are clustered around the curves of the two separate components: one with nanometric hydrodynamic diameters, positive zeta potential, and an isoelectric point comparable with that of the TiO2 reference sample (TiO2@TX) and the other with micrometric hydrodynamic diameters, negative zeta potential, and an isoelectric point similar that of LP. This result offered a clear indication of which design option to select if we wish to prioritize the TiO2 or the LP colloidal identity in the hybrid system.
A breaking point, passing from the 1: 1 and 1: 2 TiO2:LP ratios, was also observed in the XRD diffractograms (Figure 2). The peaks of TiO2 anatase with small traces of brookite were observed up to the TiO2:LP 1:1 weight ratio. In the group of samples with higher LP content, the characteristic peaks of the anatase phase disappeared. In this case, we can hypothesize the formation of very small clusters where the ionic phase is still in equilibrium with the solid [23,24] or the presence of amorphous titania phase [25]. In this group of samples, in relation to the high content of LP, we noticed the formation of NaCl as a by-product of the synthesis. This was identifiable based on peaks at 2θ = 32° and 47°. At 2θ = 18°, a broad peak, which was attributable to the organic phase, confirmed the presence of the high concentration of LP.
In order to verify the formation of TiO2 NPs, TEM analysis was carried out. Figure 3 reports the TEM images of TiO2@LP_S_1:0.1 and TiO2@LP_S_1:1 sample, confirming the presence of crystalline well-dispersed TiO2 NPs, with sizes ranging from 3 to 12 nm and from 2 to 10 nm, respectively. The selected area electron diffraction (SAED) pattern and the relative rotational average (Figure S2) showed that all rings can be indexed as a mixture of anatase (majority phase) and brookite nanocrystals, confirming the data obtained via XRD analysis (Figure 2). By increasing the content of LP in TiO2@LP_S_1:2 and TiO2@LP_S_1:6 samples, no evidence of the presence of TiO2 NPs could be found via TEM analysis. Moreover, no evidence of the presence of crystalline NPs could be detected by SAED patterns. The TEM results confirm the hypothesis that very small clusters in equilibrium with their ionic phase should form at a high LP concentration, as the presence of LP hindered the growth of the as-formed nuclei.
## 2.2. Heterocoagulation Process (TiO2/LP_E)
The physical mixing of oppositely charged TiO2@TX_S and LP (Table 2) provided the heterocoagulated samples TiO2/LP_E, whose components are mainly bound by electrostatic attractive interactions [26]. The samples were prepared at different TiO2:LP weight ratios (see Section 3.2.2 for details). Additionally, in this case, we investigated the colloidal behavior of DLS and zeta-potential measurements and noted an increase in the hydrodynamic size of the multicomponent system with the increase in LP content. In particular, the sample corresponding to the TiO2:LP 1:1 weight ratio was the first to reverse the positive zeta potential of TiO2, which had dramatic consequences for the colloidal stability (DLS size around 1 μm), as reported in Table 2 and Figure S3a. With higher content of LP, the hydrodynamic diameter decreased, and the negative zeta potential of the composite increased due to the electrosteric contribution of S which, in the case of heterocoagulated samples, acts as a dispersing agent. As was the case for sol–gel samples, the isoelectric points (pHiep) of the heterocoagulated samples at high content of LP (1:6 and 1:8 TiO2:LP weight ratio) are coincident to that of LP (Figure S3b) even if the breaking point is not so evident, as in the previous case.
The XRD diffractograms showed the presence of both phases, as expected (Figure 4). TiO2 (anatase phase) was recognized from characteristic peaks at 2θ = 25°, 38, 48, and 54°. Additionally, small traces of brookite were detected at 2θ = 26°. The LP organic phase showed a broad peak at 2θ = 18°. We observed a proportional increase in intensity of the LP peak as the LP content in the samples increased; this passed from TiO2/LP_1:1_E to TiO2/LP_1:8_E. The formation of a synthesis by-product, NaCl, was also identifiable, with peaks at 2θ = 32° and 47°.
## 2.3. Comparison between TiO2@LP_1:1_S and TiO2/LP_1:1_E
The TiO2@LP_1:1_S and TiO2/LP_1:1_E samples are the most representative for both synthesis methods of hybrid systems; in fact, they represent the breaking point, with a shift of properties from TiO2 to the LP component. Therefore, these samples were further investigated by additional characterization techniques (FTIR spectroscopy and BET analysis).
In Figure 5a, comparison between the FTIR spectra of TiO2@LP_1:1_S and TiO2/LP_1:1_E samples with single components (TiO2@TX and LP) is reported. The reference TiO2@TX (black curve) showed a broad band at 500–800 cm−1 corresponding to the vibration of Ti-O-O bond [27] and Ti-O stretching [28], confirming the presence of TiO2. Moreover, we observed some peaks in the wavenumber range 1100–1600 cm−1; these are attributable to Triton X. Their low intensity is due to the high TiO2:Triton X weight ratio (Table S1). The peaks at 1100 and 1243 cm−1 correspond to the asymmetric stretch of aromatic ether; those in the range 1360–1450 cm−1 are related to the C-H bending vibration; and peaks at 1511 and 1610 cm−1 correspond to the stretching vibration of the benzene group [29]. The light-blue curve in Figure 5a shows the FTIR spectrum of the LP component, which clearly highlights the typical peaks of lipopeptide, with peaks at 3350 and 1528 cm−1 attributed to NH-stretching mode and peaks at 2956–2870 cm−1 and 1467–1368 cm−1 representative of the C–H group of aliphatic chains (–CH3; –CH2–) with symmetric stretching at 2870 cm−1.
The FTIR analysis on hybrid TiO2@LP_1:1_S and TiO2/LP_1:1_E samples allowed us to confirm the presence of typical functional groups of both TiO2 and LP. The main characteristic peaks of TiO2 and LP were observed in both TiO2@LP_1:1_S and TiO2/LP_1:1_E samples (Figure 5a). Through detailed comparison of the two samples, we can observe a lower intensity of peaks corresponding to the LP and the absence of characteristic bands of LP at high wavenumber in the TiO2@LP_1:1_S sample (blue curve). On the other hand, in the TiO2/LP_1:1_E sample (dark-green curve), obtained by heterocoagulation, all characteristic peaks of LP were recognized. These observations could be justified by a stronger interaction between TiO2 NPs and LP in the sample obtained by sol–gel synthesis method, with the formation of a new hybrid phase slightly different from the single component.
The specific surface areas (LPAs) of spray-freeze-dried (SFD) powders are reported in Figure 5b. Samples synthesized using a sol–gel method at a low LP concentration show high values of surface area comparable with that of the TiO2 component. The LPA of TiO2:LP_1:1_S sample is five-fold higher than the corresponding heterocoagulated sample. This result is most likely due to intimate molecular interaction between the two components in the sol–gel-synthesized samples, which promotes a real dispersing action of LP over TiO2 NPs. The abrupt decrease in surface area that occurs as a result of the increasing TiO2:LP weight ratio is in agreement with the increased agglomeration caused by the LP depletion action discussed previously (Table 1). Additionally, the low surface area of the heterocoagulated sample is justified by the high degree of agglomeration of this sample, which decreases the number of TiO2-accessible surface sites.
## 2.4.1. Photocatalytic Tests
The results of photocatalytic tests performed in water and expressed as a percentage of conversion of the rhodamine B (RhB) under visible solar light are reported in Figure S4 and Table 3.
Firstly, no samples demonstrated adsorption of RhB after one hour of contact in the dark (Figure S4a). The TiO2@TX reference component had the highest photocatalytic performance, with a conversion of $99\%$ and the highest kinetic constant (9.5 × 10−2 min−1). The hybrid systems for low LP content showed very good photocatalytic performance, with conversion around $90\%$ and a high kinetic constant (k) up to the sample with TiO2:LP 1:0.5. Increasing the content of LP led to an abrupt decrease in photocatalytic activity up to samples TiO2@LP_1:6_S and TiO2@LP_1:8_S, which did not demonstrate any significant photocatalytic activity despite the photoactivation (absorption in the range between 300–400 nm, reported in Figure S8 and Table S3). The reduction in photocatalytic activity around TiO2:LP 1:0.5 and 1:1 weight ratios is in agreement with the abrupt change in physicochemical properties and the previously noted absence of TiO2 crystalline peaks detectable through XRD (Figure 2) or TEM SAED analysis. Moreover, the trend caused by the increased amount of LP surrounding TiO2 NPs can be justified by the shielding effect of organic LP coating, which depresses the photocatalytic activity of TiO2 NPs [30].
The results of tests performed using samples prepared via heterocoagulation (TiO2/LP_E) are reported in Figure S5 and Table 4.
For samples obtained via heterocoagulation, almost no sorbent capacity was observed for RhB after one hour of contact in darkness (Figure S5a). The samples obtained via heterocoagulation had very poor photocatalytic performance, with conversion data of less than $20\%$ and a very low kinetic constant. As expected, the presence of the LP layer surrounding TiO2 NPs, which depresses the specific surface area (Figure 5b), also has a strong shielding effect on the TiO2 photocatalytic performances, with a reasonable quenching of radicals produced by TiO2 NPs due to their organic coating [31].
Overall, the comparison of photocatalytic performances of TiO2@LP_1:1_S and TiO2/LP_1:1_E samples highlights how, in the sol–gel-synthesized hybrids specifically, it is possible to take advantage of the highly surface-area-dependent photocatalytic properties of TiO2.
## 2.4.2. Sorption Tests
The results of sorption tests performed on representative samples are reported in Table 5. They are expressed as the Cu2+ sorption capacity, which allows it to simulate these materials’ use for the removal of heavy metals from wastewater. The data show similar trends for both sol–gel synthesis and heterocoagulation samples, with a sorption capacity that is dependent on the LP content. Below the TiO2:LP 1:1 weight ratio, the samples show the same sorption capacity of TiO2, whilst at the highest concentration of LP, the samples show the same behavior of LP alone. This result suggests the main sorption/complexing role of LP is solely dependent on the amount of LP available and not its degree of agglomeration or interaction with the TiO2 component. Moreover, we observed no significant increase in Cu2+ sorption over time, demonstrating that the sorption ability of all these samples is characterized by fast kinetics.
## 2.4.3. Antibacterial Tests
Biocidal action was tested on TiO2@LP_S nanosols obtained via sol–gel synthesis and de-posited on polyester textile substrates via a dip-pad curing method [32]. In Table 6, the add-on (%) and the bacterial reduction (%) data are reported.
The LP alone showed a low bacterial reduction ($40\%$) due to the low add-on value ($1.7\%$). The presence of TiO2 increases the amount of material that can be transferred on the sample, with consequent improvement of antibacterial properties (up to $89\%$ for the TiO2@LP_1:0.1_S sample). We also we observed a decrease in performance at the highest LP content despite the highest add-on, confirming that the LPA and availability of free surface sites also play a huge role in the biological reactivity in this case. Overall, it was difficult to determine if synergic effects occurred between the two potentially active components; the only evident effect is the improved adhesion (add-on value) provided by the TiO2 phase.
## 2.4.4. NOx Abatement Tests
Photocatalytic performances were also evaluated on TiO2@LP_S coated textiles through NOx abatement tests. The data expressed as NO depletion trend as a function of time are reported in Figure 6.
As expected, the inactivity of LP alone was demonstrated by the negligible depletion of NO (LP—black curve). In agreement with this result, low reactivity was also found at the highest LP concentration (TiO2@LP_S_1:8—green curve) despite the highest amount of composite deposited on the textile (add-on value reported in Table 6). On the other hand, the reference (TiO2@TX) and the hybrid samples with low LP content showed complete NO depletion after 2 h of UV light exposure. This trend concurs with the results of photocatalytic and antibacterial tests reported in Section 2.4.1 and Section 2.4.3, respectively. As expected, at a high concentration of TiO2, the photocatalytic properties of the inorganic photocatalyst prevail, with consequent high NO depletion. The higher degradation kinetics of hybrid samples compared with reference TiO2 (depletion around $80\%$ for TiO2:LP_1:0.1 and 1:1_and <$5\%$ for TiO2@TX, at 20 min) is highly encouraging and can be justified by the dispersing capability of LP, which maximizes the availability of TiO2 active surface sites. ( See Supplementary Materials)
## 3.1. Materials
Titanium(IV) isopropoxide, hydrochloric acid, Triton X, rhodamine B and copper chloride were purchased by Merck Life Science S.r.l. ( Milano, Italy). The mixture of lipopeptides, was provided as crude extract by AmbrosiaLab (Ferrara, Italy). All the reagents were used without further purification.
## 3.2. Methods
The hybrid materials based on TiO2 and mixture of lipopeptides (LP) were prepared using two synthesis design strategies: sol–gel synthesis and heterocoagulation.
## 3.2.1. Sol–Gel Synthesis (TiO2@LP_S)
TiO2 nanoparticles nucleated over LP solution were obtained via classical sol–gel synthesis via acidic catalysis starting from titanium(IV) isopropoxide, replacing the chemical surfactant (Triton X) at a very low concentration in the synthesis process (TiO2:Triton X 1:0.06-TiO2@TX_S) with the mixture of lipopepetides LP [33]. The resulting hybrid TiO2 phases (TiO2@LP_S) were prepared with varying TiO2:LP weight ratios (1:0.1; 1:0.5; 1:1; 1:2; 1:6 and 1:8). The sol–gel-synthesis processes are schematized in Figure S6a. All the samples prepared by sol–gel-synthesis process are summarized in Table S1.
## 3.2.2. Heterocoagulation Process (TiO2/LP_E)
The product TiO2@TX_S was mixed with aqueous solution of LP in a pH range in which both surfaces TiO2@TX and LP had opposite charges to promote the electrostatic interaction. The heterocoagulated samples were prepared with varying TiO2:LP weight ratios (1:1; 1:6, and 1:8) and maintained under stirring for 24 h to favor electrostatic interaction. The heterocoagulation process is schematized in Figure S6b. All the samples prepared via heterocoagulation are listed in Table S2.
## 3.2.3. Spray-Freeze-Drying Technique
The spray-freeze-drying technique (Figure S7) was employed here to obtain handy powders (SFD), starting from the TiO2- and LP-based nanosuspensions prepared by both methods (sol–gel-synthesis and heterocoagulation process) by means of a lab-scale granulator instrument, LS-2 (PowderPro, Mölndal, Sweden). The nanosuspensions were atomized through a peristaltic pump, blowing nitrogen gas at 0.4 bar through a 100 μm nozzle, and nebulized into a stirred solution of liquid nitrogen to enable instantaneous freezing of each generated drop. The so-frozen drops were placed into a freeze-drying apparatus with a pressure of 0.15 mbar and a temperature of −1 °C to promote the sublimation process, which was completed within 48 h, and a highly porous granulated powder was produced. All the samples prepared via the SFD process are summarized in Tables S1 and S2.
## 3.3.1. Colloidal Characterization
The particle size distribution and zeta potential were determined at 25 °C using a Zetasizer Nanoseries (Malvern Instruments, Malvern, UK) via dynamic light scattering (DLS) and electrophoretic light scattering (ELS) techniques, respectively. The DLS technique can calculate the hydrodynamic diameter of suspended particles, and the Smoluchowski equation was applied to convert the electrophoretic mobility to zeta potential. After a 2 min temperature equilibration step, samples underwent three measurements; the hydrodynamic diameter and zeta potential were obtained by averaging these measurements. The instrument is equipped with an auto-titration unit, which enables the identification of the isoelectric point (pHIEP) and automatically adds to the sample KOH 0.1 M or HCl 0.1 M in order to explore the zeta-potential trend within a selected pH range. The measurements were performed on the TiO2- and LP-based nanosuspensions prepared via both methods (sol–gel synthesis and heterocoagulation) at 0.1 g L−1 concentration.
## 3.3.2. X-ray Diffraction (XRD)
XRD measurements were carried out on sample powders obtained using a spray-freeze-drying technique (SFD) at room temperature with a Bragg/Brentano diffractometer (X’pertPro PANalytical, Malvern Panalytical, Malvern, UK) equipped with a fast X’Celerator detector, using a Cu anode as the X-ray source (Kα, λ = 1.5418 Å). Diffractograms were recorded in the range 10−80° 2θ counting for 0.2 s every 0.05° 2θ step.
## 3.3.3. Transmission Electron Microscopy (TEM)
The transmission electron analyses on TiO2@LP_S nanosols obtained via sol–gel synthesis were performed with a FEI TECNAI F20 microscope (FEI F20, Thermo Fisher Scientific, Waltham, MA, USA) operating at 200 keV. The instrument is also equipped with a dispersion micro-analysis of energy (EDS) (EDAX, Thermo Fisher Scientific, Waltham, MA, USA) and the scanning transmission electron microscopy (STEM) accessory (FEI F20, Thermo Fisher Scientific, Waltham, MA, USA). The TEM images were taken in the phase contrast mode and selected area electron diffraction (SAED). STEM pictures were recorded using a high-angle annular dark field (HAADF) detector: in this imaging mode, the intensity I is proportional to Z1.7t, where Z is the mean atomic number, and t is the thickness of the specimen. After 1:1000 dilution in water, the nanosols were sonicated for four minutes, then deposited on a holey carbon film supported by a gold grid, and dried at 100 °C.
## 3.3.4. Fourier Transform Infrared (FTIR) Spectroscopy
FTIR analysis was performed on the TiO2@LP samples after the SFD process. The powders were pelletized with KBr, adding ca. 1.25 mg of powder to 100 mg of KBr. The measurements were obtained using a Nicolet iS5 spectrometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). A wave number range between 400 and 4000 cm−1 was set for the analysis, and 24 runs were performed for each measurement with a resolution of 1 cm−1 using the IR accessory (model iD1). The positions of the peaks were identified by means of the OMNIC software (v9.2, Thermo Fisher Scientific, Waltham, MA, USA) and comparing values with the data in the literature.
## 3.3.5. Specific Surface Area by BET Method
Specific surface areas of spray-freeze-dried powders were measured by N2 physisorption apparatus (Surfer Thermo Scientific) via Brunauer–Emmett–Teller (BET) (Surfer, Thermo Fisher Scientific, Waltham, MA, USA) analysis, in which samples were pre-treated under a vacuum at 200 °C for 1 h.
## 3.4.1. Photocatalytic Degradation of Rhodamine B (RhB)
Photocatalytic degradation of RhB was conducted in a beaker at room temperature. The typical setup foresees the addition of samples, both in suspension and in powder (at 0.1 g L−1 concentration), to 150 mL of a RhB aqueous solution. In order to establish an absorption/desorption equilibrium between catalyst and RhB, the solution was kept in the dark for about 60 min, which proved to be a suitable time to ensure the equilibrium. Absorption/desorption phenomena occurring during the stirring were verified and evaluated as negligible in relation to the overall photocatalytic reaction. The suspension was stirred and irradiated via a solar simulator (SUN 2000 11000 model, Abet Technologies, Milford, CT, USA) with 1000 W intensity. The lamp was switched on before the beginning of the photocatalytic test to stabilize the emission power. The analyses were performed using a quartz cuvette as a sample-holder. The degradation reaction progress was monitored at regular times (10, 20, 30, 40, 50, and 60 min) by withdrawing and centrifuging (7500 rpm for 10 min) 3 mL of solution and measuring the absorbance at 554 nm with a single-beam spectrophotometer (UV/Vis Hach Lange, DR 3900, Hach, Loveland, CO, USA). The photocatalytic activity was quantified as the photodegradation rate constant of catalyst k (min−1). The photodegradation of RhB in presence of a catalyst can be considered a pseudo-first-order reaction and can be described by Equation [1]: ln(C0)/(C) = kt[1] According to the Lambert–Beer law, the absorbance is proportional to the RhB concentration, so ln (C0/C) is calculated by measuring the initial concentration (C0) and absorbance (A0) and after a certain irradiation time t (At). The value of k was assessed by plotting ln (C0/C) versus time (t). The conversion, calculated at $t = 120$ min, indicates the ratio between the amount of reagent consumed and the amount of reagent initially present in the reaction environment; this was determined by Formula [2]:Conversion (%) = (A0 − At)/A0 × 100 [2]
## 3.4.2. Sorption Tests
The prepared samples, in powder form, were dispersed in water and kept in contact with a solution of CuCl2 (10 mg L−1) at room temperature. The tests were performed in the presence of 2.5 g L−1 of adsorbent samples under stirring and at a working pH of 4.5. To quantify the sorption, after keeping the samples in contact with Cu2+, 8 mL were centrifuged at 4500 rpm for 40 min by ultrafiltering the sample with centrifugal filter units (Polyethersulfone, Amicon filter 5 KDa, Millipore, Burlington, MA, USA). In this way, we separated the powder samples from the solution and quantified them via inductively coupled plasma atomic emission spectroscopy coupled with a OneNeb nebulizer (ICP-OES 5100—vertical dual view apparatus—Agilent Technologies, Santa Clara, CA, USA); the non-absorbed Cu2+ remained part of the solution despite the increase in time (1 and 24 h). The analyses were performed in radial viewing mode, and calibration curves were obtained with 0.1, 1.0, 10.0, and 100.0 mg L−1 standards for the element. Nitric acid was added to standards and diluted samples (1:10 v/v). The calibration curve was evaluated and showed a good correlation coefficient (R2) above 0.99. Results from ICP-OES were reported as the average of three independent measurements with relative standard deviation.
## 3.4.3. Antibacterial Tests
Biocidal action was tested on TiO2@LP_S nanosols, obtained via sol–gel synthesis, which was deposited on polyester textile substrates via the dip-pad curing method. The textile was washed in an ultrasonic bath for 15 min in water and dried in an oven at 100 °C. Then, the washed textile was dipped in the TiO2@LP_S nanosols for 3 min, squeezed in two rolls to eliminate the excess of suspension (pad stage), dried in a stove at 80 °C, and finally cured at 120 °C for 10 min to fix the NPs to the fabric. A triple-layer impregnation was carried out, achieving the final dry add-on value (AO%; Equation [3]), which is defined as the percent amount of the finishing agent added to the fabric with respect to the initial weight of the latter; i.e., AO% = [(wf − wi)/wi] × 100 [3] where wi and wf are the weights of the fabric before and after the dip-pad curing process.
The antibacterial tests were assessed following the ASTM E2149 procedure and addition of Gram-positive bacteria *Staphylococcus aureus* (S. aureus) ATCC 6538. Before the tests, the TiO2@LP_S coated polyester textiles were pre-irradiated for 2 h 30 min under UV light (Osram ULTRA-Vitalux lamp 300 W). The test culture was incubated in a nutrient broth for 24 h and then diluted to a concentration of 1.5–3.0 × 105 CFU mL−1 (working solution). Next, 1 g of each treated fabric was transferred to a flask containing 50 mL of the working solution. All flasks were shaken for 1 h at 190 rpm. After a series of dilutions, 1 ml of the solution was plated in nutrient agar. The inoculated plates were incubated at 37 °C for 24 h, and the surviving cells were counted. The biocidal action was expressed in percent bacteria reduction by counting the surviving cells after contact with the test specimen (A) compared to the number of bacterial cells in the working solution (B), according to Equation [4]:Reduction% = [(A − B)/B] × 100 [4]
## 3.4.4. NOx Abatement Test
The NOx abatement test was conducted on TiO2@LP_S nanosol-coated textiles (10 × 10 cm), prepared via the dip-pad curing method (as described in the previous Section 3.4.3). The analyses were conducted under controlled conditions at a temperature of 26 ± 2 °C and a relative humidity of 44 ± $4\%$ and under UV irradiation (Osram ULTRA Vitalux lamp 300 W) at an intensity of 50 W m−2. The analyses were performed by injecting a pollutant gas consisting of dry air, moist air, and NO in the measuring system in the presence of the coated textiles. Then, the concentration of the gases (NO, NOx, and NO2) was monitored with a chemiluminescence detector (Thermo, model 42i, Thermo Fisher Scientific, Waltham, MA, USA). The NO degradation reaction progress was monitored at regular times (25, 45, 65, 85, 105, 125, and 145 min). The kinetics of the degradation reaction were obtained, plotting the NO depletion (%) as a function of time of activation.
## 4. Conclusions
Hybrid systems based on TiO2 and lipopeptides (LP) components were successfully synthetized via two different approaches (sol–gel synthesis and heterocoagulation). Physicochemical and colloidal properties characterization highlighted two main populations with distinct behavior. At the breaking point, around TiO2:LP 1:$\frac{1}{1}$:2, the colloidal stability of the system abruptly decreased, with dramatic consequences for functional performances. On the contrary, the presence of LP at a low concentration improved the TiO2 dispersibility, increasing the availability of active surface sites. This resulted in the highest performances in terms of photocatalytic degradation of RhB in water, abatement of NO in gas, and antibacterial properties against *Staphylococcus aureus* of coated textiles. In particular, the hybrid system with TiO2:LP 1:1 preserved the high surface area of TiO2 (specific surface area around 180 m2/g), caused a NOx depletion up to $100\%$ in 80 min, and improved adhesion of the hybrid antibacterial coating, suggesting that it is the best hybrid design for the concurrent removal of inorganic, organic, and biological pollutants in water/soil remediation applications. The evaluation of potential synergic effects of the hybrid systems leads us to the following conclusions: [1] at low LP contents, the photocatalytic properties of TiO2 are preserved, and the hybrid systems can be used in advanced oxidation processes, taking advantage of the additional LP properties; [2] at high LP contents, TiO2 loses its photoactivity due to the LP coating quenching effect avoiding undesired oxidative effects; [3] in the combined adsorbent system, the TiO2 can improve the stability and density of the lipopetides, allowing easy transport and recovery from the medium. Overall, the eco-design of hybrid systems and the proven concurrent removal of inorganic, organic, and biological pollutants can be successfully exploited in environmental remediation technologies.
## Figures, Scheme and Tables
**Scheme 1:** *Multifunctional platform designed for the removal of water/soil pollutants.* **Figure 1:** *Zeta potential as a function of pH curves for TiO2@LP_S samples obtained via sol–gel synthesis.* **Figure 2:** *XRD diffractograms of TiO2@LP_S_SFD samples (◊, LP; □, anatase; ●, brookite; ○, sodium chloride).* **Figure 3:** *TEM images of (a) TiO2@LP_S_1:0.1 and (b) TiO2@LP_S_1:1 samples.* **Figure 4:** *XRD diffractograms of TiO2/LP_E_SFD samples (◊, LP; □, anatase; ●, brookite; ○, sodium chloride).* **Figure 5:** *(a) FTIR spectra of TiO2@TX (black), LP (light blue), TiO2@LP_1:1_S (light gray), and TiO2/LP_1:1_E (dark green) samples and (b) specific surface area data (m2/g).* **Figure 6:** *NO depletion trend as a function of UV light time of irradiation.* TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 TABLE_PLACEHOLDER:Table 3 TABLE_PLACEHOLDER:Table 4 TABLE_PLACEHOLDER:Table 5 TABLE_PLACEHOLDER:Table 6
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|
---
title: Influence of the Fatty Acid Metabolism on the Mode of Action of a Cisplatin(IV)
Complex with Phenylbutyrate as Axial Ligands
authors:
- Theresa Mendrina
- Isabella Poetsch
- Hemma Schueffl
- Dina Baier
- Christine Pirker
- Alexander Ries
- Bernhard K. Keppler
- Christian R. Kowol
- Dan Gibson
- Michael Grusch
- Walter Berger
- Petra Heffeter
journal: Pharmaceutics
year: 2023
pmcid: PMC9967619
doi: 10.3390/pharmaceutics15020677
license: CC BY 4.0
---
# Influence of the Fatty Acid Metabolism on the Mode of Action of a Cisplatin(IV) Complex with Phenylbutyrate as Axial Ligands
## Abstract
For a variety of cancer types, platinum compounds are still among the best treatment options. However, their application is limited by side effects and drug resistance. Consequently, multi-targeted platinum(IV) prodrugs that target specific traits of the malignant tissue are interesting new candidates. Recently, cisPt(PhB)2 was synthesized which, upon reduction in the malignant tissue, releases phenylbutyrate (PhB), a metabolically active fatty acid analog, in addition to cisplatin. In this study, we in-depth investigated the anticancer properties of this new complex in cell culture and in mouse allograft experiments. CisPt(PhB)2 showed a distinctly improved anticancer activity compared to cisplatin as well as to PhB alone and was able to overcome various frequently occurring drug resistance mechanisms. Furthermore, we observed that differences in the cellular fatty acid metabolism and mitochondrial activity distinctly impacted the drug’s mode of action. Subsequent analyses revealed that “Warburg-like” cells, which are characterized by deficient mitochondrial function and fatty acid catabolism, are less capable of coping with cisPt(PhB)2 leading to rapid induction of a non-apoptotic form of cell death. Summarizing, cisPt(PhB)2 is a new orally applicable platinum(IV) prodrug with promising activity especially against cisplatin-resistant cancer cells with “Warburg-like” properties.
## 1. Introduction
Platinum compounds still play a very prominent role in current standard anticancer therapy regimens. Cisplatin, discovered in the 1960s by Rosenberg et al., was the first of three platinum compounds to ever achieve worldwide approval by regulators [1]. Cisplatin is administered intravenously and enters the cells from the blood stream either passively or actively via copper transporters such as CTR1 [2,3]. Intracellularly, cisplatin is hydrolyzed and subsequently induces cell death by crosslinking DNA. Even though cancer cells are more sensitive to cisplatin in comparison to cells from healthy tissue, dose-limiting side effects and occurrence of resistance reduce therapy success. To overcome these restraints and generally improve anticancer efficacy, several strategies have been investigated. Among them, the prodrug concept of platinum(IV) compounds has shown promising results. The higher oxidation state of the platinum center increases the compound’s kinetic inertness thereby reducing possible side effects in normal tissues [4,5,6,7]. Moreover, two additional (bioactive) axial ligands can be introduced, e.g., altering lipophilicity, pharmacokinetics, or generating multi-targeted complexes. In the malignant tissue, the characteristic reductive environment is supposed to activate the platinum(IV) complex to its cytotoxic platinum(II) counterpart and release the axial ligands [8]. A few platinum-based prodrugs have already been investigated in clinical trials. One example is satraplatin, the first orally available platinum(IV) prodrug, which has been investigated in multiple clinical trials since 2005 [9]. Of note, satraplatin successfully reached clinical trial phase III (NCT00069745), but ultimately failed approval due to a lack of superior efficiency for overall survival compared to standard therapy. Nevertheless, utilizing the paradigm of platinum(IV) prodrugs is an effective way to improve anticancer activity and to overcome resistance mechanisms [10,11], for example, by attaching synergistic compounds to the axial position(s). Furthermore, 4-phenylbutyrate (PhB, 4-PBA), clinically approved for the treatment of urea cycle disorders, has recently attracted attention as an anticancer compound due to its promising synergistic activity with DNA-binding drugs [12,13]. In fact, PhB is a fatty acid analog with a wide range of applications and suggested modes of actions [14]. On the one hand, PhB is a chemical chaperon, stabilizing protein conformation and, thus, one of the most frequently used endoplasmic reticulum (ER) stress inhibitors [15,16,17]. On the other hand, PhB influences cellular metabolism by binding to coenzyme A (CoA) via thiol adduct formation [18] as well as inhibiting histone deacetylase (HDAC) [19]. Moreover, PhB is able to directly inhibit pyruvate dehydrogenase kinase 1 (PDK1) in the mitochondria [20]. Even though many pathways are not yet fully understood, the strong synergism with cisplatin [21,22] prompted the development of “dual-action” cisplatin-based platinum(IV) prodrugs [8,23]. For example, cisPt(PhB)2, which carries two axial PhB residues, showed encouraging preliminary results in cell culture experiments. The aim of this study was to further characterize the biological activity of this compound in (cisplatin-resistant) cancer cells in vitro and in vivo. Our collected data indicate that the new platinum complex is especially interesting for the treatment of cancer cells with a pronounced “Warburg”-like metabolic phenotype.
## 2.1. Chemicals and Reagents
CisPt(PhB)2 was prepared as previously published [8], dissolved in dimethyl sulfoxide (DMSO) to obtain a stock solution of 10 mM, and then aliquoted and kept at −20 °C until further analysis. Cisplatin was purchased from LC laboratories (Woburn, MA, USA). For cell culture use, cisplatin was dissolved in dimethylformamide (DMF) to obtain a stock solution of 11 mM. The solution was then diluted in serum-free RPMI-1640 medium to a concentration of 5 mM. 4-phenylbutyric acid (Sigma Aldrich, St. Louis, MI, USA) was freshly dissolved in double-distilled H2O to obtain a stock concentration of 20 mM. Triacsin C (Merck, Darmstadt, Germany, 10 mM stock), perhexiline (Merck, Darmstadt, Germany, 10 mM stock), etomoxir (Adooq Bioscience, Irvine, CA, USA, 100 mM), and 5,5,6,6-tetrachloro-1,1,3,3-tetraethylbenzimidazol-carbocyanine iodide (JC-1, Enzo Life Sciences, New York, NY, USA, 1 mg/mL) stock solutions were prepared in DMSO and stored at −20 °C until analysis.
## 2.2. Cell Culture
The cell lines, their sources, and specific growth medium are summarized in Table S1. TP53 status for A2780, Capan-1, PANC-1, and MDA-MB231 cells were extracted from the IARC database, Aug 2021; for VM-1, TP53 status was assessed in the course of the precision medicine platform MONDTI [24]. All media were supplemented with $10\%$ fetal calf serum (FCS, PAA, Linz, Austria). Cells were kept in a humidified atmosphere at 37 °C and $5\%$ CO2. Cultures were checked for mycoplasma contamination before use. Cisplatin-resistant P31 and A2780 cells were selected every week with 4 and 1 µM cisplatin, respectively.
## 2.3. Cytotoxicity Assays
Cells were seeded in 96-well plates at 3500–6000 cells/well depending on the proliferation rate of the respective cell line. On the next day, the cells were treated with increasing concentrations of the compounds or their combinations for 72 h. Cell viability was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT)-based vitality assay (EZ4U; Biomedica, Vienna, Austria) following the manufacturer’s recommendations. To calculate the IC50 values (concentration that induces a reduction in cell number to $50\%$), full dose–response curves were generated using GraphPad Prism (GraphPad Software, San Diego, CA, USA, version 8.0.1 for Windows).
## 2.4. ICP-MS Measurements of Cell Uptake
Cells were seeded in triplicates in 6-well plates (Starlab, Hamburg, Germany) at concentrations to reach $80\%$ confluence after 24 h. Cells and blank wells containing no cells were treated with 5 or 10 µM of the compounds for 2 h. Subsequently, wells were washed twice with phosphate-buffered saline (PBS) and incubated with 67–$69\%$ nitric acid (VWR, Darmstadt, Germany) for 1 h. The lysates were further diluted 1:20 with H2O and analyzed using inductively coupled plasma-mass spectrometry (ICP-MS) for their platinum content. The cell number was calculated from duplicates, and platinum concentration was normalized to the cell number. Samples were measured using an Agilent 7800 ICP-QMS instrument (Agilent Technologies, Tokyo, Japan) equipped with an Agilent SPS 4 autosampler (Agilent Technologies, Tokyo, Japan) and a MicroMist nebulizer at a sample uptake rate of approx. 0.2 mL/min. The Agilent MassHunter software package (Workstation Software, Version C.01.04, 2018, Agilent, Santa Clara, CA, USA) was used for data evaluation. All of the measured samples were blank-corrected. Elemental standard solutions were purchased from Labkings (Hilversum, The Netherlands). The instrument was tuned on a daily basis.
## 2.5. Animals
Eight- to twelve-week-old BALB/c (Envigo, San Pietro Al Natisone, Italy) and C57BL/6 mice (Janvier Labs, Le Genest-Saint-Isle, France) were kept in a pathogen-free environment with a 12 h light–dark cycle with ad libitum access to food and water. Every procedure was performed under sterile conditions. This study was conducted according to the guidelines of the Declaration of Helsinki, approved by the Ethics Committee for the Care and Use of Laboratory Animals at the Medical University Vienna (proposal number BMWF-$\frac{66.009}{0084}$-II/3b/2013), and performed according to the guidelines from the Austrian Animal Science Association and from the Federation of European Laboratory Animal Science Associations (FELASA).
## 2.6. Anticancer Activity In Vivo
Murine CT26 (5 × 105 cells) or B16 cells (1 × 105 cells) were injected subcutaneously into the right flank of male BALB/c or C57BL/6 mice, respectively. Body weight was measured daily. Animals were treated with cisPt(PhB)2 (20 mg/kg, dissolved in $10\%$ DMSO, p.o.). The concentration of cisPt(PhB)2 was chosen based on previously unpublished toxicity studies (personal communication D. Gibson). Tumor size was measured daily using a caliper and tumor volume was calculated with the formula: (length × width2)/2. Animals were sacrificed if tumors were ulcerated or if the tumor length exceeded 2 cm.
## 2.7. Live-Cell Microscopy
Cells were seeded in a µ slide (8-well glass bottom, ibidi, Gräfelfing, Germany) at a cell number of 4 × 104 cells/well and allowed to recover for 24 h. In the case of the lipid droplet analysis, bodipy™ $\frac{493}{503}$ (Thermo Fisher, Waltham, MA USA) was added 15 min prior to treatment at a concentration of 0.5 µM to the supernatant. Cells were treated with the compounds for 72 h and two images per well (bright field and FITC-channel) were taken every 20 min using a Nikon Eclipse Ti with a 20X (Super Plan Fluor NA 0.45 Ph1) objective in an OkoLAB Incubation Box ($5\%$ CO2, 37 °C, passive humidifier) with a PCS sCMOS monochrome camera 4.2 MPxl. Images at specific time points (0, 6, 12, 18, 24 h) were analyzed using ImageJ software. The image background was subtracted, the threshold was applied, and the integrated density as the area occupied by cells was quantified. For the analysis of migration, the cells were manually tracked over 24 h using ImageJ, and the coordinates for each individual cell and time point were obtained. The DiPer migration tool for Microsoft Excel was used to calculate the speed of cell migration and generate plots of origin for each cell to depict individual movements over time [25].
## 2.8. Cell Cycle Analysis
Cells were seeded in 6-well plates (Starlab, Hamburg, Germany) at concentrations to reach $70\%$ confluence on the next day. Cells were then treated for 24 h and collected using trypsinization. Cell pellets were resuspended in 100 µL $0.9\%$ NaCl and added dropwise to 1.8 mL $70\%$ ethanol for fixation (at least 1 h at −20 °C). Fixated cells were centrifuged and incubated with 100 µg/mL RNase A (Merck, Darmstadt, Germany) for 30 min at 37 °C. Subsequently, nuclei were stained with 5 µg/mL propidium iodide (PI, Merck, Darmstadt, Germany) for 30 min at 4 °C and analyzed using flow cytometry (LSRFortessaTM X-20 Cell Analyzer, BD Biosciences, Franklin Lakes, NJ, USA). Quantification was performed using FlowJo_V10 software (Becton, Dickinson and Company, Franklin Lakes, NJ, USA).
## 2.9. Cell Death Analysis
CT26 or B16 cells were seeded in 6-well plates (5 × 105 cells in 1 mL per well) and left to recover overnight. The next day, cells were treated with 5 µM of cisPt(PhB)2 for different time points. The supernatant and trypsinized cells were collected. As a control for dead cells, cells were incubated on a heating block (60 °C) for 30 min. The other samples were centrifuged with 300× g for 5 min and cells were stained with annexin V (AV, 1:50) and PI (1:50) in annexin V-binding buffer (ABB) (10 mM HEPES, 140 mM NaCl, 2.5 mM CaCl2) for 15 min at room temperature in the dark. The samples were diluted with 200 µL of ABB and directly measured at 530 and 610 nm using flow cytometry (LSRFortessaTM X-20 Cell Analyzer, BD Biosciences, Franklin Lakes, NJ, USA).
## 2.10. Nucleus Staining
Cells were seeded in 6-well plates and allowed to recover overnight. The next day, cells were treated with the compounds for 24 h and collected using trypsinization. The cell suspension was transferred to a slide using a cytocentrifuge (CytospinTM 4, Thermo Fisher Scientific, Schwerte, Germany) at 1000 rpm for 5 min. Samples were fixated in an acetone:methanol mixture (1:1) for 10 min at −20 °C and mounted in VectaShield with 4′,6-diamidino-2-phenylindole (DAPI) (VECH-1200, Szabo Scandic, Vienna, Austria). Samples were analyzed using confocal microscopy (LSM700, Zeiss, Oberkochen, Germany). For each condition, five images were taken with a 63X Plan-Apochromat (NA 1.4 Oil DIC) objective (zoom 0.5, 203.2 × 203.2 µm) and nuclear morphology was analyzed and quantified under blinded conditions using ImageJ 1.53 t (Java 1.8.0_345 (64-bit), cell counter) and the particle analysis plugin.
## 2.11. Albumin Uptake
CT26 or B16 cells were seeded in 6-well plates (5 × 105 cells in 1 mL per well) and left to recover for 24 h. FITC-conjugated bovine serum albumin (10 µM, A9771, Sigma Aldrich) was diluted with serum-free RPMI medium and added to the cells. After 3 h, the cells were harvested using trypsinization, diluted in PBS, and then fluorescence was measured at 530 nm using flow cytometry (LSRFortessaTM X-20 Cell Analyzer, BD Biosciences, Franklin Lakes, NJ, USA).
## 2.12. Cellular Albumin Uptake
Cells were seeded (1.2 × 104 cells/well) on 8-well chamber slides (Falcon™, Corning Brand, USA) in growth medium with $10\%$ FCS and allowed to recover for 48 h. To determine the cellular uptake of albumin, the cells were treated with 10 µM FITC-labeled albumin (dissolved in serum-free RPMI medium) for 3 h and subsequently fixated using a solution of $4\%$ paraformaldehyde dissolved in PBS with the pH adjusted to 7.4 (Merck, Darmstadt, Germany) for 15 min at room temperature. Spots were washed 4-timeswith PBS. Additionally, a staining solution of $0.3\%$ DAPI and $0.45\%$ rhodamine-labeled wheat germ agglutinin (WGA) (Vector laboratories, Newark, CA, USA) was added to stain cell nuclei and cell membranes, respectively. Next, the slide was mounted with non-hardening mounting medium (Vectashield® Mounting Media, Vector laboratories, Newark, CA, USA), and analyzed using fluorescence measurement with a confocal microscope (Zeiss, Oberkochen, Germany) and image processing using ZEN lite software (Zeiss, Oberkochen, Germany).
## 2.13. Cellular Respiration Experiments
Cells were seeded into 96-well plates (XFe96/XF Pro Cell Culture Microplates, Agilent, USA) at a cell density of 2 × 104 cells/well in 80 μL of cell culture medium supplemented with $10\%$ FCS and cultured overnight. Cells were treated with 5 µM of cisPt(PhB)2 or solvent 4 h prior to measurement. The Seahorse Mito Stress Test (Seahorse XFp Cell Mito Stress Test Kit, Agilent, USA), with and without etomoxir, as well as the Glycolytic Rate Assay (Seahorse XFp Glycolytic Rate Assay Kit, Agilent, USA) were used for the measurement of the extracellular oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Assays were performed according to manufacturer’s recommendations. After the incubation period, the medium was replaced with Seahorse XF DMEM assay medium (pH 7.4, Agilent, Santa Clara, CA, USA) supplemented with 10 mM glucose, 2 mM glutamine, as well as 1 mM pyruvate, and incubated for 1 h in a CO2-free incubator at 37 °C. The kit reagents were sequentially added from the injection ports of the sensor cartridges (XFe96/XF Pro sensor cartridges, Agilent, USA) to a final concentration of oligomycin 1.5 μM, FCCP 1 μM, rotenone/antimycin A 0.5 μM, and etomoxir 4 µM, in the case of the Mito Stress Test, and of 2-deoxyglucose 50 mM and rotenone/antimycin A 0.5 µM, in the case of the Glycolytic Rate Assay. For quantification of cell numbers, 4 μM Hoechst 33258 (1 mg/mL in PBS, pH 7.4) was added. Following Seahorse analyses, cells were imaged, and Hoechst fluorescence was measured in the DAPI channel using the Cytation5 Cell Imaging Multimode Reader (BioTek as part of Agilent, Santa Clara, CA USA) for normalization. Data were processed with the Seahorse Wave Pro Software (version 10.0.1, Agilent, Santa Clara, CA, USA). OCR and ECAR levels are displayed per 1000 cells.
## 2.14. JC-1 Flow Cytometry Analysis
Cells were seeded at a concentration of 6 × 105 cells/well into 6-well plates and allowed to recover overnight. On the next day, cells were treated with the compounds for 24 h. Then, the cell supernatant and trypsinized cells were collected. Cell pellets were washed with PBS and cells were stained with JC-1 solution (1:100 diluted in medium) and incubated for 15 min at 37 °C in the dark. Cells were washed with medium, centrifuged, resuspended in PBS, and analyzed at 530 nm and 605 nm using flow cytometry (LSRFortessaTM X-20 Cell Analyzer, BD Biosciences, Franklin Lakes, NJ, USA). Quantification was performed using FlowJo_v10 software (Becton, Dickinson and Company, Franklin Lakes, NJ, USA)
## 2.15. Statistical Analysis
Statistical analysis was performed using GraphPad Prism version 8.0.1 for Windows (GraphPad Software, San Diego, CA USA).
## 3.1. Anticancer Activity of cisPt(PhB)2 in Platinum-Resistant and -Sensitive Cancer Cells In Vitro
In this study, a broad panel of cancer cell lines of different human or murine origin was used including colorectal, breast, ovarian, and pancreatic carcinoma as well as melanoma and mesothelioma to test the anticancer activity of cisPt(PhB)2. Moreover, several cell models with known (platinum) resistance mechanisms were included. IC50 values were calculated from viability experiments after 72 h incubation and are depicted in Table 1. *In* general, while cisplatin was able to inhibit cancer cell growth at low µM concentrations, the cisPt(PhB)2 IC50 values were mainly in the nM range (Figure 1A,B). Noteworthy, in good agreement with the literature [26,27,28], PhB alone showed only rather low cytotoxicity with IC50 values in the mM range (Figure 1B). Across all cell lines tested, cisPt(PhB)2 was on average ~36-fold more active compared to cisplatin, paralleled by an enhanced uptake of the complex into the cancer cells (Figure 1C). Both findings are in good agreement with previous results [8]. Of note, while cisplatin had low activity in colorectal cancer cell lines (average IC50 value ~8.8 µM), cisPt(PhB)2 showed a ~45-fold higher activity in this tumor entity. This is especially interesting as cisplatin typically has reduced efficacy against gastrointestinal cancers in the clinic [29]. A similar increase in activity was also observed in pancreatic cancer cell models. In total, the cell lines most sensitive to cisPt(PhB)2 treatment were the human colon carcinoma RKO, the human pancreatic carcinoma Capan-1, and the human ovarian carcinoma cell line A2780.
With regard to drug resistance, two cell models with acquired resistance to cisplatin were investigated: a subclone of the ovarian carcinoma model A2780 and the mesothelioma cell line P31. While in the resistant subclones, A2780/cisR and p31/cisR cisplatin were up to 5.6-fold less effective compared to parental cells, cisPt(PhB)2 toxicity was widely unchanged, suggesting that cisPt(PhB)2 might not be affected by the same resistance mechanisms as cisplatin [30]. In addition, the TP53 (mutation) status of the cancer cells, which has been associated with intrinsic resistance to platinum drugs [31,32], had no profound impact on the sensitivity of the cells to cisPt(PhB)2 in contrast to cisplatin. Thus, the complex is promising for the treatment of cisplatin-resistant cancer types.
## 3.2. Anticancer Activity In Vivo
As a next step, we were interested in the anticancer activity of cisPt(PhB)2 in vivo. To this end, two murine cell models (CT26 and B16) were injected subcutaneously as allograft models into immunocompetent mice of two different strains (according to their strain of origin: Balb/c for CT26 and C57BL/6 for B16).
Noteworthy, the C57BL/6 mouse strain in general displays an enhanced sensitivity to platinum drugs, so frequent adaptions in the applied doses are necessary to avoid toxicity. To test cisPt(PhB)2, mice received 20 mg/kg per oral gavage, and anticancer efficacy was compared to mice receiving the solvent (Figure 2). In the case of CT26-bearing animals, even repeated administration of the cisPt(PhB)2 (three consecutive days for two weeks), only slightly influenced the tumor growth and had no impact on overall survival (Figure 2A). In the case of the second mouse model, comparable to other platinum drugs, the C57BL/6 mouse strain was more sensitive to cisPt(PhB)2; thus, only two applications were possible. Nevertheless, two consecutive applications of cisPt(PhB)2 were able to significantly stop B16 tumor growth for up to 18 days, resulting in a significantly prolonged overall survival of the animals (Figure 2B). These experiments indicate that B16 tumors are distinctly more sensitive to cisPt(PhB)2 than CT26, which prompted us to investigate the cellular and molecular mechanisms underlying the activity of cisPt(PhB)2 in these two cell models.
## 3.3. CisPt(PhB)2 Displays an Earlier Onset of Cytotoxicity than Cisplatin, Which Is More Pronounced in B16
To further examine the cytotoxic effects of the compounds on CT26 and B16 cells, we performed live-cell microscopy analyses. In more detail, the cells were treated at a concentration of 5 µM and images were taken every 20 min for 24 h (Figure 3A,B). For cisplatin, cells remained viable over the whole imaging period with reduced cell proliferation, especially in the case of B16. This is not unexpected as DNA-targeting compounds typically require a longer incubation period to take a cytotoxic effect, as cell division necessarily results in DNA damage upon DNA platination [33]. Hence, we unexpectedly see the first effects of cisPt(PhB)2 treatment already substantially earlier (before the entire replication-dependent cytotoxicity mechanism of cisplatin could have occurred). In more detail, both cell models visibly reacted to cisPt(PhB)2 within the first few hours by retracting into roundish morphology. In addition, CT-26 cells strongly reduced their movement (Figure 3C,D), and the induction of cell death was visible after 12 h. In contrast, in B16 cells, cell death was visible already after 2–3 h, which also prohibited the movement analysis in this cell line. Interestingly, the morphological reactions induced by cisPt(PhB)2 also differed from the cells upon PhB treatment (Supplementary Figure S1). This, on the one hand, suggests again, that cisPt(PhB)2 might have additional modes of action compared to cisplatin or PhB alone. On the other hand, it supports the hypothesis that there are differences in the sensitivity and possibly cause of cell death in these two cell models.
## 3.4. Differences in Cell Death Induction by cisPt(PhB)2 in CT26 and B16 Cells
To gain more insights into the mode of cell death induced by cisPt(PhB)2, annexin V/PI stains were performed and measured using flow cytometry at different time points (1–24 h). In good agreement with the live-cell imaging, apoptotic cell death was detected in up to ~$80\%$ of the CT26 cells after 16 h (Figure 4A). Unexpectedly, in the B16 model, only ~$35\%$ of the cells could be characterized as “apoptotic” or “necrotic” at the 24 h time point (Figure 4B). This was in line with data from the DAPI stains, where only ~$10\%$ of the cells displayed apoptotic nuclei in B16 cells 24 h after treatment with cisPt(PhB)2 (Figure 4C).
Moreover, in both CT26 and B16, the surviving cell population at the 24 h time point was characterized by a distinct loss of the mitotic cell fraction (Figure 4D). In the case of cisplatin, both cell models responded rather similarly with mild apoptosis induction, enlarged nuclei (Supplementary Figure S2), and the loss of the mitotic cell population (Figure 4D) indicating activation of the G2-checkpoint and cell cycle arrest. This was further confirmed using the PI stains of ethanol-fixed cells, where 24 h treatment with cisplatin resulted in an enriched S-G2/M (CT26) or G2/M (B16) fraction, respectively (Supplementary Figure S3). In contrast, for cisPt(PhB)2, again differences in the cell populations surviving 24 h treatment were seen between the two cell models. While surviving CT26 cells had distinctly deranged cell cycle distribution, the remaining B16 cells did not vary in their cell cycle distribution from the untreated cells (Supplementary Figure S3). In conclusion, the very fast cell death induction of cisPt(PhB)2 indicates, in contrast to cisplatin, that DNA damage plays only a minor role in the activity of the new complex. In addition, B16 cells are more sensitive to this mode of cytotoxicity than CT26 cells.
## 3.5. CT26 and B16 Cells Differ in Their Metabolism and Albumin Homeostasis
PhB is an aromatic short-chain fatty acid, which, in addition to its ER stress-protecting properties, has also been discussed to impact on the cellular metabolism by direct reaction with CoA, an essential molecule for fatty acid metabolism [34,35]. The most important transport protein of fatty acids in the blood serum is albumin [36]. During our latest studies on the albumin homeostasis of cancer cells [37], we discovered that CT26 cells have a distinctly higher albumin uptake compared to B16 cells (Figure 5A,B). To investigate whether the presence of albumin in the cell supernatant has an impact on the cytotoxicity of cisplatin or cisPt(PhB)2, we performed a series of viability assays (Figure 5C–F). The addition of albumin to the cell culture medium resulted in reduced cytotoxicity of both cisplatin as well as cisPt(PhB)2. In more detail, cisplatin activity was 2.4-fold and 1.4-fold reduced in CT26 and B16 cells, respectively. In the case of cisPt(PhB)2, this effect was much more pronounced in the CT26 cells, where we observed a >5.2-fold reduction in activity upon albumin addition (25 g/L), while only 1.7-fold protection was detected in B16 cells. Consequently, we hypothesized that CT26 and B16 exhibit differences in their metabolism, resulting in a reduced need for fatty acids, and affecting their sensitivity to cisPt(PhB)2. According to the literature, CT26 cells display high ATP synthase activity, depend on aerobic respiration, and concomitantly consume high levels of oxygen [26]. In contrast, B16 cells were reported to be characterized by high lactate production [38], suggesting that these cells display “Warburg-like” characteristics [39]. To confirm this, we analyzed the energy metabolism of these models with Seahorse measurements using the glycolytic rate assay as well as the mitochondrial stress test. As shown in Figure 6A,B, CT26 cells had only half the basal lactate production of the B16 cells. Moreover, inhibition of mitochondrial respiration by rotenone/antimycin A (Rot/AA) forced CT26 cells into full glycolysis (max. lactate production), while extracellular acidification in B16 cells was not affected. This demonstrates that the amount of acidification in the B16 cells is mainly due to glycolysis and not due to mitochondrial CO2. Additionally, it indicates that B16 cells already run at the maximal glycolysis rate. Inhibition of glycolysis by exposure to the glucose analog 2-DG confirmed that these processes are glycolysis-dependent. With regard to the mitochondrial activity (Mito Stress Test, Figure 6B,D), CT26 had a 2.3-fold higher OCR than B16 cells, which could be completely inhibited by the ATP synthase inhibitor oligomycin.
Moreover, the addition of the protonophore and uncoupling agent carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP) revealed that the total mitochondrial respiratory capacity of CT26 cells was more than 2.3-fold higher than in B16 cells. When the cells were treated with 5 µM cisPt(PhB)2, only B16 cells were affected in their respiration.
More precisely, cisPt(PhB)2 had no effect on CT26 cells, while it reduced the maximal mitochondrial respiration in B16 cells by ~$40\%$ (Figure 6 and Figure S4). Since the treatment also could not restore glycolytic capacity by inhibition of mitochondrial respiration via Rot/AA (but instead reduced the lactate release in B16 by ~$25\%$), a general inhibition of the B16 cells respiration capacity seems likely, rendering them sensitive towards the metabolic effect of cisPt(PhB)2.
To further investigate the metabolic differences with regard to cisPt(PhB)2 activity, we decided to examine the mitochondrial membrane potential (ΔΨ) using JC-1 stains. This cationic carbocyanide dye accumulates in mitochondria and exists as monomers or aggregates, which alters the emission spectrum in accordance to the mitochondrial ΔΨ [40]. While CT26 cells harbor normal mitochondrial function, in the B16 line, a higher fraction of cells already exhibits low mitochondrial ΔΨ in untreated conditions (Figure 6E).
This is in good agreement with their mitochondrial deficiency indicated by the Seahorse experiments (compare Figure 6A–D). Upon cisPt(PhB)2 treatment (24 h), CT26 cells displayed a significantly elevated level of depolarized mitochondria (Figure 6F). In contrast, the mitochondrial ΔΨ of B16 cells remained largely unaffected upon treatment with cisplatin or cisPt(PhB)2. Together with the data above, this indicates that cells with normal respiratory capacities such as CT26 (or MCF-7 [8]) die from cisPt(PhB)2-induced apoptosis via the intrinsic mitochondrial pathway, while this process is not activated in “Warburg-like” cells such as B16.
## 3.6. CisPt(PhB)2 Activity Is Associated with Enhanced Lipid Droplet Formation
To investigate the impact of cisPt(PhB)2 on fatty acid metabolism, we performed live-cell microscopic analysis using bodipy™ $\frac{493}{503}$ as a marker for neutral lipid as present in lipid droplets [41]. Generally, under control conditions, CT26 cells displayed 10-fold higher basal levels of lipid droplets than B16 cells (Figure 7A,B). Treatment with cisPt(PhB)2 induced lipid droplet accumulation in both cell lines. Notably, this effect was much more pronounced in B16 (13-fold increase in bodipy™ $\frac{493}{503}$ foci compared to the basal levels) than in CT26 cells (2.2-fold increase), shifting cisPt(PhB)2-treated B16 cells into lipid droplet concentrations comparable to untreated CT26. To gain more insight into the role of lipid droplets in cisPt(PhB)2 activity, we co-treated the cells with the non-specific long-chain acyl-CoA synthetase inhibitor triacsin C. The compound prevents formation of acyl fatty acids, which are the building blocks of lipid droplets and, thus, is supposed to inhibit fatty acid-induced apoptosis (lipoapoptosis) [42]. The combination treatment for 24 h had strong antagonistic effects in the case of CT26 but not in B16 cells (Figure 7C,D), suggesting that, in fact, lipid droplet formation supports cisPt(PhB)2 activity. As for catabolism, fatty acids need to be transported across the mitochondrial membrane by palmitoyltransferases (CPTs) [43]; thus, we investigated the impact of the CPT inhibitors etomoxir or perhexiline. Noteworthy, preliminary Seahorse experiments with etomoxir alone indicated a stronger dependence of CT26 as compared to B16 cells on mitochondrial fatty acid catabolism (Figure 7E). Thus, it was rather unexpected that, especially in the B16 cells, a visible antagonism of etomoxir with cisPt(PhB)2 was observed (while the compounds were additive in CT26 cells). In contrast, perhexiline had weakly antagonistic effects to a similar extent in both cell models.
Taken together, these data suggest that cellular lipid metabolism plays a role in cisPt(PhB)2 activity and that cells with “Warburg-like” phenotype (characterized by reduced and abnormal mitochondrial activity and enhanced aerobic glycolysis) are more vulnerable to this complex than cells with “normal” metabolism.
## 4. Discussion
Platinum-based drugs are among the most frequently used anticancer agents, especially at the late stage of the disease. However, drug resistance, for example, based on reduced drug uptake (e.g., downregulation of CTR1), changed damage recognition (e.g., TP53 mutation), or enhanced DNA damage repair (e.g., via DNA excision repair) distinctly hampers successful therapy [32]. Consequently, compounds with improved anticancer efficacy and altered activity profiles are of central interest. Here, drugs which exploit differences between healthy and malignant cells are especially promising because they allow more selective targeting of the cancer tissue. In this study, we investigated the mode of action of a novel dual-action platinum(IV) complex, cisPt(PhB)2, which releases upon activation two clinically used drugs: cisplatin and PhB [8]. PhB is an interesting combination partner for cisplatin, as there are several reports on their synergistic mode of action [13,44]. However, PhB is limited in its activity, and due to its negative charge at physiological pH, its passage through the cell membrane is very limited. This is also reflected by the very high IC50 values of the compound (in the mM range) in cell culture studies [26,27,28]. CisPt(PhB)2 facilitates synergistic accumulation of both cisplatin and PhB. On the one hand, PhB increases the lipophilicity compared to cisplatin, hence facilitating enhanced uptake of platinum. On the other hand, it neutralizes the negative charge of PhB, enhancing PhB accumulation. Indeed, cisPt(PhB)2 was highly active in the nM range against a broad panel of cancer cell models and is able to circumvent the most common resistance mechanisms against platinum drugs. This is exciting as cisPt(PhB)2 is distinctly more active in vitro than the two “parent compounds”. These data are also in good agreement with the work of Raveendran et al. [ 8], who already reported that, although cisPt(PhB)2 induced the stabilization of TP53 in MCF-7 cells, the TP53 knock-out subclone of HCT116 showed similar sensitivity to cisPt(PhB)2 as the parental cells. This suggests that, contrary to cisplatin, cisPt(PhB)2 does not depend on TP53 (a mediator for DNA damage response) for its activity. This is rather surprising since, according to reports in the literature, the anticancer activity of a set of HDAC inhibitors (including PhB) is at least in part based on TP53 [45,46]. In addition, more recently, Romeo et al. reported a selective sensitivity of glioma cell lines carrying a mutated version of TP53 to PhB [26]. Thus, our viability data suggested that cisPt(PhB)2 might have modes of action other than the so far designated DNA-targeting/HDAC-inhibiting properties [8].
In addition to the cell culture analysis, the first in vivo experiments using immune-competent allograft models suggested that cisPt(PhB)2 can be successfully applied orally with promising activity especially against B16 melanoma cells. Noteworthy, B16 cells are of the so-called “Warburg” phenotype [47,48], which summarizes their distinct metabolic state differently from healthy tissue. Warburg-like cells are characterized by abnormal mitochondrial activity, which pushes the cells towards aerobic glycolysis [47,48]. As a consequence, these cells have a reduced uptake of the (fatty acid) carrier serum protein albumin together with distinct differences in fatty acid metabolism (compare Figure 5A) [49]. Our data further suggest that Warburg-like cells are less capable of coping with cisPt(PhB)2, leading to the rapid induction of a non-apoptotic form of cell death. In contrast, in cancer cells with healthy mitochondria (e.g., CT26 and MCF-7 [8]), apoptosis via the mitochondrial pathway was seen. Noteworthy, cisPt(PhB)2 distinctly differed in its mode of action from cisplatin, and the rapid cell death induction (within a few hours) especially suggested that DNA damage is not involved in the first stage of its activity. Thus, we expect that the cisplatin arm of the mode of action will affect mainly the cell fraction surviving the first cytotoxic phase of drug activity (still, this functionality of the complex might be effective in killing potential residual cell clones later on). However, whether the observed anticancer activity originates solely from the released PhB is difficult to answer. A big obstacle in the investigation of this question is the ~10.000-fold difference in IC50 values between cisPt(PhB)2 and PhB. Moreover, it is unclear how the potential differences in drug delivery impact the intracellular PhB distribution, which allows for new or more pronounced (PhB-associated) biological activities.
*In* general, PhB is a drug with multiple modes of action. It is, for example, a chemical chaperon, stabilizing protein conformation, and, thus, one of the most frequently used ER stress inhibitors [15,16,17]. However, to the best of our knowledge, the exact mechanism underlying this effect is not fully understood. What is known is that PhB influences cellular metabolism by binding to CoA via thiol adduct formation [18] and by inhibiting histone deacetylase (HDAC) [19]. Moreover, PhB is able to directly inhibit mitochondrial PDK1 [20] as well as β-oxidation in the mitochondria in a competitive manner [34]. Interestingly, although PhB is approved for the treatment of certain metabolism-associated diseases (e.g., urea cycle disorders), the impact of this drug with respect to typical cancer-associated metabolic changes such as the Warburg effect is widely unexplored. This is surprising considering that the difference in metabolic properties between healthy and malignant tissues provides a promising Achilles heel for tumor-specific cancer treatment. Our data suggest that Warburg-like cells might be hypersensitive to the cellular PhB delivery by cisPt(PhB)2 and respond with non-apoptotic cell death induction. In more detail, B16 cells showed reduced fatty acid uptake via albumin and thus lower cellular lipid pools (10-fold fewer lipid droplets compared to CT26 cells). This can be explained by the fact that mitochondrial respiration in cancer cells usually is more dependent on fatty acid metabolism than the glucose pathway [49]. CisPt(PhB)2 seems to impact these pathways, stimulating the formation of lipid droplets. Moreover, inhibitors that interfere with cellular fatty acid metabolism such as triascin C (inhibitor of the acyl CoA synthetase and thus prevents formation of lipid droplets [50]), or etomoxir and perhexilin (both inhibiting the transport of fatty acids into the mitochondria [51,52]), affected cisPt(PhB)2 activity. Interestingly, co-treatment of cisPt(PhB)2 with triascin C only led to an antagonistic effect in CT26 cells. This suggests that in CT26 cells, cell death is mediated by cytotoxic lipid intermediates via the intrinsic mitochondrial pathway (Figure 8). However, this also allows these cells to activate anti-apoptotic signaling pathways in the mitochondria [53]. Consequently, the mitochondria with their specific fatty acid metabolism and apoptosis-regulating function could serve as a buffer against cisPt(PhB)2-induced effects. In contrast, this option is limited in “Warburg-like” cells such as B16, forcing them to die via a yet undefined, potentially lipid-associated alternative pathway. In this context, the difference between etomoxir and perhexiline is noteworthy because the activity of both compounds has been connected to the transport of fatty acids into the mitochondria. Etomoxir displayed antagonistic activity mainly in B16 cells (while perhexiline had similar activity in CT26 and B16 cells). This effect can be explained by an additional etomoxir mode of action, namely the binding to CoA at higher concentrations [54], a functionality shared with PhB [18]. Due to their reduced dependency on fatty acids for mitochondrial respiration, B16 cells are assumed to produce all of their acetyl-CoA (needed for protein acetylation) via glycolysis-derived pyruvate. This hypothesis would be in line with the inhibition of PDK1 through PhB, leading to an enhanced activation of the pyruvate dehydrogenase that converts pyruvate to acetyl-CoA. This could render these cells more sensitive to the CoA-binding of PhB. Nevertheless, the exact mechanism(s) underlying the effects observed with cisPt(PhB)2 definitely warrant more in-depth investigations, and further studies are required to analyze the exact impact of cisPt(PhB)2 on cancer cell metabolism. This is especially of interest considering several reports that drug-resistant cancer cells are characterized by an altered metabolism [32].
In summary, cisPt(PhB)2 is a novel orally active anticancer compound using a cisplatin-releasing platinum(IV) platform for the improved delivery of PhB into cancer cells. This results in enhanced anticancer activity against metabolically altered cancer cells in vivo. Therefore, cisPt(PhB)2 is an interesting candidate for further preclinical investigations.
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|
---
title: Factors Influencing Antibody Response to SARS-CoV-2 Vaccination
authors:
- Cathrin Kodde
- Sascha Tafelski
- Efthimia Balamitsa
- Irit Nachtigall
- Marzia Bonsignore
journal: Vaccines
year: 2023
pmcid: PMC9967627
doi: 10.3390/vaccines11020451
license: CC BY 4.0
---
# Factors Influencing Antibody Response to SARS-CoV-2 Vaccination
## Abstract
Vaccination plays a key role in tackling the ongoing SARS-CoV-2 pandemic but data regarding the individual’s protective antibody level are still pending. Our aim is to identify factors that influence antibody response following vaccination in healthcare workers. This single-center study was conducted at Evangelische Kliniken Gelsenkirchen, Germany. Healthcare workers were invited to answer a questionnaire about their vaccinations and adverse reactions. Subsequently, the level of anti-receptor binding domain (RBD) IgG antibody against SARS-CoV-2′s spike protein through blood samples was measured. For statistics, we used a defined correlation of protection (CoP) and examined risk factors associated with being below the given CoP. A total of 645 employees were included and most were female ($$n = 481$$, $77.2\%$). A total of $94.2\%$ participants had received two doses of vaccines ($$n = 587$$) and $12.4\%$ ($$n = 720$$) had been infected at least once. Most common prime-boost regimen was BNT162b2 + BNT162b2 ($57.9\%$, $$n = 361$$). Age ($p \leq 0.001$), days since vaccination ($$p \leq 0.007$$), and the homologous vaccination regimen with ChAdOx + ChAdOx ($$p \leq 0.004$$) were risk factors for the antibody level being below the CoP, whereas any previous COVID-19 infection ($p \leq 0.001$), the number of vaccines ($$p \leq 0.016$$), and physical complaints after vaccination ($$p \leq 0.01$$) were associated with an antibody level above the CoP. Thus, age, vaccination regimen, days since vaccination, and previous infection influence the antibody level. These risk factors should be considered for booster and vaccinations guidelines.
## 1. Introduction
At the beginning of the pandemic and before vaccination programs were implemented, SARS-CoV-2 was able to hit an immunological naïve population, resulting in a fast spread around the globe with severe outcomes.
Since late 2020, vaccinations against the novel SARS-CoV-2 have been available and early studies showed an initial sufficient vaccination efficacy [1]. However, new variants such as the Delta variant (B.1.617.2) and subsequent variants became able to escape immune recognition and led to increased reports of vaccine breakthroughs [2,3].
To measure vaccine efficacy through the amount of antibodies, there are different quantitative assays that are used in the clinical setting. Some assays measure the number of neutralizing antibodies in IU/mL. Other assays calculate the ligand binding antibody units against SARS-CoV-2 spike protein or receptor binding domain (RBD), either as arbitrary units (AU/mL) or, after adjustment to the WHO standard, as binding antibody units (BAU/mL) [4].
However, the exact level of vaccine-induced antibody response that prevents infection (correlate of protection, CoP) is still pending. A hurdle in the determination of a commonly used CoP lies within the non-standardized assays globally used to detect serum antibody levels. Additionally, the immune defense against SARS-CoV-2 takes place through a complex interplay of cellular and humoral factors. Besides antibodies, the cellular immune response by SARS-CoV-2-specific T-lymphocytes plays an important role [5,6], which makes it difficult to predict the immune response based on a defined threshold alone. Measurement of antibodies is widely used and accepted, as the cellular immune responses are technically difficult to measure.
Besides a definitive CoP in order to classify vaccine efficacy, it is important to know what potential factors may influence the antibody level.
It is known that not only the different types of vaccines (e.g., inactivated, live-attenuated, toxoid) and time since vaccination can alter the immune response, but also intrinsic host factors such as comorbidities (e.g., obesity, cancer, cardiovascular, and autoimmune or chronic diseases) influence the immune response to vaccination [7,8,9]. Age is an important factor, as individuals have a lower vaccine response at the extremes of ages of life. Neonates have a less strong antibody production; the elderly, for example, have a more rapid antibody waning and a decline in antibody response to vaccinations [7,9]. Gender can also influence the antibody response; females are known to build a stronger and longer-lasting vaccine response than males due to genetic and hormonal differences [7,10,11]. At the same time, females have been shown to report more adverse effects following vaccination than males [7,12,13]. These factors are known to alter the antibody level after known vaccinations, but it is not fully known if it also applies for the COVID-19 vaccines. Prior studies examined reactogenicity and immunogenicity of vaccines among healthcare workers but focused on either side effects or serological antibody response [2,14].
Thus, our aim is to examine the antibody titer in vaccinated healthcare workers with possible associations to age, gender, time since vaccination, adverse reactions, and type of vaccine.
## 2.1. Patient Selection and Data Collection
On 22 September 2021, all employees (approximately 1400 persons) of the Evangelische Kliniken in Gelsenkirchen, Germany with a personal email address received an invitation for a free assessment of their antibody titer through a blood sample. To reach employees with no personal email address, the invitation was posted on the hospital’s intranet top news page; additionally, it was printed and displayed in prominent areas of the hospital. The letter included a questionnaire in which participants were asked to complete if were participating. Participation was restricted to employees of the Evangelische Kliniken. Employees who, according to their questionnaire, had no history of vaccination still received antibody testing, but were not included in the study cohort.
For antibody analysis, we used the fully automated access SARS-CoV-2-IgG test by BeckmanCoulter©. This semi-quantitative assay measures IgG antibodies in blood samples directed against the receptor-binding domain of the S-protein of SARS-CoV-2, giving numerical result in arbitrary units (AU) from 2.00 to 450 AU/mL [15]. One major study calculated a CoP against COVID-19 infection of 54 IU/mL [5]. The study examined data from clinical COVID-19 vaccination trials and correlated neutralizing antibody levels with vaccine efficacy [5,16]. This threshold will be used as a reference in our study. Studies showed that AU can be directly compared to IU, because they have a strong, significant correlation. IU measures neutralizing antibodies such as IgG, IgM, and IgA, whereas Anti-RBD IgG antibody is measured in AU. In those studies both neutralizing antibodies and Anti-RBD IgG antibody levels were quantified and a strong correlation was found between these two. Thus, anti-RBD IgG antibody levels are used to assess a level of protection [17,18,19].
Written informed consent was received by all participants. Participation to the survey was voluntary and anonymous. The included questionnaire was developed by infectious diseases experts and the translations of the question can be found in Table 1. All information derived from the questionnaire and was self-reported.
## 2.2. Ethical Consent
The study was approved by the Ethic Committee of the General Medical Council (Ärztekammer) of Westfalen-Lippe (2021-573-f-S) and registered in the German Clinical Trials Register (DRKS 00027266).
## 2.3. Statistical Analysis
Data were analysed using IBM Statistics® (Vs 28.0, IBM corporation, 2021). For descriptive analysis, we presented data with numbers and percentage in nominal data and used mean and $95\%$ confidence interval in discrete data. Median and interquartile range was used in ordinal data and variables with non-normal distributions. For analysis of statistical significance, we used Fisher’s exact test, t-test, or the Mann–Whitney tests according to scale level and data distribution, respectively. In analysis with more than two groups, the Kruskal–Wallis test was used when pre-assumptions for ANOVA were fulfilled. Furthermore, we applied multivariate logistic regression analysis as a prediction model for a clinically meaningful antibody thresholds of 54 IU/mL [5]. Following transformation of measured antibody titers into a binary-dependent variable, covariables were defined based on scientific evidence. Therefore, age, gender, type of immunisation, duration in days since last known contact to COVID antigen or incidence of COVID infection, number of vaccinations, and physiologic response to vaccination entered the regression model. For regression analysis, we reported odds ratio and $95\%$ confidence interval for each variable and corresponding significance level. For all statistical analysis, we used a p value of ≤0.05 as significance level. To further explore findings of the multivariate regression analysis, we plotted resulting predicted probabilities of the model against age groups and type of vaccination. Therefore, data were visualized with error bars with mean and $95\%$ confidence intervals.
Due to the observational design of the study, alpha cumulation was not addressed as results were seen as an explorative analysis.
## 3.1. Descriptive and Inferential Statistics Results
In total, 646 employees consented to participate in this study, of which 22 employees gave incomplete data or incoherent information about previous vaccinations and were excluded from the study (see Figure 1).
Out of these, 481 ($77.21\%$) were female. One participant was diverse. With regard to this single diverse participant, no separate analysis was carried out. Baseline characteristics are described in Table 2.
The most common prime-boost regimen was BNT162b2 + BNT162b2 ($57.9\%$, $$n = 361$$), followed by the heterologous combination ChAdOx + BNT162b2 ($20.2\%$, $$n = 126$$) and ChAdOx + ChAdOx ($13\%$, $$n = 81$$). By the time of examination, most of the employees had received two doses of vaccines ($94.2\%$, $$n = 587$$), $12.4\%$ ($$n = 77$$) had been infected with SARS-CoV-2 at least once.
The vast majority of participants reported physical complaints after vaccination ($89.1\%$, $$n = 555$$). The most frequently stated complaint was pain at the injection site ($84.8\%$, $\frac{528}{623}$), followed by tiredness ($73.5\%$, $\frac{458}{623}$), and muscle or joint pain ($62.3\%$, $\frac{388}{623}$). Severe adverse events including neurological disorders (Guillain–Barré syndrome or facial nerve paralysis) occurred in one case ($0.1\%$, $\frac{1}{623}$) and cardiac complications (myocarditis/pericarditis or arrhythmias) were self-reported in 8 cases ($1.3\%$, $\frac{8}{623}$). No gender-specific differences in reactogenicity frequency was observed. The participants could rank their physical complaints according to an ordinal scale from 1 = mild, 2 = moderate, 3 = severe for each time they got vaccinated. We saw that females reported statistically significant stronger physical complaints (female mean 2.01–$95\%$ confidence interval (CI) 1.88–2.15; male mean 1.62; $95\%$ CI 1.39–1.86; $$p \leq 0.008$$).
The homologous schedule with mrNA-1273 (mean 383,4 AU/mL—$95\%$ CI 192.58–574.2) and the heterologous schedule ChAdOx1 + mRNA vaccine (mean 136,12 AU/mL—$95\%$ CI 109.32–162.92) showed the highest antibody level, followed by BNT162b2 (mean 135 AU/mL—$95\%$ CI 112.78–157.38). The lowest antibody titer was recorded for the homologous vaccine scheme with ChAdOx1 (mean 57.58 AU/mL—$95\%$ CI 36.40–78.76) (see Figure 2 “Boxplot of antibody level”). We found no gender differences in the height of antibody titer (male: mean 184 AU/mL—$95\%$ CI 134–233; female: 155 AU/mL—$95\%$ CI 133–177; $$p \leq 0.944$$).
## 3.2. Multivariate Logistic Regression Results
To identify possible factors influencing the antibody titer we defined the null hypothesis as the above-mentioned antibody neutralizing level of 54 IU/mL. If it was below, we rejected the null hypothesis. By using a multivariate analysis, we identified different parameters that are associated with a CoP < 54 IU/mL (see Table 3 “*Multivariate analysis* of influencing factors”).
For each year of life, the risk increased that the titer was not above the threshold ($p \leq 0.001$; OR 1.047; $95\%$ CI 1.031–1.063). In Figure 3, we differentiated age groups according to predicted probability for persons achieve a threshold below 54 IU/mL of antibody titer based on the multivariate regression model that shows an increase in probability with increasing age in concordance with Table 3.
The homologous scheme with ChAdOx yield a significant risk to result in a titer under the given threshold ($$p \leq 0.004$$; OR 15.159; $95\%$ CI 2.34–98.22). Individuals that received more than one vaccination were more likely to have antibody level above the threshold: each additional vaccination increases the possibility to be above the threshold ($$p \leq 0.016$$ OR 0.150; $95\%$ CI 0.032–0.700). Additionally, it was more likely that the individuals’ antibody titer was above the given threshold when somebody was infected before or after vaccination. Longer time since vaccination was associated with an antibody level below threshold ($$p \leq 0.007$$ OR 1.005 $95\%$ CI 1.001–1.009). Figure 4 shows the predicted probability for persons to reach a threshold below 54 IU/mL of antibody titer based on the multivariate regression model that shows an increase in probability with regard to different vaccines schedules.
A high reactogenicity was associated with an antibody level above the threshold ($$p \leq 0.010$$ OR 0.842 $95\%$ CI 0.739–0.960).
To report the area under the curve (AUC) and c-statistics for the multivariate logistic regression we used an analysis model fit using a Hosmer–Lemeshow test for the model that demonstrated sufficient model quality. To further backup this analysis, we performed requested c- statistics for reported model. Our results showed a suitable c-statistics with an AUC of 0.780 [$95\%$ CI 0.743–0.817] (see Supplementary Materials, Figure S1).
## 4.1. Summary and Contributions
Higher age, more days since last antigen contact, and a homologous vaccination with ChAdOx were associated with higher odds for an antibody level below threshold. Numerous vaccinations and an additional infection led to lower odds. Although women reported a higher severity of experienced reactogenicity, gender did not influence the odds for an antibody titer below threshold.
Our study reports a negative correlation between age and antibody titer; with each year of life, it was more likely that individuals did not reach the given threshold. It is widely known that elderly people have a lower antibody response to different vaccinations such as hepatitis B, seasonal influenza, tetanus, and pneumococcal vaccine [7,20,21]. In contrast to young individuals, the elderly have a rapid waning rate of neutralizing antibodies that makes them more susceptible for vaccine-preventable diseases. This age-related decrease in neutralization level is due to the decline of innate and adaptive immunity [21].
We saw a positive correlation of vaccine-induced symptoms with antibody levels. To this date, no clear picture is drawn whether more side effects means higher antibody levels or not [22,23,24]. However, more recent studies saw a positive correlation between reactogenicity and immunogenicity [24,25]. The underlying physiological mechanism is not well studied yet. Our study supports the notion that an intensive physical response promotes a stronger antibody response.
Our study demonstrated that females were more likely to report stronger side effects after vaccination than males consistent with other studies [12,22]. Females reported higher levels of reactogenicity with more moderate to severe physical complaints after vaccination. The height of reactogenicity has been associated with the height of immunogenicity for other vaccines [7,10]. However, we found no correlation between gender and the risk for an antibody titer below threshold.
Generally, it is known that females tend to have higher antibody response than males. These findings apply for the majority of vaccines including hepatitis A and B, seasonal influenza, *Haemophilus influenza* A, yellow fever, and measles [7,10]. Males on the other hand have a higher antibody response to tetanus and diphtheria vaccines [7,26,27]. The females’ innate and adaptive immune system responds faster to vaccinations, not only contributing to stronger immunogenicity but also higher reactogenicity because of hormonal, behavioral, and genetic factors [12,13,28,29]. However, recent studies on gender-specific differences of SARS-CoV-2 vaccine-induced immunity yield conflicting results. In accordance with our study, no gender-based differences in antibody level were also found in other studies [22,25,28,30].
We report that the different vaccination regimen had a significant influence on the immune response. The homologous vaccine regimen with ChAdOx resulted in a higher risk of being below the given threshold. This finding is in accordance with recent studies where this vaccine regimen led to a weaker immune response, whereas BNT162b2/BNT162b2 vaccines elicit a stronger antibody response [31,32]. Studies also showed that heterologous vaccines regimen mostly ChAdOx/BNT162b2 tend to have a stronger immunogenicity than homologous BNT162b2 regimen because of the additional effect of each vaccine on the humoral immune system response [31,33]. However, our data did not confirm these results. This finding may not be representative as the vast majority of our study population has received the homologous BNT162b2/ BNT162b2 regimen, as this was the first authorized vaccine and primarily used in the clinical setting.
Comparable antibody levels where seen in our study between BNT162b2/BNT162b2 regimen and infected participants who received one additional dose of any vaccination. Immunological studies assume that a natural infection elicits and triggers a broader humoral immune response [34]. Thus, vaccinations prior or post-infection act as a booster in individuals [34,35].
With regard to our results, we recommend that people should get at least two vaccinations, as every additional contact to the virus through either vaccination or through natural infection increases the immune response. Elderly people should know that they may have a lower antibody response and thus frequent boosters may be required.
*In* general, a booster vaccination is important to maintain a sufficient antibody level and thus protection from infection. In our study, we saw that each administered vaccinations reduced the risk of being below the threshold. Time since vaccination is a widely known risk factor for waning antibodies levels [30,31], which was also demonstrated in our study.
## 4.2. Strengths and Limitations
The strength of our study is the comparable high number of participants and the use of real-world data. Our study has some limitations that may have biased the results.
One limitation is the given threshold in IU/mL measuring neutralizing antibodies including IgG, IgM, and IgA, whereas our used assay detects specifically Anti-RBD IgG antibody of the S-protein of SARS-CoV-2 (AU/mL). However, studies showed a strong correlation between both levels. Anti-RBD IgG antibody is clinically used to assess a level of protection as it comprise for about $90\%$ of neutralizing activity [18,19]. Our cohort consisted only of workers from the healthcare sector, naturally including more females than males in the working age range. Thus, male gender and younger or elderly individuals are underrepresented in our study. We included a sample with imbalanced sample sizes that was not modifiable in this trial. Despite observed differences between groups were evaluated with statistical tests, imbalanced sample sizes could result in reduced power and therefore results should be assessed in further trials. Participants with intense side effects may have led to an over reporting as they wanted to share their experiences through the questionnaire.
We also relied on self-reporting regarding the side effects, number of vaccinations, and infections. We have not performed an anti-spike/anti-nucleocapsid antibody test to identify all previously infected participants, which may have biased the outcome of antibody level. Furthermore, potential interactions of variables were not addressable in this analysis due to limited sample size; however, sexes may differ in more dimensions such as pain-, infection-, or vaccination response [36,37,38].
## 4.3. Future Work
Distinct studies should be carried out to see if risk factors for a lower or higher antibody response are proven. Further studies are important to establish booster guidelines with regard to individual risk factors for a lower antibody response and thus the need for a booster vaccination. Some influencing factors such as age and previous infection are already known. Additionally, our study supports the assumption that a stronger reactogenicity results in a higher antibody response, especially in females. Thus, gender specific research regarding antibody level and side effects should be run. It is also important to examine if the same risk factor applies for mRNA vaccinations as well as traditional vaccinations (e.g., live, inactivated, or conjugate vaccines).
## 5. Conclusions
Our study identifies different factors influencing antibody response to SARS-CoV-2 vaccination such as age, vaccination regimen, days since vaccination, and previous infection. The findings are important with regard to vaccination and booster guidelines for COVID-19 as we were able to identify risk factors for a lower antibody response.
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|
---
title: Safe and Effective Delivery of mRNA Using Modified PEI-Based Lipopolymers
authors:
- Huijing Wang
- Xin Liu
- Xuefeng Ai
- K. C. Remant-Bahadur
- Teo A. Dick
- Bingqian Yan
- Tingting Lu
- Xingliang Zhou
- Runjiao Luo
- Minglu Liu
- Xiangying Wang
- Kaixiang Li
- Wei Wang
- Hasan Uludag
- Wei Fu
journal: Pharmaceutics
year: 2023
pmcid: PMC9967631
doi: 10.3390/pharmaceutics15020410
license: CC BY 4.0
---
# Safe and Effective Delivery of mRNA Using Modified PEI-Based Lipopolymers
## Abstract
Chemically modified mRNA (modRNA) has proven to be a versatile tool for the treatment of various cancers and infectious diseases due to recent technological advancements. However, a safe and effective delivery system to overcome the complex extracellular and intracellular barriers is required in order to achieve higher therapeutic efficacy and broaden clinical applications. Here, we explored All-Fect and Leu-Fect C as novel transfection reagents derived from lipopolymers, which demonstrated excellent biocompatibility, efficient delivery capabilities, and a robust ability to escape the lysosomes. These properties directly increase mRNA stability by preventing mRNA degradation by nucleases and simultaneously promote efficient gene translation in vitro and in vivo. The modRNA delivered with lipopolymer vectors sustained effective transfection in mouse hearts following direct intramyocardial injection, as well as in major organs (liver and spleen) after systemic administration. No observable immune reactions or systemic toxicity were detected following the systemic administration of lipopolymer-mRNA complexes to additional solid organs. This study identified commercial reagents for the effective delivery of modRNA and may help facilitate the advancement of gene-based interventions involving the safe and effective delivery of nucleic acid drug substances.
## 1. Introduction
Messenger RNA (mRNA) vaccines have rapidly emerged as a novel platform for prophylactic use and in the treatment of certain cancers [1,2,3,4,5,6]. Despite the remarkable progress in mRNA-based therapeutics, the instability and immunogenicity of mRNA hamper its clinical applications. Recent improvements in mRNA structure and function, together with enhanced manufacturing and purification processes, have highlighted mRNA as a novel therapeutic agent [7,8,9]. Chemically modified mRNAs (modRNAs) reduce levels of immune activation by avoiding toll-like receptor recognition, display a prolonged half-life, have improved stability, and are efficiently translated [10,11,12,13,14,15,16]. Hence, modRNA has become a promising therapeutic for the treatment of a wide range of diseases arising from defective proteins, which has numerous advantages over DNA-based expression modalities [14,17,18,19,20,21,22]. Unlike plasmid DNA, modRNA can quickly and efficiently express the target protein in the cytoplasm without the need to enter the nucleus, and with minimal risk of insertional mutagenesis [1,23,24]. One key challenge still facing modRNA therapies is the safe and effective delivery of the molecules to specific target cells and tissues. The most significant barrier for naked modRNA is its vulnerability to ribonuclease enzymes and its highly anionic nature, which prevents transport across cell membranes into the cells [25]. An appropriate modRNA delivery vehicle is urgently needed to these ends, but unfortunately, efficient modRNA delivery systems are still in their infancy [16,26,27].
In recent years, viral and non-viral vectors have been explored to ferry various expression systems to the target cells [5,28,29,30,31,32]. In spite of a large number of available viral vectors, unwanted genomic integration, immunogenicity (especially at repeat doses), high production costs, potential risk of secondary carcinogenesis and limited packaging capacity have hampered their wide utilization for long-term therapeutics [32,33]. On the contrary, non-viral vectors attracted significant attention due to their excellent biocompatibility and safety, ability to undergo endocytosis at the cell membrane, and efficient encapsulation ability. At present, different types of non-viral vectors have been developed to protect the nucleic acid from nucleases and facilitate uptake into cells to translate functional proteins, such as lipid nanoparticles (LNPs), polymers, dendrimers, and others [4,19,34,35,36,37,38,39,40,41,42,43,44,45,46]. However, some commercially available lipid-based transfection reagents that display high transfection efficiency also induce toxic responses in vivo [20]. Accordingly, more suitable vectors that can deliver modRNA safely with high efficiency are urgently being sought.
Polyethyleneimine (PEI) has emerged as the most widely studied cationic polymer as a non-viral delivery system owing to its spectrum of functional amines, the facile chemistry for further functionalization, its cost-effectiveness and safety profiles [40,42,45,47,48]. The cationic amine groups of PEI can complex with mRNA via electrostatic interactions and be packaged into virus-like (~100 nm) particles to ultimately be delivered to target cells efficiently [42]. PEI offers an excellent capacity to protect the nucleic acid against degradation, but it can also enhance cellular uptake via interactions with anionic cell surface proteoglycans, increasing the half-life of the cargo in the cytoplasm. Unfortunately, unmodified PEI is effective when molecular weight (MW) is ~25 kDa, and significant concerns have been raised for intolerable toxicities. Alternatively, small MW PEI with a similar chemical backbone to larger MW PEI has been functionalized with hydrophobic groups that led to superior delivery efficiency with acceptable biosafety [42]. These lipopolymers derived from low MW PEI were recently commercialized for a variety of uses with different nucleic acids [49,50].
The aim of this study was to identify and develop appropriate modRNA vectors that exhibit excellent biocompatibility, efficient cellular uptake and have the ability to easily escape the endosomes. A series of in vitro and in vivo investigations was conducted to screen and identify top-performing commercial polymeric vectors from modified PEIs. Our results demonstrated that the chosen vectors not only protected the modRNA from degradation and facilitated cellular uptake, but also promoted release from endosomal compartments to the cytoplasm for rapid protein expression. The toxicity of the modRNA formulations with polymeric vectors was minimal in animal models and they were well tolerated when delivered via either local or systemic administration. These results show polymeric mRNA complexes as a feasible, efficient, stable, and safe biomolecule delivery system with potential clinical applications.
## 2.1. Materials
Lipopolymer transfection reagents used in this experiment were purchased from RJH Bioscience (Edmonton, AB, Canada). LipofectamineTM MessengerMAX transfection reagent (MAX) was purchased from ThermoFisher Scientific (Waltman, MA, USA). Cell culture-related reagents such as $0.25\%$ Trypsin-EDTA (1×), Dulbecco’s Phosphate Buffered Saline (DPBS), Dulbecco’s Modified Eagles Medium (DMEM), Penicillin-Streptomycin antibiotic, and Fetal Bovine Serum (FBS) were obtained from Life Technologies (Carlsbad, CA, USA). Opti-MEM reduced serum medium (1×) was purchased from Gibco (New York, NY, USA). The cell counting kit-8 (CCK8) was purchased from Dojindo (Kumamoto, Japan). EdU Cell Proliferation Kit with Alexa Fluor 555 was purchased from Beyotime (Shanghai, China). Plasmid DNA used in this project was purchased from Sanggon Biotech (Shanghai, China). DEPC-Treated nuclease-free water was purchased from Ambion (Austin, TX, USA). MEGAscript T7 Transcription kit and transcription cleanup kit was purchased from Ambion (USA). Lyso-Tracker Probes were purchased from Life Technologies (USA). siRNA tracker Cy3 kit purchased from Mirus (Marietta, GA, USA). The primary antibodies used in this study were CD3 (ab1669, Abcam, Cambridge, UK) and CD68 (ab955, Abcam). A Donkey Anti-Mouse IgG H&L (ab150106, Abcam) and a Donkey Anti-Rabbit IgG H&L (ab15073, Abcam) were used as secondary antibodies. Cell lines of HeLa (Serial TCHu187), 3T3 (Serial GNM6), and MCF-7 (Serial TCHu74) used in the projects were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The human induced pluripotent stem cells (hiPSCs) were donated by Yanxin Li’s laboratory at Shanghai Children’s Medical Center’s Institute of Pediatric Translational Research.
## 2.2. modRNA Synthesis
All modRNA used in this study was produced using in vitro transcription techniques, as previously described [20,26,51]. Briefly, we constructed the plasmid DNA containing the gene of interest and transformed it into E. coli. After amplification and purification of the plasmid, it was linearized by restriction endonuclease and then amplified by PCR to generate a template for in vitro transcription. Afterward, we used the MEGAscript T7 Transcription kit to produce chemically modified mRNA (modRNA) in vitro. We purified the modRNA with a transcription cleanup kit and treated the transcripts with Antarctic phosphatase for 30 min at 37 °C to remove residual 5′-phosphates. Lastly, the modRNA was repurified and all modRNAs were quantified by Nanodrop and were stored frozen at −20 °C.
## 2.3.1. Measurement of Particle Size
The efficiency of gene transfection and cytotoxicity are significantly influenced by the polyplexes’ particle size and zeta potential. To determine the mean diameter size and the polydispersity index (PDI) of each sample, modRNA and different carriers were mixed at a 1:2 ratio, diluted in 200 μL distilled water, and loaded into a quartz cuvette. The mean diameter size of the polyplexes was measured at an angle of 173° at room temperature (25 °C) by dynamic light scattering using a Zetasizer Nano series (Malvern Instruments, Malvern, UK). Each experiment was repeated three times and the results were averaged.
## 2.3.2. Zeta Potential
The zeta potential of polyplexes was measured using the Zetasizer Nano series (Malvern Instruments, UK), as previously described [4,40,46]. Before testing, it was diluted to 1 mL with deionized water according to the optimal binding ratio of vector to modRNA. Each sample is measured at least three times to take the average value to analyze the experimental results.
## 2.3.3. Circular Dichroism Analysis
To prove the structure of the modRNA wrapped by the polymeric vectors remain unchanged, the conformation of naked modRNA and the modRNA-polymer complexes were tested by a MOS-500 Circular Dichromatic (CD, Bio-Logic Science Instruments, Grenoble, France) spectrometer in the range of 220~320 nm.
## 2.3.4. Agarose Gel Electrophoresis
To assess the nuclease resistance capability of modRNA encapsulated in the vector, agarose electrophoresis was used to evaluate the integrity of modRNA as previously reported [40]. Either free modRNA or vector-encapsulated modRNA was added to Opti-MEM medium with $10\%$ FBS and then incubated at 37 °C for 24 h. For $1\%$ agarose gel electrophoresis assays, the complexes were quantified in a volume of 10 μL, and each sample was loaded with 2 μL of 6 × loading buffer, and then loaded on a $1\%$ agarose gel. Electrophoresis was conducted for 30 min at 120 V in fresh 1 × TAE (Tris-acetate-EDTA) buffer. The gel was imaged and analyzed using a gel image system (Tanon 3500, Shanghai, China) under ultraviolet light.
## 2.3.5. Transmission Electron Microscopy (TEM)
To test the morphology and size of the polyplexes, we used a 200 kV JEOL 2100 transmission electron microscope for analysis as previously reported [4,40,46]. First, immediately after the glow discharge treatment in a vacuum, the samples were prepared on a grid coated with carbon, a drop of the polymorph suspension was added and blotted dry with filter paper after 5 min. Then, the samples were negatively stained with a $2\%$ uranyl acetate solution for 30 s. Particle size analysis and distribution were performed using the Fiji/ImageJ software version 2.3.0. Particle size measurement was carried out on the longest dimension of the polyplexes from images taken from different regions of the sample.
## 2.4.1. Cell Cultures
HeLa cells and 3T3 cells were cultured in DMEM cell medium supplemented with $10\%$ FBS and $1\%$ penicillin-streptomycin antibiotic at 37 °C under a $5\%$ CO2 atmosphere. The medium was replaced every 2 days and cell passaging was executed when the monolayer of adherent cells reached ~$90\%$ confluence.
## 2.4.2. modRNA Transfection
For in vitro transfection, 2 × 105 cells were seeded in a 6-well plate and cultured at 37 °C for 24 h. Then, modRNA (2 μg) and vectors (typically 2, 4, and 6 μL) were separately diluted in serum-free Opti-MEM medium and incubated for 5 min. *To* generate modRNA-vector complexes, the separate mixes were gently pooled together and left to incubate for 15 min at room temperature (RT). Finally, the transfection complex was added directly to the cells in a complete culture medium and incubated for 24 h for testing. To transfect modRNA in vivo, 20 μg RNA and 40 μL transfection reagent were diluted separately in 200 μL Opti-MEM medium, incubated for 5 min at room temperature, then mixed and incubated for another 20 min at RT before tail vein injection [26].
## 2.4.3. Flow Cytometric Analysis
To quantify the extent of modRNA expression, the transfection efficiency and fluorescence intensity of modRNA were measured by flow cytometry 24 h after transfection, as previously described [26]. Cells were washed with DPBS 3 times and then treated with $0.25\%$ trypsin-EDTA for 3 min before adding fresh medium. Cells were centrifuged at 1000 rpm for 4 min to remove trypsin and resuspended in a DPBS medium for flow cytometry analysis.
## 2.4.4. EdU Assay
To test the cell proliferation, Click-iT EdU Imaging Kits (Beyotime, China) was used according to the manufacturer’s instructions, as previously studied [52]. Briefly, HeLa cells were planted at a density of 5 × 104 cells in a 24-well plate 24 h before transfection. After transfection for 24 h, EdU was added to the medium according to the reagent instructions to make a final concentration of 10 μM. Then, cells were fixed with $4\%$ paraformaldehyde for 15 min at room temperature and permeabilized with $0.5\%$ Triton X-100 for 15 min. To detect EdU, the configured click reaction mixes were added to each well, incubated for 30 min at room temperature, and protected from light. Lastly, to detect the proportion of cell proliferation, nuclei were stained using Hoechst 33,342 and imaged with a Leica inverted fluorescence microscope (Leica, DMI3000B, Wetzlar, Germany).
## 2.4.5. Cellular Uptake and Endosomal Escape Analysis
In order to observe the cellular uptake and escape from the lysosome of modRNA complexes, GFP modRNA and luciferase modRNA were labeled with the fluorophore Cy3, as in previously published studies [4,40]. Initially, cells were seeded into confocal dishes for 24 h incubation and then transfected with Cy3-conjugated modRNA. The following day, the escape of modRNA from lysosome was tracked using Lyso-Tracker™ Green DND-26 of lysosomal staining dye, in accordance with the manufacturer’s directions, and the nucleus was stained with Hoechst 33342 for 15 min at room temperature. Finally, the cells were washed three times with DPBS. The intracellular localization of modRNA complexes was observed at different times by confocal laser microscopy (Leica, TSC SP8).
## 2.4.6. In Vitro Cytotoxicity Assay
The in vitro cytotoxicity of the vectors was assessed by the Cell Counting Kit-8 [4]. Briefly, HeLa cells were seeded into a 96-well plate at a density of 1 × 104 cells per well and cultured overnight. Then, the cells were treated with GFP modRNA complexed with MessengerMAX, ALL-Fect, or Leu-Fect C at 37 °C, and $5\%$ CO2 for different times, respectively. For control groups, cells were either exposed to naked modRNA or left untreated. The vector-to-modRNA mixing ratio was 3:1 and all groups were performed in five parallel wells. After different time treatments (1, 2, 3, 4, and 5 days), cells were washed with DPBS and incubated with 10 μL of CCK-8 and 90 μL of DMEM cell medium at 37 °C for 2 h. Two hours later, the absorbance of the plates was measured at wavelengths of 450 nm by a multifunctional microplate reader (BIOTEK Synergy2, BioTek Instruments, Winooski, VT, USA).
## 2.5.1. In Vivo Cytotoxicity Assessment and Histological Evaluation
In vivo biocompatibility of the vectors was assessed by histological evaluation and hematological examination, as previously described [4,26,40,46]. The study was divided into two parts: local organ injection and tail vein injection. For local injection, 50 μL vector and 50 μL serum-free Opti-MEM medium were mixed evenly and injected into pancreatic organs of 6–8 weeks old C57BL/6 male mice (purchased from Shanghai JSJ Company, Shanghai, China), and the organs were harvested 3 days later. Then, the extracted organs were embedded in paraffin, sectioned, and stained with hematoxylin and eosin (H&E). Tissue inflammation was further analyzed by immunofluorescence, which involved incubating sections with primary antibodies against CD3 and CD68 overnight at 4 °C followed by staining with the Alexa Fluor-$\frac{488}{555}$ conjugated secondary antibodies for 2 h at room temperature. Lastly, DAPI was incubated for 3 min at RT before observing and imaging the sections with the Leica DM6000 B system.
For the systemic toxicity study, C57BL/6 male mice were administered 500 μL mixed solution of reagents (50 μL) and DPBS (450 μL) by tail vein injection, once every two days for 7 injections. The mice’s body weights were also measured. On day 14, mice were sacrificed, blood was drawn, and the serum was isolated. The activities of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and counts of white blood cells (WBC), lymphocytes (Lymph cell), monocyte (Mon cell), and neutrophils were measured using individual assay kits. Meanwhile, organs (including the heart, liver, spleen, lung, kidney, and intestine) were gathered for histological analysis. The organs were fixed in $4\%$ paraformaldehyde overnight, embedded in paraffin followed by sectioning (5 μm), and stained with hematoxylin and eosin. The slides were pathologically evaluated using a Leica DM6000 B system.
## 2.5.2. In Vivo modRNA Delivery and Expression
To study in vivo transfection efficiency of modRNA, the complexes were delivered via direct intramyocardial injection or systemic tail vein infusion [4,40,43]. Rosa26mTmG mice were anesthetized with isoflurane, intubated, and the thorax was carefully opened to locate and find the heart, as well as to place retractors into the incision to ensure clarity of view. Then, 15 μg of Cre mRNA was injected into the heart before closing the chest. After three days, hearts were harvested, frozen sections were prepared, confocal fluorescence imaging was performed, and modRNA expression was statistically analyzed using Image J software.
Additionally, the biodistribution of mRNA was also evaluated using tail vein injection. The injection was prepared by adding 20 μg of Cre modRNA and 40 µL of vector to 200 µL of the reaction mixture. Then, the solution was injected into the Rosa26mTmG mice at three different sites on their tails. Frozen sections of the liver, spleen, heart, and kidney were taken for staining to survey the effect of modRNA expression after three days.
## 2.5.3. Frozen Sections and Immunohistochemistry
The isolated organs were washed clean of residual blood with sterile DPBS and fixed in $4\%$ paraformaldehyde for 24 h at 4 °C. The following day, the organs were washed three times with DPBS and soaked in a $30\%$ sucrose solution to dehydrate until they precipitated to the bottom. Then, they were embedded in OCT compound and rapidly frozen at −80 °C. Tissue sections were performed using a cryostat (CM1950 Leica, Germany) with a section thickness of 5 μm and stored at −80 °C. Before staining, sections were defrosted and dried at room temperature for 30 min, then washed three times in DPBS, and permeabilized with $0.5\%$ Triton-X 100 solution for 30 min. Then, the slides were rinsed three times every 5 min with DPBS and blocked with $5\%$ normal goat serum for 2 h at room temperature. The sections were then probed with the appropriate concentration of primary antibody at 4 °C overnight. Following three washes, the tissue sections were incubated for two hours at room temperature and shielded from light with the appropriate fluorescently labeled secondary antibodies. Finally, imaging was carried out using a Leica TSC SP8 laser confocal microscopy system.
## 2.6. Imaging Processing
To count the number of cells, the pictures were first processed with the Image J software version 1.8.0, as previously described [52]. The image was converted to 8-bit format prior to “hole filling” and “watershed” operations being performed. Cells were counted using the “analyze particles” command. The acquired data was analyzed and graphed using Graphpad Prism version 5.0 and Origin version 8.0.
## 2.7. Statistical Analysis
The results are presented as the mean ± standard deviation (SD). Statistical analyses were performed by t-test, values of ** $p \leq 0.01$ and *** $p \leq 0.001$ were regarded as statistically significant.
## 3. Results and Discussion
Modified mRNA holds significant promise for gene and recombinant protein therapies but selecting the appropriate RNA delivery vehicle remains a challenge for unlocking the potential of modRNA therapies. Ideal carriers should have the ability to deliver modRNA to specific cell types and permit significant transgene expression for a specified duration in order to attain a satisfactory therapeutic effect, while avoiding activation from host immune responses, and/or by exhibiting ‘stealth’ features for optimal safety. A common delivery agent of choice for many RNA studies has been lipid nanoparticles (such as commercial transfection reagents RNAiMAX and MessengerMAX), which effectively express exogenous genes with high efficiency [20,26,53,54,55]. However, cytotoxic side effects of lipid nanoparticle delivery systems are common. Previous reports demonstrated that lipofectamine reagents of RNAiMAX induced a higher incidence of in vitro cell death, are also detrimental to the heart, and may cause apoptosis in vivo [20]. Furthermore, it has been reported that direct intramyocardial injections of modRNA in a clinically safe carrier containing saline/sucrose-citrate buffer can improve cardiac function in small and large animal models of heart disease (reference both the Zangi paper and the AZ paper). However, repeated injections of high doses of modRNA are associated with elevated costs and may limit clinical translations [51]. Therefore, in this study, we explored several cationic lipopolymers of PEI for modRNA delivery. The lipopolymers were previously commercialized for delivery of other nucleic acids such as siRNA [49] and pDNA [56], but they have not been explored for modRNA delivery.
## 3.1. Characterization of modRNA Complexes
We explored the capacity at which four lipopolymer carriers could safely and efficiently deliver modRNA in both in vitro and in vivo model systems. MessengerMAX was chosen as a reference carrier since its transfection efficiency was reported to be as high as ~$80\%$ for in vitro cells of human fibroblasts [26]. We first characterized the physiochemical properties of complexes formed with the GFP modRNA. As shown in Figure 1A and Figure S1, the complexes from the lipopolymers had an average hydrodynamic diameter between 150 and 240 nm, which are sufficiently small for effective cellular internalization. Furthermore, the zeta potential values of the lipopolymers reduced slightly after binding to modRNA, but they remained electropositive with charge values ranging from 25 to 35 mV, showing that these lipopolymer complexes have good stability and can penetrate the cell membrane barrier (Figure 1A). The polydispersity index (PDI) of modRNA complex particles was typically between 0.25 and 0.4, which indicated that the particles remained relatively uniform with no major aggregation and were relatively homogenous in size (Figure 1B). The size and PDI of MessengerMAX complexes were also similar to the values reported with the polymeric modRNA complexes. To further verify the conformational stability of modRNA, CD spectrum analysis was employed, where the naked modRNA and modRNA complexes shared similar conformations at ~270 nm peak (indicated by red dashed squares in Figure 1C). This demonstrated that modRNA in complexes had similar confirmation as free modRNA and should remain non-degradative and functional following release from the complexes. To assure that the polymer particles can protect the modRNA from enzymatic degradation, the modRNA complexes were incubated in $10\%$ FBS at 37 °C for 24 h and analyzed by agarose gel electrophoresis (Figure 1D). The naked modRNA was completely degraded by the serum nucleases in FBS (indicated by white arrows in Figure 1D), while modRNA samples complexed with the polymeric carriers remained non-degradative (indicated by red dashed squares in Figure 1D).
The nature of the modRNA complexes was further analyzed with TEM and the results of analysis from a representative carrier (ALL-Fect) are shown in Figure 1E,F. The complexes were well dispersed, and the morphologies observed were mostly spherical (top right corner of Figure 1E). Irregular and elongated shapes were also found, mostly on the largest particles of the sample, which may be due to a small degree of agglomeration (indicated by white arrows in Figure 1E). Note that a certain polydispersity in complex sizes was also evident in the TEM analysis. The particles analyzed ranged from 20 to 90 nm in diameter with an average size of 38 nm (Figure 1F). The great majority of the sample (~$90\%$) was below 60 nm and the particle population peaked at 30 nm. The average size of the ALL-Fect complexes in TEM were significantly lower than the hydrodynamic size determined by the zetasizer. The dry state of the complexes under TEM conditions and the lack of a hydration shell are the likely reasons for reduced size measurements under this analysis. This series of characterization experiments clearly indicated that lipopolymeric carriers had the right properties for delivery of modRNA to the cells.
## 3.2. In Vitro Screening for modRNA Delivery
To investigate the transfection efficiency of modRNA delivered by the chosen carriers, we initially transfected HeLa cells with a GFP modRNA at different mixing ratios (1:1 to 1:3), where different amounts of carriers were mixed with a fixed amount of modRNA (2 μg). The cells were incubated with the complexes for 24 h and analyzed by fluorescence microscopy (Figure 2A,B) and flow cytometry (Figure 2C–G). Based on the flow cytometry quantitation of mean GFP expression (Figure 2G), the transfection efficiency with polymeric carriers was comparable to that of Messenger-MAX at the optimal ratio (2:5). Particularly, ALL-Fect and Leu-Fect C had the highest delivery efficiency that reached ~$83\%$ at 3:1 ratio with these reagents. As expected, naked modRNA did not give any GFP expression in the absence of a carrier (Figure 2A). Therefore, through screening experiments, we resoundingly selected ALL-Fect and Leu-Fect C reagents for further evaluation, based on better encapsulation efficiency and delivery capacity of modRNA.
To further explore the performance of ALL-Fect and Leu-Fect C, we conducted similar experiments in 3T3 and human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs) in addition to HeLa cells using GFP expressing modRNAs (eGFP and nGFP), as well as a modRNA expressing mCherry. As can be seen from Figure 3, ALL-Fect and Leu-Fect C reagents could deliver several modRNA gene candidates (eGFP, nGFP, mCherry) to 3T3 and hiPSC-CM cells in addition to the HeLa cells with good transfection efficiency and high fluorescence intensity. Of interest, the GFP-transfected cardiomyocytes were still beating naturally 24 h later, suggesting that the lipopolymeric carriers could deliver mRNA to non-regenerative cells without any obvious effects on their normal physiological activity (Video S1). In addition, these novel carriers can efficiently transfect human breast cancer MCF-7 cells, as shown in Figure S2. Thus, these results show that the selected polymeric carriers displayed potent transfection efficiency in culture with a multitude of cell types (both cell lines and primary cells), suggesting their alternative use as promising leads for therapeutic applications in a clinical setting.
## 3.3. In Vitro Biocompatibility
To verify the biocompatibility of the chosen carriers, we first tested their cytotoxicity through a series of cell culture experiments. The cytotoxic effects of the carriers were evaluated by GFP modRNA transfection in HeLa cells, using the CCK-8 assay which provides a measure of the total metabolic activity of the cells (Figure 4). Under optical microscopy (Figure 4A), the morphological characterization of cells treated with ALL-Fect and Leu-Fect C complexes showed no significant changes as compared to untransfected control groups. However, cells transfected with MessengerMAX displayed slower growth and apoptotic bodies were observed. This was consistent with the outcome of the CCK8 assay (Figure 4B), which revealed a significant decrease in proliferation rates of MessengerMAX transfected cells. On the other hand, the cells treated with ALL-Fect and Leu-Fect C complexes revealed no significant difference in proliferation capacity, as compared to the untreated cells (Figure 4B).
Next, we conducted an EdU proliferation assay to further assess the biocompatibility of the carriers. The proliferation of HeLa cells was assessed by EdU staining after 1, 2, and 3 days post-seeding and transfection (Figure 4C–E). A significant increase in the number of EdU-positive cells was seen in both ALL-Fect and Leu-Fect C complexes when compared to the cells treated with MessengerMAX complexes (Figure 4F–H). No noticeable differences of EdU incorporation were seen among the control groups and the All-Fect/Leu-Fect C complexed groups. This result further confirmed that the transfection of mRNA with the lipopolymeric carriers All-Fect and Leu-Fect C displayed low cytotoxic effects and did not impede cellular proliferation.
## 3.4. Cellular Uptake and Endosomal Escape
Following intracellular uptake, subsequent endosomal/lysosomal escape of the complexes is necessary for successful gene expression. To track intracellular uptake and localization of modRNA complexes in cells, Cy3 fluorophore was tagged to GFP modRNA so we could follow the intracellular localization of modRNA complexes. In Figure 5A, the GFP modRNA complexed with MessengerMAX (as representative analysis) revealed a significant presence of red fluorescence (Cy3-GFP modRNA complexes). These complexes were localized predominantly in the cytoplasm at 24 h as compared to 4 h, which indicated that these complexes were successfully endocytosed into the cytoplasm over time and released GFP modRNA for functional translation (given by RED GFP signals). The maximal uptake was seen 30 and 48 h after incubation of the cells with the Cy3-modRNA complexes. From Figure S3A,B, it was also demonstrated that ALL-Fect and Leu-Fect C complexes could be endocytosed and enter the cytoplasm to translate the modRNA cargo.
The escape of the modRNA complexes from the endosomes/lysosomes was explored next. Luciferase modRNA was labeled with Cy3 and LysoTracker DND-26 (green) was used to inspect the co-localization of modRNA and lysosomal bodies (Figure 5B and Figure S3C). The red (representing Luciferase modRNA) and green (representing lysosomes) fluorescent areas overlapped less frequently with increasing incubation time, which indicated that the internalized modRNA complexes successfully escape from the endosomal/lysosomal compartment. These results indicated that the polymeric complexes can convey modRNA to evade the lysosome and enter the cytoplasm to synthesize the target protein from the modRNA expression.
## 3.5. In Vivo Evaluation of modRNA Delivery
Encouraged by the suitable biocompatibility and effective transfection results in vitro, we next investigated PEI-modRNA delivery in a mouse model. Previous studies have shown that modRNA therapy prevents cardiomyocyte death and induces neovascularization with minimal side effects [21]. However, this experiment required multiple injections of large amounts of modRNA to secure adequate protein expression. To further explore the therapeutic effects of modRNA with the current carriers, modRNA encoding for the Cre reporter protein was used to evaluate the expression of modRNA by immunohistochemistry. First, primary fibroblasts derived from Cre-LoxP reporter mice were used to assess the expression of modRNA coding for tdTomato (Figure 6A). Efficient tdTomato expression was obtained by the modRNA delivered by all 3 vectors; MessengerMAX, ALL-Fect, and Leu-Fect C (Figure 6B,C). Next, we used insulin syringes to inject a low dose of modRNA complexes directly into the myocardium of Cre-LoxP reporter mice, where the tdTomato gene expression is activated upon excision of LoxP locus by cyclization recombinase (Figure 6A). All 3 carriers efficiently delivered functionally active modRNA and expressed the target protein (given by red tdTomato expression) after 3 days of local injection (Figure 6D). Based on analysis of the tdTomato-positive cell population (Figure 6E), Leu-Fect C delivering modRNA was superior to MessengerMAX and ALL-Fect carriers.
Intravenous (IV) injection is considered to be an efficient way to induce target protein expression in the liver and spleen, since most nano-sized complexes are typically deposited into the liver and spleen from the systemic circulation [4]. To test this approach, we administered a low dose of Cre modRNA/polymer complexes (20 μg of Cre modRNA) through the tail vein of Cre-LoxP reporter mice and assessed the efficiency of transfection in spleen and livers after 3 days (see schematic, Figure 7A,D). Using the same methodology as above, a strong tdTomato fluorescence was detected in target organ tissues of spleen (Figure 7B) and liver (Figure 7E). Interestingly, the delivery efficiency by the Leu-Fect C complexes was superior to both ALL-Fect polymer and MessengerMAX control, based on the expression pattern resulting from Cre activity in both the spleen (Figure 7C) and liver (Figure 7F), respectively. Of interest, very limited or no tdTomato expression was observed in heart and kidney following tail vein injections (Figure S4). These results imply potential liver and splenic tissue tropism of Leu-Fect C mRNA delivery following systemic administration. Furthermore, these results indicated that the lipopolymer carriers maintain strong encapsulation properties and protect modRNA during systemic circulation. Ultimately, the desired in vivo-produced protein can be effectively expressed with a relatively small dose of administered modRNA.
## 3.6. In Vivo Biocompatibility
To evaluate the safety of polymer carriers in vivo, we first tested the local tolerability of the carriers by evaluating the effects of local injection (50 μL) into the pancreas, a major secretory organ of the body (Figure 8A). At three days post-administration, the pancreas was harvested and processed for H&E staining (Figure 8B). Examination of the tissue sections revealed that pancreatic tissues receiving MessengerMAX displayed severe tissue necrosis, while the pancreases receiving lipopolymeric carriers exhibited normal tissue morphologies without any signs of necrosis or apoptosis. These results add further credence to the excellent biosafety of the ALL-Fect and Leu-Fect C reagents in vivo. Next, we stained the sections to assess for the presence of infiltrating CD3+ and CD68+ lymphocytes and monocytes, indicators of local immune responses (Figure 8C,D). Indeed, quantitative analysis revealed a significant increase in the number of CD3+ and CD68+ cells in the pancreases receiving MessengerMAX injection, while polymer injections to the pancreas with ALL-Fect and Leu-Fect C showed no discernable differences to the control (Figure 8E,F).
Next, we further explored the biosafety of the delivery systems by repeat administration into the tail vein once every 2 days over the course of 2 weeks, for a total of 7 times (Figure 9A). Body weights of mice were analyzed as an indicator of general treatment-induced toxicity as a study endpoint. As seen in Figure 9B, no significant body weight loss was observed in any group during the treatments, indicating unnoticeable adverse effects in this delivery mode. Systemic toxicity was also assessed by histopathology and blood serum chemistry. Based on the HE staining results (Figure 9C), there were no pronounced histological abnormalities found in the heart, liver, spleen, lung, kidney, or intestine tissues of mice following administration of the different administered carrier groups. Based on the analysis of cells associated with inflammation, the population of WBC (white blood count) cells and lymphocytes (Lymph) was significantly increased in the MessengerMAX treatment group compared to all other groups (Figure 9D,E). Repeated administration with the MessengerMAX treatment group also elevated levels of monocytes (Mon population) compared to no treatment/baseline levels (Figure 9F), but this elevation was not significantly different from the other treatment groups. No clear distinction between the granulocyte (Gran) cells was evident among the study groups, as shown in Figure 9G. The hematological analysis also showed normal liver function with levels of AST and ALT in the normal range for all carriers (Figure 9H,I). Based on this analysis, the novel lipopolymeric vectors displayed significant advantages over the commercial liposomal reagent MessengerMAX in terms of their tolerability in vivo, which confirm a satisfactory safety profile for further animal testing en route to the clinical application of modRNA therapeutics.
## 4. Conclusions
Our in vitro study results highlighted excellent transfection efficiencies when transfecting modRNA in cells using ALL-Fect and Leu-Fect C polymer carriers. Transfection efficiencies reached >$80\%$ at the optimal ratio of 3:1, yielding higher delivery efficiency as compared to the other polymeric carriers. Further investigation showed that these two novel reagents can mediate endosomal escape and release of modRNA cargo, which may be due to the small particle size of the resultant complexes. Importantly, ALL-Fect and Leu-Fect C demonstrated potent delivery capability in vivo at low dose administration. We also observed ideal biocompatibility and tolerability in mouse models with no adverse effects under the study conditions. The toxicity studies and histopathology analysis revealed that repeated administration is well tolerated even at higher doses, where no evidence of tissue necrosis or organ failure was documented. Of interest were our suggestive findings that alluded to lipopolymer tissue tropism in spleen and liver. More experiments are needed in order to decipher the biological mechanisms underpinning this translocation. Furthermore, our findings may suggest that these lipopolymer carriers could be more potent for modRNA delivery compared to native polymers or other commercial transfection reagents. This is the first report on the use of these new lipopolymer carriers to effectively deliver modRNA in animal models and these carriers are expected to play an important role in the future delivery of modRNA for gene therapy. Therefore, this study may open up new avenues for modRNA delivery in vivo and provide great hope to generate a new avenue for the targeted treatment of human diseases.
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|
---
title: Anti-Fibrotic Potential of Angiotensin (1-7) in Hemodynamically Overloaded
Rat Heart
authors:
- Matus Sykora
- Vojtech Kratky
- Libor Kopkan
- Narcisa Tribulova
- Barbara Szeiffova Bacova
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967643
doi: 10.3390/ijms24043490
license: CC BY 4.0
---
# Anti-Fibrotic Potential of Angiotensin (1-7) in Hemodynamically Overloaded Rat Heart
## Abstract
The extracellular matrix (ECM) is a highly dynamic structure controlling the proper functioning of heart muscle. ECM remodeling with enhanced collagen deposition due to hemodynamic overload impairs cardiomyocyte adhesion and electrical coupling that contributes to cardiac mechanical dysfunction and arrhythmias. We aimed to explore ECM and connexin-43 (Cx43) signaling pathways in hemodynamically overloaded rat heart as well as the possible implication of angiotensin [1-7] (Ang [1-7]) to prevent/attenuate adverse myocardial remodeling. Male 8-week-old, normotensive Hannover Spraque–Dawley rats (HSD), hypertensive (mRen-2)27 transgenic rats (TGR) and Ang [1-7] transgenic rats (TGR(A1-7)3292) underwent aortocaval fistula (ACF) to produce volume overload. Five weeks later, biometric and heart tissue analyses were performed. Cardiac hypertrophy in response to volume overload was significantly less pronounced in TGR(A1-7)3292 compared to HSD rats. Moreover, a marker of fibrosis hydroxyproline was increased in both ventricles of volume-overloaded TGR while it was reduced in the Ang [1-7] right heart ventricle. The protein level and activity of MMP-2 were reduced in both ventricles of volume-overloaded TGR/TGR(A1-7)3292 compared to HSD. SMAD$\frac{2}{3}$ protein levels were decreased in the right ventricle of TGR(A1-7)3292 compared to HSD/TGR in response to volume overload. In parallel, Cx43 and pCx43 implicated in electrical coupling were increased in TGR(A1-7)3292 versus HSD/TGR. It can be concluded that Ang [1-7] exhibits cardio-protective and anti-fibrotic potential in conditions of cardiac volume overload.
## 1. Introduction
Heart failure (HF) is a clinical syndrome characterized by cardiac dysfunction due to structural abnormalities of the myocardium that results in the inability of the heart to eject a sufficient amount of the blood to the circulation, to cover the metabolic needs of the body. HF is a major cause of morbidity and mortality and represents an extensive health and economic burden with a huge impact due to high treatment costs, frequent hospitalizations and poor quality of life [1]. Pressure and volume overload of the heart is critically involved in the pathogenesis of HF. Left ventricular pressure overload is a severe stressor induced by systemic hypertension or aortic stenosis, promoting HF. At the same time, valvular regurgitation lesions (such as aortic and mitral insufficiency) cause volume overload resulting in myocardial remodeling and HF. Both pressure and volume loading contribute to the adverse remodeling of the extracellular matrix (ECM), impacting both the mechanical and electrical properties of cardiomyocytes [2,3,4].
The ECM as a mechanical support system maintaining tissue integrity also serves as a signaling hub. This dynamic structure transmits signal cascades critical for proper cell function, it is a reservoir of growth factors and proteases that modulate various repair processes and can be activated in the case of pathophysiology [5,6,7,8].
Electrical and metabolic communication is sustained directly via connexin-based (Cx) gap junction channels (GJC), essential for ensuring the transmission of electrical impulses and coordinated contractile and pumping activity. The prevalent isoform of Cx expressed in the heart is Cx43. Impairment of Cx43 GJC promotes the development of electrical conduction disorders, which are the basis of heart diseases, malignant arrhythmias and HF [9,10,11,12]. Therefore, the understanding and subsequent modulation of molecular pathways implicated in mechanical and electrical heart remodeling can lead to the development of new pharmacological and non-pharmacological strategies for cardioprotection.
The renin–angiotensin–aldosterone system (RAAS) is a well-known crucial factor involved in cardiac remodeling in both pressure and volume overload conditions. On the other hand, experimental studies point out the benefit of the non-canonical pathway of angiotensin-converting enzyme 2 (ACE2)-Ang [1-7]-Mas receptor, which counteracts the adverse effects of the RAAS pathway. The cardioprotective effects of angiotensin [1-7] appear to be mediated by different signaling pathways [13]. Studies have shown that the administration of Ang [1-7], during hemodynamic overload of the heart reduces myocyte hypertrophy and cardiac fibrosis [14,15]. Deletion for ACE2, on the other hand, has been shown to cause an increase in perivascular and interstitial fibrosis, ventricular dilatation, decreased intrinsic myocardial contractility and increased cardiac remodeling, as well as a general deterioration of ventricular functions up to increased mortality [16,17,18]. Thus, we aimed to explore possible implication of Ang [1-7] on myocardial ECM and Cx43 in conditions of cardiac volume overload.
## 2.1. Biometric Parameters of Rats Affected by ACF and Ang (1-7)
Body weight did not differ between individual rat strains. Heart weight (HW) index per tibia length also did not differ between the HSD ACF and TGR ACF strains. However, HW was significantly reduced in TGR(A1-7)3292 ACF compared to HSD ACF or TGR ACF rats. Left ventricular weight index was increased in TGR ACF and decreased in TGR(A1-7)3292 ACF vs. HSD ACF. There was an increase in left ventricular weight in TGR(A1-7)3292 ACF compared to TGR(A1-7)3292. We registered a reduction right ventricular weight index in TGR(A1-7)3292 ACF compared to HSD ACF or TGR ACF while there was an increase in TGR(A1-7)3292 ACF compared to TGR(A1-7)3292 (Figure 1).
## 2.2. Myocardial Markers of Oxidative Stress and Fibrotic Activity
Oxidative stress plays an important role in heart failure, including ACF. The increased synthesis and secretion of ROS leads to a disturbance of the oxidative balance, which in turn stimulates many signaling pathways that regulate various processes, including the promotion of cell proliferation and migration and the secretion of ECM [19]. The levels of TBARS, as a marker of oxidative stress, decreased in the left ventricle in the TGR(A1-7)3292 group compared to the HSD ACF group and in the right ventricle, and also in the TGR(A1-7)3292 group, but compared to the TGR ACF group (Figure 2).
Representative microscopic images of hematoxylin–eosin-stained myocardial tissue (apex) demonstrates the prevalent population of enlarged cardiomyocytes and fibrosis in TGR ACF versus HSD ACF rats (Figure 3). Hematoxylin–eosin staining (Figure 3A) revealed in TGR ACF rats an increased focal area infiltrated with polymorphonuclears (arrows), the histopathological feature of the hypertrophy or fibrosis. Moreover, hydroxyproline evaluation of collagen deposition (Figure 3B,C) revealed increased levels of collagen content in TGR ACF rats. Ang [1-7] notably suppressed polymorphonuclears and hydroxyproline content in TGR ACF rats indicating its antifibrotic potential. Hydroxyproline is a breakdown product of collagen occurring mainly in tissue fibrosis and overall cardiac remodeling expected in ACF-induced heart failure [20]. Hydroxyproline was increased in both heart ventricles in TGR ACF vs. HSD ACF. However, there was a significant decrease in hydroxyproline content in the right ventricle of TGR(A1-7)3292 ACF vs. TGR ACF (Figure 3). The sum of the results of HE staining and biochemical analysis of hydroxyproline points to the fact that Ang [1-7] in our HF model significantly reduces the level of fibrosis, especially in the right ventricle of the heart compared to TGR and normalizes them to the level of HSD control.
## 2.3. Determination of Myocardial MMP-2 Activity and Protein Levels
MMP-2 is a metalloproteinase that has an important role in the process of ECM remodeling, and its activation could be related to structural changes in cardiac ECM. There was a significant decrease in MMP-2 enzymatic activity in both heart ventricles of TGR ACF and TGR(A1-7)3292 ACF rats (Figure 4) compared to basal MMP-2 activity in normotensive HSD ACF rats (Figure 4). There were no significant changes of MMP-2 protein abundance in the left ventricle of experimental rats. ( Figure 4). However, MMP-2 protein levels were reduced in the right ventricle of TGR ACF and TGR(A1-7)3292 ACF as well as TGR(A1-7)3292 when compared to HSD ACF.
The mechanism of MMP-2 could differ between ventricles since they have a different function. These changes could also be more pronounced in our case because the right ventricle is much more affected by hemodynamic overload [21]. Unfortunately, the tendency of protein is slightly similar or shows no change (HSD ACF vs. TGR ACF); thus, it is difficult to attribute it to a different mechanism. We assume that this discrepancy between the ventricle could be attributed to the higher hemodynamic effect on right ventricle.
## 2.4. Determination of SMAD Protein Levels Implicated in Fibrosis
Increased expression of SMAD2 and SMAD3 was demonstrated mainly in fibroblasts infiltrating fibrotic and remodeling hearts [22]. We observed a decrease in the protein level of the profibrotic sum of SMAD$\frac{2}{3}$ in the left ventricle of TGR ACF versus HSD ACF and an increase in TGR(A1-7)3292 versus TGR ACF. In contrast, the right ventricle exhibited a reduction in the sum of SMAD$\frac{2}{3}$ in the TGR(A1-7)3292 ACF group compared to the HSD ACF and TGR ACF groups (Figure 5).
## 2.5. Determination of PKC Protein Levels
Protein levels of PKCα, implicated in the myocardial hypertrophy [23], were decreased in the left and right heart ventricles in TGR(A1-7)3292 ACF strain compared to HSD ACF or TGR ACF (Figure 6). Protein levels of pro-apoptotic, pro-hypertrophic and pro-fibrotic PKCδ [23] are demonstrated in Figure 6. There was a decline in PKCδ protein abundance in the TGR ACF and TGR(A1-7)3292 groups compared to HSD ACF as well as in TGR(A1-7)3292 ACF rats vs. TGR ACF. One of the protein kinases which directly phosphorylates Cx43 at Serine 368 is PKC-ε [24]. Contrary to PKCα and PKCδ, PKCε protein levels were increased in the TGR ACF and TGR(A1-7)3292 ACF rats vs. HSD ACF as well as in TGR(A1-7)3292 ACF rats vs. TGR ACF. The same trend of protein levels was observed in both left and right heart ventricles (Figure 6).
## 2.6. Myocardial Cx43 Protein Levels and Topology
Structural remodeling is associated with changes of Cx43 (protein levels and localization) responsible for electrical instability leading to increased risk of life-threatening arrhythmias. The protein levels of Cx43 in experimental rat hearts are demonstrated in (Figure 7). There was a significant increase in Cx43 protein abundance in the TGR(A1-7)3292 ACF group vs. HSD ACF/TGR ACF in both heart ventricles. However, ACF in the TGR(A1-7)3292 reduced protein abundance of Cx43 in the left as well as right ventricle. Protein levels of functional phosphorylated form of Cx43 were significantly increased in both heart ventricles of TGR hypertensive strain compared to normotensive HSD ACF rats. ( Figure 7). However, ACF in the TGR(A1-7)3292 reduced the protein abundance of the phosphorylated form of Cx43 in the left as well as right ventricle (Figure 7). Representative microscopic images of Cx43 cardiomyocyte distribution in the myocardium (apex) of experimental rats are shown in Figure 7. There is prevalent localization at the intercalated discs of the cardiomyocytes in normotensive HSD ACF. Notably, hypertensive TGR strains exhibit pronounced Cx43 distribution on lateral sides of the cardiomyocytes. Quantitative image analysis revealed a significant increase in the immunofluorescence signal in TGR(A1-7)3292 rats as well as with ACF. Total integral optical density per area (IOD) of Cx43 was similar to Cx43 protein levels significantly elevated in the myocardium (apex) of transgenic rats with increased expression of TGR(A1-7)3292 as well as in TGR(A1-7)3292 ACF.
## 3. Discussion
In order to detect the possible structural remodeling (hypertrophy) of the heart chambers after ACF induction and to monitor the influence of Ang [1-7], the biometric parameters were registered. The rat body weight was the same in all strains of rats with ACF. According to the literature, an increase in the whole heart, left ventricle and right ventricle weight normalized to the tibia length is attributed to cardiac hypertrophy [25,26,27]. We did not observe a difference in the heart weight between the HSD and TGR strains after ACF, the TGR(A1-7)3292 strain and after ACF as well. This may indicate a certain antihypertrophic effect of Ang [1-7], which was also observed in other studies [28].
Right ventricular weight imitated the results of the whole heart. Since the ACF model acutely affects mostly the right side of the heart, and based on the literature, it is logical that the right ventricular weight increases and eccentrically hypertrophies [29]; we also recorded a positive effect of Ang [1-7] in the right ventricle of TGR(A1-7)3292 strain vs. HSD and TGR after ACF. The biometric index of the left ventricle exhibited the trend of right ventricle probably due to the adaptation of the heart to volume overload in the compensatory phase of HF. On the other hand, we noted an increase in the weight of the left ventricle of TGR compared to HSD rats, which is due to the fact that the TGR strain has moderately increased blood pressure and the remodeling of the left ventricle takes place due to pressure overload even before the induction of ACF, as well as after the induction of ACF. The TGR(A1-7)3292 strain had a significantly smaller weight of the left ventricle after ACF than HSD or TGR strains. Altogether, biometric parameters indicate that Ang [1-7] influenced the size of the heart most likely by affecting cardiomyocyte growth.
We focused on the analysis of oxidative stress markers, such as TBARS, which reflects lipid peroxidation. We did not detect any alterations in heart tissue TBARS levels between individual groups or a positive or negative effect of Ang [1-7], similar to other studies [30,31]. While a positive antioxidant effect of Ang [1-7] in the kidney has been observed [32]. Furthermore, the positive influence of Ang [1-7] on the oxidation state in epididymal fat during a high-fructose diet was observed [33].
Another analyzed marker pointing out structural remodeling is hydroxyproline, a collagen cleavage product occurring mainly in tissue fibrosis [20]. We noticed an increasement of hydroxyproline content in the TGR group versus HSD after ACF. It is consistent with the fact that volume overload (already in period from 4 to 15 weeks after ACF induction) is characterized by an increased accumulation of the extracellular matrix proteins leading to cardiac fibrosis [25,34]. We observed that Ang [1-7] had no effect on the amount of hydroxyproline in the TGR(A1-7)3292 strain after ACF compared to HSD with ACF in neither the left or the right ventricle. The result in the TGR(A1-7)3292 rats’ strain is interesting, because even ACF did not cause an increase in hydroxyproline, pointing out a cardioprotective effect [25,35].
Hydroxyproline is directly linked to MMP-2 activity and protein levels. MMP-2 cause the splitting of components of the extracellular matrix, especially collagen, and thereby affect ECM remodeling and fibrosis. Both activity and protein abundance of MMP-2 were increased by ACF in the compensated or decompensated phase of HF, which is a response to the increasing need to synthesize collagen [36]. It can be considered as a compensatory mechanism in adaptation to the volume overload, which disrupts the myocardial homeostasis [25,27,37,38]. Consistent with other studies, we detected higher protein levels and activity of MMP-2 in the RV of normotensive HSD rats, and lower protein levels and activity in both hypertensive TGR and TGR(A1-7)3292 rats after ACF. Ang [1-7] had no effect on MMP-2. We detected lower MMP-2 activity in the left ventricle of TGR versus HSD after ACF, but the protein abundance was not changed. Noteworthy, ACF did not affect MMP-2 in the TGR(A1-7)3292 strain, which implies the possible anti-fibrotic effect of Ang [1-7]. In our opinion, the decrease in MMP-2 activity or its protein levels may be caused by the reduction of mean arterial pressure due to ACF in hypertensive TGR rats [27] and adaptation of the myocardium to hypertension. However, our hypothesis is associated with the ACF model, while data from hypertensive individuals suffering from volume overload are missing.
The implication of intracellular SMAD$\frac{2}{3}$ signaling involved in various hypertrophic and fibrotic pathways was also observed in HF models [39]. However, we did not detect alteration of SMAD$\frac{2}{3}$ between the HSD and TGR groups after ACF in the left or right heart ventricles. It may indicate that volume overload due to ACF is a stronger factor than hypertension in the compensatory phase. Ang [1-7] normalized SMAD$\frac{2}{3}$ protein expression in the right ventricle, compared to the HSD ACF and TGR ACF groups. This effect can be similar to the effect of simvastatin reported by Tang et al. [ 2021] [39] and considered as a certain form of cardioprotection.
Protein kinases C is a family of kinases involved in intracellular signaling during cardiovascular remodeling due to pressure or volume overload. In the heart, PKCε and PKCδ are the most expressed PKC isoenzymes, which are contradictory in cardioprotection, with the positive role of PKCε and the inhibitory role of PKCδ. In the process of hypertrophy, PKCε and PKCδ move in the same direction. PKCε induces ventricular hypertrophy via cardiomyocyte growth through phosphorylation of target proteins. PKCδ is mainly associated with ventricular hypertrophy under pathologies. Decline in PKCε and an increment in PKCδ protein levels, which has been found in several models of HF [40,41]. PKCα is responsible for cardiomyocyte growth, stimulates myocardial hypertrophy and reduces the apoptotic burden. Overexpression of PKCα protein causes a decrease in the contractile force, whereas inhibition of PKCα results in an increase in cardiac contractile performance [42,43]. Consistent with previous studies, PKCδ protein levels were decreased due to ACF reflecting possible adaptation of the myocardium to hypertension in TGR versus HSD [27]. In contrast to PKCδ, PKCε was increased in HSD and TGR groups after ACF. They act antagonistically, as also shown by others [44]. In the left ventricle, the expression of PKCε was significantly increased by the influence of Ang [1-7] in contrast to the right ventricle. It may be due to the fact that the ACF model affects the right ventricle more significantly. We detected a similar change in PKCα in the left and right ventricles, except for a significant decrease in the right ventricle in TGR compared to HSD. We did not observe any change in the left ventricle between normotensive and hypertensive animals. The TGR(A1-7)3292 strain had significantly reduced PKCα after ACF that can be attributed to the fact that Ang [1-7] has an effect through intracellular signaling on the development of hypertrophy and the contractile force. Likewise in other studies [42,43], we also did not detect in this rat strain an increase in PKCα after ACF.
Furthermore, we examined Cx43 as a protein that forms communicating channels between adjacent cardiomyocytes that are responsible for the transmission of electrical impulses. Abnormalities of Cx43 are mostly associated with electrical instability of the myocardium and thereby with an increased risk of malignant arrhythmias. Moreover, reduced expression of Cx43 promotes ECM remodeling and fibrosis [45,46]. Previously, Cx43 changes were analyzed in the decompensatory phase, not in the compensatory phase of HF [47]. Guggilam et al. [ 2013] [47] observed a significant decrease in Cx43 protein abundance, a prolongation of the QTc interval, reduced propagation of Ca2+ waves, which ultimately promote the occurrence of arrhythmias, and reduced cardiac contractility and systolic function of the heart. We did not detect alteration in Cx43 protein levels in the left ventricle after ACF in normotensive and hypertensive (HSD/TGR) rats, in contrast to the right ventricle, where we observed an increased protein levels of Cx43 in TGR after ACF versus HSD-ACF. We can explain the difference between HSD and TGR rats after ACF by the adaptation and partial normalization of pressure after ACF in hypertensive rats. Consistent with the study of Cao et al. [ 2018] [48], we also detected a significant increase in Cx43 in the TGR(A1-7)3292 strain after ACF compared to HSD and TGR after ACF. We demonstrated this cardioprotective effect of Ang [1-7] in both the left and right ventricles. A similar trend was observed in the phosphorylated form of Cx43, which is considered to be the active form of Cx43 [49,50]. PKCε, as one of the protein kinases responsible for the phosphorylation of Cx43 at serine 368, is associated with antiarrhythmic rat phenotype [51,52]. We found that pCx43 copies the protein levels of PKCε in the HSD and TGR groups after ACF in both the left and right ventricles. Even in the group of TGR(A1-7)3292 strain, we could see a decrease in pCx43 protein levels after ACF. Similar with total Cx43, we detected the cardioprotective effect of Ang [1-7] compared to HSD and TGR after ACF. Several studies have revealed a regulation of Cx43 phosphorylation at S368 by multiple PKC isozymes, not only by PKCε. For instance, PKCδ, a novel PKC isoform, has been shown to phosphorylate S368 leading to gap junction internalization and degradation through the proteasomal and lysosomal pathway [53,54]. Since in TGR(A1-7)3292 ACF rats (vs. TGR ACF) PKCδ was decreased, we can assume that an increase in Cx43 at serine 368 can be a result of decreased Cx43 internalization and degradation.
If we look at the results comprehensively, it can be concluded that Ang [1-7] exhibits cardio-protective and anti-fibrotic potential in conditions of cardiac volume overload. A limitation of this work is the absence of sham control groups in the HSD and TGR rats. In the future, it would be certainly interesting to analyze these cardioprotective effects after a longer time, or direct administration of Ang [1-7], after ACF in both normotensive and hypertensive animals.
## 4.1. Experimental Design
TGR(A1-7)3292 rats show specific testicular expression of a cytomegalovirus promoter-driven transgene that results in a doubling of circulating Ang [1-7] compared to non-transgenic control rats [55]. The hypertensive (mRen-2)27 transgenic rat strain (TGR) shows strong expression of the murine Ren-2 transgene in extrarenal tissues, which induces and maintains hypertension through conventional angiotensin II (Ang II), and hypertension is readily controlled by inhibition of the renin–angiotensin system (RAS). This transgenic rat strain is now widely used to study a variety of conditions related to tissue RAS activation, including angiogenesis, cytokine activation, profibrotic and inflammatory pathologies, thus contributing to the understanding of the underlying processes causing severe hypertension [56,57]. In the experimental model, 20 male TGR(A1-7)3292 laboratory rats, 10 male Hannover Sprague–Dawley (HSD) laboratory normotensive rats and 10 male (mRen-2)27 transgenic laboratory hypertensive rats (TGR) at the age of 8 weeks were used. HSD rats are standardly used as a normotensive control for TGR rats. The experimental animals came from the accredited laboratory breeding of the Center for Experimental Medicine, Institute of Clinical and Experimental Medicine in Prague, Czech Republic. All animal experiments were approved on 26 June 2017 by the Animal Care and Use Committee of the Institute for Clinical and Experimental Medicine, Prague; project number $\frac{50}{2017}$; in accordance with guidelines and practices established by the Directive $\frac{2010}{63}$/EU of the European Parliament on the Protection of Animals Used for Scientific Purposes. Laboratory animals TGR(A1-7)3292 were divided into two groups with sham surgery and ACF surgery, HSD and TGR with ACF surgery (Table 1). The animals were fed a standard laboratory diet, which, was available to them ad libitum, as well as drinking water. They were kept in air-conditioned rooms with a constant temperature of 22–24 °C, humidity of 40–$60\%$ and with a regular light regime of 12 h of darkness and 12 h of light. The ACF operation was performed under general anesthesia induced by isoflurane. After exposing the abdominal aorta and inferior vena cava, the aorta was occluded for 30 s in the area between the renal arteries and the iliac bifurcation. ACF was created by inserting a needle (diameter 1.2 mm) through the abdominal aorta into the inferior vena cava. The injection site was then sealed with cyanoacrylate tissue adhesive [58]. Five weeks after ACF induction, rats in the “compensated HF” phase were euthanatized by decapitation.
## 4.2. Western Blot Assay
As was described previously in our publications [51,59], frozen left ventricular heart tissue was powdered, extracted in SDS lysis buffer ($20\%$, 10 mmol/L EDTA, 100 mmol/L Tris, pH 6.8) and diluted in Laemmli buffer. Proteins were separated in $10\%$ SDS-polyacrylamide gel and transferred to a nitrocellulose membrane (0.2 m pore size, Advantec, Tokyo, Japan). Membranes were blocked in $5\%$ low-fat milk and then incubated with primary antibodies (Table 2) and horseradish peroxidase-linked secondary antibody (Table 2). Enhanced chemiluminescence was used for detection of proteins, which were consequently in triplicate quantitated using Carestream Molecular Imaging Software (version 5.0, Carestream Health, New Haven, CT, USA). For protein normalization GAPDH protein was used.
## 4.3. Gelatine Zymography for MMP-2 Activity Assessment
Samples were prepared and separated in $10\%$ gels copolymerized with gelatin (2 mg/mL) same as in the Western blot method, but in non-reducing conditions. Gels were soaked in washing buffer (50 mmol/L Tris-HCl, $2.5\%$ Triton X-100, pH 7.4) and incubated in developing buffer at 37 °C (50 mmol/L Tris-HCl, 10 mmol/L CaCl2, $1.25\%$ Triton X-100, pH 7.4). After overnight incubation, gels were stained in stain solution ($1\%$ Coomassie Brilliant Blue G-250 dissolved in a solution containing $10\%$ acetic acid and $40\%$ methanol) and distained with a solution containing $10\%$ acetic acid and $40\%$ methanol. Finally, transparent bands on a dark blue background appeared. Bands considered as enzymatic activities of MMP-2 were densitometric quantified by Carestream Molecular Imaging Software (version 5.0, Carestream Health, New Haven, CT, USA) [60].
## 4.4. Cx43 Immunostaining and Quantitative Analysis
For Cx43 immunodetection, 10 µm thick cryosections of myocardial apex tissue were used. According to our previous publications [59,61], cryosections were fixed in ice-cold methanol, permeabilized in $0.3\%$ Triton X-100, blocked in solution of $1\%$ bovine serum albumin and incubated with primary anti-Cx43 antibody (diluted 1:500, CHEMICON International, Inc., Temecula, CA, USA, #MAB 3068 and secondary antibody with FITC-fluorescein isothiocyanate (diluted 1:500, Jackson Immuno Research Labs, West Grove, PA, USA, #111-095-003). For actin filaments, visualization cryosections were stained with phalloidin (Sigma-Aldrich, St. Louis, MO, USA, #P 2141). Microscopic images were captured by Zeiss Apotome 2 microscope (Carl Zeiss, Jena, Germany). Quantification of Cx43 immunofluorescence signal was performed on a 15 randomly selected myocardial area (per heart) and expressed as total integral optical density per area (IOD) [62].
## 4.5. Collagen Content Determination by Hydroxyproline Assay
The fibrosis marker, hydroxyproline, was spectrophotometric evaluated as was described previously [59]. Myocardial tissue was hydrolyzed in 6 M HCl very briefly, dried and incubated in the solution of chloramine T-acetate-citrate buffer (pH 6.0). Finally, to stop oxidation reaction, Ehrlich’s reagent solution was added. Hydroxyproline was measured spectrophotometrically at 550 nm and expressed in mg per total weight of the LV and RV.
## 4.6. Measurement of Malondialdehyde Level
According to Shlafer and Shepard [1984], with some modifications [63,64], approximately 40 µL of tissue homogenates (prepared in 4.2. Western blot assay) were pipetted together with a mixture of two solutions: 40 µL of $20\%$ trichloroacetic acid solution with a 320 µL of TBARS reagent (37 mmol/L C4H4N2O2S, 500 mmol/L NaOH, $15\%$ v/v CH3COOH). After the incubation and cooling step, n-butanol and pyridine (14:1, v/v) were added and centrifuged 10 min at 5000× g. The resulting organic phase was measured at 535 nm by a Synergy H1 Hybrid Multi-Mode Microplate Reader (Biotek, VT, USA).
Based on the calibration curve from tetrabutylammonium malondialdehyde salt, the concentration of malondialdehyde (MDA) was calculated.
## 4.7. Statistical Analysis
Differences between groups were evaluated using one-way ANOVA and Bonferroni multiple comparison tests. Kolmogorov–Smirnov normality test to examine if variables are normally distributed was used. Data were expressed as mean ± SD; $p \leq 0.05$ was considered to be statistically significant.
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|
---
title: Disulfiram Enhances the Antineoplastic Activity and Sensitivity of Murine Hepatocellular
Carcinoma to 5-FU via Redox Management
authors:
- Iftekhar Hassan
- Hossam Ebaid
- Ibrahim M. Alhazza
- Jameel Al-Tamimi
- Ahmed M. Rady
journal: Pharmaceuticals
year: 2023
pmcid: PMC9967644
doi: 10.3390/ph16020169
license: CC BY 4.0
---
# Disulfiram Enhances the Antineoplastic Activity and Sensitivity of Murine Hepatocellular Carcinoma to 5-FU via Redox Management
## Abstract
The efficacy of anticancer drug 5-FU is suppressed due to various factors, including severe side effects and decreased insensitivity during prolonged chemotherapy. Elevated endogenous copper (Cu) levels are one of the prominent hallmark features of cancer cells. In the present investigation, this feature was targeted in diethyl nitrosamine-phenobarbital-induced hepatocellular carcinoma (HCC) in a rat model system by an established anticancer drug, 5-FU, co-administered with copper and its chelating agent, disulfiram. After treatment with the test chemicals in HCC-induced rats, blood and liver samples were subjected to biochemical, molecular, and histopathological analyses. The analysis revealed that reactive oxygen species-mediated oxidative stress is the crucial etiological reason for the pathogenesis of HCC in rats, as evidenced by the significantly compromised activity of major antioxidant enzymes and elevated levels of oxidative damaged products with major histological alterations compared to the control. However, the combination of 5-FU with DSF demonstrated a significant improvement in most of the parameters, followed by 5-FU-Cu in the combination-treated groups. The combination treatment improved the histological details and triggered apoptosis in the cancer cells to a remarkable extent, as the levels of cleaved PARP and caspase-3 were significantly higher than those in the HCC rats treated with the drug alone. The present study envisages that manipulating the Cu-level greatly enhances the antineoplastic activity of 5-FU and sensitizes cancer cells to the increased efficacy of the drug.
## 1. Introduction
Cancer is a heterogeneous and multistage disease resulting from uncontrolled cellular proliferation (initiation), consequently leading to the invasiveness of neighboring cells (progression) and distant healthy cells (metastasis). These tumorous cells can ditch cell death signals and exhaust the body’s immune system [1,2]. Despite significant developments in cancer treatment and oncology over the last five decades, the disease is still considered the second most fatal after cardiovascular diseases. Currently, a variety of cancer treatment modalities are available, including surgery, chemotherapy, radiotherapy, immunotherapy, hormonal therapy, catalytic therapy, and gene therapy, but chemotherapy based on antineoplastic drugs/agents alone or in combination is still the most favored and effective treatment strategy among all [3]. Despite developing all these treatment strategies, they are limited mainly by either their short-lived efficacy or the treatment regimen being modified or discontinued because of associated mild to severe side effects [4]. Hence, combining two or more treatment modalities is considered the best strategy to contain the disease.
Copper (Cu) is an essential metal-nutrient requisite for all life forms. The metal is incorporated into several metalloenzymes and metalloproteins involved in diverse biological activities. It executes a vital role in various metabolic and physiological processes, such as metabolism, nerve induction, neurotransmission, erythropoiesis, connective tissue synthesis, assistance to all iron-mediating biological actions in addition to immunity boost-up, including angiogenesis, wound healing and pathophysiology involving tumor growth and inflammatory diseases [5,6,7]. Cu-dependent enzymes, such as cytochrome c oxidase, NADH dehydrogenase-2, Cu/Zn superoxide dismutase, tyrosinase, ferroxidases, monoamine oxidase, and dopamine β-monooxygenase, reduce molecular oxygen. The unique redox property of Cu that enables it to deliver various biological activities also poses a potentially toxic effect because its ambivalent effects result in the generation of invasive free radicals such as superoxide and hydroxyl radicals [8,9]. If not properly regulated in the living system, copper can exert extreme cytotoxic effects and genetic mutations that can compromise Cu-homeostasis and be translated into severe clinical phenotypes. Therefore, understanding how cells maintain optimal copper levels is highly relevant to human health [10].
As one of the most prominent hallmarks in cancerous cells, the elevated endogenous Cu level has drawn the interest of many contemporary researchers [11]. In addition, Cu induces neovascularization, and its concentration is profoundly increased in angiogenic tissue [12]. Cu chelators, used to treat Wilson disease (a disease of Cu toxicity), have been cited for inhibiting tumor growth and angiogenic responses in many studies [7]. Moreover, Cu also plays a vital role in inflammatory responses involved in innate and adaptive immunity by activating NF-κB [13]. Alternatively, Cu deficiency alters the intravascular adhesion of leukocytes to activated ECs and the expression of adhesion molecules, such as ICAM-1/VCAM-112,5,13 [14]. Despite the critical role of Cu in angiogenesis and inflammation, the exact molecular mechanisms underlying these functions are entirely unknown.
Oxidative stress is a disparity between the generation of highly reactive free radicals and metabolites (oxidants) and their nullification by the natural machinery (antioxidant system) in living organisms. This imbalance causes damage to biologically significant biomolecules (proteins, lipids, and nucleic acids) and a cellular structure that can subsequently compromise cellular function and integrity. Moreover, stress can lead to chronic inflammation induced by free radicals and concurrent biological, chemical, and physical factors that enhance the chances of serious diseases, including several types of human cancers [15]. Hence, there is a strong association between oxidative stress, inflammation, and carcinogenesis, as shown by various epidemiological and experimental studies [16,17]. Hence, many antioxidants and anti-inflammatory therapies show significant efficacy in cancer prevention and management [18]. Virchow was the first to plead that certain types of inflammatory cells occur within tumors and that most tumors originate at sites of chronic inflammation [19]. Hence, such inflammation is often referred to as the “secret killer” for many health-related issues and the etiology of many diseases, such as cancer [20]. If this is not regulated, a potentially negative impact falls on the whole organism, resulting in various diseases [21]. Therefore, a vivid relationship between oxidative stress, inflammation, and cancer has recently been more widely accepted among contemporary researchers and oncologists [20].
Cancer therapeutic resistance is supposed to be directly related to the disease’s late stages and metastasis phase; however, there are no effective interventions to prevent cancer progression at such stages, even with the latest combinations of treatment modalities. Therefore, searching for novel compounds of therapeutic potential and suggestions for anticancer treatment strategies that might pave the way for a fruitful breakthrough in the future become a necessity [21]. We have previously found that endogenous copper is critical in determining the efficacy and outcome of chemotherapeutic agents [2]. This study examines whether the level of endogenous Cu plays a major role in attributing therapeutic interventions against tumors by investigating oxidative stress and critical apoptotic markers. In this work, we tried to explore how the manipulation of Cu levels can influence the anticancer efficacy of 5-FU in DEN-induced hepatocellular carcinoma in a rat model system.
## 2.1.1. AFP
This is believed to be one of the most reliable cancer markers. It was elevated by $352.37\%$ in group II compared to the control group. Groups I, IV and V demonstrated a decrease in its level by $25.90\%$, $32.91\%$, and $26.21\%$, respectively, compared to group II. Among the combination groups, groups VI and VII showed a decline in their levels of $39\%$ and $42.88\%$, respectively, compared to group II (Figure 1).
## 2.1.2. GOLPH 3
This is also a very accurate biomarker to assess hepatocellular carcinoma. In the present investigation, group II exhibited a rise in its level of $128.97\%$ compared to group I. Groups III, IV and V demonstrated a decline in their level by $12.29\%$, $29.85\%$ and $14.88\%$, respectively. In contrast, groups VI and VII showed a dip in their level by $35.02\%$ and $40.90\%$, respectively, compared to group II (Figure 1).
## 2.2.1. SOD
This is assumed to be one of the chief antioxidant enzymes in our body. The specific activity of this enzyme was compromised by $82.19\%$ in group II compared to group I. Groups III, IV and V showed an increase in the activity by $31.55\%$, $76.23\%$, and $50.95\%$, respectively. In comparison, groups VI and VII demonstrated enhancements in activity by $135.74\%$ and $160.26\%$, respectively, compared to group II (Figure 2).
## 2.2.2. CAT
The specific activity of this antioxidant enzyme was decreased by $71.73\%$ in group II compared to group I. Groups III, IV and V exhibited increases in its activity by $40.05\%$, $67.06\%$ and $48.08\%$, respectively. In contrast, groups VI and VII showed elevations in activity by $69.56\%$ and $123.45\%$, respectively, compared to group II (Figure 2).
## 2.2.3. GR
The specific activity of this enzyme decreased by $84.71\%$ in group II compared to group I. Groups III, IV and V showed an increase in its activity by $68.12\%$, $94.37\%$, and $46.87\%$, respectively. In comparison, groups VI and VII exhibited enhancements in activity by $137.5\%$ and $235.93\%$, respectively, with respect to group II (Figure 2).
## 2.2.4. MDA Levels
MDA is considered the most stable final product after lipid peroxidation in vivo. Its level was staggeringly high in group II, i.e., by $825.80\%$ compared to group I. Other groups III, IV and V showed a decrease in its level by $35.88\%$, $43.55\%$ and $40.42\%$ compared to group II. However, the combination groups VI and VII demonstrated reduction in their levels by $65.85\%$ and $70.38\%$, respectively, compared to group II (Figure 3).
## 2.2.5. Total Carbonyl Content
Group II showed a sharp increase in its level by $1075.60\%$ compared to group I. Groups III, IV and V displayed declines of $33.19\%$, $47.30\%$, and $26.34\%$, while groups VI and VII showed decreases of $55.60\%$ and $62.65\%$, respectively, in comparison to group II (Figure 3).
## 2.2.6. 8-OHdG
This is one of the reliable markers to assess oxidative DNA damage and the extent of carcinogenesis. Its level was increased by $376.71\%$ in group II with respect to group I. Groups III, IV, and V showed a decrease in its level by $41.23\%$, $44.39\%$ and $38.36\%$, respectively, compared to group II. The combination groups VI and VII demonstrated dips in their levels by $53.44\%$ and $56.72\%$ compared to group II (Figure 3).
## 2.3.1. p-53
This is considered the guardian gene in the nucleus of a cell that stabilizes nuclear DNA and its integrity. In the present study, group II showed a $65.24\%$ decline in its level compared to group I. Groups III, IV and V demonstrated $27.69\%$, $40\%$, and $33.84\%$ enhancements of its level, while groups VI and VII exhibited $41.53\%$ and $106.15\%$ increases in its level, respectively, compared to group II (Figure 4).
## 2.3.2. Cleaved PARP
This is one of the most prominent markers to confirm the occurrence of apoptosis. Its level was decreased by $29.66\%$ in group II compared to group I. Groups III, IV and V showed an increase in its level by $55.35\%$, $107.82\%$, and $94.23\%$, while group VI and VII displayed a rise in their level by $113.05\%$ and $170.46\%$ compared to group II (Figure 4).
## 2.3.3. Cleaved Caspase-3
The level of cleaved caspase-3 was compromised by $46.73\%$ in group II compared to group I. Groups III, IV, V, VI and VII showed increases in cleaved caspase-3 levels of $16.32\%$, $42.85\%$, $26.53\%$, $32.65\%$ and $65.30\%$, respectively, compared to group II (Figure 4).
## 2.4. Effect on Nuclear DNA of the Liver Cells
In the present work, group II demonstrated an increase in tail length by $101.08\%$ compared to the control. However, group III, IV, V, VI and VII showed a decrease in tail length by $20.59\%$, $24.64\%$, $17.71\%$, $28.68\%$ and $32.19\%$, respectively, when compared to group II (Figure 5).
## 2.5. Assessment of Necrosis by LDH Activity
The activity of group II was enhanced by $82.05\%$ compared to the control. Groups III, IV, V, VI and VII demonstrated a decrease in its activity by $10.49\%$, $13.44\%$, $6.14\%$, $15.36\%$ and $19.71\%$, respectively, compared to group II (Figure 6).
## 2.6. Histopathological Evaluation
The histological evaluation of the liver samples from the treatment groups reflected marked differences among the various groups, confirming the biochemical and oxidative stress analysis. The histology of the control group, group I, showed typical histological features of a normal liver with well-maintained contours of healthy hepatocytes with normal nuclei radiating toward the central vein. The less developed tumor nodules/patches on the color faded surface of the liver in the DEN-PB-treated positive control (group II) indicated hepatocellular carcinoma in the treated rats (pictures not shown). The histopathology of the control-positive group II showed severe histological alterations in the hepatocytes, mostly with distorted contours, extensive vacuole formation, disturbed sinusoids and inflammatory infiltration indicative of partial loss of tissue in the form of fibrosis and necrosis in addition to apoptosis in some of the cells. The other groups, III and V, demonstrated mild to moderate damage, including light inflammatory cell infiltration and unclear cellular boundaries with narrow sinusoids; however, these features were less prominent in group IV. The combination groups VI and VII showed improved histological details, including less vacuole formation and ceasing inflammatory features with less fibrosis and normal sinusoids with normal nuclei; however, group VII showed better histological restoration than group VI (Figure 7).
## 3. Discussion
Hepatocellular carcinoma (HCC) is the fifth most common form of cancer and causes the death of almost 600,000 patients around the world annually [22]. This form of cancer arises from complicated and multistage carcinogenesis after chronic exposure to several mitogenic and mutagenic agents, causing random genetic alterations, consequently leading to this phenotype as a disease [2]. This cancer has a high mortality rate, as its diagnosis is difficult at the early stage. Despite being a widely occurring form of cancer, no concrete breakthrough has been achieved yet for its effective treatment, even after many decades of research. However, the endogenous Cu level was significantly elevated in HCC-induced rats, similar to many other types of cancer [23]. The present investigation aims to target endogenous Cu levels to enhance the antineoplastic activity of 5-FU in HCC-induced rats, which might be an effective strategic cancer management strategy for prolonging the life span and quality of life.
In the present study, we found that DEN-PB was able to induce the second stage of HCC, as evidenced by biochemical analysis showing staggeringly enhanced tumor markers (AFP and GOLPH3) and compromised antioxidant parameters (SOD, CAT, and GR) concomitant with highly elevated products of oxidative damage to key macromolecules (MDA, carbonyl content and 8-OHdG). Furthermore, the histopathological evaluation revealed an extensive alteration in the structure of hepatocytes and distorted sinusoids, indicating acute inflammation, fibrosis, and even necrotic signs. The rats treated with copper, 5-FU and DSF also showed mild to moderate perturbation in their biochemical analysis, antioxidative parameters, oxidative stress-induced damage, and histological assessment. However, the 5-FU-treated group showed improvement in most parameters compared to the other two groups (Cu and DSF). However, the combination of the drug with Cu and DSF showed stronger antineoplastic activity than 5-FU alone in HCC rats. These combinations decreased the burden of cancer in the treated rats and improved antioxidant parameters with a significantly diminished level of oxidative damage to lipids, proteins, and DNA. It is also noteworthy that the combination of 5-FU + DSF showed better antineoplastic activity than 5-FU + Cu in the present investigation (Figure 8).
It is well established that reactive oxygen and nitrogen species (ROS and RNS), which cause relative oxidative and nitrosative stress in vivo, are the major cause of various physiological alterations, immunological pathogenesis, and diseases, including cancer [19]. In the present study, ROS and oxidative stress also play a pivotal role in chemically induced HCC, which is quite evident from the compromised activity of antioxidant enzymes concomitant with significantly elevated levels of MDA, carbonyl content and 8-OHdG in the cancer-induced group. Furthermore, endogenous *Cu is* generally elevated in cells under conditions that also facilitate ROS-mediated cellular and macromolecular damage in their vicinity. These reactive species are invasive enough to cross through the nucleus and interact with nuclear DNA, which might affect major genes, including p-53 and p-21 [23]. This might be one of the attributes of genetic instability in cancer cells, as indicated by elevated 8-OHdG levels in the HCC group. In addition, this genetic alteration can affect the normal cell cycle of such cells, resulting in necrosis or apoptosis depending on the severity of the damage incurred. In contrast, the Cu-treated rats showed slight improvement in many of the parameters that might be chiefly attributed to the enhanced activity of the antioxidant enzyme Cu-Zn-SOD in addition to the metal supporting the chromatin of nuclear DNA. It has been reported that administered Cu can bind with metallothionein (MT), accumulating in cancer cells’ lysosomes and increasing their susceptibility to cell death. In addition, the metal can also pass through the mitochondrial membrane of the cells, altering the organelle functions and gene expression that might result in apoptosis and necrosis [24,25]. However, DSF treatment showed a better effect in HCC rats than Cu treatment. The chelating agent seems to lower oxidative stress and the related damage incurred by excessive endogenous Cu in cancer cells. In addition, much of the literature suggests that the DSF-Cu complex exerts potent proteasome inhibitory and apoptosis-inducing effects in Cu-rich tumor cells with precise target specificity [26]. Furthermore, Denoyer et al., [ 27] reported that DSF, a member of the dithiocarbamate family, triggers a series of events, such as affecting the redox-related cellular machinery, altering cellular glutathione and other redox thiol proteins and changing mitochondrial permeability. All these events eventually lead to apoptosis induction in the affected cells [28].
The present investigation is based on hypothesis Hassan et al. [ 2]: that if the elevated endogenous Cu of the cancer cells is restraint managed, they can be converted into bullets to kill the same cells. Interestingly, co-administered Cu and DSF with the anticancer drug 5-FU showed enhanced antineoplastic activity compared to the drug alone in chemically induced HCC rats. As excessive Cu levels are one of the major causes of drug resistance, the 5-FU-DSF combination showed better efficacy than the 5-FU-Cu combination. Many earlier studies have demonstrated that DSF at the appropriate dose can induce apoptosis by a staggering 400–$600\%$ in many cell lines and animal model-based studies [29,30]. Additionally, Chen et al. [ 29] demonstrated that DSF not only triggers apoptosis but also enhances the apoptosis susceptibility of tumor cells in vitro and in vivo. The chelating agent has been reported to trigger apoptosis in cancer cells by various modes of action, including depleting the GSH level, decreasing the mitochondrial membrane potential and transiently increasing the cellular superoxide level [2]. Moreover, DSF also orchestrates the immune system and ceases the inflammatory and aggressive immune response in the affected cells [26]. In addition, cleaved PARP and cleaved caspase-3 were significantly higher in 5-FU-DSF-treated rats than in 5-FU-Cu-treated rats. These notions justify why 5-FU-DSF exerts a better antineoplastic combination than 5-FU-Cu. These parameters are indicators of programmed cell death progression and are considered the preferred way to kill cancer cells.
Nevertheless, it is also important to mention that the action of DSF/Cu essentially involves the NF-κB and TGF-β pathways during carcinogenesis and metastasis of hepatocellular carcinoma [31]. Furthermore, another study has shown that DSF-Cu combination can impede GSK3β activity via the inhibition of PARP1, resulting in immunosuppression via PD-L1 stabilization in hepatocellular carcinoma [32].
It is also possible that the marked elevation of Cu (II) in malignant cells is one of the cellular responses to handle the demand for high proliferation and angiogenesis in addition to providing a shield to nuclear chromatin to evade immune surveillance [2,33]. In the same frame of cellular events, elevated metal levels might cause the cellular machinery to scan nuclear DNA for vulnerability/damage. Depending on the integrity of the nuclear DNA, the cellular machinery decides either to halt cell cycle progression until the completion of repair of the damaged DNA or to trigger programmed cell death via the activation of caspase-7 and caspase-3 if the nuclear damage is extensive or highly uneconomic (in terms of NADH/ATP). Under such conditions, other critical proapoptotic markers, including p-53 and PARP, also facilitate the progression of apoptosis [2]. These findings also indicate that the chosen dose of the adjuvants (DSF and Cu) with 5-FU at its therapeutic dose in the combination groups engages these significant facilitators of apoptosis induction. Hitherto, both adjuvants may follow different modes of action in enhancing the antineoplastic activity of the drug. Nevertheless, DSF seems to be enjoying favoritism with the drug, as it might nullify the excessive endogenous Cu around the nuclear DNA in the chromatin, ceasing the aggression of the immune response, inflammation and oxidative stress, and allowing the cellular machinery to repair the damaged DNA or recruit facilitators of apoptosis induction and proteasome inhibition [25]. In addition, all of the excessive Cu might be chelated by DSF, which could allow 5-FU to bind to the target sites in cancer cells effectively. All these factors collectively favor DSF in improving the antineoplastic activity of 5-FU concerning Cu in the combination groups (Figure 9). Many contemporary researchers have shown similar findings that restrained management of oxidative stress by DSF/Cu has great potential to be an effective chemo- and radiotherapy treatment, with modalities addressing various forms of cancer, including cirrhosis and liver cancer [34,35].
## 4. Materials and Methods
All the materials and methodology applied have been detailed in the Supplementary File S1.
## 5. Conclusions
The present investigation indicates that the co-administration of DSF and 5-FU significantly envisages the antineoplastic activity of the drug in vivo. The chelating agent increases the sensitivity of the drug in the rats that reorient the antioxidant system and immune system (data not shown) in favor of apoptosis induction, consequently decreasing the overall tumor burden. These factors can significantly enhance cancer patients’ life span and quality of life. However, further studies are warranted to comprehend the complex array of the intricate mechanism involved in the present study.
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---
title: The Mutation Spectrum of Rare Variants in the Gene of Adenosine Triphosphate
(ATP)-Binding Cassette Subfamily C Member 8 in Patients with a MODY Phenotype in
Western Siberia
authors:
- Dinara Ivanoshchuk
- Elena Shakhtshneider
- Svetlana Mikhailova
- Alla Ovsyannikova
- Oksana Rymar
- Emil Valeeva
- Pavel Orlov
- Mikhail Voevoda
journal: Journal of Personalized Medicine
year: 2023
pmcid: PMC9967647
doi: 10.3390/jpm13020172
license: CC BY 4.0
---
# The Mutation Spectrum of Rare Variants in the Gene of Adenosine Triphosphate (ATP)-Binding Cassette Subfamily C Member 8 in Patients with a MODY Phenotype in Western Siberia
## Abstract
During differential diagnosis of diabetes mellitus, the greatest difficulties are encountered with young patients because various types of diabetes can manifest themselves in this age group (type 1, type 2, and monogenic types of diabetes mellitus, including maturity-onset diabetes of the young (MODY)). The MODY phenotype is associated with gene mutations leading to pancreatic-β-cell dysfunction. Using next-generation sequencing technology, targeted sequencing of coding regions and adjacent splicing sites of MODY-associated genes (HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11, ABCC8, and APPL1) was carried out in 285 probands. Previously reported missense variants c.970G>A (p.Val324Met) and c.1562G>A (p.Arg521Gln) in the ABCC8 gene were found once each in different probands. Variant c.1562G>A (p.Arg521Gln) in ABCC8 was detected in a compound heterozygous state with a pathogenic variant of the HNF1A gene in a diabetes patient and his mother. Novel frameshift mutation c.4609_4610insC (p.His1537ProfsTer22) in this gene was found in one patient. All these variants were detected in available family members of the patients and cosegregated with diabetes mellitus. Thus, next-generation sequencing of MODY-associated genes is an important step in the diagnosis of rare MODY subtypes.
## 1. Introduction
Maturity-onset diabetes of the young (MODY) is a rare monogenic type of diabetes mellitus with autosomal dominant inheritance and includes 14 subtypes, which are classified by causative genes: HNF4A, GCK, HNF1A, NEUROD1, PDX1, HNF1B, KLF11, CEL, PAX4, INS, BLK, KCNJ11, ABCC8, or APPL1 [1]. The complexity of diagnosing MODY is due to the similarity of its clinical signs with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) [2]. Patients with monogenic types of diabetes mellitus require a personalized approach to the selection of a proper treatment [3]. Verification of these types of diabetes is possible only through molecular genetic testing. Without this analysis, up to $80\%$ of cases of monogenic diabetes can be misdiagnosed or may go undiagnosed [4]. Most MODY cases ($70\%$) are due to mutations in the GCK or HNF1A gene, whereas pathogenic variants in other genes are rarer [5]. *The* gene of adenosine triphosphate (ATP)-binding cassette subfamily C member 8 (ABCC8) is reported to be associated with the MODY12 subtype, permanent or transient neonatal diabetes mellitus, and an opposite phenotype: hyperinsulinemic hypoglycemia [6,7,8]. *This* gene is located on the short arm of chromosome 11, consists of 39 exons, and encodes a protein of 1581 amino acid residues. The product of ABCC8 is a sulfonylurea receptor (SUR1), a regulatory subunit of the ATP-sensitive K+ channel in membranes of pancreatic β-cells. This channel is composed of four inward-rectifier potassium ion pore-forming subunits (Kir6.2) and four SUR1 subunits combined into a hetero-octameric complex [9]. One of the main functions of this channel is the regulation of insulin secretion through changes in the membrane potential of the cell [10]. When the glucose level rises, the ATP/adenosine diphosphate (ADP) ratio increases in β-cells, thus leading to the closure of the K+ channel with the subsequent opening of a voltage-gated calcium channel. Insulin secretion goes up as a consequence [10]. An increase in ADP concentration influences SUR1 by forcing the channel to open and preventing an insulin release [11]. SUR1 is known to be a multidomain protein that includes transmembrane-domain 0 (TMD0, exons 1–4), loop 0 (L0, exons 5 and 6), transmembrane domain 1 (TMD1, exons 6–12), a part of nucleotide-binding domain 1 (NBD1, exons 13–15), and a sulfonylurea receptor motif (exons 2, 3, 5, and 7). Exons 17 to 39 code for P-loop-containing nucleoside triphosphate hydrolase, transmembrane domain 2 (TMD2), and nucleotide-binding domain 2 (NBD2) [12]. More than 400 mutations in the ABCC8 gene have been described, most of which are located in coding parts of the gene (www.hgmd.org, accessed on 2 November 2022). Hyperinsulinism of various severity levels is usually induced by inactivating mutations in ABCC8 [13]. Activating mutations in the ABCC8 gene reduces the sensitivity of the channel to the inhibitory effect of ATP and enhances its sensitivity to ADP, thereby leading to the channel opening regardless of glucose levels. Such mutations can cause permanent or transient neonatal diabetes, MODY, or T2DM [14,15,16]. Most patients with ABCC8 mutations have diabetes only; however, a greater decrease in the channel’s sensitivity to ATP gives rise to a more severe clinical phenotype, which may include neurological features, such as a developmental delay, seizures, epilepsy, mild dystonia, tonic posture, and muscle weakness [14,15].
The ABCC8-associated phenotype may depend on the type of mutation: variants activating the channel cause diabetes mellitus, whereas inactivating ones usually induce hyperinsulinism [13,14]. Few cases are described where the carriage of the same substitution in the same residue causes hyperglycemia or congenital hyperinsulinism in different patients [17,18]. There are also cases when congenital hyperinsulinism transforms into diabetes mellitus later in life [19,20,21]. An association of common variant rs757110 G of the ABCC8 gene with the risk of T2DM has also been shown in the global population [22]. Clinical variability of symptoms and genetic heterogeneity of patients carrying mutations in the ABCC8 gene complicates MODY12 diagnosis. Most cases of ABCC8-dependent diabetes are misdiagnosed as other types of diabetes mellitus, and insulin is mistakenly prescribed, which can result in poor control of carbohydrate metabolism [23]. Therefore, genetic testing is required for the identification of a causative gene in patients with a family history of diabetes.
In this study, the screening of rare genetic variants in ABCC8 was performed using next-generation sequencing (NGS) technology in patients with hyperglycemia accompanied by the absence of antibodies against pancreas islet cells and glutamic acid decarboxylase and without ketoacidosis. The pathogenicity of the genetic variants was evaluated according to the standards of the American College of Medical Genetics (ACMG) and Genomics and the Association for Molecular Pathology [24], available databases, and literature data.
## 2.1. Study Subjects
The study protocol was approved by the local Ethics Committee of the Institute of Internal and Preventive Medicine (a branch of the Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia), protocol number 7 of 22 June 2008.
The total group of unrelated patients consisted of 285 persons (23.1 ± 11.7 years old [mean ± SD]; $37.9\%$ males) examined at the Clinical Department of the Institute of Internal and Preventive Medicine from the year 2014 to 2022. Diabetes mellitus was diagnosed according to the criteria of the American Diabetes Association (Arlington County, VI, USA): HbA1C ≥ $6.5\%$, or fasting plasma glucose ≥ 126 mg/dL (7.0 mmol/L), or 2-h plasma glucose ≥ 200 mg/dL (11.1 mmol/L) during an oral glucose tolerance test (in the absence of unequivocal hyperglycemia; the result had to be confirmed by repeat testing), or a patient with classic symptoms of hyperglycemia or a hyperglycemic crisis with a random plasma glucose level ≥ 200 mg/dL (11.1 mmol/L) [25]; a debut of the disease in probands at the age of 35 years or earlier; a family history of diabetes mellitus; the absence of obesity; the absence of antibodies against pancreas islet cells and glutamic acid decarboxylase; intact secretory function of β-cells; normal or mildly reduced C-peptide levels; no need of insulin therapy; and the absence of ketoacidosis at the onset of the disease. The study population could include patients with MODY as well as T1DM patients with a negative antibody test result and an early onset of T2DM. Patients with clinical features of atypical diabetes mellitus (differing from those of T1DM and T2DM) and, in some cases, lacking a family history were included in this study [26]. Patients with tuberculosis or human immunodeficiency virus infection, as well as those who underwent antiviral therapy for hepatitis B or C, who abused psychoactive substances or alcohol within 2 years prior to the study, were excluded.
## 2.2. Sequencing of MODY-Associated Genes and Bioinformatic Analysis
After informed consent was obtained, venous blood (5 mL) was collected from all the studied patients. DNA was extracted from the venous blood using phenol–chloroform extraction [27]. The quantity and quality of the DNA were assessed on an Epoch microplate spectrophotometer (BioTek, Winooski, VT, USA). The first step of the preparation of a DNA library included DNA fragmentation using the KAPA HyperPlus Kit (Roche, Switzerland). SeqCap EZ Prime Choice Probes (Roche, Basel, Switzerland) were employed for NGS target enrichment. Targeted regions included coding regions and adjacent splicing sites of the following MODY-associated genes: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11, ABCC8, and APPL1. The HyperCap Target Enrichment Kit (Roche, Switzerland) was used for the recovery of captured DNA regions. The quality of the analyzed DNA and of the prepared libraries was evaluated by means of a capillary electrophoresis system, Agilent 2100 Bioanalyzer (Agilent Technologies Inc., Santa Clara, CA, USA). The prepared DNA samples were sequenced on the Illumina MiSeq platform (Illumina, San Diego, CA, USA) at the multi-access center Proteome Analysis (Federal Research Center of Fundamental and Translational Medicine, Novosibirsk, Russia). Automated processing and annotation of the obtained NGS data were carried out on the NGS Wizard platform (genomenal.com, accessed on 19 May 2021).
Data on the clinical significance and pathogenicity prediction of the annotated single-nucleotide variants (SNVs), ClinVar and VarSome, and literature data were employed for the analysis. Allele frequencies were annotated using databases GnomAD v3.1.2 [28] and RUSeq, 2 November 2022 (http://ruseq.ru/). Variants described in ClinVar or VarSome or predicted in silico to be benign/likely benign, as well as variants with minor allele frequency higher than $0.01\%$ according to gnomAD and RUSeq, were excluded from the analysis. The pathogenicity of new variants was assessed in accordance with the recommendations of the ACMG and Genomics and the Association for Molecular Pathology [24].
The present study is focused on the spectrum of rare variants in the ABCC8 gene.
## 2.3. ABCC8 Confirmation Analysis
The detected substitutions c.970G>A (p.Val324Met), c.1562G>A (p.Arg521Gln), and c.4609_4610insC (p.His1537Profs*22) in the ABCC8 gene (NM_000352.6) were verified by Sanger sequencing of the corresponding DNA fragments of the ABCC8 gene in probands and their relatives available for the analysis. The oligonucleotide primers used are shown in Table 1. The design of the oligonucleotides was performed in the Primer-Blast software 19 May 2021 (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). The sequencing reaction was performed on an ABI 3500 instrument (Thermo Fisher Scientific, Waltham, MA, USA) using the BigDye Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific, USA) in accordance with the manufacturer’s protocol. The sequences were analyzed in Chromas, 2 June 2021 (http://technelysium.com.au/wp/) and Vector NTI® Advance 11 (Thermo Fisher Scientific, USA) software; a fragment of the ABCC8 gene (NG_008867.1) served as a reference sequence for alignment.
## 3. Results
The search for pathogenic variants was carried out in 14 MODY-associated genes. No such variants were identified in PDX1, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11, and APPL1. In total, 55 out of the 285 probands proved to be carriers of pathogenic or probably pathogenic (previously described in ref. [ 29,30] or new) variants in GCK, HNF1A, HNF4A, HNF1B, and ABCC8 (Supplementary Materials; Table S1.). Among these 55, only 3 probands are carriers of rare variants in the ABCC8 gene.
## 3.1. Variants in Genes GCK, HNF1A, HNF4A, and HNF1B
A total of 36 probands out of the 55 were found to be carriers of pathogenic and probably pathogenic variants (nonsense mutations, small deletions, missense mutations, or splice site mutations) in the GCK gene, and 13 probands are carriers of variants in the HNF1A gene.
Among the additionally examined patients, previously described GCK variants were identified: two patients (P398 and P412) turned out to be carriers of c.238G>A (p.Gly80Ser) in exon 2; c.556C>T (p.Arg186*) and c.562G>A (p.Ala188Thr) in exon 5 were found in probands P186 and P188, respectively; c.659G>A (p.Cys220Tyr) in exon 6 and c.683C>T (p.Thr228Met) in exon 7 was detected in probands P384 and P433, respectively (Supplementary Materials; Table S1). Novel dinucleotide deletion AC c.11_12del (p.Asp4Glufs*47) was revealed in one proband (P437) in exon 1 of the GCK gene (Supplementary Materials; Table S1).
In the HNF1A gene, novel variant c.335delA (p.Pro112Argfs*43) and previously described c.872dupC (p.Gly292Argfs*25) and c.872delC (p.Pro291Glnfs*51) were identified (Supplementary Materials; Table S1). Proband P73 is a carrier of the c.160C>T (p.Arg54*) variant in the HNF1A gene and c.1562G>A (p.Arg521Gln) in the ABCC8 gene (Supplementary Materials; Table S1). Novel single-nucleotide deletion c.85delC (p.Asn30Thrfs*74) in the HNF4A gene was detected in a heterozygous state in one proband: P381. We described the patient’s medical history and clinical features in ref. [ 31].
Two unrelated participants with diabetes and negative for autoimmunity (P27 and P400) carry previously described variant c.1006C>A (p.His336Asp) in the HNF1B gene. Some variants of this gene are associated with the MODY5 subtype and congenital anomalies of the kidneys and urinary tract and, less often, of the pancreas or genitalia [32]. In P27′s family, variant p.His336Asp did not cosegregate with a pathological phenotype. Family members of P400, other than the healthy mother, were not available for genetic analysis, and we had no information about any kidney or other anomalies among them. There are no published data with clear evidence of p.His336Asp pathogenicity [33,34], and it has been classified as a variant of uncertain significance in the LOVD database or a variant with conflicting interpretations of pathogenicity in ClinVar.
## 3.2. Variants in ABCC8
Because the MODY12 subtype is extremely rare in most populations [35], it is of interest to analyze variants in the ABCC8 gene in patients with diabetes mellitus.
Earlier, we published a detailed clinical case of proband P12 [36].
The ABCC8 gene variants identified in this study in the 285 probands (including three rare variants detected in this study) are presented in Table 2. Some common variants of this gene are reported in the literature to be associated with T2DM, but these results are ethnospecific [37]. No potentially pathogenic variants were identified here in adjacent regions of splice sites of this gene. Variants c.354C>T (p.Val118=), c.1678G>A (p.Val560Met), and c.2274G>A (p.Ala758=) were not included in the analysis because they were identified as benign in ClinVar (Variation ID: 255930, 188919, and 1097104, respectively) and in VarSome. Three heterozygous variants c.970G>A (p.Val324Met), c.1562G>A (p.Arg521Gln), and c.4609_4610insC (p.His1537ProfsTer22) were selected for further analysis.
## 3.3. The Phenotype of Patients with MODY12
Diabetes mellitus was diagnosed at ages of up to 27 in probands and up to 50 among their family members. At the onset of the disease, fasting hyperglycemia was determined during a routine examination or during pregnancy. There were no islet cell cytoplasmic antibodies (ICA), insulin antibodies (IAA), antibodies to glutamate decarboxylase (GAD), tyrosine phosphatase (IA2), antibodies to the zinc transporter (ZnT8A), and there were no symptoms of ketoacidosis at the onset of the disease. The weight of all patients was within the age norm (body–mass index (BMI): 18.2–22.6). In all the families examined, there was a family history of pathology of carbohydrate metabolism.
When observed for 3 years (2019–2022), hyperglycemia ranged from asymptomatic to significant decompensation of carbohydrate metabolism in the probands. Macro- and microvascular complications were not detectable at the time of examination and observation. All three probands (P293, P73, and P330) were on insulin therapy. Available family members of the three probands were examined for the presence of corresponding variants in the ABCC8 gene (Figure 1).
Heterozygous missense mutation c.970G>A (p.Val324Met) in ABCC8 was identified in proband P293, her affected father, and little daughter (Figure 1A,B) and was absent in the proband’s healthy mother. Close monitoring of carbohydrate metabolism parameters in proband P293′s daughter was recommended because of the high risk of diabetes mellitus. We did not find other pathogenic variants in other MODY-associated genes in the proband. This variant is classified as pathogenic in ClinVar (Variation ID: 1338342) and VarSome (ACMG: PS3, PP3, PP5, PM1, and PM2). The variant was absent in databases gnomAD and RUSeq (Table 2).
Heterozygous missense mutation c.1562G>A (p.Arg521Gln) in the ABCC8 gene was identified in proband P73 and his affected mother (Figure 1C,D). Other family members were unavailable for the examination. The proband and his mother also proved to be carriers of pathogenic variant c.160C>T (p.Arg54*) in the HNF1A gene [29]. Arg521Gln in the ABCC8 gene is classified as “conflicting interpretations of pathogenicity” in ClinVar (Variation ID: 157683) and as “Uncertain Significance” in VarSome (ACMG: PM1, PM2, PP5, and BP4). This variant is described in gnomAD v3.1.2 with minor allele frequency (MAF) = 0.0001117 and RUSeq (MAF) = 0.0004160, eastern Russia) (Table 2). In both databases, this variant is described only in a heterozygous state. In the proband and his mother, the variant cosegregated with the disease (criterion PP1).
In proband P330, the c.4609_4610insC (p.His1537Profs*22) variant of the ABCC8 gene was identified (Figure 1E,F). It is not described in databases gnomAD v3.1.2 and RUSeq (criterion PM2) or in the literature. The patient’s relatives were not available for the analysis. The c.4609_4610insC variant (p.His1537Profs*22) is a single-nucleotide deletion of cytosine that results in a frameshift and probably a premature stop codon. Loss-of-function mutations in the ABCC8 gene have been repeatedly described and are pathologically significant (criterion PVS1). In silico analysis showed that the variant is damaging (criterion PP3). Thus, according to the set of criteria (PVS1, PM2, and PP3), p.His1537Profs*22 was assumed to be pathogenic.
## 4. Discussion
MODY was suspected in the probands owing to the age of onset of diabetes mellitus before 45 years, the presence of relevant family history, the absence of ketoacidosis at the onset of the disease, the absence of relevant antibodies, and the absence of symptoms of insulin resistance. We did not find any MODY12-specific symptoms common among the three probands and their relatives other than the usual clinical signs of MODY.
The c.970G>A (p.Val324Met) substitution is located in the transmembrane domain TMD1 of SUR1. There is a report of heterozygous carriage of this mutation in a female patient (age at diagnosis: 2 days) with transient neonatal diabetes mellitus without relapse at the time of examination (22 weeks) [47]. The substitution was inherited on the maternal side, but the proband’s mother had no signs of diabetes. A male patient with neonatal diabetes and a severe developmental delay at 74 days of life has been described who carries substitutions c.970G>A (p.Val324Met) and Arg1394Leu in the ABCC8 gene; at the age of 6, he still had diabetes (C-peptide level 0.07, HbA1c 61 mmol/mol, and the absence of relevant antibodies), and his treatment was changed to sulfonylureas [38]. Carriage of a c.970G>A (p.Val324Met) and the Trp688Arg compound heterozygous variant in the ABCC8 gene was associated with permanent neonatal diabetes mellitus in a 17-year-old Italian female (age of manifestation: 15 days) [39]. A successful treatment change from insulin to sulfonylureas was reported. It is likely that the patient’s deceased mother was a carrier of the c.970G>A (p.Val324Met) variant because the 74-year-old grandfather of the proband is a carrier of this variant and has diabetes mellitus (2 h plasma glucose: 14 mmol/L). The paternal grandmother of the proband is a carrier of the Trp688Arg variant and features impaired glucose tolerance (2 h plasma glucose: 8.4 mmol/L) [39]. A heterozygous male carrier of c.970G>A (p.Val324Met) with transient neonatal diabetes mellitus (absence of relevant antibodies, glucose at 24 mmol/L, and presence of ketoacidosis) and a developmental speech delay has been described [40]. The diabetes relapsed at age 9, and treatment with insulin was prescribed. After identification of the mutation, the treatment was switched successfully to glibenclamide [40]. Functional studies on a cell line have shown that the c.970G>A (p.Val324Met) variant causes a severe activating gating defect and reduces SUR1 expression on the cell surface, followed by attenuation of its functional effect on β-cells [48].
Variants responsible for the development of late-onset autosomal dominant diabetes in genes of ATP-sensitive K+ channels have rarely been described [42]. Heterozygous variant c.1562G>A (p.Arg521Gln) in the ABCC8 gene has been found in a man with nonimmune diabetes mellitus and a family history of diabetes; the age of manifestation is 34 [41]. The same variant has been identified by laboratory tests in another person with diabetes mellitus [42]. The same as p.Val324Met, p.Arg521Gln is located in transmembrane domain 1 of the SUR1 protein; this domain is involved in ATP binding. In proband P73 and his mother (Figure 1C), this variant was found to be combined with a substitution in the HNF1A gene. In terms of the clinical phenotype, carriers of pathogenic ABCC8 gene variants are similar to patients with HNF1A and HNF4A MODY [7]; therefore, it was not possible to identify a contribution of a specific mutation to the clinical signs.
Heterozygous variant c.4609_4610insC (p.His1537Profs*22) was found in proband P330. During the survey, a family history of disorders of carbohydrate metabolism was revealed (Figure 1E), but his relatives were not available for the analysis. The detected variant is located in NBD2, which is responsible for the binding of Mg-nucleotides and, as a result, channel opening and membrane hyperpolarization, which leads to the prevention of insulin secretion. Known mutations in ABCC8 that cause diabetes mellitus either increase the activation of the Mg-nucleotide-mediated channel or alter the intrinsic gating [49]. Functional studies on this variant have not yet been conducted, and there are no data on this variant in the literature and databases.
Thus, in patients with a MODY phenotype in the Russian population, 18 previously described and one novel [c.4609_4610insC (p.His1537ProfsTer22)] variant as revealed in the ABCC8 gene. Among them, we identified four potentially causative variants [c.970G>A (p.Val324Met), c.1562G>A (p.Arg521Gln), c.4369G>C (p.Ala1457Thr), and c.4609_4610insC (p.His1537Profs*r22)], which cosegregated with diabetes mellitus in the available family members of the patients.
## Limitations
This study has some limitations due to the unavailability of information about some family members.
## 5. Conclusions
Our results suggest that variants c.970G>A (p.Val324Met), c.1562G>A (p.Arg521Gln), and c.4609_4610insC (p.His1537ProfsTer22) in ABCC8 could be the cause of MODY-ABCC8 in the Russian population. We did not detect any specific clinical features of MODY among patients carrying pathogenic variants of ABCC8, thereby confirming the need for genetic testing of patients with a MODY phenotype using NGS for correct diagnosis and treatment as well as for counseling the patients’ relatives.
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|
---
title: 'The Formulation of Curcumin: 2-Hydroxypropyl-β-cyclodextrin Complex with Smart
Hydrogel for Prolonged Release of Curcumin'
authors:
- Ljubiša Nikolić
- Maja Urošević
- Vesna Nikolić
- Ivana Gajić
- Ana Dinić
- Vojkan Miljković
- Srđan Rakić
- Sanja Đokić
- Jelena Kesić
- Snežana Ilić-Stojanović
- Goran Nikolić
journal: Pharmaceutics
year: 2023
pmcid: PMC9967663
doi: 10.3390/pharmaceutics15020382
license: CC BY 4.0
---
# The Formulation of Curcumin: 2-Hydroxypropyl-β-cyclodextrin Complex with Smart Hydrogel for Prolonged Release of Curcumin
## Abstract
Curcumin comes from the plant species *Curcuma longa* and shows numerous pharmacological activities. There are numerous curcumin formulations with gels or cyclodextrins in order to increase its solubility and bioavailability. This paper presents the formulation of complex of curcumin with 2-hydroxypropyl-β-cyclodextrin in a thermosensitive hydrogel, based on N-isopropylmethacrylamide and N-isopropylacrylamide with ethylene glycol dimethacrylate as a crosslinker. The product was characterized by chemical methods and also by FTIR, HPLC, DSC, SEM, XRD. The results show that synthesis was successfully done. With an increase in the quantity of crosslinker in the hydrogels, the starting release and the release rate of curcumin from the formulation of the complex with hydrogels decreases. The release rate of curcumin from the gel complex formulation is constant over time. It is possible to design a formulation that will release curcumin for more than 60 days. In order to determine the mechanism and kinetics of curcumin release, various mathematical models were applied by using the DDSolver package for Microsoft Excel application. The Korsmeyer-Peppas model best describes the release of curcumin from the gel formulation of the complex, while the values for the diffusion exponent (0.063–0.074) shows that mechanism of the release rate is based on diffusion.
## 1. Introduction
Curcumin ((1E,6E)-1,7-bis(4-hydroksy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione), Figure 1, is a natural polyphenol isolated from the rhizome of the plant species *Curcuma longa* which shows numerous pharmacological activities by the modulation of physiological and biochemical processes. Research shows that curcumin possesses hypoglycemic [1], antimicrobial [2], hepatoprotective [3], anti-inflammatory [4], antioxidant [5], anticancer [6], antiviral [7] and many other effects. Various animal studies and clinical trials have shown that curcumin is safe to apply at high doses because it does not affect liver and kidney function. However, due to poor water solubility and low bioavailability, it is classified as a drug of group IV by the biopharmaceutical classification system, and its therapeutic application is limited [8,9,10,11]. In order to improve the physico-chemical properties, different systems for curcumin delivery were used: cyclodextrins for the formation of inclusion complexes [12,13,14,15], micelles [16], liposomes [17,18], nanoemulsions [19], hydrogels [20], polymers formed by cross-linking of cyclodextrin [21,22,23], polymer nanofibers [24,25,26], complexes with cyclodextrin incorporated into polymers [27,28,29] and other nanoparticles [2,30]. In the study of Purpura et al., the bioavailability of formulation of curcumin with β-cyclodextrin was examined. The results of the study show that the formulation of β-cyclodextrin with curcumin significantly improves the absorption of curcumin in healthy people [31]. In the experiment of Jafer et al., with the aim of improving the delivery of curcumin in the treatment of cancer cells, an inclusion complex of β-cyclodextrin with curcumin was prepared. The obtained results show that the complex of β-cyclodextrin with curcumin improved the delivery and antiproliferative effect to the MCF-7 breast cancer cells [14]. The inclusion complex of curcumin with β-cyclodextrin obtained by coprecipitation method increased the water solubility of curcumin from 0.00122 to 0.721 mg/cm3. The release of the inclusion complex from nanocomposite and conventional poly(N-isopropylacrylamide/sodium alginate) hydrogels crosslinked with N,N′methylenebis(acrylamide) (BIS), respectively, was tested under simulated gastrointestinal conditions. At pH = 1.2, hydrogels showed the lowest release and swelling ratio, but at pH = 6.8 the highest release to swelling ratios of curcumin were achieved [28]. A thermosensitive hydrogel was synthesized, poly(D,L-lactide-co-glycolide)-poly(ethylene-glycol)-poly(D,L-lactide-co-glycolide), as a carrier for the delivery of doxorubicin in combination with an inclusion complex of curcumin with β-cyclodextrin for the treatment of cancer cells. Combined therapy based on doxorubicin and inclusion complex of curcumin with β-cyclodextrin showed greater antitumor activity than monotherapy in vitro [29]. Zhang et al., synthesized in situ forming hydrogels based on polyvinyl pyrrolidone, encapsulated with a solid dispersion of curcumin for the healing of vaginal wounds and the treatment of vaginal bacterial infections. After local application for treatment of the vaginal infection caused by *Escherichia coli* and Staphylococcus aureus, high efficiency in therapeutic treatment has been confirmed, along with inflammation reduction and improved healing of vaginal wounds [32]. Shefa et al. have synthesized a biocompatible and biodegradable hydrogel system for the delivery of curcumin based on polyvinyl alcohol and oxidized cellulose nanofibers, in order to improve the wound healing process [33]. Thermosensitive β-glycerophosphate/chitosan hydrogels, with an encapsulated complex of curcumin:β-cyclodextrin for the treatment of skin wound infections, were synthesized in work of Zao et al. The ability of wound healing using the above mentioned hydrogel was tested on induced superficial wounds in rats. By analyzing the results, it was observed that the wounds treated with hydrogel containing the complex of curcumin:β-cyclodextrin showed a faster healing rate compared to wounds that were covered only with gauze [34]. A drug delivery system based on poly(N-isopropylacrylamide), p(NiPAm), hydrogel and a suitable solvent for improvement of solubility and local release of curcumin was also synthesized in the experimental work of Ayar et al. Curcumin was incorporated in p(NiPAm) hydrogel during swelling by using methanol or polyethylene glycol of low molecular weight (PEG200). The obtained results show that PEG200 increases curcumin solubility more than methanol, and shows a superior effect on the cumulative quantitative of curcumin released over 7 days (33.163 ± 0.319 mg/cm3) compared to methanol (8.765 ± 0.544 mg/cm3). P(NiPAm) hydrogel combined with PEG200 did not show any cytotoxicity, and can be used as an effective sustained release system for curcumin [35].
In recent years, highly advanced curcumin delivery systems have been developed such as nanoparticles, ultrasound microbubbles, exosomes, biopolymer nanoparticles [36], nanogels, nanosuspensions, nanoemulsions and dendrimer [37]. The goal for creating such formulations was to improve the stability and solubility of curcumin.
The polymer hydrogels based on N- isopropylmethacrylamide (NiPMAm) and/or N-isopropylacrylamide (NiPAm) are well known because of their good property to respond to temperature changes by changing the degree of swelling [38,39]. To create a three-dimensional network of these gels, ethylene glycol dimethacrylate (EGDM) is often used as a networker. If in their structure they contain a copolymerized organic acid (acrylic acid, methacrylic acid, etc.), the degree of swelling of these gels will also change with the change in the pH value of the environment [40]. That is why these gels are called smart hydrogels, because they react by changing the degree of swelling with the change of the conditional parameters in which they are found. Namely, if the temperature of these swollen hydrogels is increased, their degree of swelling decreases and they squeeze out liquid and vice versa, but if their pH value is lowered the degree of swelling increases and vice versa. These kinds of gels have been used as matrix systems for medicinal substances [41]. In Figure 2, chemical structures of N-isopropylmethacrylamide, N- isopropylacrylamide and ethylene glycol dimethacrylate are shown.
The topic of this paper is the development of a new matrix system based on a smart polymer carrier crosslinked with poly(N-isopropylmethacrylamide-co-N-isopropylacrylamide), with an incorporated inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, with the aim of increasing the solubility of curcumin. With this system, targeted delivery and sustained release of curcumin can be performed. In Figure 3, part of a cyclic structure of a seven-membered ring molecule of 2-hydroxypropyl-β-cyclodextrin is shown.
## 2.1. Reagents
N-isopropylmethacrylamide (NiPMAm) $97\%$, N-isopropylacrylamide (NiPAm) $99\%$, 2,2′-azobis(2-methylpropionitrile) (AIBN) $98\%$ (Acros Organics, New Jersey, NJ, USA); ethylene glycol dimethacrylate (EGDM) $97\%$ (Fluka Chemical Corp, Buchs, Switzerland); curcumin (CU) $97\%$, 2-hydroxypropyl-β-cyclodextrin (2-HP-β-CD) $97\%$ (Tokyo Chemical Industry Co., Ltd., Tokyo, Japan); Tween 20 (Alfa Aesar, ThermoFisher, Kandel, Germany); potassium bromide (KBr) $99\%$, ethanol (Et) $99.5\%$, methanol for HPLC (Me) ≥$99.9\%$ (Merck KGaA, Darmstadt, Germany); Hanks’ buffered solution pH 7.4 GmbH (PAA Laboratories, Pasching, Austria). All reagents were used with no further purification.
## 2.2. Synthesis of Hydrogels
Hydrogels samples were synthesized according to the procedure described previously [39]. In short, hydrogels poly(N-isopropylmethacrylamide-co-N-isopropylacrylamide), p(NiPMAm/NiPAm), in the molar ratio $\frac{10}{90}$ were synthesized by radical polymerization of monomers NiPMAm and NiPAm, with EGDM as a crosslinker in 2 and 3 mol% relative to the total amount of monomer. Obtained gels were marked $\frac{10}{90}$/2 and $\frac{10}{90}$/3, respectively. Ethanol was used as a solvent and 30 mg of AIBN for initiation of the polymerization reaction. After dissolving the reactants, the homogenized reaction mixtures were injected into glass ampoules which were then heat sealed. The polymerization reaction was performed in the mode: 0.5 h at 70 °C, 2 h at 80 °C and 0.5 h at 85 °C. After polymerization and cooling of the samples at room temperature, copolymerized p(NiPMAm/NiPAm) hydrogels were obtained in the form of long cylinders and cut into discs of thickness 5 mm. Hydrogels prepared in this way were extracted with methanol during 168 h in order to remove unreacted reactants, then washed off with water for 24 h to remove methanol and after that, dried at 40 °C to constant weight.
## 2.3. Lyophilization of Gels
Lyophilization p(NiPMAm/NiPAm) of hydrogels swollen up to the equilibrium was performed on the apparatus LH Leybold Heraeus, Lyovac GT2 (Labexchange, Frekendorf, Switzerland). The synthesized hydrogels are firstly frozen at a temperature of −40 °C during 24 h. In first subphase of drying, the volume of solution was reduced by sublimation at −30 °C and pressure of 5 Pa during 12 h. In the second subphase of drying, i.e., isothermal desorption, the hydrogels were heated up to 20 °C during 6 h at the pressure of 5 Pa, with removal of steam. Lyophilized samples of hydrogels were packed under vacuum condition and stored in a refrigerator at 5 °C.
## 2.4. Obtaining of the Complex
Curcumin (368.38 mg) was dissolved in 200 cm3 of absolute ethanol and added to the solution of 2-hydroxypropyl-β-cyclodextrin obtained by dissolution of 1541.54 mg 2-hydroxypropyl-β-cyclodextrin in 100 cm3 of distilled water. The mixture obtained like this was equilibrated by mixing on a magnetic stirrer at room temperature during 96 h, protected from light. The resulting solution was concentrated on a vacuum evaporator at 40 °C to the minimum volume, and then dried in a desiccator over a dehydrating agent at room temperature to constant mass. The molar ratio of curcumin and 2-hydroxypropyl-β-cyclodextrin in inclusion complex was 1:1.
## 2.5. Phase Solubility
Phase solubility study was performed according to method described by Higuchi & Connors [42]. Surplus of curcumin (each 10 mg) was added in 2.5 cm3 water solution of 2-hydroxypropyl-β-cyclodextrin of concentration 0–10 mmol/dm3. The samples were stirred at room temperature during 24 h, and then filtered through a membrane filter with a pore diameter 0.45 μm (Econofilters, Agilent Technologies, Waldborn, Germany). The quantity of dissolved curcumin was determined by application of UV/V method on the basis of constructed calibration curves of absorbance dependence on concentration. Measurements were performed by spectrophotometer Cary-100 Conc (Varian PTY LTD, Springvale, Australia) at wavelength 429 nm, in quartz cuvettes (1 × 1 × 4.5 cm) at room temperature. Distilled water was used as a blank solution. The presence of 2-hydroxypropyl-β-cyclodextrin does not affect the absorbance of curcumin at 429 nm, because its absorption at that wavelength is equal to 0. The constant of stability (K1:1) of inclusion complex was calculated based on the phase solubility diagram according to Equation [1]:[1]K1:1=slopeS0(1−slope), where S0 is solubility of curcumin at 25 °C in the absence of cyclodextrin (intercept) and slope represents the value from the phase solubility graph.
## 2.6. Incorporation of Complex of Curcumin: 2-Hydroxypropyl-β-cyclodextrin into p(NiPMAm/NiPAm) Gels
Matrix systems with a curcumin: 2-hydroxypropyl-β-cyclodextrin complex and p(NiPMAm/NiPAm) hydrogels were obtained by swelling the hydrogels to equilibrium in ethanol in which the inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin in concentration of 1.23 mg/cm3 was dissolved, at a temperature of 25 °C. Weighed samples of xerogels p(NiPMAm/NiPAm), 50 mg, were covered with a solution of curcumin inclusion complex (5 cm3) and left to swell at room temperature, protected from light. After reaching equilibrium, swollen p(NiPMAm/NiPAm) the hydrogels were separated from the remaining solution by decantation, washed with distilled water in order to remove the unincorporated amount of the inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, and after that extra water was removed from the surface of the matrix gels. The quantity of incorporated curcumin in p(NiPMAm/NiPAm) was determined based on the difference in the quantities of curcumin in the initial solution of the inclusion complex curcumin: 2-hydroxypropyl-β-cyclodextrin, and the supernatant after equilibrium was reached by using the HPLC method. The efficiency of incorporation of curcumin in hydrogel, η, was calculated according to Equation [2]:[2]η(%)=LgLu · 100, where *Lg is* mass of curcumin incorporated in p(NiPMAm/NiPAm) hydrogel, mg/gxerogel, and Lu initial mass of curcumin entered by the solution of the curcumin: 2-hydroxypropyl-β-cyclodextrin inclusion complex for swelling and incorporating into xerogel, mg/gxerogel.
The schematic view of obtaining the formulation of curcumin: 2-hydroxypropyl-β-cyclodextrin complex with p(NiPMAm/NiPAm) hydrogel is shown in Figure 4.
## 2.7. The Release of Curcumin from Matrix System
In vitro study of the release of curcumin from swollen p(NiPMAm/NiPAm) hydrogels with incorporated inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin was carried out in a medium that simulates physiological conditions. Each sample was covered with 10 cm3 of solution (9 cm3 Hank’s BSS buffer with pH value 7.4 and 1 cm3 of Tween 20 solution concentration of 1.52 mg/cm3). The samples were thermostated in a water bath at 37 °C with stirring on a magnetic stirrer (Hanna Instruments, Magnetic stirrer HI 190M) during 48 h. The amount of curcumin released was monitored by sampling 200 µL of solution over time, which were then filled up with methanol up to 1 cm3, filtered on a cellulose membrane filter with a pore diameter 0.45 µm and analyzed by HPLC method. The kinetics of the curcumin release from the matrix system was evaluated by different mathematical models (Higuchi, Korsmeyer–Peppas, Baker–Lonsdale) with DDSolver package for Microsoft Excel applications.
## 2.8. Determination of the Concentration of Some Compounds by Using High Pressure Liquid Chromatography (HPLC)
The content of residual reactant (monomers and crosslinkers) in samples of synthesized p(NiPMAm/NiPAm) hydrogels was calculated by HPLC method. The analysis was performed by using the apparatus HPLC Agilent 1100 Series (Waldborn, D) equipped with diode-array detector, DAD 1200 Series. Conditions for chromatography performance: column Zorbax Eclipse XDB-C18 (4.6 × 250 mm, 5 μm) (Agilent Technologies, Inc., Santa Clara, CA, USA); temperature 25 °C; injected volume of samples 10 μL; detection wavelength 210 nm; mobile phase consists of methanol/redistilled water $\frac{70}{30}$, v/v; mobile phase flow was 0.5 cm3/min. The results obtained were processed by software Agilent Chemstation. On the basis of constructed calibration curves for the linear dependence, the equations were obtained for determining the content of NiPMAm, NiPAm and EGDM in methanol extracts obtained by the processing of synthesized p(NiPMAm/NiPAm) hydrogels.
The dependence of the peak area on the concentration of NiPMAm is linear in range of 0.005–0.250 mg/cm3. For the straight part of the calibration curve of NiPMAm the Equation [3] applies with a linear correlation coefficient R2 = 0.995. [ 3]c=A-572.1497110.1, Dependence of peak area on concentration of NiPAm is linear in range of 0.005–0.250 mg/cm3 and in the straight part of the calibration curve the Equation [4] applies, R2 = 0.997. [ 4]c=A-594.72137938.4, Dependence of peak area on concentration of EGDM is linear in range 0.005–0.250 mg/cm3. For the straight part of the calibration curve of EGDM the Equation [5] applies, R2 = 0.998. [ 5]c=A-911.18171,931, In Equations [2]–[4], A is pick area (mAU·s), and c is concentration of reactants (mg/cm3) NiPMAm, NiPAm either EGDM.
Determination of the quantity of curcumin that was not incorporated into the hydrogels, as well as monitoring of curcumin release from the hydrogels, was performed by using liquid chromatography HPLC method at these conditions: column Zorbax Eclipse XDB-CN 250 × 4.6 mm, 5 μm (Agilent Technologies, Inc., Santa Clara, CA, USA); eluent was methanol: mobile phase flow was 1 cm3/min; volume of injected samples 20 μL; column temperature 40 °C; detection wavelength 425 nm. For the straight line part of the curcumin calibration curve in range 0.53–106 µg/cm3, Equation [6] applies with a linear correlation coefficient R2 = 0.999. [ 6]c=A+158.26184.15, where A is pickk area (mAU·s), and c is concentration of curcumin (µg/cm3).
## 2.9. Swelling of Hydrogels
Swelling of synthesized p(NiPMAm/NiPAm) xerogels was monitored gravimetrically. A known quantity of p(NiPMAm/NiPAm) xerogels was immersed in a water solution of a certain pH value and temperature, and then the mass of the sample was measured at certain time intervals until equilibrium was reached, i.e., until constant mass of hydrogels was reached. Aqueous mediums for swelling were prepared by adjusting the pH value by addition of 0.1 M solution of sodium hydroxide (Centrohem, Beograd, Serbia) or 0.1 M solution of hydrochloric acid (Zorka, Šabac, Serbia) while observing the value on pH meter (HI9318-HI9219, Hanna, P). The thermosensitivity of hydrogels was tested in the temperature range of 25 to 80 °C in a water bath. The degree of swelling, α, was calculated according to Equation [7]. [ 7]α=m−m0m0, where m0—is mass of dry gel, m—mass of swollen gel in a point of time t.
To analyze the type of solvent diffusion process inside hydrogels, Equation [8] applies, which stands for condition (Mt/Me ≤ 0.6) [43,44]:[8]F=MtMe=k · tn, where F—is the fractional sorption, Mt—mass of the absorbed solvent in a point of time, Me—mass of the absorbed solvent in equilibrium, k—a constant that is characteristic for a certain type of polymer network (min1/n) and n—diffusion exponent. By logarithmizing Equation [8] comes a linear Equation [9] that can be applied to calculate the constant k and an exponent n. [9]lnMtMe=lnk+n · lnt, The value of diffusion exponent n determines the mechanism of fluid diffusion. For value $$n = 0$.5$ the fluid diffusion mechanism corresponds to Fick’s law of diffusion (case I), where the rate of solvent transport into the gel is lower than the rate of relaxation of polymer chains. When the value for diffusion exponent is lower than 0.5, the penetration of solvent is much slower than the polymer chains relaxation. The solvent transportation mechanism is a part of Fick’s diffusion and is called “less to Fick’s” diffusion. Anomalous diffusion mechanism (non-Fick’s diffusion) occurs with 0.5 < n < 1, and then the hydrogels swelling is under control by both solvent diffusion in matrix and polymer chains relaxation. The diffusion process is a lot faster when the diffusion exponent has value 1 in comparison to the polymer system chains relaxation (case II), while when n > 1 the polymer chains relaxation is under control of gels swelling (case III, Super case II). The diffusion coefficient of solvent molecules in hydrogel (D) is most often determined by applying the Equation [10] which takes into account only the initial stage of swelling ($60\%$ of swelling) during which the thickness of the polymer remains approximately constant [45,46]:[10]MtMe=4 · (Dtπl2)$\frac{1}{2}$, where D stands for diffusion coefficient (cm2/min), and l for the thickness of the dry hydrogel, xerogel (cm). By logarithmization of Equation [10], linear dependence comes between ln(Mt/Me) and lnt (Equation [11]) from the section of which the diffusion coefficient D is calculated. [ 11]lnMtMe=(4D$\frac{1}{2}$π$\frac{1}{2}$l)+12lnt,
## 2.10. Fourier Transform Infrared Spectroscopy (FTIR)
The FTIR spectra of monomers, synthesized p(NiPMAm/NiPAm) xerogels, curcumin, 2-hydroxypropyl-β-cyclodextrin, inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, xerogels with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, were recorded by the thin transparent tablets technique with potassium bromide of spectroscopic purity, by vacuuming and pressing under a pressure of approximately 200 MPa. The preparation of tablets was measured by 150 mg of potassium bromide and 0.7 mg each sample which were pulverized on an amalgamator (WIG-L-Bug, Dentsply RINN, a Division of Dentsply International Inc., York, PA, USA). Crosslinker EGDM was recorded in the form of a thin film between two plates of zinc selenide (ZnSe). The recording was performed on FTIR spectrophotometer BOMEM MB-100 (Hartmann & Braun, Baptiste, Quebec, QC, Canada) in the wavenumber range of 4000 to 400 cm−1. Spectra were processed by application Win-Bomem Easy software.
## 2.11. Scanning Electron Microscopy (SEM)
The morphology of curcumin, complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, lyophilized p(NiPMAm/NiPAm) hydrogels and p(NiPMAm/NiPAm) hydrogels with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin was examined by scanning electron microscopy. Before analysis, the pulverized sample was coated with gold/palladium alloy ($\frac{15}{85}$) by using a sprayer JEOL Fine Coat JFC 1100E Ion Sputter (JEOL Ltd., Tokyo, Japan) and recorded on apparatus JEOL Scaning Electron Microscope JSM-5300 (JEOL Ltd., Tokyo, Japan).
## 2.12. Differential Scanning Calorimetry (DSC)
For testing the thermal properties of curcumin, 2-hydroxypropyl-β-cyclodextrin, inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, empty p(NiPMAm/NiPAm) hydrogels and hydrogels with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin differential scanning calorimetry method was applied. The sample (about 3 mg) was placed in a vessel and heated in one cycle from room temperature up to 250 °C heating dynamics 10 °C/min in a nitrogen atmosphere. This testing was performed by using apparatus differential scanning calorimeter TA Instruments Q20 (TA Instruments, New Castle, DE, USA).
## 2.13. X-ray Diffraction (XRD)
XRD spectra of curcumin, 2-hydroxypropyl-β-cyclodextrin, inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, empty p(NiPMAm/NiPAm) hydrogels and hydrogels with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin were recorded at these conditions: samples were marked by monochrome CuKα radiation and analyzed at an angle 2θ between 5 and 75° with a sequence of 0.05° and recording time τ = 5 s. During recording, voltage and current used were 40 kV and 20 mA, respectively. All tested samples were recorded by a powder diffractometer Rigaku MiniFlex 600 (Rigaku, Tokyo, Japan).
## 2.14. Nuclear Magnetic Resonance (1H-NMR)
1H-NMR spectra of 2-hydroxypropyl-β-cyclodextrin and of curcumin: 2-hydroxypropyl-β-cyclodextrin inclusion complex were recorded on Bruker Avance III NMR, 400 MHz (BRUKER AXS GmbH, Karlsruche, Deutschland) apparatus in a glass cuvette with a diameter of 5 mm at room temperature by the pulse method, with multiple repetition of pulses. The samples were dissolved in deuterated water (D2O) and the solutions were treated in an ultrasonic bath for 25 min before recording.
## 3.1. Phase Solubility
Phase solubility analysis was performed in order to determine and compare the solvation and complexation power of 2-hydroxypropyl-β-cyclodextrin to curcumin. From Figure 5 it can be seen that phase solubility diagram is of “AL” type [42]. This indicates that the molar ratio between host and guest molecule in the inclusion complex is 1:1, and that the solubility of curcumin is increasing linearly with the increase of 2-hydroxypropyl-β-cyclodextrin concentration. By linear fitting, using the data from Figure 5 the following is obtained: slope = 9.953 × 10−4, intercept = 8.571 × 10−6 mol/dm3. By using the data from Figure 5 for slope and intercept and Equation [1], the value of the stability constant of the curcumin and 2-hydroxypropyl-β-cyclodextrin complex was calculated: K1:1 = 116.23, and solubilization efficiency (ratio of curcumin solubility in water solution in presence of highest tested concentration of 2-hydroxypropyl-β-cyclodextrin, 10 mmol/dm3, and solubility of pure curcumin itself in water) was 1237.18.
## 3.2. The Swelling
Dependence of the degree of swelling on time of p(NiPMAm/NiPAm) of lyophilized hydrogels ($\frac{10}{90}$/2 i $\frac{10}{90}$/3) in solution with pH = 7.4 on different temperatures (25 and 37 °C) is shown in Figure 6a,b, one after the other. From these experiments, the equilibrium values of the degree of swelling for the corresponding gels and temperatures was determined. The dependence of the degree of swelling on temperature is shown in Figure 7, and it can be seen that degree of swelling decreases when temperature increases. There is a phase transition—the lower critical temperature of solution (LCST), at a temperature of approximately 37 °C for this hydrogel composition—when hydrogel transforms from hydrophilic to hydrophobic form. At temperatures above the temperature of phase transition, the breakup of hydrogen bonds with water molecules occurs, the hydrophobic interactions become dominant and the polymer network contracts [47].
That is why this type of hydrogel has a higher degree of swelling at lower temperatures, and this property can be used to enter a larger amount of active substance into the hydrogel structure at lower temperatures. On the contrary, when the temperature increases, these hydrogels have a lower swelling degree. This means that they show a tendency to squeeze some of the liquid out of their structure. Therefore, the concept of this work was to conduct the experiment on the release of curcumin from the hydrogel complex formulation at a temperature of 37 °C, when equilibrium is established in the structure throughout the time of swelling.
In Table 1 the values are shown for kinetic parameters: the constants that are characteristic for certain types of polymer network, diffusion exponents and diffusion coefficients for swelling of p(NiPMAm/NiPAm) hydrogels at 25 and 37 °C with pH 7.4, obtained by the application of Equations [9] and [11].
The transport of solution into the polymeric matrix of p(NiPMAm/NiPAm) hydrogels at a temperature 25 °C and pH 7.4 presents the anomalous type of diffusion (non-Fick’s diffusion), where the value of the diffusion exponent has to be in the range of 0.5 < n < 1. For the tested samples it is in the range 0.60–0.82. At a temperature of 37 °C and pH = 7.4, the swelling process of p(NiPMAm/NiPAm) hydrogels $\frac{10}{90}$/2 is determined by the diffusion of the aqueous solution (“less to Fick’s” diffusion, $$n = 0$.49$ ≈ 0.5), while for the hydrogel sample, $\frac{10}{90}$/3 solvent diffusion into the matrix and the polymer chain relaxation controls the swelling because of the diffusion exponent value 0.63.
## 3.3. Residual Monomers Analysis
By using the HPLC method, the content of unreacted reactants in p(NiPMAm/NiPAm) hydrogels synthesis process was determined, using calibration curves for monomers (NiPMAm and NiPAm) and crosslinker (EGDM). At selected conditions for chromatographic analysis the retention time (Rt) for monomer NiPMAm was 6.693 min, NiPAm 6.176 min and crosslinker EGDM 12.812 min. Residual quantities of monomers in copolymer samples of p(NiPMAm/NiPAm) in relation to their initial quantity in the reaction mixture are shown in Table 2.
Since the toxicity of the residual monomers is limited by their content in the copolymer, and that in the synthesized samples their content is acceptable (<$0.3\%$), synthesized p(NiPMAm/NiPAm) hydrogels can be considered as safe for use as carriers for bioactive substances.
The procedure with variable temperature used for the synthesis of these hydrogels, which was developed through research in the previous period, enables such a low content of residual monomers. This is the minimum amount of residual monomers achieved by the synthesis. Hydrogels can even get rid of these low amounts of residual monomers by extraction with methanol and then washing with water. In this way, a hydrogel without residual monomers will be obtained, which is the most favorable for the production of pharmaceutical formulations.
## 3.4. FTIR Spectroscopy Analysis
Structural analyses of the starting monomers NiPMAm, NiPAm, crosslinker EGDM and synthesized 2 mol% EGDM p(NiPMAm/NiPAm) xerogel were carried out by using the FTIR method (Figure 8). In addition, the structure of the inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, as well as the matrix system, p(NiPMAm/NiPAm) gel in which was incorporated curcumin: 2-hydroxypropyl-β-cyclodextrin inclusion complex were examined by using this method. In Figure 8, FTIR spectra of NiPMAm monomers, comonomers NiPAm, crosslinker EGDM and synthesized p(NiPMAm/NiPAm) xerogel containing 2 mol% of EGDM are shown.
In the FTIR spectrum of NiPMAm monomer (Figure 8a), the absorption band 3291 cm−1 is a result of valence N-H vibrations, ν(N-H). Asymmetric valence vibrations of C-H bond of the vinyl group, νas(=C-H), give an absorption band with a maximum at 3061 cm−1. The absorption bands at 2973 and 2878 cm−1 are from asymmetric and symmetric valence of the methyl group in the NiPMAm monomer structure, respectively. The proof for the presence of the amide group in the monomer structure are absorption bands with maximums at 1653 cm−1 (Amide band I) and 1539 cm−1 (Amide band II). It can be assumed that amide band I is from the valence vibrations of the keto group, while Amide band II arises by coupling of N-H deformation vibrations and valence C-N vibrations. The valence vibrations of C=C bond in FTIR spectrum of NiPMAm monomer (Figure 8a) give an absorption band with a maximum at 1606 cm−1. The absorption band of asymmetric deformative C-H vibration in the plane of CH3-C group in the monomer spectrum is present at 1459 cm−1. The valence vibrations of C-H bond of isopropyl group give an absorption band with a maximum at 1363 cm−1. The presence of the isopropyl group in the monomer structure is also confirmed by the presence of an absorption band at 1157 and 1011 cm−1.
In FTIR spectrum of NiPAm comonomers in the wavelength range of 3000 cm−1 (Figure 8b), two absorption bands with different intensity can be observed. The high intensity absorption band with a maximum at 3295 cm−1 is attributed to valence vibrations of the secondary amino group, ν(N-H) which is in agreement with the research of other authors [48], while the absorption band at 3073 cm−1, is a result of asymmetric vibrations of vinyl group, νas(=C-H). In FTIR spectrum of NiPAm comonomer (Figure 8b), absorption bands with a maximum at 2971 cm−1 and 2876 cm−1 come from asymmetric and symmetric valence vibrations of C-H bond from the methyl group, respectively. The absorption band of medium intensity with a maximum at 2934 cm−1 comes from asymmetric valence vibrations, νas(C-H), of C-H bonds in isopropyl group of NiPAm. The Amide bands I, II and III with a maximum at 1659 cm−1, 1549 cm−1, 1310 cm−1, respectively, confirm the presence of an amide group in the molecule of NIPAM [49]. The valence vibrations of C=C bond in FTIR spectrum of NiPAm monomer (Figure 8b) provides an absorption band with a maximum at 1619 cm−1. The absorption band of medium intensity at 1371 cm−1, relates to deformation vibrations in the plane δ(C-H), of C-H bond in isopropyl group of NiPAm. The high intensity band with a maximum at 1167 cm−1 in the comonomer spectrum also confirms the presence of the isopropyl group in the structure of NiPAm. The appearance of absorption bands which come from deformation vibrations in the plane δ(=C-H), at 1412 cm−1 and deformation vibrations out of the plane γ(=C-H), at 990 and 917 cm−1 confirms the presence of the vinyl group in the structure of the comonomer [49].
In the FTIR spectrum of crosslinker EGDM (Figure 8c), there are absorption bands characteristic for ester and vinyl functional groups present in the molecule. Sharp absorption bands of high intensity with a maximum at 1723 cm−1 in FTIR spectrum of EGDM, comes from valence vibrations of the carbonyl group that is conjugated by a double bond, which is why the medium intensity band that corresponds to the valence vibrations of the C=C bond is noticeable at 1637 cm−1. The valence vibrations of C-O bond give an absorption band with a maximum of absorption at 1154 cm−1. In the FTIR spectrum of crosslinker EGDM, absorption bands with a maximum at 2894 cm−1 from νs(CH3), at 2961 cm−1 from νas(CH3), at 2930 cm−1 from νas(CH2) and at 3106 cm−1 from the vinyl group νas(=CH) are present, which is in accordance with the literature data [39].
By comparing the FTIR spectrum of p(NiPMAm/NiPAm) copolymer with 2 mol% of EGDM (Figure 8d) to the spectrum of NiPMAm monomer (Figure 8a) and NiPAm (Figure 8b), there is a clear difference that indicates the difference in structure between the synthesized polymer and the initial reactants. The shift and absence of some absorption bands from the characteristic functional groups of monomers was observed, which indicates the creation of a new structure. A broad absorption band of high intensity from valence vibrations of the N-H bond in the FTIR spectrum of copolymer at 3442 cm−1 is shifted to higher wavenumbers compared to the same band in the FTIR spectrum of monomer NiPMAm (Figure 8a) and comonomer NiPAm (Figure 8b). The displacement of the centroid of this band indicates the involvement of the amino group in the formation of the hydrogen bond. This fact is supported by displacement of amide band II compared to its placement in the FTIR spectrum of the monomer. An absorption band of the copolymer related to valence vibrations of the C=O group (amide band I) appears at 1649 cm−1 and shifted to lower wavenumbers compared to the absorption band in the FTIR spectra of NiPMAm and NiPAm by 4 and 10 units, respectively. The absorption bands at 1387 and 1367 cm−1 confirm the presence of an isopropyl group in the structure of the copolymer p(NiPMAm/NiPAm) and indicate that this group, that is present in monomers, was not involved in the polymerization process. The absence of an absorption band in the valence vibrations of the C=C bond, and which for monomers appears around wave numbers in the range of 1600–1640 cm−1, clearly indicates that the polymerization reaction of the NiPMAm and NiPAm monomers happened by the breaking of double bonds.
In the FTIR spectrum of curcumin (Figure 9a), a broad absorption band appears at 3421 cm−1 as a result of the valence vibrations of the free phenolic OH group. In the wavenumber range of 2800–3000 cm−1 in the FTIR spectrum of curcumin, two characteristic absorption bands appear with a maximum at 2967 and 2841 cm−1 that come from the asymmetric valence vibrations of the methyl group and the valence vibrations of the methoxy group, respectively [50,51,52]. The presence of an aromatic structure is confirmed by the absorption bands of valence vibrations of the C=C group which appears in the wavenumber range of 1600–1450 cm−1, and in the FTIR spectrum of curcumin are present with a maximum at 1627, 1590, 1512 and 1459 cm−1. In accordance with literature data, the absorption band with a maximum at 1627 cm−1 can be related to valence vibrations of the carbonyl group [53]. The absorption band with a maximum at 1209 cm−1 comes from valence vibrations of the C-O phenolic group, while the absorption band that comes from the C-O-C bond in the FTIR spectrum of curcumin appears at 1031 cm−1 [54]. In the wavenumber range 730–860 cm−1 absorption bands are present which come from deformative vibrations out of the C-H plane of the aromatic ring.
The broad absorption band, with a maximum of absorption at 3465 cm−1 in the FTIR spectrum of 2-hydroxypropyl-β-cyclodextrin (Figure 9b), is a result of valence vibrations of the hydroxyl group from 2-hydroxypropyl-β-cyclodextrin. The absorption bands coming from valence vibrations of C-H bound are appearing in the FTIR spectrum with a maximum at 2928 and 2969 cm−1 [55]. In the FTIR spectrum of 2-hydroxypropyl-β-cyclodextrin, the absorption band with a maximum at 1623 cm−1 comes from O-H deformative vibration in the plane [56]. The asymmetric and symmetric C–H deformative vibrations in the plane give absorption bands at 1458 and 1371 cm−1 in the FTIR spectrum of 2-hydroxypropyl-β-cyclodextrin, respectively. The absorption band at 1155 cm−1 indicates the valence vibrations of the C–C group, while absorption bands with maximums at 1083 and 1037 cm−1 confirm the presence of valence vibrations of the C–O bond at ether and hydroxyl groups of 2-hydroxypropyl-β-cyclodextrin. In the range of 1000–700 cm−1 valence and deformation vibration bands of glucopyranose units appear [57].
By comparative analysis of FTIR spectra of curcumin and 2-hydroxypropyl-β-cyclodextrin with the FTIR spectrum of curcumin: 2-hydroxypropyl-β-cyclodextrin complex (Figure 9c), changes in appearance of FTIR spectra of complex compared to the FTIR spectra of pure substances are noticed. The broad absorption band with the maximum of absorption at 3420 cm−1 in the FTIR spectrum of curcumin: 2-hydroxypropyl-β-cyclodextrin complex (Slika 9c) is shifted to lower wavenumbers by 45 units compared to the position of the same absorption band in the FTIR spectrum of 2-hydroxypropyl-β-cyclodextrin (Slika 9b). In the FTIR spectrum of complex of curcumin: 2-hydroxypropyl-β-cyclodextrin the absence of two characteristic absorption bands with maximums of absorptions at 2967 and 2841 cm−1 that come from asymmetric and symmetric vibrations of methyl group and valence vibrations of methoxy group of curcumin (Figure 9a), respectively, is noticed. The absorption bands that come from C-H valence vibrations with the maximums at 2928 and 2969 cm−1 in the FTIR spectrum of 2-hydroxypropyl-β-cyclodextrin are shifted by 3 units to lower i.e., by 2 units to higher wavelength numbers in the FTIR spectrum of curcumin: 2-hydroxypropyl-β-cyclodextrin (Figure 9c) and appear at 2925 cm−1 and 2971 cm−1, respectively. These changes may indicate the interaction of these groups from 2-hydroxypropyl-β-cyclodextrin with appropriate groups from the molecule of curcumin. The absorption band which comes from C-O-C bond in the FTIR spectrum of curcumin and appears at 1031 cm−1 is not present in the FTIR spectrum of curcumin: 2-hydroxypropyl-β-cyclodextrin complex (Figure 9c). The absorption band of C–O valence vibrations from 2-hydroxypropyl-β-cyclodextrin in the FTIR spectrum of complex is shifted by 2 units to higher wavelength numbers. The absence and shift of some absorption bands in the FTIR spectrum of curcumin: 2-hydroxypropyl-β-cyclodextrin complex indicate the incorporation of curcumin in holes of cyclodextrin, which is in accordance with literature data [58].
By incorporation of curcumin into p(NiPMAm/NiPAm) hydrogels, it is expected that the establishment of intermolecular interactions of the type hydrogen bondage between phenolic OH groups of curcumin as a proton-donor, with oxygen from the C=O group as a proton-acceptor of side chains of p(NiPMAm/NiPAm) copolymer occur. In addition, the C=O group of curcumin can form hydrogen bonds with NH proton donor groups of side chains of p(NiPMAm/NiPAm) hydrogels.
In the FTIR spectrum of p(NiPMAm/NiPAm), hydrogels containing 2 mol% of crosslinker with incorporated curcumin: 2-hydroxypropyl-β-cyclodextrin inclusion complex (Figure 10b), at the wavelength number range of 3500–3200 cm−1 broad absorption band with the maximum at 3430 cm−1 that comes from valence vibrations of N-H bond of hydrogels and valence vibrations of the phenolic OH group of curcumin, can be noticed. The maximum of this band is shifted by 12 units to lower wavelength numbers compared to the position of the same absorption band in the FTIR spectrum of empty hydrogel (Figure 10a), and by 9 units to higher wavelength numbers compared to the position of the absorption band in the FTIR spectrum of curcumin (Figure 9a). This indicates that the mentioned groups are involved in the formation of hydrogen bonds between curcumin molecules and the hydrogel. The amide absorption band I, ν(C=O), appears at 1653 cm−1, while the amide absorption band II, δ(N-H), appears at 1549 cm−1, and their maximums are shifted by 4, that is, 6 units to higher wavelength numbers, compared to the spectrum of hydrogel only (Figure 10a). The maximum of absorption that comes from valence vibrations of C=O in the FTIR spectrum of hydrogels with incorporated curcumin (Figure 10b) is shifted by 26 units to higher wavelength numbers, compared to the position of the same absorption band in the FTIR spectrum of curcumin (Figure 9a). The shiftment of the maximum of amide absorption bands and the decrease in their intensity compared to hydrogel only, indicates the involvement of C=O and –NH groups in the formation of hydrogen bonds. The absorption band that comes from valence vibrations of the C-O-C bond is present with a maximum at 1034 cm−1 and is shifted to higher wavelength numbers by 3 units, compared to the position of the same band in the FTIR spectrum of curcumin. The results of FTIR analysis show that the change in intensity and the shift of the characteristic absorption bands of curcumin and hydrogel to lower or higher values of wavelength numbers happened, which indicates the incorporation of curcumin into the hydrogel structure.
Shifts of the corresponding absorption maxima by several units of cm−1 indicate the formation of weak hydrogen bonds, which is favorable from the aspect of formulation development. This indicates that these weak hydrogen bonds will possibly slow down the diffusion of curcumin molecules from the hydrogel structure, and enable the release of curcumin from the formulation for a longer period of time.
## 3.5. Scanning Electron Microscopy (SEM)
The morphology of curcumin, curcumin: 2-hydroxypropyl-β-cyclodextrin complex, synthesized p(NiPMAm/NiPAm) hydrogel containing 2 mol% crosslinker and p(NiPMAm/NiPAm) hydrogel with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, was examined by SEM method. Hydrogel samples were swollen to equilibrium and then lyophilized in order to better understand their morphology. Obtained SEM micrographs are shown in Figure 11.
In Figure 11a curcumin crystals are clearly visible, while in Figure 11b crystal structure of curcumin: 2-hydroxypropyl-β-cyclodextrin complex cannot be seen. By analyzing the SEM micrographs, a clear difference between the look of the surface structure of the empty hydrogel (Figure 11c) and hydrogel with incorporated curcumin: 2-hydroxypropyl-β-cyclodextrin complex can be observed (Figure 11d). The structure of p(NiPMAm/NiPAm) hydrogel containing 2 mol% EGDM is porous, with a pore diameter in the range of 100 to 300 μm (Figure 11c). In micrography 7d, the presence of curcumin: 2-hydroxypropyl-β-cyclodextrin complex in holes of hydrogel can be seen, whose structure matches the structure of curcumin: 2-hydroxypropyl-β-cyclodextrin complex (Figure 11b). This indicates a successful incorporation of curcumin: 2-hydroxypropyl-β-cyclodextrin inclusion complex into holes of the synthesized p(NiPMAm/NiPAm) gel, and is in accordance with the result obtained by FTIR analysis.
## 3.6. Differential Scanning Calorimetry (DSC)
In Figure 12 are shown DSC curves of curcumin, 2-hydroxypropyl-β-cyclodextrin, curcumin: 2-hydroxypropyl-β-cyclodextrin complex, p(NiPMAm/NiPAm) $\frac{10}{90}$/2 hydrogel and p(NiPMAm/NiPAm) $\frac{10}{90}$/2 hydrogel with incorporated curcumin: 2-hydroxypropyl-β-cyclodextrin complex. In the DSC curve that comes from curcumin (curve 1 in Figure 12) can be seen the endothermic melting peak of curcumin at 188 °C and the peak area correspond to the curcumin melting enthalpy of 171.5 J/g. Considering that curcumin complexation occurred in the presence of 2-hydroxypropyl-β-cyclodextrin, the curcumin molecules in the complex and in the gel complex formulation cannot form curcumin crystals that would give an endothermic melting peak. Nevertheless, in the endothermic peak of the complex, a weak peak is observed at 186 °C, which may indicate that the curcumin molecules have not completely entered the holes of 2-hydroxypropyl-β-cyclodextrin (curve 3 in Figure 12). In the formulation of the complex with gel (curve 2 in Figure 12), the endothermic peak from the melting of curcumin can no longer be observed. This indicates that the supramolecular structures of the complexes are now already distributed in the gel, and that a constant release rate of curcumin could be expected from this formulation of the curcumin complex in the gel.
## 3.7. X-ray Diffraction (XRD)
The XRD spectra of curcumin, 2-hydroxypropyl-β-cyclodextrin, curcumin: 2-hydroxypropyl-β-cyclodextrin complex, synthesized p(NiPMAm/NiPAm) hydrogel containing 2 mol% EGDM and p(NiPMAm/NiPAm) hydrogel with incorporated curcumin: 2-hydroxypropyl-β-cyclodextrin complex are shown in Figure 13.
In the X-ray diffractogram of curcumin (Figure 13a), sharp peaks are present at the values of diffraction angle 2 θ: 7.6; 8.7; 16; 17.5; 21 and 42.55° that indicates that pure curcumin is in crystalline form, which is in agreement with the literature data [22]. Two broad peaks without high maximums that appear in the range of 2 θ = 5–15° and 2 θ = 15–22.5° in diffractogram of 2-hydroxypropyl-β-cyclodextrin (Figure 13b) indicate its amorphous structure [59]. By comparative analysis of diffractograms in Figure 13, it can be observed that in the diffractogram of the inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin (Figure 13c), there are no sharp peaks present in the diffractogram of pure crystalline curcumin. The appearance of new peaks in the diffractogram of the inclusion complex clearly indicates the formation of a new supramolecular structure. Sharp peaks at the values of the diffraction angle 2 θ: 7, 13.5, 16, 19 and 27° in diffractogram of the curcumin: 2-hydroxypropyl-β-cyclodextrin complex indicate that the curcumin molecule did not completely enter into the hole of the 2-hydroxypropyl-β-cyclodextrin from inclusion complex. This is understandable, since one molecule of curcumin requires two molecules of 2-hydroxypropyl-β-cyclodextrin to be completely included in the cavities of 2-hydroxypropyl-β-cyclodextrin [24]. However, that was not necessary in this case because the further homogenization was carried over by the gel. By comparative analysis of the diffractogram of the empty hydrogel and the hydrogel with incorporated complex of curcumin: 2-hydroxypropyl-β-cyclodextrin (Figure 13d and e, respectively), great similarity was observed considering the shape and position of the peaks that appear as broad in the range of 2 θ = 5–10 and 2 θ = 15–32.5, and they correspond to the peaks that appear in the diffractogram of the empty hydrogel. This indicates that the structure of the hydrogel after incorporation of the inclusion complex did not significantly change, and that the complex of curcumin: 2-hydroxypropyl-β-cyclodextrin was relatively uniformly distributed into the gel.
## 3.8. Nuclear Magnetic Resonance (1H-NMR)
In Figure 14 are shown 1H-NMR spectra of 2-hydroxypropyl-β-cyclodextrin and the complex of curcumin: 2-hydroxypropyl-β-cyclodextrin. In Table 3 are shown values for chemical shifts of 2-hydroxypropyl-β-cyclodextrin and the complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, and the change in chemical shifts of protons which originate from 2-hydroxypropyl-β-cyclodextrin in the complex. Considering that the solubility of curcumin in water is very weak, the analysis is aimed at monitoring the chemical shifts of protons from 2-hydroxypropyl-β-cyclodextrin. The changes in chemical shifts of protons Δδ which are shown in Table 3, indicate the formation of weak hydrogen bonds in which protons from 2-hydroxypropyl-β-cyclodextrin are involved which indicates the possible inclusion and creation of the inclusion complex.
## 3.9. The Loading Efficiency of Curcumin into the p(NiPMAm/NiPAm) Hydrogel
By knowing that curcumin does not dissolve in aqueous media, the incorporation of curcumin into the hydrogel was accomplished by incorporating the curcumin: 2-hydroxypropyl-β-cyclodextrin complex into samples of hydrogels. The efficiency of curcumin incorporation, η, was calculated according to Equation [2], in terms of the total starting mass of curcumin available in the complex. The data are shown in Table 4.
The efficiency of curcumin incorporation into the inclusion complex of p(NiPMAm/NiPAm) $\frac{10}{90}$/2 xerogel is greater than for $\frac{10}{90}$/3, that is in agreement with the results for the swelling for synthesized gels. These values are satisfying considering that the water solubility of curcumin is very low. By complexation with 2-hydroxypropyl-β-cyclodextrin, its water solubility is increased 1237 times, and this provides easier incorporation into synthesized hydrogels as well as a release in physiological mediums.
## 3.10. In Vitro Release of Curcumin from p(NiPMAm/NiPAm) Gels
The release of curcumin from p(NiPMAm/NiPAm) gels containing 2 and 3 mol% of EGDM was monitored under in vitro conditions at temperature 37 °C and pH 7.4, that simulate the body temperature and pH conditions as in the small intestine, by applying the HPLC method (Figure 15). The release of curcumin from the gels was monitored during 48 h.
The release rate of curcumin from p(NiPMAm/NiPAm) hydrogels containing 2 mol% of EGDM is 13.13 µg/h, and for hydrogels containing 3 mol% of EGDM it is 2.51 µg/h, which provides a prolonged release of curcumin during 366.5 h (15.27 days) and 1653.6 h (68.9 days), respectively. In Figure 15a it can be seen that there is also an initial release of curcumin in an amount of approximately 1600 µg from the formulation of sample $\frac{10}{90}$/2, and approximately 500 µg from the formulation of sample $\frac{10}{90}$/3 (Figure 15b). The results obtained indicate the possibility that thermosensitive p(NiPMAm/NiPAm) hydrogels could find application in the development of formulations with the prolonged release of curcumin. These results shows that there is a possibility of tailoring the formulation in terms of the amount of curcumin that should be incorporated into the gel through the complex, for tailoring the time and rate of curcumin release from this formulation as well as the intensity of the initial release; for example, by changing the crosslinker concentration. The amount of crosslinker for synthesis of gel will determine the density of the nodes in the network and the length of the branches in the gel network, that will affect the diffusion of curcumin molecules through the mass of gel. In a polymer network created with a higher concentration of crosslinker, the branches will be shorter and the concentration of nodes will be higher, and like this the diffusion of curcumin molecules will slow down. Analysis of the release mechanism of curcumin from the formulation of the complex in gel can be helpful for this purpose.
With the aim to further study the curcumin release mechanism from p(NiPMAm/NiPAm), hydrogels with the incorporated inclusion complex of curcumin: 2-hydroxypropyl-β-cyclodextrin, the experimental data obtained in this work are fitted by appropriate mathematical models: Higuchi, Korsmeyer–Peppes and Baker–Lonsdale, and the obtained parameters are shown in Table 5.
The highest coefficient of determination (R2) and the lowest AIC indicate that Korsmeyer-Peppes’s model best describes the release of curcumin from the formulation of p(NiPMAm/NiPAm) hydrogels containing curcumin: 2-hydroxypropyl-β-cyclodextrin complex. The value for the diffusion exponent of the hydrogel sample p(NiPMAm/NiPAm) containing 2 mol% EGDM is 0.074, but 0.063 for the sample of p(NiPMAm/NiPAm) hydrogel containing 3 mol% of EGDM, and that shows that the release mechanism of curcumin, is based on diffusion from the polymer matrix of the gels. This definitely confirms the conclusion that the right choice on the crosslinker concentration to be used for the synthesis process of p(NiPMAm/NiPAm) hydrogels can have an influence on the release rate of curcumin from the gel formulation with curcumin: 2-hydroxypropyl-β-cyclodextrin complex. The form of curcumin: 2-hydroxypropyl-β-cyclodextrin complex was applied to provide a larger amount of curcumin into the gel.
If the overall results are considered, it can be concluded that a system for the sustained release of curcumin from a formulation base on hydrogel has been developed. This was achieved primarily by increasing solubility by including curcumin to 2-hydroxypropyl-β-cyclodextrin, which enabled the required amount of curcumin to enter into the hydrogel. Incorporation of pure curcumin into the hydrogel would create curcumin agglomerates in the formulation, while the cyclodextrin complex enabled individual curcumin molecules to diffuse through the gel. By that, the entire formulation significantly contributed to increasing the solubility of curcumin.
## 4. Conclusions
In this work, the synthesis and characterization of p(NiPMAm/NiPAm) hydrogels with two different concentrations of crosslinker was done. The results show that less than $0.3\%$ of residual monomers is present in synthesized hydrogels. The FTIR analysis of reactants at the beginning of the synthesis, synthesized hydrogels, curcumin: 2-hydroxypropyl-β-cyclodextrin complex and the formulation of hydrogel with complex of curcumin: 2-hydroxypropyl-β-cyclodextrin showed that the complexation and formulation of complexes with the gel were done by the help of hydrogen bonds formation. The water swelling process is controlled by the mechanisms called “non-Fick’s diffusion“ and “less to Fick’s diffusion“. The phase solubility of curcumin in solution of 2-hydroxypropyl-β-cyclodextrin showed increased solubility by 1237 times. The SEM analysis showed the loss of the crystal structure of curcumin in the complex and in the formulation of the complex with gel, which was additionally confirmed by DSC and XRD analyses. Since the water solubility of curcumin is low (3 mg/dm3), the complexation with 2-hydroxypropyl-β-cyclodextrinthe made incorporation of curcumin into hydrogels easier by increasing the solubility. The monitoring of the curcumin release profile from the formulation of curcumin: 2-hydroxypropyl-β-cyclodextrin complex with p(NiPMAm/NiPAm) hydrogels, shows the starting release of curcumin from the formulation that slows with the increasement of crosslinker in the composition of the reaction mixture for hydrogel synthesis. In addition, with an increase in the concentration of the crosslinker, the release rate of curcumin from the formulation also decreases, which gives the possibility of tailoring the release rate from the formulation. The release rate of curcumin from the formulation of the complex with gel is constant in the function of time, and is dependent on the amount of curcumin in the formulation and the release rate. This is a formulation from which the curcumin will be released over a longer period of time can be designed, more than over 60 days. The kinetic analysis of data for curcumin release from the formulation of curcumin-gel complex showed that the mechanism of curcumin release is based on diffusion from the polymer matrix of the gels.
## 5. Patents
Patent Application RS2022P0287, Urošević, M.; Nikolić, Lj.; Gajić, I.; Nikolić, V.; Dinić, A.; Ilić-Stojanović, S.; Miljković, V.; Nikolić, G.; Cakić, S. Formulation of the matrix system with curcumine, Priority 17 Mart 2022, the Intellectual Property Office of the Republic of Serbia.
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|
---
title: 'Endocrine Disruption of Propylparaben in the Male Mosquitofish (Gambusia affinis):
Tissue Injuries and Abnormal Gene Expressions of Hypothalamic-Pituitary-Gonadal-Liver
Axis'
authors:
- Yun Ma
- Yujing Li
- Xiaohong Song
- Tao Yang
- Haiqin Wang
- Yanpeng Liang
- Liangliang Huang
- Honghu Zeng
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967665
doi: 10.3390/ijerph20043557
license: CC BY 4.0
---
# Endocrine Disruption of Propylparaben in the Male Mosquitofish (Gambusia affinis): Tissue Injuries and Abnormal Gene Expressions of Hypothalamic-Pituitary-Gonadal-Liver Axis
## Abstract
Propylparaben (PrP) is a widely used preservative that is constantly detected in aquatic environments and poses a potential threat to aquatic ecosystems. In the present work, adult male mosquitofish were acutely (4d) and chronically (32d) exposed to environmentally and humanly realistic concentrations of PrP (0, 0.15, 6.00 and 240 μg/L), aimed to investigate the toxic effects, endocrine disruption and possible mechanisms of PrP. Histological analysis showed time- and dose-dependent manners in the morphological injuries of brain, liver and testes. Histopathological alterations in the liver were found in 4d and severe damage was identified in 32d, including hepatic sinus dilatation, cytoplasmic vacuolation, cytolysis and nuclear aggregation. Tissue impairments in the brain and testes were detected in 32d; cell cavitation, cytomorphosis and blurred cell boundaries appeared in the brain, while the testes lesions contained spermatogenic cell lesion, decreased mature seminal vesicle, sperm cells gathering, seminiferous tubules disorder and dilated intercellular space. Furthermore, delayed spermatogenesis had occurred. The transcriptional changes of 19 genes along the hypothalamus–pituitary–gonadal–liver (HPGL) axis were investigated across the three organs. The disrupted expression of genes such as Ers, Ars, Vtgs, cyp19a, star, hsd3b, hsd17b3 and shh indicated the possible abnormal steroidogenesis, estrogenic or antiandrogen effects of PrP. Overall, the present results provided evidences for the toxigenicity and endocrine disruptive effects on the male mosquitofish of chronic PrP exposure, which highlights the need for more investigations of its potential health risks.
## 1. Introduction
Parabens are a group of alkyl esters widely used as ideal preservatives in cosmetics, food and pharmaceuticals since the mid-1920s, due to their excellent antiseptic, antimicrobial and antifungal properties [1]. Parabens are divided into several categories depending on the length of the ester chain, with alkyl substituents ranging from methyl to butyl or benzyl groups [2,3]. These compounds penetrate the environment during production, use and sewage treatment. Parabens are frequently found in tap water, bottled water, rivers, lakes, drinking water and waste water at concentrations from ng/L to μg/L [4,5,6] and have even been detected in aquatic animals [3,7]. According to the assessment of acute and chronic toxic exposure to parabens, they have been classified as emerging contaminants with the capability of endocrine disruption [8,9]. The potential risks of parabens to the environment and to humans have attracted considerable concern and resulted in the “paraben free” campaign [2].
Propylparaben (PrP), with the chemical name Propyl 4-hydroxybenzoate and 4-Hydroxybenzoic acid propyl ester, is one of the most commonly used parabens. The Scientific Committee on Consumer Safety (SCCS) suggested that propylparaben is safe for humans when used as a preservative in cosmetic products (up to a maximum concentration of $0.14\%$) [10]. While high values of PrP have been reported in human urine samples with a mean concentration at 34.9 μg/L (ND-462 μg/L) [11]. Moreover, PrP was also found in human blood (<0.01–12.1 μg/L) [12], breast milk (ND-0.6 μg/L) [13], maternal urine (0.23–12.44 μg/L) [14,15], urine of newborn infants (0.44–16.9 μg/L) [16], plasma (median: 19.22 μg/L) and amniotic fluid (median: 18.82 μg/L) of pregnant women [17], indicating that the ubiquitous PrP may adversely affect human health and even the developing fetus in the uterus.
PrP is also frequently detected in the aquatic environment, for instance, ND-217 μg/L in the groundwater, ND-229 μg/L in the surface water [8,18,19,20], ND-480 ng/L in source water, ND-590 ng/L in drinking water [21], 23 ng/L in mineral water and 9 ng/L in tap water [6]. It is noteworthy that PrP has the possibility of bioaccumulation in nontarget aquatic organisms, since it had been absorbed by wild fish (0–4.58 μg/kg ww in the muscle, 0–6.72 μg/kg ww in the liver, 0–8.38 μg/L in the plasma) [7,22], so the toxicity of PrP to aquatic organisms can not be ignored.
Previous reports indicated that PrP possesses endocrine interference [23], reproductive toxicity and developmental abnormality [24,25,26] to aquatic organisms. The adverse effects of PrP on the early development of zebrafish was manifested by abnormal changes in hatching rate, heart rate, survival, non-lethal malformations and anxiety-like behavior; these developmental toxicities were associated with increased oxidative stress indices and upregulated expression of apoptotic cells in a dose-dependent manner in the head of zebrafish larvae [27]. It was confirmed that PrP affected the genes from physiological pathways in the 120 dpf zebrafish, including stress response, cell cycle, DNA damage, inflammation, fatty acid metabolism and endocrine functions, and PrP showed an antiandrogenic and estrogenic activity [28]. In the 20 dpf juvenile zebrafish, 45 days of PrP exposure seemed to influence the sex differentiation processes, as the sex ratio significantly skewed towards females [29]. Similarly, the female ratio of the marine copepod (Tigriopus japonicus) was increased by 50 μg/L PrP exposure during the development, and males showed higher sensitivity compared to females in the acute toxicity assessment, indicating that PrP had a feminization effect [30].
Both in vitro and in vivo studies suggested that PrP affect estrogenic or antiandrogenic activity, disturb adipogenesis and steroidal sex hormonal homeostasis [31,32]. PrP exposure could activate estrogen-related pathways, for example, 20 nM (3.6 μg/L) PrP stimulated both the mRNA (24 h exposure) and protein (48 h exposure) expression of the progesterone receptor (PGR), estrogen receptor ERα and Erβ in MCF-7 breast cancer cells [33]. In silico molecular docking analyses showed that PrP and other parabens fitted well into the active site of human estrogen receptor ERγ, with hydrogen bonds forming between the p-hydroxyl group of parabens and the Glu275/Arg316 of ERγ, and these parabens showed inverse antagonist activities on ERγ, with a lowest observed effect level (LOEL) of 10−7 M (18 ng/L) [34]. PrP exhibited significant and concentration-dependent antiandrogenic activity via a yeast-based human androgen receptor assay [35]. Oral doses of PrP had antiandrogenic activity on immature male rats by the supported results of decreased accessory sex organ weights, increasing LH levels and histopathologic changes such as atrophy, hyalinization and anastomosis in androgenic tissues [36]. In addition, PrP disturbed steroid hormones balance by suppressing the serum testosterone level of adult male rats, with a concomitant increase in serum estradiol and an ultimate decrease in testosterone/estradiol ratio [37].
Numerous studies have investigated the endocrine disruption properties of PrP on aquatic organisms, whereas current available information is insufficient. The time- and dose-dependent manner of the potential endocrine effects, and the response of different endocrine related tissues to PrP are not clearly understood; more data are need to elucidate the underlying mechanism. The hypothalamic–pituitary–gonadal–liver (HPGL) axis is a dynamic endocrine system. It maintains the physiological state of reproduction during chemical exposure through various steady-state feedback mechanisms [38]. This axis is associated with gonadotropins release in the hypothalamus and pituitary, yolk protein precursor vitellogenin (VTG) production in the liver, and cholesterol transport and steroidogenesis in gonads of fish [39]. Gene expression changes in the HPGL axis with PrP exposure may reflect disrupted endocrine systems and reproduction of fish; thus, systematic monitoring of genes along the HPGL axis will provide further insights into the reproductive toxicity of PrP.
In this study, the widely distributed mosquitofish (Gambusia affinis) was employed as the indicator, and the male fish were exposed to different concentrations of PrP (0, 0.15, 6 and 240 μg/L) for 4 and 32 days, which simulated acute and chronic exposure conditions, respectively. Routine tissue sections (brain, liver and testes) were performed to determine the effects of PrP on the tissues and spermatogenesis in mosquitofish. *Related* gene expressions in the hypothalamic–pituitary–gonadal–liver (HPGL) axis signaling pathway of corresponding tissues were also investigated to better characterize the acutely and chronically adverse outcomes of PrP on the male mosquitofish.
## 2.1. Fish Care
The mosquitofish were purchased from a local aquaculture farm in Guilin City, China. The fish were domesticated in the aquatic culture system under standard procedures for 14 d, with a pH of 7.1–7.4, a dissolved oxygen ≥5 mg/L, a water temperature of (25 ± 1) °C, and a constant light–dark photoperiod of $\frac{14}{10}$ h. They were fed twice a day with commercial fodder and brine shrimp. All animal procedures in this study were conducted based on the guidelines of the Organization for Economic Cooperation and Development (OECD), specifically, the OECD guideline for the testing of chemicals—fish short term reproduction assay (OECD 229), with minor modifications [40]. The experiment was approved by the Animals Ethics Committee of the Guilin University of Technology and the operations were carried out in accordance with the relevant regulations.
## 2.2. PrP Exposure
Propylparaben (PrP, CAS: 94-13-3, purity ≥ $99.0\%$) was purchased from Xilong Science Co., Ltd. (Guangdong, China). The PrP stock solution was dissolved in Dimethyl Sulphoxide (DMSO), and the concentration of DMSO in the exposure solution and control group was kept with $0.05\%$ (V:V). According to the 96h-LC50 of PrP in mosquitofish (9.14 mg/L based on our previous experiment), environmental levels, and humanly realistic concentrations, four different nominal PrP treatment groups (0, 0.15, 6 and 240 μg/L) (40-fold gradient) were designed with four replicates. These concentrations corresponded to the PrP concentration in the river water (145 ng/L) [6] and surface water (ND-229 μg/L) [8]. The 240 μg/L PrP (about $\frac{1}{40}$ 96h-LC50) represented the highest concentration in the aquatic environment and the median concentration in human fluids (ND-462 μg/L) [11]. Tap water was aerated for more than 48 h and used as diluent of the PrP stock solution in the exposure experiment. The temperature, pH and dissolved oxygen of the exposure solution were monitored daily, and the exposure conditions were maintained to be the same as those of the domestication stage.
A total of 384 healthy male mosquitofish with average lengths of (2.07 ± 0.28) cm and weights of (0.12 ± 0.05) g were selected for the PrP exposure experiment. In each replicated group, 12 male mosquitofish were randomly assigned into a 2 L glass beaker, which was filled with 2 L exposure solution. The exposure period lasted for 32 d and the survival of the tested fish was recorded daily.
Based on the semi-static water change method, $\frac{1}{2}$ of the exposure solution was changed every day. The fish were fed twice with commercial fodder and brine shrimp, the residual bait and excrement was fixed and sucked out in time, and the survival of male mosquitofish was recorded daily.
## 2.3. Sample Collection
PrP in the aquatic environment may occur intermittently due to seasonal changes, variable industrial and agricultural activities, thus, aquatic organisms may be affected by periodic peak exposure and chronic exposure. The fish of each concentration and control group were sampled at 4 d (acute exposure) and 32 d (chronic exposure). After being euthanized with MS-222, the brain, liver and testes of male mosquitofish were quickly removed on ice under a microscope. In each glass beaker (4 per concentrations), tissues of three fish were placed in the RNA preservation solution (TaKaRa, Shiga, Japan) and stored at −20 °C for the extraction of total RNA ($$n = 12$$ fish in total for each time-point and each PrP concentration). Additionally, tissues of another five fish were immediately fixed in $10\%$ neutral buffered formalin and stored at room temperature for the pathological sections ($$n = 20$$ fish in total for each time-point and each PrP concentration).
## 2.4. Tissue Sections and HE Staining
The brain, liver and testes samples of the control and PrP groups were processed for tissue sections and HE staining. Briefly, the samples were dehydrated, fixed in paraffin, sectioned, mounted on glass slides, dried and HE stained. In the HE staining, the samples were fixed with methanol for 10 min, water flushed for 2 min, hematoxylin stained for 2.5 min, water rinsed for 10 min, alcohol hydrochloride differentiated for 2 s, water rinsed for 10 min, eosin stained for 30 s, $70\%$ ethanol washed for 10 s (twice), $80\%$ ethanol washed for 10 s (twice), $90\%$ ethanol washed for 10 s (twice), absolute ethanol rinsed for 10 s and xylene transparented for 10 min. The sections of fish from each group were observed and captured on the 40× objective using the microscope (Nikon ECLIPSE Ti).
The histological analysis of the brain, hepatocytes and testes were performed according to the method described in our previous research [41]. Briefly, the brain structures were identified according to Ullmann [42] and Simões [43]. The identification of hepatocyte lesions was conducted as described by Macêdo [44] and Agamy [45]. The testes structure of mosquitofish were identified according to Leusch [46]. Adult male sperm nests of the mosquitofish contain germ cells at different stages of development, namely, the primary spermatogonium (S1), secondary spermatogonium (S2), primary spermatocyte (S3), second spermatocyte (S4) and spermatozeugmata (Sz). The proportions of germ cells at different developmental stages were analyzed in 100 cells of each fish ($$n = 20$$).
The slides of the brain, liver and testes samples were scored semi-quantitatively and classified into four groups based on the average number of each lesion [47,48]. The groups were divided as follows: none or occasional: − (no lesion or 1–2 lesions), mild: + (3–5 lesions), moderate: ++ (6–8 lesions) and severe: +++ (≥9 lesions) [49].
## 2.5. RNA Extraction and qPCR
Total RNA from each sample was isolated using the Trizol reagent kit (TaKaRa, Japan) referring to the manufacturer’s instructions, and RNA quality was determined using a Quawell Q5000 spectrophotometer. The reverse transcription of the total RNA was performed using the PrimeScript reagent Kit with gDNA Eraser (TaKaRa, Japan). A total of 19 target genes related to the hypothalamic–pituitary–gonadal–liver axis were selected to detect the mRNA expression in different samples, including the estrogen receptor genes (erα and erβ), androgen receptor genes (arα and arβ) [50], vitellogenin genes (vtgB and vtgC), cytochrome P450 genes (cyp19a, cyp19a1a, cyp19a1b, cyp11a1), steroid 17-alpha-hydroxylase/17,20 lyase (cyp17), gonadotropin releasing hormone (gnrh), gonadotropin releasing hormone receptor (gnrhr), hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroid delta-isomerase cluster (hsd3b), hydroxysteroid 17-beta dehydrogenase 3 (hsd17b3), 20β-hydroxysteroid dehydrogenase type (hsd20b), sonic hedgehog (shh), patched 1 (ptc1) as well as the steroidogenic acute regulatory protein (star) [51,52]. The glyceraldehyde-3-phosphate dehydrogenase gene (gapdh) was served as the endogenous reference gene [53]. The qPCR specific primers are illustrated in Supplementary Material (Table S1).
The real-time PCR experiment was carried out using QuantStudio 3 equipment (Applied Biosystems, Waltham, MA, USA) with PowerUp SYBR Green Master Mix kits (Applied Biosystems). Each qPCR reaction was conducted in triplicate, and each plate included a negative control. According to the operating instructions, the PCR reaction system included 10 μL of PowerUp SYBR Green Master Mix, 2 μL of cDNA template, 1 μL of upstream and downstream primers (10 μmol/L) and 6 μL of ultrapure water. The reaction procedure was set as 95 °C, 30 s; 40 cycles (95 °C, 5 s; 55 °C, 30 s); melting curves: 95 °C, 10 s; 65 °C, 5 s; 95 °C, 0.50 s. The mRNA expression of the target genes were analyzed using the 2-∆∆Ct method [54].
## 2.6. Statistical Analysis and Cluster Heat Map Analysis
The results are presented as the mean ± SEM (standard error of the mean), and data processing and plotting were performed using Graphpad 8.3.0 software. Cluster analysis of all the genes in the three organs were performed to visualize the gene expression patterns across different PrP stressors, using the Origin software with Heat Map with Dendrogram v2.00 tool. The differences in mRNA expressions between the control group and the treatment groups were analyzed by t-test and one-way ANOVA (Tukey’s multiple comparison). The statistical significance is considered when $p \leq 0.05$ and indicated by asterisks (* $p \leq 0.05$; ** $p \leq 0.01$).
## 3. Results
No deaths occurred in the male mosquitofish from various treatment groups (0, 0.15, 6 and 240 μg/L) during the 32d PrP exposure, indicating that the chemicals tested at the concentrations in the present study were not acutely toxic.
## 3.1.1. Brain Histopathology
In the brain sections, the structures of stratum marginale (SM), stratum centrale (SC) and stratum periventricular tecti optici (PGZ) were shown in Figure 1A–D. The stratum marginale was formed by nerve fibers and a few neurons, the stratum centrale contained more nerve cells, and the periglomerular gray zone (PGZ) contained dense neurons.
After PrP exposure for 4d and 32d, the histological sections showed that the brain tissue in the control group had clear stratification and tight cells (Table 1, Figure 1A,C). The brain damage got worse gradually, following the increase of PrP concentrations and exposure duration. In the 240 μg/L PrP group of 4d and all PrP groups of 32d, severe pathological changes were observed in the brain, including cell cavities, cytomorphosis and blurred cell boundaries (Table 1, Figure 1B,D).
## 3.1.2. Gene Expression Changes of HPGL Axis in the Brain
After PrP exposure for 4 d, the relative expressions of endocrine-related genes (erα, erβ, arα, arβ, gnrh, gnrhr and cyp19a1b) in the brains of all PrP treatment groups (0.15, 6, and 240 μg/L) had no significant difference from that of the control group ($p \leq 0.05$) (Figure 1E). However, when the PrP exposure was extended to 32 d, the gene transcriptions in the PrP groups displayed in a parabolic path, the transcriptional levels increased in the 0.15 μg/L PrP group and declined in the 240 μg/L PrP group (Figure 1F). The expressions of all the target genes in the 240 μg/L PrP group were significantly lower than that of the control group and the 0.15 μg/L PrP group ($p \leq 0.05$) (except the cyp19a1b gene, $p \leq 0.08$).
## 3.2.1. Liver Histopathology
The histological sections showed that the hepatocytes in the control group were polygonal with clear intercellular boundaries and arranged orderly, round nuclei in uniform sizes were distributed in the center of the cells (Figure 2A,C). PrP induced morphological injuries to hepatocytes in a time- and dose-dependent manner (Table 1, Figure 2B,D), with the prolongation of exposure time and increase concentrations of PrP, the histological injuries in the liver were more severe. Mild and moderate liver injuries were found in the PrP groups (0.15, 6 and 240 μg/L) after PrP exposure for 4 d, mainly including hepatic sinus dilation and cytoplasmic vacuolation. The hepatocellular damage increased in severity after PrP exposure for 32 d, the most common lesions contained hepatic sinus dilation or hyperemia, cytoplasmic vacuoles, nuclear aggregation, cytolysis and partial cell necrosis.
## 3.2.2. Gene Expression Changes of HPGL Axis in the Liver
In comparison with the control fish, the mRNA expressions of erα, erβ, arα, arβ, vtgB, vtgC and cyp19a in the liver were both notably up-regulated after exposure to PrP (0.15, 6 and 240 μg/L) for 4 d ($p \leq 0.01$ for each case) (Figure 2E). Furthermore, 0.15 μg/L PrP resulted in marked improvement of the star gene ($p \leq 0.01$), and the star transcription in the 6 and 240 μg/L PrP groups still kept in a rising trend even though there were no significant alterations ($p \leq 0.08$). In the 32d PrP treatment cases, all the genes were not affected except the erβ and cyp19a (Figure 2F). The expressions of erβ and cyp19a in the 6 μg/L and 240 μg/L PrP groups were significantly higher than that of the control group ($p \leq 0.05$).
## 3.3.1. Testes Histopathology and Morphometry
The testicular development of adult mosquitofish was asynchronous, the testes from all groups contained five kinds of spermatocysts at different developmental stages (S1, S2, S3, S4 and Sz) (Figure 3). In the control group, germ cells at various stages were observed, which were well developed, neatly arranged and in equal sizes (Figure 3A,E). After PrP exposure for 4d, no visible morphological differentiation was found between the control and PrP groups (Figure 3B–D). When the PrP exposure was extended to 32d, the testes seemed to be fragile and disorganized, the tissue damage contained spermatogenic cell lesion, decreased mature seminal vesicle, sperm cells gathering, seminiferous tubules disorder and dilated intercellular space (Table 1, Figure 3F–H).
The proportion of germ cells at different developmental stages were analyzed in 100 cells of each fish. The statistical results showed that when exposed to PrP for 4 d and 32 d, there was no significant difference in the proportion of different sperm cells between the control and PrP treatment groups ($p \leq 0.05$) (Figure 3I). However, the ratio of mature sperms (Sz) ($60.9\%$) in the 32 d- 240 μg/L PrP group decreased significantly compared to that of 4 d- 240 μg/L PrP group ($72.3\%$), contrarily, the percentage of primary spermatocyte (S3) in the 32 d- 240 μg/L PrP group ($9.1\%$) was higher than that of 4 d ($4.92\%$), which indicated that PrP may induce a delayed spermatogenesis.
## 3.3.2. Gene Expression Changes of HPGL Axis in the Testes
There were no significant changes in 15 endocrine-related genes (erα, erβ, arα, arβ, vtgB, vtgC, star, cyp19ala, cyp11a1, ptc1, hsd3b, cyp17, hsd17b3, hsd20b and shh) in all treatments (0.15, 6 and 240 μg/L) ($p \leq 0.05$) after PrP exposure for 4d (Figure 4A,B). In the 32d PrP treated fish, the expressions of vtgC gene in the 0.15 μg/L PrP group, hsd20b gene in the 6 μg/L PrP group, as well as erβ gene in the 240 μg/L PrP group were all stimulated ($p \leq 0.05$). The star transcription in all the PrP groups raised sharply ($p \leq 0.05$). Increased expressions of hsd17b3 and shh were all observed in the 6 and 240 μg/L PrP groups ($p \leq 0.05$). In the condition of hsd3b gene, the gene was down-regulated in the 0.15 μg/L PrP group ($p \leq 0.05$) while up-regulated in the 240 μg/L PrP group ($p \leq 0.01$) (Figure 4C,D).
## 3.4. Cluster Heat Map Analysis of HPGL Axis Related Genes in the Male Mosquitofish
In the heat maps, the gene expression data is displayed in a grid where each row represents a gene and each column represents a PrP group. The color and intensity of the boxes represent the gene expression changes. As shown in Figure 5A, the expressions of endocrine-related genes were roughly divided into two categories: upregulation and unaffected. After suffering from different concentrations of PrP for 4d, heatmap analysis revealed that the genes of the three organs (the brain, liver and testes) in the 0.15 μg/L PrP treatment were clustered close to the 6 μg/L PrP treatment, these groups then clustered with the 240 μg/L PrP treatment, all the PrP groups were away from the control group, which indicated that the genes in these treatments shared similar expression patterns. Most of the target genes in the liver with higher expression were clustered on the top, including the cyp19a, vtgB, vtgC, arβ, arα, erβ, erα and star orderly.
While in the 32d PrP exposure experiments, the genes of the three organs in the 0.15 μg/L PrP treatment were clustered close to the control group, and the genes in the 6 μg/L PrP treatment were clustered together with the 240 μg/L PrP treatment (Figure 5B), which indicated a cumulative effect of exposure time and dose. Most of the target genes in the brain were aggregated at the bottom, the expression of shh, star, hsd17b3, hsd20b and vtgC in the testes were gathered on the top.
## 3.5. The Time and Dose Dependent Manner of HPGL Axis Related Genes in the Male Mosquitofish
As shown in Figure S1, endocrine-related genes (erα, erβ, arα, arβ, gnrh, gnrhr and cyp19a1b) in the brain of the male mosquitofish showed a similar down-regulation expression trend with 4d and 32d PrP treatment at different concentrations. No significant difference was found among all the genes at the two time points with the same concentrations ($p \leq 0.05$).
Interestingly, the expression trends of erα, erβ, arα, arβ, vtgB, vtgC, star, and cyp19a in the liver of the 4d-PrP treatments were all up-regulated and higher than that of the 32d-PrP groups (Figure S2). Among these genes, the expressions of erα, erβ, arα, arβ and cyp19a in all the PrP groups at the two time points were significantly different ($p \leq 0.05$). In the 6 and 240 μg/L PrP groups, there was a significant difference between the expression of vtgB and vtgC with different exposure durations (4d and 32d) ($p \leq 0.05$). Besides, the mRNA level of the star gene in the 0.15 μg/L PrP group varied significantly due to different exposure times ($p \leq 0.05$).
In the testes, the changes of the expression trend were complicated (Figure S3), which indicated that the genes response in the testes were controlled by multiple factors. Statistics analysis showed that some of the tested genes were significantly expressed ($p \leq 0.05$) with different exposure times, i.e., hsd20b at 0.15 μg/L PrP group, shh and star at 6 μg/L PrP group, star and hsd17b3 at 240 μg/L PrP group. Among these genes, the star gene in the 32d-PrP treatments were up-regulated and higher than that of the 4d-PrP groups (6 and 240 μg/L PrP).
## 4.1. PrP Induced Injuries in the Brain, Liver and Testes of Male Mosquitofish
In this study, microstructure observation in the three tissues displayed the overt toxicity of PrP, the mRNA changes of genes along the HPGL axis revealed the cryptic endocrine disruption on the reproductive systems.
The susceptibility to PrP of three target organs in mosquitofish revealed a time-dose response relationship, with the prolongation of exposure time and increase concentrations of PrP, the histological injuries in the brain, liver and testes were more severe. The visible hepatocellular damage occurred in the acute PrP exposure (4d), whereas the lesions in the brain and testes were observed until 32d. Congruously, the transcriptional abnormalities of HPGL axis-related genes in the brain and testes were detected at 32d. While the HPGL axis-related genes tested in the liver were all increased significantly at 4d, only two genes (erβ and cyp19a) were significantly changed at 32d. Moreover, the expression trends in the liver of the 4d-PrP treatments were all up-regulated and higher than that of the 32d-PrP groups. Thus, the liver was more sensitive to the acute toxicity of PrP, and it seemed to have an adaption of the endocrine dysfunction in the liver. The PrP effects on the brain and testes were not able to be observed immediately, but did occur in the chronic exposure. Therefore, the long-term presence of PrP in the water will threaten the health of aquatic animals, even at low environmental levels.
Parabens can disrupt several molecular pathways within cells via ER-mediated or AR-mediated mechanisms, oxidative stress-induced impairment, lysosomal and mitochondrial disorder and DNA damage [55]. Previous researches demonstrated that PrP induced detrimental influence on zebrafish, including lipid metabolism disorder [26,56], oxidative stress, DNA double-strand breaks and apoptosis [28]. Studies also suggested that PrP and other parabens may contribute to carcinogenicity [55,57]. The negative physiological effects of PrP on the vital tissues of mosquitofish were likely associated with these toxic mechanisms, which may affect normal physiological activities of the brain, liver and testes. The pathological injuries in these tissues were the embodiment of multiple synthetic influences of PrP. The HPGL axis plays a pivotal role in the regulation of reproductive function [58], the gene expression changes along the HPGL axis suggested a compensatory mechanism and feedback-regulation for PrP damage.
As a pivotal organ responsible for detoxification, metabolism, immunization, and epidemic prevention, chemical-induced hazardous effects usually appear primarily in the liver [59]. Available literature revealed that PrP is hepatotoxic. PrP induced disruption of energy metabolism and increased synthesis of superoxide anions and apoptosis in the liver cells [60]. PrP (4.0 mg/L) caused oxidative stress (a decrease in 6d and an increase in 12d of total glutathione) in the liver cells of *Nile tilapia* (Oreochromis niloticus) [61]. Hepatic atrophy and cellular degeneration in the brain were found in the 13 dpf-old medaka eleuthero-embryos exposed to 4000 μg/L PrP during embryo development [25]. In the present work, similar findings were shown in the histological liver structures from PrP groups, which reflected the biochemical changes and failure of cellular protective mechanisms under PrP stress.
It is confirmed that embryonic exposure to PrP triggered anxiety-like neurobehavioral response in zebrafish, which is correlated with oxidative-stress-induced apoptosis in the head of the larvae [27]. Nevertheless, PrP was suggested to reduce the excitability of hippocampal neurons in rats [62], and to have anticonvulsant effects on pentylenetetrazol-induced seizures in zebrafish [63], demonstrating the potential for use in anticonvulsant drugs. In this study, cell cavitation, cytomorphosis and blurred cell boundaries were found in the brain of mosquitofish, the deleterious effects of PrP on the physiological function of brain should be noteworthy to illuminate the safety and toxicity mechanisms.
Numerous studies have verified that PrP exhibits the characteristics of antiandrogenic and estrogenic activity, and has harmful effects on reproductive functions. For the invertebrates, PrP exposure caused fecundity-reduction in the female fruit fly Drosophila melanogaster [64], Aedes aegypti [65], nematode Caenorhabditis elegans [66], and marine copepod *Tigriopus japonicus* [30]. PrP also prolonged the pupation and maturation times of the fruit fly D. melanogaster [64]. For the vertebrates, chronic exposure to PrP at humanly relevant doses led to endocrine disorders, altered the estrus cycle, hormone levels and ovarian reserve, as well as accelerated ovarian aging in adult mice [67]. Kolatorova et al. [ 68] found a negative association between the PrP and testosterone levels in human cord blood, indicating a PrP risk for prenatal male development. PrP exposure resulted in a female-biased sex ratio in juvenile zebrafish [29] and marine copepod T. japonicus [30]. Additionally, parabens are suggested as effective spermicides [69], e.g., oral PrP exposure decreased testosterone concentration, sperm production and quality in male rats [70]. However, in Gazin’s research on rats, oral PrP did not show effects on male reproductive organs’ weight, epididymal sperm parameters, hormone levels or histopathology [71].
In the present study, testes lesions and a delayed spermatogenesis were found in the PrP groups, providing evidence that PrP has adverse effects on male reproduction. Similar testes lesions were also found in the zebrafish with methyl paraben exposure, including general testicular atrophy, multi-nucleated gonocytes, impaired germ cell, spermatogonial proliferation, Leydig cell hyperplasia, interstitial fibrosis and apoptosis of Sertoli cells [72]. Teleost gonads are sensitive to environmental factors; endocrine disruptors such as estrogens and estrogen mimics may induce temporary or permanent morphological changes in the gonads and result in an impairment of gonadogenesis and sex differentiation [73]. Steroid hormones and steroid-regulated genes play important and distinct roles in controlling fish spermatogenesis and testis maturation [74]. As expected, there was a robust transcriptional response in the testes of PrP-treated mosquitofish, which help to explain the morphological changes and reproductive abnormality.
## 4.2. Deleterious Impacts of PrP Stress on Endocrine Markers in HPGL Axis
EDCs modulate the endocrine functions through several means; they can bind nuclear receptors as ligands and act like agonists or antagonists, and can disrupt the biosynthesis, metabolism, transportation and biotransformation of endogenous hormones [32]. In this study, most of the target genes associated with the HPGL axis in the male mosquitofish showed significant transcriptional changes during PrP exposure, indicating the endocrine interference potency.
Parabens can act as either an estrogenic agonist or androgenic antagonist. The mRNA expression of several tested genes in the liver of male mosquitofish, including Ers, Ars, Vtgs, cyp19a and star, were dramatically up-regulated after 4d PrP exposure at all concentrations. These data showed that PrP could disrupt estrogenic and androgenic receptors. Parabens could activate both ERα and ERβ receptors, with similar or stronger effect versus ERβ receptors [2]. Consistently, the erβ gene in the liver and testes of the 32d-PrP treated mosquitofish was also significantly increased compared to control. The cytochrome P450 aromatase gene cyp19a is a rate-limited step for catalyzing the conversion of androgens into estrogen [75], thereby, the enhanced cyp19a transcripts may raise the production speed of estrogen, resulting in the synchronized increase of erα and erβ. ERs are sensitive biomarker of estrogen endocrine disturbance, similar to other parabens [76,77], the raised erα and erβ genes at various concentrations and exposure duration confirmed the estrogenic effect of PrP, which may cause imbalance of ERs-dependent transcriptional signaling pathways.
The androgen receptor (AR) is a steroid hormone receptor that is responsible for androgen-sensitive genes regulation, as well as for the development and maintenance of male secondary sexual characteristics [78]. The transcriptional responses of arα and arβ genes in the liver of PrP exposed group exhibited an upward tendency, indicating an antiandrogenic effect. Similar results were also found in the liver of male medaka that were treated with antiandrogens vinclozolin and flutamide [79]. The steroidogenic acute regulatory protein (star) is involved in catalyzing the first step of the steroidogenesis pathway, and play an important role in regulating the transport of cholesterol into the inner mitochondrial membrane [51]. The high star transcripts may increase the endogenous androgen levels, which compete with exogenous antiandrogen-like PrP for androgen receptors. Hence, the increased arα and arβ expressions may be due to the positive feedback results from the increase steroid hormone level of the male fish, displaying a compensatory response for blocking ARs [79].
Vitellogenin (VTG), the fish egg yolk precursor protein, is a common biochemical endpoint to assess the presence of estrogenic substances in fish. The liver is considered to be the main tissue for VTG synthesis in fish [80]. The vtg gene is usually silent in male fish but can be stimulated by estrogen and estrogen-like hormones [81]. PrP exposure raised the VTG plasma concentration and mRNA expression levels of vtg-1, vtg-2 and erα in the liver of male medaka [82]. Increased plasma vitellogenin levels in the rainbow trout were reported [23,83], which proved that this paraben had oestrogenic properties. Consistent with these studies, significant upregulation of vtgB and vtgC genes in the liver were found after PrP exposure for 4 d. Meanwhile, the vtgC levels in the testes of 32d-PrP groups were higher than that of the control group. ERs are functionally involved in the regulation of vitellogenesis with Erα and act as the central mediator in teleost [84]; in the present study, the increased *Ers* genes triggered vitellogenesis and may eventually yield higher contents of VTG. Vitellogenin can cause fertility disorders, such as gonadal histopathology changes or feminization of male fish, which could lead to reproduction suppression of fish [85]. The elevated vtg gene expressions may be associated with the proportion changes of spermatogenic cells at various differentiation stages.
Fish reproduction is regulated by synergistic interactions between steroid hormones along the HPGL axis and by steroidogenesis in the gonad [51]. During steroidogenesis, the star gene is responsible for the rate-limiting transportation of cholesterol into the mitochondrial membrane, then, the cholesterol is stepwise converted to testosterone under the catalytic action of CYP11a1, 3β-HSD, CYP17a, and 17β-HSD, finally the testosterone is converted to 17β-estradiol by the aromatase (CYP19a) [86]. As known, the hydroxysteroid 3β dehydrogenase (hsd3b gene) catalyzes the second step of steroid production, namely converts the pregnenolone to progesterone, which is necessary for the synthesis of all steroids [87]. The hydroxysteroid 17β dehydrogenase 3 (hsd17b3 gene) is a key enzyme in the last step of sex hormone synthesis, it performs the conversion of androstenedione to testosterone [88]. The hsd20b gene encodes the enzyme involved in the production of 17α, 20β-dihydroxy-4-pregnen-3-one (DHP), the main progesterone for fish [89].
*The* genes involved in steroid hormone production in the testes of mosquitofish treated with PrP (6 and 240 μg/L) for 32d were all stimulated, including the star, hsd3b, hsd17b3 and hsd20b, while the levels of cyp11a1, cyp17 and cyp19a1a were constant. The simultaneous up-regulation of these genes would promote steroidogenesis activity and may result in the accumulation of progestogen and androgens. The results in Gal’s research supported this speculation, because PrP aggrandized the expression of star, as well as increased the content of testosterone and 17β-estradiol in the mouse-cultured antral follicles [90]. Sex steroid hormones are important in the regulation of fish sex differentiation, gonadal development and secondary sexual characteristics [91]. The intervention of PrP may disrupt the levels and balance of hormone homeostasis in the gonad of male mosquitofish and lead to the delayed spermatogenesis. However, future studies are warranted to verify this hypothesis, since we did not test the hormone levels.
Shh (sonic hedgehog) is one of the effector genes that regulate reproductive organ formation associated with hormonal signals, it can interact with function downstream of the androgenic pathway [92]. According to the literature, the Shh signaling pathway is operative and necessary in the developing prostate [93] and is indispensable for the establishment of male external genitalia characteristics [94]. Overactivation of hedgehog signaling in the developing Müllerian duct interferes with duct regression in male mice and causes subfertility [95]. Analogously, Shh protein was detected in the testis of juvenile and adult mice, and higher shh mRNA levels were seen in the patients with obstructive azoospermia and prostate cancer compared with the patient with cryptorchidism, suggesting that Shh signaling is involved in normal spermatogenesis [96]. In agreement with these findings, in the male mosquitofish, PrP induced transcriptional overexpression of the androgen-dependent sonic hedgehog (shh) and its receptor patched 1 (ptc1), which is likely to influence gonadal development.
In the brain, the gene transcriptions in different doses of 32d-PrP groups displayed a parabolic path, with incremental expressions in the 0.15 μg/L PrP group and a reduced level in the 240 μg/L PrP group, which may be due to the overwhelming toxic stress or related to the negative feedback loop for the action of PrP. GnRH is an important hormone in the neuroendocrine modulation of testicular development and spermatogenesis [97] via a coordinated interaction with sex steroids. Synchronized suppressions of gnrh and gnrhr mRNA expression and spermatogenesis were found in the male rats that suffered from chronic exposure to isoflurane [98]. Researchers found that GnRH steroids or agonist treatment stimulates the recovery of spermatogenesis and fertility [99]. Herein, after chronic exposure to 240 μg/L PrP for 32 d, the delayed maturity of sperm in the male mosquitofish may be associated with the inhibited expression of gnrh and gnrhr.
## 5. Conclusions
This study provided an integrative perspective of the endocrine interference effects of PrP on the male mosquitofish. The results systematically demonstrated that acute and chronic exposure to different concentrations of PrP caused tissue injuries in the hormone-dependent organs and delayed spermatogenesis. The tissue impairments in the brain, liver and testes presented a time- and dose-dependent manner, while the endocrine-related gene expressions varied with exposure durations, exposure concentrations and organs. The transcriptional level changes of the genes along the HPGL axis suggested that PrP stimulated abnormal steroidogenesis, estrogenic effects or antiandrogen effects (Figure 6). The findings of this work strongly indicated that PrP are a potential hazard to the physiologic functions and reproduction of adult male mosquitofish, even at an environmentally and humanly relevant dose. Considering that PrP is frequently used in daily lives and is ubiquitous in the aquatic environment, PrP safety requires special attention and further investigation. In addition, the potential risks of PrP for humans deserve scrutiny, since high concentrations of PrP were detected in different human tissues and fluids.
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|
---
title: Convergent Validity between Electromyographic Muscle Activity, Ultrasound Muscle
Thickness and Dynamometric Force Measurement for Assessing Muscle
authors:
- Umut Varol
- Marcos J. Navarro-Santana
- Juan Antonio Valera-Calero
- Sergio Antón-Ramírez
- Javier Álvaro-Martínez
- María José Díaz-Arribas
- César Fernández-de-las-Peñas
- Gustavo Plaza-Manzano
journal: Sensors (Basel, Switzerland)
year: 2023
pmcid: PMC9967681
doi: 10.3390/s23042030
license: CC BY 4.0
---
# Convergent Validity between Electromyographic Muscle Activity, Ultrasound Muscle Thickness and Dynamometric Force Measurement for Assessing Muscle
## Abstract
Muscle fatigue is defined as a reversible decline in performance after intensive use, which largely recovers after a resting period. Surface electromyography (EMG), ultrasound imaging (US) and dynamometry are used to assess muscle activity, muscle morphology and isometric force capacity. This study aimed to assess the convergent validity between these three methods for assessing muscle fatigue during a manual prehension maximal voluntary isometric contraction (MVIC). A diagnostic accuracy study was conducted, enrolling 50 healthy participants for the measurement of simultaneous changes in muscle thickness, muscle activity and isometric force using EMG, US and a hand dynamometer, respectively, during a 15 s MVIC. An adjustment line and its variance (R2) were calculated. Muscle activity and thickness were comparable between genders ($p \leq 0.05$). However, men exhibited lower force holding capacity ($p \leq 0.05$). No side-to-side or dominance differences were found for any variable. Significant correlations were found for the EMG slope with US ($r = 0.359$; $p \leq 0.01$) and dynamometry ($r = 0.305$; $p \leq 0.01$) slopes and between dynamometry and US slopes ($r = 0.227$; $p \leq 0.05$). The sample of this study was characterized by comparable muscle activity and muscle thickness change between genders. In addition, fatigue slopes were not associated with demography or anthropometry. Our findings showed fair convergent associations between these methods, providing synergistic muscle fatigue information.
## 1. Introduction
Muscle contraction is produced by electric stimuli originating from the central nervous system (CNS) to motor neurons inserted into the muscle cells and branches. At this location, the electric stimulus produces the release of chemical neurotransmitters (acetylcholine) from synaptic vesicles to nicotinic receptors located on the motor endplate. This coupling induces muscle membrane depolarization, which is propagated to the sarcoplasmic reticulum to release the calcium ions needed for muscle contraction [1].
Although this physiological process is identical for all skeletal muscles, the endurance capacity for each muscle is not the same, as there are different muscle fibers described according to their properties and function [2]. Type I fibers contain several mitochondria and myoglobin, and are resilient and activated for sustained and prolonged submaximal demands (therefore, a high blood supply for this aerobic process is needed). In contrast, type II fibers provide more tension and more powerful forces during shorter times. As these are more anaerobic, less blood supply is needed (for this reason, they are also known as white muscle fibers) and they are characterized by rapid fatigue [3].
Muscle fatigue is defined as the reversible decline in performance after intensive use, which largely recovers after a resting period [4]. Chronic conditions including muscle atrophies (due to immobilization, sarcopenia or neurogenic etiology) or fiber type changes in chronic pain populations including neck pain [5] focused on muscle fatigue are a determinant factor affecting the functional capacity and quality of life of individuals [6].
Three methods widely used for assessing muscle performance are dynamometry, surface electromyography (EMG) and ultrasound imaging (US). These three methods can be used for monitoring changes in the applied force, electrical activity and muscle morphology, respectively, during a sustained maximum voluntary isometric contraction (MVIC) [7]. It should be noted that each method is characterized by its own strengths and limitations. For instance, US is portable, safe (as no ionizing radiation is used for acquiring the images), fast, accessible and provides real-time information, allowing the examination of immediate changes [8]. Due to these advantages and the range of imaging methods based on US (e.g., B-mode, M-mode, Doppler US, strain elastography, shear-wave elastography and panoramic US, among others [9]), it is a tool that is widely used in health sciences for the educational (i.e., teaching anatomy and pathologies [10]), research (i.e., to obtain objective measurements of muscle function, size, shape and composition [11]) and clinical settings (e.g., as a supportive tool for guiding needle interventions, visual feedback for motor control exercises or monitoring changes after interventions [12]). However, important limitations should be acknowledged. First, US is an operator-dependent method and certain exams require the examiner to be experienced so as to ensure good validity, reliability, sensibility and specificity [13]. Thus, due to the US interaction with the tissues (i.e., attenuation and refraction), some artifacts impede the visualization of some structures, including intra-articular elements or deep structures [14].
Regarding the strengths of EMG, its safety, ease and cost-effectivity should be highlighted. In contrast to needle EMG, it is not necessary to pierce the skin to record from single motor units to wide muscle areas [15]. This tool is not limited to providing the electrical activity difference between rest and contraction, facilitating cognition during motor control exercises [16], but also provides timing information, which is considered a determinant factor to differentiate clinical and asymptomatic populations [17]. The most important limitations of this tool are the limited ability to monitor muscle sites (as the neuromuscular system is complex, reducing the function to one or two channels may not represent the real function of the musculoskeletal system) [18], the possibility of “cross-talking” (a phenomenon where electrical activity from other muscles may bias the recording of the targeted muscle) and the need to normalize the data for correct interpretation [19].
Finally, hand dynamometers are characterized by their simplicity and portability for measuring the hand grip force and extrapolating the general strength level [20]. However, regular recalibrations are needed to ensure its accuracy and hand size is a determinant factor to be considered during the exams.
Despite previous research analyzing the association between US and EMG simultaneously with MVIC [21], evidence is limited regarding the convergent validity of these three methods for assessing simultaneously muscle fatigue during a sustained MVIC. Therefore, the aim of this study was to assess the association of the fatigue-adjusted line using US, EMG and dynamometry simultaneously during a sustained MVC to verify the association between isometric force capacity, electrical muscle activity and muscle morphology.
## 2.1. Study Design
This diagnostic accuracy study consisted of a single-group, cross-sectional concordance design. This study was conducted between October 2021 and February 2022 in a private university located in Madrid, Spain. Patients were evaluated once by two blinded examiners with +10 years of experience in each method. The study was conducted according to the directives of the Standards for Reporting of Diagnostic Accuracy Studies (STARD) [22] and the Enhancing the Quality and Transparency Of health Research (EQUATOR) guidelines and checklist [23]. All procedures were approved by a local Ethics Committee and conducted in accordance with the Declaration of Helsinki.
## 2.2. Participants
Healthy participants were recruited using fliers posted around the university campus. Participants had to be aged between 18 and 65 years and had to read and sign the informed consent form to be enrolled in the study. Exclusion criteria included [1] neurological, muscular, cardiovascular or any other condition contraindicating hand grip MVIC performance or contributing to pain appearance; [2] subjects with a body mass index (BMI) > 35 kg/m2 since this could bias the US and EMG measurements [21].
## 2.3. Sample Size Calculation
Sample size was calculated based on the only previous similar study analyzing simultaneously MVIC, US and EMG [21] (peak, but not fatigue) in healthy subjects. Accordingly, a minimum sample size of 38 participants could be considered appropriate. If this study was considered as a prognostic study, a range of 10 to 15 data points per potential predictor (with no more than five predictor variables) was recommended for avoiding overestimation of the results [24]. Therefore, considering the inclusion of 10 potential variables assessed in this study (excluding side and dominance as no differences are expected), the minimum sample size required was set at 100 measurements. Due to the cross-sectional nature of this study, no losses were considered.
## 2.4. Fatigue Measurement Instruments
Data collection procedures were performed using a dynamometer, a surface EMG device and a US device simultaneously and synchronized during a sustained 15 s MVIC. A single measurement from both sides was acquired. Previously, participants were familiarized with the dynamometer and the starting position (subjects placed the Jamar in their hand, with the arm beside the trunk, the shoulder in a neutral position and the elbow flexed at 90°, and pulled the metal bar with their fingers), performing 2–3 submaximal contractions (to avoid early fatigue appearance), as illustrated in Figure 1. All procedures were conducted following the instructions described by Trinidad-Fernández et al. [ 21], as they demonstrated acceptable reliability.
## 2.4.1. Ultrasound Imaging
All US procedures were conducted using the Alpinion Ecube i8 equipment (Gyeonggi-do, Republic of Korea) with a linear transducer E8-PB-L3-12T 3–12 MHz, setting the same parameters for all exams (frequency: 12 MHz; gain: 55 dB; dynamic range: 85 dB; brightness: 74), but the depth was adapted for each subject. Firstly, forearm length was determined as the distance from the elbow flexion crease to the wrist flexion crease [25]. The transducer was placed in the middle distance between these points, avoiding excessive pressure. In addition, this location was used to measure the forearm girth (Figure 1A). The transducer was glided medially to locate both the flexor digitorum superficialis and profundus and the cubital bone surface in the center of the image (Figure 1B).
## 2.4.2. Hand Grip Force
The Hand Grip Force test is a simple, fast, reliable and relatively inexpensive test for assessing grip strength [26]. A Jamar hand dynamometer (JLW Instruments, Chicago, IL, USA) was used (Figure 1B). The handle diameter was set at $19.7\%$ of the participant’s hand length, as recommended by Kong et al. [ 27]. One researcher explained and demonstrated the procedure before proceeding with the data collection. Participants were placed in the sitting position, holding the Jamar in their hand, with the arm beside the trunk, the shoulder in a neutral position and the elbow flexed at 90°. This procedure was conducted bilaterally, asking the participants to pull the metal bar with their fingers as hard as they could (respecting the positioning explained) for 15 s.
## 2.4.3. Surface Electromyography
The surface electromyographic activity was collected using a mDurance Pro device (mDurance Solutions S.L., Granada, Spain). Data were transferred and processed using the mDurance software v.2.11.2 for Android 5.0. Prior to the electrodes’ placement, the skin was prepared following the recommendations provided by the Surface ElectroMyoGraphy for the Non-Invasive Assessment of Muscles [28]. Three 30-mm-diameter circular electrodes were used: one ground electrode was placed on the bone surface located at the medial humeral epicondyle and two reference electrodes were placed in line over the proximal third of the forearm to collect the muscle activity of the flexor digitorum superficialis and profundus as a single functional muscle (Figure 1B). This procedure followed the recommendations provided by the European Society of Electromyography regarding the spatial sensor characteristics and placement (reference electrodes located longitudinally to the fiber direction with an inter-electrode distance of 20 mm), electrode materials (Ag/AgCl) and signal conditioning (lower and upper cut-offs were set at 20 and 500 Hz, respectively, and sampling frequency was set at 1024 samples/second) and processing (root mean square, RMS) [29] based on previous studies assessing the same muscles during the same task [21,30,31].
## 2.5.1. Isometric Force Holding
The Hand Grip Dynamometry provided the force (expressed in kilograms) during the 15 s MVIC hand grip test. Data for each second were collected and analyzed to measure force changes due to muscle fatigue.
## 2.5.2. Muscle Thickness Change
M-mode ultrasound imaging provided information about the muscle thickness (Y-axis) per time (X-axis) (Figure 2A). Firstly, time frames of 1 s were marked in the M-mode images (where T0 corresponds to the contraction initiation). Then, muscle thickness was measured for each time point as the distance between the internal and superficial fascia of the flexor digitorum superficialis to the deep and internal fascia of the flexor digitorum profundi (Figure 2B).
## 2.5.3. Muscle Activity Change
The surface EMG provided the muscle activity (expressing the amplitude in μV) during the 15 s test. Previous studies demonstrated the use of the flexor digitorum muscle during this task [32,33]. Data for each 0.25 s were collected and analyzed to measure muscle activity fatigue.
## 2.6. Data Analysis
The adjusted line for the function of each measurement method (force holding capacity, muscle activity and muscle thickness changes in the Y-axis) by time (X-axis) was calculated to obtain the linear regression slope and variance (R2). Adjusted lines for each method are available in Figure 3.
## 2.7. Statistical Analysis
All statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS) v.27 for Mac OS (Armonk, NY, USA). Normal distribution of each variable was verified using the Kolmogorov–Smirnov test if $p \leq 0.05.$ Then, descriptive statistics were used to summarize continuous variables as the mean and standard deviation (if normally distributed) or median and interquartile range (if non-normally distributed) and categorical variables as frequency and percentage.
Student’s t-tests for independent samples were used to identify differences in gender (demographic, anthropometric and fatigue variables), side and dominance (both anthropometric and fatigue variables).
Pearson’s correlation coefficients (r) were used to calculate a multivariate correlation matrix including all demographic, anthropometric and fatigue variables. Association strength was interpreted accordingly with the values obtained (0–0.3 were poor, 0.3–0.5 fairly, 0.5–0.7 moderate and 0.8–1.0 strong), and direction (for continuous variables) was interpreted depending on the r sign (negative values as indirect correlations and positive values as positive correlations) [34].
## 3. Results
From a total of 52 volunteers responding to the announcements, two participants were excluded due to exceeding the BMI considered for this study. All registered measurements ($$n = 100$$) from the 50 participants enrolled were included in the analyses.
Table 1 and Table 2 summarize all demographic and anthropometric data of the total sample and divided into groups (gender, left/right sides and side dominance). Although participants had a comparable age ($p \leq 0.05$), men showed a greater BMI (difference = 0.6 to 4.7 kg/m2; $p \leq 0.05$) and in general were taller and heavier (difference = 0.08 to 0.16 m; $p \leq 0.001$). Forearm length and girth were larger in men compared to women (difference = 1.1 to 3.0 and 2.0 to 4.2, respectively; both $p \leq 0.001$). However, no side-to-side or dominant–non-dominant statistically significant differences were found ($p \leq 0.05$).
Table 3, Table 4 and Table 5 show the slope decrease rate and variance for each instrument by gender, side and dominance, respectively. For instance, the muscle activity assessed with EMG in males decreased at a rate of 1.08 μV per second. Therefore, after the 15 s maneuver, a mean decrease of 16.2 μV was observed. Fatigability results obtained from EMG, US and dynamometry were compared by gender, dominance and side. No linear regression slope differences were found between males and females for fatigue properties measured with EMG or US ($$p \leq 0.508$$ and $$p \leq 0.693$$, respectively). However, females were more capable of holding the MVIC compared with males ($$p \leq 0.022$$), demonstrating lower fatigability. On the other hand, comparisons between the right and left hand and between dominant and non-dominant sides showed no significant differences for EMG, US and dynamometry slopes (all $p \leq 0.05$).
Table 6 contains the correlation matrix. *In* general, we found anthropometric characteristics to be associated with several demographic features. Forearm girth was associated with age, height, weight, BMI, forearm length and gender (all $p \leq 0.01$), and forearm length was associated with height, weight, BMI (all $p \leq 0.01$) and gender ($p \leq 0.05$). Muscle activity fatigue and thickness change during the MVIC showed no significant correlations with demography or anthropometry (all $p \leq 0.05$). However, isometric force holding capacity was negatively associated with height ($p \leq 0.05$), forearm girth ($p \leq 0.01$) and length ($p \leq 0.05$). In addition, male sex was associated with greater force fatigue ($p \leq 0.05$). Finally, significant correlations between all methods used for quantifying muscle fatigue were found ($p \leq 0.05$).
## 4. Discussion
This study aimed to analyze the convergent validity of muscle activity assessed with EMG, muscle thickness assessed with US and isometric prehensile force assessed with dynamometry for measuring muscle fatigue. To our knowledge, this is the first study using adjusted line slopes with these tools to compare the association between them for measuring fatigue indicators such as electrical activity, muscle thickness and force capacity. Our findings showed significant weak associations between all methods, suggesting the use of all of them to provide synergistic information in the fatigue assessment, as it seems to be sensitive to different aspects and overcomes the limitations introduced previously (e.g., use of US for evaluating deep muscles not accessible with EMG). These findings could assist both clinicians and researchers to acquire overall information. The rationale for selecting the forearm muscles was supported by the anatomical disposition, which allows the simultaneous assessment with EMG, US and dynamometry and highlights the clinical importance of this muscular group [35]. Previous studies highlighted the importance of hand grip force as it is associated with a greater impact of rheumatoid arthritis [36], fibromyalgia [20], sarcopenia [37], cancer [38] or diabetes [39]. Additionally, it is considered an important predictor of mortality associated with falls [40,41] and heart failure [42].
Ultrasound imaging is widely used for assessing muscle morphology, histology and function [43,44]. Previous research demonstrated this tool to be useful in fatigue assessment to provide strategies aiming to alleviate muscle [45] or tendon failure [46] based on echogenicity and strain features, or as a discriminative and reliable tool for identifying clinical populations based on their ability to maintain an isometric contraction [47]. In addition, M-mode US could be a potential tool to be used in rehabilitative exercise programs, providing more effective feedback than tactile, with or without verbal advisements, in both exercise performance and retention success [48].
Shi et al. [ 49] conducted a sonographic study analyzing the feasibility of the muscle thickness change in measuring muscle fatigue while monitoring muscle activity during biceps brachii isometric contractions ($80\%$ MVIC) in eight healthy participants. Although they demonstrated this muscle deformation to be valid for measuring muscle fatigue, the sample size was small, and the procedures used for assessing the muscle thickness change with B-mode US were complex and not readily applicable during the clinical practice (e.g., software was needed to display results frame by frame, requiring off-line assessments). M-mode is an easy-to-use, accessible and applicable imaging mode, allowing both the examiner and participant to obtain real-time feedback in measuring the muscle thickness changes [50] of individual muscles, even if they are overlapped. Despite these methodological procedures’ differences, our results were consistent.
In this study, we focused on the Hand Grip Force as it is a widely considered outcome in a wide range of populations with different ages, sexes, states of health and pathological conditions [51]. One possible reason may be that muscle weakness is a risk factor in developing disability and dependence during activities of daily life, frailty and mortality [52]. Although Trinidad-Fernández et al. [ 21] found moderate and strong associations between EMG and muscle thickness, this association was found for the maximum grip force peak with the EMG score (calculated as the difference between the maximum and minimum peaks). Differences in the strength of the correlations between the two methodologies may be explained by the activity demands in muscle fibers derived from the cross-sectional and longitudinal designs.
Finally, previous studies evaluated electromyographic changes occurring during sustained muscle contractions for assessing muscle endurance [53,54,55]. For instance, Falla et al. [ 53] reported existing slope differences between healthy subjects and neck pain patients at $25\%$ and $50\%$ of MVIC for the sternocleidomastoid and anterior scalene muscles, suggesting the greater presence of type II fibers and greater fatigability of superficial neck muscles in neck pain patients compared with healthy subjects. In addition, Robinson et al. [ 54] and Elfving et al. [ 55] demonstrated significant differences for fatigue slopes between patients with chronic low back pain and asymptomatic subjects.
## Limitations
Although this study addressed many limitations of previous studies, several limitations remain. Firstly, this was a diagnostic accuracy study, and we limited this research to the agreement between methods and did not consider the fatigue demeanor. Further studies are needed assessing EMG, US and dynamometry differences between healthy and clinical populations for a better overall understanding of fatigue mechanisms. Secondly, we assessed both flexor digitorum muscles as a single unit, as we used surface EMG. Further studies should clarify whether there are muscle activity and thickness interactions between overlapped or adjacent muscles. Finally, fatigue assessments considering many other situations (e.g., populations, muscles, methods, contraction types and normalizations) would be of utility.
## 5. Conclusions
Our findings showed fair convergent associations between muscle thickness changes assessed with M-mode US, muscle activity changes assessed with surface EMG and hand grip force sustainment assessed with dynamometry. Although we found comparable muscle activity and muscle thickness changes between genders, men exhibited a greater decrease in force holding capacity. Fatigue slopes assessed with all methods were not associated with demography or anthropometry, but forearm girth and length were associated with force holding capacity. These findings suggest that these three methods assess different aspects of muscle fatigue, providing synergistic information about muscle activity, thickness and force capacity and allowing alternatives to overcome the limitations described previously for each method.
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|
---
title: 'Development and Validation of Vitamin D- Food Frequency Questionnaire for
Moroccan Women of Reproductive Age: Use of the Sun Exposure Score and the Method
of Triad’s Model'
authors:
- Noura Zouine
- Ilham Lhilali
- Aziza Menouni
- Lode Godderis
- Adil El Midaoui
- Samir El Jaafari
- Younes Zegzouti Filali
journal: Nutrients
year: 2023
pmcid: PMC9967684
doi: 10.3390/nu15040796
license: CC BY 4.0
---
# Development and Validation of Vitamin D- Food Frequency Questionnaire for Moroccan Women of Reproductive Age: Use of the Sun Exposure Score and the Method of Triad’s Model
## Abstract
This cross-sectional study aimed to develop and validate a vitamin D food frequency questionnaire (VitD-FFQ) to assess vitamin D intake in Moroccan women of reproductive age. Using the method of triads, the VitD-FFQ was validated against seven-day dietary records (7d-FR) and 25-hydroxyvitamin D (25(OH)D) as a biomarker of vitamin D status in 152 women (aged 18–45 years). Participants’ sun exposure scores (SES) were assessed using a specific questionnaire (SEQ). Predictors of vitamin D status were identified via linear regression models. Several statistical tests were applied to evaluate the criterion validity of the FFQ against two references methods (7d-FR and the biomarker-serum 25(OH)D). Median (Interquartile range) intakes were 7.10 ± 6.95 µg /day and 6.33 ± 5.02 µg/ day, respectively, for VitD-FFQ and 7d-FR. Vitamin D status was mainly determined by SES ($R = 0.47$) and vitamin D absolute food intakes derived by the VitD-FFQ ($R = 0.56$), which demonstrated a more significant prediction ability compared to 7d-FR ($R = 0.36$). An agreement was observed between the VitD-FFQ and 7d-FR (BA index of $3.29\%$) with no proportional bias (R2 = 0.002, $$p \leq 0.54$$). <$10\%$ of participants were incorrectly classified, and weighted kappa statistics showed that VitD-FFQ had an acceptable ranking ability compared to the 7d-FR and the biomarker. The validity coefficient for the VitD-FFQ was high: ρQR = 0.90 ($95\%$CI: 0.89–0.92), and a range from 0.46 to 0.90. Adjustment for the participants’ SES and BMI (body mass index) improved the biomarker’s validity coefficient (ρRB 0.63 ($95\%$ CI 0.39–0.82). Our results indicate that the VitD-FFQ is valid for estimating absolute vitamin D intake in Moroccan women of reproductive age.
## 1. Introduction
Althouμgh biologically inactive, vitamin D is an essential nutrient that can be converted to the steroid hormone 1,25(OH)2D3 and influences multiple processes unrelated to calcium metabolism while regulating gene transcription [1]. Over the past decades, extensive research revealed significant associations between vitamin D status and various health outcomes [2,3]. Studies have reported that vitamin D deficiency is associated with skeletal disorders (i.e., rickets in children, osteoporosis and osteomalacia in adults) [4], chronic disorders, such as diabetes type I mellitus [5], respiratory infections and asthma [6], cardiovascular diseases and hypertension [7,8], and cancers [8,9]. Large–scale observational studies support the crucial role of vitamin D in women’s reproduction and offspring development [9,10,11]. More recently, vitamin D deficiency has emerged as a possible contributor to the cytokine storm that heralds some of the most severe COVID-19 disease complications [12,13].
Sun exposure is the primary determinant of vitamin D status during more than $99\%$ of human evolution. Vitamin D3 (Cholecalciferol) might be generated endogenously when the epidermis is exposed to sunlight [4,14]. The amount of vitamin D3 synthesized in this process is affected by numerous factors, including latitude, seasons, time of the day, skin pigmentation, air pollution, clothing, and sunblock lotions use [15]. Thus, to have sufficient vitamin D3 production, certain researchers advise sun exposure to the face, arms, hands, and legs for around 5 to 30 min, preferably between 10 a.m. and 4 p.m., daily or at least twice per week without the use of sunscreen [16,17].The second and exogenous source of vitamin D3 is a diet, such as animal sources and plants (in the form of ergocalciferol (D2)) [16]. Notably, food sources containing significant amounts of this nutrient are very scarce, such as oily fish (i.e., salmon, sardines and tuna) and oils of cod liver, beef liver, yolk, and sun-exposed mushrooms [3,16,18].Specific orange juice formulations, yoghurt, cheese, margarine, bread, and breakfast cereal may also be fortified with vitamin D [19].*The serum* level of 25(OH)D indicates the overall synthesis of vitamin D from both dietary and solar sources [20]. Nevertheless, under conditions where UVB exposure is limited, vitamin D production in the skin may be altered in contrast, and this nutrient must be supplemented in the diet regularly [14,21]. Depending on the country, guidelines for the recommended supplemented dose vary from 200 IU to 2000 IU daily in children and adults [17].
It is noteworthy that, dietary intake measures are challenging, and no single method can accurately estimate dietary exposure [22]. Food frequency questionnaires (FFQs) are self-report methods used in large-scale epidemiological research to examine long-term dietary intakes. It is a reasonably simple, inexpensive, and time-efficient [22,23]. Even in the case of a nutrient with restricted dietary sources such as vitamin D, FFQs are very effective [24]. It can estimate usual intake and classify individual intakes into broad categories to allow meaningful comparisons of the attributes associated with high or low intakes [25]. However, FFQ should be developed specifically for each study group and research purposes because diet may be influenced by various factors, including ethnicity, culture, individual’s preferences, and economic status [26,27]. Prior validation of the instrument is also a fundamental step, since incorrect information can lead to false associations between diet and the onset of certain diseases [28].
In the validation process, the FFQ is compared to other self-report methods as reference methods, such as 24 h-recalls or food records [29]. However, both the instrument being tested (FFQ) and the reference method present similar random and systematic errors due to reliance on memory as well as inaccuracies related to the estimation of reported food consumption [29,30]. These random errors cannot be predicted and may result in more significant correlation estimations between the two methods, thereby the FFQ’s validity [30]. Using nutritional biomarkers as an additional reference method in a triangle validation technic may improve validity estimates since measurement errors in biomarkers are essentially uncorrelated with errors in any dietary assessment [29,31]. Ultimately, the method of triads is widely used to provide a more objective metric in validation studies of vitamin D FFQs [32,33,34,35].
Likewise, based on Koppen Climate Classification, Morocco has “dry-summer subtropical” climates, which are often referred to as “Mediterranean”, with a burst of year-round sunshine [36]. Nevertheless, hypovitaminosis is emerging as a major public health concern. Studies show a high prevalence of hypovitaminosis D in the general female population [37]. This prevalence ranges between 78.1 and $98.4\%$ when the 25OHD threshold is defined at concentrations <20 ng/mL, while it affects $90\%$ of women with levels <30 ng/mL [37].
Numerous factors are related to this prevalence such as cultural aspects and lifestyle, which discourage women from spending time in the sun (i.e., wearing protective or restricting clothes and staying at home) [37,38,39,40], and additionally contribute to the widespread obesity and dark skin in many parts of the country [37]. Under such conditions, vitamin D status relies greatly on dietary sources, which might not be enouμgh to meet the requirements. Moroccans’ dietary habits are believed to follow a Mediterranean pattern, generally characterized by low to moderate consumption of cheese, yoghurt, fish, poultry and eggs and low consumption of red meat, which are all vitamin D-rich foods [41]. The government mandated a fortification program in the nation, allowing less than 300 IU of vitamin D3 in the daily ration of some food products [42]. However, there is scant accurate information on vitamin D habitual dietary intake among the Moroccan population. To our best knowledge, no specific questionnaire has been developed or validated to determine the daily intake and frequency of consumption of vitamin D-rich/fortified foods.
Therefore, the main objective of this study was to develop a new self-administrated FFQ to estimate the daily intake of vitamin D in Moroccan women of reproductive age (18–45 years) and to assess the criterion validity of the FFQ using the method of triads. The vitamin D dietary intake estimated by the VitD-FFQ was compared with the daily intake measured by 7d-FR and with the 25(OH) D serum concentrations. We applied the SEQ and the VitD-FFQ simultaneously (with respect to the known half-life of circulating 25(OH)D) to enable accurate estimate of the validity coefficient of the FFQ while controlling for endogenously synthesis induced by the sun exposure. Comparison of the dietary assessment tools by their ability to explain the objective measures of the nutrient was also performed.
## 2.1. Study Design, Population Enrollment and Samples Size
This was a cross-sectional study in which the vitamin D intake of participants was estimated using the method of triads that combine three assessment methods: FFQ, 7d-FR and vitamin D serum biomarker. The study process is represented in Figure 1. Healthy women of reproductive age (18–45 years) living in Meknes province and surrounding areas were recruited throuμgh an announcement at Moulay Ismail university population. The latitude of the chosen study area is around 33.89° which make vitamin D skin synthesis possible across $\frac{300}{364}$ days of the year [43]. Therefore, participant recruitment was performed between March and April 2019, in early spring season, when UVB strength would probably be moderate.
The literature identifies a sample size of 100 individuals as a quality criterion for validation studies [44]. A minimum of 50 subjects is indicated when using biomarkers as a reference method [44,45]. Similarly, for applying the Bland Altman approach, at least 50 is preferable to evaluate the limits of agreement [28]. Since 189 participants replied to our invitation voluntarily and were enrolled in the present study, the sample size was then considered as satisfactory. Exclusion criteria for the study were: women involved in loss weight programs, diet restriction (i.e., veganism or vegetarianism, lactose intolerance), or under medication known to interfere with vitamin D metabolism, such as glucocorticoids, carbamazepine used to treat epilepsy or Cholesterol-lowering druμgs, statin [46]. Furthermore, pregnant or breast-feeding women and women with self-reported medical conditions were excluded (i.e., severe anemia, hemophilic syndrome and malabsorption syndromes that may cause decreased vitamin D) [47].
All participants were invited to attend two appointments for data collection.
In visit 1: All participants were informed about the study process and the data collection. Next, inclusion/exclusion criteria were verified. Screening identified 167 women of reproductive age eligible and agreed to participate in the study. Afterwards, participants were divided into four groups and a dietitian explained and administered the ViD-FFQ and 7d-FR to each group. However, food record brochures that included written instructions and examples were provided individually to complete at home. The participants were asked to complete the VitD-FFQ and then the 7d-FR the following week to avoid memory bias between the dietary assessments. In order to reduce the social desirability bias, it was clearly explained to all participants that the aim of the study was nothing more than the evaluation of the VitD-FFQ as opposed to their food habits.
In visit 2: One week later, another visit was organized, and all VitD-FFQs and the 7d-FR were reviewed upon completion and submission by the same dietitian as the first visit. We only included the participants who fully completed and returned their 7d-FR. Incomplete FFQs and FR were excluded (i.e., missing items or day, an unreported quantity of food product and portion sizes consumed and others). In addition, blood samples and anthropometric measurements were taken by two registered nurses. All participants were interviewed to evaluate their sun exposure score during the last month using the sun exposure questionnaire (SEQ). The demographic information, such as the age and socioeconomic status of all participants, was also collected using a general questionnaire.
A total of 154 VitD-FFQs and the associated 7-FRs were of good quality of completeness. However, two participants failed to provide a blood sample. Therefore, the total number of women included in the analysis was 152. The ethics committee of biomedical research at Moulay Ismail University (reference; N°1/CERB-UMI/19) approved the study protocol, and all investigations were conducted under the principles of the Declaration of Helsinki. All participants signed written informed consent.
## 2.2. VitD-FFQ Description and Development
Different approaches were employed to develop the FFQ: Data from national population surveys and published scientific literature were compiled to inventory the dietary habits and foods commonly consumed by the Moroccan population [48,49,50,51]. Visits to typical supermarkets were made to identify local foods fortified with vitamin D3, their consequent brands and packaging labels. Subsequently, a list of foods naturally rich in vitamin D (at least 0.1 ng/100 g food) and supplemented was established [42,52,53,54,55]. In sum, 78 food items were incorporated in the final version of the VitD-FFQ. The foods were grouped into eight categories: Dairy products and beverages, eggs, fish and seafood, meat and products, fatty products (butter, margarine and oil), breakfast cereals, bakery and Moroccan biscuits, chocolate and cocoa.
The concept for the VitD-FFQ was based on a Belgium food-frequency questionnaire developed to assess the usual intake of methyl-group donors in women [56]. For each food item in the VitD-FFQ was assigned 3–5 daily portion size categories and a list of standard measures referring to commonly used household utensils (e.g., plates, glass, bowl, spoons) or “natural” units (e.g., one egg). Photographs from a booklet of Food and typical preparations of the Moroccan population’ were also showed to the participant as examples of portion size [57]. In the case of particular commercial fortified food, we incorporate the portion on product packaging labels (e.g., breakfast cereals). The developed vitamin D FFQ had to reflect the food consumption of the last month as we consider the 15-day half-life of 25(OH)D in circulation [58]. Therefore, participants were asked to indicate whether they had consumed the selected food items in the previous month in increasing six frequencies (monthly and weekly basis): never or less than once a month; 1–3 d/month; 1 d/week; 2–4 d/week; 5–6 d/week; every day [59]. Two open questions were asked at the end of the questionnaire to address the usual participant consumption of foods that were not included in the FFQ (frequency, brand/type and quantity) in addition to any nutritional supplements of vitamin D during the last month (type, dosage and frequency of dietary supplements).
The amounts of food consumed per day were computed by multiplying the averages of the frequencies taken as a standard unit (i.e., one serving/week = 0.14 serving/day) with the mean of the serving size range that the participants reported [56]. As a result, the daily vitamin D intakes were calculated by multiplying the quantities of Food consumed per day by the value of the vitamin D content per 100 g of product.
As no Moroccan food composition database that provides the food amount values of vitamin D is available, the nutritional content was derived from the most recent versions of the French CIQUAl food composition database [55]. The Nutrient Database for Dietary Studies 2015–2016 of the United States Department of Agriculture National Food (USDA) [60] was used when values were missing in the previously cited database.
Finally, in order to obtain the most reliable estimate of intake, the vitamin D content value for local and fortified Food (e.g., breakfast cereals and oils) were investigated to brand level detail and packages’ labeling. When necessary, we contacted companies to obtain the nutrient values of their product. A nutrient calculation tool was built in-house to evaluate vitamin D intake derived from the FFQs using Microsoft ® Excel® 2013.
Before starting the validation study, the FFQ was pre-tested to address content and comprehension-related issues, in a convenience sample ($$n = 25$$) who did not participate in the main study. The timing to answer the developed FFQ took approximately 20 to 30 min.
## 2.3. Description of the 7d-FR
We choose to incorporate vitamin D dietary intake from 7d-FR as a first reference technique in the method of triads in order to collect accurate quantitative information on individual food consumed during the validation period [59]. The food record, in contrast with the FFQ, is open-ended, does not rely on memory, and includes a direct estimate of portion size [28].
Moreover, with seven consecutive recording days of the week, food diaries overcome the within-person variation in food consumption, which is essential in women due to the significant weekday effect [60].
All participants were asked to register their typical consumption for seven consecutive weekdays and one weekend day. The seven days diet record was administered to study participants, with detailed instructions for filling in their diary.
For each day, the subject had to record six eating occasions (breakfast, morning snacks, lunch, afternoon snacks, dinner, and evening snacks.), a detailed description of the date, time of the meal, the menu, the food types and drinks (i.e., use of whole, semi-skimmed, or skimmed milk, the type of fish consumed, etc.) the food preparation methods, the ingredients of mixed dishes, recipes and the brand name of commercial products where appropriate. The portion sizes were expressed as common household measures (e.g., bowls, cups, plates and glasses), standard units or units such as grams or liters). A photograph aids for standard Moroccan household measures [57], and an example of one correctly filled in the day was also provided to participants to help them record precise quantities of food consumed. Participants were also requested to indicate if they took a vitamin D or multivitamin supplement, consistent with the FFQ or the EDR assessment.
For the estimate of vitamin D intake, the diet records were linked to the same food composition databases as for the FFQ (CIQUAl food composition database, the USDA) [54,58].
## 2.4. Sun Exposure Questionnaire (SEQ)
Dosimetry is the optimal method to assess sun exposure. However, a sun exposure questionnaire may provide similarly result, as statistically significant correlations have been reported between the two methods [61]. Thus, in our study, we developed the SEQ to objectively evaluate participants’ sun exposure during the last month and to address related environmental factors that account for the strength of UVB rays in the Moroccan context.
In summary, the SEQ (see in Supplementary Materials, Table S2) was designed according to previous studies [62,63,64,65,66,67]. It includes three domains of modifiable factors that influence vitamin D3 production in the skin. The indoor and outdoor sun exposure factors reflect time, frequency of sun exposure and body parts exposed to the sun. The tired domain describes participant’s different sun protection behaviors. All domains compute 15 items, and each item is scored on a scale of 0 to 4.
The sun exposure score (SES) is calculated as the product of the summed domains factors rating values, multiplied by one on the five points score attributed to each non-modifiable factor which are participant phototype (type I to type VI) and weather characteristics during the study period.
As a result, the SES was used to stratify participant sun exposure levels according to a score of 0 to 30. The sun exposure level was considered as insufficient if SES < 17, moderate if SES = 7.5 to 15, sufficient if SES = 15 to 30 and very sufficient or high if the score is > 30 [67].
To ensure the questionnaire’s clarity and comprehensibility, 30 university students who were not enrolled in the study took part in a pretest. Afterwards, the questions were revised based on the outcomes of the pretest.
The final questionnaire was administered to the sample population. The reliability of the questionnaire was assessed by internal consistency using Cronbach’s alpha, with an acceptable cutoff value of 0.7 [68].
## 2.5. Vitamin D Status Biomarker Assessment (25(OH)D)
The serum 25(OH)D analysis took place in a medical analysis laboratory of Mohamed V hospital in Meknes using electrochemiluminescence protein binding assay (ECLIA) using Roche Diagnostics, Cobas e411 analyzer. Registered nurses collected venous blood samples in EDTA tubes from all the participants in the study. All tubes were centrifuμged, and serum was stored at −80 °C until analysis.
A serum 25(OH)D concentration <20 ng/mL was considered a vitamin D deficiency, whereas a serum 25(OH)D concentration <30 ng/mL but >20 ng/mL define an insufficiency. Optimal status was considered a serum 25(OH)D ≥ 40 ng/mL [69] which is the level found in humans living naturally in sun-rich environments [70,71].
## 2.6. Anthropometry Measurement
Anthropometric measurements were performed while participants were minimally clothed and without shoes. The weight in kilograms was measured with a digital scale (SECA®), with a precision of 0.5 kg. The calibration of the devices was carried out using a known weight. Height was measured with a portable stadiometer (SECA 214) to the nearest 0.1 cm. Body Mass Index (BMI) was calculated as weight in kilograms divided by height in meters squared. Anthropometric status was categorized using classification according to BMI as follows: Underweight: BMI<18.5kg/m2, Normal: BMI: 18.5–24.9 kg/m2, Overweight: BMI 25–29.9 kg/m2, and obese ≥30 kg/m2 [72].
## 2.7. Statistical Analysis
Before analysis, the data were checked for normality of distribution using Kolmogorov-Smirnov and Shapiro-Wilk tests (n > 50), respectively. Data were non-normally distributed. Consequently, only non-parametric tests were used during the analysis. Descriptive data analysis was reported as medians, interquartile range in addition to means, standard deviations (SD) and percentage where applicable.
A range of statistical methods was conducted to assess the validity of the VitD-FFQ against the 7d-FR and the biomarker.
Firstly, Wilcoxon signed-rank test was used to compare the mean intake differences between the VitD-FFQ and 7d-FR. An effect size (r) was calculated where a large effect was 0.50 or higher, a medium between 0.30 and 0.5, and a small effect was between 0.10 and 0.30 [73].
The Bland–Altman scatterplots were used to investigate the level of agreement at an individual level visually. Bias and Limits of agreement (LOA) were calculated. We calculated the BA index based on how many differences lie outside the LOA. BA <$5\%$ was used as standard value for good agreement [74,75]. Regression analysis was also performed to quantify the proportional bias effect on the estimated intake difference between the VitD-FFQ and the 7d-FR [76].
Estimates from VitD-FFQ and each reference method (7d-FR and biomarker concentration) were grouped by quartiles for cross-classification (Individuals intakes belonging to the same quartiles, adjacent (±1) quartiles, or entirely misclassified (by ≥ two quartiles). It is recommended that at least $50\%$ of participants are correctly classified, and less than $10\%$ of participants are grossly misclassified into the opposite quartiles for each nutrient [77]. The weighted kappa statistic was used alongside cross-classification for another level of agreement. The weighted kappa statistic was calculated based on the observed and expected percentage of agreement from the cross-classification table. To interpret the kappa statistic the following standards were used: 0–0.20 = poor; 0.21–0.60 = acceptable; >0.61 = good [76,78].
Spearman Rank Correlation Coefficients were used to determine correlations between serum 25(OH) D concentrations, Vitamin D dietary intakes assessed by the FFQ and the 7d-FR, participants’ socio-demographic characteristics, SES and anthropometric measures (BMI). The magnitude of the correlation was set between −1 and +1, indicating the strength of the relationship. Correlation coefficients of (±0.8 to ±0.9 = very strong correlation, ±0.60 to ±0.70 = moderate correlation, ±0.20 to ±0.5 = fair correlation, and less than ±0.20 was a poor correlation[78].
Multiple linear regressions were applied to create models explaining 25(OH) D serum concentrations in all participants using potential predictor variables. The studied models were designed to compare, in particular the impact of vitamin D intake estimated by the VitD- FFQ and the 7dFR on the vitamin D status of participants. The linear correlation was studied between the dependent and explanatory variables using Spearman rank coefficient. Assumptions for the predictive models were tested by checking no multicollinearity (using variance inflation factors-VIF), multivariate normality and homoscedasticity of the residuals. A VIF > 10 was used to remove the variable from the model [77].
The triangular approach to validation, known as the method of triads, as described previously by Ocke and Kaaks in 1997 [29], was used to estimate validity coefficients between ‘unknown’ true nutrient intake and vitamin D intake estimated by the FFQ and 7d-EDR as subjective methods and the objective biomarker (25(OH)D concentration).
At first, the Spearman correlation coefficients were used to correlate vitamin D intake between the three dietary assessment methods (FFQ and EDR, FFQ and biomarkers, EDR and biomarkers). Next, the validity coefficient for the dietary assessment methods was calculated, and the estimated true ‘unknown’ vitamin D intake value (T) was according to the following equations:ρ QT = √[(rQR ∗ rQB)/rRB] ρ RT = √[(rQR ∗ rRB)/rQB] ρ BT = √[(rQB ∗ rRB)/rQR]. where: ρ = the validity coefficient, Q = FFQ; $R = 7$d-DR andB = serum 25(OH) D concentration The validation coefficient is considered as low (<0.2), moderate (between 0.2 and 0.6) or high (>0.6).
The calculated validity coefficient FFQ (ρQI) was considered as the upper limit and the correlation between the biomarker and vitD-FFQ was interpreted as the lower limit.
The $95\%$ confidence intervals for the validity coefficients were estimated using bootstrap sampling, where 1000 samples of equal size ($$n = 152$$) were obtained with replacement from the study participants. In addition, we applied sensitivity analyses to adjust the approach of triads for covariates that were predictive of the serum 25(OH)D concentration among our participants [29].
All statistical analyses were performed in R version 3.4.2 [2017-09-28]. A p-value of < 0.05 was considered significant for this study.
## 3.1. The VitD- FFQ Items Presentation
The VitD-FFQ developed for this study included 78 items, as shown in Table 1.
Items of the VitD-FFQ consisted of 8 groups: dairy products and beverages, eggs, fish and sea products, meat and products, fat products (butter, margarine and oil), breakfast cereals, bakery and Moroccan biscuits, chocolate and cacao. In addition, two items were added at the end of the questionnaire to quantify vitamin D nutritional and other vitamins D-rich food consumption.
Example of the VitD- food frequency questionnaire for Moroccan women of reproductive age: items of cow milk and canned fish are provided as a supplementary file (see in Supplementary Materials, Table S1).
## 3.2.1. Study Participant’s Characteristics
In total, 152 women of reproductive age were included in this validation study. They had good-quality FFQ and FR and gave a blood samples. Table 2 present the characteristics of the study participants. The median age was 25 years (IQR ±11; range 20–44). In this case, 14 women ($9.22\%$) were employed at the time of the study, while 138 participants ($90.78\%$) were mostly students ($72.46\%$) and housewives ($18.31\%$). The majority of the participants ($73.68\%$) had a university education degree or higher, while $16.44\%$ and $9.88\%$ of them had, respectively, secondary level and primary one. Most of the women participants ($61.84\%$) resided in urban while the remaining ($38.15\%$) resided in rural areas.
The median length of our female participants was 1.64 m (IQR: ±0.06), while the median weight was 70 kg (IQR: ±17). Thus, the median BMI was 26.45 (IQR: ±7.67), with the majority of participants ($75\%$) classified as having, respectively, overweight ($45\%$), obesity ($20\%$) and severe obesity ($10\%$).
## 3.2.2. Sun Exposure Scores and Related Factors
The SEQ (Table S2) achieve an acceptable internal consistency (Cronbach’s alpha = 0.73).
The median SES was 15.75 (±8.25) as shown in Table 3. The participant median (± IQR) scores for SEQ domains factors 1, 2, and 3 were 9.00 (±2.00), 16.50 (±10.75) and 6.00 (±5.00), respectively. Scores for each domains factor and the total SES increased significantly as sunlight exposure increased from low to high (all $p \leq 0.001$). When the SESs were interpreted, more the vast majority ($96.37\%$, $$n = 147$$) were classified as having, respectively ($55.26\%$, $$n = 84$$), sufficient and moderate ($41.44\%$, $$n = 63$$) sunlight exposure (see in Supplementary Materials, Table S3).
## 3.2.3. Vitamin D Status, Dietary Intake of Vitamin D Estimated by the VitD-FFQ and the 7d-FR
The median dietary intakes were 6.33 ± 5.02 and 7.10 ± 6.95 for 7d-FR and FFQ (Table 4). The vitamin D intakes determined from participants’ 7d-FR ranged between 3.01 and 25.96 µg/ day, whereas intakes estimated using the FFQ ranged from 3.28 to 21.60 µg/ day. None of the women participants in the study reported taking a vitamin D3 supplement.
In order to evaluate the change in vitamin D estimated intake between the two methods, a Wilcoxon sign rank test revealed a statistically insignificant difference in median vitamin D intake between the FFQ and the 7d-FR (Z =−1.538, $p \leq 0.05$). Thus, based on the positive Wilcoxon rank, the FFQ appears to overestimate the study participants’ vitamin D intake by 24 ($15.78\%$). However, the overall effect size is small ($r = 0.08$) (Table 4).
Based on the average derived intake of the VitD-FFQ (8.77 (±4.98) μg/d) and 7d-FR (8.16 (±4.78) μg/d) within the validation study sample, respectively, $90.78\%$ and $84.21\%$ of participants had vitamin D intakes below the recommended daily allowance (RDA) (15 μg/day) by the Moroccan Ministry of health as well as the European Food Safety Authority. Moreover, $62.5\%$ and $70.72\%$ of participants’ reported intakes (in the FFQ and the 7d-FR, respectively) were below the world health organization and Institute of Medicine (IOM) recommendations (10 μg/d).
The major contributor to vitamin D intake in the VitD-FFQ was fish and seafood ($52.90\%$), followed by milk and dairy products, including yoghurt and processed cheese ($15.36\%$), eggs ($11.36\%$), meat and meat product ($8.45\%$) and fortified food (margarine, vegetable oil, and butter) ($4.6\%$).
Median (IQR) serum 25(OH)D concentrations for the study sample were 8.48 ± 6.55, and the average (SD) was 9.35 ((±5.38). The values ranged between 3–29.29 (ng/mL) (Table 4). Thus, all participants had a low level of serum circulating 25(OH) D, in which 144 ($94.7\%$) participants were classed as deficient (<20 ng/mL). The remaining 8 ($5.3\%$) participants were insufficient (20 ng/mL <vit D <30 ng/mL) (Figure 2).
## 3.2.4. Association between Vitamin D Status, Dietary Intake, Sun Exposure Score, BMI and Socio-Demographic Characteristics of the Participants
Serum 25(OH) D status of all participants was significantly associated with vitamin D intake estimated by the FFQ (rho = 0.46), the 7d-EDR (rho = 0.36) and the total sun exposure score (rho = 0.36) (all $p \leq 0.01$). The strength of those correlations is fair (0.2< r < 0.5). Geographic localization and BMI were negatively associated with vitamin D status (respectively, rho = −0.15, rho = −0.17, $p \leq 0.05$). However, this correlation appears to be poor (rho < 0.20). No significant associations were shown between vitamin D status and socio-demographic participant’s characteristics (age, employment and education degree) (Table 5).
## 3.2.5. Predictors of Serum 25(OH) D
Table 6 displays the association between participant serum 25(OH)D levels and explanatory variables as established by the regression analysis. The two models identified distinctively three variables as significant predictors of serum vitamin D concentration. VitD-FFQ vitamin D intake, sun exposure score, and urban localization are combined in the first model. In contrast, 7d-FR vitamin D intake, sun exposure score and BMI are combined in the second. Each model explains significantly $47\%$ of the variance ($p \leq 0.001$) in serum vitamin D concentration. In addition, serum 25(OH) D concentration increased further when vitamin D daily intake was assessed by the VitD-FFQ rather than the vitamin D intake reported in the 7d-FR. 25(OH)D concentration increased by +0.56 ng/mL for each +1 uμg/day vitamin D intake (FFQ) versus +0.42 ng/mL for each 1 uμg daily vitamin D intake (7d-FR). Similarly, each positive unit change in the total sun exposure score may increase the 25(OH) D concentrations almost equally in the two models (+0.32 ng/mL in model I versus +0.34 ng/mL in the model II. The sun exposure score seems to be the most contributing variable in the vitamin D status over the two models ($R = 0.47$, $p \leq 0.001$). In model I, participants who live in an urban area may also have higher vitamin D levels +3.17 ng/mL. In model II, a 1 kg/m−2 increases in BMI may reduce serum 25(OH) D concentration of −0.16 ng/mL.
## 3.3.1. Bland-Altman Analysis between VitD-FFQ and 7d-FR
Figure 3 presents the Bland Altman agreement plot. Overall, there was an agreement between vitamin D intake from FFQ and vitamin D intake from 7d-FR. The bias between the vitamin D intakes from the two methods was 0.60µg/day. The upper agreement limit was 9.81, and the lower agreement limit was −8.61. Approximately $96.71\%$ of vitamin D intakes were within the agreement limits. Only 5 ($\frac{5}{152}$) outlier observations (Four positives and one negative) occurred outside the $95\%$ agreement range for the nutrient intake. Thus, the BA index is $3.29\%$. No correlation between the mean and the difference in vitamin D estimated intake using the 7d-FR and the VitD-FFQ was found in the linear regression analysis (R2 = 0.002, $$p \leq 0.545$$), indicating that there is no proportional bias (i.e., the mean vitamin D intake increases as the differences between the means increase).
## 3.3.2. Cross-Classification and Weighted Kappa Cross-Classification of Vitamin D Intake into Quartiles by VitD-FFQ and Validation Methods (7d-FR and Status)
The quarterly categorization of vitamin D intakes and concentration distribution was used to assess the consistency between the three methods of estimate: VitD-FFQ, 7d-FR and 25(OH) D (Table 7). For participants in the same quartile, the serum concentration of vitamin D compared to the intake estimate from the VitD-FFQ recorded the lowest value ($45.39\%$). The percentage of participants classified in the same quartiles according to the intake estimated by the VitD-FFQ and the 7d-FR was $59.21\%$. However, the cross-classification test reflects the agreement at the individual level. In contrast, the opposite quartile (%) showed that intake assessment by the VitD-FFQ and the two validation reference methods (7d-FR, the objective biomarker) had good validity at the individual level (≤$10\%$).
The weighted kappa showed an acceptable classification agreement at the individual level, respectively, between both the VitD-FFQ and7d-FR (0.37, $95\%$ CI: 0.27–0.46) and the FFQ-25(OH)D (0.28, $95\%$ CI:0.18–0.38) (Table 6). A result between 0 and 1 for the weighted kappa coefficient is commonly expected agreement (excluding chance) at the individual level. Negative numbers imply an agreement “worse” than can be predicted by chance alone, whereas values of zero or near zero indicate “no more than pure chance” [78].
## 3.4. Application of the Method of Triads Model
The results from the method of triads are presented in Table 8. A significant correlation was clear between each of the three measurements in the method of triads, suμggesting a moderate association between estimates of vitamin D intake by VitD-FFQ and 7d-EDR (rQR = 0.64, $95\%$ CI −0.53–0.73, $p \leq 0.01$) and a fair association between VitD-FFQ and participants 25(OH)D serum concentrations (r QB = 0.46, $95\%$ CI −0.32–0.59, $p \leq 0.01$)) as between and vitamin D intake form the 7d-FR (rRB = 0,36, $95\%$ CI −0.36–0.50, $p \leq 0.01$)) and 25(OH)D concentrations.
The overall validity coefficient calculation for the VitD-FFQ with true intake was 0.90 ($95\%$CI: 0.89–0.92), indicating high validity. The validity coefficient between FFQ and the true intake range from 0.46 to 0.90. Whereas the validity coefficients for the 7-DR and biomarker -serum 25(OH)D were 0.70 ($95\%$CI: 0.58–0.78) and 0.53 ($95\%$CI: 0.35–0.63), respectively (Table 8 and Figure 4).
Additional adjustment for covariates (sun exposure score and BMI) of the participants improved the coefficients for the biomarker (validity coefficient 0.63 ($95\%$ CI 0.39–0.82) but had no considerable effect on the estimates for the other validity coefficient of the VitD-FFQ that remain high (0.72, $95\%$ CI 0.51–0.92).
## 4. Discussion
Regarding the prevalence of hypovitaminosis D among Moroccan women and its possible implications on reproduction, assessing the dietary intake of this nutrient is critical for surveillance, mainly when undertaken with an adequate and well-validated FFQ.
In terms of usability, the newly developed FFQ is a semi-quantitative, self-administered and does not require specialized nutritional skills to be complete. Thus, we presume that this FFQ is practical for epidemiological research to reduce the cost of hiring interviewers and to elude social desirability bias in participants’ responses that interviewers’ presence may promote [28]. The ease of administration of this FFQ is enhanced by incorporating portion size based on standard Moroccan household measures and local market product packaging. Participants could complete this FFQ within 20 to 30 min which seems to be the average time appropriate for FFQ administration [28]. The VitD-FFQ food groups were organized on a list rather than meals, as neither option significantly affected nutrient estimates from the questionnaire in the literature [79]. The number of food items in the VitD-FFQ is within the range recommended for FFQ construction [28] and agrees with other FFQs developed to assess vitamin D intake in women [32,33,80,81,82] where items length ranged from 4 [80] to 161 food items [82].
As no accepted gold standard for measuring dietary intake exist, the errors of the two dietary assessment methods employed in the current study had to be as independent of one another as possible [27]. Food diaries allow for the long-term monitoring of participants’ eating patterns and account for any potential variations in dietary habits between weekdays and weekends [83]. Previous studies have utilized food diary methods, biomarkers of serum 25(OH)D concentration, or both to validate vitamin D-specific FFQs in women and various populations [30,31,32,33]. Thus, the validity of the VitD-FFQ was evaluated against criterion of 7d-FR and vitamin D status biomarker according to the method of triads.
Our results show a mean vitamin D intake assessed by FFQ of 8.77 (±4.98) uμg/day, similar to the estimated intake in other validation studies [30,32,84]. However, the median of the FFQ was 7.10 ± 6.95 uμg/day and seems to be higher than studies with published data for adult women from Qatar (5.98 uμg/day) [80], Libya (5.1 ± 5.7 uμg/day) [85], Korea (5.13 ± 3.50 uμg/day) [82] Ireland (4.91 uμg/day) [35], Uk (5.4 ± 7.7 uμg/day) [34], and Serbia (2.7 ± 1.7 uμg/day) [33]. This discrepancy may be attributed to differences in the participant’s age [28], which was broader in some studies [35,81], and the choosing time frame of diet recall [28] that reflected consumption over the 3previous months [85], six months [34,35] and 12 months in [82], compared with last month reporting intake in our study. Moreover, in other studies, we attempted to shorten the FFQ food items to only four main rich vitamin D foods [80], which may lead to underestimating nutrient intake [86].
A consistent finding among published studies is that vitamin D intake estimates by FFQs tend to average $3.12\%$ [33] to $51.59\%$ [34] higher than intake estimates by reference methods, including food diaries obtained over 3 to 14 days [32,34,35,80,81]. In line with this, our results showed an overestimation of FFQ-derived vitamin D compared with the FR estimates (+$10.84\%$) that referred, however, to a small effect size ($r = 0.08$). A possible explanation for these differences is that respondents’ dietary vitamin D intake from 7days-FR was underestimated because they did not consume vitamin D-rich food during the research validation days.
In addition, the results from the Bland–Altman plot support a good agreement between the two methods of dietary intake (VitD-FFQ and 7d-FR). The BA index was $3.29\%$, which is <$5\%$, a recommended standard for validation [74,75]. Similarly, in a validation study of vitamin D-specific FFQ against three days FR, conducted among Qatari women, Ganji et al. obtained a BA of $3.23\%$ [80]. Park et al. compared two FFQs, the *Korean calcium* assessment tool (KCAT) and the *Canadian calcium* assessment tool (CAT), to estimate calcium and vitamin D intake in Korean women. The results showed a BA index of $3.1\%$ for women under 50 and $3.9\%$ in the total population, demonstrating an agreement between the FFQ and the reference method [82]. Moreover, the estimates of vitamin D intake obtained by the VitD-FFQ were comparable to those from the 7d-FR recalls (small mean difference) with no observed proportional bias [74]. The agreement interval approximately was near the national recommended daily vitamin D intake of 15 uμg/day. These findings indicate that the developed VitD-FFQ may perform consistently in populations with greater mean intakes and capture population intakes at or above the RDA threshold. Furthermore, this result makes our FFQ particularly appealing for application in epidemiological screening for dietary vitamin D intake inadequacy.
The dietary vitamin D intakes reported by either dietary assessment tool were generally low, and did not meet in the majority of the participant, the reference intakes recommended by international and national guidelines. Consequently, all women participants in this validation study present a hypovitaminosis D condition (25(OH)D < 30 ng/mL) and significant rate of vitamin D deficiency ($94.7\%$) consistently with previous national studies [38,39,87]. The entire vitamin D participant intake, however, was obtained from natural food sources with no reported use of dietary supplements. These results align with other studies revealing that consuming vitamin D-rich food without food supplements is insufficient to cover physiological needs in most cases ($97\%$ to $100\%$) [82,83,84]. Indeed, according to 14 randomized control trials conducted in the MENA region and published between 2012–2017, supplementary doses of 1000–2000 IU/d may be necessary to reach a desirable 25(OH) D level at the target of 20 ng/mL [88].
On the other side, as stated earlier, the Moroccan food market provides affordable fortified food products to which vitamin D is added voluntarily, such as margarine breakfast cereals, processed cheese and yoghurt. However, it should be noted that no formal control is conducted on this product to determine its exact nutrient content. As a mandatory practice, 340 IU/liter of vitamin D3 is added to milk. This level corresponds to $17\%$ of RDA [52]. In addition, $90\%$ of edible oil is fortified with vitamin D3 at a rate of 300 IU/g, which satisfies $30\%$ of daily needs [53]. However, the consumption of all fat-fortified products (margarine, vegetable oil, and butter) in our study sample represented only $4.6\%$ of the total intake. In contrast, animal sources food (fish and seafood, milk and dairy product, eggs, meat and meat product) had a dominant contribution to the total daily vitamin D intake, assessed by the VitD-FFQ. Our participants’ young age profile (mean age: 26.6 ± 6.66 years) may support the findings, indicating a generational shift away from traditional Moroccan dietary models and toward a more westernized dietary pattern in which dairy products are increasingly contributing to intake [89]. Much more, several studies concluded that vitamin D was bioavailable in fortified milk and yoghurt and improved 25(OH) D status as well as markers of bone turnover [90,91]. Hence, the nutritional value and the resulting position of milk and milk products in the daily diet of youth highlight in our context the need for increased fortification of these products. The current fortification levels are likely insufficient to meet physiological requirements even in countries where vitamin D food fortification is mandatory [92].
The vitamin D status remains dependent on many factors [15] Above all else, we underlined individual sun exposure that greater affects the cutaneous production of 25(OH) D and may have a more significant impact on vitamin D status than dietary sources [14]. In the current study, we employed a specially designed questionnaire (SEQ) to assess participants’ UVB exposure while estimating their food intake over the previous month, which corresponded to the early spring season (March–April). The computed SES showed a fair significant correlation with 25-OHD levels (rho = 0.36, all $p \leq 0.01$) as our data indicated that the extreme majority of the participant was classified as having moderate ($41.44\%$) to sufficient sunlight ($55.26\%$) and the 25-OHD levels in the different categories of sunlight exposure (insufficient, moderate, sufficient, and high) significantly increased as sunlight exposure moved from moderate to high levels ($p \leq 0.001$) (see in Supplementary Materials, Table S4). Evenly, our finding is consistent with the previous research when a questionnaire scoring system was used. In a tropical setting, a study by Mansibang et al. [ 2020] on 75 adult Pilipino showed that most participants ($80\%$) had moderate sunlight exposure in summer. A significant correlation was computed between the sun exposure score and 25(OH) D ($r = 0.396$, $p \leq 0.001$) [93]. Furthermore, the average serum 25-OHD was higher in each of the sunlight exposure groups as compared to our findings (low sunlight exposure group 17.51 ± 5.96 ng/mL; moderate sunlight exposure group 26.78 ± 6.55 ng/mL; high sunlight exposure group 30.97 ± 5.88 ng/mL) [93]. Among a South Asian population and subtropical sitting in Pakistan, Humayun et al. found that the mean short-term sun exposure questionnaire scores had a fair correlation to the 25-OHD levels in summer ($r = 0.36$) and winter ($r = 0.43$) [94]. Such comparisons may lead to misinterpretation, due to differences in locations and seasons of the conducted studies [95]. In addition, measuring sunlight exposure is complex, as every personal and environmental factor increases the chance of inaccuracy [96]. The association between individual UV exposure and serum 25(OH) D concentrations when using a questionnaire is expected to be low [96].
Furthermore, we developed two predictive models for vitamin D concentration, comparing the contribution of vitamin D intake of the VitD-FFQ and the 7d-FR in the 25(OH)D concentration variance. We account, in addition, for all participants’ characteristics and factors that may influence serum vitamin D concentration. The set of predictors included in our final models explained about $47\%$ of the total variability in vitamin D concentration. The most consistent contributor to the predictive ability of the vitamin D status models was sun exposure. Evenly, all the predictors (BMI, urban localization and sun exposure) found herein had various association strengths with the vitamin D concentration and have been identified as consistent predictors of low 25(OH) D levels across the lifecycle in the MENA region [88]. In particular, we demonstrated that natural food vitamin D intakes were, significant predictors of vitamin D status and that the FFQ performed better than the FR in the objective measures’ prediction. The FFQ intake account for $56\%$ of 25(OH) D levels variance while 7d-FR explain $36\%$ of the variance. Such finding was not reported previously. In the one published validation study that performed a regression model to explain vitamin D status among athletes, total dietary vitamin D intakes assessed by a three-month recall FFQ and seven-day food records, as well as vitamin D supplement intakes, were unable to predict vitamin D status across all time seasons. BMI and tanning bed were the only predictors in winter and spring [84]. Main raisons that must be considered to interpret theses different results are associated to the food products fortification amount adopted in each country and variation in eating habits. Thus, using serum 25(OH) D concentrations as a biomarker for FFQ validation is challenging and has its limitations due to the influence of several factors other than diet.
In FFQs validation studies, correlation coefficients greater than 0.7 are uncommon. This phenomenon is known as the “ceiling of validity” and is attributed to the fact that a structured questionnaire cannot fully capture the inherent complexity of the human diet [97]. According to this, studies showed that for most nutrients, correlation coefficients with biomarkers are 0.3 to 0.5 [28]. Similarly, in our result, the absolute Spearman rank-correlation coefficient between total vitamin D intake assessed by the FFQ and biomarker showed a significant moderate association ($r = 0.46$). However, correlations were slightly better between FFQ and biomarker than between EDR and biomarker (rho = 0.36), which is reasonable because the FFQ and EDR are two methods that estimate dietary intake while, the biomarker status can be influenced by more factors than diet, such as sun exposure. Herein, it is essential to consider the different timeframes for each dietary exposure measure in this study. The FFQ expresses dietary habits over the past month, the EDR on the intake of one week, and the serum biomarkers are likely to represent the preceding month of dietary intake considering the half time of 25(OH) D in 15 days. Thus, the true EDR correlations may be underestimated due to differing time frames. Moreover, there may be another factor, such as the high educational level of our research participants (university degree in 73.68 % of cases), which generally affects recall of diet by FFQs [28].
In addition, vitamin D intake estimated by the FFQ showed moderate (rho = 0.63) levels of relative validity compared with the 7d-FR. This correlation was consistent with the strength of correlations observed in previous validation research (using food records), reporting a correlation coefficient of 0.56 [34,98]. Far more, cross-classification analysis, in contrast to correlation, could provide accurate and unbiased sight of how the FFQ performed [27]. In our results, the cross-quartile data agreement at the individual participant level between the intake assessment by the VitD-FFQ and the 7d-FR and serum 25-(OH)D biomarkers was $10\%$ gross misclassification (opposite quartile), with computed kappa values (k) of 0.37 and 0.28, respectively, indicating acceptable classification agreement. These results support the ability of the FFQ to adequately rank women participants to their vitamin D intake categories in a similar way as the reference methods [76] and exclude pure chance in the interpretation of the predicted agreement [78]. Moreover, our findings are consistent with prior validation studies that included female participants and used a food record [32,82] or both 24h recall and biomarker as reference methods [85].
The validity coefficients between the ‘true’ intake (I) of vitamin D and for the FFQ (ρ QT = 0.90) as well as the 7d-FR (ρ RT = 0.70) were higher than those for the serum biomarker (ρ BT = 0.53) which was moderate. Moreover, the observed validity coefficient for the FFQ tended to be higher than those for both the dietary reference method (FR in current research) and the biomarker. Our results are similar to most studies that used the method of triads model for validation of vitamin D FFQ among women of reproductive age: ρ QT = 0.84 [33], and as well as among mixed groups of man and women ρ QT = 0.92 [34], ρ QT = 0.88 [35]. The method of triads model assume that random errors between the three methods are independent and that all three measurements have a linear relationship with the unknown true intake [29]. Violation of this assumption is more common when 24hR or food records are used as reference methods since they all, as the FFQ, rely on self-report. Positively correlated measurement errors may lead to an overestimation of the validity of the FFQ [29]. Using data from self-reported questionnaires and nutritional biomarkers should provide extensive insight when quantifying dietary vitamin D FFQs and FR. According to Kaaks et al. [ 30], althouμgh biomarkers can be measured more objectively, they do not necessarily reflect dietary intake better than self-reported intake. Only a few recovery biomarkers (i.e., 24 h urinary nitrogen for protein intake) directly reflect quantitative dietary intake. However, most nutritional biomarkers, such as vitamin D, which are concentration markers, are presumed to be associated with intake but do not reflect absolute nutrient intakes. Moreover, differences in biomarker concentrations can occur due to intrinsic variability (i.e., bioavailability and metabolism) [28], genetic [99] and environmental factors [96].
Based on this fact, we considered the validity coefficient FFQ (ρQI) as the upper limit and the correlation coefficient of FFQ and biological markers (rQB) as the lower limit of the validity coefficient between FFQ and the true intake. With this approach, we observed a lower limit of the validity coefficient of 0.46 and an upper limit of 0.90. Hence, the overall validity varies from moderate to high and further demonstrates that our developed FFQ is valid for assessing vitamin D intake in Moroccan women. Furthermore, the $95\%$ confidence intervals for the validity coefficients in our study are narrow, and the upper limit for all intervals is lower than 1. This strength reflects the accuracy of the validity coefficient and an absence of random sampling variations between dietary methods or violations in the underlying assumptions of the model [27,43].
Moreover, after controlling for the most influencing confounding (Sun exposure and BMI), the strength of the biomarker’s validity coefficient improved from moderate to high (0.53 to 0.63). However, the validity coefficients of both dietary assessment methods (FFQ and FR) almost remain high (0.72) when controlling for participants BMI. However, to improve the intake estimation by the dietary methods, it is also imperative to adjust nutrient intakes for the total energy intake. Studies showed that subjects tend to underreport energy intake in FR and over-report energy intake in FFQ. Unfortunately, our FFQ was not designed for energy assessment, so we cannot account for potential dietary misreporting in the present study [100]. In other validation studies, we found a comparable association between total vitamin D consumption measured by the FFQ and the vitamin D biomarker using the energy-adjusted Spearman rank-correlation coefficient and the crud data [33].
We acknowledge that our study has some limitations. The primary limitations lie in the study’s cross-sectional nature due to time and logistic constraints. Thus, all data were collected on only one occasion for each participant. The FFQ was not validated in all four seasons, which may be essential in the study design, given the seasonal variation in vitamin D intake. In addition, we recruited a large sample of 150 women participant for a validation study using biomarker as reference method [44], but it may not represent Moroccan women regarding specific social characteristics such as education level. Indeed, illiteracy is common in Morocco’s general population, whereas most of our study sample was composed of students with a high level of education. Furthermore, a selection bias might have been present as a participant were all volunteers, mainly from the university community and were promised a vitamin D status result and medical advice at the end of the study. However, forcing unmotivated subjects to participate in the study may impact data quality [100].
The study had several strengths. First, the development and validation of vitamin D-specific FFQ was the first initiative in Morocco. Our results describe vitamin D dietary intake in Moroccan women, which correlates with vitamin D status for the first time. This information could be valuable in developing dietary guidelines, especially when no other types of relevant data are available. Another essential feature of the developed FFQ is that easy to use and practical. It includes a comprehensive list of fortified foods we attempted to collect in the local market to ensure representativeness and precision in estimating intakes based on product labels. Second, participants were trained and motivated by qualified professionals to complete the FFQ and the FR without contributing to misclassification, which is an essential factor that favorably impacts data collection quality [101]. The FFQ has also been developed in both French and Arabic, reducing the impact of language barriers and promoting self-administration.
Lastly, the major strength of our study is the multiple statistical approaches to assess agreement between methods and comparisons with previous studies using the method of triads that have demonstrated the completeness and validity of our FFQ. We assessed the agreement between VitD-FFQ and FR and the biomarkers with different statistical tests (i.e., BA plot, cross-quartile classification, weighted K, and correlation). Based on these tests, we achieved an acceptable to good agreement between the vitamin D intakes from VitD-FFQ and 7d-FR. More importantly, we validated the newly established FFQ using a triangular approach to overcome the dependent errors that may be present in dietary assessment methods (herein, the FFQ and FR methods). As a result, we reported on how individual risk factors affected the computation of the triad method’s validity coefficients and the predictive ability of 25(OH) D3 in regression models. We demonstrated a reasonable accuracy of estimates and interpretation of the results. Furthermore, the correlation between the circulating 25(OH) D concentrations and dietary intake assessed by the VitD-FFQ confirms that the significant confounding effect of sun exposure was effectively controlled, such that vitamin D status in our participants was attributed to food consumption. Further Moroccan research may benefit from using the established VitD-FFQ and the SEQ to generate detailed data on how sun exposure factors and vitamin D intakes may impact vitamin D status in women, particularly during the summer season.
## 5. Conclusions
In this validation study applying the method of triads, results indicate that the developed VitD-FFQ demonstrated high criterion validity for estimating absolute vitamin D intake among Moroccan women of reproductive age. This FFQ can serve as a valuable tool in research to assess usual dietary vitamin D intake and identify women at risk for vitamin D deficiency, particularly in resource-limited settings. Further studies, however, are required to determine the FFQ reproducibility and its validity in other groups of the Moroccan population. The study showed, in addition, a high prevalence of vitamin D deficiency in the study sample, strengthening the epidemiological evidence that vitamin D deficiency is widespread in Moroccan women and dietary intake is an essential determinant. A national strategy is needed to address this public health concern.
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|
---
title: 'A Single-Group Study on the Effect of OnabotulinumtoxinA in Patients with
Chronic Migraine Associated with Medication Overuse Headache: Pain Catastrophizing
Plays a Role'
authors:
- Licia Grazzi
- Danilo Antonio Montisano
- Paul Rizzoli
- Erika Guastafierro
- Alessia Marcassoli
- Arianna Fornari
- Alberto Raggi
journal: Toxins
year: 2023
pmcid: PMC9967692
doi: 10.3390/toxins15020086
license: CC BY 4.0
---
# A Single-Group Study on the Effect of OnabotulinumtoxinA in Patients with Chronic Migraine Associated with Medication Overuse Headache: Pain Catastrophizing Plays a Role
## Abstract
Pain catastrophizing and cutaneous allodynia are commonly altered in patients with chronic migraine associated with medication overuse headache (CM-MOH) and tend to improve in parallel with clinical improvement. The relation between pain catastrophizing and cutaneous allodynia is poorly understood in patients with CM-MOH receiving OnabotulinumtoxinA therapy. In this single-arm open-label longitudinal observational study, patients with CM-MOH were assigned to structured withdrawal and then administered OnabotulinumtoxinA (5 sessions on a three-month basis, 195 UI per 31 sites). Headache frequency, medication intake, disability, impact, cutaneous allodynia and pain catastrophizing were evaluated with specific questionnaires. In total, 96 patients were enrolled and 79 completed the 12-month follow-up. With the exclusion of cutaneous allodynia and the magnification subscale of the pain catastrophizing questionnaire, all variables showed significant improvement by the sixth month, which was maintained at 12 months. Reduction of pain catastrophizing, and particularly of its helplessness subscale, was a significant predictor of reduction in headache frequency and medication intake. Pain catastrophizing is often implicated in the clinical improvement in patients with CM-MOH receiving behavioral treatments, but, in this study, also showed a role in patients receiving OnabotulinumtoxinA; combining OnabotulinumtoxinA and behavioral treatments specifically addressing pain catastrophizing might further enhance patients’ clinical outcome.
## 1. Introduction
Chronic migraine (CM) is a primary headache disorder, a progression of episodic migraine (EM), that is characterized by a headache frequency of fifteen or more headache days/month, of whom at least eight per month exhibit typical migraine features, for at least 3 consecutive months [1]. It is often associated with the overuse of symptomatic drugs and, as such, can be seen as a comorbidity for a secondary headache disorder, medication overuse headache (MOH) [1]. MOH is itself characterized by 15 or more headaches/month for more than 3 months: it develops as a consequence of regular medication overuse, and it usually resolves once the overuse is stopped. Specific criteria exist for assigning the MOH diagnosis on the basis of the kind of overused drugs: basically, 15 or more analgesics per month, or 10 or more of the other drugs used to treat migraine, for more than 3 months. The prevalence of MOH ranges between $1\%$ and $2\%$ in the general population [2] and it is associated with poor quality of life (QoL), significant disability, and increased societal burden and cost [3,4,5,6].
As CM-MOH is a condition in which clear biological, psychological and social components are jointly present—i.e., a condition with a biopsychosocial etiology [7]—its treatment should account for each of them, and is therefore based upon three main pillars: [1] withdrawal of overused drugs and prescription of tailored prophylaxis, [2] management of psychological triggers, such as stress, if not direct treatment of mental health aspects, such as anxiety and depression, and [3] education on lifestyle issues (e.g., diet, sleep, physical exercise) [8,9].
Migraine-specific prophylaxis may involve both pharmacological and non-pharmacological treatments, the latter basically including neuromodulation, nutraceuticals and behavioral approaches [10]. Among pharmacological prophylaxis agents, many medications are available, including antidepressants, anti-epileptics, anti-hypertensives, OnabotulinumtoxinA and the newly marketed monoclonal antibodies [11,12,13]. OnabotulinumtoxinA is among the most well-tolerated and safest prophylactic treatments for CM [14,15,16,17], with several studies showing efficacy [16,17], and its therapeutic indication is for CM only.
Different hypotheses have been postulated about the mechanism of action of OnabotulinumtoxinA. When OnabotulinumtoxinA is injected, it enters in the cell cytoplasm cleaving the C-terminus of Synaptosomal-Associated Protein, 25 kDa (SNAP-25), which is the target of botulinum neurotoxin type A both in motor nerve and in sensory nerve terminals. This may result in the inhibition in the release of neuropeptides, inflammatory peptides, substance P, glutamate and calcitonin gene-related peptide (CGRP) within the central nervous system, thus playing a therapeutic role in migraine prevention [18,19]. Its efficacy in headaches other than migraine as well as the factors associated to therapeutic success, however, are not completely clear [20,21].
Several factors have been shown to promote migraine “chronification”, or persistent increase, such as metabolic factors, comorbidities, genetic predisposition, lifestyle, medication overuse, and psychological factors [22,23,24,25,26,27,28,29,30]. Among the latter, pain catastrophizing has been postulated as a potential mechanism of action in the progression of migraine frequency [27,28,29,30]. Pain catastrophizing is a common psychological trait among individuals with migraine, detected in around one fourth of the patients [31], and it is defined as a negative anxiety-driven set of emotions in response to anticipated or actual pain. It is characterized by a set cognitive and emotional features in response to pain, including persistent and invasive thoughts about pain, exaggerated worries about pain and its consequences, and perceived helplessness in response to pain [32]. Patients with high-levels of pain catastrophizing also report higher subjective pain experiences [33]; in fact, pain catastrophizing is considered as a risk factor for pain severity, pain-related disability, psychological distress, and improper use of medications such as analgesics [34].
Pain catastrophizing has been shown to have a role in the process of improvement, in particular following behavioral interventions such as mindfulness and acceptance and commitment therapy [30,35,36,37], but also in relation to pharmacological prophylaxis with erenumab and galcanezumab [38,39], as well as in educational programs [40]. On the contrary, relations between catastrophizing and migraine in patients on OnabotulinumtoxinA therapy was not systematically addressed, with a single study showing improvement in catastrophizing over a six-month period in patients with CM-MOH receiving OnabotulinumtoxinA treatment [41].
The relationship between pain catastrophizing and other variables often implicated in pain experience, such as external locus of control (i.e., the idea that individuals have little possibility to control events) and cutaneous allodynia (i.e., the perception of pain in response to typically innocuous stimuli to the skin, such as heat, cold, or pressure), is poorly understood in patients with CM-MOH receiving OnabotulinumtoxinA therapy.
With this study, therefore, we aimed to enhance our understanding of the role of allodynia and pain catastrophizing in particular by addressing their improvement in patients receiving OnabotulinumtoxinA according to the PREEMPT protocol (Phase III REsearch Evaluating Migraine Prophylaxis Therapy) [42], and by exploring their potential predictive effect on the main outcomes used in headache research, namely headache frequency and medication intake.
## 2. Results
A total of 96 patients were included in the study, 85 ($88.5\%$) were females; mean age was 46.9, SD 9.0, and the mean migraine duration was 28.6 years, SD 9.5. With regard to overused drugs, 40 ($41.7\%$) were triptans over-users only, 16 ($16.7\%$) were analgesics over-users only, and the remaining 40 ($41.7\%$) overused multiple drug classes; additionally, 44 ($45.8\%$) patients showed ASC-12 score ≤ 2, indicative of no allodynia; 29 patients ($30.2\%$) reported headache on a daily basis.
Table 1 reports the differences between study completers and drop-outs for all study variables as measured at the baseline evaluation: no significant differences were observed in any of them. None of the patients complained about adverse events throughout the 12 months.
A total of 17 patients dropped-out before the study’s completion, so longitudinal analyses were carried out over the records of 79 patients. Table 2 reports the longitudinal course of headache frequency and of the other clinical variables. Almost all of the variables showed a significant improvement between baseline and six months, which was then maintained up to 12 months, but no further improvements were recorded after the sixth month. The only exceptions to this were ASC-12 and PCS-Magnification, which were basically stable along the three time points.
Table 3 and Table 4 report the results of the linear regression model predicting the reduction in headache frequency and medication intake between baseline and 6 months. The delta in PCS-Helplessness subscale between baseline and 6 months was the only significant predictor in both models, which accounted for $9.7\%$ of headache frequency reduction and for $12.5\%$ of medication intake reduction.
Table 5 reports the results of the linear regression model predicting the reduction in headache frequency between baseline and 12 months. The delta in PCS-Helplessness subscale between baseline and 12 months was the only significant predictor, and the model accounted for $11.6\%$ of headache frequency reduction.
Table 6 reports the results of the linear regression model predicting the reduction in medication intake between baseline and 12 months. The delta in PCS total score between baseline and 12 months was the only significant predictor, and the model accounted for $10.9\%$ of medication intake reduction.
## 3. Discussion
The results of this study showed that over 12 months, patients with CM associated with MOH who received OnabotulinumtoxinA as prophylaxis according to the PREEMPT study [42] underwent a significant reduction in headache frequency and medication intake, as well as in a set of outcomes such as headache severity, disability, impact and pain catastrophizing, but not allodynia.
OnabotulinumtoxinA is one of the most effective and safest among the available preventive treatments for migraine [14,15,16,17] and the results of our study confirm this. Although we did not implement a systematic data collection for adverse events, none of the patients reported events preventing return to normal activities or requiring treatment interruption, such as some of those reported in a pooled analysis on OnabotulinumtoxinA trials, e.g., neck pain, muscle weakness, facial paresis, stiffness, or respiratory problems [43]. In terms of effect, we showed a reduction by 7.9 days per month at six months ($95\%$ CI: 5.6 to 10.3 days) which was maintained at 12 months (mean difference 8.0 days per month, $95\%$ CI: 5.6 to 10.3 days). A recent meta-analysis by Lanteri-Minet and colleagues on patients with CM showed a higher average level of improvement, i.e., 10.6 days ($95\%$ CI: 9.2 to 12.3) at six months and 10.3 ($95\%$ CI: 5.7 to 14.5) at 12 months [44], and a likewise higher decreased in HIT-6. It has to be noted that, however, the features of the patients herein enrolled are likely different from those resulting from such a pooled analysis. Lanteri-Minet and colleagues did not report average scores for baseline variables, but it has to be noted that for some variables our sample was clearly different; in particular, disease duration was significantly longer (29.2 ± 10.9 years in our study; comprised between 2.4 ± 3.5 and 25.7 ± 12.3 in Lanteri-Minet’s review), whereas HIT-6 was likely lower. In fact, the average HIT-6 score of our patients would place them at the sixth rank out of all the studies which reported HIT-6 (19 studies in total): in a sense, the lower degree of reduction might be due to the lower impact at baseline. Finally, it is difficult to compare the drug intake analysis, as we included the total amount of intake, whereas the review from Lanteri-Minet and colleagues addressed days with acute medication intake.
Patients did not report any significant variation in allodynia scores, as measured by ASC-12 questionnaire, throughout the 12 months of the present study. In previous study in which the ASC-12 was used in patients with CM treated with OnabotulinumtoxinA, a significant ASC-12 decrease was instead observed [45]. However, compared to the patients enrolled by Ozarslan and colleagues [45], the group of patients enrolled in our study reported a lower baseline ASC-12 score (4.4 on average in our study, 6.5 on average in the study of Ozarslan and colleagues). In addition, although the majority of patients in the present sample had ASC-12 scores suggestive of cutaneous allodynia ($54.2\%$ of the cases), such a percentage is lower compared to that observed in other studies, e.g., $92.5\%$ by Benatto and colleagues [46], $70.5\%$ by Mathew and colleagues [47], $67.7\%$ by Barbanti and colleagues [48] and $62.7\%$ by Buse and colleagues [49].
The role of pain catastrophizing remains an intriguing psychological concern in migraine patients, as well as in those with chronic pain. Pain catastrophizing is strictly related to several pain-related outcomes, including pain expression, disability and mood impairment, as well as with several physiological, cognitive, affective and interpersonal factors associated with pain [34]: thus, improvement in pain catastrophizing is expected to produce improvement in pain severity, and eventually vice versa. Pain catastrophizing is a common facet of migraine, being present in around one-fourth of the patients and associated with migraine attacks severity and migraine chronification, as well as disability, particularly among those with CM [31,50,51,52], and it has been shown to improve following non-pharmacologic interventions [35,37,52,53,54]. However, improvement in pain catastrophizing following pharmacological treatment was, to the best of our knowledge, previously reported in two real-life studies on erenumab and galcanezumab [38,39], and for the first time in the present study following OnabotulinumtoxinA treatment.
Such an improvement in pain catastrophizing is of primary clinical relevance, as it is associated with decreased quality of life, and greater use of healthcare services and longer hospital stays in pain-related syndromes [55,56]. In particular, among migraine sufferers it is associated with higher attacks frequency, poor treatment response, increased medical consultation, higher disability and lower health-related quality of life [57]. The fact that it not only improves after treatment, but that pain catastrophizing improvement was an independent predictor of both the six-month and the twelve-month reduction in headache frequency and medication intake, with the adjusted model accounting for $9.7\%$ to $12.5\%$ of the variance in these outcomes, provides further evidence to the importance of such a dimension. In particular, improvement in the helplessness dimension (i.e., patients’ belief that they can do nothing to alleviate pain), seemed to play a role in determining the observed improvement among our patients. We hypothesize that through the therapy patients gathered confidence and ability in managing both acute treatments’ use, recognizing when they are really needed, and thus limiting the amount of days with headache. Parallel to this, it has to be taken into account the administration modality of OnabotulinumtoxinA: in fact, the three-month periodic meeting with the neurologist, which encompass discussion on the clinical course of migraine (clearly only in real-world settings) clearly plays a role in inducing clinical advantage related to an improvement of mental constructs.
Some limitations need to be acknowledged. First, we did not have a control condition, for example another kind of pharmacological prophylaxis: therefore, we cannot entirely disentangle the effect of the specific treatment with OnabotulinumtoxinA from that of the general clinical improvement. The regression models we applied provide justification on the direction of the relation: however, a strict causal relation explaining headache frequency and medication intake reduction cannot exclude OnabotulinumtoxinA treatment which, being an inclusion criterion, cannot be part of the regression models. Second, it was a monocentric study, with the sample being drawn from a third-level specialty center where patients with a considerable disease severity and long history of CM-MOH are expected to attend. Third, in relation to the previous limitation, it has to be taken into account that clinicians working in our center promote patients’ awareness of their mental states and on the correct use of medication. The degree to which such an approach promoted the aforementioned improvement in pain catastrophizing, which had an independent effect on headache frequency and medication intake reduction, cannot be ascertained: however, it cannot be completely ignored. Finally, a note on the possible effects of imputation on the precision of estimates is needed. In fact, the error term that is produced by the imputation is likely lower than the error that would be produced by “real cases”. The implication of this is a possible bias the relations between different variables: this in turn might produce a degree of precision in the imputed values which is higher than warranted, and the predictive power of regression models might be overestimated. However, we think that, considering the trend observed among real cases (i.e., a wide improvement between baseline and 6 months, and then substantial stability over the next six months) and the fact that we imputed only the 12 month values, the overall results of our study would not be significantly different if attrition was smaller. Therefore, we deem that the overall degree of bias can be acceptable.
## 4. Conclusions
In conclusion, the results of this study show that headache frequency, medication intake and pain catastrophizing improved in patients receiving OnabotulinumtoxinA prophylaxis for CM-MOH. Such an improvement is evident at six months from the inception of the treatment, and is maintained up to 12 months. Moreover, pain catastrophizing, and particularly its helplessness dimension, was predictive for decreased headache frequency and medication intake over 12 months.
Learning how to manage headache pain is a process that deals with avoiding catastrophizing in relation to pain. It is reasonable to presume that combining OnabotulinumtoxinA prophylaxis with a behavioral treatment specifically addressing pain catastrophizing might further on enhance patients’ clinical outcome.
## 5.1. Study Design and Patients’ Selection Criteria
A longitudinal single-arm open-label retrospective observational study design was implemented. Clinical documentation of patients who met the criteria of the International Classification Headache Disorders, third version (ICHD-3) [1] for Chronic Migraine (CM, code 1.3) with associated Medication Overuse Headache (MOH, code 8.2) and who received OnabotulinumtoxinA as prophylaxis following the PREEMPT protocol [42] were included. Known intolerance to OnabotulinumtoxinA and pregnancy constituted exclusion from the treatment. All patients signed an informed consent form for the standard treatment and a second for the use of retrospective data: the study was retrospectively authorized by the Institute’s Ethical Committee (approval n. $\frac{66}{2022}$, 14 September 2022). Patients were enrolled between January 2018 and December 2019.
Patients were enrolled at the time they entered a structured in-hospital withdrawal treatment, which was organized in a day hospital regimen for 5 days in order to stop the overuse of symptomatic medications. The main pillars of structured withdrawal included [58,59]: intravenous hydration, intravenous steroids, oral benzodiazepines, oral or intravenous metoclopramide or indomethacin if needed for intense rebound headache. Overused drugs were abruptly stopped, and tailored counseling on the correct use of medications was provided. As part of patients’ education, recommendations on the consumption of at least three regular meals per day, sleep hygiene (7–8 h of sleep per night) and on physical activity (20–30 min per day of moderate level physical activity) was included. All patients were advised to stop work or any other activity during the withdrawal and to stay at home and rest as much as possible after the therapy.
Once structured withdrawal was completed, patients were administered OnabotulinumtoxinA as prophylaxis following the PREEMPT protocol [42]: 5 sessions on a three-month basis, at the dosage of 195 UI per 31 sites. The PREEMPT protocol is now a standard for treatment of CM-MOH and patients have access to it by co-paying the whole cost, which for approximately $80\%$ is covered by the Italian National Health System. Patients were followed up for one year.
## 5.2. Research Protocol
Monthly headache frequency, measured with headache diaries, was used as primary endpoint. In addition to headache frequency, diaries included a section on the total intake of symptomatic medications. Both headache frequency and medication intake were evaluated at each OnabotulinumtoxinA administration, i.e., every three months. Other collected data included measures of disability and severity, impact, cutaneous allodynia and catastrophizing attitude: these questionnaires were administered at the baseline, at six and at twelve months.
Disability and average headache severity were measured with the Migraine Disability Assessment (MIDAS) [60]. The MIDAS is composed of seven items referred to the preceding 3 months. The first five address the influence of headache in different domains and patients have to refer the number of days in which: they were completely unable to carry out paid and schoolwork activities (item 1) or limited in $50\%$ or more of their ability in the same activities (item 2); completely unable to carry out household work (item 3), or limited in $50\%$ or more of their ability in the same activities (item 4); finally, the fifth item addresses the number of days in which headaches had an impact (full or partial) over leisure activities with family or in social situations. MIDAS score is the sum of responses to questions 1–5, it ranges between 0 and 270, and four severity grades are available: minimal (0–5), mild (6–10), moderate (11–20), and severe (>21) disability. The last two items investigate the total number of days with migraine attacks and the average pain intensity (0–10 scale).
The Headache Impact Test (HIT-6) [61] is a 6-item scale that measures lost time in 3 domains and other areas of impact (e.g., pain severity, fatigue, and mood), based on patient’s recall of the previous past 4 weeks. Each item is rated on a scale ranging from “never” to “always”, and HIT-6 total score ranges between 36 and 78, with higher scores indicating greater impact: scores ≥ 60 are indicative of a severe impact.
The 12-item Allodynia Symptom Checklist (ASC-12) [62] was used to measure cutaneous allodynia. The ASC-12 is composed of items reflecting situations in which increased unpleasant skin sensation or pain can be experienced during a migraine attack (e.g., combing hair, putting eyeglasses on, resting face on a pillow). For each of the 12 items patients have to respond identifying how often they experience such a sensation (never, rarely, less than half of the time, half of the time or more), and they can also reply that the item does not apply (e.g., people who do not wear contact lenses or earrings). Never and rarely are scored as 0, less than half of the time is scored as 1, half of the time or more is cored as 2, so that the total score range is 0–24. ASC-12 score 0–2 indicates no allodynia, 3–5 mild allodynia, 6–8 moderate allodynia and 9 or more indicates severe allodynia.
The Pain Catastrophizing Scale (PCS) [63] was used a measure of catastrophizing as it relates to pain, i.e., an exaggerated negative mental set brought to bear during actual or anticipated painful experience. The PCS is composed of 13 items that form three subscales, which identify the dimensions of rumination (the constant thinking about pain), magnification (the exaggeration of pain and of its consequences), and of helplessness (the belief that there is no or limited possibility that pain may improve). Items are to be rated between 0 and 4 (from “not at all” to “all the time”) and total PCS score ranges between 0 and 52, with higher scores indicating a higher tendency to catastrophize, and scores ≥30 indicating clinically significant levels of catastrophizing.
## 5.3. Data Analysis
Due to the important drop-out rates related to COVID-19 pandemics, we operated a missing value imputation for those patients who were lost at the follow-up between the sixth and the twelfth month due to the important limitations in mobility imposed by the pandemic. In fact, almost half of the study participants could did not attend follow-up (45 out of 96), of whom approximately two-thirds (28 of 45 patients) dropped-out between month six and month twelve during the first waves of COVID-19 pandemics in 2020. The last observation carried forward approach was used for missing data imputation. The rationale for this was that our analysis showed that the variation in the herein used endpoints was reported between baseline and six months and, conversely, no change or only minimal changes were observed between six and twelve months.
We calculated baseline differences between study completers (including those who were imputed) and drop-out using independent-sample t-test, and longitudinal differences using a repeated-measures ANOVA, with Bonferroni post-hoc analysis. Mauchly’s W test of sphericity was used, and Hyun-Feldt or Greenhouse–Geisser corrections were used when sphericity was violated: the Hyun-Feldt correction was used when Mauchly’s W test was higher than 0.75, and the Greenhouse–Geisser when W was lower than 0.75.
Finally, four multivariable linear regression models were implemented to address the predictors of the following: headache frequency change between baseline and six months and between baseline and twelve months; medication intake change between baseline and six months and between baseline and twelve months. Predictors were the respective change, i.e., delta between baseline and six months and delta between baseline and twelve months, in ASC-12, PCS-total and PCS subscales. A backward approach was used, with variables entered together and then excluded if they were not significantly associated to the outcome (i.e., exclusion criterion was p-value ≥ 0.05).
Data were analyzed with SPSS 28.0.
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|
---
title: 'Risk Prediction for the Development of Hyperuricemia: Model Development Using
an Occupational Health Examination Dataset'
authors:
- Ziwei Zheng
- Zhikang Si
- Xuelin Wang
- Rui Meng
- Hui Wang
- Zekun Zhao
- Haipeng Lu
- Huan Wang
- Yizhan Zheng
- Jiaqi Hu
- Runhui He
- Yuanyu Chen
- Yongzhong Yang
- Xiaoming Li
- Ling Xue
- Jian Sun
- Jianhui Wu
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967697
doi: 10.3390/ijerph20043411
license: CC BY 4.0
---
# Risk Prediction for the Development of Hyperuricemia: Model Development Using an Occupational Health Examination Dataset
## Abstract
OBJECTIVE: Hyperuricemia has become the second most common metabolic disease in China after diabetes, and the disease burden is not optimistic. METHODS: We used the method of retrospective cohort studies, a baseline survey completed from January to September 2017, and a follow-up survey completed from March to September 2019. A group of 2992 steelworkers was used as the study population. Three models of Logistic regression, CNN, and XG Boost were established to predict HUA incidence in steelworkers, respectively. The predictive effects of the three models were evaluated in terms of discrimination, calibration, and clinical applicability. RESULTS: The training set results show that the accuracy of the Logistic regression, CNN, and XG Boost models was 84.4, 86.8, and 86.6, sensitivity was 68.4, 72.3, and 81.5, specificity was 82.0, 85.7, and 86.8, the area under the ROC curve was 0.734, 0.724, and 0.806, and Brier score was 0.121, 0.194, and 0.095, respectively. The XG Boost model effect evaluation index was better than the other two models, and similar results were obtained in the validation set. In terms of clinical applicability, the XG Boost model had higher clinical applicability than the Logistic regression and CNN models. CONCLUSION: The prediction effect of the XG Boost model was better than the CNN and Logistic regression models and was suitable for the prediction of HUA onset risk in steelworkers.
## 1. Introduction
Hyperuricemia (HUA) is a metabolic disorder disease that develops due to abnormal purine metabolism, resulting in elevated serum uric acid (SUA) concentrations [1]. A 2014 meta-analysis covering 16 provinces, municipalities, and autonomous regions in China showed that the prevalence of HUA in China was $13.3\%$ ($19.4\%$ for men and $7.9\%$ for women) [2]. Another meta-analysis in 2021, which included 2,277,712 subjects, showed that the prevalence of HUA had increased to $16.4\%$ ($20.4\%$ for men and $9.8\%$ for women) [3]. Previous studies have shown that the prevalence of HUA in China has doubled in the last 20 years and has become another public health problem of concern after diabetes [4]. Worldwide, the burden of gout has increased in 195 countries and regions, especially in developed countries and regions [5]. HUA is not only an early stage of gout but also an independent risk factor for coronary heart disease, hypertension, diabetes, and chronic kidney disease [6], which seriously endangers human health.
The steel industry is a pillar industry of the Chinese economy and directly employs as many as two million people. The health status of the workers is directly related to the development of the Chinese steel industry. It has been pointed out that steelworkers are exposed to occupational hazardous factors such as shift work, high temperature, and noise for a long time, and also have unhealthy habits such as smoking, alcohol consumption, and a high-salt diet, which cause or affect the risk factors of HUA differently from the general population [7]. Therefore, there is an urgent need to develop new risk prediction models for steelworkers’ morbidity, which can be used to improve the quality of life and health status of steelworkers.
Logistic regression is a traditional prediction model commonly used in the medical field and is widely used for a variety of disease predictions because of its clear parameter meaning and easy-to-understand outcome metrics. The convolutional neural network (CNN) is a feedforward neural network with a deep structure that is good at mining local features of data and extracting global training features and classification and has some advantages that traditional techniques do not have [8]. XG Boost, known as eXtreme gradient boosting, achieves classification by iterative computation of classifiers, and the addition of its regular term ensures the model’s robustness and reduces the time to process features because it was good at handling missing data [9]. We established the above three HUA morbidity risk prediction models based on the medical examination data information of more than two thousand steelworkers and compared their prediction effects, aiming to select the optimal model and provide a theoretical basis for the health management of this special occupational group.
At present, the popularization of HUA in *China is* still insufficient, the prevention and treatment situation is not optimistic, and the awareness rate and cure rate of HUA among patients are low [10,11]. Therefore, screening risk factors affecting HUA to establish prediction models, early identification, detection, and intervention of HUA patients has great social value to prevent and control the development of HUA and reduce the burden of the disease.
## 2.1. Study Design and Participants
The present study was a retrospective cohort study, relying on the Chinese National Key Research and Development Program “Beijing-Tianjin-Hebei Regional Occupational Population Health Effects Cohort Study”, which completed the baseline survey from January to September 2017 and the follow-up survey from March to September 2019. A total of 2992 steelworkers were included in the study, and the inclusion criteria for the study population were formal employees of the unit; more than 1 year of service; non-HUA patients at the time of the baseline survey; and voluntary signing of the informed consent form. Exclusion criteria were age > 60 years; and those with incomplete information. The study was reviewed and approved by the Ethics Committee of North China University of Technology (approval number: 16004).
## 2.2. Data Collection and Preprocessing
The subjects of this study were workers in the production department of Tangshan Iron and Steel Group who participated in the health examination, and all information was obtained from the baseline and follow-up surveys of the Beijing-Tianjin-Hebei cohort, including questionnaires, physical examinations, and laboratory examinations. The final data set was randomly divided into the training set ($70\%$ of observations) and the validation set ($30\%$).
The questionnaire for the survey was developed by our team, one-on-one interviews were conducted by professionally trained PhD and MSc students from the School of Public Health of North China University of Technology to the workers of the steel enterprise.
Physical examinations were conducted by trained professional medical examiners according to standard testing methods for height, weight, blood pressure, and other indicators for workers in this enterprise.
For laboratory testing, fasting blood and morning urine were collected by the medical examination hospital before 9:00 a.m. daily and sent to the laboratory department of the medical examination hospital for uniform blood biochemical testing using a Myriad automatic biochemical analyzer (BS-800). The test indexes included fasting plasma glucose (FPG), uric acid (UA), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL), triglyceride (TG), lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), creatinine (Cr), urea nitrogen (BUN), etc.
## 2.3. Definition of HUA
According to the Practice Guidelines for the Diagnosis and Management of Hyperuricemia in Renal Diseases in China (2017 edition) [12], developed by the Nephrologist Branch of the Chinese Physicians Association, blood uric acid ≥ 420 μmol/L in men and ≥360 μmol/L in women are being treated for HUA during the follow-up survey.
## 2.5. Sample Size Calculation
The sample size calculation method for developing a clinical prediction model proposed by Richard et al. was used [21].
To ensure that the model could accurately predict the mean of the outcome events, the prevalence of hyperuricemia ɵ approximately $12\%$ [22] was reviewed in the literature, and the margin of error δ was set at 0.05, which was calculated to require at least 144 study subjects. [ 1]n=(1.96δ)2 θ(1−θ) In order to control the minimum mean error of all individual prediction values, the mean absolute error MAPE was set to 0.05, the expected shrinkage rate RCS2 was set to 0.1, and the predictor variable P was about 15, which was calculated to require at least 433 study subjects. [ 2]n=exp(−0.508+0.259ln(θ)+0.504ln(p)−ln(MAPE)0.544) To ensure that the expected shrinkage rate was $10\%$ and reduce model overfitting, S was 0.9, the study variable P was about 15, and it was calculated that at least 1274 cases of study subjects were required. [ 3]n=p(s−1)ln(1−RCS2s) To ensure that the difference between the developed model and RCS2 optimization adjustment value was minimized, RCS2 in Equation [4] was 0.1, maxRCS2 was 0.48, and S was calculated to be 0.81, which was calculated to require at least 600 study subjects. [ 4]s=RCS2RCS+δmaxRCS22 [5]n=p(s−1)ln(1−RCS2S)
It was calculated that at least 1274 cases were needed to establish the model sample, and a total of 2992 cases were included in this study. The sample size met the needs of the study.
## 2.6. Model Building
The current study consisted of two main phases: [1] variable screening and [2] model development. We used LASSO regression for variable selection, and we screened the significant variables among 54 clinical characteristics by compressing the coefficients to achieve the effect of variable screening. The code for the LASSO regression implementation is shown in Supplementary Material S1. Logistic regression models, CNN models, and XG Boost models were then developed based on the selected variables and literature review.
## 2.6.1. Logistic Regression Model
The logistic regression model was built using the Sklearn package of python 3.6. The code for the logistic model implementation is shown in Supplementary Material S2.
## 2.6.2. CNN Model
The CNN model was built using the Numpy package, and the sigmoid function was used as the excitation function. The code for the CNN model implementation is shown in Supplementary Material S3.
## 2.6.3. XG Boost Model
The XG Boost model was built using the Sklearn package, using the sigmoid function as the excitation function and the BCE (Binary Cross Entropy) binary cross entropy as the loss function. The code for the XG Boost model implementation is shown in Supplementary Material S2.
## 2.7. Model Evaluation
The prediction effectiveness of the model was evaluated in terms of discrimination, calibration, and clinical applicability. The discrimination index included sensitivity, specificity, Youden index, ROC curve, and area under the curve. The calibration index includes the Brier score, Log loss, and calibration curve. Clinical applicability was evaluated by DCA graphs.
## 2.8. Statistical Analysis
An Excel 2010 database was established based on the questionnaire and physical examination data to screen the risk factors for HUA in steelworkers, and a prediction model was established based on the screened variables. Count data were described as rates or composition ratios, and the χ2 test was used for comparison between groups; ordinal data were described as rates or composition ratios, and the Kruskal–Wallis test was used for comparison between groups. SPSS 26.0 and Python 3.9 statistical software were used. The test level α was set at 0.05, and both two-sided tests were used.
## 2.9. Quality Control
Design phase: review the literature and consult experts to modify and improve the subject scheme; data collection stage: investigators were uniformly trained. Double-checking of data entry was used, and manual and computerized checking of data entry and logical error checking were performed to ensure the authenticity of the data; *Data analysis* stage: randomly selected training set and test set.
## 3.1. Study Population
A total of 4518 steelworkers participated in the occupational health screening, removing 989 HUA patients, 385 missed visits, and 152 incomplete information from the baseline survey, resulting in a final cohort size of 2992. The study population was randomly divided into a training cohort [2094] and a validation cohort [898] in a ratio of 7:3, as shown in Figure 1.
## 3.2. Analysis of Study Population Characteristics
The cohort was followed up from March to September 2019 with a median follow-up time of 26 months and 465 new HUA patients and a crude incidence rate of $15.5\%$, including $16.31\%$ in men and $7.58\%$ in women. A comparative analysis of the basic characteristics of the workers in the training and validation cohorts revealed no statistically significant differences in the indicators, as detailed in Table 1.
## 3.3. Variable Screening
Predictor variables were screened by LASSO regression, and 6 predictor variables were finally screened out of 54 variables, including total cholesterol, BMI, blood pressure, waist circumference, creatinine, and DASH score, as shown in Figure 2. The figure on the left was the LASSO coefficient path diagram, where each curve represents the trajectory of the coefficient of each variable, and the variables first attributed to point 0 were excluded. The figure on the right is the cross-validation curve. The mistakes were the smallest when the parameters corresponding to the dashed line were selected, and the intersection of the dashed line and the abscissa coordinates corresponded to the Lambda in the left figure. Finally, six indicators with a large impact on the study outcome were screened. Throughout the literature review, we found that smoking, alcohol consumption, and physical activity were also important influencing factors of HUA [23], so they were added together to the subsequent model development.
## 3.4. Multicollinearity Test
The predictor variables were tested for multicollinearity, and we found that the variance inflation factors of all variables were greater than 0 and less than 1.4, and the tolerances were between 0 and 1. There was no multicollinearity problem, as shown in Table 2.
## 3.5. Evaluation of Model Effectiveness
The results of the training set of 2094 cases ($70\%$) showed that the XG Boost model was better than the other two models in terms of sensitivity, specificity, Youden index, F1 score, AUC ($95\%$ CI), Brier score, and Log loss, respectively. The CNN model had a higher classification accuracy of $86.8\%$. The Logistic regression model indicators were slightly worse, as shown in Table 3, ROC curves as shown in Figure 3a.
The results of the validation set of 898 ($30\%$) showed that the XG Boost model outperformed the other two models in terms of classification accuracy, sensitivity, specificity, Youden index, F1 score, AUC ($95\%$ CI), Brier score, and Log loss, respectively, as shown in Table 3, ROC curves as shown in Figure 3b.
The XG Boost model outperformed both the CNN and Logistic regression models in terms of Brier Score and Log loss, the calibration curves for both the training and validation sets were close to the diagonal, with no serious deviation from the results. Moreover, the XG Boost model performed best in terms of calibration accuracy, with the Logistic Regression model coming second and the CNN model deviating more from the diagonal, as shown in Figure 4.
The clinical decision curves for the three models are shown in Figure 5, among which the XG Boost model had the highest clinical applicability, and the logistic regression and CNN models had slightly worse clinical applicability. The nomogram of HUA risk in steelworkers was shown in Figure 6.
## 4. Discussion
In this study, we used LASSO regression for the screening of predictor variables, and eventually screened out 6 influencing factors among 54 predictor variables. LASSO regression was an advanced variable selection algorithm for high-dimensional data, and the complexity of the model can be simplified by constructing a penalty function to complete the screening of predictor variables [24]. Compared with the traditional stepwise regression method, LASSO regression can simultaneously process all independent variables at the same time, which not only effectively controlled model overfitting, but also made the model much more stable. On top of this, we added three influencing factors of HUA among steelworkers, such as smoking, alcohol consumption, and physical activity, found through the literature review, to improve the efficiency of the study. By comparing the predictive effects of the three different models, we found that the XG Boost model was the optimal model in this study and that the XG Boost model achieved better results in three areas: discrimination (AUROC 0.806), calibration (Brier Score 0.095), and clinical applicability. Our study highlighted the value of occupational health screening data in predicting HUA, and the screening of predictor variables may provide a scientific basis for the prevention and treatment of HUA in steelworkers.
The current study showed that overweight and obesity were important risk factors for the development of HUA in steelworkers, which is similar to the findings obtained from several previous studies [25,26,27]. Some studies have shown that obesity and the development of HUA were causally related to each other and were closely associated with unhealthy dietary habits, alcohol intake, and a sedentary lifestyle [11]. On the one hand, obese people tend to eat more meat, leading to increased exogenous purine intake and causing HUA. On the other hand, obese people ingest more energy than they consume, resulting in hyper-synthesis of purines in the body, leading to increased endogenous uric acid production [28]. An analysis of the US population found that BMI was the most important modifiable risk factor for HUA, with $44\%$ of the population attributing HUA to overweight or obesity [29]. Both previous and current studies suggested that controlling overweight and obesity was beneficial in reducing the incidence of HUA. Dietary factors were also another important factor influencing the occurrence of HUA. The DASH dietary pattern involved in the current study was originally designed and developed to control hypertension and was a dietary pattern focusing on plant-based foods and high-quality protein that not only significantly reduced blood pressure but had also been used for cardiovascular disease prevention. Regarding the effect of the DASH diet on the risk of gout, Sharan conducted a cohort study that included more than 40,000 study subjects with up to 26 years of follow-up, and their results showed that the DASH diet score was negatively associated with the risk of gout [30]. The possible mechanism for this was that the DASH diet was lower in purines, reducing the purine load in the body. In addition, the DASH diet may act by improving insulin resistance in order to reduce SUA levels [31]. The above study supported the view of the current study that the DASH dietary pattern was a protective factor for the occurrence of HUA in steelworkers. Eating more fruits and vegetables and controlling sugar intake can contribute to the primary prevention of HUA in steelworkers.
Some studies have shown that reducing smoking and alcohol consumption, and a less sedentary lifestyle, can contribute to the prevention of HUA [23]. Smoking or second-hand smoke can increase the risk of HUA and gout. The possible reason for this is that smoking can excite the autonomic nervous system and affect the metabolism of purines in the body, with the potential effect of elevating SUA. In addition, the harmful substances in tobacco can adversely affect the respiratory and circulatory systems, leading to slower blood circulation and impaired uric acid excretion [32]. Alcohol consumption was another important influencing factor in the development of HUA. Firstly, the metabolic process of ethanol in the body consumed a large amount of water, which made the SUA value high. Secondly, the metabolism of ethanol was very likely to produce lactic acid, which was excreted through the kidneys and prevents the normal excretion of uric acid [33]. A sedentary lifestyle could lead to increased uric acid due to slower blood circulation. Moderate exercise accelerates metabolism and facilitates the excretion of uric acid. Long-term moderate-intensity aerobic exercise and aerobic exercise combined with strength training could reduce SUA concentrations in HUA patients [34], and there is a positive correlation between the amount of exercise and the decrease in SUA when exercise is performed at aerobic intensity. The possible mechanism is that long-term moderate-intensity aerobic exercise may protect renal function by alleviating the inflammatory response and ameliorating renal injury through pro-uric acid-excretory protein expression. Exercise plays a direct or indirect role in reducing SUA [35].
In this study on the prediction of HUA onset in steelworkers, the XG Boost model achieved better results and was more suitable for the prediction of HUA onset risk in steelworkers. XG *Boost is* a classification supervision model based on multiple trees, which essentially took the sum of the predicted values of each tree as the final predicted value. XG Boost had excellent computational efficiency, predictive generalization ability, and overfitting control, making it a long-term dominant data science competition solution. Rajdeep used six different machine learning algorithms to predict obesity risk and achieved a classification accuracy of up to $97.87\%$ for the XG Boost model [36]. Savitesh predicted the risk of pre-diabetes in children and adolescents and found that XG Boost was the best classification model with a 10-fold cross-validation score of up to $90.13\%$. Savitesh integrated the XG Boost algorithm into a screening tool for completing the automatic prediction of pre-diabetes [37]. Shoukun performed miner fatigue identification based on physiological indicators from ECG and EMG and found that the XG Boost model had the best accuracy and robustness with a recognition accuracy of $89.47\%$ and AUC of 0.90, the recognition of miner fatigue based on the XG Boost model is feasible [38]. The unique ability of logistic regression to correct different prevalence rates made it widely used in medical research, but it showed the poor ability of correct classification and low sensitivity in this study. Although the classification ability of the CNN model was relatively strong, it performed poorly in calibration, possibly because it was better at dealing with image problems.
Our study has several advantages. Firstly, in the process of evaluating the sample size, we did not choose the empirical-based estimation algorithm of 10-fold EPV but used the calculation method proposed by Richard that guaranteed the expected shrinkage rate and controls the error of individual prediction values [21], which made the calculation of the sample size of the HUA onset risk prediction model for steelworkers more rigorous. Second, instead of the traditional stepwise regression method, we chose LASSO regression, which allowed for extensive variable screening in the selection of predictor variables. LASSO regression compensated for the shortcomings of stepwise regression in terms of local optimal estimation and effectively helped us in the selection of predictor variables. In addition, we added three recognized influences such as smoking, alcohol consumption, and physical activity, based on the literature review, making the development of a predictive model for HUA in steelworkers of public health significance. Third, during the development of the model, we made a comprehensive determination in terms of discrimination, calibration, and clinical applicability. Fourthly, we developed a nomogram to predict the risk of HUA in steelworkers. The nomogram was clear and intuitive. From the perspective of steelworkers, the nomogram could predict their own risk of developing HUA in the future, and from the perspective of clinicians, the nomogram could be used to quickly and accurately identify workers at high risk of HUA for targeted health education. By understanding their own risk of HUA and raising awareness of risk factors, steelworkers can change their unhealthy lifestyles accordingly and reduce the risk of illness.
Our study has certain limitations. Firstly, as data are not easily available, our study did not find a suitable dataset to externally validate the newly developed HUA risk prediction model for steelworkers. Secondly, we only used traditional machine learning algorithms and did not improve on the relevant algorithms. Therefore, in the future, we will further investigate new algorithms to improve the predictive performance of the model.
## 5. Conclusions
The prediction effect of the XG Boost model was better than the CNN and Logistic regression models and was suitable for the prediction of HUA onset risk in steelworkers.
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|
---
title: Growth performance, meat quality, and blood characteristics of finisher crossbred
pigs fed diets supplemented with different levels of green tea (Camellia sinensis)
by-products
authors:
- Nguyen Cong Oanh
- Cu Thi Thien Thu
- Nguyen Thi Hong
- Nguyen Thi Phuong Giang
- Jean-Luc Hornick
- Pham Kim Dang
journal: Veterinary World
year: 2023
pmcid: PMC9967713
doi: 10.14202/vetworld.2023.27-34
license: CC BY 4.0
---
# Growth performance, meat quality, and blood characteristics of finisher crossbred pigs fed diets supplemented with different levels of green tea (Camellia sinensis) by-products
## Abstract
### Background and Aim:
Dietary supplementation with green tea by-product shows special effects on animal parameters. This study aimed to assess the effects of green tea by-products (GTBP) in the diet on some blood parameters, growth performance, and carcass characteristics of finishing pigs and on meat quality, and nutritional composition of pork.
### Materials and Methods:
One hundred and sixty crossbred pigs with an initial body weight of 65.15 ± 0.38 kg, were distributed into four dietary treatments, with four replicates of 10 pigs each. The dietary treatments were a basal diet (control diet, CON), and three experimental diets (GTBP8, GTBP16, and GTBP24) based on the CON diet supplemented with GTBP at 8, 16, and 24 g/kg of feed. The studied parameters were examined during the experimental period of 10 weeks.
### Results:
No statistical differences in average daily feed intake, average daily gain, and feed conversion ratio were observed between the diet treatments ($p \leq 0.05$). Backfat thickness decreased (linear, $p \leq 0.05$) according to the GTBP levels but no other carcass parameters. Meat quality was not influenced by the GTBP levels ($p \leq 0.05$). However, pigs fed with GTBP had a decrease in cholesterol content and an increase in crude protein and total omega-3 content of pork compared to the CON diet ($p \leq 0.05$). Moreover, dietary supplementation with GTBP significantly decreased plasma cholesterol ($p \leq 0.05$), and trends for the decrease in low-density lipoprotein cholesterol and urea nitrogen were observed (linear, $$p \leq 0.08$$).
### Conclusion:
Up to 24 g/kg GTBP in the diet for finishing pigs does not impair animal performance and makes carcass leaner with softer meat as well as positive effects on cholesterol and fatty acid metabolism. Further experiments are needed to determine the optimal levels of GTBP addition in finishing pig diet to produce higher meat quality.
## Introduction
The growth performance of animals is affected by many factors such as sex, age, breed, feeding, and antibiotics. Antibiotics used in animal feed, such as higher growth rate, prevention of pathogen diseases, and enhancement of economic efficiency [1–3]. However, due to the occurrence of antibiotic-resistant bacteria and antibiotic residues in animal products, the use of alternative sources to antibiotics in animal feed is required, particularly those from medicinal plants, which are considered safe and effective agents in disease prevention, growth promotion, and quality enhancement of animal products [4–7]. Regarding human dietary habits in meat consumption, the most consumed meat in the world is pork [8]. Therefore, preserving and enhancing the growth performance and meat quality of pigs are necessary.
Green tea (Camellia sinensis), a variety of tea plants from the Theaceae family, contains a great number of bioactive compounds with numerous health benefits [9], so it is largely used for medicinal goals in many countries in the world [10]. Vietnam is now the 6th largest tea producer in the world, with 270 thousand tons produced per year [11]. However, a considerable amount of green tea by-products (GTBP) from the simple drying methods is presumed to be produced annually by tea producers to processing companies in Vietnam [12]. These by-products are potential sources of feed additives for animals but their exploitation is not effective. According to An et al. [ 12], GTBP from tea processing companies in Vietnam contains $35\%$ dry matter (DM), and on a DM basis, $18\%$ crude protein, $20\%$ crude fiber, and $28\%$ neutral detergent fiber. Moreover, GTBP still contains more than 200 bioactive compounds and 300 various substances showing antimutagenic, anticarcinogenic, and antioxidant activities [4].
Catechins (C), the main class of polyphenols found in green tea and GTBP, possess high biological activity. Dietary supplementation with green tea powder has been reported to improve average daily gain (ADG) and feed conversion ratio (FCR) in broiler chickens [13], goats [14], cattle [15], and fishes [16]. Moreover, dietary supplementation with green tea in animal diets decreased thiobarbituric acid reactive substances values and preserved the oxidative stability of pork and broiler meat [5, 17]. In addition, dietary supplementation with GTBP reduced cholesterol content and improved fatty acid composition in animal meat [14, 17, 18]. Offering GTBP to finishing pigs also resulted in positive effects on humoral and cell-mediated immunity [19]. Nevertheless, limited studies have been carried out to evaluate the effect of GTBP from the artisanal drying method in Vietnam on production parameters of pigs, while local beverage green tea companies produce an increased quantity of GTBP.
This study aimed to assess the effects of GTBP in the diet on some blood parameters, growth performance, and carcass characteristics of finishing pigs and on meat quality, and nutritional composition of pork.
## Ethical approval
The research protocol was approved by the Ethics Committees on Animal Experiments, Vietnam National University of Agriculture, Vietnam (Application VNUA - $\frac{2021}{05}$).
## Study period and location
This study was conducted from June to August 2022 at the experimental farm of the Faculty of Animal Science, Vietnam National University of Agriculture, Vietnam.
## Preparation of GTBP and composition analysis
The dried residues of buds and tea leaves were obtained from tea processing companies in Thai Nguyen province, Vietnam. The by-products were then ground into powder (GTBP). Samples were prepared for analysis according to the method of Vietnamese standards [20]. The main constituents of GTBP were analyzed for DM, crude protein, ether extract, ash, crude fiber, and neutral detergent fiber according to the association of analytical chemists’ methods [21]. The content of polyphenol was determined using the Folin–Ciocalteu method as previously described [22]. The amounts of individual Cs, including C, epicatechin (EC), epigallocatechin (EGC), EC gallate (ECG), and EGC gallate (EGCG) were analyzed using a Shimadzu LC-20A high-performance liquid chromatography system (Shimadzu, Kyoto, Japan), according to Balci and Özdemir [23].
## Experimental design, animals, and diets
A total of 160 crossbred growing pigs (80 males and 80 females, breeding: Duroc × (Landrace × Yorkshire), initial body weight: 65.15 ± 0.38 kg) were divided into four dietary treatments, balanced IBW, and gender, for 10 weeks feeding trial. Four replicate pens were assigned to each of the four treatments, with 10 pigs (five males and five females) per replicate pen. The effect of sex was not investigated in this study. Each pen (3.5 m × 4.3 m) was equipped with one automatic feeder and two automatic nipple drinkers. The temperature of pig house was around 26–28°C, while relative humidity was around $65\%$–$85\%$ over the entire experimental period. Each treatment was randomly allocated to one of four diets, including a basal diet (control diet, CON) and three other diets – GTBP8, GTBP16, and GTBP24 – based on the CON diet supplemented with GTBP at 8, 16, and 24 g/kg, respectively. Water and feeding were provided for ad libitum consumption over the entire experimental period.
Raw feed materials, including yellow maize, soybean meal, fish meal, rice bran, wheat bran, and others, were supplied and formulated by a local feed processing company. Nutrient levels of the basal diet met the recommended requirements for finishing pigs (Table-1) [24, 25].
**Table-1**
| Item | Basal diet |
| --- | --- |
| Ingredients (as-fed basis) | |
| Yellow maize | 386.0 |
| Soybean meal | 102.0 |
| Fish meal | 20.0 |
| Rice bran | 250.0 |
| Wheat bran | 200.0 |
| Limestone | 15.0 |
| Vitamin-mineral premi×1 | 5.0 |
| NaCl | 10.0 |
| Farm enzyme2 | 5.0 |
| L-lysine HCl, 98.5% | 5.0 |
| DL-methionine, 98% | 2.0 |
| Analyzed composition (% DM) | |
| DM | 88.8 |
| Crude protein | 16.5 |
| Ether extract | 7.78 |
| Crude ash | 7.56 |
| Crude fiber | 5.15 |
| Neutral detergent fiber | 18.0 |
| Calcium | 1.26 |
| Total phosphorus | 0.9 |
| Gross energy (MJ/kg DM) | 18.6 |
| Metabolizable energy3 (MJ/kg DM) | 14.6 |
| Lysine4 | 1.16 |
| Methionine4 | 0.5 |
## Pig performance
The animals were individually weighed using an electronic scale of 300 kg (accuracy 0.01 kg) at the beginning and finishing dates of the trial. The average daily feed intake (ADFI, kg/pig/day), ADG (g/pig/day), and FCR (kg feed/kg pig weight gain) were recorded and calculated for each pig, replicate pen, and treatment over the entire period of the experiment [26].
## Carcass traits
At the end of the trial, 48 pigs (12 pigs per treatment, two barrows, and two females per pen) were slaughtered by electrical head-only stunning followed by exsanguination. Hot carcass (kg), carcass weight (kg), killing-out percentage (%), dressing percentage (%), and backfat thickness (mm) were measured as previously described [27].
Longissimus thoracis muscle (LTM) samples at the middle of the 13th and 14th ribs were collected immediately after slaughter. Two subsamples of LTM (around 250 g) were taken from the left side of each carcass. The subsamples were distinctly weighed and placed in tight plastic bags. Then, one subsample was stored at 4°C for technological quality assessment at 24 h after slaughter. The other one was then kept at −20°C to analyze the chemical composition, cholesterol content, and total omega-3 fatty acids [28].
## Technological quality of LTM muscle
pH values were determined at two points time (45 min and 24 h), and other parameters of LTM were determined at 24 h postmortem. pH values were measured using a portable pH (pH-STAR, Germany). Meat color CIE Lab values (L* a* b*) were determined using the model CR-410 Chroma Meter (Minolta, Japan) as previously described by Choi et al. [ 29]. Drip loss and drip cooking percentages were determined as previously described by Oanh et al. [ 27]. Shear forces were recorded using a Warner-Bratzler shear machine (USA) [29].
## Chemical composition of pork
The chemical composition of LTM samples was analyzed through measures composed of DM content, crude protein content, lipid content, and total ash content, according to the AOAC method [21].
The content of cholesterol was analyzed using a Shimadzu GCMS-QP2010 gas chromatography (GC)–mass spectrometer (Shimadzu) as previously described by Derewiaka and Obiedziński [30]. The content of omega-3 fatty acids (C18:3n3, C20:3n3, C20:5n3, and C22:6n3) was measured using an Agilent 6890 plus GC equipped with a flame ionization detector (Agilent Technologies, USA), SP-2560 capillary GC column, according to the steps as previously described by Ding et al. [ 31].
## Blood and serum analyses
One day before the end of the experiment, 24 animals (six pigs per treatment, one barrow, and one female per replicate pen) were randomly chosen for blood sampling through the jugular vein using an 18-G needle, as previously described by Oanh et al. [ 6]. Briefly, aliquots of blood samples were separately placed in both Vacutainer tubes containing K2EDTA and serum tubes. Hematology parameters, including red blood cell count (RBC), white blood cell count (WBC), hemoglobin (Hb) content, and lymphocyte percentage, were determined using the hematology analyzer ABX Pentra DX 120c (Horiba Medical, Montpellier, France). The serum tubes were centrifuged at 3000× g at 4°C for 15 min, and the plasma samples were transferred to plastic vials. The concentrations of aspartate aminotransferase (AST), alanine aminotransferase (ALT), bilirubin, total cholesterol, creatinine, high-density lipoprotein, low-density lipoprotein (LDL), protein, and urea nitrogen were determined using Cobas 8000 modular analyzer series (Roche, Germany).
## Statistical analysis
Experimental data were measured using the PROC MIXED procedure (version 9.4; SAS Inst. Inc., Cary, NC, USA), and diet was the fixed effect. Pens were as the experimental unit for growth performance, whereas individual pigs served as the experimental units for carcass characteristics, meat quality, chemical composition, and sensory data. Orthogonal polynomials were used to determine the linear and quadratic effects of increasing the inclusion of GTBP in diets on studied parameters. The results are shown as the least square means with a standard error of the mean. Multiple comparisons were determined using Tukey adjustment. The significance level was tested as p ≤ 0.05, while 0.05 < $p \leq 0.10$ was a trend.
## Constituents of GTBP
The GTBP product had crude protein and crude fiber close to $20\%$. The contents in total polyphenols were close to $20\%$. The EGCG proportion among total polyphenols was significantly higher than that of ECG, EGC, EC, and C (Table-2).
**Table-2**
| Item | Value |
| --- | --- |
| Chemical composition (% DM) | |
| Moisture, % | 9.5 |
| Crude protein, % | 18.6 |
| Ether extract, % | 3.33 |
| Crude fiber, % | 19.8 |
| Crude ash, % | 4.68 |
| Bioactive compound (% DM) | |
| Total polyphenol (%) | 19.5 |
| Total catechins (%) | 14.9 |
| Catechin | 0.33 |
| Epicatechin | 0.86 |
| Epigallocatechin | 2.23 |
| Epicatechin gallate | 2.19 |
| Epigallocatechin gallate | 9.15 |
## Growth performance and carcass parameters
The different inclusion levels of GTBP in the experimental diets did not influence final live body weight (FBW), ADFI, ADG, and FCR ($p \leq 0.05$). However, pigs that received the diet supplemented with $2.4\%$ GTBP had a slightly decreasing trend in ADG in comparison with other diets (Table-3).
**Table-3**
| Item | Dietary treatment1 | Dietary treatment1.1 | Dietary treatment1.2 | Dietary treatment1.3 | SEM | p-value | p-value.1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Item | | | | | SEM | | |
| Item | CON | GTBP8 | GTBP16 | GTBP24 | SEM | Linear | Quadratic |
| Number of pigs | 40 | 40 | 40 | 40 | | | |
| IBW (kg) | 65.11 | 65.22 | 65.11 | 65.17 | 0.75 | 0.98 | 0.97 |
| FBW (kg) | 113.8 | 114.6 | 114.0 | 111.3 | 1.38 | 0.20 | 0.21 |
| ADFI (kg/d) | 2.15 | 2.19 | 2.19 | 2.10 | 0.05 | 0.47 | 0.27 |
| ADG (g/d) | 695 | 705 | 698 | 658 | 16.7 | 0.13 | 0.15 |
| FCR (kg/kg) | 3.11 | 3.10 | 3.14 | 3.20 | 0.13 | 0.62 | 0.81 |
Dietary supplementation of GTBP in the diets did not influence killing-out percentage and dressing percentage ($p \leq 0.05$). However, a significant decrease (linear, $$p \leq 0.04$$) in back fat thickness (BFT) was found for pigs fed diets with increasing GTBP levels, with the lowest value of BFT when the diet was supplemented with $2.4\%$ GTBP (Table-4).
**Table-4**
| Item | Dietary treatment1 | Dietary treatment1.1 | Dietary treatment1.2 | Dietary treatment1.3 | SEM | p-value | p-value.1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Item | | | | | SEM | | |
| Item | CON | GTBP8 | GTBP16 | GTBP24 | SEM | Linear | Quadratic |
| Number of pig | 8 | 8 | 8 | 8 | | | |
| Final body weight, kg | 113.0 | 114.8 | 114.2 | 111.8 | 1.75 | 0.60 | 0.25 |
| Killing-out percentage, % | 80.2 | 80.9 | 80.6 | 80.2 | 0.45 | 0.80 | 0.23 |
| Dressing percentage, % | 70.3 | 71.4 | 70.6 | 70.4 | 0.49 | 0.75 | 0.18 |
| Backfat thickness, mm | 18.9 | 16.6 | 16.4 | 16.1 | 0.91 | 0.04 | 0.28 |
## Technological quality of pig meat
The pH values (pH45 and pH24), drip losses (DL24), and cooking loss (CL24) of LTM were not significantly different (linear, p ≥ 0.39) between pigs fed the diets with the inclusion of GTBP and the CON (Table-5). The shear forces (SF24) of LTM tended to decrease (linear, $$p \leq 0.05$$) in response to the addition of GTBP when compared to the control group. Meat lightness (L*24) did not differ between the groups, but redness (a*) and yellowness (b*) tended to increase trend in pigs offered GTBP (linear, p ≤ 0.08).
**Table-5**
| Items | Dietary treatment1 | Dietary treatment1.1 | Dietary treatment1.2 | Dietary treatment1.3 | SEM | p-value | p-value.1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Items | | | | | SEM | | |
| Items | CON | GTBP8 | GTBP16 | GTBP24 | SEM | Linear | Quadratic |
| Number of pig | 8 | 8 | 8 | 8 | | | |
| pH at 45 min | 6.31 | 6.36 | 6.34 | 6.34 | 0.04 | 0.83 | 0.54 |
| pH at 24 h | 5.52 | 5.51 | 5.52 | 5.49 | 0.03 | 0.52 | 0.86 |
| Drip loss at 24 h (%) | 1.30 | 1.10 | 1.22 | 1.25 | 0.25 | 0.98 | 0.63 |
| Shear force at 24 h (N) | 39.2 | 36.3 | 35.4 | 33.5 | 1.80 | 0.05 | 0.78 |
| Lightness at 24 h (L*) | 54.4 | 55.0 | 55.5 | 56.1 | 1.45 | 0.39 | 0.99 |
| Redness at 24 h (a*) | 11.9 | 12.7 | 13.4 | 13.4 | 0.45 | 0.06 | 0.21 |
| Yellowness at 24 h (b*) | 5.16 | 6.10 | 6.16 | 6.13 | 0.34 | 0.08 | 0.20 |
## Chemical composition of pig meat
Pigs fed diets supplemented with GTBP tended to have increased crude protein content (linear, $$p \leq 0.04$$; quadratic, $$p \leq 0.02$$) and decreased lipid content in LTM meat (quadratic, $$p \leq 0.01$$), but DM and ash content were not changed. A decreased trend in cholesterol content (linear, $$p \leq 0.08$$; quadratic, $$p \leq 0.01$$) and an increase in total omega-3 fatty acid content (C18:3n3, C20:3n3, C20:5n3, and C22:6n3) (both linear and quadratic $$p \leq 0.01$$) in LTM meat were observed in pigs received GTBP in comparison to CON (Table-6).
**Table-6**
| Items | Dietary treatment1 | Dietary treatment1.1 | Dietary treatment1.2 | Dietary treatment1.3 | SEM | p-value | p-value.1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Items | | | | | SEM | | |
| Items | CON | GTBP8 | GTBP16 | GTBP24 | SEM | Linear | Quadratic |
| Number of pig | 8 | 8 | 8 | 8 | | | |
| Dry matter, % | 26.9 | 27.3 | 27.7 | 27.4 | 0.31 | 0.28 | 0.14 |
| Crude protein, % | 22.2b | 23.2a | 23.0ab | 23.7a | 0.26 | 0.04 | 0.02 |
| Lipids, % | 2.57a | 2.42a | 2.30ab | 1.98b | 0.09 | 0.75 | 0.01 |
| Ash, % | 1.40 | 1.43 | 1.35 | 1.43 | 0.03 | 0.92 | 0.39 |
| Cholesterol, mg/100 g | 59.1a | 54.5a | 42.8b | 39.2b | 1.24 | 0.08 | 0.01 |
| Total omega-3, mg/100 g | 17.0d | 32.5c | 40.0b | 54.4a | 1.55 | 0.01 | 0.01 |
## Blood parameters
The inclusion of GTBP did not induce a significant effect on blood parameters, including WBC, RBC, Hb, AST, ALT, bilirubin, protein, and creatinine (Table-7). However, plasma cholesterol content decreased with increasing GTBP levels in the diets (linear, $$p \leq 0.02$$). Moreover, a trend for a decrease in blood LDL-cholesterol and urea nitrogen was observed in pigs fed diets with increasing GTBP (linear, $$p \leq 0.08$$).
**Table-7**
| Items | Dietary treatment1 | Dietary treatment1.1 | Dietary treatment1.2 | Dietary treatment1.3 | SEM | p-value | p-value.1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Items | | | | | SEM | | |
| Items | CON | GTBP8 | GTBP16 | GTBP24 | SEM | Linear | Quadratic |
| Number of test pigs | 8 | 8 | 8 | 8 | | | |
| White blood cell (G/L) | 14.5 | 17.2 | 15.5 | 17.7 | 1.15 | 0.15 | 0.83 |
| Red blood cell (T/L) | 6.57 | 7.06 | 6.65 | 6.48 | 0.36 | 0.68 | 0.36 |
| Hemoglobin (g/dL) | 10.3 | 11.3 | 10.9 | 11.8 | 0.77 | 0.27 | 0.92 |
| AST, U/L | 56.2 | 69.5 | 63.4 | 59.2 | 9.88 | 0.95 | 0.39 |
| ALT, U/L | 54.3 | 65.8 | 58.2 | 55.2 | 5.65 | 0.85 | 0.22 |
| Bilirubin (mmol/L) | 0.73 | 0.78 | 0.74 | 0.84 | 0.13 | 0.65 | 0.85 |
| Protein (g/L) | 70.6 | 70.7 | 72.6 | 71.2 | 1.52 | 0.60 | 0.60 |
| Creatinine (mmol/L) | 108 | 115 | 120 | 133 | 7.65 | 0.65 | 0.85 |
| Total cholesterol (mmol/L) | 2.62 | 2.52 | 2.38 | 2.09 | 0.14 | 0.02 | 0.53 |
| High-density lipoprotein (mmol/L) | 1.08 | 1.13 | 1.04 | 1.05 | 0.05 | 0.34 | 0.66 |
| Low-density lipoprotein (mmol/L) | 1.21 | 1.07 | 1.06 | 0.88 | 0.12 | 0.08 | 0.88 |
| Urea nitrogen (mmol/L) | 5.45 | 4.32 | 5.08 | 4.17 | 0.36 | 0.08 | 0.77 |
## Discussion
This study aimed to assess the effects of GTBP in the diet on some blood parameters, growth performance, and carcass characteristics of finishing pigs and on meat quality, and nutritional composition of pork. The chemical composition of GTBP was in the same range as values reported for similar by-products [12, 27]. Total phenolic content in the experimental GTBP was in the range of $13.2\%$–$21.7\%$ DM, as reported by Khoa et al. [ 32]. Balci and Özdemir [23] reported a total polyphenol concentration between $6.8\%$ and $13.1\%$ DM, which is lower as compared to our results. This may be related to the tea varieties, geographical areas, time of harvesting and leaf age, leaf buds, processing methods, and extraction conditions [32, 33]. Moreover, EGCG content was the major compound representing $61.4\%$ of the total Cs in GTBP. According to Zaveri [34], EGCG was the most abundant C in green tea, accounting for $65\%$ of the total Cs constituent. Khoa et al. [ 32] reported that the content of EGCG in green tea was found in the range of $52\%$–$63\%$. Many of the health benefits of green tea for humans and animals relate to Cs, particularly EGCG content [23, 35].
In this study, supplementation of finishing pigs with diet inclusions of GTBP was evaluated through production parameters. Growth performance, including FBW, ADG, and FCR was not affected by the dietary supplementation with GTBP at 0.8, 1.6, and $2.4\%$ when compared to the control group. These results are in line with the previous studies [4, 19], which obtained similar data of FBW and ADG by adding up to $2\%$ GTBP in finisher pig diets. However, Hossain et al. [ 4] reported that significantly higher values of ADFI and FCR were found in a finisher pig diet supplemented with GTBP at $2\%$ compared to a CON. In addition, dietary supplementation at higher GTBP levels was negatively related to body weight gain in pigs and broilers [18, 36], probably due to great tannin concentration in GTBP leading to the inhibition of protein digestion and also to the high-fiber content in GTBP. The contradictory results regarding ADFI and FCR responses to GTBP could be differences in pig breeds, animals’ age, or experiment lasting.
In this study, different diets did not influence the killing-out and dressing percentage. However, BFT decreased with increased supplementation of GBTP, which is consistent with the previous studies on mice [37, 38]. This is probably associated with Cs contents of GTBP by interference in digestive lipase activity, inhibition of synthesis, and upregulation of β-oxidation of fatty acids in animal liver, thereby reducing BFT accumulation in animals [4, 36].
This study found that dietary supplementation of GTBP did not change pH values at 45 min and 24 h. The technological parameters of LTM meat in our work were classified as normal meat as described by Lengerken and Pfeiffer [39] and Monin [40]. Moreover, the shear force of pig meat decreased with increasing supplementation levels of GTBP, which is consistent with a similar study confirmed by Hossain et al. [ 4]. Smaller shear force results in softer meat and better taste. Therefore, dietary supplementation of GBTP improved meat quality which meets the demands of today’s market. Dietary GTBP supplementation did not significantly influence the surface color of LTM meat. However, meat color in redness (a*) and yellowness (b*) of LTM meat tended to increase with increasing inclusion of GTBP, which is consistent with the previous results found by Uuganbayar et al. [ 41], who stated that dietary supplementation with GTBP at $2\%$ increased redness and yellowness values of animal meat. This phenomenon could be due to the pigments of GTBP that percolate directly in meat [4].
The pork from pigs fed diets supplemented with GTBP had a higher protein content relative to the CON, which is consistent with a previous study by Flores-Mancheno et al. [ 42]. Dietary supplementation with GTBP in the finishing diets significantly decreased the cholesterol content of LM meat, which may have been due to the high polyphenol, particularly EGCG, that could form insoluble complexes with cholesterol in the gastrointestinal tract and inhibit the absorption of endogenous and exogenous cholesterol in the intestine of animals [43, 44].
In this study, a significant reduction of blood cholesterol content in finishing pigs when their diets were supplemented with GTBP is similar to the results obtained from the previous studies [13, 45] that found that the blood cholesterol content in broilers was reduced when their diets were supplemented with green tea powder up to $1.5\%$. This could be due to the GTBP inhibiting the activity of β-hydroxy β-methylglutaryl-CoA reductase as a rate-limiting enzyme in the cholesterol biosynthesis pathway [46].
## Conclusion
In Vietnamese finishing pigs, the supplementation with GTBP up to $2.4\%$ into the diets appears to have strong effects on lipid metabolism by reducing the total amount of body lipids without affecting animal performance. Its effects on meat technological parameters are unclear. Further experiments need to be carried out to determine the optimal levels of GTBP addition in the finishing pig diet to produce higher meat quality.
## Authors’ Contributions
PKD, NCO, and JH: Conceived and designed the study. NCO, NTPG, and CTTT: Conducted the trial and collected the samples. NCO and NTH: Analyzed the pork and blood samples. NCO and JH: Analyzed the data. PKD, NCO, and CTTT: Revised the manuscript. All authors have read and approved the final manuscript.
## Competing Interests
The authors declare that they have no competing interests.
## Publisher’s Note
Veterinary World remains neutral with regard to jurisdictional claims in published institutional affiliation.
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|
---
title: Ameliorating effect of Mucuna pruriens seed extract on sodium arsenite-induced
testicular toxicity and hepato-renal histopathology in rats
authors:
- Preethi Lavina Concessao
- Kurady Laxminarayana Bairy
- Archana Parampalli Raghavendra
journal: Veterinary World
year: 2023
pmcid: PMC9967728
doi: 10.14202/vetworld.2023.82-93
license: CC BY 4.0
---
# Ameliorating effect of Mucuna pruriens seed extract on sodium arsenite-induced testicular toxicity and hepato-renal histopathology in rats
## Abstract
### Background and Aim:
A significant cause of arsenic poisoning is polluted groundwater. Arsenic poisoning results in the suppression of spermatogenesis and the liver and kidneys are vulnerable to the toxic effects as well. Mucuna pruriens has been identified to have fertility-enhancing and anti-lipid peroxidation properties. Based on these properties of M. pruriens, this study aimed to investigate the efficacy of M. pruriens seed extract in reducing sodium arsenite-induced testicular impairment and hepato-renal histopathology in rats.
### Materials and Methods:
The study was divided into two groups; short-term (45 days) and long-term (90 days) treatment groups and each group was divided into nine subgroups. Subgroups 1 and 2 served as normal and N-acetyl cysteine (NAC) controls, respectively. Subgroups 3–9 received sodium arsenite in the drinking water (50 mg/L). Subgroup-4 received NAC (210 mg/kg body weight [BW]) orally once daily. Subgroups 5–7 received aqueous seed extract of M. pruriens (350, 530, and 700 mg/kg BW, respectively) orally once daily. Subgroups 8 and 9 received a combination of NAC and aqueous seed extract (350 and 530 mg/kg BW, respectively) orally once daily. Following the treatment, animals were sacrificed and sperm parameters and DNA damage were evaluated. Testis, liver, and kidneys were analyzed for histopathology.
### Results:
Sodium arsenite-induced a significant reduction in sperm parameters and increase in the abnormal architecture of spermatozoa. Histology revealed tissue necrosis. The M. pruriens seed extract ameliorated the damaging effects of sodium arsenite with respect to tissue architecture and sperm parameters when coadministered.
### Conclusion:
Mucuna pruriens has beneficial effects against the deleterious effects of sodium arsenite on various tissues. Thus, M. pruriens (530 and 700 mg/kg BW) supplementation would reduce the adverse changes observed with sodium arsenite exposure.
## Introduction
Arsenic is an all-pervading metalloid found in the earth’s crust and exists in elemental, organic, and inorganic forms. Contaminated groundwater is the major cause of arsenic poisoning [1]. Arsenic predominantly disturbs the sulfhydryl groups in cells [2], affecting cell respiration, enzymes, and mitosis [3, 4]. The human body is exposed to arsenic through different avenues, such as ingestion, air inhalation, and absorption through the skin [5]. Arsenic affects male sex organs and can lead to reproductive issues. It may disrupt gonadal function by decreasing testosterone synthesis [6], and induces apoptosis and necrosis [7, 8]. Studies have demonstrated a reduction in the weight of the reproductive organs and steroidogenesis with elevated levels of arsenic in the testis, indicating reproductive toxicity [9–11]. Toxicity due to arsenic was also shown to result in injury to the liver cells, fatty degradation, and progressive fibrosis [12, 13]. Several metal chelating agents have been previously tested and reported, including N-acetyl cysteine (NAC). It is a thiol and a precursor of reduced glutathione that serves as a free radical scavenger since it interacts with reactive oxygen species.
Several reports have shown that herbs and plant products could be used to mitigate arsenic toxicity. Mucuna pruriens is a leguminous plant that possesses antidiabetic and aphrodisiac effects [14, 15]. Seeds of M. pruriens have been shown to improve semen quality, testosterone, and luteinizing hormone levels [16], re-activate the antioxidant defense systems, and reduce stress [17, 18]. The existing literature established that excessive arsenic exposure causes oxidative cellular damage, which leads to organ damage. Mucuna pruriens serves as a source of natural antioxidants, reducing the damage caused by oxidative stress. However, there are no available reports on the use of M. pruriens seed extract to possibly reduce or prevent systemic toxicity induced by arsenic.
This study aimed to determine the effects of M. pruriens against sodium arsenite-induced sperm abnormalities and histopathological changes in the liver, kidney, and testes of rats.
## Ethical approval
All procedures used in this study were approved by the Animal Ethics Committee of Manipal Academy of Higher Education (IAEC/KMC/$\frac{52}{2015}$).
## Study period and location
This study was conducted from December 2018 to August 2019 at Animal House of Manipal Academy of Higher Education and at the Laboratory of Melaka Manipal Medical College, Manipal.
## Chemicals
Sodium arsenite A.R ($98.5\%$) was obtained from Nice Chemicals (P) Ltd., Cochin, India. NAC (Samarth Life Sciences Private Limited, India) was procured from a medical store at Udupi. Hematoxylin stain, Eosin Y stain and Cresyl violet powder were obtained from Karnataka laboratories, Mangalore, India.
## Plant extract preparation
Identification of M. pruriens seeds was conducted by the Faculty of Pharmacognosy (Specimen No: SDM/$\frac{954}{17112301}$). Seeds of M. pruriens were collected locally and cleaned. A total of 100 g of powdered seeds was soaked in 1000 mL distilled water at 4°C for 8 d. The suspension was centrifuged at 10000× g for 25 min and the supernatant was removed and used as the extract [19].
## Extracts quality assessment
The M. pruriens seed extract was qualitatively checked for the identification of carbohydrates, saponins, phenolic compounds, tannins, flavonoids, proteins, amino acids, gums, and mucilage. The physiochemical parameters were assessed for the standardization of each batch of prepared extract. The yield from the extract was 15.8 g.
## Experimental animals
One hundred and eight Sprague Dawley male rats (9–12 weeks old) were selected for the study and locally bred at the central animal house of Manipal Academy of Higher Education, Manipal. They were individually housed in polypropylene cages containing sterile paddy husk (locally procured) as bedding throughout the study and maintained under standard conditions with the temperature at 22°C–24°C, a 12 h/12 h light/dark cycle, and $40\%$–$60\%$ relative air humidity. The animals were acclimatized to the laboratory conditions for one week before the start of the experiment. Breeding and maintenance of animals were performed in accordance with the guidelines of the Committee for control and supervision of experiments on animals and Animal Welfare Division, Government of India for the use of laboratory animals. Three animals were housed in each cage to prevent overcrowding. Standard laboratory feed and water were available ad libitum to the animals.
## Experimental design
The study was divided into two groups: short-term (45 days) and long-term (90 days) treatment groups.
## Short-term group
Subgroup-1 (normal control) received normal drinking water as a vehicle for 45 days.
Subgroup-2 (standard drug NAC) received NAC at a dose of 210 mg/kg body weight (BW) once per day for 45 days.
Subgroup-3 (sodium arsenite - toxic control) received sodium arsenite in the drinking water (50 mg/L) for 45 days [20].
Subgroup-4 (sodium arsenite + standard drug NAC) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW [21] once per day for 45 days.
Subgroup-5 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 350 mg/kg BW [22] orally once per day for 45 days.
Subgroup-6 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 530 mg/kg BW orally once per day for 45 days.
Sub group-7 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 700 mg/kg BW orally once per day for 45 days.
Subgroup-8 (sodium arsenite + NAC + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW + M. pruriens at a dose of 350 mg/kg BW orally once per day for 45 days.
Subgroup-9 (sodium arsenite + NAC + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW + M. pruriens at a dose of 530 mg/kg BW orally once per day for 45 days.
## Long-term group
Subgroup-1 (normal control) received drinking water as a vehicle for 90 days.
Subgroup-2 (standard drug NAC) received NAC at a dose of 210 mg/kg BW once per day for 90 days.
Subgroup-3 (sodium arsenite − toxic control) received sodium arsenite in drinking water (50 mg/L) for 90 days.
Subgroup-4 (sodium arsenite + standard drug NAC) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW once per day for 90 days.
Subgroup-5 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 350 mg/kg BW orally once per day for 90 days.
Subgroup-6 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 530 mg/kg BW orally once per day for 90 days.
Subgroup-7 (sodium arsenite + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + M. pruriens at a dose of 700 mg/kg BW orally once per day for 90 days.
Subgroup-8 (sodium arsenite + NAC + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW + M. pruriens at a dose of 350 mg/kg BW orally once per day for 90 days.
Subgroup-9 (sodium arsenite + NAC + M. pruriens) received sodium arsenite in drinking water (50 mg/L) + NAC at a dose of 210 mg/kg BW + M. pruriens at a dose of 530 mg/kg BW orally once per day for 90 days.
Following the treatment, the animals were sacrificed and the sperm parameters and DNA damage were assessed. Testis, liver, and kidneys were analyzed for histopathology.
## Investigated parameters
Epididymal sperm count, sperm motility, and sperm morphology tests were performed as described by Vega et al. [ 23].
The sperm chromatin dispersion test was performed as described by Kumari et al. [ 24].
Histopathological evaluation of the kidneys, liver, and testis was performed.
All animals in the experimental groups were euthanized after treatment. The liver, testis, and kidneys were dissected and fixed with formalin ($10\%$). The tissues were processed for paraffin sectioning and stained with Hematoxylin and Eosin. The presence of vacuoles, gaps, and aberrant cells was examined in stained tissues.
## Seminiferous tubular diameter
The diameters of 10 transversely cut round seminiferous tubules were randomly selected per animal and measured using an ocular micrometer calibrated with a stage micrometer. In each tubule, two measurements were taken, one perpendicular to the other and their average was determined.
Animals treated with sodium arsenite showed a significant increase ($p \leq 0.001$) in the seminiferous tubular diameter, indicating a distortion of the tubule when compared to the normal controls. In the long-term treatment group, co-administration of sodium arsenite + M. pruriens (350, 530, and 700 mg/kg BW [$p \leq 0.001$]) and co-administration of sodium arsenite + NAC+ M. pruriens (350 and 530 mg/kg BW [$p \leq 0.001$]) exhibited a significant decrease in the seminiferous tubular diameter when compared to sodium arsenite only treated group (Tables-2 and 3).
## Seminiferous epithelial height
In a similar manner to the seminiferous tubular diameter measurement, the epithelial height was measured in 10 tubules from the basement membrane to the surface of the epithelium in two distinct areas, and the average was calculated.
Sodium arsenite administration caused a significant reduction ($p \leq 0.001$) in the seminiferous epithelial height when compared to the normal control group. In the short-term treatment group, animals treated with sodium arsenite + M. pruriens 700 mg/kg BW had a significantly increased ($p \leq 0.001$) seminiferous epithelial height when compared to the sodium arsenite-only treatment group. Animals treated with sodium arsenite + NAC + M. pruriens (350 mg/kg BW) showed a significant increase ($p \leq 0.001$) in seminiferous epithelial height when compared to the sodium arsenite-only treated group. In the long-term treatment group, co-administration of sodium arsenite + M. pruriens (350, 530, and 700 mg/kg BW [$p \leq 0.001$]) and co-administration of sodium arsenite + NAC + M. pruriens (350 and 530 mg/kg BW [$p \leq 0.001$]) exhibited a significant increase in the seminiferous epithelial height when compared to sodium arsenite only treated group (Tables-2 and 3).
## Statistical analysis
Data were analyzed using a one-way analysis of variance followed by a post hoc Tukey test with Prism Version 5.0 (trial version). Results were expressed as mean ± standard deviation. p ≤ 0.05 was considered as significant.
## Phytochemical screening of the M. pruriens aqueous seed extract
The yield from the aqueous seed extract of M. pruriens was 15.8 g. The seed extract was subjected to primary phytochemical investigation and the presence of alkaloids, carbohydrates, saponins, tannins, flavonoids, and phenols was detected (Table-1).
**Table-1**
| Test | Inference |
| --- | --- |
| Alkaloid | +++ |
| Carbohydrate | +++ |
| Flavonoids | + |
| Saponins | ++ |
| Tannin | +++ |
| Terpenoid | - |
| Protein | - |
| Phenol | ++ |
| Steroid | + |
## Sperm count
There was a significant reduction ($p \leq 0.001$) in the sperm count after treatment with sodium arsenite compared to the normal control group. Co-administration of M. pruriens (350, 530, and 700 mg/kg BW) along with sodium arsenite significantly increased ($p \leq 0.01$) the sperm count in comparison to the sodium arsenite-only treated group following both treatment durations. The groups treated with a combination of sodium arsenite + NAC along with M. pruriens (350 [$p \leq 0.05$] and 530 mg/kg BW [$p \leq 0.01$]) exhibited an increase in sperm count when compared to the sodium arsenite-only treatment group (Tables-2 and 3).
## Sperm motility
The number of motile sperm significantly decreased ($p \leq 0.001$) in the sodium arsenite-only treated group compared to the normal control. Co-administration of M. pruriens (350, 530, and 700 mg/kg BW) along with sodium arsenite significantly increased ($p \leq 0.01$) the number of motile sperm in comparison to the sodium arsenite-only treated group. Sperm motility significantly increased in the animals treated with a combination of sodium arsenite + NAC along with M. pruriens (350 and 530 mg/kg BW [both $p \leq 0.01$]) in comparison to the sodium arsenite-only treated group (Tables-2 and 3).
## Sperm morphology
Exposure to sodium arsenite significantly increased ($p \leq 0.001$) the number of abnormal sperm in comparison to the normal control. Co-administration of M. pruriens (350 [$p \leq 0.05$], 530 [$p \leq 0.001$], and 700 mg/kg BW [$p \leq 0.001$]) along with sodium arsenite significantly decreased the number of abnormal sperms in comparison to the sodium arsenite only treatment group. Animals treated with sodium arsenite + NAC + M. pruriens (350 [$p \leq 0.05$] and 530 [$p \leq 0.001$] mg/kg BW) showed a significant decrease in the number of abnormal sperms when compared to sodium arsenite + NAC treatment group (Tables-2 and 3).
## Sperm DNA damage
In the group treated with sodium arsenite alone, a significant increase ($p \leq 0.001$) in the percentage of spermatozoa carrying DNA damage when compared to normal control was observed. Animals treated with a combination of M. pruriens (530 and 700 mg/kg BW [$p \leq 0.001$]) along with sodium arsenite showed a reduction in the spermatozoa containing damaged DNA in comparison to the sodium arsenite-only group. The spermatozoa from the groups treated with a combination of NAC and M. pruriens (350 and 530 mg/kg BW [$p \leq 0.001$]), along with sodium arsenite, also exhibited a significant reduction in the percentage of DNA damage (Table-4).
**Table-4**
| Groups | Sperm DNA damage (%) | Sperm DNA damage (%).1 |
| --- | --- | --- |
| Groups | | |
| Groups | 45 days treatment | 90 days treatment |
| Control | 6.67 ± 0.88 | 9 ± 1.57 |
| As control | 24.66 ± 0.88$a | 30.33 ± 1.21$a |
| As+NAC | 10 ± 2.08$b | 13 ± 2.08$b |
| As+MP (530) | 16.6 ± 1.45$b | 17.33 ± 2.96$b |
| As+MP (700) | 12 ± 2.31$b | 15 ± 1.52$b |
| As+NAC+MP (350) | 13.33 ± 2.34$b | 18 ± 5.81$b |
| As+NAC+MP (530) | 13 ± 2.85$b | 20 ± 1.85#b |
## Histopathology of the testis
The testicular architecture of the control and NAC groups showed normal organization of the seminiferous tubule. Sodium arsenite administration (45 and 90 days) showed a significant reduction in seminiferous tubule diameter, seminiferous tubule epithelial height, and increased tubular lumen. Sloughed germ cells with no maturation stages were observed and the tubular basement membrane was irregular or interrupted. The cell lining of Sertoli cells was damaged and in general, there were fewer spermatozoa observed in the central core of the tubule. Co-administration of M. pruriens (350 and 530 mg/kg BW) along with sodium arsenite minimized the toxic effect of arsenic on the testis. The combination of NAC + M. pruriens (350 and 530 mg/kg BW) along with sodium arsenite showed improved structural recovery with minimal damage and intact cellular structures with an improved cell count (Figures-1 and -2).
**Figure-1:** *Representative photographs of H and E stained sections of testis following 45 days of treatment, viewed under 100×. Scale bar=20 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=M. pruriens aqueous seed extract 350 mg/kg BW, MP (530)=M. pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=M. pruriens aqueous seed extract 700 mg/kg body weight. Control group and NAC group showed normal organization of seminiferous tubule. Arsenic treated group showed reduced seminiferous tubule epithelial height and increased tubular lumen. The tubular basement membrane was irregular or interrupted. There was less number of spermatozoa in the lumen. As + MP (350) and As + MP (530) treated group exhibited cellular damage (arrow) and Sertoli cell damage (arrow). Higher doses of Mucuna pruriens and the combination treatment showed improved cell count, decreased structural damage. L=Lumen, E=Epithelium, S=Stroma.* **Figure-2:** *Representative photographs of H and E stained sections of testis following 90 days of treatment, viewed under 100×. Scale bar=20 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=Mucuna pruriens aqueous seed extract 350 mg/kg body weight, MP (530)=Mucuna pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=Mucuna pruriens aqueous seed extract 700 mg/kg body weight. Control group and NAC group showed normal organization of seminiferous tubule. Arsenic treated group showed reduced seminiferous tubule epithelial height and increased tubular lumen. The tubular basement membrane was irregular or interrupted (arrow). Less spermatozoa in the lumen. Provoked alterations in the seminiferous tubules were evident. Sloughing of germ cells was seen (arrow head). As+ MP (350) treated group showed intact basement membrane (arrow), but reduction in the cell count in the lumen. The higher doses of Mucuna pruriens (530 mg/kg body weight and 700 mg/kg body weight) and the combination treatments showed minimal damage and improved cell count. L=Lumen, E=Epithelium, LC=Leydig cell.*
## Histopathology of the liver
The liver of the normal group showed hepatocytes that were arranged in strands radiating from the central vein and sinusoids and Kupffer cells were observed. Exposure to sodium arsenite for 45 days resulted in damage to the cell lining of sinusoids and an increase in sinusoidal spaces. The wall of the central vein was damaged and appeared to be dilated. Long-term exposure resulted in damage that was extended to other areas of the liver. Disorganization of hepatic lobules and cellular necrosis of hepatocytes was evident. In the animals exposed to sodium arsenite + NAC, there were major changes in the sinusoidal regions. The higher doses of M. pruriens (530 and 700 mg/kg BW) showed improved cellular structure. Clear sinusoidal regions were evident. Inflammatory changes were reduced. The combination of M. pruriens and + NAC showed reduced inflammatory and degenerative changes due to sodium arsenite (Figures-3 and -4).
**Figure-3:** *Representative photographs of H and E stained sections of liver following 45 days of treatment, viewed under 100×. Scale bar=10 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=Mucuna pruriens aqueous seed extract 350 mg/kg body weight, MP (530)=Mucuna pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=Mucuna pruriens aqueous seed extract 700 mg/kg body weight. Normal histoarchitecture with normal hepatocytes (arrow head), sinusoids, central vein (C) and Kupffer cells were observed in control and the NAC treated groups. Arsenic treated group showed damage to the cell lining of sinusoids, increase in sinusoidal spaces and dilated central vein. Wall of the central vein was damaged. Cellular necrosis of hepatocytes was seen (double arrow). As + MP (350) treated group showed inflammatory changes in the hepatocytes along with increase in the area of sinusoids (arrow) and dilated central vein.* **Figure-4:** *Representative photographs of H and E stained sections of liver following 90 days of treatment, viewed under 100×. Scale bar=10 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=Mucuna pruriens aqueous seed extract 350 mg/kg body weight, MP (530)=Mucuna pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=Mucuna pruriens aqueous seed extract 700 mg/kg body weight. Normal histoarchitecture with normal hepatocytes (arrow head), central vein (C), sinusoids, and Kupffer cells were observed in control and the NAC treated groups. Arsenic treated group showed damage to the cell lining of sinusoids, increase in sinusoidal spaces (arrow). Cellular necrosis of hepatocytes was seen (double arrow). As + MP (350) treated group showed macrophage activity. Increased sinusoidal spaces were evident (arrow).*
## Histopathology of the kidney
Sections from kidney tissue exposed to sodium arsenite showed damage to the bowman capsule leading to increased urinary space. There was clear damage to the basement membrane and intercellular structures. Co-administration of M. pruriens (350 mg/kg BW) with sodium arsenite reduced the toxic effects of arsenic. There was damage to the cellular lining of the duct system. Higher doses of M. pruriens (530 and 700 mg/kg BW) showed minimal damage and an improved histological structure in comparison to the lower dose. The kidney tubules exhibited acidophilic cytoplasm. The combination of M. pruriens (350 and 530 mg/kg BW) + NAC showed results that were similar to sodium arsenite + M. pruriens (700 mg/kg BW) (Figures-5 and -6).
**Figure-5:** *Representative photographs of H and E stained sections of kidney following 45 days of treatment, viewed under 100×. Scale bar=20 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=Mucuna pruriens aqueous seed extract 350 mg/kg body weight, MP (530)=Mucuna pruriens
Mucuna pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=Mucuna pruriens aqueous seed extract 700 mg/kg body weight. The kidney tissue of control and NAC treated rats showed normal renal corpuscle (G), proximal convoluted tubules (P), distal convoluted tubules (D). In the arsenic treated rats, renal cortex swelling and congestion in the renal corpuscle (arrow), showed damage to the bowman capsule, basement membrane, increased urinary space, damage to the intercellular structures (arrow head). As + NAC treated group showed inflammatory changes (arrow). As + MP (350) treated group showed infiltration of inflammatory cells (double arrow) and macrophage activity (arrow).* **Figure-6:** *Representative photographs of H and E stained sections of kidney following 90 days of treatment, viewed under 100×. Scale bar=20 μm. NAC=N-acetyl cysteine, As=Arsenic, MP (350)=Mucuna pruriens aqueous seed extract 350 mg/kg body weight, MP (530)=Mucuna pruriens aqueous seed extract 530 mg/kg body weight, MP (700)=Mucuna pruriens aqueous seed extract 700 mg/kg body weight. The kidney tissue of control and NAC treated rats showed normal renal corpuscle (G), proximal convoluted tubules (P), distal convoluted tubules (D). Arsenic treated rats showed damage to the bowman capsule (arrow), basement membrane increased urinary space, damage to the intercellular structures (double arrow). As + MP (350) treated group showed damage to the cellular lining of the duct system. As + MP (530) group showed reduction in the urinary space (arrow head).*
## Discussion
In this study, a significant reduction was observed in the sperm count and motility and an increase in aberrant sperm in the animals exposed to sodium arsenite in both treatment periods when compared to the normal control. A significant distortion in the shape of the seminiferous tubule, reduction in the epithelial height, and increased spermatozoa carrying damaged DNA were evident in the animals exposed to sodium arsenite in both treatment durations. It was previously reported that exposure to 60 mg/L of AsO2Na in drinking water for 15 days resulted in decreased testicular and epididymal weights, reduced sperm quality, and decreased sperm volume [25]. In another study, exposure to 5 mg/L of sodium arsenite in drinking water for 4 weeks reduced the weight of the testis and epididymal sperm counts and caused considerable degeneration of germ cells [26]. Our findings are in agreement with these studies. Histological examination of the testis revealed seminiferous tubule atrophy, total loss of the spermatogenic layer, absence of spermatozoa in the lumen, and Leydig cell degeneration in animals exposed to sodium arsenite. Meanwhile, the control group displayed active spermatogenesis of all germ cells, such as spermatogonia, and primary and secondary spermatogenesis. Earlier studies found that sodium arsenite treatment caused Leydig cell degeneration, decreased sperm production and spermatid number, and a reduction in the number of epididymal sperm due to oxidative stress [27]. Arsenic activates the hypophysial-adrenocortical axis and enhances the pituitary secretion of adrenocorticotropic hormone. This results in a rise in plasma levels of corticosterone, which suppresses the sensitivity of gonadotrophic cells to the hormone-releasing gonadotropin and thus, prevents the secretion of gonadotropin. High levels of adrenocorticotropic hormone and corticosterone also directly inhibit testosterone production and secretion, by decreasing spermatogenesis and epididymal sperm count [7, 9]. Decreased intratesticular testosterone concentration results in germ cell detachment from the seminiferous epithelium [28]. It may induce germ cell apoptosis because high testosterone levels in the testis are essential for normal spermatogenesis and maintenance of the structure of the seminiferous tubule [29–34].
In this study, sodium arsenite administration in rats demonstrated pathological changes in the liver, including signs of hepatocellular degeneration, inflammation, and pyknosis. The microscopic kidney sections of the rats treated with sodium arsenite revealed tubular degeneration and congestion. Sodium arsenite has been shown to cause histological changes in kidney tissue and increased serum levels of creatinine and urea. The tubular epithelium in kidney sections of rats given sodium arsenite 10 mg/kg BW showed varying degrees of degeneration [35, 36]. Increased concentration of reactive oxygen species [37], decreased efficiency of the antioxidant defense system, and reduced energy levels in cells due to arsenic exposure may result in tissue damage, eventually leading to cell death [38]. It has been documented that sodium-potassium adenosine triphosphate (Na/K ATPase) is responsible for energy-dependent sodium ion extrusion and potassium ion uptake, an essential part of maintaining ionic homeostasis [39]. Oxidative stress induced by arsenic could impair the functioning of the Na/K ATPase pump, resulting in a significant alteration in ion and water transport. This could further lead to the swelling of cells due to fluid accumulation [40]. Decreased Na/K ATPase activity in the plasma membrane of the liver has been observed in mice fed with drinking water containing arsenic [41].
There was significant improvement observed in the sperm count and structure in the animals treated with M. pruriens 700 mg/kg BW, and a combination of NAC + M. pruriens 530 mg/kg BW in both the treatment groups, respectively. A significant increase in the number of motile sperms in the group treated with 700 mg/kg BW of M. pruriens in comparison to M. pruriens administered at other doses was also evident. Long-term exposure in animals to 530 and 700 mg/kg BW of M. pruriens demonstrated a better response in reducing the tubule size in comparison to the other treatment doses. Epithelial height of the tubules showed a significant increase in the animals treated with 700 mg/kg BW of M. pruriens and a combination of NAC + M. pruriens 350 mg/kg BW. In one study, there was a significant increase in the concentration of caudal sperm in rats treated with M. pruriens orally at a dosage of 300 mg/kg BW for 14 consecutive days [42]. The positive results observed in the experiment were due to the characteristics of M. pruriens.
The seeds of M. pruriens are abundant in L-DOPA and metabolites, namely dopamine, epinephrine, and norepinephrine [43]. Dopamine has been suggested to prevent the release of prolactin from the anterior lobe of the pituitary gland [44] and this induces the secretion of gonadotropin-releasing hormone by the hypothalamus and forebrain. This in turn, activates the anterior pituitary gland to secrete gonadotropins resulting in increased testosterone synthesis. The hormone binds to luteinizing hormone receptors present on the cell membrane, inducing activation and the cyclic adenosine monophosphate (cAMP) second messenger system is activated [44]. Increased cAMP levels, due to rapid cholesterol mobilization, are primarily responsible for an increase in steroid production by Leydig cells [45]. Therefore, increased levels of dopamine optimize hormone development, like testosterone, which contributes to improved sexual behavior [46, 47]. Many bioactive constituents, including alkaloids, coumarins, flavonoids, and alkylamines, have been reported to be present in M. pruriens [48], which play a significant role in increasing the antioxidant potential in treated males. Mucuna pruriens has been reported to significantly reduce lipid peroxide levels in infertile men [49, 50] and it is established that lipid peroxidation is a process induced by free radicals and that the lipids in spermatozoa are vulnerable to peroxidation [51, 52]. This antioxidant property may act as a protective effect of M. pruriens.
Administration of M. pruriens with sodium arsenite demonstrated macrophage activity and improved hepatic structure and sinusoids and inflammatory changes were minimized. Similar results were observed in a study where M. pruriens reduced hepatocellular necrosis and prevented cellular infiltration and vacuolation in diabetic rats exposed to 200 mg/kg BW of M. pruriens for 28 days, which may be due to its rich antioxidant properties [53]. Alkaloids and saponins are reported to elicit hepatoprotective activity by inhibiting lipid peroxidation [54, 55], thus stabilizing the hepatocellular membrane, preventing cell leakage, and increased hepatic regeneration.
In both treatment groups, graded doses of M. pruriens concurrent with sodium arsenite showed substantial damage in the nephron and glomerulus, as observed by histopathological examination. Mucuna pruriens successfully attenuated the tubular necrosis caused by sodium arsenite in the kidneys of the experimental animals. Mucuna pruriens proved to be effective due to the potent antioxidant ability of its constituents, which reduced the toxic effects induced by sodium arsenite. This study confirmed that further protection was shown by the simultaneous administration of preventive substances along with arsenic.
## Conclusion
Excessive arsenic ingestion leads to significant damage to various body tissues (liver, kidney, and testes), making the individual prone to further complications. Sodium arsenite-exposed animals showed impaired hepatic and renal function and reproductive toxicity. The supplement of M. pruriens (530 and 700 mg/kg BW) with sodium arsenite was found to attenuate the adverse changes observed with arsenic exposure. The study suggests that a diet supplemented with M. pruriens can ameliorate the undesirable changes in rats exposed to sodium arsenite.
## Authors’ Contributions
PLC, KLB, and APR: Contributed to the conception and design of the study. PLC: Performed the experiment and wrote the manuscript. PLC, KLB, and APR: Statistical analysis. KLB and APR: Reviewed the manuscript. All authors have read and approved the final manuscript.
## Competing Interests
The authors declare that they have no competing interests.
## Publisher’s Note
Veterinary World remains neutral with regard to jurisdictional claims in published institutional affiliation.
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|
---
title: The first study on urinary loss of iron and transferrin in association with
proteinuria in dogs with chronic kidney disease
authors:
- Nawat Sannamwong
- Chollada Buranakarl
- Saikaew Sutayatram
- Monkon Trisiriroj
- Thasinas Dissayabutra
journal: Veterinary World
year: 2023
pmcid: PMC9967729
doi: 10.14202/vetworld.2023.154-160
license: CC BY 4.0
---
# The first study on urinary loss of iron and transferrin in association with proteinuria in dogs with chronic kidney disease
## Abstract
### Background and Aim:
Anemia is an important factor in surviving chronic kidney disease (CKD). Anemia in CKD is associated with various factors, such as inadequate production of erythropoietin and the availability of iron and its binding protein. Reduced total iron-binding capacity (TIBC) and iron concentrations may be related to their urinary loss along with proteinuria. This study aimed to determine the urinary loss of iron and transferrin (TF) in relation to the degree of proteinuria.
### Materials and Methods:
The study was performed on 37 dogs with CKD. Dogs were divided according to the severity of proteinuria into two groups based on the mean of urinary protein–creatinine (UPC) ratio into UPC ratio <4 and UPC ratio >4. The hematocrit (HCT), blood chemistries, plasma iron, plasma TF, UPC ratio, urinary iron per creatinine ratio (U-Iron/CR), and urinary TF per creatinine ratio (U-TF/CR) were evaluated.
### Results:
Anemia was associated with the severity of renal impairment as demonstrated by reduction of HCT when staging of CKD was higher. Dogs with UPC ratio >4 had higher urinary loss of both U-Iron/CR ($p \leq 0.01$) and U-TF/CR ($p \leq 0.001$) with lower plasma TIBC ($p \leq 0.001$). The UPC ratio was positively correlated with both U-Iron/CR ($r = 0.710$, $p \leq 0.001$) and U-TF/CR ($r = 0.730$, $p \leq 0.001$) but negatively with TIBC (r = –0.462, $p \leq 0.01$).
### Conclusion:
Proteinuria was associated with urinary loss of both iron and TF which may contribute to anemia in CKD.
## Introduction
Both anemia and proteinuria were associated with decreased survival rate in dogs [1, 2] and cats [3, 4]. Non-regenerative anemia usually presents in the advanced stage of chronic kidney disease (CKD), which is associated with inadequate production of erythropoietin (EPO) [5] due to the loss of functional renal parenchyma. However, other factors may contribute to the anemia in CKD, such as uremic toxin, inflammation, nutritional imbalance, blood loss, disordered iron metabolism, or shortened erythrocyte survival [6–8]. In patients with CKD, iron deficiency could be developed from decreased consumption, reduced gastrointestinal absorption, loss through gastrointestinal bleeding, or urinary loss through glomerular filtration. Measurement of the iron panel analysis, which includes serum iron concentration, ferritin, and total iron-binding capacity (TIBC), is available in clinical practice. Normally, serum iron concentration is mostly bounded to transferrin (TF), an iron transport protein, while their interaction was reviewed earlier [9]. The TF level and saturation can be used to indicate the iron status [10, 11], while it can be estimated indirectly as TIBC using a summation of serum iron concentration and unsaturated iron-binding capacity (UIBC) [11]. Measurement of the iron panel may be essential since altered iron homeostasis could play an important role in impaired erythropoiesis in patients with CKD particularly when EPO is still sufficient.
The previous study showed that erythroid hypoplasia and normocytic normochromic anemia were common in dogs with CKD with a prevalence of >$80\%$, and serum iron level showed significant correlations with erythrocyte precursors from bone marrow aspirates in dogs with early stages of CKD but not in the late stage [12]. However, serum EPO in those dogs showed no correlation with bone marrow or erythrogram findings. For anemia treatment response in dogs with CKD, baseline hematocrit (HCT), iron supplementation, dosage of darbepoetin, severity of azotemia, age, or comorbidities of dogs showed no correlation with darbepoetin treatment responses [13]. While in another study, low iron and TIBC were associated with the degree of anemia and the erythropoietic response to darbepoetin treatment with iron supplementation in dogs with CKD [14]. Thus, alteration in iron metabolism and bone marrow status could significantly impact erythropoiesis in dogs with CKD, even with EPO treatment and iron supplementation. Proteinuria and alteration in iron status have been demonstrated in patients with Type 2 diabetes mellitus and nephrotic syndrome, and iron deficiency was reported to be approximately $33\%$ in children with nephrotic syndrome [15, 16]. Excessive urinary losses of iron, TF, EPO, transcobalamin, and/or copper in relation to anemia and its ineffectiveness after iron and EPO supplementation in nephrotic syndrome were extensively reviewed [17]. It was also suspected that iron and TF may be lost, especially in proteinuric dogs, which may in part, be responsible for anemia in these dogs with CKD. Increased urinary excretions of both albumin (ALB) and TF were previously demonstrated in Stage I CKD cats [18].
Therefore, this study aimed to evaluate the effect of proteinuria on urinary loss of iron and TF and plasma TIBC levels in proteinuric dogs. This is the first study regarding the proteinuria on urinary loss of iron or iron-binding protein which may affect TIBC in dogs with CKD.
## Ethical approval and informed consent
The consent forms were obtained from all owners. All diagnosed CKD dogs were undergoing blood and urine collections. The clinical data were also retrieved and recorded. The study protocol was conducted in accordance with the standard clinical practice protocols, the animal use guidelines, and the Institutional Animal Care and Use Committee approval (protocol No 2031081).
## Study period and location
The study was conducted from September 2020 to February 2022. The enrolled dogs in this study were client-owned dogs which were treated at the Small Animal Teaching Hospital, Faculty of Veterinary Science, Chulalongkorn University, Thailand.
## Animals and criteria
Experienced veterinarians confirmed the presence of CKD in all 37 client-owned dogs based on medical history, a complete physical examination, radiographic imaging and/or ultrasonography, and laboratory evaluation. The severity of proteinuria in all dogs was categorized into two groups based on the average mean urinary protein–creatinine (UPC) ratio of this study at 4.1 to be UPC ratio <4 and >4 groups, respectively.
## Experimental protocol
All dogs with CKD received a complete physical examination and blood collection on the 1st day of the study. A total of 2.5 mL of blood sample was collected from cephalic or saphenous venipuncture. The 0.5 mL of blood was placed in an ethylenediaminetetraacetic acid tube for complete blood count (CBC) analysis, and another 1 mL of blood was put in a heparinized tube for measurements of blood chemistries (i.e., blood urea nitrogen [BUN]; creatinine [CR]; total protein [TP]; ALB; and inorganic phosphorus [Pi]). Additional 1 mL of blood was separated and placed into plain tubes, allowed to clot, and then centrifuged at 4°C, 1000× g for 15 min to separate serum. Approximate 500 μL of serum was kept at –20°C to measure serum concentrations of iron, TF, and UIBC. The urine samples of all dogs were collected by voiding or urinary catheterization and 5 mL of urine was kept at –20°C for measurements of concentrations of protein, iron, TF, and CR.
## Analytical procedure
Hematology was analyzed using an automated machine (BC-5000Vet, MINDRAY, Shenzhen, PR China). The blood biochemistry (BUN, CR, TP, ALB, and Pi) was analyzed using an automated machine (ILAB 650 Chemistry Analyzer, Diamond diagnostics, Holliston, MA, USA). Serum and urine iron concentration and serum UIBC were analyzed by the standard colorimetric ferrozine method (Cobas c501, Roche Diagnostics, Indianapolis, IN, USA). The TIBC was calculated by the sum of plasma iron and UIBC. The TF level in both plasma and urine was analyzed by enzyme-linked immunosorbent assay method (Canine TF ELISA Kit [ab157704], Abcam, Cambridge, UK). The urinary protein was analyzed by multicolor method (Olympus Au 400, Olympus America Inc., Melville, NY, USA). Urinary protein, iron, and TF were divided by urinary CR and expressed as UPC ratio, urinary iron per CR ratio (U-Iron/CR), and urinary TF per CR ratio (U-TF/CR), respectively.
## Statistical analysis
All statistical analyses were performed using SigmaStat Version 12.0 (Systat Software Inc, California, USA). The data are presented as means ± standard error. The differences between proteinuric groups were tested using an unpaired t-test. The correlations among parameters were analyzed by Pearson correlation. A probability value of $p \leq 0.05$ was regarded as being statistically significant.
## Dog characteristics
In this study, 37 dogs with CKD were recruited. No differences in age or weight were found when dogs were divided into two groups based on the severity of proteinuria as UPC ratio <4 group ($$n = 22$$) and UPC ratio >4 group ($$n = 15$$) (Table-1). Breed, sexual status, and existing comorbidities of dogs in each group varied. Some dogs presented with comorbid diseases as shown in Table-1. In addition, some anemic dogs with CKD received iron, darbepoetin administration, and/or blood transfusion. The average dose of iron was 38.9 mg of element iron/dog/day (range: 6–100 mg of element iron/dog/day), and the duration of administration was 29.6 days (range: 1–60 days). Darbepoetin was injected subcutaneously in some dogs every 1 week at the dose of 1 mg/kg. The duration of darbepoetin treatment varied between 7 and 21 days, and the maximal injection was 3 times. The mean initial HCT in those dogs before darbepoetin was $19.7\%$ ± $1.4\%$, and it was not different from the day of study ($22.9\%$ ± $1.9\%$). Two dogs received blood transfusion 2 and 3 weeks before the study. The initial HCT before transfusion was $14.8\%$ and $12.8\%$, whereas HCT after transfusion was $13.0\%$ and $9.7\%$, respectively.
**Table-1**
| Parameters | Proteinuria | Proteinuria.1 |
| --- | --- | --- |
| Parameters | | |
| Parameters | UPC ratio <4 (n = 22) | UPC ratio >4 (n = 15) |
| Age (years) | 11.5 ± 0.9 | 9.5 ± 1.0 |
| Weight (kg) | 11.7 ± 1.6 | 9.9 ± 2.8 |
| Breed | | |
| Mixed | 15 | 5 |
| Poodle | 3 | 3 |
| Shih tzu | 1 | 1 |
| Pomeranian | 1 | 4 |
| Chihuahua | 1 | - |
| Yorkshire terrier | 1 | - |
| Beagle | - | 1 |
| Bull terrier | - | 1 |
| Neutered status | | |
| M/Mc/F/Fs | 4/8/1/9 | 6/1/1/7 |
| Comorbidities | | |
| E. canis infectious | 5 | 3 |
| Cardiovascular | 2 | 1 |
| Inflammatory | 3 | 1 |
| Urolith | - | 2 |
| Hepatobiliary | 1 | 1 |
| Neurological | 3 | - |
| Ophthalmic | - | 1 |
| Dermatological | 1 | - |
| Treatments | | |
| Iron supplement | 7 | 9 |
| Darbepoetin injection | 6 | 6 |
| Blood transfusion | 1 | 1 |
## Blood profiles in dogs as categorized by severity of CKD
The number of dogs in Stages I, II, III, and IV CKD as categorized by International Renal Interest Society (IRIS) group were 5, 11, 13, and 8, respectively. The CBC and some biochemical profiles are shown in Table-2. The HCT was reduced along with the severity of CKD. Stage IV CKD had significantly lower HCT compared with Stage I ($p \leq 0.05$). The BUN and Pi were significantly higher when renal impairment was advanced. Lower TP was found in Stage III compared with Stage I ($p \leq 0.05$). The ALB tended to be reduced without significance along with the severity of CKD. The white blood cell, alanine transferase, and UPC ratio were not different among stages.
**Table-2**
| Parameters | n | Stage of CKD | Stage of CKD.1 | Stage of CKD.2 | Stage of CKD.3 |
| --- | --- | --- | --- | --- | --- |
| Parameters | n | | | | |
| Parameters | n | I | II | III | IV |
| HCT (%) | 5/11/13/8 | 37.4 ± 2.8a | 29.0 ± 3.3ab | 26.7 ± 5.1ab | 18.5 ± 2.3b |
| WBC (×103 cells/mL) | 5/11/12/8 | 7.23 ± 1.86 | 14.69 ± 3.59 | 9.92 ± 2.52 | 13.27 ± 4.02 |
| BUN (mg/dL) | 5/11/13/8 | 47.3 ± 10.9bc | 48.2 ± 6.8b | 92.6 ± 23.0ac | 158.2 ± 28.0a |
| CR (mg/dL) | 5/11/13/8 | 0.96 ± 0.17b | 2.14 ± 0.10b | 3.99 ± 0.42ac | 8.49 ± 0.71a |
| ALT (U/L) | 4/10/11/8 | 129.5 ± 51.3 | 108.9 ± 18.4 | 54.1 ± 32.5 | 117.4 ± 32.0 |
| TP (g/dL) | 5/11/13/8 | 7.82 ± 0.53a | 6.68 ± 0.35ab | 6.20 ± 0.62b | 6.86 ± 0.27ab |
| ALB (g/dL) | 5/11/13/8 | 2.50 ± 0.27 | 2.34 ± 0.11 | 2.14 ± 0.18 | 2.05 ± 0.16 |
| Pi (mg/dL) | 5/10/13/7 | 3.7 ± 0.3b | 5.2 ± 0.6b | 9.6 ± 1.2ac | 12.4 ± 1.8a |
| UPC ratio | 5/11/13/8 | 3.32 ± 1.37 | 2.82 ± 0.79 | 5.94 ± 2.58 | 3.28 ± 0.72 |
## Blood profiles and iron parameters in dogs as categorized by degree of proteinuria
The blood parameters did not differ between groups when dogs were categorized based on proteinuria (Table-3). However, TIBC was significantly lower ($p \leq 0.001$) while U-Iron/CR and U-TF/CR were significantly higher in UPC ratio >4 group than those in UPC ratio <4 group.
**Table-3**
| Parameters | n | Degree of proteinuria | Degree of proteinuria.1 |
| --- | --- | --- | --- |
| Parameters | n | | |
| Parameters | n | UPC ratio <4 | UPC ratio >4 |
| HCT (%) | 22/15 | 28.8 ± 2.4 | 24.6 ± 2.1 |
| WBC (×103 cells/mL) | 21/15 | 11.67 ± 1.69 | 11.86 ± 2.78 |
| BUN (mg/dL) | 22/15 | 91.7 ± 15.5 | 81.3 ± 10.2 |
| CR (mg/dL) | 22/15 | 4.1 ± 0.7 | 3.8 ± 0.4 |
| ALT (U/L) | 20/13 | 112.5 ± 17.5 | 68.5 ± 16.1 |
| TP (g/dL) | 22/15 | 6.9 ± 0.2 | 6.4 ± 0.3 |
| ALB (g/dL) | 22/15 | 2.27 ± 0.10 | 2.17 ± 0.07 |
| Pi (mg/dL) | 20/15 | 7.3 ± 1.1 | 9.1 ± 0.7 |
| Iron (mg/dL) | 22/15 | 114.5 ± 9.4 | 101.1 ± 12.9 |
| TIBC (mg/dL) | 22/15 | 339.8 ± 19.9 | 231.3 ± 19.9*** |
| TF (mg/dL) | 14/14 | 448.7 ± 55.2 | 366.8 ± 36.6 |
| U-Iron/CR (mg/mg CR) | 22/15 | 246.9 ± 37.0 | 457.1 ± 84.6** |
| U-TF/CR (mg/mg CR) | 14/14 | 25.8 ± 6.0 | 73.7 ± 9.5*** |
| UPC ratio | 22/15 | 2.0 ± 0.1 | 7.2 ± 0.9*** |
## Relationship among parameters
HCT was correlated negatively with BUN ($p \leq 0.01$), CR ($p \leq 0.001$), and Pi ($p \leq 0.01$) but positively with ALB ($p \leq 0.05$) (Table-4). Strong positive relationships were found between UPC ratio and U-Iron/CR ($p \leq 0.001$) (Figure-1a) and U-TF/CR ($p \leq 0.001$) (Figure-1b) but negative with TIBC ($p \leq 0.01$) (Figure-1c). The TIBC was correlated positively with both ALB ($p \leq 0.05$) and plasma TF concentration ($p \leq 0.001$) (Figure-1d). Urinary iron per CR ratio was correlated positively with U-TF/CR ($p \leq 0.01$).
## Discussion
In this study, the dogs developed CKD with proteinuria. Both groups with low and high UPC ratios included a variety of breeds with different sexual status and were old. The prevalence of CKD was found in old age, which was due to renal impairment over time. Rather than old age, risk factors for CKD development were inflammatory/infectious diseases, history of anesthetic-surgical procedures, heart disease, neoplasm, endocrinopathies, and exposure to nephrotoxic drugs [2]. Canine vector-borne disease, particularly Ehrlichia spp., was associated with proteinuria [19]. Dogs with E. canis infection had membranoproliferative glomerulopathy and interstitial nephritis along with hypoalbuminemia [20]. In case of heart disease, three dogs had degenerative mitral valve disease, American College of Veterinary Internal Medicine stage B1 and not receiving any diuretic drugs. All dogs are in stable hydration status. Two dogs had urinary calculi. One dog had nephrolithiasis, and the other had cystic calculi. The calculi were not removed, but no urinary tract obstruction and infection were found. Many dogs received drugs to treat their concurrent diseases. However, the dose and duration of treatment were in a standard recommendation that should not affect kidney function. Some dogs had anemia and required iron supplementation, darbepoetin administration, or blood transfusion.
Both degrees of renal impairment and proteinuria are important factors determining survival in patients with CKD. In dogs, UPC ratio >0.5 was significantly associated with reduced survival and proteinuria, which could increase the risk of death at any time point [1]. The previous study in cats with CKD showed that both plasma CR and UPC ratio were associated with shorter renal survival time [3, 4]. In dogs, slow disease progression and higher survival rates were related to persistent monitoring of SDMA, renal proteinuria, and timely therapeutic management [2]. The IRIS group categorized the severity of kidney disease and proteinuria in which the upper value of plasma CR in Stage III was 5.0 mg/dL, whereas proteinuria in dogs is considered when the UPC ratio is higher than 0.5 [21]. Most of the dogs in this study ($\frac{33}{37}$) had UPC ratio higher than 0.5.
Besides proteinuria, another risk factor related to decreased survival rate is anemia [2]. In patients with diabetic nephropathy, after clinical and renal pathologic covariate adjustment, anemia was associated with adverse renal outcomes [22]. Increased urea, phosphate, and decreased HCT were dependent risk factors that were associated with shorter renal survival time in cats with CKD [4]. The present study showed that the HCT of dogs was related to the severity of renal impairment as categorized by the stage of CKD in which higher CKD stage had more anemia. Hematocrit and renal function parameters showed a negative correlation (BUN; $p \leq 0.01$, CR; $p \leq 0.001$ and Pi; $p \leq 0.01$). The results were similar to the previous study in dogs with CKD [12]. The reduction in HCT, along with severity of CKD was mainly due to the failure to produce EPO relative to the severity of anemia [5]. In addition, desensitization of the oxygen-sensing mechanism in EPO-producing cells by uremic toxin indoxyl sulfate was demonstrated in human hepatoma cell line HepG2 [6].
Other than a lack of EPO in CKD, other factors may contribute to anemia in patients with CKD. Plasma ALB concentration was negatively correlated with HCT. The results were similar to the previous study in CKD and control healthy dogs [14]. This association was also found in patients with diabetic nephrosclerosis [23]. Decreased ALB in CKD may be associated with reduced production from anorexia or increased urinary loss in protein losing nephropathy. Therefore, proteinuria may aggravate the progression of CKD by reduced ALB and other factors contributing to erythropoiesis, including iron, TF, EPO, transcobalamin, and/or copper [17]. Thus, heavy proteinuria could alter erythrocyte metabolism resulting in enhanced erythrocyte death and anemia [24]. Moreover, many anemic dogs with CKD failed to respond to the EPO treatment and iron supplementation [13, 14]. It is likely that iron metabolism is one of important factors affecting anemia in patients with CKD. The iron balance is regulated by dietary iron absorption and iron sequestration from storage sites, such as liver and reticuloendothelial macrophages. Among iron parameters, TIBC is a reliable indicator of iron metabolism. The iron content when TF is saturated with iron is TIBC. Total iron-binding capacity could indirectly indicate plasma TF level, which was confirmed by a strong positive relationship between TF and TIBC in the present study. Some studies recommended TF determination using immunologic-based techniques rather than TIBC, although genetic variation in TF was found in some populations [25]. The level of iron in dogs of all groups was lower than those measured from control healthy dogs [14]. The TIBC was lower in UPC ratio >4 group than UPC ratio <4 groups, and TIBC was negatively correlated with UPC ratio. Thus, TIBC was affected by the degree of proteinuria. Lower TIBC and HCT were found in both dogs and cats with CKD than in healthy control [14, 26]. Unfortunately, proteinuria was not evaluated in both studies.
Iron deficiency can be characterized as a true iron deficiency when serum iron and ferritin concentrations are low and TIBC is high. In contrast, in cases of functional iron deficiency, ferritin concentrations are generally normal or above the reference interval, and serum iron concentrations and TIBC are generally decreased [11]. Functional iron deficiency was suggested in CKD cats, in which mean total iron and TIBC were lower than control healthy cats with no alteration of ferritin level [26]. The same may be applied to dogs with CKD, especially those with proteinuria. Unfortunately, plasma ferritin was not measured in this study.
The present study showed that dogs with CKD with proteinuria had a urinary loss of iron and TF, resulting in a lower TIBC. The UPC ratio was correlated positively with both U-Iron/CR and U-TF/CR and negatively with TIBC. Excessive urinary losses of iron, TF, EPO, transcobalamin, and some metals were found in patients with nephrotic syndrome [17]. In humans with diabetic nephropathy, the urinary ALB was related to urinary TF, and urinary TF significantly increased with respect to the progression of glomerular diffuse lesions [27]. Higher urinary loss of TF than ALB was found due to higher isoelectric point of TF in which less polyanion may favor the higher excretion, although TF has slightly higher molecular weight than ALB (77 kD vs. 66 kD) [28]. The urinary TF was suggested to be used as a diagnostic marker of early diagnosis of renal disease in Stage I of CKD cat since leakage of urinary TF in urine precedes leakage of urinary ALB, and their sensitivity and specificity were higher than those of plasma CR concentration [18].
The U-Iron/CR and U-TF/CR were also correlated ($r = 0.486$, $p \leq 0.01$, $$n = 28$$). Urinary iron excretion was found to be associated with urinary TF and urinary protein in CKD human patients [29]. In a patient with overt proteinuria, iron/TF ratio in urine was greater than the ratio in plasma, suggesting that renal handling of iron may be dissociated from TF [30]. The inconsistent rate of excretion may be due to different rates of filtration, tubular reabsorption, and the existence of dissociated species of iron and TF that could be filtered.
This study cannot rule out the factors affecting some parameters, such as inflammation or nutritional status. Inflammatory cytokines were associated with iron metabolism and red blood cell profiles in patients with CKD [31]. Inflammatory cytokines can result in anemia by decreased production of endogenous EPO, delayed response of erythroid progenitor to EPO, and increased production of hepcidin which was extensively reviewed [8, 32, 33]. During the acute phase response of non-specific inflammatory reaction of the host, some negative acute phase proteins (APPs), such as ALB and TF, were reduced, while some positive APPs, such as serum amyloid A, were increased [34]. Furthermore, hepcidin, the iron regulatory hormone, which can be induced by inflammation and contributes to anemia was documented [7, 11, 35–38]. In cats with CKD, the mean serum iron concentration, TIBC, and HCT were lower, whereas serum amyloid A and hepcidin levels were higher than in healthy control cats [26]. However, no change in hepcidin was found in dogs with CKD [14]. Rather than inflammation, nutritional status can affect plasma TF concentration. A report on using TF as a nutritional marker for malnutrition in dogs receiving nutritional treatment was documented [39]. It is possible that the lower TF in this study may be in part due to the malnourishment of dogs with CKD.
In this study, anemia may be associated with external factors other than the degree of CKD and proteinuria. Anemia during the acute phase of naturally infected E. canis was reported to be associated with altered oxidative status, low iron levels, and high levels of both ferritin and TF [40]. Supplementation of iron had no effect on HCT. Similar results were found in dogs with CKD in which iron supplementation did not affect HCT, plasma iron levels, and TIBC [14]. In addition, darbepoetin administration did not relate to HCT level. The maximum number of darbepoetin administration was three injections in five dogs. The HCT was unaltered after injection, which may be due to the duration after injection until blood collection was too short, or dogs did not respond to darbepoetin. It was reported that median time to achieve an HCT ≥$30\%$ was 29 days after administration with a dose of 0.4–2.1 μg/kg given once a week [13]. The low response to darbepoetin treatment and iron supplements may also be a result of erythroid hypoplasia, which was commonly reported in dogs with CKD in varying stages [12]. This bone marrow feature could also affect erythropoiesis and HCT. However, bone marrow aspiration was not performed in this study. Finally, blood transfusion was not related to HCT in the present study. The HCT was declined quickly within a few weeks after transfusion.
This study has some limitations. The number of dogs with CKD in the present study was small. Moreover, the inflammatory cytokines, ferritin, EPO levels, and bone marrow status were not measured.
## Conclusion
High urinary loss of iron and TF along with low TIBC was associated with a degree of proteinuria and may be a contributing factor of anemia in dogs with CKD. Reduced urinary loss and/or supplementation of iron may be helpful in this situation.
## Authors’ Contributions
CB, NS, and SS: Conception and design of the study, statistical analysis, and drafted the manuscript. NS, MT, and TD: Data collection and laboratory analysis. CB, NS, and SS: Revised the manuscript. All authors have read and approved the final manuscript.
## Competing Interests
The authors declare that they have no competing interests.
## Publisher’s Note
Veterinary World remains neutral with regard to jurisdictional claims in published institutional affiliation.
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|
---
title: Chemical Characterization and Leishmanicidal Activity In Vitro and In Silico
of Natural Products Obtained from Leaves of Vernonanthura brasiliana (L.) H. Rob
(Asteraceae)
authors:
- Yuri Nascimento Fróes
- João Guilherme Nantes Araújo
- Joyce Resende dos Santos Gonçalves
- Milena de Jesus Marinho Garcia de Oliveira
- Gustavo Oliveira Everton
- Victor Elias Mouchrek Filho
- Maria Raimunda Chagas Silva
- Luís Douglas Miranda Silva
- Lucilene Amorim Silva
- Lídio Gonçalves Lima Neto
- Renata Mondêgo de Oliveira
- Mylena Andréa Oliveira Torres
- Luís Cláudio Nascimento da Silva
- Alberto Jorge Oliveira Lopes
- Amanda Silva dos Santos Aliança
- Cláudia Quintino da Rocha
- Joicy Cortez de Sá Sousa
journal: Metabolites
year: 2023
pmcid: PMC9967733
doi: 10.3390/metabo13020285
license: CC BY 4.0
---
# Chemical Characterization and Leishmanicidal Activity In Vitro and In Silico of Natural Products Obtained from Leaves of Vernonanthura brasiliana (L.) H. Rob (Asteraceae)
## Abstract
Vernonanthura brasiliana (L.) H. Rob is a medicinal plant used for the treatment of several infections. This study aimed to evaluate the antileishmanial activity of V. brasiliana leaves using in vitro and in silico approaches. The chemical composition of V. brasiliana leaf extract was determined through liquid chromatography-mass spectrometry (LC-MS). The inhibitory activity against *Leishmania amazonensis* promastigote was evaluated by the MTT method. In silico analysis was performed using Lanosterol 14alpha-demethylase (CYP51) as the target. The toxicity analysis was performed in RAW 264.7 cells and Tenebrio molitor larvae. LC-MS revealed the presence of 14 compounds in V. brasiliana crude extract, including flavonoids, flavones, sesquiterpene lactones, and quinic acids. Eriodictol (ΔGbind = −9.0), luteolin (ΔGbind = −8.7), and apigenin (ΔGbind = −8.6) obtained greater strength of molecular interaction with lanosterol demethylase in the molecular docking study. The hexane fraction of V. brasiliana showed the best leishmanicidal activity against L. amazonensis in vitro (IC50 12.44 ± 0.875 µg·mL−1) and low cytotoxicity in RAW 264.7 cells (CC50 314.89 µg·mL−1, SI = 25.30) and T. molitor larvae. However, the hexane fraction and Amphotericin-B had antagonistic interaction (FICI index ≥ 4.0). This study revealed that V. brasiliana and its metabolites are potential sources of lead compounds for drugs for leishmaniasis treatment.
## 1. Introduction
Leishmaniasis is among the neglected tropical diseases (NTDs). It has a wide geographic distribution and is endemic in underdeveloped countries [1,2]. According to the World Health Organization (WHO), an estimated 12 million people are infected annually, with about 20.000 to 30.000 deaths, and 350 million people are at risk of infection [2]. It is a complex and spectral anthropozoonosis caused by several species of the Leishmania genus. According to the infecting species and the immunological development of each person, it can evolve into different clinical forms. Among the clinical presentations of leishmaniasis, the cutaneous form stands out, which has *Leishmania amazonensis* as the major causative agent [3].
Pentavalent antimonials are still the drugs of choice for treating the disease. These medications have high toxicity, adverse effects during and after treatment, and prolonged time of parenteral administration, which leads to low patient adherence to treatment [4,5]. In addition, when used in sub-doses or discontinuously, they do not have the desired effect, which favors parasite resistance or relapses [6,7]. This context indicates the need to discover new alternatives for therapy against leishmaniasis.
A wide range of traditional medicine and natural products can be considered for therapy against several diseases, including COVID-19 [8,9], cancer [10,11], parasitic infections [12,13], diabetes [14,15], and obesity [16]. In fact, the WHO recognizes the importance of traditional medicine, especially in underdeveloped countries, where approximately $85\%$ of the population uses medicinal plants as a therapeutic alternative. In Brazil, the species *Vernonanthura brasiliana* (L.) H. Rob. belongs to the list of plants of interest to the public health system. V. brasiliana, popularly known as “assa-peixe”, is endemic to the Brazilian Cerrado (Brazilian Savannah) biome but can be found in other biomes due to its cosmopolitan and pantropical aspect [17,18,19,20]. It belongs to the Asteraceae family, the tribe Vernonieae, with more than 1000 species cataloged in the tribe. Among these, some species have been used in traditional medicine to treat numerous diseases [17].
The plants from the genus Vernonanthura are widely used, especially the leaves and roots, in cases of flu, colds, cough, bronchitis, bruises, hemorrhoids, rheumatism, hepatic colic, bleeding, and uterine infections [17,21]. Studies show the potential of this plant as a therapeutic alternative with anti-inflammatory, antimicrobial, antifungal, insecticidal, antioxidant, immunomodulatory, anthelmintic, antinociceptive, and antiprotozoal action [12,18,22,23,24,25]. Some studies also report the activity of the essential oil of V. brasiliana against L. amazonensis, L. infantum, and L. donovani promastigotes [23,26,27].
Due to the difficulties in treating leishmaniasis, this research aimed to investigate the anti-Leishmania action of V. brasiliana extract and fractions. The in silico interactions of the compounds detected in the V. brasiliana extract were assessed using the enzyme cytochrome P450 Lanosterol 14alpha-demethylase (CYP51) as the target. Furthermore, the toxicity of these products was evaluated in the RAW 264.7 cell line and Tenebrio molitor larvae, seeking to support the idea of this plant as a source for new compounds with less toxicity and leishmanicidal efficacy.
## 2.1. Plant Material
Aerial parts of V. brasiliana were collected in the city of Bacabeira, Maranhão State, Brazil (3°03′34.5″ S 44°20′12.4″ W), at the dry period, 8:00 a.m. The plant material was identified at the Herbarium “Prisco Bezerra” of the Federal University of Ceará, and a voucher specimen was deposited (number 55227).
## 2.2. Preparation of Crude Extracts and Fractions
The leaves were dried and ground in a knife mill. The hydroalcoholic crude extract of V. brasiliana (EBVb) was obtained after maceration and agitation in $70\%$ ethyl alcohol for seven days, in a proportion of 3:1 (v:m) (alcohol and plant material, respectively). The aqueous crude extract was obtained in the same conditions as EBVb [28]. EBVb was concentrated in a rotary evaporator (Fisatom® 802, São Paulo, SP, Brazil) and lyophilized (Terroni® Enterprise, São Carlos, SP, Brazil). EBVb (1 g) was successively partitioned with hexane, ethyl acetate, and methanol to obtain the respective fractions (FHVb, FAEVb, and FMVb). The samples were stored under refrigeration and protected from light until analysis.
## 2.3. Liquid Chromatography-Mass Spectrometry Analyses (LC-MS)
For chemical characterization, 10 mg of each sample was dissolved in methanol (1.0 mL). The samples were filtered on a PTFE® filter (0.22 µm and 20 mL) and injected into a liquid chromatograph coupled to a mass spectrometer (Amazon Speed® ETD-Bruker, Billerica, MA, USA). The chromatographic profile of EBVb and fractions were analyzed in the LCQ mass spectrometer (Thermo Scientific®, San Jose, CA, USA), equipped with a column (Phenomenex® Luna C18 columns, California, CA, USA) 250 mm × 4.6 mm; 5 μm, with a flow rate of 0.9 mL/min. The identification of EBVb compounds and fractions was performed by fragmentation mechanisms in negative mode, comparing mass spectral data with the literature.
## 2.4. In Silico Studies and Molecular Docking
The compounds identified in EBVb were structurally schematized in 3D with the GaussView® 5.0.8, Wallingford, CT, EUA, program [29]. The geometric and vibrational properties were calculated and vacuum optimized at the Density Functional Theory (DFT) level, using the hybrid function B3LYP combined with the base set 6–31 ++ G (d, p) with the Gaussian® 09, Wallingford, CT, EUA [30].
The sterol 14-alpha-demethylase (CYP51) of L. infantum ($99.3\%$ similarity with L. amazonensis) was obtained from the Protein Data Bank (PDB) (#3L4D), resolved by X-ray crystallography with a resolution of 2.75 Å. Fluconazole and other molecules in the crystal were removed, keeping only one of the two homologous chains and the HEME group.
Molecular docking procedures were performed using Autodock® Vina (La Jolla, California, EUA) [31]. The L. infantum CYP51 (LiCYP51) structure and ligands were prepared for molecular anchorage calculations using Autodock® Tools 1.5.7, (La Jolla, California, EUA [32]. The docking methodology described in the literature [33] was used, with modifications [33]. Gasteiger partial charges were calculated after adding all hydrogens for both ligands and LiCYP51 structure. The dimensions of the cubic box on the X, Y, and Z axes were 30 × 30 × 30. The grid box was centered on the Iron atom of the LiCYP51 HEME group.
The conformations of the initial interaction coordinates of the LiCYP51 complexes and V. brasiliana compounds were chosen based on the best binding free energy parameters and visual inspection.
## 2.5. Parasites
Promastigote forms of L. amazonensis (MHOM/BR/1987/BA-125) were cultured at 26 °C in Schneider’s Insect Medium, supplemented with $10\%$ fetal bovine serum, 100 U/mL of penicillin, and 100 μg·mL−1 of streptomycin.
## 2.6. Activity against Promastigote Forms
L. amazonensis promastigotes (106 parasites. mL−1) were plated into 96-well plates and treated with different concentrations of EBVb and fractions obtained by serial dilutions (512 to 4 µg·mL−1). After 24, 48, and 72 h of incubation, the viability of the parasites was measured by the colorimetric method with tetrazolium-dye 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) [34] and Neubauer chamber counting. Aspects such as mobility, size, and shape of the parasites were also evaluated. MTT solution (10 μL; 5 mg·mL−1) was added to each well and, after four hours, 100 μL of DMSO was added to dissolve the formazan crystals. The absorbance was analyzed on a spectrophotometer at a wavelength of 570 nm. Data were normalized using the formula: % survival = sample OD − blank OD/control OD − blank OD × 100. The results were used to calculate the IC50 (inhibitory concentration for $50\%$ of parasites). Meglumine antimoniate and amphotericin-B were used as reference drugs. All tests were performed in triplicate and repeated at least twice.
## 2.7. Fluorescence Microscopy
L. amazonensis promastigotes (106 parasites·mL−1) were incubated with EBVb and FHVb (1 × IC50 and 2 × IC50). After 48 h, acridine orange (3,6-dimethyl-amino-acridine; 10 µg·mL−1) was added to each sample, for 20 min. Phosphate buffer solution, $70\%$ methanol, and Amphotericin-B were used as controls. For fluorescence evaluation, slides were prepared and analyzed in Axio Imager fluorescence microscope (Zeiss®, Jena, Germany) (Alexa Filter-488 nm).
## 2.8. Determination of Drug Interactions
After preliminary tests, the hexane fraction of V. brasiliana (FHVb) and amphotericin-B were selected to conduct drug interaction assays. The interaction of the two substances was assessed using the adapted isobologram method [35]. The IC50 values of the compounds were used to establish the concentrations of each drug in the combination:Combination 1 (5:0): 160 µg·mL−1 FHVb + 0.0 µg·mL−1 amphotericin-B. Combination 2 (4:1): 80 µg·mL−1 FHVb + 0.25 µg·mL−1 amphotericin-B. Combination 3 (3:2): 40 µg·mL−1 FHVb + 0.5 µg·mL−1 amphotericin-B. Combination 4 (2:3): 20 µg·mL−1 FHVb + 1 µg·mL−1 amphotericin-B. Combination 5 (1:4): 10 µg·mL−1 FHVb + 2 µg·mL−1 amphotericin-B. Combination 6 (0:5): 5 µg·mL−1 FHVb + 4 µg·mL−1 amphotericin-B.
The experiments were performed in the same way as described in item 2.6. After 72 h, the viability of L. amazonensis promastigotes were measured by Neubauer chamber counting. The results were normalized in percentage. After data normalization, fractional inhibitory concentrations (FIC) at the IC50 level were calculated for both drugs. The value obtained was used to classify the nature of the interaction as synergistic (FICI < 0.5), additive (0.5 < FICI < 4), or antagonist (FICI > 4).
## 2.9. Cytotoxicity Assay in RAW 264.7 Cells
The RAW 264.7 cell line, provided by the Immunophysiology Laboratory of the Federal University of Maranhão—UFMA, was cultured in RPMI medium, supplemented with $10\%$ FBS, 20 mM of L-glutamine, $7.5\%$ sodium bicarbonate, penicillin (100 μg·mL−1), and streptomycin (50 μg·mL−1), at 37 °C and $5\%$ CO2. The cytotoxic effect of natural products of V. brasiliana was performed using the RAW 264.7 cell line. The cells were seeded in 96-well plates (5 × 104 cells/well) and, after 24 h, were treated with different concentrations of EBVb and FHVb (1024 to 8 µg·mL−1). After 48 h, cell viability was measured by MTT colorimetric assay [34,36]. Culture medium and DMSO $20\%$ (40 µg·mL−1) were used, respectively, as negative and cytotoxic controls. The plates were analyzed in a microplate reader, at a wavelength of 570 nm. Data were normalized for CC50 (cytotoxic concentration for $50\%$ of cells) calculation and the selectivity index (CC50/IC50 ratio). Tests were performed in triplicate.
## 2.10. Toxicity in Tenebrio Molitor Larvae
In vivo toxic effect of the compounds with leishmanicidal activity was evaluated on larvae of the insect T. molitor. Larvae (100.0 mg) were randomly divided into groups (10 larvae/group). Before inoculating the natural compounds, the cuticles were cleaned with $70\%$ alcohol, and then 10.0 µL of each test solution was injected. Glucantime® was used as a positive control and $1\%$ PBS as a negative control. The survival curve was determined by the absence of movement or total melanization of the larvae over five days. The damage caused by natural products used in T. molitor larvae was also evaluated. The degree of suffering was observed through melanization, movement, reaction to stimuli, and survival [37].
## 2.11. Statistical Analyses
Values were expressed as mean ± standard deviation. The results were analyzed using a two-way analysis of variance (ANOVA) followed by the Tukey post hoc test. For the toxicity tests in T. molitor larvae, the log-rank test (Mantel–Cox) was performed, and to evaluate the difference between the severity degree, the two-way ANOVA was used. Differences were considered significant when $p \leq 0.05.$
## 3.1. Chromatography and Identification of Compounds
To chemically characterize and prospect the studied species, correlating it with its biological potential investigated in this study, the EBVb was submitted to chromatographic analysis (LC-MS), and 14 peaks were identified, listed according to the retention time, as shown in Figure 1.
The identified compounds are classified as flavonoids, flavones, sesquiterpene lactones, and quinic acids. The identification was elucidated by comparing data obtained by LC-MS with the fragmentation profiles described in the literature (Table 1).
## 3.2. In Silico Studies and Molecular Docking
For molecular docking calculations, all compounds identified in EBVb were evaluated. Among the evaluated compounds, the best free binding energy parameters were presented by eriodyctiol, luteolin, and apigenin, with values of −9.0 kcal/mol, −8.7 kcal/mol, and −8.6 kcal/mol, respectively.
In addition to the compounds present in the extract, the azole antifungal fluconazole was also anchored. It is observed that eriodyctiol, luteolin, and apigenin showed higher affinity parameters than the antifungal (Table 2). Fluconazole is the native molecule of the LiCYP51 (*Leishmania infantum* CYP51) crystal structure, so fluconazole redocking was performed to validate the docking protocol. The root-mean-square deviation (RMSD) between the predicted coupling conformation and the observed X-ray crystal structure was 1.47 Å. Values below 2 Å indicate that the coupling protocol is valid. Other compounds identified in the V. brasiliana extract showed more discrete affinity parameters when compared with eriodyctiol, luteolin, and apigenin, but still suggested a favorable interaction with LiCYP51. The results of the free binding energy values of all ligands are shown in Table 2.
Evaluating the LiCYP51 complex with the ligands and the best binding free energy parameters, it is observed that all ligands performed stable interactions with amino acid residues of the active site of LiCYP51, those being eriodictyol with hydrogen bonds with Tyr115, Ala286, Met357 and Met459 residues, and van der Waals interactions with Tyr102, Met105, Phe109, Leu126, Phe289, Val356 residues and with the HEME group (Figure 2).
Luteolin was stabilized with the amino acid residues of LiCYP51 by hydrogen bonds with the residues Tyr115, Ala286, Met357, and Met459, and van der Waals interactions with Tyr102, Phe109, Phe289, Val356, Leu358, and Val460 residues and with the HEME group. Another molecule is apigenin with stabilization in Tyr115, Ala286, Met459 residues (hydrogen bonds) and Tyr102, Met105, Phe109, Phe289, Val356, Met357, Leu358 and Val460, and the HEME group (van der Waals) (Figure 2).
## 3.3. Leishmanicidal Activity
The natural products from the leaves of V. brasiliana demonstrated action against the promastigote forms of L. amazonensis, with satisfactory in vitro inhibition, characterized by low IC50 values, at the three evaluated times, 24 h, 48 h, and 72 h. The lowest IC50 was for FHVb, equal to 5.76 µg·mL−1 in the first 24 h of treatment, as shown in Table 3.
EBVb showed a moderate concentration-dependent inhibition against the promastigote forms between 24 and 72 h of exposure. There was no significant difference between the times of 24 and 48 h ($$p \leq 0.8890$$); however, there was a difference between the times of 48 and 72 h due to the reduction of the IC50 ($p \leq 0.0001$).
FAEVb also showed moderate activity against the parasites, but there was a resumption of parasite growth and an increase in IC50 between 24 and 72 h ($p \leq 0.0001$). FHVb showed a significant difference between its IC50 values in the incubation times ($p \leq 0.0001$). The FMVb showed very divergent IC50 between the times evaluated, suggesting instability of the fraction.
Among the fractions of V. brasiliana, FHVb was the one that best induced parasitic inhibition at 24 and 48 h of exposure, showing a significant difference between its IC50 values in the treatment times ($p \leq 0.0001$).
The first-choice reference drug, meglumine antimoniate, was ineffective against the clinical isolate used in our in vitro assays. Little or no change was observed in the mobility and size of the parasites during 48 h of exposure. Therefore, it was not used as a positive control for the experiment. However, amphotericin-B, used as a chemotherapy drug of second choice in Brazil, proven to be effective, destroying or reducing the size and mobility of the parasites at very low concentrations.
To verify and illustrate the action of the natural products evaluated on the promastigote forms of L. amazonensis, an analysis was carried out by fluorescence microscopy, using acridine orange. The exposure for 48 h of the promastigote forms to the IC50 of the test solutions, EBVb, FHVb, and amphotericin-B, confirmed the leishmanicidal action of the tested products, with a reduction of more than half of the load of the parasitic inoculum, which was standardized at a concentration of 1.106 mL−1 cells. Also noteworthy is a flagellar shortening in the promastigote forms of L. amazonensis treated with FHVb and amphotericin-B (Figure 3).
Furthermore, when using concentrations of twice the IC50 value, there was an almost total reduction of the parasites, in agreement with the indices of leishmanicidal activity obtained. The controls, negative (only parasites in Schneider culture medium) and positive (parasites treated with $70\%$ methanol) were as expected, agglomeration of promastigote forms and destruction of promastigote forms, respectively (Figure 3).
## 3.4. Determination of Drug Interactions
Among the natural products evaluated, FHVb presented the best results, and so was chosen for the drug interaction test. The results of the interaction analysis, combined or isolated in each association, are shown in Table 4. The interaction between FHVb and amphotericin-B was classified as antagonistic, with a FICI index greater than or equal to 4.0.
In the first combination, no L. amazonensis promastigotes were seen, therefore, there was a clear field of view. In the second combination, only one promastigote form was seen per field of view, with low mobility and flagellar shortening. The other combinations and amphotericin-B alone reduced the cell viability of the parasites by $100\%$. These results classified FHVb as a natural product with antagonistic action (FICI ≥ 4.0) on amphotericin-B in vitro.
## 3.5. In Vitro Cytotoxicity
In the search for a natural product with less toxicity and leishmanicidal efficiency, cytotoxic tests were conducted in RAW 264.7 cells for the natural compounds of V. brasiliana, with better leishmanicidal action. After 48 h of exposition, the cytotoxic concentration values for $50\%$ of the cells (CC50) ranged from 8 to 314, 8 µg·mL−1 (Table 5).
EBVb and FAEVb showed low CC50 values. The EBVb showed abnormal data, and the lowest concentration used for the assays (8 µg·mL−1) resulted in a total reduction of cell viability in 48 h, a result confirmed with visualization under an inverted optical microscope and a Neubauer chamber.
FAEVb showed a moderate value of CC50; however, when the ratio between its indices (CC50/IC50) was calculated as a low index, selectivity was obtained. FHVb was the least cytotoxic among the evaluated compounds, presenting high selectivity to the parasites (SI = 25.3). The cytotoxic control (DMSO) reduced the cell viability by $100\%$ in 48 h of exposure; therefore, the confidence interval values and data correlation (R²) were not determined.
## 3.6. In Vivo Toxicity against Tenebrio Molitor
Subsequently, it was decided to conduct an assay of the natural products, EBVb and FHVb, and the leishmanicidal reference drug (Glucantime®), in an alternative model (in vivo), with larvae of T. molitor. The larvae exposed to Glucantime® suffered melanization and reduced mobility, an aspect of suffering from the third day of evaluation, where $30\%$ of the larvae did not resist a concentration of 200 µg·mL−1. This fact was noticed with greater intensity for the EBVb: in 24 h of exposition, only $40\%$ of the larvae were alive, also with melanization and low mobility. After the third day, only $30\%$ of the larvae were alive at both concentrations used in the assays (Figure 4).
The percentage of larval survival against exposure to FHVb was high compared to the others evaluated, where only one larva did not survive in both concentrations evaluated, that is, $90\%$ of the larvae survived. The larvae that remained alive until the fifth day did not show melanization, and remained with unaltered mobility (Figure 4).
When multiple comparisons of the degree (score) of the suffering of larvae exposed to natural products (EBVb and FHVb) and Glucantime® were performed, there was no difference between EBVb and Glucantime® ($$p \leq 0.9958$$) and the score was lower. However, FHVb was the one that least attacked the larvae (highest score), with no difference from the negative control (PBS $1\%$) ($$p \leq 0.9344$$)(Figure 5).
## 4. Discussion
This research evaluated the chemical composition of natural products obtained from the leaves of V. brasiliana, to elucidate their ability to inhibit the growth of promastigote forms of L. amazonensis, in addition to evaluating the in vitro cytotoxicity and in vivo toxicity, an alternative model.
The genus Vernonanthura has bioactive potential as they are rich in terpenes and sesquiterpenes, with reports of in vitro antiplasmodic, anti-Leishmania, antimicrobial, anti-schistosomiasis, and anti-inflammatory activity [20]. This genus has previous reports of activity against the promastigote forms of L. amazonensis and L. infantum species [12,28].
Chemical and chromatographic analyses of EBVb revealed the presence of 14 compounds, classified as flavonoids, flavones, sesquiterpene lactones, and quinic acids. There was disagreement regarding the number and types of compounds identified in our research group by previous chromatographic analyses, where they identified 24 different compounds in the same plant species. It is understood that the variation of metabolites produced by a plant can be attributed to physical, chemical, and biological factors (phytopathogens) and edaphoclimatic characteristics (weather, climate, wind, altitude, etc.) [ 38,39].
In silico studies were conducted to evaluate the binding strength between the compounds identified in this work, described in Table 1. The flavonoids eriodyctiol, luteolin, and apigenin obtained higher binding energy with Lanosterol demethylase [40], a fundamental compound for the biosynthesis of ergosterol specific to the Leishmania genus. Lanosterol demethylase is an enzyme complex (P45014DM) essential for ergosterol metabolic pathways that participate in the organization of the cytoplasmic membrane of the parasites [41].
Amphotericin-B is a drug that traditionally acts on fungal infections, binding to ergosterol in the plasma membranes of the cells of these organisms, causing disruption of membrane function, and allowing the leakage of electrolytes (particularly potassium) and small molecules, resulting in death of the cell [42], and has been successfully used for the treatment of Leishmaniasis. Another noteworthy fungicide fluconazole, which inhibits CYP51, which is responsible for the synthesis of ergosterol; this drug is also capable of inhibiting CYP51 of L. infantum [43]. Thus, CYP51 is a relevant target for research of compounds with leishmanicidal activity. This enzyme plays a key role in the synthesis of lanosterol to ergosterol. Ergosterol is an essential compound in the fungal cell membrane, and once lanosterol accumulation occurs due to non-conversion to ergosterol, the plasma membrane is disrupted, damaging the cell [42,43].
Based on the results obtained, it was observed that EBVb and its fractions have leishmanicidal activity against L. amazonensis. The compounds identified in the extract were submitted to molecular docking to evaluate the possible interaction of these compounds with the crystallographic structure of LiCYP51, which has a similarity of $99.3\%$ with the enzyme of L. amazonensis, which was not available. Negative values of free binding energies indicate that these interactions are favorable for the formation of the ligand-receptor complex [33]. Through molecular docking, we found that, among the compounds identified in the extract, eriodictiol, luteolin, and apigenin were the compounds that presented the most favorable parameters for complex formation with LiCYP51.
Thus, our results suggest that the biological activity of V. brasiliana against L. amazonensis may also be associated with an inhibition of ergosterol biosynthesis, mediated by CYP51. Thus, it is inferred that the metabolites of V. brasiliana can be considered potential new leishmanicidal candidates. These metabolites found in V. brasiliana have already been detected in other plants, such as *Pistacia atlantica* Desf and Limonium aureum, species found in the East. P. atlantica has been reported to reduce the development of cutaneous lesions triggered by Leishmania major in Balb/c [44,45,46].
Some molecules present in EBVb have antimicrobial and leishmanicidal activities, such as eriodictiol, previously isolated from *Psorothamnus polydenius* and Limonium brasiliense. Eriodictiol showed excellent inhibition against promastigote forms of L. donovani (IC50 = 25 ± 4 µg·mL−1, CC50 = 32.8 ± 12.3 µg·mL−1) with a reduction in the number of infected macrophages by 55 ± $16\%$ [41,47], and against *Leishmania amazonensis* (IC50 = 12.38 µg·mL−1) [46,48]. Another example is the flavonoid luteolin which has in vitro and in vivo ability to inhibit L. donovani. In silico studies also revealed that luteolin can inhibit the action of topoisomerase II, an important kinetoplast DNA (kDNA) replication enzyme, promoting apoptosis of parasites and inducing low toxicity to mammalian cells [49,50,51].
Apigenin is another flavonoid with several known pharmacological actions, including antibacterial, anti-inflammatory, antioxidant, and leishmanicidal effects [52,53,54,55,56,57]. Apigenin inhibits arginase in L. amazonensis and L. donovani in vitro and in vivo; blocking this enzyme can trigger oxidative stress, controlling the infection. The effect of apigenin on L. amazonensis and L. tropica may be associated with the production of reactive oxygen species (ROS) leading to mitochondrial collapse [58,59,60]. Drug combinations, such as miltefosine and apigenin, have already been studied, demonstrating a reduction in the parasite load of the amastigote form of L. amazonensis in Balb/c mice [61,62].
In vitro studies about the interaction (synergistic, indifferent, or antagonistic effects) of natural products and reference drugs are few reported. An additive effect between Glucantime® and a natural compound isolated against L. amazonensis has already been observed by Gonçalves-Oliveira et al. [ 62]. The synergism of isolated products can be effective for the development of new chemotherapeutics combined with natural compounds [62,63]. Moreover, the incorporation of natural products and conventional drugs into nanoformulations opens a new avenue for antileishmanial therapy [64,65,66].
The toxicity of the natural products used in this study was also evaluated using larvae of T. molitor. As expected, the reference drug for the treatment of cutaneous leishmaniasis (Glucantime®) presented high toxicity and suffering for T. molitor larvae compared to the negative control. When the larvae were exposed to EBVb, suffering and a lower percentage of survival were also observed compared to FHVb, which demonstrated the lowest toxicity, a low index of suffering, and a higher percentage of survival of T. molitor larvae.
## 5. Conclusions
The hexane fraction of V. brasiliana is a promising source of leishmanicidal compounds, demonstrating greater potency (dose inhibition) against parasites. This fraction has low toxicity towards RAW 264.7 cells and T. molitor larvae and showed a good selectivity index. The compounds identified in the crude extract, such as eriodictiol, luteolin, and apigenin, demonstrate excellent strength of molecular interaction on lanosterol demethylase, an important enzyme that participates in the formation of membrane ergosterol in the parasites. Therefore, these results reinforce the continuity of studies with this plant species for further biomedical explanations, further strengthening the idea of the hexane fraction as a raw material for the isolation of metabolites and/or development of new chemotherapeutics for the treatment of leishmaniasis.
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|
---
title: Transcriptomic Analysis Reveals Dysregulation of the Mycobiome and Archaeome
and Distinct Oncogenic Characteristics according to Subtype and Gender in Papillary
Thyroid Carcinoma
authors:
- Daniel John
- Rishabh Yalamarty
- Armon Barakchi
- Tianyi Chen
- Jaideep Chakladar
- Wei Tse Li
- Weg M. Ongkeko
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967748
doi: 10.3390/ijms24043148
license: CC BY 4.0
---
# Transcriptomic Analysis Reveals Dysregulation of the Mycobiome and Archaeome and Distinct Oncogenic Characteristics according to Subtype and Gender in Papillary Thyroid Carcinoma
## Abstract
Papillary Thyroid Carcinoma (PTC) is characterized by unique tumor morphology, treatment response, and patient outcomes according to subtype and gender. While previous studies have implicated the intratumor bacterial microbiome in the incidence and progression of PTC, few studies have investigated the potential role of fungal and archaeal species in oncogenesis. In this study, we aimed to characterize the intratumor mycobiome and archaeometry in PTC with respect to its three primary subtypes: Classical (CPTC), Follicular Variant (FVPTC), and Tall Cell (TCPTC), and also with respect to gender. RNA-sequencing data were downloaded from The Cancer Genome Atlas (TCGA), including 453 primary tumor tissue samples and 54 adjacent solid tissue normal samples. The PathoScope 2.0 framework was used to extract fungal and archaeal microbial read counts from raw RNA-sequencing data. Overall, we found that the intratumor mycobiome and archaeometry share significant similarities in CPTC, FVPTC, and TCPTC, although most dysregulated species in CPTC are underabundant compared to normal. Furthermore, differences between the mycobiome and archaeometry were more significant between males and females, with a disproportionate number of fungal species overabundant in female tumor samples. Additionally, the expression of oncogenic PTC pathways was distinct across CPTC, FVPTC, and TCPTC, indicating that these microbes may uniquely contribute to PTC pathogenesis in each subtype. Furthermore, differences in the expression of these pathways were observed between males and females. Finally, we found a specific panel of fungi to be dysregulated in BRAF V600E-positive tumors. This study demonstrates the potential importance of microbial species to PTC incidence and oncogenesis.
## 1. Introduction
Thyroid cancer is the fastest-growing cancer in the world [1,2] and the fifth most common cancer in women [3], accounting for more than 586,000 new cases in 2020 [2]. Papillary Thyroid Carcinoma (PTC) accounts for more than $88\%$ of total thyroid cancer cases and consists of three primary variants, each of which is characterized by a unique treatment course and prognosis [4,5]. Classical Papillary Thyroid Carcinoma (CPTC) is the most common subtype, consisting of more than $67\%$ of total PTC diagnoses in the US from 2000–2017 [6]. While the standard definition has varied frequently, Follicular Variant (FVPTC) prognostically lies between CPTC and Follicular Papillary Thyroid Carcinoma (FPTC) and is associated with a high mortality rate and increased metastasis compared to CPTC [7]. Although much less frequent in incidence, the Tall Cell (TCPTC) variant is considered one of the most aggressive forms of PTC, exhibiting significantly poorer prognosis and 5-year survival rates compared to classical forms of PTC [8,9].
While only a few risk factors for PTC are understood, gender is a defining feature of PTC occurrence and development [10]. Female patients are three times more likely to be diagnosed with PTC than males [11,12]. Despite the significantly higher incidence rates of PTC in females, the prognostic significance of gender in PTC does not appear to follow the same trend. In a retrospective cohort study of 3572 PTC patients, it was found that overall survival outcomes were comparable between men and women. An increased Hazards Ratio (HR) was observed for men diagnosed before 55 years of age, whereas the HR was similar for men and women diagnosed between 55–69 years of age [12]. Similarly, a comprehensive study of 43,712 PTC patients in the US using the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) cancer registry found significantly elevated mortality among male PTC patients after adjusting for confounding variables [13]. It is worth noting that these gender differences are primarily prevalent in CPTC, whereas patients with more lethal variants of PTC experience similar incidence rates and survival characteristics across gender comparisons [14]. Several potential mechanisms, such as differences in sex hormones and reproductive factors [11], have been proposed as an explanation for this disparity, but studies have not conclusively proven a mechanism for these differences. Thus, while PTC subtype and gender disparities in PTC incidence and outcomes are clearly evident, more research is needed to elucidate how such differences contribute to PTC oncogenesis.
Studies of the human microbiome have revealed its important implications on the human body and the pathogenesis of a variety of diseases [15,16]. While early studies of the microbiome focused primarily on the interactions of gut flora with innate phenotypes [17,18], novel studies have characterized the microbiome as an important driver of various diseases, including inflammatory bowel disease (IBD) [19,20], arthritis [21,22], Alzheimer’s [23,24], diabetes [25,26], cardiovascular disease [27,28] and cancer [29]. The intratumor microbiome in cancer has emerged as an important player in mediating effective immune response, treatment efficacy, and cell survival through the production of metabolites and downstream interactions within the tumor microenvironment [30,31,32]. Previously, we have implicated the intratumor microbiome in head and neck [33], pancreas [34], prostate [35], lung [36], and bladder [37] cancers, particularly in initiating oncogenesis through immune response, mutation events, methylation, microRNAs (miRNA) and more.
In addition to these studies, we also characterized the intratumor bacterial microbiome in PTC, demonstrating its unique implications for PTC prognosis through immunological pathways, mutation events, and gene methylation. Importantly, we found significantly distinct microbial and potential mechanistic landscapes across PTC subtype and gender comparisons, indicating that these factors likely serve as an important modulator of the intratumor microbiome in PTC. Additionally, we also found unique oncogenic signature pathways associated with each PTC subtype, further indicating the importance of studying the transcriptomic landscape according to these clinical characteristics [38].
Given our previous findings of the bacterial microbiome in PTC, we aimed to further investigate intratumor fungal and archaeal microbes according to PTC subtype and gender comparisons. In this study, we characterized the similarities and differences in the PTC mycobiome and archaeometry according to PTC subtype and gender comparisons. We first identified significantly dysregulated microbes according to these cohorts, assessed the relevance of these microbes with patient clinical variables, investigated their correlations with known driver gene signature pathways of PTC oncogenesis, such as BRAF and RET/PTC [39,40], and finally studied the association of these intratumor microbes with the presence of the BRAF V600E mutation (Figure 1).
## 2.1. Data Acquisition and Extraction Identification of Microbial Reads
In order to evaluate intratumor fungal and archaeal microbial species pertinent to PTC, we downloaded raw RNA-sequencing data for 453 PTC patients and 54 adjacent normals from The Cancer Genome Atlas (TCGA). Fungal and Archaeal microbial read counts were extracted from RNA-sequencing data using the PathoScope 2.0 framework. Clinical data for patients in the TCGA-THCA project were downloaded from the Broad Institute GDAC Firehose Database (https://gdac.broadinstitute.org/), accessed on 15 January 2022.
## 2.2. Removal of Potential Contaminants
Following the successful extraction of microbial read counts, we identified potential contaminants using three methods of contamination correction. Selected plots generated in this analysis are shown in Figure 2. A full list of fungal and archaeal contaminants identified in our study is included in Supplementary File S1. First, we identified six potential archaea contaminants using correction by sequencing date (Figure 2D). We did not identify any potential fungal contaminants using correction by sequencing date (Figure 2A). Next, we evaluated potential fungal and archaeal contaminants likely introduced by sequencing plates. Our analysis did not, however, identify any fungal or archaeal contaminants using correction by sequencing plate (Figure 2B,E). Finally, we identified 1492 fungal and 286 potential archaeal contaminants using correction by total microbe abundance (Figure 2C,F). In total, we identified 1492 and 292 potential fungal and archaeal contaminants, respectively. These microbes were removed from the original 9829 fungal and 483 archaeal species extracted for downstream analyses.
## 2.3. Differentially Abundant Fungal and Archaeal Species across PTC Subtype and Gender Comparisons
In order to characterize the role of the intratumor mycobiome and archaeometry in PTC, we first identified and compared significantly dysregulated fungal and archaeal species across PTC subtype and gender comparisons. Significantly differentially abundant microbes were defined by a p-value of <0.05 and a log-fold change (FC) > 1. The Bonferroni method was used to correct p-values for multiple hypothesis testing. We first identified 109 significantly dysregulated microbes between tumor and normal tissue (Supplementary File S2). Of these significantly dysregulated species, 14 fungi were overabundant in tumor tissue, while 94 fungi and one archaeal species were overabundant in normal tissue. Fungal species overabundant in PTC tumor tissue included *Metarhizium acridum* CQMa 102, *Saccharomyces cerevisiae* YJM1338, and Phaffia rhodozyma, which we similarly found to be abundant in HNSCC tumor tissue [33]. Additionally, the archaeal species *Anomalluma dodsoniana* was overabundant in PTC tumor tissue compared to adjacent normal. We found significantly more species overabundant in normal tissue, however, including Candida albicans, Microallomyces dendroideus, and the archaeal species Anomalluma dodsoniana.
Additionally, we identified similarly significantly dysregulated fungal and archaeal microbes in comparisons of CPTC vs normal samples, FCPTC vs normal samples, and TCPTC vs normal samples with respect to the direction of dysregulation. Select microbes and corresponding overlaps across these subtypes are visualized in Figure 3, and the full list of significantly dysregulated microbes is included in Supplementary File S2. In total, 63 fungal species were overabundant in CPTC, FVPTC, and TCPTC, including Botrytis cinerea, Pichia cephalocereana, and *Trematosphaeria pertusa* (Figure 3A,C, Supplementary File S2). The majority of dysregulated fungal and archaeal species were overabundant in comparisons of PTC subtypes with normal samples. Specifically, 24 fungal species were overabundant in TCPTC and FVPTC patients, 3 fungal species were overabundant in TCPTC and CPTC patients, 12 fungal species were overabundant in FVPTC and CPTC patients, 33 fungal species and one archaeal species were overabundant in TCPTC only, 28 fungal and 2 archaeal species were overabundant in FVPTC only, and only one fungal species was overabundant in CPTC only (Figure 3A). Only CPTC and TCPTC subtypes shared similarly underabundant species, which included *Rhizopus arrhizus* and uncultured Uromyces. CPTC exhibited the most underabundant species, with 16 underabundant fungi compared to normal samples, while FVPTC samples were significantly underabundant in 6 fungal species, and TCPTC displayed correlations to zero significantly underabundant microbes compared to normal samples. Interestingly, significantly dysregulated archaeal species were distinct in each PTC subtype: uncultured euryarchaeote Alv-FOS5 was found to be overabundant in TCPTC tumor tissue compared to normal samples (Figure 3C); uncultured marine archaeon and unculture Pyrobaculum sp. were overabundant in FVPTC tumor tissue compared to normal samples (Figure 3C); while Halovivax ruber XH-70 and Methanosarcina sp. WH1 were both overabundant in normal samples when compared to CPTC tumor tissue (Figure 3C). Overall, a large number of microbes were similarly significantly overabundant in all three PTC types, with FVPTC exhibiting the most significant dysregulated microbes, followed by TCPTC and CPTC. While certain commonalities in microbial abundance appear to be present across these PTC subtypes, these findings suggest a unique microbial landscape within the tumor microenvironment, dysregulated by CPTC, FVPTC, and TCPTC variants.
Given the known importance of gender in PTC incidence and outcomes, we additionally identified similarly significantly dysregulated microbes in male and female PTC tumor samples compared to adjacent gender-controlled tissue normal (Figure 3B, Supplementary File S2). Significant differences were observed in gender comparisons, with a total of 88 significantly dysregulated fungal microbes in females only, compared to only 11 significantly dysregulated fungal and archaeal microbes in males only. A total of 10 fungal species were overabundant in male and female PTC tumor tissues compared to solid tissue normal, including *Coemansia reversa* (Figure 3D), Pneumocystis carinii, and Inosperma maculatum. A total of 80 fungal species were overabundant in female tumor tissue only, including Pseudosperma obsoletum, Yamdazyma, triangularis, and Candida albicans, while 8 fungal species were underabundant in female tumor tissue when compared to female adjacent normal tissue samples, which included *Thremochaetoides thermophila* DSM 1495 (Figure 3D), *Aspergilus fumigatus* Af293, and *Saccharomyces cerevisiae* YJM1418 (Figure 3B). We identified four fungal species that were overabundant in male PTC tumor tissue, while five fungal species were underabundant in male PTC tumor tissue, compared to male adjacent normal samples. Interestingly, the only significantly dysregulated archaeal species identified were underabundant in male PTC tumor tissue, which included Halovivax ruber XH-70 (Figure 3D) and *Natrialba magadii* ATCC 43099 (Figure 3B). Thus, our findings indicate that significant dysregulation of intratumor fungal and archaeal species is present according to gender. Interestingly, these microbes were disproportionately dysregulated in female tumor tissue, indicating that these species may play a potential role in increasing the risk for PTC occurrence, which is substantially higher for females.
## 2.4. Correlation of Significantly Dysregulated Fungal and Archaeal Species to Clinical Variables
Next, we correlated the abundance of significantly dysregulated microbes to clinical variables pertinent to PTC prognosis and outcomes. Specifically, we analyzed the following clinical variables: follow-up vital status, perineural invasion, pathologic stage, and cancer T, N, and M staging. We performed clinical variable analysis using the Kruskal–Wallis test (p-value < 0.05) on all patients with PTC ($$n = 453$$).
In our analysis, we found 26 total microbes to be significantly correlated with patient clinical variables (Figure 4). No archaeal species were significantly associated with clinical variables in our analysis. A full list of microbial species significantly correlated with pertinent clinical variables is included in Supplementary File S3. In patients with follow-up vital status, Brevicellium exile was overabundant in patients who were deceased compared to those who were still alive. We found that *Piptocephalis corymbifera* and Zoophthora occcidentalis, however, were overabundant in PTC patients with neoplasms compared to those with no neoplasms. Interestingly, all microbe correlations with Patholgic staging (including M and N staging) were associated with a higher pathologic stage (Figure 4, Supplementary File S3). We found that *Chaetomium globosum* CBS 148.51 abundance was correlated with increasing pathologic stage. In total, 18 fungal species were correlated with a higher pathologic M stage, including Candida Albicans, Eremascus albus, and *Thanatephorus cucmeris* (Figure 4, Supplementary File S3). Finally, Wickerhamiella pararugosa, uncultured Cryptomycota, and *Spiromyces aspiralis* were associated with a higher pathologic N stage. The correlation of studied species with a pathologic T stage yielded no significant results. Due to the lack of significantly dysregulated archaeal microbes in differential abundance analysis and correlation with PTC clinical variables, we did not further analyze these species in downstream analyses.
## 2.5. Microbe Abundance Correlation to PTC-Specific Oncogenic Pathways
Given the unique microbial differences we characterized across PTC cohorts and gender comparisons, we correlated clinically relevant fungal species to known oncogenic drivers of PTC. In particular, we focused on the BRAF, RET, P53, RAS, MAPK, and AKT pathways, all of which are implicated in PTC initiation and progression [41,42,43,44,45,46,47,48]. We used Gene Set Enrichment Analysis (GSEA) to correlate fungal microbial abundance to the following gene set signatures available on the Molecular Signature Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp), accessed on 7 November 2022: [1] PID_PI3KCI_AKT_PATHWAY, [2] BIOCARTA_RAS_PATHWAY, [3] REACTOME_SIGNALING_BY_MODERATE_KINASE_ACTIVITY_BRAF_MUTANTS, [4] KEGG_P53_SIGNALING_PATHWAY, [5] REACTOME_RET_SIGNALING, and [6] REACTOME_ONCOGENIC_MAPK_SIGNALING. In order to characterize the association of the intratumor mycobiome with these oncogenic PTC pathways, we correlated clinically relevant fungal species with these pathways according to the cohorts in which they were significantly dysregulated.
First, we correlated fungal microbial abundance to oncogenic PTC pathways in CPTC patients (Figure 5A). We found that Metschnikowia santaceciliae, Pacynthium nigrum, Thanatephorus cucumeris, and *Spriromyces aspiralis* were correlated with negative enrichment of PI3K/AKT pathway, while *Metschnikowia santaceciliae* and *Placynthium nigrum* were associated with negative enrichment of the RAS signaling pathway. Conversely, we observed that Uncultured Galactomyces was correlated with positive enrichment of BRAF kinase activity, indicating a potential oncogenic role of this species in CPTC. The majority of significantly enriched pathways were negatively enriched in CPTC patients, suggesting these microbes may play a tumor-suppressive role in CPTC.
Next, we associated fungal microbes with known oncogenic PTC pathways in TCPTC patients (Figure 5B). We found three fungal species, Brevicellicium exile, Eremascus albus, and Zoophthora occidentalis, associated with positive enrichment of p53 signaling, and two fungal species, *Metschniokowia santaceciliae* and uncultured Glomus, correlated with positive enrichment of BRAF kinase activity. Brevicellicium exile, Metschniokowia santaceciliae, and uncultured Glomus were also correlated with positive enrichment of RET, MAPK, and RAS signaling, indicating these microbes may play a significant role in TPTC initiation and progression through multiple oncogenic pathways.
In patients with FVPTC, we found species categorized as uncultured Glomus were associated with positive enrichment of BRAF kinase activity and MAPK signaling, and *Rozella allomycis* was correlated with positive enrichment of only the BRAF kinase activity signature (Figure 5C). These findings suggest that uncultured Glomus may be pertinent to FVPTC oncogenesis, while significant enrichment via other microbes was not observed. Further studies are needed, however, to culture Glomus species and elucidate which specific microbes may be associated with the enrichment of these pathways.
Finally, we identified enriched oncogenic pathways in male and female patients according to fungal species abundance (Figure 5D). We did not observe any significant pathway enrichment in male patients. In female patients, however, *Coemansia reversa* and *Spiromyces aspiralis* were associated with positive enrichment of BRAF kinase activity, and *Coemansia reversa* exhibited a positive correlation with RET signaling. Moreover, *Spiromyces aspiralis* was also associated with positive enrichment of RET signaling.
In all, GSEA analysis showed unique correlations with oncogenic pathways implicated in PTC, indicating that these fungal microbes may play a unique role in occurrence and oncogenesis through different mechanisms in each PTC subtype and gender.
## 2.6. Differential Abundance according to BRAF 600VE Mutation Status
Given the unique oncogenic components associated with these microbes, we also conducted differential abundance analysis according to the incidence of the BRAF V600E mutation (Figure 6). The BRAF V600E mutation is the most common genetic alteration in PTC, initiating tumorigenic events through the mitogen-activated protein kinase (MAPK) signaling transduction pathway [49,50].
In our analysis, we found 18 fungal species overabundant in tumor tissue with no BRAF V600E present, including *Phaeoacremonium minimum* UCRPA7 and *Saccharomyces cerevisiae* YJM1615 (Figure 6A,B). Only six fungal species were overabundant in tumor tissue with the BRAFV600E mutation, including Volvariella volvacea, and Metarhizium anisopliae. Thus, these species appear to be overabundant, primarily in BRAF V600E-negative tissues. Further studies are needed to validate the presence of these microbes and the mechanisms by which they may confer oncogenic activity in vitro.
## 3. Discussion
In this study, we characterized the intratumor mycobiome and archaeometry in PTC according to CPTC, TCPTC, and FVPTC subtypes and gender comparisons. Previously, we investigated the intratumor bacterial microbiome in PTC according to these cohorts [51]; our findings suggested that a unique microbial landscape exists in PTC according to these factors and is furthermore associated with distinct immune-associated, oncogenic, mutational, and methylation elements.
To our knowledge, we are the first to associate the abundance of fungal species within the tumor microenvironment with important prognostic variables and oncogenic signatures. Recently, a pan-cancer study of the mycobiome in 35 cancers demonstrated the relevance of these fungal microbes for diagnostic purposes, developing a highly-accurate machine learning model from these microbial elements in thyroid and many other cancers [52]. While this study was one of the first to associate the fungal mycobiome with PTC using data from TCGA [52], specific characterization of the intratumor PTC mycobiome according to key diagnostic and prognostic factors, such as subtype and gender, was not pursued due to the scale of the study. Thus, our study provides important insights into how the dysregulation of the mycobiome may influence PTC oncogenesis through pathways distinct to patient subtype and gender. Further in vitro experimentation is needed, however, to validate these results and elucidate the specific metabolic mechanisms which may lead to these oncogenic effects.
Additionally, our study explores a novel aspect of the human microbiome in cancer. While most investigations of the microbiome in cancer focus on bacteria and fungi, archaeal species are rarely studied in human disease. Currently, most studies of archaeometry analyze species abundant in the gut, which consist primarily of methanogens [53,54]. A recent study, however, found archaeal species abundant in organs with high exposure to the environment, including the lung, nose and skin [55]. So far, studies of the archaeome in cancer have been limited to colorectal cancer [56,57]. Thus, our investigation of the archaeometry in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) was the first to associate archaeal microbes with pertinent metabolic and oncogenic pathways in any non-colorectal cancer [58]. In this paper, we found that intratumor archaeal species were distinctly dysregulated between LUAD and LUSC samples and exhibited associations with unique cellular pathway regulation and clinical progression variables. Thus, we aimed to investigate a similar potential correlation between the intratumor PTC archaeometry and known oncogenic pathways in PTC, in addition to the association with prognostic variables.
Overall, fungal species were disproportionately abundant in our samples compared to archaeal species. Interestingly, our findings suggest that higher dysregulation of fungal microbes exists in PTC tissue compared to the bacterial dysregulation we previously identified [51]. A large proportion of fungal microbes identified in our study were similarly overabundant in CPTC, FVPTC, and TCPTC, indicating that these microbes may be more dysregulated between cancer and normal samples than between subtypes of PTC. Additionally, the vast majority of these dysregulated microbes were overabundant in PTC tumor tissue compared to adjacent normals, indicating that intratumor PTC mycobiome may largely play a cancer-promoting role. Despite significant commonalities in fungal microbe composition across PTC subtypes, however, CPTC, FVPTC, and TCPTC still exhibited noticeable differences in dysregulated species. TCPTC, for example, exhibited the most amount of dysregulation of the three subtypes, followed by FVPTC and CPTC: with particularly disproportionate upregulation of dysregulated microbes. Unlike the FVPTC and TCPTC variants, however, microbes uniquely dysregulated in CPTC tumor tissue were primarily underabundant compared to normal samples. Thus, uniquely dysregulated microbes of the intratumor microbiome in CPTC may serve a tumor-suppressive role, while fungal species unique to TCPTC and FVPTC may be implicated more significantly in oncogenic functionalities. Our analysis of fungal microbe abundance with oncogenic pathway enrichment suggested similar results, with negative enrichment of these pathways associated with fungal species only observed in CPTC patients. Future in vitro studies are needed to confirm these microbial differences in PTC subtypes and further characterize their role in oncogenic events.
While our previous study of the intratumor bacterial PTC microbiome found almost comparable differences in abundance between male and female tissue samples [51], we found significant differences in the fungal mycobiome according to gender. Although a higher proportion of dysregulate fungal microbes was common to all study types of PTC, most dysregulated fungal microbes in gender comparisons were distinct to males and females. Female tumor samples exhibited 80 uniquely overabundant microbes compared to normal samples, including Pseudosperma obsoletum, Yamadazyma triangularis, and Candida albicans. We found that only four species were uniquely overabundant in male tumor samples: Rhizomucor miehei, Didymella macropodii, Geranomyces variabilis, *Vittaforma cornaea* ATCC 50505. As such, our findings suggest that differences in the intratumor PTC mycobiome are likely more noticeable in gender comparisons than in subtypes.
Few archaeal species were found to be dysregulated in our analysis. However, these species were unique to CPTC, FVPTC, and TCPTC tissue. Additionally, archaea were only found to be dysregulated in males, including Halovivax ruber XH-70 and *Natrialba magadii* ATCC 43099. Thus, few differences in archaeal abundance were observed according to these cohorts. However, further studies and culturing of archaeal species may reveal even more species abundant in thyroid tissue. The lack of archaeal species in the thyroid tissue may be due to its relatively lower exposure to the environment compared to other organs, such as the mouth, lungs, and nose.
Additionally, we correlated these dysregulated fungal microbes to clinical progression and vital status variables in all PTC patients. Brevicellium exile was overabundant in patients who were deceased at the last follow-up. The majority of our clinical variable analysis indicated that many of these microbes are pertinent to the pathologic stage, particularly the pathologic M stage. The abundance of *Chaetomium globosum* CBS 148.51, for example, was correlated with a higher overall pathologic stage. The abundance of 18 microbial species, including Candida albicans and Eremascus albus, were correlated with higher pathologic M stage, suggesting that these fungal microbes may be additionally pertinent in PTC tumor metastasis.
In order to further characterize the role of these microbes in PTC oncogenesis, we associated dysregulated fungal microbes with known pathways implicated in PTC development, including the BRAF, P53, RET/PTC, MAPK, KAT, and RAS signature pathways. Consistent with our findings of underabundance in CPTC tumor tissue compared to normals, we found that the majority of these pathways were negatively enriched in CPTC, primarily PI3K/AKT, which induces tumor growth and energy storage of cancer cells [59,60]. Unlike in TCPTC and FVPTC, microbes dysregulated in CPTC appeared to be associated with the inhibition of cancer-promoting pathways. Enrichment of the BRAF and P53 signaling pathways, however, was associated with multiple fungal species in TCPTC. Fewer pathways were enriched by microbes in FVPTC; however, BRAF and MAPK signaling were positively enriched by uncultured Glomus. Interestingly, no pathways were significantly enriched by dysregulated microbes in male patients. Similar to TCPTC and FVPTC, the BRAF pathway was enriched by multiple fungal microbes in females. Interestingly, RET signaling was not associated with enrichment via microbe abundance nearly as much as other studied pathways, including BRAF, P53, MAPK, and AKT. The RET/PTC arrangement is a hallmark of PTC development and is the most common genetic alteration in PTC [61]. Thus, future studies should validate if the microbiome is implicated in PTC oncogenesis through pathways other than RET signaling. Additionally, further in vitro experimentation is needed to understand the exact metabolic interactions of intratumor microbes with these signaling pathways.
We also found several microbes were dysregulated in tumor samples with the BRAF V600E mutation. The BRAF V600E mutation is the most commonly mutated oncogene in PTC, which initiates tumorigenesis via activation of the MAPK signaling pathway [50]. Interestingly, we found that the majority of dysregulated microbes, according to BRAF V600E mutation status, were overabundant in BRAF V600E-negative tissue. Thus, it is plausible that this mutation may also dysregulate fungal microbes within the tumor microenvironment; however, further studies are needed to elucidate this mechanistic role in PTC.
In all, our findings suggest that the intratumor mycobiome and archaeometry in PTC differ greatly according to subtype and gender. To the best of our knowledge, we are the first to associate these microbial elements in PTC with pertinent prognostic variables. Additionally, the abundance of fungal species exhibited correlations to higher pathologic staging, particularly metastasis, and unique correlations to known oncogenic PTC pathways in CPTC, FVPTC, TCPTC, and females. Due to the correlative nature of our study, in vitro analysis must be conducted to confirm the role of these microbes in PTC incidence and progression. Although CPTC, FVPTC, and TCPTC were the primary tumors available from TCGA, future studies should also characterize how these microbes may uniquely contribute to oncogenesis in other forms of thyroid cancer [62,63,64].
## 4.1. Data Acquisition
Raw whole-transcriptome RNA-sequencing data were downloaded from TCGA-THCA project (https://portal.gdc.cancer.gov/projects/TCGA-THCA), accessed on 15 January 2022, for 453 thyroid carcinoma primary tumor samples and 54 adjacent solid tissue normals. Clinical data for the patients investigated in this study were obtained from the Broad Genome Data Analysis Center (GDAC) Firehose database (https://gdac.broadinstitute.org/), accessed on 3 January 2023. All data analyzed in this study were accessed and analyzed during the period January 2022–December 2022.
## 4.2. Extraction and Normalization of Fungal and Archaeal Read Counts
Fungal and Archaeal read counts were extracted from raw RNA-sequencing data using the PathoScope 2.0 alignment tool and the NCBI nucleotide database. Microbial reads were successfully extracted from all 507 RNA-sequencing files. In order to normalize data and reduce variance across samples, we conducted Aitchison’s log transformation on all extracted read counts.
## 4.3. Evaluation of Contamination
In order to account for potential contaminants introduced through sequencing or sampling methods conducted on our samples, we conducted contamination correction by sequencing date, plate, and microbial abundance. First, we conducted contamination correction by sequencing date by creating scatter plots of the sequencing date compared to microbial abundance for each microbe. Microbes with a scatter plot exhibiting one functional abundance cluster on a certain date were considered potential contaminants. Second, we conducted contamination correction by sequencing plate by plotting boxplots of microbial abundance according to each respective sequencing plate. Microbes that were disproportionately abundant in two or fewer sequencing plates were identified as potential contaminants. Finally, contamination correction by total microbe abundance was conducted by creating scatter plots of total microbial abundance (global abundance of microbes in each patient) compared to abundance of each individual species. We identified potential contaminants in plots with a slope of zero (margin of error ± 0.1). Visual identification of contaminants was verified by at least two authors for each contamination correction method. A complete list of identified contaminants, including those not visualized in Figure 2, is included in Supplementary File S1.
## 4.4. Differential Abundance between PTC, Gender, and Mutation Cohorts
Differential abundance analysis was conducted on the following patient cohorts: [1] primary tumor samples and adjacent normal samples, [2] CPTC samples and adjacent normal samples, [3] FVPTC samples and adjacent normal samples, [4] TCPTC samples and adjacent normal samples, [5] male cancer samples and male adjacent normal samples, and [6] female cancer samples and female adjacent normal samples. Differential abundance analysis was conducted for each of these cohorts for fungal and archaeal data, using the Kruskal–Wallis test in the edge-R library. Statistically significant results were defined with a p-value < 0.05. We then identified similar differentially-abundant microbes across PTC subtypes and gender comparisons according to the direction of overabundance. Significantly dysregulated microbes were used in further analyses. A complete list of significantly dysregulated microbes, including those not visualized in Figure 3, is included in Supplementary File S2.
Similarly, we also conducted differential abundance analysis on BRAF V600E positive cancer samples and BRAF V600E negative cancer samples. Clinical information for PTC subtype, gender, and mutation status was extracted from the GDAC Firehose clinical data file.
## 4.5. Association of Microbial Abundance to Clinical Variable
We assessed significantly dysregulated microbes to clinical variables using the Kruskal–Wallis test (p-value < 0.05). In order to correct for multiple hypothesis testing, we adjusted our p-values using the Bonferroni method. We examined six main clinical variables pertinent to PTC prognosis and clinical course: follow-up vital status, perineural invasion, pathologic stage, and cancer T, N, and M staging. We performed clinical variable analysis on all patients with PTC ($$n = 453$$).
## 4.6. Correlation of Microbial Abundance to Oncogenic PTC Signature Pathways
We conducted Gene Set Enrichment Analysis (GSEA) to correlate microbial abundance to known pathway signatures implicated in PTC oncogenesis. Three input files were prepared for GSEA analysis: the expression file, the phenotype file, and the gene set file. The expression file consisted of gene expression data, and the phenotype file contained microbial abundance features for each sample. *The* geneset file was created with the following signature pathways defined by the Broad Institute: [1] PID_PI3KCI_AKT_PATHWAY, [2] BIOCARTA_RAS_PATHWAY, [3] REACTOME_SIGNALING_BY_MODERATE_KINASE_ACTIVITY_BRAF_MUTANTS, [4] KEGG_P53_SIGNALING_PATHWAY, [5] REACTOME_RET_SIGNALING, [6] REACTOME_ONCOGENIC_MAPK_SIGNALING. The specific classification file is included in Supplementary File S4. Only statistically significantly enriched signatures were further analyzed (p-value < 0.05) and false discovery rate (FDR) < 0.25).
## 5. Conclusions
In conclusion, our study provides novel insights into the potential importance of fungal and archaeal species to oncogenesis within the PTC microenvironment. Additionally, we characterized important similarities and differences in the intratumor PTC mycobiome and archaeometry according to PTC subtype (classical, follicular variant, and tall cell) and gender. Overall, the majority of dysregulated species in PTC samples were overabundant in tissue. A total of 63 fungal species were commonly overabundant in CPTC, FVPTC, and TCPTC, including Botrytis cinerea, while 33 fungal species were uniquely overabundant in TCPTC, and 28 in FVPTC, whereas 16 fungal species were uniquely underabundant in CPTC. This collection of microbes includes Phialophora verrucosa, Boletinellus merulioides, and Bipolaris sorokiniana, respectively. We found that the fungal and archaeal landscapes, however, were more distinct across gender comparisons. Amongst 80 total microbes, *Pseudosperma obsoletum* and Candida albicans were uniquely overabundant in female PTC tumor tissue. Archaeal species were uniquely dysregulated according to PTC subtypes and gender. Halovivax ruber XH-70 and *Natrialba magadii* ATCC 43099 were uniquely underabundant in male PTC tumor tissue compared to male-controlled adjacent normal tissue. In clinical variable analyses, several fungal microbes were associated with higher pathologic staging, including Candida albicans and Eremascus albus. CPTC was characterized primarily by negative enrichment of oncogenic PTC pathways, including the PI3K/AKT signaling pathway. Conversely, the P53 and BRAF mutant pathways were positively enriched by several microbes in TCPTC, FVPTC, and females, including uncultured Glomus, Eremascus albus, and Metschnikowia santaceciliae. Finally, we found that *Volvariella volvacea* was overabundant in BRAF V600E-positive tumors, while *Phaeoacremonium minimum* UCRPA7 was overabundant in BRAF V600E-negative tumors. Future in vitro experiments are needed to validate these microbial differences and associations to clinical variables and pertinent cancer pathways.
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|
---
title: Analysis of the Occurrence of Predicative Factors of Chronic Fatigue in Female
Patients with Cancer of the Reproductive Organs with Respect to Stage of Treatment
authors:
- Magdalena Kłysiak
- Sylwia Wieder-Huszla
- Dorota Branecka-Woźniak
- Katarzyna Karakiewicz-Krawczyk
- Izabela Napieracz-Trzosek
- Joanna Owsianowska
- Anna Jurczak
- Aneta Cymbaluk-Płoska
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967751
doi: 10.3390/ijerph20043732
license: CC BY 4.0
---
# Analysis of the Occurrence of Predicative Factors of Chronic Fatigue in Female Patients with Cancer of the Reproductive Organs with Respect to Stage of Treatment
## Abstract
The aim of this study was to search for mechanisms contributing to cancer-related fatigue in patients with gynecologic cancer. The study involved 51 women with advanced endometrial cancer and ovarian cancer undergoing chemotherapy. Data were gathered at four points in time. After giving consent, each of the women had their blood drawn several times (before surgery and the first, third, and sixth cycle of chemotherapy) to determine serum levels of pro- and anti-inflammatory cytokines. Empirical data were collected using the MFSI-SF and an original questionnaire. Cancer-related fatigue (CRF) was present at every stage of treatment, but the highest mean scores were noted before cytoreductive surgery (8.745 ± 4.599), and before the sixth cycle of chemotherapy (9.667 ± 4.493). Statistically significant relationships were found between IL-1α, IL-1β, IL-2, Il-6, and IL-10 and fatigue at different stages of treatment. Older age and an above-normal BMI were the major prerequisite factors for the occurrence of fatigue in female oncological patients. The analysis of changes in cytokine levels and the severity of fatigue may be used to improve our understanding of cancer-related fatigue, and to take action to alleviate the obtrusive symptoms experienced by female patients with cancer of the reproductive organs.
## 1. Introduction
Many symptoms occur during the course of cancer, starting with pain, through nausea/vomiting and loss of appetite, to weakness. One of the most frequent symptoms experienced by oncological patients is weakness—one of the symptoms of cancer-related fatigue (CRF) [1,2]. The consequences of chronic fatigue are serious, because it affects not only the physical quality of life, but also the psychological and the social. The syndrome causes over $80\%$ of cancer patients to reduce their daily activity, because even the simplest tasks become too difficult for them to perform [2]. The fatigue also impairs concentration, making it even more difficult to function. Patients often treat fatigue as a natural result of cancer and are not aware of the presence of other symptoms of chronic fatigue [3]. According to the literature, between $70\%$ and $100\%$ of patients who have undergone chemotherapy, immunotherapy, radiotherapy, or surgical treatment will have suffered from CRF, and the occurrence of the syndrome is not limited to those in poor general condition. It is often found in young patients, especially women ($75\%$). Symptoms of CRF are also found in patients in good and very good general condition [3,4,5]. First symptoms of CRF are usually observable with the commencement of cancer treatment, although they may begin to appear during the diagnosis period, since even $50\%$ of patients feel fatigued during diagnostic examinations aimed at determining the final diagnosis [6]. CRF symptoms usually become more severe during chemotherapy, and the occurrence of the symptoms is determined by more intense cancer treatment, previous intensity of the symptoms, and occurrence of new symptoms (e.g., pain, nausea, vomiting). Patients who undergo chemotherapy experience more intense symptoms once they receive an injection with chemotherapeutics. The symptoms are the most intense 48 to 72 h later, and their intensity depletes over the next 3 weeks. The intensity depends on the kind of chemotherapeutics that are administered [7]. Finishing the cancer treatment does not always lead to the symptoms’ quick disappearance—almost $40\%$ of patients feel fatigued up to 3 years after they have finished chemotherapy [3]. Most patients consider chronic fatigue to be the most unpleasant symptom they experience as a result of cancer and/or oncological treatment. All symptoms resulting from CRF have negative effects on the quality of life and make physical, mental, and social functioning more difficult, frequently leading the patient to give up on treatment due to them feeling helpless, lonely, experiencing cognitive difficulties, and loosening of relationships [8]. Some patients think that fatigue signifies that the treatment is not working, or that the disease is advancing. The etiology of CRF is multi-factorial and most likely has to do with imbalances in three interconnected systems: physiological, biochemical, and psychological. Researchers have put forward numerous hypotheses regarding chronic fatigue etiology, emphasizing genetic, immunological, psychological, hormonal, and even viral causes [9,10]. The syndrome is, then, a disorder with a complex, not yet fully understood etiology, but it is apparent that advancing cancer as well as cancer treatment are factors contributing to its emergence. The causes are frequently being attributed to changes in the immune system which occur during cancer. Many studies show that patients with CRF have increased production of pro-inflammatory cytokines and an overly activated immunological response, leading to a prolonged lymphocyte activation [11,12,13,14]. IL1α, IL1β, IL2, IL5, IL6, IL8, IL10, IL13, INFγ, TNFα, and TGFβ are some of the cytokines considered to be markers of chronic fatigue syndrome [15]. Research has also confirmed disturbed functioning of cells of the immune system [8]. Therefore, observing chronic fatigue syndrome is still a challenge for researchers and clinicians, because the symptoms vary between individuals. Additionally, an incorrect interpretation of the causes induces stress, and may lead to stopping pharmacotherapy or changing the treatment plan [16]. The aim of our study was to search for mechanisms which influence the development of chronic fatigue syndrome in female patients with cancer of the reproductive organs.
## 2.1. Study Sample Selection
The study sample consisted of 51 women undergoing treatment at the Department of Gynecological Surgery and Gynecological Oncology of Adults and Adolescents of the Pomeranian Medical University in Szczecin. A prerequisite for participation was giving informed consent. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Bioethics Committee (KB-$\frac{0012}{81}$/18). The study sample included female patients with ovarian cancer and endometrial cancer who were undergoing first-line chemotherapy, or systemic treatment due to a recurrence of cancer. The patients with primary ovarian cancer underwent surgical treatment followed by 6 cycles of chemotherapy using platinum-based regimens and paclitaxel, or, if the surgical treatment was incomplete, the patients were given 18 doses of bevacizumab. In the case of a recurrence, the choice of chemotherapy depended on the platinum-sensitivity of the tumor. The patients with endometrial cancer underwent surgical treatment followed by chemotherapy and radiotherapy. The chemotherapy consisted of platinum-based regimens and paclitaxel administered in 6 cycles. In the case of recurrences, doxorubicin regimens were administered.
## 2.2. Study Design
The research procedure was divided into two parts: structured interview and biochemical analysis of the researched parameters in the serum.
## 2.2.1. Structured Interview
The diagnostic survey method with the questionnaire technique was applied, and the standardized research tool were used to collect the empirical data: Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF). An original survey questionnaire was also used, containing the basic sociodemographic data, that is age, place of residence, professional activity, education, marital status, menstruation, history of cancer in the family, medication administered, and physical activity.
Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF) by Stein et al. [ 16,17]—this questionnaire is used to measure fatigue. It consists of 30 self-report statements relating to the last 7 days. The accuracy of each statement is evaluated on a 5-point Likert scale, from 0 to 4 (from “not at all” to “extremely”). The final score allows us to evaluate fatigue in five dimensions: General, Physical, Emotional, Mental, and Vigor. The higher the score, the more intense the fatigue, except for the Vigor scale, where the higher the score the less intense the fatigue (meaning more Vigor). The total is calculated by subtracting the points for Vigor from the subtotal of all the other scales. It is contained between -24 and 96 points. MFSI-SF does not have a set cut-off point, a high total means more intense fatigue.
## 2.2.2. Determination of Biochemical Parameters
In accordance with the study protocol, each of the studied women had to give their consent to participate in the study. After that they had their blood drawn several times (before surgery, and before the first, third, and sixth cycle of chemotherapy). The blood was drawn on an empty stomach (at least 8 hours since the last meal), and 5.5 mL maximum of venous blood was drawn using the S-Monovette system. After the biological material was obtained, the blood was centrifugated and the serum was frozen at −80 °C until biochemical analysis could be performed.
The determination of biochemical parameters (see Supplementary Material) was performed at a certified laboratory of the Pomeranian Medical University in Szczecin using commercial, standardized methods.
The obtained serum was used to determine the concentrations of cytokines (IL-1α, IL-1β, IL-2, IL-6, TNFα, INF-γ, IL-4, IL-10). The concentrations of cytokines and analysis were performed using commercially available reagents (High Sensitivity Human ELISA kit) and an ELx800 absorbance microplate reader manufactured by BIO-TEK Instruments (Winooski, VT, USA) using wavelengths recommended by the manufacturer.
## 2.3. Statistical Analysis
Statistical analysis was performed in MedCalc software (version 20.210; Ostend, Belgium). The probability of $p \leq 0.05$ was considered statistically significant.
The normality of continuous variables was verified by means of Shapiro–Wilk test. Consequently non parametric Kruskal–Wallis test was used to see the differences between independent groups. Post hoc analyses were conducted by means of the Dunn method. Correlation analyses were conducted by means of Spearman’s method. For qualitative variables comparisons, the Chi square test was used. Descriptive statistics were presented as medians and interquartile ranges.
## Characteristics of the Subject Group
The subjects included in the study were 51 women diagnosed with uterine cancer ($$n = 25$$, $49.0\%$) or ovarian cancer ($$n = 26$$, $51.0\%$). The average age of the studied women equaled 61 (12 ± 8.77) years. Most of the women had secondary ($47.1\%$) or higher ($17.6\%$) education, and were married ($31.4\%$). The highest number of the studied women lived in cities—$88.2\%$, and $45.1\%$ received a sickness allowance. Every third woman ($31.4\%$) was employed. None of these variables’ frequency was significantly different in terms of cancer type as presented in Table 1.
The studied women struggled with general fatigue at every stage of treatment, a significantly lower score for mental and overall measure (i.e., total score) was compared at the time of surgery to other time points. Data are presented in Table 2 and Figure 1.
At each time point, age did not have significant impact on any dimension measured by mean of MFSI-SF survey (Table 3).
A statistically significant dependence was found between high concentrations of all of the studied interleukins and the occurrence of all of fatigue’s dimensions in female patients with cancer of the reproductive organs at all stages of treatment. Out of the bioactive agents of the immune system, these were the concentrations of IL-6, IL-2, IL-1α, IL-1β, IL-10, TNF, IFN-γ, and IL-4 that conditioned fatigue. In the case of IL-6, it has been observed that it has a significant effect on fatigue at three of the measured points in time, both in terms of general and physical fatigue, and vigor. It also had an effect on mental fatigue at the last stage of treatment. Out of the analyzed cytokines, a statistically significant dependence was found between IL-1α, IL-1β, IL-2, Il-6, IL-10 and the occurrence of fatigue in patients at various stages of treatment. The results are presented in Table 4.
For the total score measured by means of we found significant but moderate positive correlation with Il 1α ($r = 0.407$; $$p \leq 0.021$$), Il 1β ($r = 0.298$, $$p \leq 0.043$$), Il2 ($r = 0.368$; $$p \leq 0.049$$), IL 6 ($r = 0.461$; $$p \leq 0.034$$) and IL10 ($r = 0.515$, $$p \leq 0.002$$)—Table 5.
## 4. Discussion
Advancements in cancer treatment aim at decreasing patients’ suffering resulting from the underlying disease, and at reducing treatment-related side effects. Sadly, despite these efforts and continuous advancements in medicine, cancer patients still complain about having a poor quality of life due to treatment. One of the most frequently mentioned side effects is weakness and/or fatigue. CRF, which accompanies cancer, is defined as a prolonged, debilitating, and subjective feeling of fatigue which affects cancer patients during illness and treatment, therefore it is a result of the disease or applied treatment [18,19]. Apart from fatigue, patients complain about becoming tired quickly, loss of sleep or feeling overly sleepy, being in a bad mood, and having trouble concentrating. Problems such as these often lead to emotional distress and feeling helpless and lonely. Unlike fatigue in healthy people, these symptoms found in cancer patients do not go away after rest and can affect up to 80–$90\%$ of patients undergoing treatment, or in advanced stages of cancer [20,21,22].
According to Brown et al., cancer patients who experience more fatigue function physically worse compared to others [23]. De Jong’s team, based on a literature review, found that fatigue is one of the most common side effects of chemotherapy, since high and fluctuating indicators of fatigue are found both during treatment and after it has finished [24]. In our own study, the patients suffered from general fatigue at all stages of treatment, with slightly higher levels of fatigue before cytoreductive surgery and the sixth cycle of chemotherapy. When we compared the dimensions of fatigue at each measured point in time, we observed that the mean score was the highest for mental fatigue in patients before surgical treatment, and for physical fatigue in patients before the sixth cycle of chemotherapy. At the same time, patients entering the last stage of treatment had high mean scores for vigor. Our results may confirm that the fatigue experienced by patients at the initial stages of illness is due to the diagnosis and diagnostic examinations aimed at determining the final diagnosis [6]. The symptoms of chronic fatigue increase during chemotherapy, reaching a critical point before it finishes, but approaching the end of treatment gives the body new energy and a fighting spirit.
Studies by Maurer’s team showed that the level of education, BMI, level of physical activity, and chronic inflammatory diseases present prior to the diagnosis are strong predicators of long-term CRF. According to the researchers, lifestyle, coexisting conditions, and socioeconomic factors may be more informative in identifying patients at risk of long-term CRF than the presence of inflammation biomarkers [5]. Bower et al., on the other hand, have analyzed the effects of chronic illnesses on the level of fatigue. Their results confirmed that women showing symptoms of fatigue are more likely to suffer from diabetes, arterial hypertension, or heart conditions [25]. Our own studies confirm the influence of sociodemographic factors, i.e., age, education, professional activity, as well as of medical factors, i.e., BMI and co-existence of diabetes, on the feelings of fatigue in all its dimensions.
Many studies have shown that cancer treatment causes imbalances in the immune system resulting in long-term inflammation. Higher concentrations of pro-inflammatory cytokines are symptomatic of that [26,27]. Searches for biomarkers of cancers of the reproductive organs reaffirm the effects of interleukins in the development of these cancers. TNF-α, IL-1, and IL-6 participate in the development of endometriosis, and carcinogenesis of the endometrium [28,29]. The literature also confirms the participation of IL-6 as an inflammatory factor in the proliferation of cancerous cells in some cancers [30,31], including metastasis of uterine cancer [32,33]. A high concentration of IL-6 in the serum of endometrial cancer patients is linked both with the carcinogenesis of the endometrium [34,35,36,37] and with advancement of the cancer [34]. High concentrations of cytokines IL-4, IL-6, and IL-10 are also found in cases of ovarian cancer [38,39], and studies by Clendenen et al. provide proof that high concentrations of IL-2, IL-4, and IL-6 are closely tied to the risk of developing this type of cancer [40]. According to the researchers, topical inflammatory cytokines such as IL-1β and TNF-α are the main inductors of the expression and secretion of IL-6 [41,42]. High concentrations of IL-1β and TNF-α have also been found in the serum of patients with advanced ovarian cancer [43,44,45,46]. It has also been shown that the high concentration of TNFα found in these patients [45,47] correlates strongly with increased advancement of the cancer [45,47], a shortened survival period [48], and increased expression of IL-6 [49]. Inflammatory factors can modulate the response of cancerous cells to chemotherapy, and anti-cancer drugs can cause the expression of some of the cytokine genes, including those of TNFα, IL-1β, and IL-6 [50,51,52]. Numerous studies have shown lower concentrations of the analyzed cytokines in the serum of patients treated with chemotherapy [45,53,54].
According to Panju et al. and Inagaki et al., changes in the concentrations of cytokines, especially IL-6, IL-1β, and TNF-α, may lead to sickness behaviors, including symptoms of fatigue [55,56]. Collado-Hidalgo’s team conducted research on the dependence between markers of fatigue and inflammation, and their results showed increased production of interleukin IL-6 and TNF-α in breast cancer survivors with symptoms of fatigue [57]. Maurer et al. ’s longitudinal study on breast cancer patients confirmed the dependence between IL-6 and chronic fatigue. That being said, some believe that the diagnostic value of IL-6 as a fatigue marker may be limited, due to its double effects, both pro- and anti-inflammatory [30]. This is why some researchers choose to focus on unambiguous inflammation biomarkers, such as IL-1β and TNF-α, even though Maurer’s team’s results have not shown that they have any noteworthy effects on CRF [25]. Ahlberg et al. observed an increase in fatigue in uterine cancer patients undergoing radiotherapy; however, they did not observe any noteworthy changes in the concentrations of IL-1, IL-6, or TNF-α [58]. Kwak et al. [ 59] and Orre’s team [60,61] also found no dependence between the level of fatigue and the pro-inflammatory cytokine IL-6. Our own studies confirm the influence of cytokines (i.e., concentrations of IL-1A, IL-1B, IL-2, IL-6, IL-10, TNF, and IL-4) on the emergence of fatigue in all its dimensions in patients with cancers of the reproductive organs at various stages of treatment.
In Goff’s team’s research, a higher concentration of IL-6 was closely tied to fatigue before surgery. Authors describe the existence of fatigue in ovarian cancer as “a pre-diagnostic symptom”, because it is one of the most frequently occurring symptoms patients complain about before they are diagnosed with this type of cancer [62,63]. In Inagaki’s team’s research, the concentration of IL-6 correlated strongly with physical fatigue in patients with terminal cancer [55]. In our own studies, IL-6 had a significant effect on the symptoms of fatigue both before surgery, as well as before the first and sixth cycle of chemotherapy, not only in the physical dimension, but also in the general dimension and vigor. The relationship between fatigue and the concentration of IL-6 before surgery was also observed by Clevenger’s team [64]. Inflammatory markers may be direct causes of fatigue, because they affect pathways of the central nervous system, causing vegetative behaviors [57,65,66,67,68,69,70]. Redeker observed that higher concentrations of IL-6 before surgery correlated significantly with sleep disturbances and tiredness, and the lowering of the cytokine’s concentration between the surgery and a year from it had to do with a better quality of sleep and decrease in fatigue [71].
When conducting a systematic research review, Salignan’s team proved that increased symptoms of fatigue, especially in women in early stages of breast cancer, were caused by increased concentrations of IL-6 and TNF, and of IL-1β during chemotherapy, and of IL-6 during radiotherapy [72]. On the other hand, Panju et al. ’s studies on patients with acute myeloid leukemia showed strong correlations between fatigue and IL-10 between the tested time periods—the beginning and after 4–6 weeks [56]. In our own studies, IL-1β correlated with fatigue at all of the measured points in time, determining vigor and emotional fatigue before cytoreductive surgery, and physical fatigue before the sixth cycle of chemotherapy. TNF and IL-10, on the other hand, affected not only general fatigue and vigor before surgery, but also mental fatigue before the third cycle of chemotherapy, and determined general and mental fatigue and vigor before the end of treatment.
The causes of cancer-related chronic fatigue have not yet been determined, but researchers agree that the phenomenon is multifactorial. Studies of inflammation biomarkers are justified, because they facilitate a better understanding of the biological pathways related to CRF, and achieving a better therapeutic effect whilst preserving a high quality of life of patients.
Our study has some limitations. First of all, a limited number of participants were screened at each study phase. In addition, we did not intend to compare the results with controls, thus we did not recruit either healthy women (matched for age and sex) or patients with benign conditions such as, for instance, endometriosis. Additionally, comparing the observed results with ones collected in women undergoing other surgical procedures (e.g. laparoscopy; robotic surgery) could act as an added value to the present research. Further research on such comparisons is warranted.
## 5. Conclusions
We observed the dependence between the concentrations of selected cytokines and fatigue in the studied group of patients. The dominating factors predisposing the occurrence of fatigue in the patients were age, higher than normal BMI, and, to a smaller degree, education, professional activity, and diabetes. Analyzing the changes in cytokine concentrations and fatigue intensity (in all its dimensions) may allow us to better understand the mechanisms behind cancer-related fatigue. Evaluating how these components change during treatment may help identify the kind of interventions which will help alleviate the most debilitating symptoms in patients with cancer of the reproductive organs.
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|
---
title: Accelerated Shelf-Life and Stability Testing of Hydrolyzed Corn Starch Films
authors:
- Andra-Ionela Ghizdareanu
- Diana Pasarin
- Alexandra Banu
- Andreea Ionita (Afilipoaei)
- Cristina Emanuela Enascuta
- Alexandru Vlaicu
journal: Polymers
year: 2023
pmcid: PMC9967754
doi: 10.3390/polym15040889
license: CC BY 4.0
---
# Accelerated Shelf-Life and Stability Testing of Hydrolyzed Corn Starch Films
## Abstract
Nonbiodegradable food packaging films are made from plastics such as polyethylene and polypropylene, which can take hundreds of years to decompose and create environmental hazards. On the other hand, biodegradable food packaging films are made from renewable materials such as corn starch or cellulose, that degrade within a few weeks or months and prove to be more sustainable and environmentally friendly. In this work, we used corn starch hydrolyzed (CSH) with α-amylase to prepare a film with biodegradable properties. The film was tested for 60 days at different accelerated temperatures and relative humidity (RH), 13 ± 2 °C and 65 ± $5\%$ RH, 23 ± 2 °C and 45 ± $5\%$ RH, and 33 ± 2 °C and 30 ± $5\%$ RH, to test its durability and stability. Soil biodegradation of the CSH film was evaluated by visual appearance, microscopic observation, weight loss, scanning electron microscopy (SEM), and Fourier-transformed infrared spectroscopy (FTIR) every 6 days. The film was found to have strong hygroscopic properties and was able to last up to 10 months if it is maintained at 20 ± 5 °C and 45 ± $5\%$ RH. After the biodegradability test for at least 30 days, the film showed a significantly higher weight loss rate and microbial activity on the surface of the film, which indicates that the film is biodegradable. The present work recommends biodegradable CSH films as an excellent environmentally friendly choice for dried foods packaging, due to their good shelf life at room temperature, which is beneficial when shipping and storing products, but these films are not suitable for foods with high moisture content.
## 1. Introduction
The overuse of plastic packaging films and the accumulation of plastic waste due to the long degradation period have increased the interest in environmentally friendly packaging films from natural and sustainable sources [1]. Polymeric materials are used extensively throughout the world. Due to their properties and capabilities, these materials have a significant advantage over other, more traditional materials such as metals and wood; it is believed that $99\%$ of these polymeric materials are derived from fossil fuels. Since their main raw material poses a threat to the preservation of the environment, these plastics pose a number of problems. The degradability and durability of these materials are incompatible. For most applications, it is beneficial if the material retains certain properties over a long period of time, but it is also desirable that it can be easily disposed of and degraded after use [2]. Currently, films used for food packaging are not easily biodegradable in soil or by microorganisms. To promote plastic decomposition and reduce soil C and N2O losses under field conditions, N fertilization may be advisable in conjunction with optimal irrigation (to ensure adequate redox conditions) [3].
Therefore, plant-derived natural polymers are considered a promising alternative to replace synthetic packaging [4]. In recent years, research has been conducted in various fields to develop biodegradable materials for different applications. Recently, a dextran hybrid hydrogel based on peptide nanopods was produced. The combination of all these compounds makes it a promising new biomaterial platform for expanding its applications in tissue engineering and drug delivery [5]. The potential applications of biomaterials inspired by membraneless organelles (MO), with examples from biochemical reactors, synthetic biology, drug discovery, and drug delivery, were also discussed [6]. Due to their excellent biocompatibility and degradability, natural substances such as cationic polysaccharides and (poly)peptides have recently attracted great interest in the construction of novel polymeric vectors [7]. Biodegradable packaging films based on starch from different sources have gained attention in recent years due to their large occurrence in nature, non-toxicity, film-forming ability, and biodegradability [8]. The fact that starch is composed of two different carbohydrate polymers, namely amylose (20–$30\%$) and amylopectin (70–$80\%$), which are extremely high molecular weight polymers, has increased the interest in starch as the most important film-forming product in the packaging industry [9]. It has been demonstrated that cassava bagasse can be used effectively as a non-edible starch-based material for film production. In order to determine if the produced films are suitable for commercial biodegradable food packaging, additional research is needed to look into the mechanical and functional properties, food security, and biodegradability of the films [10].
Since the starch sources have different amylose/amylopectin ratios, the film-forming properties are also different [11]. Higher amylose content is preferable to obtain an opaque and thicker film, whereas thinner and transparent films are obtained with lower amylose content. While the amylopectin content provides the optimum consistency of the starch film solution, amylose determines the optical properties of the film [12]. However, the use of starch to develop packaging films is associated with several drawbacks, such as poor thermal and moisture stability [13]. To improve the mechanical properties of starch-based films, Sommerfield et al. [ 14] reduced the average molecular weight and amylopectin content of corn and potato starch by partial hydrolysis using acid catalysis and obtained readily biodegradable films. Zhang H et al. [ 15] increased pea starch films’ tensile strength and relative crystallinity by acid hydrolysis of pea starch with hydrochloric acid. In the study by Martins et al. [ 16], films were prepared from acid-hydrolyzed (hydrochloric acid) and esterified rice starch (citric acid), which exhibited higher tensile strength and relative crystallinity and better biodegradability, but lower water solubility. Although starch is not thermoplastic, it can be extruded or injected to produce films, similar to other polymers, after the addition or in the presence of plasticizers such as glycerol or water [17].
To improve the film-forming properties, the polymeric starch matrix can be modified or reinforced with various agents or other polymers. The final properties of starch-based films also depend on the processing technique or the type of plasticizer used [18]. The addition of plasticizers improves films’ flexibility and processing properties, but at higher levels reduces moisture inhibition and flexibility [19]. Studies have shown that the incorporation of glycerin at high concentrations in films based on arrowroot starch (Maranta arundinaceous) increases film thickness, moisture content, and water solubility [20].
Moisture transfer in packaged foods can lead to their spoilage and depends mainly on the water activity in the food, the temperature and humidity conditions in the storage environment, but also the moisture of the packaging and its permeability to water vapor; this phenomenon is of great importance to the food packaging industry [21]. The water permeability of starch-based films is a complex phenomenon due to the strong interaction of water molecules with the polymeric matrix of starch.
The water sorption isotherms of starch-based films are highly nonlinear in the range of 5–45 °C due to the varying amylose content of the starches. *In* general, the main mechanical properties of these water-absorbent polymers are highly dependent on their water content and ambient relative humidity [22]. Therefore, the determination of the shelf life and stability of food packaging films is highly dependent on the permeability and moisture absorption properties. The moisture absorption of the packaging is particularly important when packaging a moisture-sensitive food, and all phenomena affecting this must be taken into account [23]. In the previous study, the data for two different mathematical models (Q10 rule and Arrhenius equation) were relatively similar. The data were extrapolated to real temperature to analyze the influence of accelerated temperature conditions on fruit smoothies [24].
The shelf life of moisture-sensitive products can be predicted using Arrhenius’ mathematical model by considering the moisture content, deterioration over time, and permeability characteristics of the package concerning the relative humidity and temperature of the storage environment.
Due to the limited time, due to the long shelf life of food packaging, predictions of quality deterioration as a function of important parameters along the food chain, such as moisture, temperature, or UV radiation, are often made using mathematical models [25].
The aim of this study was to estimate the shelf life at ambient temperature and under normal RH conditions by accelerated stability tests, and to investigate the biodegradability of food packaging films produced from enzymatically hydrolyzed corn starch.
## 2. Materials and Methods
Corn starch was purchased from SCM Colin Daily Romania, and glacial acetic acid and glycerol were purchased from SC Chimreactiv SRL. α-amylase, from *Bacillus amyloliquefaciens* (A7595), was purchased from Sigma-Aldrich (St. Louis, MO, USA). All the materials were food-grade ingredients.
## 2.1. Preparation of Corn Starch Hydrolysate (CSH)
Enzymatic hydrolysis of corn starch with α-amylase from *Bacillus amyloliquefaciens* was used to prepare biofilms for food packaging, based on the method described by Kong et al. [ 26] with minor modifications.
The polymeric matrix of hydrolyzed corn starch was reinforced by the addition of glycerol as a plasticizer. A material commonly used for food packaging, polyethylene, was selected for biodegradability comparisons.
## 2.2. Preparation of CSH Films
CSH films were prepared using the casting method described by Beer-Lech et al. [ 27] using CSH, glycerol, and glacial acetic acid (as crosslinking agents). The CSH film-forming solution was prepared by mixing 20 g of CSH with 150 mL of distilled water at 50 °C.
To the film-forming solution, 10 mL of glycerol as plasticizer (1:2 v/w of CSH) and 10 mL of 0.5 M acetic acid were added. The mixture was kept at 70 °C with a heating magnetic stirrer under constant stirring at 300 rpm until complete gelatinization.
The film-forming solution was then cooled to 50 °C and poured into glass plates (20 × 20 cm) to ensure that the film thickness was uniform, and dried at room temperature of 25 °C for about 72 h. After drying, the film was removed from the glass plates and stored in a desiccator until characterization.
## 2.3. Physical and Hygroscopic Properties: Film Thickness, Moisture Content (Mc), Swelling Degree (Sd), and Total Soluble Matter (Tsm)
The hygroscopic properties of film-forming materials are considered important factors in choosing films for use in specific applications. Water resistance and integrity are required for packaging foods with high moisture content, so water solubility or moisture absorption of the material used may be detrimental. The CSH film samples were compared in terms of their hygroscopic properties to a control sample obtained with non-hydrolyzed corn starch.
## 2.3.1. Film Thickness
The film thickness was measured in five points (one in the center and the others in different parts of the film) using a digital micrometer. The average thickness value was calculated.
## 2.3.2. Moisture Content (Mc), Swelling Degree (Sd), and Total Soluble Matter (Tsm)
Mc, Sd, and Tsm were determined according to the three-step method described by Janik W. et al. [ 28] with minor modifications. For Mc, Sd, and Tsm determination, the weights M1, M2, M3, and M4 were determined. Triplicate specimens of CSH film samples and the control sample were cut into pieces 3 × 3 cm and weighed on an analytical balance with an accuracy of 0.001 (M1). The samples were dried for 24 h at 105 °C and weighed again (M2). Then, the CSH film samples and the control samples were kept in 50 mL of distilled water for approximately 24 h and weighed again (M3). For the determination of Tsm, the CSH film samples and the control samples were dried again for 24 h at 105 °C and weighed (M4). All measurements were performed at least three times, and the mean values were calculated using the following equations (Equations [1]–[3]):[1]Mc=M1−M2M2×100, [2]Sd=M3−M2M2×100, [3]Tsm=M2−M4M2×100
## 2.3.3. Water Vapor Permeability (WVP)
The water barrier efficiency of films is indicated by the WVP value and is an important factor to monitor because it can affect the quality of food packaged in films, especially during distribution and storage [29]. The predominance of hydrophilic molecules such as glycerol and the hydrophilic structure of starch, which constitute the majority of compounds in the matrix of CSH film, facilitate the diffusion of water molecules inward; therefore, the WVP of CSH films depends on the hydrophobic–hydrophilic balance of the components that make up the films and the degree of bonding between the molecules [30].
The WVP value for the CSH film samples was determined according to the method described by Kumar et al. [ 31,32] and according to ASTM E96 [33] with minor modifications. Briefly, Berzelius beakers containing calcium chloride (pre-dried at 105 ± 1 °C for 24 h) were sealed with CSH film samples placed on the top of the beaker. All Berzelius beakers covered with CSH film samples were weighed and placed in a desiccator where the relative humidity was maintained at $75\%$ RH (using the saturated solution of sodium chloride, NaCl). The temperature and RH inside and outside the desiccator were recorded using a digital instrument for measuring temperature and humidity.
The desiccator was placed in an incubator at 35 ± 3 °C. The weight of all beakers was recorded every 8 h for the first 24 h and every 24 h thereafter for 3 days. All measurements were performed at least three times for each sample. WVP was calculated using Equation [4] after plotting the weight gain of the samples as a function of time:[4]WVP=(SlopeA×t)/ΔP, where the slope of the line was calculated by linear regression (R2 > 0.9) of the weight change versus time, t is the average film thickness (mm), A is the exposed film area (mm2) and ΔP is the partial vapor pressure difference between the outside and inside of the film-covered beaker (RH $75\%$–RH $0\%$), ΔP = 0.35 kPa.
## 2.4. Accelerated Shelf Life and Stability Testing
The accelerated shelf-life testing (ASLT) method was applied to obtain rapid data, which were modeled and statistically analyzed to provide information on the shelf life of CSH film under normal conditions of use and storage. The ASLT method consists of keeping the samples under extreme storage conditions to accelerate their degradation and constantly monitor the parameters with direct influence on their shelf life. The CSH film samples were tested according to the protocols for the ASLT method described by Mizrahi et al. [ 34].
The ASLT method applies to any degradation process (mechanical, chemical, physical, biochemical, or microbiological) for which there is a valid kinetic model and experimental data that can be extrapolated [35]. To predict the actual shelf life, it is necessary to evaluate how the deterioration process behaves as a function of time under accelerated conditions [36].
The method can be achieved by two different approaches, either applied separately or simultaneously:-Time compression (high usage rate, testing is performed more intensively than actual usage);-Accelerated degradation testing (the same conditions that degrade the product under normal storage conditions).
Variables that can accelerate the degradation of packaging films are usually temperature, humidity, pH, light, or UV rays [37,38,39].
For CSH film samples, the hygroscopic depreciation and folding strength were monitored during the test period to observe how different extreme storage conditions influence the stability and shelf life.
Triplicate specimens of CSH film samples were placed at three different temperatures and RH conditions (13 ± 2 °C and 65 ± $5\%$ RH, 23 ± 2 °C and 45 ± $5\%$ RH, and 33 ± 2 °C and 30 ± $5\%$ RH) in climate chambers. The samples were removed from the chambers at a 15 day interval to determine the moisture absorption and folding strength.
## 2.4.1. Moisture Absorption (Ma)
Ma was determined according to the method described in ASTM D 570-98 [40]. Triplicate specimens of CSH film samples were cut into pieces 3 × 3 cm, dried at 105 °C, and initially weighed before being placed in the climate chambers. The weight of the samples was measured at different time intervals.
The Ma value of the samples was calculated according to Equation [5]:[5]Ma=Mt−MiMi×100, where Mt—final weight at different time intervals, Mi—initial weight before placing them in climate chambers.
## 2.4.2. Folding Strength
Fold strength was evaluated using the method described by Sharmilla et al. [ 41], used to assess the decrease in film elasticity under extreme storage conditions. The number of double folds required for the film to break is defined as the fold strength and evaluated using Equation [6]:[6]F=log 10 D, where F—folding strength, D—number of double folding.
The depreciation of CSH film hygroscopicity and elasticity was evaluated by analyzing the results using a stability test based on a regression model and a shelf-life test based on a reliability statistics model (Minitab 20 statistics software. Minitab LLC, State College, PA, USA).
## 2.5. Biodegradability Property: Soil Burial Test
Biodegradability was evaluated by assessing the effects of the natural environment and soil microorganisms on film weight during the soil burial test.
The CSH films obtained were subjected to a 30-day soil burial test using topsoil as a microbial source to simulate the degradation process in the natural environment, using the protocols described by Nissa et al. [ 1] with minor modifications. The test was conducted at a room temperature of 23 °C ± 2 and under controlled humidity conditions. Three specimens of CSH film samples (3 × 3 cm) were buried at a depth of approximately 2 cm in darkened pots (6.5 × 6.5 × 6.5 cm) filled with topsoil (approximately 1000 g). Polyethylene film samples (3 × 3 cm) were used as positive controls.
The pots were sprayed twice daily to maintain soil moisture and simulate natural conditions. At regular intervals (at six-day intervals), the samples were carefully removed from the pots, gently brushed off, washed three times with distilled water, and dried at room temperature. Biodegradation was evaluated by FTIR analysis and SEM characterization, visual and microscopic observation, and weight loss.
The degree of degradation evaluated by weight loss was calculated using Equation [7]:[7]Weight loss=Wi−WtnWi×100, where *Wi is* the initial weight of the samples and *Wtn is* the weight of the samples at time tn where n (0…5).
## 2.5.1. Visual Appearance
The physical changes of the CSH films during the soil burial test were photographed with a camera at least five times during the soil burial test (at six-day intervals). Before photographing, the CSH film samples were removed from the soil, washed, and dried.
## 2.5.2. Polarized Light Microscopy
The surface of the CSH films was observed with a Nikon Eclipse E100 light microscope (Nikon Corporation, Kanagawa, Japan) and analyzed at least five times (at six-day intervals) during the soil burial test. After washing the samples with distilled water, images of dried CSH film samples (×10 and ×40 magnification) were taken using a Canon PowerShot A640 camera (Melville, NY, USA).
## 2.5.3. SEM Characterization
Microstructures of the cross-sections and surface morphology were visualized using SEM characterization with a Hitachi TM4000 plus II equipped with a BSE detector and vacuum conductor at an accelerating voltage of 5–15 kV. Digital SEM images of the surface and cross-sections of the CSH films were also analyzed at least five times (at 6-day intervals) during the burial test. The CSH film samples were placed on an SEM tube with carbon tape and the images were recorded (×35, ×500 magnification).
## 2.5.4. FTIR Analysis
FTIR spectra were acquired using a spectrometer (Bruker, Germany), model Tensor 27 with a ZnSe ATR (Attenuated Total Reflection) accessory The CSH films were tested to investigate the effects of biodegradation on the IR spectrum or changes in molecular structure, analyzed at least five times (at 6-day intervals) during the burial test.
The CSH film samples were washed with distilled water, dried at 30 °C, and crushed for further IR analysis. The analyzed samples were directly spread on the ATR-ZnSe crystal. The ATR crystal was cleaned with ethanol before each measurement to eliminate the presence of residues. FTIR spectra were recorded in the wavelength range of 650–4000 cm−1 with 32 scans per sample, at a resolution of 4 cm−1 and a speed of 0.32 cm/s.
## 2.6. Statistical Analysis
Data were analyzed with Minitab 20 statistical software using Tukey’s comparison test to detect significant differences ($p \leq 0.05$). Regression and reliability statistical models were performed to process the data and analyze the influence of different temperatures and RH conditions on the durability and stability of the CSH film. All results were reported as mean ± standard deviation of at least three measurements ($$n = 3$$).
## 3.1.1. Film Thickness, Mc, Sd, and Tsm
The hygroscopic properties of the obtained starch-based films are shown in Table 1.
The obtained CSH films showed a lower Mc value (19.15 ± $0.020\%$) and Tsm (4.75 ± $0.030\%$) than the control film, and a higher −Sd (60.3 ± $0.025\%$). For all analyses, there was a statistically significant difference ($p \leq 0.05$), which was denoted by different lowercase letters in the same column.
This may be due to the incorporation of hydrolyzed starch, which may be more stable and balanced in terms of amylose and amylopectin content following enzymatic hydrolysis, which might have a direct influence on the ability of the film to retain water.
The obtained results are similar to those of the Janik et al. study [21] for the starch film. Rodriguez et al., 2014 [42] observed, for the chitosan films, that the amount of glycerol had a substantial impact on the swelling behavior of the film.
Since the CSH film samples were obtained with the same amount of glycerol as the control sample, but we have a higher Sd value for these film samples, lower glycerol ratios can be tested to obtain the film from hydrolyzed starch.
In many applications, such as food packaging, solubility is a desirable property, Tsm value being an important factor in selecting films for packaging. However, water resistance and integrity are required for foods with high moisture content, and the high solubility of a film is detrimental.
Low solubility in water is desired in our situation. These results are better than earlier research made by Guo et al. [ 43], which has shown that pure polysaccharide-based films are almost entirely soluble. The CSH film samples have better qualities than the control sample for applications in food packaging, especially for hygroscopic properties such as Mc and Tsm, which had lower values.
## 3.1.2. WVP
Figure 1 and Table 2 present the obtained values of WVP for the CSH film sample compared with the control sample.
Compared to the control samples, the values for WVP of the CSH film samples are improved but significantly different (using the Tukey comparison test for $p \leq 0.05$), and similar to the values obtained by Liu Fei et al. [ 44] for gums films. For certain types of food products, such as processed foods, it is desirable to decrease the WVP of the packaging.
The food packaging material should not facilitate the moisture transfer between the food and the environment for extending the shelf life of the product.
In this context, the addition of oils can improve the WVP values of the CSH film samples.
Rodriquez et al. [ 35] obtained a highly synergistic interaction between glycerol and emulsifiers in potato starch films, achieving the smallest WVP results for starch films.
## 3.2.1. ASLT
ASLT was used to estimate the time until failure in terms of hygroscopicity and elasticity depreciation of CSH film samples using accelerated temperatures and different RH conditions.
This test was used to estimate the time until $5\%$ of the CSH film samples were expected to fail under normal temperature conditions.
Figure 2 and Table 3 show the failure probability plot at three different temperatures and RH conditions during the 60-day test, as well as the predicted failure time under normal temperature and RH conditions.
The “ALT” function (Minitab 20 statistics software) was used to estimate the shelf life at different storage temperatures, taking into account all the parameters analyzed.
If, during the test (T0…T4), any of the parameters are not within the acceptance limit (the sample is severely degraded), this sample is classified as non-compliant and given a score of 0.
In cases where the product has not suffered deterioration of the analyzed parameters, it is given a score of 1, i.e., compliant (data not shown).
The experimental results are processed, specifying the distribution of the data (lognormal, Weibull, etc.) and the mathematical probability model (linear or nonlinear). Since the sample depreciation was affected by temperature and humidity, the linear model is chosen and the Arrhenius equation is used with an error of $5\%$.
Based on results obtained with Minitab 20 statistical software, $95\%$ of CSH film samples are expected to remain unchanged after 8.89 months when the film is used at normal temperature conditions (20 ± 5 °C and 45 ± $5\%$ RH), with a lower limit of 7.66 months and an upper limit of 10.25 months when temperature and RH change beyond these values.
## 3.2.2. Stability Test
In order to use the “stability” function in the Minitab 20 statistical software, it is necessary to specify a property that is most important for the stability of the sample under study.
For the CSH film samples, the most important property in terms of hygroscopicity was moisture absorption under various relative humidity conditions (data not shown).
As part of this function, it is necessary to select the minimum and maximum limits within which the product or film being analyzed must fall to be optimal (Figure 3).
The function checks whether the starting point of the fitted line is between specifications, and then determines the direction of the slope of the fitted lines before deciding from which limit to calculate the shelf life.
If the decrease in average response is statistically significant, the shelf life is determined based on the lower limit of the specification. If the increase in average response over time is statistically significant, the shelf life is determined based on the upper limit of the specification. In terms of design, if the slope of the average line response has a decreasing trend, we should take a look at the upper limit. *The* general shelf life of CSH film from a hygroscopic point of view was determined to be 10.29 months.
The results of the stability and acceleration tests were in agreement, with the CSH film having an expected shelf life of at least 7.66 months when kept under normal environmental conditions.
## 3.3. Biodegradability Property
The weighted loss plot function of the degradation of the CSH films over time during the burial test is shown in Figure 4.
Biodegradability was evaluated by weight loss during the 30-day soil burial test. The CSH film samples showed a higher percentage of film biodegradability compared to the control samples, which showed little color change but no weight loss.
As expected, significant mass loss was observed, which increased with the duration of burial in the soil. After the 30-day burial test, the CSH films showed a weight loss of $56.82\%$, which is in agreement with the results of the study by Lucchese et al. [ 2] and the requirements of the European standard EN13432 [45] (biodegradable plastics must lose $90\%$ of their mass after at least six months and decompose into water, CO2 and biomass). As only small CSH film samples were investigated, the obtained results should be considered estimates.
## 3.3.1. Visual Appearance
Changes in the physical appearance of the CSH film samples due to biodegradation during the soil burial test were monitored and observed by photographing the samples. The photographs of the CSH film samples before and after the biodegradation test are shown in Figure 5.
There was significant degradation by microorganisms in the CSH film samples. The main indicators of biodegradation can be seen in the physical changes of the CSH film samples, which had lost their structural integrity and original appearance and had become glassy and brittle.
## 3.3.2. Polarized Light Microscopy
Film solubility is an important factor in biodegradability and is directly related to degradation by microorganisms in the soil. At the beginning of the process, changes in film surface and roughness are to be expected due to enzyme attack on the polymer structure. Higher solubility means that the components of the CSH film are more accessible for degradation by the microorganisms present in the soil, such as bacteria, fungi, and protozoa [4].
The microscopic images of the CSH film samples and control sample (Polyethylene film), recorded during the soil burial test, are presented in Figure 6.
Figure 6 shows an intensification of soil microorganism activity on the surface of the CSH films during the biodegradation test, which is a clear sign of the continuous biodegradation process.
## 3.3.3. SEM Characterization
Bulleted lists look like this: SEM images were also recorded for every test time interval to better understand the biodegradation behavior of the CSH film sample. Figure 7 shows SEM images of the CSH film samples during the soil burial test.
As shown in Figure 7, the surface of the CSH film sample was smooth, compact, and clean before the burial test. During the soil burial test, all CSH film samples lost their original appearance and structural integrity, and the film surface became rough and had small voids. After 30 days of burial test, the surfaces of all CSH film samples exhibited similar microstructure, becoming both dull and porous, with numerous voids and cracks, compared to the control sample, which had no visible surface changes. SEM images confirmed the continuous biodegradation rate, which showed a significant increase in the degradation of CSH films in the soil, mainly by microorganisms.
## 3.3.4. FTIR Analysis
Using the FTIR spectrum of the CSH film samples during the soil burial test, the changes in molecular structures were investigated. The fingerprint area and characteristic bands of the CSH film and control samples were recorded before and during the soil burial test. Figure 8 shows the FTIR spectra of the CSH film samples during different degradation phases compared to the control sample.
The absorption maximum of the CSH film samples is observed at 3278 cm−1 and is attributed to the stretching vibrations of starch due to the presence of hydroxyl groups. The peak attributed to CH groups in the disaccharide bonds is observed in the range 2926–2847 cm−1. Most of the absorption peaks are observed in the ranges 1460 cm−1, 1150 cm−1, 1001 cm−1, 924 cm−1, and 860 cm−1 and are attributed to the CO bonds. After exposing the CSH film samples to the soil, a decrease in the peaks representative of the starch film is observed, indicating a weakening of the bonds. Considering that $56.82\%$ of the CSH film samples were degraded in terms of weight loss, this was also reflected in the FTIR spectrum of the samples as most of the bonds appeared to be cleaved and a decrease and shift in the peaks were observed.
For example, due to the degradation of starch and/or glycerol by soil microorganisms, the OH-stretch band in soil for the degraded CSH film samples not only showed a significant decrease in intensity but also shifted from 3278 cm−1 to 2420 cm−1 at the end of the biodegradability test. In contrast, the control sample remained undamaged during the soil burial test, and there were no visible changes in the FTIR spectrum.
## 4. Conclusions
The CSH film will remain stable from its hygroscopic qualities for at least 7.66 months if kept in a normal atmosphere, according to the findings of the accelerated shelf life and stability tests.
All analyses conducted during the soil burial test backed up the conclusion that the CSH films underwent a sequentially progressing biodegradation process. This process included weight loss microbial activity and an increase in the film’s porosity, with numerous voids and cracks.
The breakage of the starch component by soil microorganisms, leakage of the plasticizer, and the breakdown of the chemical structure into small molecular units were also observed, as indicated by the SEM micrographs and FTIR analyses.
## Outlook
Biodegradable corn starch hydrolysate films are an excellent choice for dried foods packaging due to their good shelf life at room temperature, which is beneficial when shipping and storing products. They are also environmentally friendly because they are made from renewable plant-based materials and degrade over time, so less waste ends up in landfills. It should be noted, however, that these films are not suitable for foods with high moisture content, as they decompose easily under these conditions. Additionally, when using these films for packaging, care should be taken to ensure that the shelf life of the product is not affected.
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---
title: Ursolic Acid Ameliorates Myocardial Ischaemia/Reperfusion Injury by Improving
Mitochondrial Function via Immunoproteasome-PP2A-AMPK Signalling
authors:
- Luo-Luo Xu
- Hui-Xiang Su
- Pang-Bo Li
- Hui-Hua Li
journal: Nutrients
year: 2023
pmcid: PMC9967761
doi: 10.3390/nu15041049
license: CC BY 4.0
---
# Ursolic Acid Ameliorates Myocardial Ischaemia/Reperfusion Injury by Improving Mitochondrial Function via Immunoproteasome-PP2A-AMPK Signalling
## Abstract
Cardiac ischaemia/reperfusion (I/R) injury causes cardiomyocyte apoptosis and mitochondrial dysfunction. Ursolic acid (UA), as a pentacyclic triterpenoid carboxylic acid, exerts several bioactivities in animal models of different diseases, but the preventive role of UA in I/R-induced myocardial dysfunction remains largely unknown. Male wild-type mice were pre-administered with UA at a dosage of 80 mg/kg i.p. and then subjected to cardiac I/R injury for 24 h. Cardiac function and pathological changes were examined by echocardiography and histological staining. The protein and mRNA levels of the genes were determined using qPCR and immunoblotting analysis. Our results revealed that UA administration in mice significantly attenuated the I/R-induced decline in cardiac function, infarct size, myocyte apoptosis, and oxidative stress. Mechanistically, UA increased three immunoproteasome catalytic subunit expressions and activities, which promoted ubiquitinated PP2A degradation and activated AMPK-PGC1α signalling, leading to improved mitochondrial biosynthesis and dynamic balance. In vitro experiments confirmed that UA treatment prevented hypoxia/reperfusion (H/R)-induced cardiomyocyte apoptosis and mitochondrial dysfunction through activation of AMPK signalling. In summary, our findings identify UA as a new activator of the immunoproteasome that exerts a protective role in I/R-induced myocardial dysfunction and suggest that UA supplementation could be beneficial for the prevention of cardiac ischaemic disease.
## 1. Introduction
Myocardial infarction (MI) is a well-known medical disease that causes high morbidity and mortality rates in the world. Timely reperfusion has been demonstrated to efficiently limit infarct size and attenuate cardiac dysfunction, but it also aggravates cardiac tissue injury, which is known as cardiac ischaemia and reperfusion (I/R) injury [1]. Interestingly, multiple pathophysiological features are involved in the pathological process of cardiac I/R impairment, including cell death, inflammation, Ca2+ overload, excessive production of oxygen free radicals (ROS), endothelial dysfunction, aggregation of platelets, and mitochondrial energy dysfunction [1]. However, at present, no available treatments effectively protect the heart against this injury. Thus, it is essential to discover and develop novel strategies to prevent or cure myocardial I/R injury to ameliorate clinical outcomes in MI patients.
The proteasome complex is a proteolytic enzyme that regulates the degradation of misfolded, damaged, or aggregated proteins in mammalian cells, which is required to maintain the homeostasis of proteomes and most cellular processes [2]. The core 20S proteasome is composed of 28 α or β subunits. Among them, there are three constitutive catalytic β subunits, including β1, β2, and β5 (also known as PSMB6, PSMB7, and PSMB5, respectively), which are responsible for three proteolytic activities (caspase-like, trypsin-like, and chymotrypsin-like, respectively). Upon inflammatory stimulation, these constitutive β subunits are substituted by three β immunoprotease subunits, β1i, β2i, and β5i (also known as PSMB9/LMP2; PSMB10/LMP10; PSMB8/LMP7), to generate the 20S immunoproteasome [2,3]. Early studies indicated that the immunoproteasome primarily regulates antigen presentation and the inflammatory response [2]. Recently, more studies have demonstrated that the expression and activity of the β2i and β5i subunits are highly upregulated during heart angiotensin II infusion or pressure overload [4,5,6,7]; furthermore, these subunits are critically involved in several types of cardiovascular diseases, including heart failure, cardiac hypertrophic remodelling, abdominal aortic aneurysm, and atrial fibrillation [4,5,6,7]. Interestingly, the immunoproteasome plays an important role in the regulation of cardiac ischaemic injury. Activation of the β1i subunit and proteasome activator PA28α restores I/R-mediated cardiac dysfunction by decreasing PTEN protein levels and inhibiting the Akt or HIF-1α signalling pathway [8,9,10]. In contrast, inhibition of endogenous β5 and proteasome chymotrypsin-like activity in mice by overexpressing T60A-β5 significantly accelerates cardiac I/R injury [11]. Thus, an increase in immunoproteasome activity may protect against cardiac I/R injury.
Accumulating evidence from clinical trials and population studies reveals that a healthy diet that is higher in plant foods (whole grains, nuts, seeds, fresh vegetables, and fruits) and lower in animal foods can significantly reduce the risks of noncommunicable diseases, including cancer and cardiovascular disease [12]. Indeed, natural therapeutic agents, which are isolated from plants and vegetables containing active ingredients, can effectively prevent cardiac I/R injury in different models of animals [13]. However, translation into clinical practice is less successful. Ursolic acid (UA; 3 β-hydroxy-urs-12-en-28-oic acid) is a pentacyclic triterpenoid (PT) carboxylic acid which has been identified in numerous traditional medicinal herbs and foods, including ginseng, apple peel, cranberry, plum, calendula, rosemary, and pear [14]. The chemical formula of UA is C30H48O3, with a molecular weight of 456.7 g/mol and low solubility in water (Figure 1A) [14]. UA and its derivatives are safe and have low toxicity against normal cells; furthermore, these compounds have numerous critical pharmacological activities which make them potential therapeutic drugs for cancers [14]. Numerous studies have indicated that UA and its derivatives display diverse biological properties and exert anti-inflammatory, antioxidant, and neuroprotective activities and anti-diabetic effects through different mechanisms [15]. In terms of the antitumour effects, UA can modulate the growth factor receptors (EGFR, HER-2, and PDGF), transcription factors (AP-1, STAT3, p53, and NF-kB), production of pro-inflammatory cytokines, and other molecular mediators which are crucial for the regulation of the cell death, proliferation, metastasis, and angiogenesis of tumour cells [16]. Indeed, UA has a beneficial role in various diseases, such as cancer, diabetes, and some cardiovascular diseases, in experimental animal models. Moreover, several clinical trials have been reported to test the effects of various formulations of UA on healthy subjects or patients with different cancers [15]. The findings from these studies suggest that UA and its distinct derivatives may become potential therapeutic drugs for treating these diseases. Moreover, UA has recently been reported to alleviate apoptosis in hypoxia/reoxygenation (H/R)-induced cardiomyocytes in vitro [17] and ameliorates I/R-mediated myocardial injury in isolated rat heart [18]. Interestingly, a recent study suggests that UA can induce the proteasome activity in Caenorhabditis elegans [19]. However, whether UA could increase proteasome activity in the heart to protect against cardiac I/R-related dysfunction and its underlying mechanism are unclear.
Here, our results indicated that UA exerted a cardioprotective role in I/R-induced cardiac impairment and heart failure. Mechanistically, UA highly upregulated immunoproteasome subunit expression and activity that promoted PP2A degradation and activated AMPK-PGC1α signalling leading to Mfn$\frac{1}{2}$ and Drp1 balance, thereby improving I/R-induced perturbation of mitochondrial biosynthesis and dynamics. Therefore, our data provide new evidence that UA may be considered a promising candidate for preventing cardiac I/R injury in patients.
## 2.1. Mice
C57BL/6J mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd (Beijing, China). All animals were kept in a pathogen-free room with a temperature of 25 ± 1 °C. Standard mouse chow and water ad libitum were provided to all mice throughout the study in the animal facility of the Beijing Chaoyang Hospital Medical Research Center.
## 2.2. Ischaemia/Reperfusion (I/R) Model and UA Treatment
Cardiac I/R injury was induced in male mice (20–23 g, $$n = 46$$) at 8–9 weeks old by occlusion of the proximal left anterior descending coronary artery (LAD) for 0.5 h followed by reperfusion for 24 h as described previously [20,21]. Sham mice ($$n = 54$$) underwent the same operation procedure with no LAD artery ligation. To evaluate the impact of UA on cardioprotection against I/R injury in mice, UA (purity = $99.66\%$; HY-NO140, MCE, powder) was fully dissolved in $5\%$ dimethyl sulfoxide (DMSO) and then diluted with corn oil to reduce DMSO toxicity. A previous study administered UA at 40 mg/kg body weight/day to rats from 3–9 days after isoproterenol injection [22]. Another study administered UA (80 mg/kg/day) for 7 days prior to intraperitoneal (i.p.) injection of doxorubicin in mice [23]. In the present experiment, we chose intraperitoneal administration of UA at 80 mg/kg/day (200 μL per mouse) to mice 2 and 24 h prior to the I/R operation based on our preliminary data shown in Figure 1 and Figure 2. Corn oil without UA was administered to mice as vehicle control. To test the impact of UA on cardiac I/R damage, animals ($$n = 6$$ per group) were randomly divided into 4 groups, sham + vehicle, sham + UA (80 mg/kg), I/R + vehicle, and I/R + UA (80 mg/kg).
## 2.3. Echocardiographic Assessment
After 24 h of I/R or sham injury, all mice ($$n = 6$$ per group) were anaesthetized using 1.5–$2.0\%$ isoflurane. Echocardiography was used to detect cardiac structure and left ventricular (LV) function with a Vevo 2100 Imaging System (Visual Sonics Inc., Toronto, ON, Canada) The parameters, including LV internal dimension at end-diastole (LVIDd) and end-systole (LVIDs), LV posterior wall at end-diastole (LVPWd) and end-systole (LVPWs), LV anterior wall at end-diastole (LVAWd) and end-systole (LVAWs), ejection fraction (EF%), and fractional shortening (FS%) for all mice were analysed as previously described [21,24]. All data used for the calculation of these parameters are provided in Supplementary Table S1.
## 2.4. Evaluation of Cardiac Infarct Size
Measurement of cardiac infarct size was performed at 24 h of reperfusion. Animals ($$n = 6$$ per group) were anaesthetized with 100 mg/kg pentobarbital sodium. The heart was flushed with $0.9\%$ saline, the LAD artery was religated, and 200 μL of $1\%$ Evans blue solution was infused into the LV. Then, frozen heart was cut into 4 equal sections at 2 mm thickness and then dyed in $1\%$ 2,3,5-TTC solution (Sigma–Aldrich, Saint Louis, MO, USA) for 20 min at 37 °C. After 24 h of fixation in $4\%$ paraformaldehyde, each section was photographed by a Leica microscope (Wetzlar, Germany), and Image-Pro Plus software (National Institutes of Health) was used to analyse all images. The infarct area is shown in red, the LV area at risk (AAR) is shown in white + red, and the nonischaemic region is shown in blue. Average percentage of total ischaemic areas = infarct area/LV area; percentage of AAR = (infarct + at-risk) area/LV area [21].
## 2.5. Histological Examinations
Heart tissues from sham or I/R mice ($$n = 6$$ per group) were fixed in $4\%$ tissue-fixing fluid (Solarbio) and embedded in paraffin. Four sections of heart tissue were cut serially and adhered to slides. A TUNEL Apoptosis Detection Kit was used to evaluate myocyte apoptosis in the heart sections based on the manufacturer’s description (Roche). Cardiac myocytes were confirmed with fluorescence staining using an antibody against α-actinin (green). DAPI was used to identify nuclei (blue). For detection of reactive oxygen species (ROS) levels, heart tissue was immersed in optimal cutting temperature compound and sliced into 5 µm thick cryosections, which were stained with 1 µmol/L dihydroethidium (DHE) in PBS for 30 min at 37 °C. Each section was visualized using a Leica fluorescence microscope (German). Five visual fields were chosen randomly in each sample for the analysis of TUNEL-positive myocytes or DHE intensity. TUNEL-positive cells as well as ROS levels were analysed by ImageJ software.
## 2.6. Analysis of Proteasome Activity
Three types of proteasome caspase-like, trypsin-like, and chymotrypsin-like activities were detected in the I/R or sham heart tissues ($$n = 6$$ per group) using 3 fluorogenic peptide substrates (Z-mLPnLD, Z-LRR, and Suc-LLVY) in Proteasome-Glo assay kits (Promega, Madison, WI, USA) as previously described [4,25]. The proteins from ischaemic areas of the heart were purified with PBS. Equal volumes of protein supernatant and prepared proteasome substrate reagent were incubated in a 96-well plate for 10 min (37 °C). The fluorescence intensity for each sample was detected on a multimode microplate reader (Tecan, Spark model).
## 2.7. Cell Culture, Hypoxia/Reoxygenation Model, and Treatment
Neonatal rat cardiac myocytes (NRCMs) were purified from 1-day-old Sprague–Dawley (SD) rats (total 18 rats, $$n = 3$$ per group), which were sterilized with $75\%$ alcohol. The hearts were quickly removed, cut into small pieces (1 mm3), and digested with trypsin and collagenase II based on a previous report [4]. Isolated cardiomyocytes were incubated in DMEM/F12 supplemented with $15\%$ FBS for 24 h and then incubated in serum-free DMEM/F12 containing the appropriate chemicals for subsequent in vitro studies.
For the hypoxia/reoxygenation (H/R) assay in vitro, NRCMs were incubated in hypoxia buffer containing NaCl, NaHCO3, NaH2PO4·2H2O, anhydrous CaCl2, MgCl2·6H2O, sodium lactate, KCl, 2-D-ribose, and 2-deoxyglucose under hypoxic conditions ($1\%$ O2) for 6 h, and then the cells were incubated in normal DMEM (without FBS) and $1\%$ penicillin/streptomycin and reoxygenated under normal oxygen conditions ($95\%$ O2) for 24 h. UA (0.5 µM) and Compound C (CC, an AMPK inhibitor, 10 µM) or both were added to the culture medium for 24 h prior to H/R injury as described previously [26,27,28].
## 2.8. Mitochondrial and TUNEL Staining In Vitro
Mitochondria in cardiomyocytes were stained using 0.02 μM MitoTracker Red CMXRos (Beyotime) fluorescent probe for 20 min based on the instructions provided by the manufacturer. Mitochondrial images were photographed using a confocal microscope (Zeiss LSM510 META) as previously described [29]. Five visual fields were randomly selected from each group to quantify the number of mitochondrial fission in each image to obtain the mean value of each sample ($$n = 3$$/group).
For apoptosis measurement of NRCMs ($$n = 3$$ per group), cells cultured in 96-well plates were exposed to H/R conditions treated with and without UA (0.5 µM). After fixation with $4\%$ paraformaldehyde and $0.2\%$ Triton X-100 in PBS, cells were stained with a TUNEL Apoptosis (red) Detection Kit and DAPI (blue) based on the protocols provided by the manufacturer (Roche). Five images in each sample were randomly selected to quantify the number of apoptotic cells.
## 2.9. Mitochondrial Membrane Potential and mPTP Opening Detection In Vitro
For the detection of mitochondrial membrane potential (∆Ψm, MMP), NRCMs were washed with PBS and then stained with JC-1 working solution (Beyotime) for 20 min at 37 °C. Five images of each sample were photographed using fluorescence microscopy (Leica, DM2500) and analysed by ImageJ software (1.48v). The relative ratio of JC-1 aggregate (red)-to-monomer (green) fluorescence intensity was used to evaluate the proportion of depolarized mitochondria [30].
For the examination of mitochondrial permeability transition pore (mPTP), NRCMs were stained with a Mitochondrial Permeability Transition Pore Assay Kit based on the description of manufacturer (Beyotime). The relative calcein green fluorescence intensity in mitochondria was used to judge the degree of mPTP opening. All values of fluorescence intensity were normalized to controls. Five visual fields in each sample were randomly chosen to quantify the JC-1 or mPTP fluorescence intensity.
## 2.10. Examination of ATP Levels
Cardiac ATP levels in each sample ($$n = 6$$ per group) were examined with an ATP-level assay kit based on the manufacturer’s description (Beyotime). Ten milligrams of fresh cardiac tissues ($$n = 6$$ per group) was resuspended in ATP lysis buffer (100 μL), homogenized, and centrifuged at 12,000× g for 5 min. Then, supernatants were added into ATP assay working solution (100 μL) for 5 min [21,31]. A spectrophotometer plate reader (Tecan, Spark model) was used to measure the fluorescence intensity, and all values were normalized to controls.
## 2.11. LDH Activity Measurement
Supernatant from the fresh heart tissues ($$n = 6$$ per group) and serum from the mice ($$n = 6$$ per group) were collected as described in the I/R model method. Lactate dehydrogenase (LDH) activity was measured with an LDH activity assay kit (Jiancheng Bioengineering Institute, Nanjing, China). The fluorescence intensity for each sample was recorded at an excitation wavelength of 450 nm.
## 2.12. Quantitative Real-Time PCR Analysis
Sham or I/R hearts ($$n = 6$$ per group) were harvested. Total RNA was isolated from the border zone of the heart with TRIzol reagent (Takara). Equal amounts (1–2 μg) of total RNA and RT Enzyme mix (Takara) were used to synthesize cDNA. The mRNA expression of the target genes was analysed with a PCR thermocycler (Applied Biosystems) as previously described [21]. The data were normalized to GAPDH expression levels. All PCR primer sequences for each gene used are provided in Table 1.
## 2.13. Immunoblotting Analysis
The I/R or sham hearts ($$n = 4$$ per group) were flushed with PBS and harvested. The ischaemic border zone of the heart was lysed with RIPA lysis buffer containing protease inhibitors and sonicated as described [21]. The protein concentrations of each sample were measured with a protein assay kit based on the instructions of the manufacturer. Equal amounts (40–50 μg) of proteins were separated by SDS–PAGE on $10\%$ gels, transferred to PVDF membranes, and then incubated with the primary and secondary antibodies. Each blot density was quantified with scanning densitometry using a FluorChem R (ProteinSimple) imaging system and normalized to GAPDH as previously described [21]. All primary antibodies used in this study are shown in Supplementary Table S2.
## 2.14. Immunoprecipitation and Ubiquitylation Assays
Cardiac tissues were lysed with lysis buffer containing 20 mM trisHCl (pH 7.5), 150 mM NaCl, $1\%$ Triton X-100, sodium pyrophosphate, β-glycerophosphate, EDTA, Na3VO4, leupeptin, and plus PMSF (Beyotime) on ice for 0.5 h. The cell lysates were centrifuged at 12,000 rpm for 15 min (4 °C) to obtain the protein supernatants. Then, 2 mg/mL of the protein was incubated with anti-PP2A rabbit antibody (0.33 μg) and 30 μL of protein A–Sepharose (Amersham Biosciences), and gently shaken at 4 °C for 24 h. The pellets were washed five times with wash buffer (Beyotime). Bound proteins were eluted with 2× sample buffer with boiling. The ubiquitinated PP2A protein was evaluated with immunoblotting analysis with an anti-ubiquitin (Ub) antibody [4].
## 2.15. Statistical Analysis
All results are expressed as the mean ± SEM. Statistical analyses were carried out with GraphPad Prism 9 or IBM SPSS Statistics software 21.0. The Shapiro–Wilk normality test was used to examine the normal distribution of the data. Differences among groups were tested by one-way ANOVA analysis. A value of $p \leq 0.05$ was considered statistically significant.
## 3.1. UA Upregulates Cardiac Immunoproteasome Subunit Expression and Activity
UA has been reported to be an inducer of proteasome activity in the brain [19]. To determine whether UA activates proteasome activity in the heart, we treated WT mice with two doses (40 or 80 mg/kg) of UA for 24 h. Compared with the vehicle control, UA treatment at both 40 and 80 mg/kg had no cardiotoxic effect, as reflected by the measurement of LDH activity (Figure 1B). However, UA dose-dependently increased the three catalytic caspase-like, trypsin-like, and chymotrypsin-like activities of the proteasome in the heart tissues, similar to what has been previously described [4,6,25,32] (Figure 1C). Therefore, we chose UA at 80 mg/kg to treat mice for 12 or 24 h and found that compared with the vehicle control, UA treatment for 24 h markedly upregulated the activity of all three proteasome subunits in the heart (Figure 1D). Next, we determined which catalytic subunits of the proteasome were responsible for the increased proteasome activity. qPCR analysis showed that among the six catalytic subunits, the mRNA levels of the β1i, β2i, and β5i subunits, but not those of the β1, β2, and β5 subunits, were highly enhanced after 24 h of UA treatment (Figure 1E). The increased protein levels of β1i, β2i, and β5i were confirmed in cardiac tissue by immunoblotting analysis (Figure 1F). Taken together, these data reveal that UA at 80 mg/kg effectively enhances cardiac immunoproteasome activity via upregulation of the inducible catalytic subunits.
## 3.2. UA Attenuates the I/R-Mediated Reductions in Cardiac Immunosubunit Expression and Activity
To test whether UA prevents the development of I/R-triggered cardiac injury by upregulating proteasome activity, we treated WT mice with UA (80 mg/kg) for 24 h before I/R surgery (Figure 2A). Consistent with a previous report [11], I/R for 24 h significantly reduced three caspase-like, trypsin-like, and chymotrypsin-like activities in the heart tissues of the I/R model mice compared with those in the hearts of the sham mice, whereas this decrease was markedly blunted in the hearts of UA-treated I/R model mice (Figure 2B). Accordingly, I/R-mediated decreases in the mRNA and protein levels of the β1i, β2i, and β5i subunits were also reversed in the hearts of UA-treated mice (Figure 2C,D). Moreover, UA treatment also increased the β1i, β2i, and β5i expression and activities under sham conditions (Figure 2A–D).
## 3.3. UA Ameliorates I/R-Triggered Cardiac Impairment and Dysfunction
To determine whether UA-enhanced proteasome activity prevents I/R-mediated cardiac dysfunction in vivo, mice were pre-treated with UA (80 mg/kg) before sham or I/R surgery. After 24 h treatment, echocardiography indicated that I/R resulted in a significant decline in cardiac contractile function as indicated by reduced EF% and FS%, in vehicle-treated mice compared with sham mice, but this decrease was remarkably attenuated in UA-treated mice (Figure 3A, Supplementary Table S1). Accordingly, I/R-mediated enlargement of left ventricular (LV) chamber dimensions as indicated by increased LVIDd and LVIDs, was also greatly reduced in UA-treated mice (Supplementary Table S1). Then, we assessed the action of UA on I/R-mediated cardiac infarct size and cell apoptosis, which are the main inducers of cardiac injury and dysfunction. TTC/Evans blue and TUNEL staining revealed that I/R injury for 24 h highly augmented the infarct size as indicated by the increased infarct area/LV ratio, percentage of TUNEL+ myocytes, and Bax/Bcl-2 ratio in vehicle-treated mice compared with sham mice, but these actions were all dramatically suppressed in UA-treated mice after I/R injury (Figure 3B,C). Moreover, the ROS burst from the mitochondrial complex is a critical cause of cardiac I/R injury. We then tested the impact of UA treatment on oxidative stress and found that it markedly suppressed the I/R-mediated increase in the ROS level as indicated by increased DHE fluorescence intensity, the mRNA expressions of NADPH isoforms NOX2 and NOX4, as well as the LDH activity in serum and heart tissues compared with vehicle treatment after I/R injury (Figure 3D–G). Thus, these data suggest that UA has a cardioprotective role against I/R impairment.
## 3.4. UA Promotes Mitochondrial Biogenesis and Dynamic Balance through Activation of AMPK-PGC1α Signalling and Increased PP2A Degradation
Mitochondrial dysfunction has been considered a critical mechanism of cardiac I/R damage, and the AMPK axis exerts a key role in regulating mitochondrial biogenesis and dynamic balance during I/R injury [33]. Therefore, we tested the impact of UA on the activation of AMPK, regulators of mitochondrial biogenesis (PGC1α, TFAM, and TFB2M), and mitochondrial dynamics (Drp1 and Mfn$\frac{1}{2}$). Immunoblotting and qPCR analysis indicated that I/R surgery greatly reduced the protein levels of phosphorylated (p)-AMPKα (T172) and total PGC1α and the mRNA levels of TFAM and TFB2M in mice compared to those in the sham control, whereas this decrease was significantly attenuated in UA-treated mice (Figure 4A,B). Similarly, UA treatment also increased the protein levels of (p)-AMPKα (T172) and PGC1α and the mRNA levels of TFB2M and TFAM after sham surgery (Figure 4A,B). Moreover, I/R surgery-induced upregulation of the pro-fission protein Drp1 and downregulation of the profusion proteins Mfn$\frac{1}{2}$, which were greatly reversed in the hearts of UA-treated mice after I/R (Figure 4C). In addition, the ATP level was significantly higher in the hearts of UA-treated mice than in the hearts of vehicle-treated mice after I/R injury (Figure 4D). Therefore, these data suggest that UA treatment can improve cardiac mitochondrial biogenesis and mitochondrial dynamic imbalance after I/R surgery.
Multiple studies have revealed that activation of AMPK signalling is negatively regulated by PP2A, a Ser/Thr phosphatase [34]. To understand the molecular mechanisms whereby UA activates the AMPK-PGC1α axis in the I/R heart, we tested the effect of UA on cardiac PP2A protein levels. We found that I/R surgery significantly upregulated PP2A protein levels in vehicle-treated mice, an effect that was markedly reversed in UA-treated mice (Figure 4E). This effect likely occurred because PP2A stability is known to be modulated by the ubiquitin-proteasome system [35,36,37]. Consistent with these findings, the immunoprecipitation assay confirmed that I/R caused a significant upregulation of ubiquitinated PP2A proteins due to reduced proteasome activity, but this increase was blocked in UA-treated hearts (Figure 4F).
## 3.5. UA Improves H/R-Induced Cardiomyocyte Apoptosis, Mitochondrial Fragmentation and Dysfunction, Whereas Inhibiting AMPK Abolishes These Effects In Vitro
To validate the cardioprotective role of UA on cardiac I/R injury in vivo, we assessed the impact of UA on H/R-mediated cardiomyocyte apoptosis and mitochondrial function in vitro. Neonatal rat cardiomyocytes (NRCMs) were treated with UA at 0.1–5 µM for 24 h based on previous reports [26,27]. Measurement of LDH activity indicated that UA at 0.5 μM had no toxicity on NRCMs (data not shown). Next, NRCMs were cotreated with UA (0.5 μM) and CC (10 µM) for 2 h and then exposed to sham or H/R condition for an additional 24 h. Immunostaining of NRCMs indicated that H/R exposure for 24 h markedly increased the apoptotic cell numbers and mitochondrial fission and aggravated mitochondrial dysfunction as indicated by increased MMP and mitochondrial permeability transition pore (mPTP) values compared with those of the sham group after vehicle treatment (Figure 5A–D, lane 4 vs. 1). These effects were reversed in UA-treated NRCMs (Figure 5A–D, lane 5 vs. 4), but the reversals were abolished in CC-treated NRCMs (Figure 5A–D, lane 6 vs. 5). However, there was no difference in the parameters for mitochondria after sham treatment (Figure 5A–D, lane 1–3).
## 4. Discussion
Natural vegetation is the main source of active substances that are used as therapeutic drugs for numerous diseases. One group of compounds isolated from plants is PT, which has been reported to have many health benefits, including antiapoptotic, anti-inflammatory, antitumoural, and antibacterial properties with low toxicity [14]. Interestingly, high consumption of various fruits and vegetables is related to a reduced incidence of cancer and diseases in animal models [14]. Moreover, UA and oleanolic acid (OA) are two representative examples of PT compounds and are found in a number of plants. Multiple studies have confirmed that UA exerts antioxidative and antiapoptotic properties, playing protective roles in the development of several cardiovascular conditions, particularly hypertension, atherosclerosis, cardiac toxicity, cardiac remodelling, and myocardial infarction [14,21,22]. More recently, a study suggested that UA treatment significantly ameliorated H/R-mediated apoptosis of cultured H9c2 cardiomyocytes In vitro [17]. In the present study, our results verified these previous findings and further identified that UA, as a bioactive compound, increases immunoproteasome expression and activity, which promotes PP2A degradation and improves AMPK-dependent mitochondrial function, thereby leading to the attenuation of I/R-triggered cardiac dysfunction (Figure 1, Figure 2, Figure 3 and Figure 4). The protective effects of UA against H/R-mediated cardiomyocyte apoptosis and mitochondrial dysfunction were confirmed in cultured primary cardiomyocytes (Figure 5). Therefore, our data indicate that UA can prevent I/R-mediated mitochondrial impairment and cardiac dysfunction possibly by increasing the activity of the immunoproteasome–PP2A–AMPK pathway and highlight that UA supplementation could be beneficial for patients who undergo cardiac I/R injury.
The immunoproteasome is mainly involved in the inflammatory response and its expression and activity are markedly upregulated in both immune and nonimmune cells under various forms of cellular stress. Many inflammatory cytokines (IFN-γ and TNF-α) and other factors (ON, angiotensin II, and pressure overload) can upregulate the expression of the β1i, β2i and β5i subunits in different tissues and cell types via multiple signalling pathways [2,3,4,5,6,38]. In this study, we further identified that UA treatment significantly enhanced the expression levels of β1i, β2i, and β5i subunits and their activities in the hearts of mice (Figure 1) and markedly reversed the I/R-induced reduction in the three immunoproteasome subunits (Figure 2), suggesting that UA is an activator of the immunoproteasome at the transcriptional level. However, the precise mechanism by which UA upregulates immunoproteasome subunit expression remains to be elucidated.
Mitochondrial quality control mechanisms are required for preserving mitochondrial fission/fusion dynamic balance, mitophagy activation, and cell survival, which are key contributors to cardiac I/R impairment. AMPK is a herotrimeric complex composed of α/β/γ subunits and is activated by activated by upstream kinases (LKB1,CaMKK2, and TAK1) and increased ratio of ADP or AMP/ATP but is inhibited by protein phosphatase 2A and 2C (PP2A, PP2C) and oxidation or acetylation of cysteines in the α subunit [39]. AMPK is a key energy sensor that modulates cardiac glucose and fatty acid metabolism and exerts beneficial effects against cardiac I/R impairment through multiple mechanisms, which include amelioration of oxidative stress and inflammation, increase in mitochondrial synthesis and improvement of dynamic balance [40]. Pharmacological activation of AMPK protects against I/R-mediated cardiac myocyte death and contractile dysfunction [39]. AMPK/mTOR and AMPK/ULK1 signalling pathways are also crucial for activation of autophagy/mitophagy, which is a cytoprotective mechanism for cardiac I/R injury [39]. Meanwhile, AMPK critically promotes PGC-1α-dependent mitochondrial biogenesis by activating NRF$\frac{1}{2}$-MTFA-mediated transcription and replication of mitochondrial DNA in I/R [41,42]. Furthermore, mitochondrial dynamics are tightly controlled by a range of dynamin GTPases, such as Drp1 (the key factor for mitochondrial fission) and Mfn$\frac{1}{2}$ (key factors for mitochondrial fusion) [43]. The imbalance of Drp1 and Mfn$\frac{1}{2}$ levels leads to excessive mitochondrial fragmentation, which is an early hallmark of mitochondrial dysfunction and cardiomyocyte death after I/R surgery [43]. Increasing evidence indicates that AMPK is critically involved in regulating mitochondrial dynamics and redox homeostasis by suppressing the Drp1, NOX4, and SIRT1-PGC-1α pathways [44]. Previous reports suggest that UA has anti-inflammatory, antioxidant and antiapoptotic effects by regulating different signalling pathways, including Nrf2, PPARα, Bcl2-BclxL, p53-Bak-caspase-3, AKT-NO, NOX4-ROS, and CXCL2-NF-κB [17,22,23,45,46,47,48]. However, it is unclear whether UA regulates AMPK-PGC1α and subsequent mitochondrial biogenesis and dynamics in the heart after I/R injury. Here, our data revealed that UA significantly inhibited the I/R-mediated decreases in the protein levels of p-AMPK and PGC-1α and the mRNA levels of TFAM and TFB2M in heart tissues (Figure 4A,B). Moreover, I/R-induced upregulation of Drp1 and downregulation of Mfn$\frac{1}{2}$ were effectively reversed in the I/R heart (Figure 4C). Together, these data suggest that UA can reverse I/R-induced impairment of cardiac mitochondrial biogenesis and dynamic balance through AMPK-dependent signalling.
Phosphatases are involved in the cell cycle in tumours and are being actively explored as therapeutic targets. PP2A is a serine/threonine phosphatase that regulates over 50 protein kinases, including MAPKs and AMPK. Studies have demonstrated that PP2A can dephosphorylate Thr172 of the α-subunit of AMPK to inactivate its kinase activity [34,49]. Accumulating evidence suggests that PP2A plays critical roles in regulating various cellular processes and diseases, including cell apoptosis, autophagy, cancer, cardiac I/R injury, and MI, by inhibiting AMPK-dependent pathways [50,51,52,53,54]. Thus, modulating PP2A expression may represent a promising strategy for treating these diseases [49]. Indeed, PP2A activity can be modulated by posttranslational modifications, including phosphorylation, carboxymethylation, and ubiquitination. Several studies have revealed that ubiquitination of PP2A mediated by ubiquitin E3 ligases promotes its degradation by the proteasome. Conversely, knockout of E3 ligases or inhibition of the proteasome increases PP2A protein levels and activity, which thereby regulates cell apoptosis and asthma [35,36,37]. However, it is unknown whether UA-mediated immunoproteasome activity enhances PP2A degradation in cardiomyocytes after I/R injury. Our data revealed that UA treatment could significantly increase I(H)/R-induced degradation of PP2A, leading to the activation of AMPK-PGC1α-dependent signalling pathways in the heart and cultured cardiomyocytes (Figure 4E). Similarly, the immunoprecipitation assay confirmed that I/R significantly increased ubiquitinated PP2A protein levels due to reduced immunoproteasome activity, but this effect was reversed in the hearts of UA-treated mice (Figure 4F). These data suggest that UA can promote PP2A degradation possibly by increasing immunoproteasome activity.
## 5. Conclusions
This study revealed that UA exerts a critical role in protecting against I/R-induced cardiac injury and dysfunction. UA treatment markedly upregulated the immunoproteasome subunit expression and activity, which increased PP2A degradation that led to activation of AMPK-PGC1α signalling and the Drp1/Mfn$\frac{1}{2}$ balance, thereby improving mitochondrial biosynthesis and dynamic balance in the I/R heart. Our data also highlight that UA supplementation could be a promising strategy for the prevention of cardiac ischaemic disease. Future studies need to confirm the protective role of UA in other animal models of cardiac I/R injury, to elucidate the potential mechanism by which UA upregulates immunoproteasome activity to promote PP2A degradation in the I/R heart, and to define whether supplementation with UA could be a new option for preventing I/R-related diseases.
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|
---
title: 'Evaluation of the Association between Low-Density Lipoprotein (LDL) and All-Cause
Mortality in Geriatric Patients with Hip Fractures: A Prospective Cohort Study of
339 Patients'
authors:
- Xin Kang
- Bin Tian
- Zan-Dong Zhao
- Bin-Fei Zhang
- Ming Zhang
journal: Journal of Personalized Medicine
year: 2023
pmcid: PMC9967768
doi: 10.3390/jpm13020345
license: CC BY 4.0
---
# Evaluation of the Association between Low-Density Lipoprotein (LDL) and All-Cause Mortality in Geriatric Patients with Hip Fractures: A Prospective Cohort Study of 339 Patients
## Abstract
Background: Many factors affect the prognosis of hip fractures in the elderly. Some studies have suggested a direct or indirect association among serum lipid levels, osteoporosis, and hip fracture risk. LDL levels were found to have a statistically significant nonlinear U-shaped relationship with hip fracture risk. However, the relationship between serum LDL levels and the prognosis of patients with hip fractures remains unclear. Therefore, in this study, we assessed the influence of serum LDL levels on patient mortality over a long-term follow-up period. Methods: Elderly patients with hip fractures were screened between January 2015 and September 2019, and their demographic and clinical characteristics were collected. Linear and nonlinear multivariate Cox regression models were used to identify the association between LDL levels and mortality. Analyses were performed using Empower Stats and R software. Results: Overall, 339 patients with a mean follow-up period of 34.17 months were included in this study. Ninety-nine patients ($29.20\%$) died due to all-cause mortality. Linear multivariate Cox regression models showed that LDL levels were associated with mortality (HR = 0.69, $95\%$CI: 0.53, 0.91, $$p \leq 0.0085$$) after adjusting for confounding factors. However, the linear association was unstable, and nonlinearity was identified. An LDL concentration of 2.31 mmol/L was defined as the inflection point for prediction. A LDL level < 2.31 mmol/L was associated with mortality (HR = 0.42, $95\%$CI: 0.25, 0.69, $$p \leq 0.0006$$), whereas LDL > 2.31 mmol/L was not a risk factor for mortality (HR = 1.06, $95\%$CI: 0.70, 1.63, $$p \leq 0.7722$$). Conclusions: The preoperative LDL level was nonlinearly associated with mortality in elderly patients with hip fractures, and the LDL level was a risk indicator of mortality. Furthermore, 2.31 mmol/L could be considered a predictor cut-off for risk.
## 1. Introduction
Osteoporosis is characterized by reduced bone mass and strength, which increases the risk of fragility fractures [1,2,3], and causes long-term severe pain and/or dysfunction, seriously affecting patients’ quality of life [4,5,6,7]. Osteoporosis and osteoporotic fractures become more common with advancing age. Worldwide, osteoporotic fractures accounted for $0.83\%$ of the global burden of non-communicable diseases, increasing to $1.75\%$ of the burden in Europe [8]. Total fragility fractures in the EU are estimated to increase by $23\%$, from 2.7 million in 2017 to 3.3 million in 2030, and the resulting annual fracture-related costs (EUR 37.5 billion in 2017) are expected to increase by $27\%$. An estimated 1.0 million quality-adjusted life years (QALYs) are lost due to these fractures, and the disability-adjusted life years (DALYs) are higher than the estimates for stroke, chronic obstructive pulmonary disease, and common cancers, with the exception of lung cancer.2,8 Osteoporotic fractures typically occur in the hip, spine, wrist, and humerus. Fractures of the hip are among the most common and serious sites of osteoporotic fracture, which account for the majority of fracture-related healthcare expenditures and mortalities in men and women over the age of 50 years [8,9,10,11,12,13,14]. This poses a heavy burden on both individuals and society due to high treatment costs, reduced health-related quality of life, and reduced survival [15]. Fracture-related burdens are expected to continue increasing in the coming decades [2]. Therefore, preventive identification and prompt intervention for the risk of geriatric hip fractures are needed in these patients.
Many factors affect the prognosis of hip fractures in the elderly population. Pneumonia and circulatory system diseases are the most common causes of death in this population, and the mortality risk factors with a higher relative risk are advanced age, male sex, increased comorbidities, delirium, and medical complications during admission. Underlying risk factors include decompensation of chronic illness, fracture-related functional decline, and malnutrition. Patients with worse conditions at admission also have the highest risk of mortality [16,17,18,19].
Low-density lipoproteins (LDL), termed “bad cholesterol,” are large molecules comprising many proteins and lipids, including cholesterol, phospholipids, and triglycerides. Oxidized low-density lipoproteins (Ox-LDL) modulate the innate and adaptive immune responses, and can act in both pro- and anti-inflammatory manners through many proposed mechanisms [20,21,22,23]. Some studies have suggested a direct or indirect association among serum lipid levels, osteoporosis, and hip fracture risk [24,25,26,27]. In a prospective cohort study following 5832 participants aged ≥ 65 years from the Cardiovascular Health Study for hip fracture for a mean of 13.5 (SD 5.7) years. LDL levels were found to have a statistically significant nonlinear U-shaped relationship with hip fracture risk ($$p \leq 0.02$$) [28]. LDL cholesterol comprises $90\%$ of the circulating cholesterol in most people; therefore, there is a high correlation between total cholesterol and LDL levels [29].
However, the relationship between serum LDL levels and the prognosis of patients with hip fractures remains unclear. Therefore, in this study, we assessed the influence of serum LDL levels on patient mortality over a long-term follow-up period. We hypothesized that there would be either a linear or nonlinear association between LDL levels and mortality. This prospective cohort study aimed to identify the role of LDL levels in hip fractures.
## 2.1. Study Design
We recruited elderly patients who were treated for hip fractures between 1 January 2015 and 30 September 2019 at the largest trauma center in Northwest China. This prospective study was approved by the Ethics Committee of the Xi’an Honghui Hospital (No. 202201009). All procedures involving human participants were performed in accordance with the 1964 Declaration of Helsinki and its amendments.
## 2.2. Participants
The demographic and clinical data of the patients were obtained from their original medical records. The inclusion criteria were as follows: [1] age ≥ 65 years; [2] a radiographic or computed tomography diagnosis of a femoral neck, intertrochanteric, or subtrochanteric fracture; [3] patients receiving surgical or conservative treatment in a hospital; [4] availability of clinical data in the hospital; and [5] patients able to be contacted by telephone. Patients who could not be contacted were excluded from the study.
## 2.3. Hospital Treatment
The patients were examined using blood tests and ultrasonography to prepare for surgery. Intertrochanteric fractures are often managed with closed/open reductions and internal fixations of the proximal femoral nail by antirotation. Femoral neck fractures are often treated with hemiarthroplasty or total hip arthroplasty, depending on the patient’s age. Prophylaxis for deep vein thrombosis was initiated on admission. Upon discharge, the patients were asked to return for monthly check-ups to assess fracture union or function.
## 2.4. Follow-Up
After discharge, the patients’ family members were contacted by telephone from January 2022 to March 2022 to record data on survival, survival time, and activities of daily living. This follow-up was conducted by two medical professionals with two weeks of training and one year of experience. Contact was attempted two more times for patients who could not be contacted initially. If the family members could not be contacted, we recorded the patient as lost to follow-up.
## 2.5. Endpoint Events
The endpoint event in this study was all-cause mortality after treatment. We defined all-cause mortality as death reported by patients’ family members.
## 2.6. Variables
The variables in our study were as follows: age, sex, occupation, history of allergy, injury mechanism, fracture classification, presence of hypertension, diabetes, coronary heart disease, arrhythmia, hemorrhagic stroke, ischemic stroke, cancer, associated injuries, dementia, chronic obstructive pulmonary disease (COPD), hepatitis and gastritis, time from injury to admission, time from admission to operation, LDL level, duration of surgery, blood loss, infusion, transfusion, treatment, total hospital stay, and follow-up.
LDL level was defined as the liver function in the blood test performed at admission. If a patient did not undergo surgery for any reason, the final results before discharge were selected. The dependent variable was all-cause mortality, while the independent variable was LDL level. The other variables were defined as potentially confounding factors.
## 2.7. Statistical Analysis
Continuous variables are reported as the mean ± standard deviation (Gaussian distribution) or median (range, skewed distribution). Categorical variables are presented as numbers with proportions. Chi-square (categorical variables), one-way analysis of variance (ANOVA (normal distribution)), or Kruskal–Wallis H test (skewed distribution) were performed to detect the differences in different LDL levels. Univariate and multivariate Cox proportional hazard regression models (three models) were used to test the association between LDL levels and mortality. Model 1 was not adjusted for covariates. Model 2 was minimally adjusted only for sociodemographic variables. Model 3 was fully adjusted for all covariates. To test the robustness of our results, we performed a sensitivity analysis. We converted the LDL level into a categorical variable according to the anemia criteria, calculated p for the trend to verify the results of LDL as a continuous variable, and examined the possibility of nonlinearity. Because Cox proportional hazards regression model-based methods are suspected to be unable to deal with nonlinear models, the nonlinearity between LDL and mortality was addressed using a Cox proportional hazard regression model with cubic spline functions and smooth curve fitting, termed the penalized spline method. If nonlinearity was detected, we first calculated the inflection point using a recursive algorithm and then constructed a two-piecewise Cox proportional hazards regression model on both sides of the inflection point.
All analyses were performed using statistical software packages R (http://www.R-project.org, R Foundation for Statistical Computing, Vienna, Austria) and EmpowerStats (http://www.empowerstats.com, X&Y Solutions Inc., Boston, MA, USA). Hazard ratios (HR) and $95\%$ CI were calculated. Statistical significance was set at $p \leq 0.05$ (two-sided).
## 3.1. Patient Characteristics
Overall, 399 patients treated between January 2015 and September 2019 were included in this study. The mean follow-up period was 34.17 months, and 99 patients ($29.20\%$) died due to all-cause mortality. LDL concentrations were divided into three groups. Table 1 lists the demographic and clinical characteristics of the 399 patients, including comorbidities, factors associated with injuries, and treatment.
## 3.2. Univariate Analysis of Association between Variates and Mortality
We performed univariate analysis to identify potential confounding factors and the relationship between variables and mortality (Table S1). According to the criteria of $p \leq 0.1$, the following variables were considered in the multivariate Cox regression: age, CHD, arrhythmia, dementia, and treatment strategy.
## 3.3. Multivariate Analysis between LDL and Mortality
We used three models (Table 2) to correlate LDL levels and mortality. When LDL concentration was a continuous variable, linear regression was observed. The fully adjusted model showed a decrease in mortality risk (HR = 0.69, $95\%$CI: 0.53–0.91, $$p \leq 0.0085$$) when LDL concentration increased by 1 mmol/L after controlling for confounding factors. When LDL concentration was used as a categorical variable, we found statistically significant differences in LDL levels among the three models ($p \leq 0.0001$). In addition, the p for trend also showed a linear correlation in the three models ($p \leq 0.0001$).
However, we found that the changing interval was slow in the subgroups with different LDL levels (Table 2). This instability indicates the possibility of a nonlinear correlation.
## 3.4. Curve Fitting and Analysis of Threshold Effect
As shown in Figure 1, there was a curved association between LDL levels and mortality after adjusting for confounding factors. We compared two fitting models to explain this association (Table 3). Interestingly, we observed an inflection point in the saturation effect at 2.31 mmol/L. This indicates that at LDL < 2.31 mmol/L, the mortality risk decreased by $58\%$ (HR = 0.42, $95\%$CI: 0.25–0.69; $$p \leq 0.0006$$) when LDL concentration increased by 1 mmol/L; when LDL > 2.31 mmol/L, the mortality risk did not decrease with a LDL change (HR = 1.06, $95\%$CI: 0.70–1.63; $$p \leq 0.7722$$).
The Kaplan–Meier survival curves according to LDL level ($p \leq 0.0001$) and the inflection point of 2.31 mmol/L ($$p \leq 0.0016$$) are shown in Figure 2.
## 4. Discussion
In this study, we identified a nonlinear association between LDL and all-cause mortality in geriatric hip fractures, finding that when LDL < 2.31 mmol/L, the mortality risk decreased by $58\%$ with an LDL concentration increase of 1 mmol/L (HR = 0.42, $95\%$CI: 0.25–0.69; $$p \leq 0.0006$$); conversely, when LDL > 2.31 mmol/L, the mortality risk did not decrease with LDL change (HR = 1.06, $95\%$CI: 0.70–1.63; $$p \leq 0.7722$$). LDL < 2.31 mmol/L could be considered a predictor of the risk of increased mortality in clinical settings, with a lower LDL level being associated with higher mortality. The LDL results were unexpected, indicating that the lowest levels of LDL were associated with the highest risk of mortality following hip fractures.
At present, most related studies have focused on the association between lipid levels and osteoporosis risk, finding conflicting results. Some studies have suggested positive associations, some report no associations, and others report negative associations [30,31,32,33,34]. At the same time, studies on hip fractures are limited. Although a follow-up study showed that lipids and lipoproteins are associated with hip fracture risk in older adults, no relationship between LDL levels and the prognosis or all-cause mortality in geriatric hip fractures has been identified. Therefore, in this study, we explored the relationship between LDL levels and the prognosis of hip fractures in the elderly to provide further evidence of the relationship between LDL and geriatric hip fractures.
In addition to the linear relationship, we speculatively identified the existence of a curvilinear relationship through subgroup analysis and curve fitting. We were further able to find an inflection point in the curve. For this reason, the curve linear relationship is more appropriate to explain the relationship between LDL levels and geriatric hip fracture mortality.
A prior cohort study showed that the association between LDL levels and the risk of all-cause mortality was U-shaped, with low and high levels of LDL being associated with an increased risk of all-cause mortality. An LDL concentration of 3.6 mmol/L indicated the lowest risk of all-cause mortality. The association between low levels of LDL and an increased risk of all-cause mortality could be explained by reverse causation [35]. Debilitation and illness could decrease cholesterol levels, especially in elderly hospitalized patients, and comorbidities were more frequent in individuals with the lowest levels of LDL [36,37]. A survival analysis in China showed that a lower-admission LDL level (LDL < 2.755 mmol/L) was associated with an increased risk of long-term mortality in acute aortic dissection (HR = 3.287, $95\%$CI: 1.637–6.600, $$p \leq 0.001$$) [38].
The “cholesterol paradox” could also explain our results. This paradox states that low cholesterol is related to a worse prognosis and higher mortality. Several studies on cardiovascular diseases support this conclusion. For example, some studies on heart failure and acute myocardial infarction have shown that a lower baseline LDL increases the risk of patient mortality [39,40,41,42]. Physiologically, LDL is critical for the synthesis of cellular membranes and steroid hormones. Several factors may account for the “cholesterol paradox,” including a higher proportion of elderly patients, a higher proportion of baseline comorbidities, and malnutrition [43,44,45]. Some previous studies have shown a significantly negative association between LDL and bone mineral density (BMD), thereby increasing fracture incidence and all-cause mortality [46,47,48]. A cohort study of bone mineral density and 5-year mortality in end-stage renal disease patients previously showed that low total BMD were independent predictors of increased risk of all-cause mortality [49]. The same conclusion was drawn in several studies of hemodialysis patients [50,51]. Furthermore, low LDL levels have also been reported to be associated with decreased cognitive function, depression, and mood disorders, which could affect prognosis [52].
The strengths of our study include the following: First, as a prospective cohort study, we tried our best to avoid a loss to follow-up. Patients who could not be contacted were excluded from the study. Second, information on the cause of death for each individual was reported by the patients’ family members. Third, we adjusted for several confounders with an effect on mortality risk as well as LDL levels [53,54,55,56,57] to control for the majority of confounding factors.
However, this study has some limitations. First, loss to follow-up is unavoidable in a prospective cohort study, and this study is no exception. Therefore, we performed multiple telephone follow ups with those patients who could not be contacted initially to obtain patients’ outcome information. Second, this study was not able to determine the causal relationship between LDL levels and geriatric hip fracture prognosis; this will need to be confirmed in future studies. Third, our study population was derived only from western China; therefore, the conclusions may have geographical and ethnic limitations. Caution should be exercised when using this conclusion for other population groups.
In summary, we found that the preoperative LDL level was nonlinearly associated with mortality in elderly hip fracture patients, and a low LDL level was a risk indicator of mortality. Furthermore, an LDL concentration of 2.31 mmol/L could be considered a predictor cut-off for risk.
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|
---
title: Effect of Different Fiber Sources as Additives to Wet Food for Beagle Dogs
on Diet Acceptance, Digestibility, and Fecal Quality
authors:
- Amr Abd El-Wahab
- Jan Berend Lingens
- Julia Hankel
- Christian Visscher
- Cristina Ullrich
journal: Veterinary Sciences
year: 2023
pmcid: PMC9967778
doi: 10.3390/vetsci10020091
license: CC BY 4.0
---
# Effect of Different Fiber Sources as Additives to Wet Food for Beagle Dogs on Diet Acceptance, Digestibility, and Fecal Quality
## Abstract
### Simple Summary
Obesity in dogs is a common problem that can have a negative impact on the health and welfare of these animals. For weight reduction, commercial diets with fibrous ingredients are produced. Because of the added fiber, energy intake can be reduced, and the feeling of satiety can be promoted. Cellulose is a common dietary fiber used mainly in powdered form; however, other processing forms or additives are available. This work aimed to investigate the influences of various types of fibers on palatability, apparent total tract digestibility, and fecal quality in dogs. Four different diets were fed to eight dogs for 14 days each. In addition to a basic diet without added fiber (control group), three experimental diets with the following fiber sources were fed: powdered cellulose, granulated cellulose, and lignocellulose. The study showed that all fiber supplements led equally to a reduction in energy intake compared with the basal diet, without affecting palatability. Fecal quality was not negatively affected by the fiber supplements; only wet fecal excretion was higher in the fiber groups than in the control groups. This study demonstrated that other fiber sources, such as granulated cellulose or lignocellulose, can be used as an alternative to cellulose without limitations.
### Abstract
In order to enhance the health and welfare of obese dogs and to facilitate the required loss of body weight, commercial diets are produced with fibrous ingredients. Cellulose is a common dietary fiber used mainly in powdered form. However, other processing forms and fibers are available as fibrous additives. This work aimed to test the effects of different fiber sources on apparent total tract digestibility and fecal quality in dogs. Four diets were fed to eight dogs (experimental design: 4 × 4 Latin square) for a 14-day period each. In addition to a basal diet (CO), three experimental diets varying in fiber sources were used: powdered cellulose (CE), granulated cellulose (GC), and lignocellulose (LC). Dogs fed the CO had lower crude fiber digestibility than those fed the other experimental diets ($p \leq 0.0033$). Dogs fed diets supplemented with fiber sources had lower gross energy digestibility (range: 76.2–$77.3\%$) compared with those fed the CO ($84.4\%$). In all groups, the fecal score (consistency and shape) ranged within the optimal values; solely wet fecal output was increased for the fiber groups compared with those on the CO. This study demonstrated that various sources of fiber such as GC and LC can be used as alternatives to CE without restrictions.
## 1. Introduction
In 2020, at least one pet was owned by about 88 million European households; approximately $24\%$ of these households owned dogs [1]. Most companion animals now live in close relationship with their families, and are perceived as part of them [2]. Pet owners now demand improved nutritional food standards be offered to their animals as a result of this change [3]. The globally growing number of obese pets supports this development (in 2007, $52\%$ and $55\%$ of dogs and cats, respectively, compared with 56 % and 60 %, respectively in 2017 [4]). The causes of obesity are known to be multifactorial [5,6,7]. Moreover, this disease has long-term consequences for animal health, such as orthopedic disease, cardiorespiratory disorders, and gastrointestinal disorders [5,6,7]. Various factors may promote/increase pet obesity risk, such as inappropriate feeding, insufficient exercise, genetics, age, sex, and health conditions [8,9,10]. Thus, preventing the occurrence of obesity through weight management is key to maintaining the health and well-being of companion animals.
In most cases, increased exercise, combined with a controlled intake of carefully prepared food, results in successful weight loss [11]. Additionally, when it comes to weight loss plans for pets, high-fiber meals are frequently regarded as the ideal choice [12,13,14]. Because of their benefits to animal nutrition and health (reducing calorie consumption, enhancing satiety, and maintaining gastrointestinal health), pet food producers have manufactured canine foods using a number of fiber sources over the years [12,13,15,16,17,18]. The gastrointestinal (GI) microbiome represents an ecosystem of organisms that play important symbiotic roles in digestion, metabolism, nutrient absorption, and immunomodulation. Pet foods with specific fiber formulations that activate and nourish the canine GI microbiome and encourage selective microbial fermentation of the fiber in the gut may be particularly useful among dogs with chronic diarrhea [19,20].
So far, cellulose is mostly used as a source of dietary fiber for diets targeting weight loss, i.e., diets that are reduced in calories [21,22,23]. When trees are used to make paper pulp, the component cellulose is created. Cellulose is poorly fermented [24] and can reduce dry matter (DM) digestibility as well as organic matter digestibility in dogs [25]. It also increases fecal output according to several studies [26,27,28,29]. Furthermore, the higher the concentration of added cellulose, the more the digestion of organic matter is impaired, and the more the fecal output elevates [21,30]. Despite the benefits of cellulose for caloric dilution, product performance, and animal health, pet food manufacturers are looking to other types of fiber due to the product’s increased costs and limited consumer appeal [3].
Lignocellulose is a known sustainable energy source [31]. Additionally, as it is a component of plant cell walls, it is one of the most abundant and biologically renewable biomasses on earth [31]. Therefore, lignocellulose is used to manufacture biofuel [31]. From fresh naturally dried wood, lignocellulosic cellulose is mechanically extracted through fibrillation [32]. It can also be offered to dogs to replace traditional sources of fiber; nevertheless, to the best of our knowledge, very rarely have studies been performed in pets. The effects of lignocellulose on piglets have been studied [33]. The chemical construction of lignocellulose significantly diverges from the cellulosic structure, suggesting that its effect on the gastrointestinal tract is different from that of cellulose. Although lignocellulose consists of cellulose, which is the main structure, other components such as hemicellulose, pectin, and lignin are embedded therein [34]. Due to these features, lignocellulose is predicted to be lowly to moderately fermentable in canine intestines [34].
Another important aspect of including dietary fiber in pet food is the possible negative impact on palatability. For example, in a study by Koppel et al. [ 23], the intake of the feed with added fiber (in this case, sugar cane fiber and wheat bran were used) was lower. The dogs preferred the control diet without the additional fiber. The scientific literature provides very limited information on the impact of fiber on pet food acceptability. Therefore, additional research on this subject has to be conducted. The purpose of the presented experimental setup was to test the extent to which various fiber sources had an influence on apparent total tract digestibility, fecal quality, as well as acceptance in beagles, and whether differences were detectable between the different fibers.
## 2.1. Experimental Design and Diet Production
The University of Veterinary Medicine Hannover, Foundation, Hannover, Germany provided eight healthy, intact female Beagle dogs for this study. The average body weight (BW) of the beagles was about 11.1 kg and their age was within a range of 2–4 years. Once a week, the dogs were weighed and assessed for body condition scores (9-point scale [35]) prior to being fed. The animals were kept separately in kennels measuring 4.00 × 2.05 m, at constant room temperature, with light provided for 12 h daily. The trial was conducted using a 4 × 4 Latin square experimental design, in which the eight dogs were divided into two groups of four dogs each. Thereafter, the diets were changed within each group so that each dog received each of the four tested foods. The animals were accustomed to the food for nine days (d), and then feces were collected for five days so that each animal's apparent nutrient digestibility and fecal scores could be determined. Except for collection days, the dogs were provided time for interaction with conspecifics outside the kennels. Contact with humans was provided daily for the entire duration of the trial. Dogs had access to fresh water ad libitum. To measure the daily water intake (taking into account the evaporated fraction), each dog was provided with a weighed container of sufficient size filled with fresh water. At the end of each day, the remaining amount of water was weighed and subtracted from the amount weighed in the morning. The amount of food received by the dogs was calculated using the equation for the daily energy requirements of adult dogs (0.45 MJ metabolizable energy × BW0.75/d) [36], and the diets consisted of the same nutrient content, except for the source of dietary fiber. The animals were fed once per day. The daily food intake of all dogs averaged at 649 ± 33 g of wet food. The amount of food offered and that remaining in the bowl was noted daily after each meal to determine the amount of food consumed. The base meal was a wet commercial diet (Royal Canin® Veterinary Diet Senior Consult Mature; ROYAL CANIN Tiernahrung GmbH & Co. KG, Cologne, Germany) supplied to the control group (CO). The other three experimental diets were made by adding three different fiber sources to the basic diet. The experimental fiber sources were powdered cellulose (JELUCEL, CE), granulated cellulose (GC), and lignocellulose (JELUVET, LC). The fiber sources were commercially purchased (JELU-WERK J. Ehrler GmbH & Co. KG, Rosenberg, Germany). The amount of each was also determined on the basis of BW and consisted of 2 g/kg. The average amount of fiber additive was about 22.2 ± 1.50 g.
## 2.2. Chemical Analysis
The chemical analysis of all samples was carried out in duplicate. Samples from each collection period were defrosted and mixed to obtain one pooled sample per week and experimental diet. In order to analyze the dried feed material, it was ground through a 1 mm sieve (Retsch ZM200, Haan, Germany). The Association of German Agricultural Analytical and Research Institutes e.V. (VDLUFA) [37] procedures were used to determine the nutrients in the diets and fecal samples (Table 1). To measure the calcium concentration, an atomic absorption spectrometer (Solaar M-Serie Atomic Absorption Spectometer, Cambridge, England) was used in accordance with the Association of Official Analytical Chemists (AOAC) [38], while the phosphorus level was photometrically measured (Spectrophotometer UV-1900 i, Schimadzu Corporation, Kyoto, Japan) using the vanadate molybdate method, as described by Gericke and Kurmies [39]. The metabolizable energy content of the diets was calculated, as recommended by the National Research Council [36], according to the following equation: (MJ/kg) = 0.01674 × crude protein + 0.03767 × crude fat + 0.1674 × nitrogen-free extract.
The procedure for the determination of total dietary fiber (TDF) was based on the methods of Lee et al. [ 40] and Prosky et al. [ 41]. Briefly, 1 g of the dried food sample was subjected to sequential enzymatic digestion by heat-stable α-amylase, protease, and amyloglucosidase. After filtering out the insoluble components, the soluble fiber was precipitated with ethanol after adding distilled water to the filtrate. To determine the TDF, the residue was filtered, dried, and weighed. The TDF value was corrected for protein and ash content.
## 2.3. Scores for Food Intake and Apparent Total Tract Digestibility
The food intake scoring (palatability and speed of food intake) was classified into three groups in accordance with Zahn [42]. Briefly, score 1 indicates the lowest level of acceptance, score 2 indicates a moderate level of acceptance, and score 3 indicates the highest level of acceptance. After the adaption phase (9 d), the collection phase began (for 5 d), during which the feces excreted daily were collected. Following the weighing of the fresh feces, a subsample of $10\%$ of the feces per animal per day was analyzed for DM content. Subsequently, the remaining fecal samples were stored at −20 °C. At the end of the study, the five-day fecal samples from each dog were thawed and homogenized for further analyses. The apparent total tract digestibility (%) was computed by multiplying ((food − feces)/food) by 100.
## 2.4. Fecal Scores
Fecal consistency scores were calculated using a five-point scale: 1 for extremely hard feces; 2 for solid, well-formed, 'optimum' feces; 3 for soft, still-forming feces; 4 for pasty, slushy feces; and 5 for watery diarrhea, in accordance with Moxham [43], as shown in Figure 1. The fecal form scoring system devised by Abd El-Wahab et al. [ 44] involves a four-point scale (where 1 represents an individual fecal mass; 2, strong constrictions at the ‘optimal’ fecal surface; 3, cracks at the fecal surface; and 4, shapelessness), which was used to describe the shape of feces.
## 2.5. Statistical Analysis
The statistical evaluation was carried out with Statistical Analysis System (SAS) Enterprise Guide 7.1 (SAS Institute Inc., Cary, NC, USA). Mean values, as well as the standard deviation (SD) of the mean, were computed for all parameters. A Shapiro–Wilk test for normal distribution was performed for continuous data, and normally distributed data were checked for significant differences with the parametric Ryan–Eino–Gabriel–Welsch test (one-way ANOVA). For non-normally distributed data, the nonparametric Kruskal–Wallis test was performed, followed by the non-parametric pairwise Wilcoxon two-sample test. The significance level was set at $p \leq 0.05.$
## 3. Results
During the entire time of the trial, the dogs showed good overall health status. Throughout the study, the BW of the dogs was comparable among the experimental groups ($p \leq 0.05$). During feed intake, high acceptance was observed, thus achieving a high score (range: 1.00–1.43; $$p \leq 0.3178$$), and no refusals were observed. Additionally, the water intake was comparable among the groups (range: 135–223 g; $$p \leq 0.6962$$). Moreover, the BW of the dogs remained unchanged throughout the trial (average 11.4 kg BW). Additionally, the BCS values were maintained (average body condition score: 4.88).
## 3.1. Apparent Nutrient Digestibility
The results of the apparent nutrient digestibility are shown in Table 2. No significant differences were observed for the apparent digestibility of crude ash, crude fat, and crude protein among the groups. The dogs fed the basic diet (CO) without supplementation showed significantly lower crude fiber digestibility (22.6 %) compared with the other groups. No significant differences were observed in the apparent digestibility of calcium, phosphorus, or magnesium among the three groups (Table 2). Additionally, the supplementation of various fiber sources resulted in significantly lower digestibility of gross energy (range: 76.2–$77.3\%$) among the dogs in comparison with those animals fed the nonsupplemented diet ($84.4\%$).
## 3.2. Fecal Quality
The fecal consistency scores (Table 3) did not differ among the groups (range: 2.02–2.25; $$p \leq 0.2670$$). Additionally, supplementing the basic diet with various fiber sources did not result in differences in the fecal form scores among the groups (range: 2.01–2.16; $$p \leq 0.5412$$). The quantity of daily wet feces was significantly affected by the addition of different fiber sources (range: 137–143 g/d) compared with that of dogs fed the nonsupplemented basic diet (99.1 g/d). No significant differences were noted in the fecal DM content among the test groups (range: 31.4–35.6 %; $$p \leq 0.0786$$).
## 4. Discussion
In the present trial, the fiber digestibility was significantly affected by the fiber quantity, irrespective of its source. Several studies have demonstrated that the amount and quality of different fiber sources can influence the digestibility of nutrients [16,25,45,46]. This fact was demonstrated in the present work by the increased excretion of undigested and unfermented matter.
Similar protein digestion in dogs was not affected by a change in the supplemented fiber (beet pulp or corn fiber,) or the amount of fiber used studies were performed in other dog breeds and other countries [47]. In a study conducted by Guevara et al. [ 48], (TDF $8.40\%$ to $10.2\%$). In the present study and in a study by Kienzle et al. [ 49], it was found that increasing dietary fiber content, more undigested organic material was excreted by the animals. Nevertheless, not all studies could confirm such an effect of dietary fiber sources [50]. In contrast to our results, in a study by Beloshapka et al. [ 51], the digestibility of crude protein decreased as total dietary fiber consumption increased in dogs. In their study, resistible corn starch, which is fermentable by gut microbiota, was used in increasing concentrations ($0\%$ to $4\%$). However, the authors did not attribute the reduced protein digestibility to the increased fiber content, but suggested that it could be related to an increase in microbial activity and fecal nitrogen excretion.
In the current work, $2\%$ of each of the various dietary fibers was added to commercial food. The idea behind the use of equal amounts of fiber was achieving a uniformly elevated dietary fiber level and ensuring as equal a composition as possible of the remaining ingredients of the basic feed. Therefore, our hypothesis was that the type of dietary fiber was the only factor contributing to the findings, not differences resulting from shifts in the proportion of other dietary components. The commercial diets used for weight maintenance and weight loss most commonly contain high levels of dietary fiber. Consequently, it was necessary to simulate these diets through the addition of $2\%$ of the respective fibers that were to be tested. This percentage has also been used in previous studies demonstrating that nutrient digestibility is thereby not reduced to an undesirable extent and that positive effects on fecal quality, among others, can already be observed [49,52]. In the present study, no differences in food intake occurred relative to the added fibers (an average of 649 g of the experimental diet was consumed). Refusal of feed intake did not occur over the course of the entire trial.
A key factor to consider when assessing dog foods is fecal quality. This study found that neither the addition of fiber alone nor the kind of fiber element to the diet had any effect on the fecal consistency score (average: 2.16). Similarly, there was no difference in the fecal shape scores between dogs that received the control food and those in the fiber-added groups. Additionally, there were no differences among the groups given various fiber sources (average: 2.10). Dogs supplied with fiber-rich diets had significantly higher wet fecal output (average: 140 g/d), regardless of the fiber source, than those offered a nonsupplemented diet (99.1 g/d). Nevertheless, the fecal DM did not follow the same trend as wet fecal output and remained without differences at a range of 31.4–$35.6\%$.
The DM content in the feces of pets can be significantly influenced by numerous different factors. One factor, for example, is the fermentation activity of fibers. The fermentation activity and the moisture content of dog feces have been shown to have strong positive associations [16,26,53]. This finding might be connected to fiber's ability to add bulk, and it seems to be most strongly connected to sources of insoluble fiber that are both poorly fermentable and have a high capacity to bind water [26].
Short-chain fatty acids are often produced in greater quantities by the gastrointestinal microbial fermentation of soluble fiber (mainly acetate, propionate, and butyrate). Pigs’ digestive tracts absorb more water due to short-chain fatty acids. However, the overdosing of butyrate might induce an osmotic effect, resulting in increased fecal moisture content in pigs [54]. Guevara et al. [ 48] offered food to dogs containing beet pulp and different sources of corn fiber. They found a decrease in fecal DM when beet pulp (moderately fermentable fiber) was added to the diet compared with when the tested corn fiber was added. While the TDF content of these fiber sources was similar, the soluble fiber content of the corn fiber was much lower than that of the beet pulp [48], thereby confirming the idea that increasing the amount of soluble fiber in the diet, and thus in the intestinal lumen, may alter the nature of water flow and decrease the DM content of feces.
Moreover, the water intake of animals may be reduced through the addition of dietary fibers, due to their different water-binding capacities. Thus, in addition to the reduced water intake, as well as the aforementioned alteration in water flow, the dry matter of the feces may be reduced. In their study, Silvio et al. [ 46] used experimental diets for dogs with varying proportions of cellulose (as an insoluble fiber) and pectin (as a soluble fiber). Then, digestibility was measured at the ileum and total tract. They reported a decrease in fecal DM percentage, as the pectin content of the diet increased at the expense of that of the cellulose. This supports the hypothesis that the fermentation of soluble fibers could increase fecal water content.
Because the fiber used in the present study was insoluble [46], the DM content in the feces was not affected. This is explained by the low water-binding capacity of cellulose [54]. Lignocellulose is also considered an insoluble fiber, and, like cellulose, has a low water-binding capacity [33]. Therefore, the DM content in the feces was not negatively influenced either. Moreover, in the present study, the amount of wet fecal mass per day was significantly affected by the content of the dietary fiber. In agreement with our data, dietary fiber is known to affect the volume of fecal excretion negatively [26,28,29].
## 5. Conclusions
Supplementing these three fiber sources did not affect the fecal consistency and/or form scores. Independent of the fiber source, increasing the amount of dietary fiber resulted in a significant increase in the wet fecal output. In view of the results of this study, lignocellulose can be used as an alternative to cellulose as a fiber source in wet dog food. As lignocellulose reduces gross energy digestibility to the same extent as cellulose, it can also be used in dietary feed for overweight dogs. When feeding the regular amount of feed, less energy is utilized when using these fibers.
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|
---
title: Stabilization Activity of Kelp Extract in Ethylene–Propylene Rubber as Safe
Packaging Material
authors:
- Traian Zaharescu
journal: Polymers
year: 2023
pmcid: PMC9967782
doi: 10.3390/polym15040977
license: CC BY 4.0
---
# Stabilization Activity of Kelp Extract in Ethylene–Propylene Rubber as Safe Packaging Material
## Abstract
This paper presents the stabilization effects of the solid extract of kelp (Ascophyllum nodosum) on an engineering elastomer, ethylene–propylene copolymer (EPR), which may be used as packaging material. Progressive increase in additive loadings (0.5, 1, and 2 phr) increases the oxidation induction time for thermally aged rubber at 190 °C from 10 min to 30 min for pristine material and modified polymer by adding 2 phr protection powder. When the studied polymer is γ-irradiated at 50 and 100 kGy, the onset oxidation temperatures increase as a result of blocking the oxidation reactivity of free radicals. The stabilization effect occurs through the activity of alginic acid, which is one of the main active components associated with alginates. The accelerated degradation caused by γ-exposure advances more slowly when the kelp extract is present. The OOT value for the oxidation of EPR samples increases from 130 °C to 165 °C after the γ-irradiation of pristine and modified (2 phr of kelp powder) EPR, respectively. The altered oxidation state of EPR samples by the action of γ-rays in saline serum is faster in neat polymer than in stabilized material. When the probes are placed in physiological serum and irradiated at 25 kGy, the OOT value for neat EPR (145 °C) is much lower than the homologous value for the polymer samples protected by kelp extract (153 °C for the concentration of 0.5 phr, 166 °C for the concentration of 1 phr, and 185 °C for the concentration of 2 phr).
## 1. Introduction
The presence of an efficient stabilization compound is an essential condition for the safety applications of long-life materials with special reference to packaging materials, which are always subjected to stressing factors such as heat and light. Differences in the protection activities of various antioxidants relate to their efficiencies as well as the manner through which they are produced. Material durability is highly related to structural stability, which depends on the characteristics of raw products and the blending formulation. Though synthesis compounds such as hindered phenols or amines are appropriately used for the preservation of stability under hazardous conditions [1,2], they are converted into quinone structures, which poisonous to the human body, when they act in oxidizing polymers [3]. Attempts to diminish oxidation rate are generally based on the substitution of mobile protons from existing hydroxyl moieties in the stabilizing molecules [4], whose mobility determines whether lifetime is extended. An important factor that mitigates polymer oxidation is the material’s strength against oxidative ageing [5], when the local concentration of free radicals, the intermediates that sustain the propagation of degradation, does not reach a critical amount [6].
The natural antioxidants that result from the application of extraction procedures on herbs and plants have been increasingly used, particularly in cases where their use is compatible with human factors [7]. The chain-breaking action of natural antioxidants operates at various temperatures [8], when fragmentation moieties are subjected to the attack of oxygen that diffuses inside the polymer bulk. Fortunately, they may be associated with other types of stabilizers, with which synergistic effects are obtained [9]. Several interesting applications of these types of stability improvement are reported [10,11,12,13,14], illustrating their largely assumed potential.
The healthy contributions of phytocompounds to the quality of food is generally accepted either for preservation of properties [15] or for packaging materials [16]. The extension of dietary applications of algal extracts covers a large area of interest, where the use of algal powders prevents oxidation through their various classes of compounds: polyphenols, phlorotannins, carotenoids, polysaccharides, and polyunsaturated fatty acids [17]. The most attractive effects of natural antioxidants are revealed by their dietary use for several diseases [18,19,20].
Current investigations into the curative properties of natural extracts have inspired detailed examinations of the antioxidant activities of algal extracts [21]. Based on their active components with outstanding antioxidant features, algal extracts have become a main source of oxidation protectors in various areas: medicine [22], pharmaceutics [23], cosmetics [24], nutritional sources [25], ecological packaging [26], and many others. Starting from convenient production technologies [27], algal extracts are suitable materials for anti-ageing protectors in plastics according to some previous assays [28].
The presence of antioxidants in *Ascophyllum nodosum* as 2605.9 mg GAE/100 g of brown seaweed powder [29] shows the enormous potential of these macroalgae to provide healthy extraction materials for the production of ecological plastics. From the group of brown seaweeds, *Ascophyllum nodosum* has the highest antioxidant content [30], which explains the large interest in medicine, food, and cosmetic industries in this seaweed. The abundance of phenolic compounds (2605.89 ± 192.97 mg gallic acid equivalents/100 g dm) in this algal extract [31] recommends it as a pertinent and attractive stabilizer for many applications, especially where it is compatible with needs for natural bioactive additives.
The wide spread of *Ascophyllum nodosum* in different types of forests [32] and the ease of harvesting these seaweeds [33] indicate commercial availability and ready access [34,35]. The brown seaweeds, including Ascophyllum nodosum, contain preponderantly alginic acid and alginates [36] as active elements having antioxidant properties [37]. Active components existing in the extracts act successfully as biostimulators [38] because of their contributions as growing agents and antioxidant preventers.
The alginic acid and alginates indicated in the structure presented in Figure 1 belong to the natural polysaccharide class, which exists in the majority of spice and herb extracts in various proportions. The large variety of alginate structures offers support for the wide scale of antioxidant capacities, where their compositions (mannuronic/guluronic (M/G) ratio) vary [39].
The extension of functional features of alginic acid and alginates on the antioxidant range is characterized by the retardation of peroxidation of lipids [40]. The abundance of stabilization elements such as carotenoids in marine resources [29], bioactive compounds such as catechins [41], and seaweed phenolic antioxidants [42] are significant indications for potential uses of seaweed in anti-ageing products. Brown seaweeds are sources of alginate-based compositions available for protective applications [43,44,45]. The variety of preparation procedures starting from macroalgae [46,47,48,49] is an open door for the usage of alginates as efficient protectors against oxidation in polymer composites [28,50,51]. The stability of alginic acid and alginates as feedstocks for composites is explained by their ability to retain free molecular fragments [52,53,54]. Seaweeds, which are very rich in polysaccharides and antioxidants [55], may be considered as a potential source of stabilizers if the polymers are involved in ecological applications or in health care development.
The destructive action of high energy radiation is described by the superunitary value of radiochemical scission yield (G(s) = 1.3) for Na-alginates [56], which describes the degradation trend of this solid type of polysaccharide. This procedure of radiation processing is appropriate for the conversion of numerous polysaccharides into useful products as fertilizers [57], water absorbers [58], hydrogels for drug delivery [59], and high-yield biogas production [60].
However, structures belonging to the polysaccharide class of polymers show the formation of—COOH and—OH functions that are active during the protection of host materials against oxidation [61]. Proof of radiation resistance associated with the preservation of antioxidant capacity of algal extracts under γ-irradiation is the satisfactory protection activity of algal extracts added in polymers [62]. The γ-radiolysis of various alginates produces blends of polyguluronic acid and polymannuronic acid fractions in different mixing proportions, which may be identified by FTIR analysis [63]. These decomposition components are largely used in individual antioxidant protection [63,64], the safe drug delivery of polymers [65], and the crosslinking of alginic acid films [66]. The use of radiolysis mechanism in the processing of alginates [67] shows antioxidant features [68] that support the continuous protection activity in the irradiated EPR samples. This situation is similar to polymer modification by rosemary extracts [69], which is very efficient due to the antioxidant activities of descendants of rosmarinic [70] and carnosic [71] acids. A comparison study on the stabilization efficiency of natural extracts in protecting food packaging materials was published [72].
This paper presents a reliable procedure for the stability improvement of polymer materials by means of algal extracts. Samples consisting of ethylene–propylene copolymer are modified by various loadings of *Ascophyllum nodosum* extract powder. The protection effect offered by this additive is an example for any other packing material, whose use may be a reliable option for ecological products.
## 2. Materials and Methods
The studied polymeric material, ethylene–propylene copolymer (EPR), is an elastomer produced by ARPECHIM (Pitesti, Romania) as TERPIT C. The pristine rubber has an ethylene/propylene ratio of 3:1. Algal extract from kelp (Ascophyllum nodosum) harvested between May and November in Canada was available from the market by Z-Company (Eindhoven, the Netherlands).
The polymer samples were prepared by the dissolution of elastomer in chloroform, whose evaporation at room temperature leaves unchanged the polymer film. After the filtration of this primary solution, aliquots of 10 mL were transferred into three other separate glass flasks, where appropriate amounts of algal powder were put in for the preparation of three other second set solutions containing 0.5, 1, and 2 phr of additive. These last solutions were the sample sources from which 100 mL of liquid was poured into previously weighted aluminum round pans. After gentle drying on the table at room temperature, thin films were obtained, whose weights are placed around 3 mg.
The γ-exposure of probes was accomplished in air at room temperature in a specialized machine, Ob Servo Sanguis type irradiation equipment (Budapest, Hungary) provided with 60Co source at four total doses of 0, 25, 50, and 100 kGy by permanent rotation of the processing can. Gamma irradiation of polymer samples was carried out at a dose rate of 0.5 kGy h−1, which is a convenient value for the attendance of oxidative degradation. Occasionally, for the study of radiation effects on algal extract, two doses of 12.5 kGy and 75 kGy were also applied. Both control and modified samples were investigated immediately after the end of each irradiation, avoiding any structural modification due to the decay of short-life radicals.
Chemiluminescence (CL) measurements are considered the most appropriate analytical procedure through which the induced effects of γ-radiolysis, a convenient accelerated procedure, may be pertinently controlled. The CL determinations were carried out with LUMIPOL 3 (Institute of Polymers, Slovak Academy of Sciences, Bratislava, Slovakia), when the evaluation of degradation could be performed with a low temperature error (±0.5 °C). This extremely sensitive method for the investigation [73] of structural modifications occurring in the studied polymer matrices is based on photon emission through the de-excitation of carbonyl compounds when they are formed by the reactions of free radicals with molecular oxygen [74]. For the isothermal CL measurements, three values of temperatures (160 °C, 170 °C, and 180 °C) were selected, as they were appropriate investigation conditions for their convenient oxidation rates. For nonisothermal CL assay a suitable heating rate, 10 °C min−1, was preferred. A similar measurement parameter (10 °C min−1) was applied when the stability evaluation was conducted by heating specimens immersed in water and physiological serum at 80 °C for 5 h and 10 h. The confidence of CL values is very high because the average differences between the analogous values for emission intensities are ±50 Hz. This allows for a very low measurement error of less than 10−$2\%$.
## 3. Results
Evaluation of the stabilization efficiency of the studied material, the solid extract of brown microalgae Ascophyllum nodosum, is highly related its stability. During γ-radiolysis of the powder, the degradation of active components in algal extract takes place through depolymerization [75] that leads to a gelation of aqueous solutions or intramolecular fragmentation due to differences in the energies of the bonds. Unfortunately, the structural modifications induced by accelerated degradation induced by γ-rays were not reported and, consequently, any comparison is not possible. However, in Figure 2, some fundamental features related to modifications in the chemistry of kelp powder may be revealed:−The thermal or radiation degradation occurring in polymer matrix progresses through the fragmentation of molecules. These scissions are preferentially produced in EPR in polypropylene units, because the bonds of tertiary carbon atoms have a lower energy. The radicals may be subjected to oxidation through their reactions with diffused oxygen or they participate in crosslinking when the recombination reforms the polymer structure and increases the stability of the material. The presence of any antioxidant turns the evolution of the radicals into stabilization. Though there is a difference between thermal degradation and radioinduced degradation based on the local concentration of radicals, both processes have similar mechanisms based on the propagation stage as the median step [76]. In the presence of antioxidants, the competition between oxidation as degradation process and crosslinking as the improvement route is clearly gained by the latter, because the decay of radicals is achieved by their recombination. Thus, the stabilized material is characterized by the relevant contribution of antioxidant to the delay of oxidation by the protection of radicals against their conversion into oxygenated structures.−At low irradiation dose (12.5 kGy), early degradation starts, which is proved by the intensity peak at 75 °C. This photon emission would be caused by the molecular fragmentation into large moieties. This maximum will be never noticed in the other CL spectra obtained on the algal extract subjected to intensive damaging action of γ-radiation. This assumption is valid as sustained by detailed investigations of radiation effects on polysaccharides [77,78]. Additionally, this dose range is suitable for the preparation of hydrogels starting from polysaccharides, when the crosslinking of processed material is certainly reached by the further reactions of these intermediates [79].−The presence of permanent maximum, which appeared at 165 °C, indicates the vulnerability of components upon the energy transfer occurring on the radiation tracks. The evolution of radiochemical degradation is described by the increase in the values of emission intensities, which are the consequence of scission in the structure of monosaccharide units. This process always occurs in all similar molecules, whose radiation stabilities depend on molecular construction [80].−The common joint point may define a certain limit in the reactivity of fragments with respect to oxidation when degradation is guided at high temperatures.
Analysis of families of CL isothermal spectra (Figure 3) demonstrates the capacity of algal extracts from *Ascophyllum nodosum* to extend service life of the studied elastomeric material. The increase of additive concentration in the studied compositions leads to an extension of degradation periods, where the propagation step becomes longer (Figure 3). If the loadings of *Ascophyllum nodosum* extract are greater than 1 phr, the oxidation rates for these samples are extremely low at 160 °C. This means that the operation of items manufactured as modified EPR products is safe for a very long period. The delay of oxidation is indubitably conditioned by the scavenging activities of active components on protection material, especially alginic acid. The long degradation periods are demonstrative proof of improved stability when packaging materials are left in inappropriate conditions such as sunlight and accidental heating. The contribution of algal additive is relevant when its concentration is 2 phr and the degradation temperature does not exceed 100 °C. This situation scarcely occurs. Thus, the presence of algal extract is a guaranteed formulation for long-life products, which operate under ageing conditions.
In considering the possibilities offered by the presence of antioxidants in the formulation of polymer materials, it is easy to identify that the algal extracts are active materials and that their contribution to the extension of durability is related to protection against oxidation by the scavenging of radicals [81]. Relevant components in extracts of *Ascophyllum nodosum* [82] are possible antioxidants with different stabilization efficiencies. Oxidation as a harmful process can be avoided by the addition of appropriate compounds, such as seaweed powder extracts [83]. Their scavenging activities are influenced by the complex composition through which a synergetic effect occurs. This assessment offers the possibility to connect their efficiencies with the functional performances of materials where they are active. Material lifespan is influenced by the initiation of inactivation of radical reactions by seaweed extracts; long-term stability is guaranteed by the antioxidant capacity in natural environments [84].
The γ-irradiation of EPR samples produces differences between pristine material and the polymer improved by algal extract (Figure 4). The degradation periods for EPR in the presence of algal powder are much longer and the emission intensities for the three formulations are significantly reduced. This benefit is evidence of the contribution of oxidation protection through which polymer support may gain an extended durability.
The nonisothermal spectra that depict the development of oxidation in the EPR samples (Figure 4) reveal the stabilization effects of algal extract on the host polymer material under γ-irradiation as well as in the pristine samples. The anti-ageing efficiency that increases as the concentration of additive is increased illustrates the significance of this kind of material in the formulation of packaging materials subjected to accelerating damage in different thermal hazardous environments.
Radiolysis action modifies the oxidation states of materials to quicker degradation when the initiation of oxidation appears earlier under higher exposure of γ-dose. As stated earlier [85], polysaccharides extracts from seaweed are intelligent protectors on packaging materials, because they induce the extension of stability due to the descendants, namely 1,4-β-D-mannuronic acid and 1,4-α-L-guluronic acid, whose sequential distribution may influence the amplitudes of activities.
The modification of temperature values for the start of oxidation is correlated with the exposure dose because the molecular breaking generates not only polymeric forms of descendants (polymannuronic acid and polyguluronic acid), but also monomers which are able to continue the protection action by means of mobile protons of hydroxyl moieties. Because alginic acid is a hydrophobic polysaccharide and the antioxidant activity is determined by the active hydroxyls [86], the width of application ranges may be enlarged by the derivation under the action of γ-radiation according with the results presented in Figure 5.
The inclusion of alginic acid or alginates in the composition of packaging polymer materials allows the implementation of radiation sterilization without affecting the material’s qualities. The radiation processing of these compounds causes structural rearrangements, which may offer a certain level of protection [87,88].
The degradation of EPR/*Ascophyllum nodosum* powder samples in water and physiological serum (Figure 6) is subjected to the effects of interference with water. The water dipoles act as hydrolysis agent [89] as well as attack agent in thermal [90] and radiation [91] environments. The degradation rates present greater values for the modified polymer, while the neat EPR resist for longer periods in aqueous solutions. At the same time, the CL spectra recorded on EPR/algal extract samples does not differ which suggests that the concentration of stabilizer does not significantly affect progress in the oxidation of polymer substrate.
## 4. Discussion
The stability of materials, a fundamental feature in service periods, is influenced by the presence of a compound acting as a degradation protector. As it was previously demonstrated, inorganic structures are able to play the role of anti-ageing factor [92,93,94]. Interest in the extension of the life of materials using ecological products has focused on algal extracts, whose efficiency is one of the main factors in the evaluation of its utility [95]. The significant role of additives for protection against oxidation is exemplified when the local concentration of free radicals reaches a certain level from which the oxidation rate exceeds the accumulation rate [95].
The radiolysis effects on the studied extract of *Ascophyllum nodosum* are characterized by the increase in the oxidation state of processed material due to the scission of molecules. If the molecules of polysaccharide are split as the first degradation step, this process generates radicals available for oxidation [96]. Thus, the first peak at 80 °C appears at low γ-exposure dose (Figure 2). Once the fragments are generated, the rate of their oxidation becomes the dominant process, when the accumulation of peroxyl radicals advances sharply (Figure 2). At the dose exceeding 50 kGy, both processes take place simultaneously. The overlapping of these maxima on the curve recorded for the sample irradiated at 75 kGy is proof for the development of these processes at the same time. However, the descendants of molecular splitting (mannuronic acid and guluronic acid) present antioxidant features which were already demonstrated [97].
The progress of oxidation in the polymer bulk is conditioned by the activity of the used additive, which acts as any hindered phenolic structures [4] (Figure 7). The Bolland–Gee mechanism [66] that describes the oxidation of the elastomer sample explains the sigmoidal shape of isothermal CL spectra. The protection action of added algal extraction is present at the propagation stage of degradation, when the free radicals generated by scissions are tightly scavenged by the alginic acid or its descendants. The supplementary activities of mannuronic and guluronic acids are also related to the extended stabilization periods when the prolongation of the propagation stage of oxidative degradation over 400 min is at a striking discrepancy with the behavior of pristine polymer.
The sustained antioxidant activity of neat and irradiated extract of *Ascophyllum nodosum* is also beneficial for stability when materials are stored, or they are used for food preservation. The predicted stability from the contribution of *Ascophyllum nodosum* powder corresponds to the activity of hydroxyls existing in the structure of the additive [98,99]. Antioxidant responses to harmful conditions are related to the characteristics of polyphenols, whose mobile protons are substituted by free radicals (Figure 7) [100].
The nonisothermal chemiluminescence assays on the antioxidant contributions of the solid extract from *Ascophyllum nodosum* reveal its contribution as the inhibitor of oxidation in the solid polymer probes subjected to the destructive action of γ-radiation in air (Figure 5). The effects are more visible on the high temperature range over 150 °C, when thermal movement is accelerated and the probability of jointing radicals onto active phenol hydroxyls is higher. The best results were obtained when the additive concentration was 2 phr. The existence of a prominent peak at 220 °C demonstrates the formation of structured peroxyls after a longer degradation period, and their decay takes place much later. The availability of active descendant fragments is proved by the increase in their abundance due to the radiation’s damaging effects on macromolecular components [64]. The promising results obtained in the presence of algal extract compose the protective picture by which phenolic structures are involved via the formation of methoxy moieties after the scavenging free radicals.
Unfortunately, the dissimilar effect of algal extracts is noticed in aqueous environments, distilled water, and physiological serum. The nonisothermal CL curves recorded on the EPR specimens modified with *Ascophyllum nodosum* powder are placed under the curve for pristine material. This feature would be ascribed to hydrolysis of the additive, which diminishes protection capacity. However, the lack of contrary effect on the low temperature range up to 100 °C is a positive behavior through which the active configurations are available for moderate stabilization.
## 5. Conclusions
This paper presents relevant results through which the application of ethylene–propylene elastomer may be used as a safe material for the preservation and handling of food. Stability investigation through isothermal and nonisothermal chemiluminescence proves the good protective activity of *Ascophyllum nodosum* powder. The values of kinetic parameters, namely oxidation induction times and onset oxidation temperature, are appropriate evidence when the polymer is subjected to accelerated degradation by γ-irradiation. While the increase of induction period is revealed, the increase in the temperature when the effective oxidation starts indicates the significant anti-ageing activity of the additive. The propagation of oxidative degradation is delayed by the replacement of protons existing in the alginic acid, the main active component of *Ascophyllum nodosum* extract. The stability testing achieved by radiation processing provides strong proof for the useful contribution of algal extracts to the extension of material durability in wide areas of application. An interesting opportunity for the use of *Ascophyllum nodosum* powder in the formulation of polymer materials is its addition to packaging sheets or beverage bottles.
The extension of application ranges for algal extracts opens numerous doors through which nature offers suitable solutions for a healthy life and convenient and economical versions of product manufacturing.
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|
---
title: 'Revised Harris–Benedict Equation: New Human Resting Metabolic Rate Equation'
authors:
- Eleni Pavlidou
- Sousana K. Papadopoulou
- Kyriakos Seroglou
- Constantinos Giaginis
journal: Metabolites
year: 2023
pmcid: PMC9967803
doi: 10.3390/metabo13020189
license: CC BY 4.0
---
# Revised Harris–Benedict Equation: New Human Resting Metabolic Rate Equation
## Abstract
This paper contains a revision of the Harris–Benedict equations through the development and validation of new equations for the estimation of resting metabolic rate (RMR) in normal, overweight, and obese adult subjects, taking into account the same anthropometric parameters. A total of 722 adult Caucasian subjects were enrolled in this analysis. After taking a detailed medical history, the study enrolled non-hospitalized subjects with medically and nutritionally controlled diseases such as diabetes mellitus, cardiovascular disease, and thyroid disease, excluding subjects with active infections and pregnant or lactating women. Measurement of somatometric characteristics and indirect calorimetry were performed. The values obtained from RMR measurement were compared with the values of the new equations and the Harris–Benedict, Mifflin–St Jeor, FAO/WHO/UNU, and Owen equations. New predictive RMR equations were developed using age, body weight, height, and sex parameters. RMR males: (9.65 × weight in kg) + (573 × height in m) − (5.08 × age in years) + 260; RMR females: (7.38 × weight in kg) + (607 × height in m) − (2.31 × age in years) + 43; RMR males: (4.38 × weight in pounds) + (14.55 × height in inches) − (5.08 × age in years) + 260; RMR females: (3.35 × weight in pounds) + (15.42 × height in inches) − (2.31 × age in years) + 43. The accuracy of the new equations was tested in the test group in both groups, in accordance with the resting metabolic rate measurements. The new equations showed more accurate results than the other equations, with the equation for men (R-squared: 0.95) showing better prediction than the equation for women (R-squared: 0.86). The new equations showed good accuracy at both group and individual levels, and better reliability compared to other equations using the same anthropometric variables as predictors of RMR. The new equations were created under modern obesogenic conditions, and do not exclude individuals with regulated (dietary or pharmacological) Westernized diseases (e.g., cardiovascular disease, diabetes, and thyroid disease).
## 1. Introduction
Metabolism refers to the set of biochemical reactions that take place in the cells of living organisms. Basic metabolism includes all the biochemical processes in the organism involved in the production and release of energy to sustain life during a period of complete rest [1].
Basal metabolic rate (BMR) represents the amount of energy in kilocalories used over a given period of time (e.g., 24 h) to perform the most basic functions of the body. BMR can be accurately assigned under very restrictive conditions of a laboratory or hospital environment: thermally neutral, in the post-absorptive stage, after sleep, in an awake state, during complete rest, during physical and mental calm, and avoiding stimulation of the sympathetic nervous system. It can be measured by direct calorimetry (DC) and more often by indirect calorimetry (IC). BMR is the lowest metabolic rate after the sleep metabolic rate. It represents 60 to $75\%$ of daily calorie expenditure for most people and decreases after the second decade of life by 1–$2\%$ per decade, mainly due to changes in metabolically active muscle tissue [2].
Resting metabolic rate (RMR) represents the amount of energy the body needs to function while at rest. The measurement to determine RMR differs from the measurement of BMR in that it does not need to be performed before getting out of bed, as it involves low-effort daily activities such as using the bathroom, dressing, gentle movement, etc., in addition to basic body functions. It is usually measured by indirect calorimetry, in the morning before the first meal and after abstinence from factors that may affect the metabolic rate such as exercise, caffeine and alcohol consumption, and smoking. In the modern sedentary lifestyle, RMR accounts for most of the energy expended during the day. RMR is slightly higher by about $10\%$ than BMR due to the contribution of low energy expenditure [3].
Resting energy expenditure (REE) represents the energy expended by humans in an awake, resting, interstitial state. It is considered by the American Research Council to be an equivalent term to RMR and is used to calculate resting energy processes [4]. In the international literature, the terms BMR, RMR, and REE are usually confused and applied for exactly the same purpose. Thus, the term REE is used by the Harris–Benedict [5,6], Roza and Shizgal [7], and Mifflin–St Jeor [8] equations; the term BMR by the FAO/WHO/UNU equations [9]; and the term RMR by the OWEN equations [10].
Both direct and indirect calorimetry measurements that can provide an accurate measurement of metabolic rate are expensive and require trained personnel, special site conditions, and subject preparation. In this aspect, mathematical formulas have been developed for the indirect determination of RMR, usually based on parameters of healthy adults, such as body weight, height, age, and sex [5,6,7,8,9,10,11,12]. In recent years, in the context of adapting prediction equations to specialized categories of individuals and situations, several prediction equations have been developed that are specific to particular diseases [13,14,15,16,17], ethnicity [18,19], special categories such as athletes [20,21], overweight and obese people [22,23], children [24], and people after middle age [25]. Several attempts to create new RMR prediction equations using individual characteristics, such as free fat mass (FFM), have emerged from time to time but they require the use of body composition analysis devices [26]. Some of the widely used prediction equations are listed below.
## 1.1.1. Harris–Benedict
Based on the literature, the Harris–Benedict (H–B) equations [5,6] constitute the principle of creating the equations (Harris–Benedict principle) without the help of modern computers. They were published more than 100 years ago (1918 and 1919) and remain still the most frequently used equations in daily practice. These equations were based on 239 subjects (136 men and 108 women), aged 16–63 years (Table 1). The equation for males had a coefficient of R2 = 0.64 and the equation for females had a sample correlation coefficient of R2 = 0.36.
## 1.1.2. Roza and Shizgal
The first revision of the H–B equations was carried out 65 years later by Roza and Shizgal [1984], based on a sample that was older, larger by 98 persons ($$n = 337$$), and almost equally divided between the sexes (168 men and 169 women). These equations (Table 1) showed stronger correlation coefficients (R2 = 0.77 and R2 = 0.68 for men and women, respectively) for both sexes than the H–B equations [7].
## 1.1.3. Mifflin–St Jeor
The second revision/simplification of the H–B equations was carried out 71 years later [1990] by Mifflin–StJeor, based on a sample that was wider in age (19–78 years) and larger by 259 individuals ($$n = 498$$), of which 251 were men and 247 were women (Table 1). These equations showed a common coefficient R2 = 0.71 for both males and females [8].
## 1.1.4. FAO/WHO/UNU Equations
The Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU) equations were developed in 1985 (Table 1) using equations derived mainly from studies in Western Europe and North America [12]; almost half of the data came from studies between the late 1930s and early 1940s involving Italian men with relatively high BMR values. These equations were based on a large population sample ($$n = 11000$$) and categorized into six age groups (<3, 3–10, 10–18, 18–30, 30–60, and >60 years), with R2 ranging between 0.60–0.97 for men and 0.70–0.97 for women [9].
## 1.1.5. Owen
Owen, in two consecutive years, created new, simpler equations (Table 1) using body weight as the only parameter. In 1986, he presented the equation for women with a coefficient $r = 0.74$, which was based on a sample of 44 women aged 18–65 y whose body weight ranged between 43 and 171 kg [10]. A year later [1987], he presented the equation for men with a coefficient similar (R2 = 0.56) to that for women (R2 = 0.54), which was based on a sample of 60 men aged 18–82 years and weighing 60–171 kg [11].
The aforementioned equations, and other more specific equations used extensively for body weight management, have been evaluated for their validity and reliability by a plethora of studies, which indicates a tendency to overestimate or underestimate REE compared with indirect calorimetry [27,28].
The changes that have occurred in people’s lifestyles, diets, work, and physical activity since the first equations were created have resulted in the diversification of somatometric characteristics due to a considerable increase in overweight/obesity, which, based on World Health Organization data, has almost tripled between 1975 and 2016.
The global prevalence of obesity between 1975 and 2016 has almost tripled [29] and the proportion of obesity-related deaths from 1990 to 2017 has increased by $8\%$ [30]. This upward trend in the global obesity rate will continue, as according to the fourth World Atlas of Obesity, between 2010, 2025, and 2030 it will rise from$11.4\%$ to $16.1\%$ to $17.5\%$, respectively [31]. Studies from various European countries support this steady increase in the prevalence of overweight/obesity, which they attribute to a combination of unhealthy diets and physical inactivity, unhealthy body weight in early life, environmental factors, digital marketing of unhealthy foods to children, sedentary lifestyles, online gaming, and to other factors [32] that did not exist during the time period when the H–B equations were created.
Therefore, the aim of this study was to revise the Harris–Benedict equation, 104 years after its original version and 32 years after its last revision by Mifflin–St Jeor, using the same easily measurable anthropometric indicators (weight, height, age, and sex).
## 2.1. Participants
A total of 722 Caucasian subjects (173 men and 549 women) were included in this retrospective study after receiving their full medical history. Non-hospitalized individuals with common diseases such as cardiometabolic diseases (e.g., hypertension, coronary artery disease, prediabetes, diabetes mellitus, hyperlipidemias, thyroid diseases, etc.), which are controlled by either dietary or medication (e.g., antidiabetic, anti-lipidemic, benzodiazepines, etc.), were not excluded from the sample. Subjects with pregnancy [33], lactation [34], active infections [35], and unregulated diseases were excluded from participation in the study. The characteristics of the participants are presented in Table 2.
## 2.2. Predictive Equations
The H–B, Mifflin–St Jeor, FAO/WHO/UNU, and Owen equations were used to compare with the new equations.
## 2.3.1. Anthropometric Measurements
The Tanita device (MC-780, Tanita Corporation, Tokyo, Japan) was used to measure body weight with an accuracy of 0.1 kg. Measurement was performed according to protocol with light clothing, without shoes, socks, or stockings, and with arms and legs slightly separated from the body. All measurements were performed during the same visit and in the early morning hours.
A Seca 222 wall-mounted stadiometer with an accuracy of 0.5 cm was used to measure stature utilizing a standard technique, without shoes and hair ornaments, with the legs straight, joined and resting on the wall, arms at the side, shoulders flat, the angle of view parallel to the floor, head, shoulders, buttocks, and heels in contact with the flat surface (wall) [36].
Body mass index was calculated by dividing weight (in kilograms) by the square of height (in meters).
## 2.3.2. Indirect Calorimetry
The IC device, Cosmed Fitmate Pro, which has demonstrated test/retest/retest reliability both within a day and between two different days, was used to measure RMR [37,38]. This device measures the Respiratory Quotient (RQ), i.e., the ratio of carbon dioxide (CO2) produced by the body to oxygen (O2) consumed by the body. The tests were performed with a face mask.
The procedure was performed using the best-appropriate practice methods [39].
Participants were instructed to avoid vigorous activity for 12 h before the visit and to abstain from food, energy drinks, coffee, alcohol, and nicotine for at least 8 h. The examination was performed in a thermally neutral room, in a quiet environment, and after 10 min of rest. The same procedure was repeated one week later for each participant and the mean RMR value was used.
For statistical convenience and to distinguish between equation-predicted RMR values, and IC-measured RMR values, RMRP and RMRIC were assigned, respectively.
## 2.4. Statistical Analysis
The statistical analysis was performed mainly in statistical package R (R version 4.1.3 [2022]. In the creation of the formula, the initial approaches used different types of regressions (linear, polynomial, logarithmic) and linear regression had the most accurate results based on the coefficient of determination (R2) and standard error of the estimate (SEE). The Kolmogorov–Smirnov test and the Shapiro–Wilk test were used to examine whether variables were normally distributed (the subjects were randomly assigned to the training or test subset in such a way that the ratio between sexes remained constant (for males 133 and 40 and for females 429 and 127). To minimize bias and to optimize the validation data, k-Fold cross-validation was applied with linear regression for the production of the equations for female and male training groups. In R to apply k-Fold cross-validation, we used the caret package (version 6.0-93, Max Kuhn, can be found on CRAN and the project is hosted on GitHub). In summary, what k-Fold cross-validation does is shuffle the training dataset randomly and split it into equal groups (if possible), then, for each group, the following procedure is followed: [1] Take the group as a holdout or validation data set; [2] Take the remaining groups as a training data set; [3] *Fit a* model on the training set and evaluate it on the holdout set; [4] Retain the evaluation score and discard the model. After that procedure, it summarizes the skill of the model using the sample of model evaluation scores. Each observation in the data sample is assigned to an individual group and stays in that group for the duration of the procedure. Thus, after the observations split into groups they remain in the same group during the whole procedure.
## 3. Results
The final results showed that for both sexes the weight was significantly associated with RMRIC (for both genders p-value < 0.001). On the other hand, regarding height, the results suggest that it is more significant for females (p-value = 0.001) than for males (p-value = 0.065). Lastly, the results indicated that the age of both sexes is significant but slightly more for males (p-value = 0.005) than females (p-value = 0.011). It should be noted that the resampling results gave us more accurate results for males (R-squared: 0.95) than females (R-squared: 0.86). The new equations for both sexes in both the metric and imperial systems are presented in Table 1 and below:
## 3.3. Differences between Predictive Equations and Measurement RMR
The difference between the predictive equations (RMRP) and measurement RMRIC, the percent bias (accuracy at the group level), and the root mean square error for both the new equations and selected equations are described in Table 3 and Table 4. We found that both the male equation and the female equation showed a bias of <$9\%$. Specifically, the mean bias of the male equation was $8.3\%$ and that of the female equation was $8.9\%$. Among the selected equations from the literature, we found that the introduced equation in both men and women was the most accurate at the group level (mean bias 8.32 and 8.93, respectively). Table 5 and Table 6 illustrates some more metrics of the differences between RMRP and RMRIC that validate that the most successful prediction for males and females comes from the introduced equation and the H–B equation, respectively.
Regarding the accuracy at the individual level, the percentages of participants with an RMRP within ±$10\%$ of the RMRIC for the new and other predictive equations are reported in Figure 1. The new equation reported the highest accuracy in men together with Harris–Benedict ($67.5\%$ and $65\%$, respectively), and the same two equations reported the highest accuracy in women ($59.1\%$ and $57.5\%$, respectively) when compared to the other equations. It should be noted that the least-accurate equations tend to under predict RMRP in both sexes when not accurate.
## 3.4. Bland–Altman Plots of RMRP-RMRIC Differences
The Bland–Altman plots of predicted–measured RMR differences vs. mean predicted–measured RMR obtained by all equations are depicted in Figure 2. There is a good agreement for both the H–B equation and the new equations.
## 4. Discussion
The results of this present study are important because they were conducted under the conditions of the modern “fat-inducing” environment of prolonged sedentary behavior, low levels of physical activity, abundant consumption of energy-rich, over-processed foods, etc., which partly explains the increased mean BMI; this slightly drags up energy needs, compared to the H–B equation. In the second decade of the 1900s, when the H–B equations were created, the average REE was about 1400 to 1600 calories per day for women and men, respectively [40]. According to our study, in the modern sedentary lifestyle of the 2020s, the average RMR ranges between 1500 kcal for women and 2000 kcal for men. Other studies also report a much higher average RMR of 3000 calories/day, mainly for men [41]. This variation in metabolic rate creates the need for revisions of the original H–B equations.
Another important point of this present study relates to the fact that the new proposed equations were based on a broader body mass index (BMI: 17–48 kg/m2) population sample than the original H–B equations (BMI: 12.3–32.5 kg/m2), in which the proportion of subjects with BMI > 30 kg/m2 was only $5\%$ [5,6].
A particularly important point to note about the new equations proposed by our study is the fact that the population sample included both healthy individuals who were not receiving medication and individuals with high-prevalence diseases that were controlled nutritionally and/or pharmacologically. This fact facilitates the use of these equations in daily practice, as it does not preclude their use in population groups associated with diseases with increased rates [42,43], constituting an important part of the population in need of nutritional support.
An interesting aspect of the new equations is that they showed small reductions in prediction error and overestimation bias compared with the measured RMRIC values. The fact that all equations manifest strong reliability in the population from which the data of [44] were drawn is counterbalanced by the better response shown by the new equations compared to other equations presented in this study (H–B, Mifflin–St Jeor, FAO/WHO/UNU, and Owen).
The importance of body weight in improving the predictability of the equations for both sheets, observed in this present study, strengthens the data supporting the contribution of body size to metabolic rate [45,46].
The involvement of age as an important factor in the predictability of the equations presented by the current study has been supported by other studies [47], which is probably based on the modifications of body composition (muscle tissue and lean mass) over time.
However, there are also limitations in our study, which are related to the complete absence of the underweight category from the sample of men (20 to 48 kg/m2) and of individuals overall with BMI < 17 kg/m2.
In this present study, better coefficients for linear relationships were verified, however, allometric relationships have not been considered, which have been shown by other studies to increase the reliability of predicting both BMR and RMR in healthy subjects, adding another level of accuracy to calculations [44].
Another limitation of this present study that should be pointed out concerns the lower population sample of men compared with that of women, but this is not a particularly important drawback as it is not smaller than that used in both the H–B and Roza and Shizgal equations [5,6,7]. In addition, the newly proposed predictive equations of men showed higher reliability than those of women.
## 5. Conclusions
In conclusion, the new resting metabolic rate prediction equations proposed by this study are reliable, easy to use, and can be widely used for body weight management when the measurement of RMR by direct and indirect calorimetry systems is not feasible. However, it is strongly recommended to derive new resting metabolic rate prediction equations for different population races beyond the Caucasian race with different genetic backgrounds, lifestyle factors, anthropometric characteristics, and nutritional habits.
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|
---
title: 'Associations between Body Mass Index and Prostate Cancer: The Impact on Progression-Free
Survival'
authors:
- Dorel Popovici
- Cristian Stanisav
- Marius Pricop
- Radu Dragomir
- Sorin Saftescu
- Daniel Ciurescu
journal: Medicina
year: 2023
pmcid: PMC9967817
doi: 10.3390/medicina59020289
license: CC BY 4.0
---
# Associations between Body Mass Index and Prostate Cancer: The Impact on Progression-Free Survival
## Abstract
Background and objectives: This study aimed to evaluate the impact of body mass index on PCa outcomes in our institution and also to find if there are statistically significant differences between the variables. Materials and Methods: A retrospective chart review was performed to extract information about all male patients with prostate cancer between 1 February 2015, and 25 October 2022, and with information about age, weight, height, follow-up, and PSA. We identified a group of 728 patients, of which a total of 219 patients resulted after the inclusion and exclusion criteria were applied. The primary endpoint was progression-free survival, which was defined as the length of time that the patient lives with the disease, but no relapses occur, and this group included 105 patients. In this case, 114 patients had a biological, local or metastatic relapse and were included in the progression group. Results: Our study suggests that prostate cancer incidence rises with age (72 ± 7.81 years) in men with a normal BMI, but the diagnostic age tends to drop in those with higher BMIs, i.e., overweight, and obese in the age range of 69.47 ± 6.31 years, respectively, 69.1 ± 7.51 years. A statistically significant difference was observed in the progression group of de novo metastases versus the absent metastases group at diagnostic ($$p \leq 0.04$$). The progression group with metastases present ($$n = 70$$) at diagnostic had a shorter time to progression, compared to the absent metastases group ($$n = 44$$), 18.04 ± 11.37 months, respectively, 23.95 ± 16.39 months. Also, PSA levels tend to diminish with increasing BMI classification, but no statistically significant difference was observed. Conclusions: The median diagnostic age decreases with increasing BMI category. Overweight and obese patients are more likely to have an advanced or metastatic prostate cancer at diagnosis. The progression group with metastatic disease at diagnostic had a shorter time to progression, compared to the absent metastases group. Regarding prostate serum antigen, the levels tend to become lower in the higher BMI groups, possibly leading to a late diagnosis.
## 1. Introduction
Globally, according to a study in 2016, $39\%$ of adults aged 18 years old and older were overweight ($39\%$ of men and $40\%$ of women) and about $13\%$ obese ($11\%$ of men and $15\%$ of women) [1]. Obesity is a major public concern around the world because it is also a disease in its own right and is now considered to be a cause of at least 13 types of cancer [2]. Each year, it is estimated that 19 million new cancer cases are diagnosed worldwide—around 10 million cases are in men and 9.2 million in women, with a mortality rate of $54\%$, and $43\%$, respectively [3]. The biological pathway between obesity and cancer is currently being investigated, but not completely understood. Sakers et al. suggest that the negative health effects of obesity come from physiologic stimuli that induce alterations in adipose tissue metabolism, structure, and phenotype. Simply explained, adipocytes lose their plasticity causing a diminished or aberrant response to signaling and promoting the pathological outcome [4]. Obese people suffer from significant metabolic and endocrinological abnormalities that lead to enhanced insulin and insulin-growth factor signaling, dysregulation of sex hormone metabolism, and adipose tissue-derived inflammation [2,5]. Experimental animal models have shown that obesity leads to cancers of the mammary gland, colon, skin, and prostate [6].
According to Globocan, in 2020, prostate cancer (PCa) was among the most diagnosed cancers worldwide, with around 1.4 million men affected by the disease ($7.8\%$), being surpassed by breast (2.2 million), lung (2.2 million) and colorectal cancer (1.9 million). Globally, prostate cancer was the second most diagnosed cancer in male subjects ($15.1\%$), following lung cancer ($15.4\%$), and taking the fifth place in the mortality rate [3].
In Europe, the estimated number of new cases of PCa was ~470,000 ($20\%$ of the male total), which makes it the most frequent cancer diagnosed in men. Additionally, the cumulative risk of being diagnosed with prostate cancer before the age of 75 is $8.2\%$ (1 in 12 men), while the risk of PCa death before the age of 75 is $1\%$ (1 in 103 men) [7].
In Romania, 8055 new PCa cases were diagnosed in 2020, representing $8.15\%$ among all cancers in men aged 45+, and taking second place, after lung cancer [3,7]. The proportion of men diagnosed with PCa before the age of 60 is $1.2\%$, with a mortality rate of $0.2\%$, and after the age of 60 is $14.2\%$, with a mortality rate of $7.5\%$ [3].
Studies suggest that nonmodifiable risk factors, besides age, include several others such as family history of cancer, height, lower testosterone level, type 2 diabetes, higher serum glucose, and high insulin levels. Accounted as significant modifiable risk factors are overweight and obesity, high intake of red meat, fat, dairy, and eggs, consumption of fish, and soy foods, tobacco smoking, and alcohol consumption [8].
Over time, PCa incidence and mortality were significantly different during the past years, worldwide, and they seem tightly correlated to the use of prostate-specific antigen (PSA) measurement in the male population [9]. Incidence rates for PCa are estimated to rise by +$71.6\%$ worldwide, followed by a rise of +$97.1\%$ in mortality rate, between 2020 and 2040. The highest incidence will be registered in Africa (+$106.8\%$), Asia (+$94.1\%$), Latin America and the Caribbean, (+$81.5\%$), and Oceania (+$47.7\%$), followed by the lowest incidence rates in Europe (+$27.6\%$) and Northern America (+23.5). The mortality rate will also rise significantly on all continents, with Asia (+$112.7\%$) leading the charts, followed by Africa ($112.3\%$), Latin America and Caribbean (+$110.4\%$), Oceania (+$92.5\%$), Northern America (+$80.7\%$) and Europe (+$53.2\%$). In Romania, the incidence is estimated to rise by +$21.5\%$, followed by a mortality rate of +$31.2\%$ [3].
The current study aimed to evaluate the impact of body mass index (BMI) on PCa outcomes in our institution and also to find if there are statistically significant differences between the variables.
## 2.1. Criteria
We performed a retrospective chart review to extract information about all male patients with prostate cancer seen in our electronic health record system between 1 February 2015 and 25 October 2022, with information about age, weight, height, follow-up, and PSA. We identified 728 patients, of which we excluded 509 patients due to missing information on height, weight; PSA measured in other medical laboratories; low body mass index; association of other malignancies and patients missing from follow-up visits. This resulted in a total of 219 patients who were included in the final analysis. The primary endpoint was progression-free survival (PFS), which was defined as the length of time that the patient lives with the disease, but no relapses occur, and this group included 105 patients. In this case, 114 patients had a biological, local or metastatic relapse and were included in the progression group (Figure 1). The body mass index (BMI) of each patient was calculated using weight and height, documented in the patient medical history. This analysis is partly based on self-declaration of weight and height, which might be underestimated by the patients, which might lead to potential deviations. Data about the radical prostatectomy, orchiectomy, lymphadenectomy and pathological staging is limited because the surgeries and the histopathological exam were performed in other hospitals. This study was approved by the committee board members of OncoHelp Association Timisoara.
## 2.2. Statistical Analysis
Numeric variables were expressed as mean (±SD) and discrete outcomes as absolute and relative (%) frequencies. We created three groups according to the values of BMI. Group comparability was assessed by comparing baseline follow-up duration between groups. Normality and heteroskedasticity of continuous data were assessed with Shapiro-Wilk and Levene’s test, respectively. Continuous outcomes were compared with ANOVA, Welch ANOVA, or Kruskal-Wallis tests according to data distribution. Discrete outcomes were compared with chi-squared or Fisher’s exact test accordingly. The alpha risk was set to $5\%$ and two-tailed tests were used. The difference between ages according to modalities of BMI was assessed with the ANOVA.
If the null hypothesis of the ANOVA test was rejected, post-hoc pairwise analyses were performed with Tukey’s HSD test. The alpha risk was set to $5\%$ (α = 0.05). Statistical analysis was performed with EasyMedStat—version 3.20; www.easymedstat.com (accessed on 21 October 2022).
## 3.1. Patient Population
The clinical characteristics of patients are shown in Table 1. Of the 219 patients, $28\%$ [62] were categorized as normal weight (NW) (18.5–24.9 kg/m2), $43\%$ [94] as overweight (OW) (25–29.9 kg/m2), and $29\%$ [63] as obese (OB) (30+ kg/m2).
## 3.2. BMI and Age
We identified a statistically significant difference ($p \leq 0.05$) regarding age in the BMI categorized groups. The median age for the NW group was 72 ± 7.81 years vs. 69.47 ± 6.31 years in the OW group and 69.1 ± 7.51 years in the OB group (Table 1, Figure 2). The difference between ages according to modalities of BMI was assessed with ANOVA. The null hypothesis was rejected ($$p \leq 0.007$$), so we performed a post-hoc Tukey test to explore the differences between the means of all three groups and observed a significant difference between the NW and OW groups ($$p \leq 0.023$$) and NW and OB groups ($$p \leq 0.0087$$; Table 2). There was no significant difference ($$p \leq 0.9$$) between the OW and OB groups.
## 3.3. BMI and cTNM Stage
Group stages in correlation with BMI were represented as follows: stage 2–$4.84\%$ NW, $11.70\%$ OW, and $14.28\%$ OB: stage 3–$30.65\%$ NW, $31.91\%$ OW and $23.81\%$ OB and stage 4–$64.52\%$ NW, $56.39\%$ OW and $61.90\%$. No statistically significant difference was found between the groups ($$p \leq 0.567$$).
## 3.4. BMI and De Novo Metastases
De novo metastasis rates were $51.61\%$, $46.81\%$, and $46.03\%$ in patients categorized as NW, OW, and OB, respectively. No statistically significant difference was found ($$p \leq 0.788$$).
## 3.5. BMI and Recurrent Metastases
Recurrent metastasis rates were $19.35\%$, $25.53\%$, and $20.63\%$ in patients for which BMI was NW, OW and OB. No statistically significant difference was found between the groups ($$p \leq 0.614$$).
## 3.6. BMI and Gleason Score
The Gleason score ≥4 + 3 = 7 was most seen between the groups, with 46 ($72.19\%$) in the NW group, 71 ($74.50\%$) in the OW group and 49 ($77.77\%$) in the OB group. No statistically significant difference was found between the groups, overall ($$p \leq 0.905$$).
## 3.7. BMI and GnRH Agonists
Leuprorelin and Triptorelin were the most used agonists among PCa patients (rates of $58.06\%$, $59.57\%$, and $73.02\%$ in the NW, OW and OB groups). No statistically significant difference was found between GnRH agonists ($$p \leq 0.147$$).
## 3.8. BMI and Bisphosphonates
The use rates of zoledronic acid were $20.96\%$, $10.64\%$, and $11.11\%$ within the NW, OW, and OB groups, respectively, with no statistically significant differences ($$p \leq 0.422$$).
## 3.9. BMI and Radical Prostatectomy or Orchiectomy
Approximately ¼ of the patients from each BMI category group underwent radical prostatectomy ($24.19\%$, $26.61\%$, and $23.81\%$ for the NW, OW, and OB groups), while orchiectomy was applied in much lower rates ($3.23\%$, $4.32\%$, and 5.0), with no statistically significant difference between therapeutic approaches within the groups ($$p \leq 0.907$$ and $$p \leq 0.914$$).
## 3.10. BMI and PSA
The median PSA for the NW group was 123.45 ± 366.58 vs. 48.67 ± 132.6 in the OW group and 54.23 ± 156.6 in the OB group, with no statistically significant difference ($$p \leq 0.1$$).
## 3.11. Progression Group According to De Novo Metastases
Overall, 114 events that define progression of PCa were included in this analysis. 70 patients ($61\%$) in the group of events were recorded with de novo metastases and 44 ($39\%$) were without. The median progression time for those patients who presented with de novo metastasis was 15.91 months, while 20.17 months was for those without de novo metastases. The Mann-Whitney test was used to compare the progression group median according to de novo metastasis. There was a statistically significant difference in the progression group between the patients with present and absent metastases ($$p \leq 0.04$$, Table 3).
## 3.12. Progression Group According to Recurrent Metastases
From the same group of 114 patients that experienced events, 49 patients ($43\%$) in the group presented with recurrent metastases and 65 patients ($57\%$) did not have recurrent metastases. The median progression time was 16.8 and 17.03 months for patients with, and without recurrent metastasis, respectively. The Mann-Whitney test was used to compare the median progression time according to recurrent metastasis. There was no statistically significant difference ($$p \leq 0.859$$, Table 4).
## 3.13. Progression Group According to BMI
Finally, from the same group of 114 patients who presented with progression of the disease, 32 ($28\%$) were NW, 46 ($31\%$) were OW, and 36 ($41\%$) were OB. The median time of progression was 15.42, 19.56, and 17.01 months for the patients categorized as NW, OW, and OB, respectively. The Kruskal-Wallis one-way analysis of variance was used to compare the median time in the progression group according to BMI. There was no statistically significant difference between NW and the other two groups ($$p \leq 0.4$$, Table 5). We also performed a Mann-Whitney test to compare in the progression group the median time between NW and OW, NW and OB, and OW and OB groups. There was no statistically difference between NW and OW ($$p \leq 0.3$$), NW and OB ($$p \leq 0.1$$), and OW and OB ($$p \leq 0.2$$).
We used the Kaplan-Meier method to estimate the progression of PCa as an end-point, from the diagnostic date until the date of the last consultation in the progression group. The log-rank non-parametric test for comparison of progression distributions was used to compare recurrence differences between the NW, OW, and OB groups. There was no difference between the recurrence distributions ($$p \leq 0.09$$, Figure 3).
## 4. Discussions
Prostate cancer remains a global health burden and cases will continue to rise, but pharmacological and technological advances are considerably improving and should enable future precision and improved clinical outcomes [10]. A proof-of-concept for future precision was recently demonstrated in some studies, where the teams used a Transient Receptor Potential Melastatin 8 channel (TRPM8) agonist, an ion channel in the plasma membrane, encapsulated into a Lipid NanoCapsule in order to inhibit PCa cell migration. The use of TRPM8 has a great impact in castration-resistant prostate cancer, which is considered to be the most aggressive form of PCa, because it is usually resistant to androgen deprivation therapy [11,12]. However, it is clear that over time a high index of body mass will influence our general physical well-being, along with age and other factors, and can lead to negative results in cases of pathologies, such as cancers.
Our study suggests that prostate cancer incidence rises with age (72 ± 7.81 years) in men with a normal BMI, but the diagnostic age tends to drop in those with higher BMIs, i.e., overweight, and obese in the age range of 69.47 ± 6.31 years, respectively, 69.1 ± 7.51 years. A single-center retrospective study from 2022 investigated the relationship between BMI and prostate cancer risk in 1079 Italian men, which also revealed that overweight and obese men were diagnosed at younger ages, compared to normal-weight patients. Furthermore, excessive fat accumulation contributes to a more favorable tumor microenvironment onset and growth [13].
We also observed, as well mentioned in the study cited above, that PSA tends to diminish with increasing BMI classification, but no statistically significant difference was observed. Both factors, higher BMI and lower PSA, can lead to a high-grade PCa, avoiding an early diagnostic, also seen in this study, where almost half of OW and OB patients had a stage IV PCa diagnostic.
A study from 2017 suggests that long-term weight gain is associated with an increased risk of high-grade PCa among never smokers and among men who were overweight or obese at age 21 [14]. Furthermore, OB men tend to have higher levels of insulin, insulin-like growth factor-1, and lower level of androgens and adiponectin, suggesting that inflammatory and hormonal pathways are involved. Prolonged hyperinsulinemia raises the bioavailability of IGF-1, which has been shown to promote proliferation and inhibit apoptosis in normal prostate and tumor cells in vitro, increasing the risk of PCa [14,15,16,17,18]. Adiponectin is secreted by the adipose tissue and is inversely related to the degree of adiposity [19]. This protein hormone promotes apoptosis and inhibits proliferation and angiogenesis, and higher concentrations have been shown to decrease the risk of high-grade prostate cancer [14,19] Opposed to adiponectin, leptin concentrations are directly related to adiposity and the biological effects are to stimulate cell proliferation and promote angiogenesis [20].
The immune response could also play an important role in the progression of PCa. In a recent study by Fujita et al., they researched the relationship between high-fat diet (HFD) induced inflammation and tumor progression PCa in mice and found that local inflammation of the prostate is one of the most important factors for the progression of PCa in obese and HFD-fed mice in early and late stages. Interestingly, the number of B cells, T cells, macrophages, and mast cells and the ratio of CD8/CD4 T cells were not changed by the HFD, but the number of myeloid-derived suppressor cells and the M2/M1 macrophage ratio were significantly increased in the HFD-fed mice compared with the control group. Using celecoxib, a cyclooxygenase 2 inhibitor, the promotion of tumor growth by the HFD was canceled, which suggests that inflammation plays a specific role in tumor progression caused by HFD. All these hormonal and immune changes in obese people lead to chronic inflammation and play an important role in the development and progression of PCa [21].
We observed a statistically significant difference in the progression group of de novo metastases versus the absent metastases group at diagnostic ($$p \leq 0.04$$). The progression group with metastases present ($$n = 70$$) at diagnostic had a shorter progression time, compared to the absent metastases group ($$n = 44$$), 18.04 ± 11.37 months, respectively, 23.95 ± 16.39 months. No other statistically significant difference was found between the progression and recurrent metastasis group ($$p \leq 0.859$$) or BMI ($$p \leq 0.4$$).
Our study has its limitations. Since the cohort study has not had enough participants, it is possible that the results could not meet the criteria for significance. For example, the progression of PCa in the BMI groups was not statistically significant between the NW group and the OW, or OB group, but looking at the Kaplan-Meier curve, the NW line has a more obvious decrease at some point, compared to the OW and OB groups. Some studies suggest that there is an inverse association in the progression of the disease between obese and normal-weight patients, where normal-weight patients have a faster relapse and obesity has a protective effect from the PCa recurrence [22,23]. This inverse association is called the obesity paradox. A study conducted by Martini et al. and another study by Schiffmann et al., revealed that obese patients treated with docetaxel and prednisone for metastatic castration-resistant prostate cancer benefited of a protective factor against overall mortality and death, respectively, the second team mentioned that increased BMI was associated with a decreased risk of metastases after radical prostatectomy [24,25]. We propose that urologists should be attentive to radical prostatectomy procedures in overweight and obese patients in order to avoid positive surgical margins. Marenco et al. suggests the fluorescent confocal microscopy as a novel technique that could be used for real-time diagnosis of PCa and also for the evaluation of surgical margins during radical prostatectomy. An advantage of fluorescent confocal microscopy, compared to other intraoperative histological evaluations, could be the rapid application to whole tissue sections [26]. Regarding lymph node dissection, we think that a more aggressive approach is currently suited for the patients with increased BMI, but we believe that further studies need to be corelated with the molecular mechanisms underlying PCa migration, in order to enable a better clinical, surgical and pharmacological management. Such molecular mechanisms were studied recently in vivo and revealed that the upregulation of HGK (a component of Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4), Culin 4B (a scaffold protein with oncogenic activity), overexpression of Human Homebox B9 (a key transcription factor that promotes metastases) and low levels of Receptor tyrosine kinase-like receptor (a noncanonical Wnt receptor) play a major role in the aggressive behavior of PCa [27,28,29,30]. Our data about the radical prostatectomy, orchiectomy, lymphadenectomy and pathological staging is limited because the surgeries and the histopathological exam were performed in other hospitals.
## 5. Conclusions
Our results suggest that the median diagnostic age decreases with increasing BMI category. Furthermore, overweight, and obese patients are more likely to have an advanced or metastatic prostate cancer at diagnosis. In the metastatic group we observed that the progression of the disease has a shorter interval, leading to a faster relapse. The levels of prostate serum antigen tend to become lower in the higher BMI groups, possibly leading to a late diagnosis. Further studies are needed to determine if there is an inverse association between progression of prostate cancer in normal weight and overweight or obese patients, involving excessive fat as a protective mechanism against prostate cancer. We want to address a further question. Does the subcutaneous fat exert a protective effect on the development and recurrence of prostate cancer or other pathways are involved?
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---
title: The Urgent Need for Cardiopulmonary Fitness Evaluation among Wildland Firefighters
in Thailand
authors:
- Jinjuta Panumasvivat
- Wachiranun Sirikul
- Vithawat Surawattanasakul
- Kampanat Wangsan
- Pheerasak Assavanopakun
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967820
doi: 10.3390/ijerph20043527
license: CC BY 4.0
---
# The Urgent Need for Cardiopulmonary Fitness Evaluation among Wildland Firefighters in Thailand
## Abstract
Wildland firefighting is a high-risk occupation. The level of cardiopulmonary fitness can indicate whether wildland firefighters are ready to perform their job duties. This study’s objective was to determine wildland firefighters’ cardiopulmonary fitness using practical methods. This cross-sectional descriptive study aimed to enroll all 610 active wildland firefighters in Chiang Mai. The participants’ cardiopulmonary fitness was assessed using an EKG, a chest X-ray, a spirometry test, a global physical activity questionnaire, and the Thai score-based cardiovascular risk assessment. The NFPA 1582 was used to determine “fitness” and “job restriction”. Fisher’s exact and Wilcoxon rank-sum tests were used to compare cardiopulmonary parameters. With a response rate of $10.16\%$, only eight wildland firefighters met the cardiopulmonary fitness requirements. Eighty-seven percent of participants were in the job-restriction group. An aerobic threshold of eight METs, an abnormal EKG, an intermediate CV risk, and an abnormal CXR were the causes of restriction. The job-restriction group had a higher 10-year CV risk and higher systolic blood pressure, although these differences were not statistically significant. The wildland firefighters were unfit for their task requirements and were more at risk of cardiovascular health compared to the estimated risk of the general Thai population. To improve the health and safety of wildland firefighters, pre-placement exams and health surveillance are urgently needed.
## 1. Introduction
Firefighters are known to be high-risk workers [1]. They are subjected to high levels of physical stress at work while wearing bulky safety gear and performing demanding physical duties, such as lifting, pulling, and climbing. They confront extreme temperatures, toxic gases and substances, shift work, and psychological stress in emergencies, which are potential cardiovascular hazards [2]. Both urban and wildland firefighters encounter dangerous hazards, but their locations, circumstances, and strategies are different. Wildland firefighters could experience more unsafe conditions, such as steep terrain, rocky and muddy ground surfaces, isolated and remote areas, limited escape options, and long working hours lasting up to 14 to 21 days of assignments. They also require specialized equipment, such as piles, pulaskis, and hoes, as well as expertise skills, such as smokejumping [3]. Even though there is a standard for personal protective equipment (PPE) for wildland firefighters, it seems unlikely that they would use self-contained breathing apparatus (SCBA) in the same situation as urban firefighters [3,4]. Because SCBA is too bulky and heavy and has limited-time use, wildland firefighters are more likely to be exposed to hazardous hazards through their respiratory systems [5].
Performing firefighting tasks leads to physiological change through an increase in heart rate and prolonged beating in higher-intensity zones, which is positively correlated with the duration of fire suppression [6]. For the health and safety of firefighters, an adequate cardiopulmonary condition is necessary. Aerobic capacity is one of the best measures to determine cardiopulmonary fitness. Many countries develop their aerobic capacity standard for firefighters’ fitness for duty. For newly hired firefighters in the US, the National Fire Protection Agency (NFPA) mandates at least 12 metabolic equivalents (METs) for new recruitment and at least 8 METs for yearly examinations. Firefighters who have less than eight METS have to limit their duties and improve their physical fitness [7]. In the UK, VO2 max above 42.3 mg/kg/min is the minimum standard, and a value below 35.6 mg/kg/min is considered unfit. A firefighter who has 35.6–42.2 mg/kg/min needs fitness training [8]. In Australia’s New South Wales, candidates must have at least 12 METs; if not, they must increase their fitness [9]. Recent studies demonstrate a positive association between high levels of physical fitness and firefighters’ performance and ability [10,11]. Additionally, a low level of physical fitness raises the risk of cardiovascular disease [12]. There are also many health impacts on wildland firefighters’ cardiopulmonary status from occupational exposure [13,14,15,16,17], such as increased prevalence of hypertension and cardiovascular symptoms [14,15], and decreased lung function [16,17]. Continuous occupational exposure could produce a long-term effect on cardiopulmonary status and increase cancer risk [13]. Health impact might lead firefighters to perform their tasks in an unsafe and ineffective manner and disqualify their work. Therefore, it is crucial to offer a periodic medical examination to assess employee health and safety and ensure that firefighters can perform their full range of duties.
In Thailand, urban firefighters and wildland firefighters have somewhat different tasks, and wildland firefighters might experience more dangerous hazards due to the nature of their job. As a developing country or an upper-middle-income country, there is still no standard for pre-placement, periodic examination, and health surveillance of wildland firefighters. Without the emphasis on risk-based evaluation, only general health examinations are performed. Aerobic capacity tests, such as exercise stress tests, are rarely performed in Thailand to determine work fitness due to a lack of resources, high cost, and a lack of cardiologists to administer them. This study aims to determine the cardiopulmonary fitness level of wildland firefighters by following international standards and using practical methods. The findings may support the creation of occupational health management guidelines for Thai wildland firefighters.
## 2.1. Study Design and Population
This cross-sectional descriptive study aimed to enroll all 610 active wildland firefighters in Chiang Mai to assess their fitness levels for work. The firefighters were informed about the study through a coordination with the Organization of Protected Areas, Regional Office 16, Department of National Parks, Wildlife, and Plant Conservation, Thailand. The participants were required to have worked for at least a year and be at least 18 years old to participate in the study. This study’s inclusion criteria and items of cardiopulmonary fitness assessment were communicated to the coordinator of the organization, who then communicated the information to all wildland firefighters via organizational communication. This study was conducted from 15 December 2021 to 25 January 2022. Figure 1 represented the enrollment and discontinuation of study participants.
## 2.2. Data Collection
The fitness level for firefighting was assessed using the cardiopulmonary fitness assessment according to the NFPA standard. The wildland firefighters were interviewed by research assistants with the use of a questionnaire for their occupational history and prior history of health problems, and they were examined with calibrated tools for an assessment of their current cardiopulmonary status.
## 2.3. Questionnaire Design
The participants were interviewed using a questionnaire, which was adapted from the NFPA standard for collecting firefighting tasks and from the medical clearance form of the respiratory protection program for history of cardiopulmonary problems. This questionnaire was made up of three main parts:[1]General information of the participants, including age, gender, body weight (kg), height (cm), waist circumference (cm), body mass index (BMI, kg/m2), smoking status, and alcohol drinking status. BMI was categorized into four groups using the Asian BMI classification: underweight (<18.5 kg/m2), normal weight (18.5–22.9 kg/m2), overweight (23–24.9 kg/m2), and obese (≥25 kg/m2) [18].[2]Information on work tasks, including work experience (years), working hours (h/day), shift work, and job tasks.[3]Prior cardiopulmonary problems, such as myocardial infarction, arrythmia, asthma, and stroke.
## 2.4. Cardiopulmonary Fitness Assessment
This section was made up of three parts:[1]Spirometry, chest X-ray (CXR), and electrocardiogram (EKG) were performed for the participants. The spirometry test was assessed using the SpiroMaster PC-10. The procedures were performed and required at least three acceptable graphs, following the ATS/ERS standards [19]. Various parameters, including FEV1, FCV, and FEV1/FCV, were collected. The Thai Siriraj equation [20] was used as the predicted value reference.[2]Metabolic equivalents are defined as caloric consumption during an activity. One MET means caloric consumption at rest. They are used as an estimate of functional capacity, with greater METs indicating that more energy is consumed during an activity. To estimate METs for physical activities performed at work, a face-to-face interview using the global physical activity questionnaire (GPAQ) was utilized [21]. The participants were asked about their “intensity and duration” of physical activity at work and in transportation. Using the GPAQ data, the following MET values were used to determine a person’s overall energy expenditure: four METs for moderate activity and eight METs for vigorous activity. The data were analyzed as MET minutes per week based on the intensity of physical activity and duration of activity in minutes per week. We categorized the MET groups as eight METs (19,200 MET minutes per week) and twelve METs (28,800 MET minutes per week) according to the requirements in the guidance of NFPA. The calculation was based on the assumption of 8 working hours in 5 days a week.[3]The Thai CV risk score was used to estimate the 10-year incidence prediction of cardiovascular disease [22]. The parameters included age, sex, height, blood pressure, smoking status, diabetes history, and waist circumference. The researcher measured each participant’s waist circumference. The risks of over $10\%$ were categorized as intermediate risks.
## 2.5. Definition of Fitness Level
According to the NFPA 1582[3]’s annual examination standards guideline [7], fitness levels were divided into two groups: “Fit” meant workers who could handle all firefighting jobs without limitation, and “Job restriction” meant those who must be restricted from some firefighting activities due to their limited cardiopulmonary health. We considered a work restriction if any participants met at least one of the following criteria: under 8 METs for aerobic capacity; intermediate CV risk with SBP > 140 mmHg or DBP > 90 mmHg; FEV1 and FVC lower than $70\%$ as predicted by the spirometry test; and any abnormal EKG or chest X-ray in category A or B (Appendix A).
## 2.6. Statistical Analysis
The difference between the fit group and the job-restriction group was analyzed using Fisher’s exact test, unpair t-test, and Wilcoxon rank-sum test. STATA version 16 was used for all statistical analyses. ( StataCorp. 2019. Stata Statistical Software: Version 16. College Station, TX, USA: StataCorp LLC.) Statistical significance was set up at p-value < 0.05.
## 3. Results
With a response rate of $10.16\%$ of all active wildland firefighters, 62 wildfire firefighters participated in the study, but only 56 performed the spirometry test. Most participants were men, with an average age of 41.66 years. The baseline characteristics are shown in Table 1. All participants had 8 h of working hours. In addition, $72.58\%$ of participants had 12 h of shift work.
## Cardiopulmonary Fitness
The characteristics between the 54 job-restriction workers and the 8 fit-for-duty workers were not found to be statistically different. Eight firefighters were fully fit for duty by passing all cardiopulmonary parameters’ standards, and 55 firefighters needed restrictions from their firefighting tasks. Six individuals were found to have hypertension on the test day, resulting in only 56 people being examined with spirometry. All of the participants with a completed spirometry met the pulmonary function requirements. The most unmet fitness requirements were, in order, METs below eight, abnormal EKG, intermediate CV risk, and abnormal CXR. The proportion between fit and job restriction in each of the cardiopulmonary parameters is shown in Figure 2. The main cause of abnormal EKG was arrhythmia (PVC and long QTc) and ST abnormality (ischemia and pericarditis). One restriction from CXR showed subsegmental atelectasis. The overall cardiopulmonary parameters are presented in Table 2.
Of the total 54 participants with job restriction, 43 people were limited by METs alone, 7 people were limited by METs and abnormal EKG, 3 people were limited by METs and high CV risk, and 1 person was limited by METs and abnormal CXR. The subset of cardiopulmonary causes of unfitness, represented in an Euler diagram, is shown in Figure 3.
The “job restriction” group had significantly fewer MET minutes per week compared to the fit-for-duty group ($p \leq 0.001$). This group also had a greater ten-year CV risk and higher systolic blood pressure; however, these differences were not significant. This trend of difference between the two groups is shown in Figure 4.
## 4. Discussion
This study showed that only $12.9\%$ of participants were entirely fit for their jobs. In addition, all 54 participants failed in cardiopulmonary fitness based on the NFPA annual aerobic capacity requirement [7]. To work without restrictions, they must maintain an aerobic capacity of at least eight METs. In comparison, the maximal oxygen consumption (VO2 max) standard proposed by the NFPA was passed by $51.0\%$ of Colorado firefighters [23] and $27.5\%$ of New Mexico wildland firefighters [24], which showed a higher proportion than this study. However, both studies were conducted with firefighters at a younger age. Age is a potential factor for the decline in aerobic capacity, especially at 40–50 years of age [25]. According to research conducted in Belgium [26], the percentage of firefighters who meet the 42 mL/kg/min VO2 max criterion declines at 45 years old and significantly decreases at the age of 50, with three-quarters failing this criterion at this age. Lower aerobic capacity increases cardiovascular disease [12,27] and increases the risk of injury [28]. One of the job restriction conditions was due to abnormal EKG, which showed arrhythmia and ST abnormalities. These findings might have been caused by work conditions due to firefighters being confronted with many potential cardiovascular hazards in their work, such as CO, smoke, physical work, heat stress, shift work, poor diet, and occupational stress [2]. There is evidence that fire suppression is associated with thrombus formation and vascular dysfunction, which are the pathological mechanisms for an acute myocardial infarction [29]. In one study, EKG tracing at 12 h post-fire suppression showed a rate of $20\%$ for ventricular arrhythmia and $16\%$ for ST-segment changes [30]. According to a cohort study of Danish firefighters, there was considerable increase in CVDs, such as angina pectoris, myocardial infarction, and atrial fibrillation, in firefighters compared to the general population when using standardized incidence ratio of 1.16, 1.16, and 1.25, respectively [31]. Even though we discovered a significant number of cardiopulmonary causes of work restrictions, with $6.45\%$ for arrhythmia and $4.84\%$ for ST abnormalities in our study, we could not explain if these problems were already there before being exposed to cardiovascular risk at work or if they were caused by work. In the case of high-risk job tasks, these firefighters must be restricted in their work fitness if they had a potentially life-threatening abnormal EKG or a high CV risk. There is a significant correlation between physical ability performance and cardiovascular diseases [11,12]. Screening of firefighters’ health using pre-placement examination is necessary to assess their fitness to work.
For pulmonary fitness, four participants had a mild obstruction and one participant had a mild restrictive lung condition. The NFPA’s guidelines, however, let those with mild abnormal pulmonary function without symptoms work. Wearing SCBA reduces risk exposure but increases physiological strain by increasing airflow resistance, dead space, and breathing rate, which could limit a firefighter’s ability in case of pulmonary disease [32,33]. In case of health effects, hazards at work might also harm or aggravate the respiratory system in firefighters [5]. Systematic review studies report a significant decline in pulmonary function both in cross-shift and cross-season firefighters [13]. A longitudinal study of spirometry found that FEV1, FVC, and PEF decline after smoke exposure and significant decline at more than 24 h post-exposure. FCV and FEV1 have been shown to decrease daily when compared to the prescribed burn period [17]. A previous study conducted in Chiang Mai reported that another group of firefighters had short-term effects on small airway dysfunction but no effect on spirometry [34]. This might differ from the participants in this study, as their average age was lower than that of the participants in this study. Wildland firefighters mostly do not wear SCBA due to inappropriate movement and flexibility, which can expose them to more hazards to their lungs. Thus, even though all participants met pulmonary function standards, health surveillance to follow lung decline in firefighters should be performed. To avoid work-related cardiopulmonary disease in Thai wildland firefighters, pre-placement examinations, medical monitoring, and health screening are required.
Some wildland firefighters’ organizations in Chiang Mai conduct physical fitness testing by having candidates run five kilometers and perform one minute of pushups to determine their physical fitness. Although their organizations conduct these periodic physical fitness evaluations to evaluate their fitness and estimate their readiness for job tasks, the proportion of physiologically fit individuals remains low. Low aerobic capacity could be improved through physical training programs and an increase in physical activity [11,35,36,37]. A meta-analysis study showed that an exercise intervention, including aerobic exercise, resistance exercise, or a combined method of 3–4 sessions/weeks for 16.5 ± 10 weeks, could improve aerobic capacity [35]. Chizewski et al. [ 11,37] reported that high-intensity fitness training improved fitness and firefighting ability [37]. After performing a fitness training program for seven weeks, VO2 max increased from 40.84 ± 5.09 in the first week to 45.30 ± 5.24 in the seventh week [11]. Therefore, even though cardiopulmonary fitness declines with age, it might be improved or maintained in a good condition by a fitness training program. The training program of one study encourages firefighters to engage in moderate-to-vigorous leisure-time physical activity and to improve cardiovascular workload while performing job tasks [36].
In developed countries, including the United States of America (USA), the United Kingdom (UK), and Australia, there are standards for firefighters’ fitness for duty. All workers are required to have a pre-placement examination for fitness evaluation and baseline health surveillance, as well as an annual examination to determine if there are any work-related hazards. To the best of our knowledge, Thailand still needs to reach a consensus on a fit-for-duty standard for firefighters. The majority of the findings on work restrictions provide good supporting evidence to emphasize the urgency of developing occupational health management standards for Thailand in the near future. Urban and wildland firefighters’ pre-employment and routine checkup programs are determined by organizational management, which could vary depending on the setting. Available resources and national contexts might be considered to develop guidelines for fit-to-work and health surveillance among Thai firefighters. For example, the exercise stress test, as a gold standard for aerobic capacity, is a limited resource for many developing countries. Non-exercise tools have been developed to estimate VO2 max, which have more practical use in large populations. Self-perception of aerobic fitness, such as the physical activity questionnaire, has been widely used to determine firefighters’ aerobic capacity [38,39]. A study with 102 working-age adults reported that self-reported daily vigorous physical activity was associated with aerobic capacity [38]. As a beginning for developing a standard in a country with limited resources, a self-perception questionnaire might be useful for screening. Utilizing screening or non-invasive methods might aid in the early detection of any abnormalities in the cardiovascular system.
To our best knowledge, this is the first investigation of cardiopulmonary fitness in Thai wildland firefighters. There are several limitations to this study. First, as a cross-sectional study, the direction of associations cannot be determined. This study only evaluated cross-sectional health status without comparing it to the baseline because there were no baseline data for each participant and also because of an inadequate pre-placement examination program. Second, there might have been selection bias due to the low number of wildland firefighters who agreed to participate in this study. Although about $10\%$ of the study population responded, the findings could be considered generalizable to other firefighting settings with different contexts and resources. However, the majority of fire-prone regions in Thailand have a similar geography. Moreover, most of the wildland firefighters in Thailand are Thai nationals with comparable job descriptions. *The* generalizability of this study’s findings to other Thai wildland firefighters could be advantageous. Another factor could contribute to selection bias. As we attempted to recruit all Chiang Mai wildland firefighters, we recognized that people who might be interested in participating were those who were concerned about their health. This might have led to a higher average age of the participants compared to other studies. Third, as the MET evaluation used in this study was based on self-report using the GPAQ for practical assessment, it might not reflect the firefighters’ actual aerobic capability as accurately as quantitative methods. Future studies should be conducted, including a longitudinal study with baseline health assessments to determine the causal relationships and trends in participants’ fitness. We also suggest using a more effective recruitment method to increase the number of participants in future studies.
## 5. Conclusions
The majority of Thai wildland firefighters had low cardiopulmonary fitness according to international standards. This might affect their work productivity and health. Low aerobic capacity was the major cause of job restriction, and the job-restriction group tended to have a higher risk of CVD risk, even though this trend was not statistically significant. These results demonstrate that Thailand needs an effective surveillance system for hazardous occupations. To protect wildland firefighters from potential dangers, it is urgent to establish standards, guidelines, and policies for fitness for duty. Every wildland firefighter should receive training to improve their functional fitness, and non-invasive screening techniques could be a useful tool for monitoring their fitness.
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---
title: Encapsulation of SAAP-148 in Octenyl Succinic Anhydride-Modified Hyaluronic
Acid Nanogels for Treatment of Skin Wound Infections
authors:
- Miriam E. van Gent
- Tom van Baaren
- Sylvia N. Kłodzińska
- Muhanad Ali
- Natasja Dolezal
- Bjorn R. van Doodewaerd
- Erik Bos
- Amy M. de Waal
- Roman I. Koning
- Jan Wouter Drijfhout
- Hanne Mørck Nielsen
- Peter H. Nibbering
journal: Pharmaceutics
year: 2023
pmcid: PMC9967827
doi: 10.3390/pharmaceutics15020429
license: CC BY 4.0
---
# Encapsulation of SAAP-148 in Octenyl Succinic Anhydride-Modified Hyaluronic Acid Nanogels for Treatment of Skin Wound Infections
## Abstract
Chronic wound infections colonized by bacteria are becoming more difficult to treat with current antibiotics due to the development of antimicrobial resistance (AMR) as well as biofilm and persister cell formation. Synthetic antibacterial and antibiofilm peptide (SAAP)-148 is an excellent alternative for treatment of such infections but suffers from limitations related to its cationic peptidic nature and thus instability and possible cytotoxicity, resulting in a narrow therapeutic window. Here, we evaluated SAAP-148 encapsulation in nanogels composed of octenyl succinic anhydride (OSA)-modified hyaluronic acid (HA) to circumvent these limitations. SAAP-148 was efficiently (>$98\%$) encapsulated with high drug loading ($23\%$), resulting in monodispersed anionic OSA-HA nanogels with sizes ranging 204–253 nm. Nanogel lyophilization in presence of polyvinyl alcohol maintained their sizes and morphology. SAAP-148 was sustainedly released from lyophilized nanogels (37–$41\%$ in 72 h) upon reconstitution. Lyophilized SAAP-148-loaded nanogels showed similar antimicrobial activity as SAAP-148 against planktonic and biofilm-residing AMR *Staphylococcus aureus* and Acinetobacter baumannii. Importantly, formulated SAAP-148 showed reduced cytotoxicity against human erythrocytes, primary human skin fibroblasts and human keratinocytes. Additionally, lyophilized SAAP-148-loaded nanogels eradicated AMR S. aureus and A. baumannii colonizing a 3D human epidermal model, without inducing any cytotoxicity in contrast to SAAP-148. These findings indicate that OSA-HA nanogels increase SAAP-148′s therapeutic potential for treatment of skin wound infections.
## 1. Introduction
Chronic wounds, such as diabetic foot ulcers and burn wounds, affect up to $3.5\%$ of the United States population, constituting a painful burden for patients and a significant expenditure to healthcare systems and societies around the world [1,2,3]. As standard care, chronic wounds are regularly cleaned, debrided and covered using wound dressings [4]; however, the slow healing process of chronic wounds may allow bacteria to infiltrate and subsequently infect the wound. Opportunistic pathogens, such as *Staphylococcus aureus* and Acinetobacter baumannii, among others, are notorious for colonizing chronic wounds [5,6]. Moreover, antimicrobial resistance (AMR) development [7,8], biofilm formation [8] and the evolution of persister cells [9] by these pathogens hampers their effective eradication with current antibiotics. Therefore, there is an urgent need for novel and effective treatments of chronic wound infections.
Antimicrobial peptides (AMPs), such as synthetic antibacterial and antibiofilm peptide (SAAP)-148, are promising alternatives to antibiotics for treatment of bacterial wound infections. SAAP-148 is a potent and broad-spectrum antimicrobial that can eradicate AMR bacteria, including S. aureus and A. baumannii biofilms from murine skin [10]. Additionally, SAAP-148 is effective against AMR S. aureus persister cells in antibiotic-exposed mature biofilms [11]. Moreover, SAAP-148 has proven successful in the treatment of superficial skin wound infections in mice [10]. Nevertheless, SAAP-148 was not as successful in surgical skin wound infections in rats [12]. The limitations of SAAP-148 in the latter study were partly related to components within the wound micro-environment, such as binding to (plasma) proteins and degradation by proteases. Other challenges for further development of SAAP-148 are related to its cationic peptidic nature, including a short half-life and cytotoxicity, resulting in a narrow therapeutic window.
Nano-scaled drug delivery systems can be used to circumvent several of these limitations associated with SAAP-148. Drug delivery systems have been shown to improve pharmacokinetic and -dynamic properties of AMPs by (i) improving their stability and bioavailability [13,14,15], (ii) mediating their sustained release, thus reducing their overall cytotoxicity [16,17], (iii) assisting their transport across cellular membranes and improving intracellular uptake [17,18], and (iv) improving their biofilm penetration and intracellular retention [17,18,19,20]. In particular, nanogels are excellent carriers for wound treatment due to their combined features of nanoparticles and hydrogels, thereby allowing high encapsulation of water-soluble drugs, like AMPs, and providing a moist environment ideal for wound healing [21,22,23]. Nanogels composed of hyaluronic acid (HA) are of particular interest due to HA’s biodegradability, biocompatibility, and its intrinsic antiadhesive and antibiofilm properties towards bacteria [24]. Furthermore, modification of HA with octenyl succinic anhydride (OSA) produces an amphiphilic polymer [25], that can self-assemble into soft flexible nanogels composed of hydrophobic and hydrophilic zones within the nanogel matrix [22,26]. Finally, OSA-HA nanogels have been shown to reduce the cytotoxicity of a range of biomacromolecules, including AMPs [27], peptidomimetics [28], and antibiofilm peptides [16].
In this study, we encapsulated SAAP-148 in OSA-HA nanogels with the aim to improve its selectivity index. For this purpose, we determined the physicochemical properties of the nanogels and evaluated their antibacterial and cytotoxic activities in vitro and in a 3D human epidermal infection model. This study describes successful encapsulation of SAAP-148 in OSA-HA nanogels that showed reduced cytotoxicity and maintained antimicrobial activities against AMR bacteria, thus improving SAAP-148’s selectivity index.
## 2.1. Materials
Hyaluronic acid (HyaCare, 50 kDa) was purchased from Evonik Nutrition and Care (Essen, Germany). Octenyl succinic anhydride (OSA, $97\%$ purity), lysozyme egg white, trifluoroacetic acid (TFA), tetracycline, TritonTM X-100 and bovine serum albumin (BSA) were obtained from Sigma-Aldrich (St. Louis, MO, USA). Sodium bicarbonate (NaHCO3), sodium hydroxide (NaOH), calcium chloride (CaCl2) and human serum were obtained from Merck (Darmstadt, Germany). SAAP-148 was synthesized using standard Fmoc chemistry, purified to >$95\%$ as described previously [29], and stored lyophilized until use. 6-Carboxytetramethylrhodamine (6-TAMRA)-labeled SAAP-148 (acetyl-LK(6-TAMRA)RVWKRVFKLLKRYWRQLKKPVR-amide) with a purity of $96.9\%$ was purchased from Pepscan (Lelystad the Netherlands). Polyvinyl alcohol (PVA) was purchased from Acros Organics (Geel, Belgium) and dextran-40 was a kind gift from Avivia B.V. (Nijmegen, the Netherlands). Uranyl acetate was obtained from Honeywell Fluka (Charlotte, NC, USA). Analytical-grade solvents for UPLC analysis included ultrapure water (Veolia Purelab Chorus 1, ELGA Labwater, High Wycombe, UK) and acetonitrile ($100\%$, VWR, Radnor, PA, USA). Ultrapure water for synthesis of polymer, and sample preparation and analysis was obtained from a MilliPore system, and phosphate-buffered saline (PBS) from Fresenius Kabi (Graz, Austria). Tryptic soy broth (TSB), brain heart infusion (BHI) and Mueller–Hinton (MH) agar were purchased from Oxoid (Basingstoke, UK). Dulbecco’s Modified Eagle Medium (DMEM) supplemented with $1\%$ (v/v) GlutaMAX™, penicillin-streptomycin (pen/strep), trypsin-EDTA, keratinocyte serum-free medium (KSFM), bovine pituitary extract (BPE) and human recombinant epidermal growth factor (EGF) were obtained from Gibco (Waltham, MA, USA). Microplates were purchased from Greiner BioOne (Alphen a/d Rijn, The Netherlands), and culture plates and inactivated fetal bovine serum (FBSi) from Corning Inc. (Corning, NY, USA). Alexa FluorTM Plus 405 Phalloidin, 4’,6-diamidino-2-fenylindool (DAPI) and ProLong Diamond Antifade mountant were purchased from Invitrogen (Waltham, MA, USA), while $1\%$ (v/v) paraformaldehyde (PFA) was obtained from the Department of Clinical Pharmacy and Toxicology (Leiden University Medical Center, Leiden, The Netherlands).
## 2.2. Modification of Hyaluronic Acid with Octenyl Succinic Anhydride
Octenyl succinic anhydride-modified hyaluronic acid (OSA-HA, 15-$20\%$ degree of substitution, see Figures S1–S3) was synthesized as described previously [25]. In short, 1.25 g HA was dissolved in 50 mL ultrapure water and NaHCO3 was added and mixed for 1 h to yield a 2 M carbonate solution. Afterwards, the pH was adjusted to pH 8.5 with 0.5 M NaOH, and OSA was added dropwise to the HA solution to reach a molar OSA:HA ratio of 50:1. The solution was left to react overnight at room temperature. Then, the reaction product was dialyzed against ultrapure water at 4 °C until the conductivity reached 5 µS/cm and then lyophilized. The degree of substitution for OSA-HA was determined using 1H-NMR. The degree of substitution of OSA-HA, which corresponds to the number of grafted molecules per 100 disaccharide units was calculated by comparing the intensity per proton of the terminal methyl protons on the grafted octenyl succinate groups (0.9 ppm) to that of the methyl protons on native HA (2.0 ppm) [25].
## 2.3. Preparation of Octenyl Succinic Anhydride-Modified Hyaluronic Acid Nanogels
SAAP-148-loaded OSA-HA nanogels were produced at room temperature using a microfluidic chip design described previously [30]. Briefly, SAAP-148 and OSA-HA were dissolved in ultrapure water to a concentration of 1500 µg/mL (10× final peptide concentration) and 500 µg/mL, respectively. The solutions were filled into three gastight fixed Luer lock-tip glass syringes (Prosense, Oosterhout, The Netherlands) mounted on three NE-300 syringe pumps (Prosense) to control the flow rates. The OSA-HA solution was injected into the two outer streams of the microfluidic chip at a flow rate of 0.99 mL/min and the SAAP-148 solution was injected in the inner stream at a flow rate of 0.22 mL/min, resulting a combined flow of 2.2 mL/min. The produced nanogels contained 150 µg/mL SAAP-148 and 500 µg/mL OSA-HA. Freshly prepared nanogels and lyophilized and redispersed nanogels were used, and the concentration of peptide is given as the total peptide concentration present in the sample. Freshly prepared nanogels were stored at 4 °C and used within one week. For lyophilization of nanogels, 1–10 mg/mL PVA or dextran-40 was added in a 1:1 (v/v) ratio to the nanogels. Subsequently, the nanogel solution was frozen with liquid N2 and lyophilized overnight at −52 °C and 0.025 mbar using an Alpha 1–4 LSCbasic freeze dryer (Martin Christ Gefriertrocknungsanlagen, Osterode am Harz, Germany) with RV3 vacuum pump and EMF10 oil mist filter (Edwards, Burgers Hill, UK). Freshly prepared nanogels were diluted and lyophilized nanogels were redispersed in the relevant media before use.
## 2.4. Physicochemical Properties of OSA-HA Nanogels
The average size, polydispersity index (PDI) and zeta potential (ZP) of the OSA-HA nanogels was determined using dynamic light scattering. The size, PDI and ZP measurements of OSA-HA nanogels were performed at a concentration of 150 µg/mL SAAP-148 and/or 500 µg/mL OSA-HA in ultrapure water at 25 °C using a Zetasizer Nano ZS (Malvern Instruments, Worcestershire, UK) equipped with a 633 nm laser and 173° detection optics. Malvern DTS v.6.20 software was used for data acquisition and analysis. Measurements were performed in triplicate for at least three independent sample batch replicates.
## 2.5. Transmission Electron Microscopy
OSA-HA nanogels were visualized using negative stain transmission electron microscopy (TEM). In short, 200 mesh formvar and carbon coated copper EM grids (Agar Scientific, Stansted, UK) were glow-discharged by 0.2 mbar air for 1 min using the glow discharger unit of an EMITECH K950X (Quorum Technologies, Lewes, UK). Three µL of OSA-HA nanogel solution (containing 150 µg/mL SAAP-148 and 500 µg/mL OSA-HA) was applied per glow-discharged grid for 1 min and the grids were blotted to remove excess of sample. Subsequently, the grids were stained on droplets of $2\%$ (w/v) uranyl acetate in water for 1 min, after which excess staining solution was removed with blotting paper. Imaging of the air-dried grids was performed at 120 kV on a Tecnai 12 electron microscope (ThermoFisher, Waltham, MA, USA). A 4k × 4k *Eagle camera* (ThermoFisher) was used to record images at 11,000× magnification.
## 2.6. Quantification of SAAP-148
Quantification of SAAP-148 was performed using an ACQUITY H-class UPLC-MS system (Waters, Milford, MA, USA) with an LCT-premier mass detector (Waters). Chromatographic separation was carried out using an ACQUITY UPLC BEH C18 column (100 × 2.1 mm, 1.7 µm; Waters). The mobile phase consisted of eluent A ($100\%$ ultrapure water) and eluent B ($100\%$ acetonitrile), both containing $0.05\%$ (v/v) TFA. Samples were run with a gradient of 5 to $75\%$ eluent B over 8 min at 0.5 mL/min at 50 °C. The data were analyzed with respect to a calibration curve of SAAP-148 (0.01–0.1 mg/mL) using MassLynx Software V4.2.
## 2.7. Encapsulation Efficiency and Drug Loading of SAAP-148 in OSA-HA Nanogels
The amount of encapsulated SAAP-148 in the OSA-HA nanogels was determined indirectly by measuring the residual amount of peptide present in the aqueous bulk phase after nanogel production. The aqueous bulk phase was obtained by centrifuging the nanogels at 500,000× g for 30 min to ensure sedimentation of the nanogels. Quantification of encapsulation efficiency (EE) was performed in triplicate for three independent sample batch replicates. The calculations of the EE are based on the theoretical drug loading, because only non-encapsulated SAAP-148 could be measured:[1]EE (%)=Total SAAP−148 (µg)−Unencapsulated SAAP−148 (µg)Total SAAP−148 (µg)×$100\%$ The drug loading (DL) is calculated similarly:[2]DL (%)=Encapsulated SAAP−148 (µg)OSA−HA polymer (µg)+Encapsulated SAAP−148 (µg)×$100\%$
## 2.8. Release of SAAP-148 from PVA-Lyophilized OSA-HA Nanogels
In vitro release studies with PVA-lyophilized and redispersed SAAP-148-loaded nanogels were performed in PBS using dialysis membranes (Spectra-Por® Float-a-Lyzer® G2, MWCO 100 kDa, Spectrum Labs, Breda, The Netherlands). Prior to use, dialysis membranes were soaked and washed according to the manufacturer’s protocol to remove all present salts. Next, dialysis membranes were incubated with 1 mg/mL lysozyme egg white for 1 h at 37 °C and 200 rpm using an Innova® $\frac{40}{40}$R orbital shaker (New Bunswick Scientific, Nijmegen, The Netherlands) to reduce binding of peptide to the membrane. Dialysis membranes were washed with ultrapure water and 1 mL of SAAP-148 or SAAP-148-loaded nanogels (300 µg/mL) were loaded inside the dialysis cassette and placed in 6 mL of PBS while continuously shaking at 200 rpm. The temperature was maintained at 37 °C throughout the experiment and 1 mL samples were taken until 5 h and sample volume was replaced by equal volume of PBS. From 5 h onwards, 6 mL samples were taken. Samples were stored at −20 °C until analysis by UPLC. Results are expressed as percentage of SAAP-148 released from the nanogels normalized to diffusion of SAAP-148 solution as a control.
Alternatively, release of SAAP-148 from nanogels was determined by a centrifugation method, where PVA-lyophilized SAAP-148-loaded nanogels were redispersed in 1 mL PBS to a concentration of 150 µg/mL, and these samples were continuously shaken at 37 °C and 200 rpm. The vials were centrifuged at 500,000× g for 30 min at different time points, the supernatants collected and stored at −20 °C until analysis by UPLC. Results are expressed as SAAP-148 released from the nanogels relative to theoretical total amount of SAAP-148 loaded in the nanogels.
## 2.9. Bacteria
In this study, AMR strains of S. aureus (LUH14616; NCCB100829) and A. baumannii (RUH875), and GFP-producing methicillin-resistant S. aureus (MRSA; USA300 JE2) were used. Bacteria were stored in glycerol at −80 °C until use. Prior to experiments, non-GFP producing bacteria were cultured overnight on blood agar plates (BioMérieux SA, Marcy-l’Étoile, France) at 37 °C. On the day of the experiment, 3–5 bacterial colonies were cultured to mid-log phase in 10 mL TSB or BHI for 2.5 h at 37 °C while shaking at 200 rpm in an orbital shaker. Afterwards, bacteria were centrifuged at 1000× g for 10 min, washed with PBS, and resuspended in the preferred medium to the required concentrations based on the optical density at 600 nm. On the contrary, GFP-producing MRSA was cultured overnight in TSB containing 5 µg/mL tetracycline at 37 °C while shaking at 200 rpm in an orbital shaker. On the day of the experiment, the bacterial culture was split 1:333 (v/v) and grown for an additional 2.5 h to mid-log phase at 37 °C before washing steps and optical density measurements were performed.
## 2.10. In Vitro Killing Assay
Mid-log phase bacteria were resuspended in PBS to a concentration of 5 × 106 colony forming units (CFU)/mL. Next, 20 µL bacterial suspension was mixed with 30 µL PBS containing increasing concentrations of SAAP-148, PVA-lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels and 50 µL of filtered, inactivated and centrifuged human plasma (Sanquin, Leiden, The Netherlands) in polypropylene V-shaped 96-well microplates. After incubation for 4 h or 24 h at 37 °C under rotation at 200 rpm using an orbital shaker, 10-fold serial dilutes were made and plated onto MH agar plates to determine the number of viable bacteria. Results are expressed as lethal concentration (LC)99.9, i.e., the lowest concentration of SAAP-148 killing $99.9\%$ of the inoculum.
## 2.11. In Vitro Biofilm Breakdown Assay
Mid-log phase bacteria were diluted to 1 × 107 CFU/mL in BHI to grow 24 h biofilms. Briefly, 100 µL of bacterial suspension was added to each well of a polypropylene flat-bottom microplate and the plates were incubated for 24 h at 37 °C in a humidified environment. The next day, planktonic bacteria were removed from the wells and the biofilms were washed twice with PBS to remove non-adherent bacteria. Then, biofilms were exposed to PBS containing increasing concentrations of SAAP-148, PVA-lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels. The plates were sealed with non-breathable plastic film sealers (Amplistar adhesive plate sealers, Westburg, Leusden, the Netherlands) and incubated for 24 h at 37 °C under continuous rotation using a shaking incubator. Medium controls were used to monitor possible contamination. Finally, the biofilms were washed twice with PBS and the biofilm-residing bacteria were harvested in 100 µL PBS by sonication (40 kHz, 10 min) using a Branson 1800 sonicator (Branson Ultrasonics BV, Ede, The Netherlands). The number of viable bacteria was assessed microbiologically. Results are expressed as biofilm eradication concentration (BEC)99.9, i.e., the lowest concentration of SAAP-148 that killed $99.9\%$ of the biofilm-encased bacteria.
## 2.12. Hemolysis Assay
Whole blood from healthy donors (Sanquin, NVTO128.02, with informed consent) was collected in citrate tubes (BD Vacutainer Systems, Plymouth, UK), centrifuged at 1811× g to pellet the erythrocytes, washed three times using PBS and diluted in PBS to a $2\%$ (v/v) erythrocyte suspension. Next, 25 µL of PBS containing increasing concentrations of SAAP-148, lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels were mixed with 50 µL of pooled human plasma or PBS and 25 µL of $2\%$ (v/v) human erythrocytes in wells of a polypropylene V-shaped microplate. A $5\%$ (v/v) TritonTM X-100 solution in PBS and PBS solution were included as positive and negative control, respectively. The plate was incubated for 1 h at 37 °C and $5\%$ CO2, after which the erythrocytes were pelleted by centrifugation for 3 min at 290× g. The supernatant was transferred to a 96-well flat-bottom plate and the optical density was measured at 415 nm. Calculations of hemolytic activity are based on the following formula:[3]Hemolysis (%)=OD415sample−OD415negative controlOD415positive control−OD415negative control×$100\%$ Results are expressed as effective concentration (EC)50, i.e., the concentration of SAAP-148 resulting in $50\%$ hemolysis. Non-linear regression curves with bottom and top restrictions at 0 an $100\%$ were fit to each individual experiment to determine the medians (and ranges) of the EC50 values.
## 2.13. Cytotoxicity Assays Using Human Primary Skin Fibroblasts and Human Ker-CT Keratinocytes
Human primary skin fibroblasts (kindly provided by Dr. A. El Ghalbzouri, Department of Dermatology, LUMC) were cultured in culture flasks using DMEM supplemented with $1\%$ (v/v) GlutaMAX™, $1\%$ (v/v) pen/strep and $5\%$ (v/v) FBSi. Next, fibroblasts were harvested using $0.05\%$ (w/v) trypsin-EDTA, washed and resuspended to 2 × 105 cells/mL in DMEM supplemented with $1\%$ (v/v) GlutaMAX, $1\%$ (v/v) pen/strep and $0.5\%$ (v/v) human serum. Human keratinocytes of the Ker-CT cell line (ATCC® CRL-4048™, Manassas, VA, USA) were cultured in culture flasks using KSFM supplemented with BPE, EGF, 0.3 M CaCl2 and $1\%$ (v/v) pen/strep. The keratinocytes were harvested using trypsin-EDTA, washed and resuspended to 2 × 105 cells/mL in their culture medium. For both cell types, 20,000 cells were seeded in 96-well culture plates and monolayers formed overnight at 37 °C and $5\%$ CO2. Monolayers were exposed for 4 h or 24 h to increasing concentrations of SAAP-148, PVA-lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels dissolved in the respective seeding medium. $1\%$ (v/v) TritonTM X-100 was used as positive control and medium as negative control. Lactate dehydrogenase (LDH) release from dead cells to the supernatants was detected by the Cytotoxicity Detection Kit (Roche, Basel, Switzerland) and the metabolic activity of the cells was assessed using cell proliferation reagent WST-1 (Roche), both according to the manufacturer’s instructions. Results are expressed as EC50 and non-linear regression curves with bottom and top restrictions at 0 and $100\%$ were fit to each individual experiment to determine the medians (and ranges) of the EC50 values.
## 2.14. 3D Human Epidermal Infection Model
Human skin equivalents (HSEs) were cultured over 14 days using Ker-CT cells as previously described in detail [29]. At least two days before infection, their culture medium was replaced for culture medium without antibiotics. The HSEs were infected with AMR S. aureus or A. baumannii at a concentration of 1 × 105 CFU/model for 1 h at 37 °C and $5\%$ CO2. After infection, the bacterial suspension was removed, the cells were washed with PBS and the HSEs were treated with SAAP-148, PVA-lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels at the desired concentrations in PBS for 4 h after which the supernatants (non-adherent bacteria) were stored on ice, while the HSEs (adherent bacteria) were homogenized using a bead-beater and both fractions were microbiologically assessed. Results are expressed as individual values and medians of three individual measurements performed in duplicate.
## 2.15. Cytotoxicity Assays in a 3D Human Epidermal Model
HSEs were exposed to SAAP-148, lyophilized and redispersed SAAP-148-loaded nanogels or placebo nanogels at the desired concentrations in PBS for 4 h including $1\%$ (v/v) TritonTM X-100 as positive control and PBS as negative control. Afterwards, LDH release from dead cells to the basal medium was detected by the Cytotoxicity Detection Kit according to manufacturer’s instructions. Furthermore, the HSEs were cut out, transferred to 24-well flat-bottom culture plates, and exposed to WST-1 reagent in DMEM medium overnight to determine the metabolic activity of the cells in the models. Read-out of medium solutions without the HSEs was performed according to manufacturer’s protocol. Results are expressed as percentage cytotoxicity or metabolic activity relative to controls.
## 2.16. Confocal Microscopy of an MRSA-Colonized 3D Human Epidermal Model
HSEs were changed to antibiotic-free medium at least two days before infection with GFP-producing MRSA. Bacteria were added to the HSEs at a concentration of 1 × 108 CFU/model, spun down on top of the HSEs for 2 min at 300× g, and incubated for 1 h at 37 °C and $5\%$ CO2 to infect the HSEs. After infection, the bacterial suspension was removed, and the HSEs were treated with TAMRA-SAAP-148 or PVA-lyophilized and redispersed TAMRA-SAAP-148-loaded nanogels in PBS for 4 h after which the HSEs were fixed in $1\%$ (v/v) PFA for 1 h at 4 °C. HSEs were washed and stored in PBS at 4 °C until staining. Cell culture inserts were blocked with PBS containing $1\%$ (w/v) BSA and $0.3\%$ (v/v) TritonTM X-100 (PBT) for 15 min at room temperature. Transparent membranes were removed from plastic inserts with a scalpel and the membranes were incubated with Phalloidin Alexa Fluor 405 diluted 1:50 (v/v) and DAPI diluted 1:100 (v/v) in PBT for 2 h at 4 °C. Membranes were washed three times in PBS and three times in demineralized water, then placed on a glass slide, and treated with ProLong Diamond Antifade mountant. All samples were imaged with a Leica SP-8 upright confocal microscope and 3D images were produced using a Leica SP8 WLL-2 inverted confocal microscope (Leica Microsystems, Wetzlar, Germany).
## 2.17. Statistics
Statistical differences among groups were evaluated by a Kruskal–Wallis test, followed by a Mann–Whitney rank sum test using Graphpad Prism software version 6.0 (Graph Pad Software, San Diego, CA, USA). Differences were considered statistically significant when $p \leq 0.05.$
## 3.1. Physicochemical Properties of Freshly Produced OSA-HA Nanogels Containing SAAP-148
Microfluidics were used to mix increasing concentrations of SAAP-148 with OSA-HA in a fixed ratio to determine the optimal loading conditions. Results revealed very efficient encapsulation of SAAP-148 in these nanogels, with low polydispersity and anionic surface charge (Table 1). Increasing the concentration of SAAP-148 significantly ($$p \leq 0.0021$$) increased particles sizes from 229 nm to 419 nm. OSA-HA nanogels containing 150 µg/mL SAAP-148 were selected for further evaluation, since a particle size between 5 to 100–200 nm, but not exceeding 500 nm, is preferred for targeting bacterial biofilms and to prevent clearance from the blood stream by the complement system [31,32].
## 3.2. Effect of Lyophilization on the Physicochemical Properties and Morphology of SAAP-148-Loaded OSA-HA Nanogels
Lyophilization is necessary for concentrating the OSA-HA nanogels and for their long-term storage. A lyophilization study with 1–10 mg/mL PVA and dextran-40 was performed to select the optimal conditions for lyophilization of the SAAP-148-loaded nanogels. PVA and dextran-40 were selected based on their previous success in lyophilization of OSA-HA nanogels containing Ab-Cath [van Gent and Nibbering, personal communication]. Results revealed that lyophilization without cryoprotectants increased the size ($$p \leq 0.0021$$) and polydispersity ($$p \leq 0.0021$$) of SAAP-148-loaded nanogels upon redispersion in ultrapure water, while the encapsulation efficiency was also lowered by $18\%$ ($$p \leq 0.0091$$), resulting in more negatively charged nanogels ($$p \leq 0.0010$$) with a ZP of –24.4 mV (Table 2). Lyophilization in the presence of 10 mg/mL PVA maintained the size of SAAP-148-loaded nanogels, while minimally increasing the polydispersity ($$p \leq 0.021$$) and only slightly reducing the peptide EE and DL to $93.4\%$ ($$p \leq 0.0091$$), and $21.9\%$ ($$p \leq 0.0045$$), respectively. As expected, the ZP of the nanogels was significantly ($$p \leq 0.0010$$) lowered in the presence of the anionic PVA. Lower concentrations of PVA and 1–10 mg/mL of dextran-40 were not able to protect SAAP-148-loaded nanogels during lyophilization. Additionally, morphology of freshly prepared SAAP-148-loaded and placebo nanogels were compared to these nanogels lyophilized in presence of 10 mg/mL PVA using transmission electron microscopy. Results revealed monodispersed spherical nanogels and confirmed that PVA stabilized the nanogels during the lyophilization process and maintained the morphology of the nanogels (Figure 1). Together, these data indicate that PVA at a concentration of 10 mg/mL protects SAAP-148-loaded nanogels during lyophilization, thus 10 mg/mL PVA-lyophilized SAAP-148-loaded nanogels were selected for further evaluation.
## 3.3. Sustained Release of SAAP-148 from PVA-Lyophilized OSA-HA Nanogels
The release of SAAP-148 from OSA-HA nanogels redispersed in PBS after lyophilization with 10 mg/mL PVA was evaluated at 37 °C over a time period of 72 h by two methods, namely dialysis and centrifugation. Results from the dialysis study showed that SAAP-148 was released from the nanogels in biorelevant medium with a burst release of $16\%$ in the first hour followed by gradual release up to $41\%$ within 72 h, indicating a sustained release of SAAP-148 from OSA-HA nanogels over multiple days (Figure 2a). As a control, it was shown that diffusion of SAAP-148 in solution was slowed by the dialysis membrane, but all peptide was recovered within 72 h (Figure S4). Evaluation of the release-exponent (n) of the median percentages of SAAP-148 cumulatively released from the OSA-HA nanogels using the Korsmeyer–Peppas model revealed that $$n = 0$.2109$ with R2 = 0.9641 (Figure 2b). This n-value is below 0.5, and therefore suggests that the mechanism of drug release followed a quasi-Fickian process [33], indicating partial diffusion and controlled release of SAAP-148 from the OSA-HA nanogels. The centrifugation method confirmed the burst release of SAAP-148 with $36\%$ of SAAP-148 released in the first hour with no further release for up to 72 h (Figure 2c). Both methods indicated that SAAP-148 was released to a limited extend from the nanogels, therefore the swelling of the nanogels in PBS was evaluated. Results showed that the nanogels expand over time, more than doubling in size within 4 h, but not resulting in complete dissociation of the nanogels withing 96 h (Figure 2d). This size expansion is combined with a slow increase in outer surface charge over time (Figure 2e).
## 3.4. Antimicrobial Activities of PVA-Lyophilized SAAP-148 OSA-HA Nanogels
The antimicrobial activities of SAAP-148-loaded nanogels redispersed in PBS after lyophilization in presence of 10 mg/mL PVA were compared to SAAP-148 against planktonic and biofilm-residing AMR bacteria. Results revealed that SAAP-148-loaded nanogels were 2-fold less effective in killing planktonic AMR S. aureus and A. baumannii after 4 h exposure compared to SAAP-148 in PBS containing $50\%$ (v/v) plasma; however, after 24 h of exposure the antimicrobial activities were identical (Table 3). In addition, SAAP-148-loaded nanogels equally well eradicated AMR S. aureus biofilms in 24 h but were slightly less effective against AMR A. baumannii biofilms compared to SAAP-148 in PBS. Placebo nanogels did not show antibacterial and antibiofilm activities.
## 3.5. Hemolytic and Cytotoxic Activities of PVA-Lyophilized SAAP-148 OSA-HA Nanogels
Next, the hemolytic and cytotoxic activities of SAAP-148-loaded nanogels redispersed in the relevant medium after lyophilization using 10 mg/mL PVA were compared to SAAP-148. Results revealed that encapsulation of SAAP-148 in OSA-HA nanogels decreased the peptide’s hemolytic activity 1.9–2.5-fold and reduced the cytotoxic activities 2.9–3.6-fold and 1.5–2.3-fold for human primary skin fibroblasts and Ker-CT keratinocytes, respectively (Table 4). Moreover, the hemolytic activity of SAAP-148 was reduced dramatically in presence of $50\%$ plasma and the cytotoxic activities of SAAP-148 to human primary skin fibroblasts and Ker-CT keratinocytes were slightly increased with time. Together, these data indicate that encapsulation of SAAP-148 in OSA-HA nanogels reduced the peptide’s hemolytic and cytotoxic activities >2-fold.
## 3.6. SAAP-148-Loaded OSA-HA Nanogels Protected with PVA during Lyophilization Effectively Eradicate AMR S. aureus and A. baumannii Infections from a 3D Human Epidermal Model
The efficacy of SAAP-148-loaded nanogels upon reconstitution in PBS after lyophilization using 10 mg/mL PVA was evaluated in a 3D human epidermal model colonized with AMR S. aureus or A. baumannii. Results revealed that SAAP-148-loaded nanogels dose-dependently eradicated both bacterial strains colonizing the 3D human epidermal model to the same extent as SAAP-148 in solution (Figure 3). Exposure of the infected 3D human epidermal model to the highest dose of placebo nanogels was without antibacterial effect.
## 3.7. SAAP-148-Loaded OSA-HA Nanogels Protected with PVA during Lyophilization Reduce Cytotoxic Activities of the Peptide in a 3D Human Epidermal Model
Moreover, the cytotoxic activities of SAAP-148-loaded nanogels upon reconstitution in PBS after lyophilization using 10 mg/mL PVA were evaluated in a 3D human epidermal model. Results revealed that SAAP-148 in PBS dose-dependently reduced the metabolic activity of the eukaryotes in the model and simultaneously increased LDH release from these cells to the basal medium, while encapsulation of SAAP-148 in OSA-HA nanogels lyophilized with 10 mg/mL PVA prevented a reduction in metabolic activity of the cells in the models and reduced LDH release from these cells (Figure 4). Unexpectedly, placebo nanogels increased the metabolic activity of the cells in the model, but did not have any effect on the LDH release from these cells.
## 3.8. TAMRA-SAAP-148-Loaded OSA-HA Nanogels Protected with PVA during Lyophilization Penetrate into the Superficial Layers of a 3D Human Epidermal Model
Finally, confocal microscopy was used to image the 3D human epidermal model colonized with GFP-producing MRSA and exposed to TAMRA-SAAP-148-loaded nanogels or TAMRA-SAAP-148 to analyze their penetration capability into the cell layers of this model. It was shown that the 3D human epidermal model had a thickness of about 25 µm, similar to the non-colonized model (Figure S5), and that MRSA and TAMRA-SAAP-148-loaded nanogels localize only in the superficial layers of the 3D human epidermal model upon 4 h incubation (Figure 5a). Notably, labeling of SAAP-148 with TAMRA reduced the efficacy of the peptide towards planktonic GFP-producing MRSA (Figure S6). For confocal microscopy, a suboptimal concentration (5 µM) of TAMRA-SAAP-148 was used to allow visualization of both peptide and bacteria. Results revealed that redispersed PVA-lyophilized TAMRA-SAAP-148 nanogels seemed to partly eradicate MRSA from the superficial layers of the model to the same extend as TAMRA-SAAP-148, as indicated by the reduction in MRSA-GFP fluorescent signal compared to PBS (Figure 5b–g). In addition, in both cases TAMRA-SAAP-148 was internalized in a substantial number of cells in these superficial cell layers. Moreover, it was observed that TAMRA-SAAP-148 and MRSA co-localized, confirming a MRSA-bound fraction of TAMRA-SAAP-148. Together, these data indicate that both MRSA and TAMRA-SAAP-148 localize in the superficial cell layers, but that the capability of TAMRA-SAAP-148 nanogels to penetrate deeper layers of the 3D human epidermal model is limited.
## 4. Discussion
Antimicrobial peptides such as SAAP-148 are promising alternatives to current antibiotics for the treatment of bacterial wound infections. However, the cutaneous use of SAAP-148 is hampered by limitations related to its peptidic nature resulting in low bioavailability in the wound environment due to protein binding and/or degradation by proteases along with cytotoxicity due to its cationic nature, altogether resulting in a narrow therapeutic window [10,12]. It is hypothesized that these limitations can be overcome by using nanogels as a drug delivery system. Here, we describe the use of a nanogel formulation for cutaneous application with the aim to decrease cytotoxicity, while maintaining antimicrobial activities, thereby increasing the selectivity index of SAAP-148.
OSA-HA nanogels encapsulating 150, 175 and 200 µg/mL of SAAP-148 were prepared and characterized. These anionic nanogels ranged from 229 to 419 nm in size, with increased SAAP-148 concentrations being positively correlated with increased nanogel sizes. The use of microfluidics allowed precise control during the production of the nanogels [34], thus resulting in a low polydispersity of the nanogel solutions. All SAAP-148-loaded nanogels showed a more neutral ZP compared to placebo nanogels in accordance with previous reports [16,35], suggesting the presence of surface-bound peptide in addition to encapsulated peptide. Moreover, the cationic SAAP-148 was very efficiently encapsulated in these anionic nanogels, resulting in a high DL of more than $20\%$ (w/w). This DL is much higher than that achieved for most existing nanomedicines (DL < $10\%$) [36], which further emphasizes the potential of OSA-HA nanogels as high AMP-loading nanomedicine. Lyophilization of these nanogels using 10 mg/mL PVA maintained their optimal physicochemical properties upon reconstitution in ultrapure water, while dextran-40 was not effective in maintaining the small size of the nanogels. These findings contrast with those of our previous lyophilization study of OSA-HA nanogels loaded with snake cathelicidin Ab-Cath [van Gent and Nibbering, personal communication], where both PVA and dextran-40 were effective cryoprotectants. We hypothesize that the lower molecular weight, lower net charge and higher hydrophilicity of SAAP-148 compared to Ab-Cath could potentially explain the suboptimal protection of SAAP-148-loaded nanogels by dextran-40.
It is hypothesized that release of peptides from nanogels such as OSA-HA is triggered by the presence of salts, changes in pH and/or by degradation of the polymer [22]. In this study, release of SAAP-148 from OSA-HA nanogels was evaluated in PBS and by using the dialysis method it was revealed that SAAP-148 was released in a sustained manner reaching a total release of 37–$41\%$ of SAAP-148 within 72 h, as was also demonstrated to be the maximum released amount found by using the centrifugation method. Contradictorily, using the centrifugation method this fraction of SAAP-148 was released immediately, which is most likely the effect of physical stress during centrifugation that forces not tightly bound SAAP-148 out of the nanogel. The release rate of SAAP-148 from OSA-HA nanogels was slower than that of DJK-5 with $80\%$ release in 5 h and complete release in 48 h [16], but very comparable to that of novicidin with $55\%$ release in 72 h followed by a sustained release phase over 12 days [27]. Moreover, in 72 h, SAAP-148-loaded nanogels doubled in size and became more neutrally charged, indicating only partial dissociation of the nanogels. Therefore, we believe that SAAP-148 release from OSA-HA nanogels is triggered by presence of PBS, but that approximately $60\%$ of SAAP-148 remains associated with the HA polymer likely due to strong electrostatic and hydrophobic interactions. The possibility of SAAP-148 binding to the dialysis membrane or plastic was taken into account by correcting for the total recovery of SAAP-148 solution, which ranged from 65–$96\%$ (Figure S4). Nevertheless, the maintained antimicrobial activity of SAAP-148-loaded nanogels at 24 h exposure in combination with 30–$41\%$ SAAP-148 released in this time period implies that the HA-associated SAAP-148 fraction remains antimicrobial.
The capability of these OSA-HA nanogels to shield the cationic charge of SAAP-148 resulting in anionic nanogels is important to improve the safety of this peptide, since an increase in the net charge of such peptides has been linked to increased hemolysis and/or cytotoxicity to eukaryotic cells [37,38]. The improved safety of SAAP-148 upon encapsulation in OSA-HA nanogels was confirmed for both 4 h and 24 h of exposure to a range of eukaryotic cells present in the wound environment, i.e., human erythrocytes, human primary skin fibroblasts and human keratinocytes. This is in line with previous studies indicating that OSA-HA nanogels are particularly effective at shielding the cationic charges of encapsulated peptides [27,28]. Moreover, the sustained release of SAAP-148 from OSA-HA nanogels could play a role in the reduced cytotoxicity upon formulation, as cells might tolerate exposure to increasing concentrations of peptide released from the nanogels over time compared to the total dose directly available when using the peptide in solution. Indeed, the improved safety of SAAP-148-loaded nanogels compared to SAAP-148 is most pronounced (2.2–3.6-fold) at 4 h exposure but is still observed at 24 h (1.5–2.9-fold), and can be related to the sustained release of SAAP-148 (22–$39\%$ at 4 h; 30–$41\%$ at 24 h). Notably, the enhanced safety was also proven in a 3D human epidermal model that is more resistant to cytotoxic activities of SAAP-148 [29].
Importantly, the antimicrobial activities against planktonic, biofilm-residing and skin-colonized AMR S. aureus and A. baumannii were maintained for SAAP-148-loaded OSA-HA nanogels, but because of its sustained release required up to 24 h of exposure to reach the same antimicrobial activity as SAAP-148. For future studies, it would be of interest to investigate whether these effects also hold for polymicrobial communities of S. aureus and A. baumannii, as co-infections are very common in diabetic wounds [39]. Together, the improved safety combined with maintained antimicrobial activity resulted in an up to 2.9-fold improvement in the selectivity index for SAAP-148 when encapsulated in OSA-HA nanogels. A similar improvement in selectivity index was previously reported for the peptides DJK-5, LBP-3 and novicidin after encapsulation in OSA-HA nanogels [16,27,28], further emphasizing the applicability of this delivery system for a range of AMPs. Potentially, this selectivity index could be further improved by actively targeting the bacteria and/or site of infection. This could be achieved by functionalization of the HA polymer with ligands of the bacterial surface [40] or by rendering the nanogel responsive to stimuli of the bacterial microenvironment, such as pH changes or presence of enzymes and molecules associated with bacterial infections [41].
Markedly, confocal microscopy showed that GFP-producing MRSA infected the 3D human epidermal model only in the superficial layers and that TAMRA-SAAP-148 nanogels located in the same layers, indicating favorable localization of TAMRA-SAAP-148 to eradicate the bacterial skin infection. Notably, F-actin breakdown and DNA degradation is part of the keratinocyte differentiation process occurring in the 3D human epidermal model [42], which explains the suboptimal staining of the superficial layers (e.g., stratum corneum) in the model. Moreover, it is important to emphasize that the GFP-labeled MRSA is genetically different from the AMR S. aureus, although they were similarly susceptible to SAAP-148 (Figure S6). Their differences in infection efficiency and penetration capability were not further investigated in the present study. In addition, labeling of SAAP-148 with TAMRA reduced the efficacy of the peptide towards the GFP-producing MRSA from 6.4 µM to 25.6 µM (Figure S6). This was expected, as reduced antimicrobial activities of AMPs upon fluorescently labeling have been reported previously [43]. Together, confocal microscopy revealed that TAMRA-SAAP-148 nanogels as well as TAMRA-SAAP-148 did not penetrate deeper layers of the model. In the future, using a wounded skin model should be considered, as used by others [44,45,46], which might facilitate penetration of SAAP-148-loaded nanogels into deeper layers of the tissue and allow for studying wound healing processes.
## 5. Conclusions
In conclusion, OSA-HA nanogels are a promising delivery system for cutaneous application of SAAP-148 to treat skin wound infections. SAAP-148-loaded nanogels exhibited excellent physicochemical properties, including a small size (219 nm), low polydispersity (PDI = 0.03), anionic surface charge (ZP = −14.5 mV), high encapsulation efficiency ($98.7\%$) and drug loading capacity ($22.8\%$) and a sustained release profile (37–$41\%$ released in 72 h). Moreover, OSA-HA nanogels maintained the antimicrobial activity of SAAP-148 against AMR bacterial strains, while reducing its cytotoxicity against eukaryotic cells present in the wound environment >2-fold, thus improving the selectivity index of SAAP-148 up to 2.9-fold in conditions relevant for skin wound infections. Although the nanogels showed excellent performance using in vitro models, SAAP-148′s proteolytic stability after encapsulation remains to be investigated using proteases. Moreover, more extensive evaluation using in vivo models would allow for a better understanding of the delivery system’s pharmacokinetic and -dynamic properties. Additionally, development of a macroscale delivery system, such as a gel, cream or ointment, containing the SAAP-148-loaded OSA-HA nanogels would help assess the potential of this nanoscale delivery system as an antimicrobial treatment for clinical applications.
## 6. Patents
The SAAP-148 peptide described in the present study is patented by the Leiden University Medical Center (patent number WO2015088344; the co-inventors are J.W.D. and P.H.N.).
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|
---
title: Assessing Handrail-Use Behavior during Stair Ascent or Descent Using Ambient
Sensing Technology
authors:
- Yusuke Miyazaki
- Kohei Shoda
- Koji Kitamura
- Yoshifumi Nishida
journal: Sensors (Basel, Switzerland)
year: 2023
pmcid: PMC9967829
doi: 10.3390/s23042236
license: CC BY 4.0
---
# Assessing Handrail-Use Behavior during Stair Ascent or Descent Using Ambient Sensing Technology
## Abstract
The increasing geriatric population across the world has necessitated the early detection of frailty through the analysis of daily-life behavioral patterns. This paper presents a system for ambient, automatic, and the continuous measurement and analysis of ascent and descent motions and long-term handrail-use behaviors of participants in their homes using an RGB-D camera. The system automatically stores information regarding the environment and three-dimensional skeletal coordinates of the participant only when they appear within the camera’s angle of view. Daily stair ascent and descent motions were measured in two houses: one house with two participants in their 20s and two in their 50s, and another with two participants in their 70s. The recorded behaviors were analyzed in terms of the stair ascent/descent speed, handrail grasping points, and frequency determined using the decision tree algorithm. The participants in their 70s exhibited a decreased stair ascent/descent speed compared to other participants; those in their 50s and 70s exhibited increased handrail usage area and frequency. The outcomes of the study indicate the system’s ability to accurately detect a decline in physical function through the continuous measurement of daily stair ascent and descent motions.
## 1. Introduction
Over the past few decades, the geriatric population has been increasing worldwide. The WHO states that between 2015 and 2050, the population of people with ages equal to and greater than 60 years will rise from $12\%$ to $22\%$ [1]. In Japan, the percentage of elderly was $28.8\%$ as of 1 October 2020. By 2065, the age of one in every 2.6 people will be equal to or greater than 65, and that of one in 3.9 will be equal to or greater than 75 [2]. Elderly people rarely make a sudden transition from a healthy state to one that requires nursing care, often going through an intermediate stage referred to as frailty, which gradually leads to a state of dependency [3,4]. It has also been reported that a healthy state of a frail individual can be restored with appropriate interventions [5].
In Japan, a questionnaire-based frailty assessment, referred to as the “Kihon Checklist”, has been used as an indicator for frailty in the elderly [6,7]. This checklist consists of a group of 25 questions and is validated as a frailty index in Japan as well as in several other countries [8,9,10]. One question on this list is whether the person can ascend or descend stairs without using handrails or walls. Stair ascent or descent activities are known to be the most difficult physical task of daily activities for the elderly [11]. Therefore, assessing the characteristics of stair ascent and descent activities and handrail dependency in elderly people is significant to determine the frailty index.
However, the questionnaire-based frailty assessment requires the elderly to fill in the questionnaire voluntarily, regularly, and consciously, which is burdensome. Automated constant and spontaneous assessment of stair ascent and descent in daily life as well as quantitative frailty assessment based on motion measurement would help to reduce the burden and detect declines in physical functions in the elderly through long-term measurement.
To realize a system that can constantly and naturally assess stair ascent and descent in the daily life of elderly people, the Internet of Things (IoT) and machine learning (ML) have been employed. Markerless motion capture systems that include a depth camera are useful for the measurement of daily activities. Daily activities of the elderly have been captured using Microsoft Kinect v2 (Microsoft co.) to identify behavioral parameters that best distinguish between high- and low-fall risk individuals [12]. Kinect was deployed in the apartments of the elderly in an independent living facility to analyze gait characteristics by continuous in-home gait measurement [13]. Prediction of falls from pre-fall changes was explored based on the Kinect-recorded gait parameters over 10 years for the residents of independent living apartments [14]. A health monitoring system based on Kinect was developed to categorize movements during walking, standing up, and sitting down as normal or unusual [15]. Furthermore, a dataset of the daily activities of the elderly was developed, wherein the daily activities of 50 elderly were measured using Kinect v2 and classified into 55 actions [16]. We previously developed an “elderly behavior library” [17,18,19], which includes RGB-D videos, that showed the natural behavior of elderly people when using consumer products that were placed in their residences or residential facilities. We then analyzed the relationship between the natural standing behavior of elderly people and classes of standing aids as well as the physical and cognitive abilities that help prevent injury due to falling indoors [20,21]. Thus, the integration of ambient sensing into IoT devices has helped to record the daily activities of elderly people in their homes in a non-invasive manner and evaluate their physical functions according to the recorded patterns. However, to the best of the author’s knowledge, no studies have attempted to assess frailty based on the daily measurements of stair ascent and descent activities or dependence on the use of handrails. These parameters are closely related to frailty assessment.
Therefore, we developed an ambient sensing system for human behavior that could analyze the characteristics of ascending and descending stairs and handrail use behavior in daily life. The aim of this study was to construct an ambient sensing system that could non-invasively, continuously, and quantitatively assess stair ascending and descending characteristics for the elderly, and subsequently identify handrail gripping points. This study is the first to continuously measure the stair ascent and descent behavior as well as the handrail use in a natural living environment on a daily basis
## 2.1. Automatic Measurement of Three-Dimensional Human Behavior and Household Environment Using Depth Cameras
Azure Kinect DK (AK) (Microsoft Co.) was used as the depth camera. AK can estimate 32 three-dimensional (3D) skeletal points of the body skeleton in the camera coordinate system based on the depth information in conjunction with the Body Tracking Software Development Kit (SDK). In the case of long-term and continuous measurement of everyday activities with AK, it is ideal to store the skeletal coordinates only when a person appears in the angle of view. Therefore, we constructed a system that automatically stores the 3D coordinates of the skeleton and the RGB image of the depth camera viewpoint when a person appears and their skeleton is recognized. The sampling rate was 15 Hz.
## Observation Environment for Stair Ascending or Descending Activities
The daily stair ascent or descent activities were measured in two separate houses, labeled Environment 1 and Environment 2. Environment 1 was a two-story house with four people living in it including a male in his 20s (p1), female in her 50s (p2), male in his 50s (p3), and a female in her 20s (p4). Environment 2 had two participants, a male in his 70s (p5) and a female in her 70s (p6). In Environment 1, a method for analyzing the stair ascent or descent activities (described in Section 2.3) was developed. The same method was integrated for analyzing participants in a pre-frail state in Environment 2.
In Environment 1, the AK recorder was installed on a staircase with a handrail, as shown in Figure 1. The three-dimensional motion was measured during staircase ascent and descent using the handrail (Figure 1a). The data acquired in this environment consisted of 402 ascending and descending activities. In Environment 2, the AK recorder was installed, as shown in Figure 1b. The data acquired in Environment 2 consisted of 22 ascent and descent activities. The participant labels (p1/p2/p3/p4/p5/p6), ascent and descent labels (up/down), and labels for objects held during ascent and descent (none/material/phone) were manually assigned to each series of obtained data. When analyzing the ascending and descending data, the data with the “none” label were included.
The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Tokyo Institute of Technology Human Participants Research Ethics Review Committee (protocol code 2019150) and the AIST Ergonomics Experiment Review Committee (protocol code 2016-659H).
## 2.3.1. Definition of Stair Local Coordinate System
A local coordinate system that describes the stair ascent and descent motions were defined by setting the origin on the handrail and orthonormal–orthogonal basis from the depth map obtained from AK. Then, the stair ascending and descending motion data expressed in the camera coordinate system was transformed into a stair local coordinate system. This method helps compare human motions when ascending and descending stairs and behavioral patterns of using handrails in different environments.
## 2.3.2. Obtaining 3D Coordinates
The 3D coordinates in the camera coordinate system of an arbitrary point on the depth map extracted from AK were obtained using the following approach: The depth map was obtained from AK in a 16-bit image format and then stored in each pixel. The 3D coordinates, p=[X,Y,Z], in real space for an arbitrary point C=[u,v] on the depth map obtained using the internal parameters A of the depth camera are used in Equation [1]. [ 1](uv1)Pz=Ap where Pz represents the pixel value of the depth map. Subsequently, the three-dimensional coordinates in the environment were obtained using Equation [1].
## 2.3.3. Orthonormal Basis for the Stair Coordinate System
The coordinate axes of the stair coordinate system were derived from the three-dimensional coordinate points of the handrails and walls of the staircase. The stair coordinate system shown in Figure 2 was defined based on the camera coordinate system. The longitudinal direction of the handrail in the right-hand coordinate system was defined as the x-axis of the stair coordinate system, the orthogonal downward direction as the z-axis, and the orthogonal lateral direction as the y-axis.
The start and end points of any line segment in the longitudinal direction of the handrail were selected from the depth map and converted to three-dimensional coordinates using Equation [1] to obtain the longitudinal vector nx of the handrail.
Next, the y-plane and its normal vector ny′ were obtained using the following approach. A rectangular region was manually selected from the depth map wall surface, and the 3D coordinate point cloud P=[X,Y,Z] in the region was obtained using the same approach. P follows Equation [2]. [ 2][X,Y,1][abd]=−cZ+E where E is the distance from the y-plane to each point. In this case, because the plane that is measured by the camera is not always perpendicular to the camera, constants a and c and constants a, b, and d are assumed so that c ≠ 0.
Solving this using the least-squares method yields Equation [3], where P′=[X,Y,1], so we obtain the following. [ 3][abd]=−(P′TP′)−1P′TZ The wall normal vector ny′ can be defined using a and b, as shown in Equation [4]. [ 4]ny′=[abc] Then, the vectors nx and ny′ are normalized, and nz is calculated from Equation [5]. [ 5]nz=nx×ny′ Because ny′ is not always orthogonal to nz and nx, the value of ny can be determined again using Equation [6] to define an orthonormal basis for the staircase coordinate system. [ 6]ny=nz×nx
The edge point of the handrail on the depth map was selected as the stair coordinate system origin P0. A homogeneous coordinate transformation matrix was then defined using P0 and the orthonormal basis of the staircase coordinate system. The rotation matrix R is defined using Equation [7] according to nx,ny,nz, and the homogeneous transformation matrix H is defined using Equation [8]. The stair ascent and descent motions measured in the camera coordinate system were transformed into the stair coordinate system using H. [7]R=[nxTnyTnzT] [8]H=[RP001]
## 2.3.4. Calculating Stair Ascent and Descent Speed
Kawai et al. demonstrated that walking speed in daily life reflects physical function and that walking speed may be used to screen frailty [22]. Therefore, measuring the speed of ascending and descending stairs in daily life helps assess frailty. Each participant’s stair ascent/descent speed was defined as the average speed in the range $x = 0$–1000 mm using the pelvis point. T-tests were conducted to estimate the difference between the ascent and descent speeds within each participant.
## 2.4. Determining Handrail Grasping Point
To quantitatively assess the dependence on handrails, which is one of the basic checklist items for frailty assessment, we developed a method to calculate the handrail grasping ratio when ascending and descending stairs. The Azure Kinect Body Tracking SDK defines three skeletal coordinates for each hand: HAND, HANDTIP, and THUMB [23]. The respective coordinates were Phand, Phandtip and Pthumb, and it was assumed that the grasping point coincides with the center-of-gravity coordinates Pgp of those points. [ 9]Pgp=13(Phand+Phandtip+Pthumb)=(PgpxPgpyPgpz) Among the 402 ascent and descent motions, 10 were extracted as sample motions, one with and another without grasping the handrail. The images stored in the time frames of each motion were manually checked and labeled as either “grasped” or “not grasped” (Figure 3).
After extracting the motions in the range 0 < Pgpx < 1000 as the handrail’s straight part, a decision tree model was constructed for the classification of labels as either “grasped” or “not grasped” by using Pgpy and Pgpz as the predictors. Table 1 shows the resulting confusion matrix that was trained using the 5-segment cross-validation. The model yielded a classification accuracy of $86.9\%$ (Figure 4). A grasp classification model for Environment 2 was also created for the ascending and descending data in p5–p6 using the same method, as shown in Figure 5. The decision tree model with a classification accuracy of $85.2\%$ was used as the grasp classification model (Table 2).
## 2.5. Evaluating Handrail Grasping Area and Frequency
The ratio of handrail grasping in the stair ascent and descent activities was calculated to evaluate the degree of dependence on handrails in the assessment of frailty. The grasp classification model was applied to all ascending and descending activities without a single HAVE_LABEL, and the ratio of frames to be grasped for the total number of frames (n) was calculated for each participant.
In addition, the area and frequency of the handrail grasping were visualized as a heat map. The developed method highlighted the grasping points of the handrail by transforming Pgp to the camera coordinate system in the frames where grasping was estimated and then projected it onto the RGB image using the perspective projection method.
## 3.1. Stair Ascent and Descent Speed
As shown in Figure 6 and Table 3, the average ascent speeds of p1–p4 were within the range of ±$10\%$ and were almost identical. Conversely, the ascent speeds of p5 and p6 were less than the ascent speed of p1 at a significance level of $1\%$. As shown in Figure 7, the descent speeds of p1–p4 were almost the same, and those of p5 and p6 were lower than that of p1 at a significance level of $5\%$.
In addition, the speeds of ascent and descent tended to differ according to the participants, with descent speeds higher than the ascent speeds in the cases of p1–p5, while the descent speed of p6 was significantly slower than the ascent speed at a significance level of $5\%$.
## 3.2. Handrail Grasping Ratio and Grasping Area
From the handrail grasping ratios shown in Table 4 and Table 5 and the handrail grasping area visualized in Figure 8, p1, a male in his 20s, showed the smallest handrail grasping ratio when ascending and descending stairs in Environment 1. Therefore, p1 almost entirely ascended and descended the stairs without using a handrail, indicating that he is not dependent on a handrail. Second, p3, a male in his 50s, was less dependent on the handrail, and his handrail grasping ratio tended to increase slightly when descending. P4, who is in her 20s, held the handrail more while ascending than while descending. However, her handrail grasping position was concentrated locally, which indicates her preference for using the handrail. Furthermore, p2, who is in her 50s, held the handrail the most among the participants in Environment 1, both when ascending and descending. The grasping ratio increased approximately twice as much when descending, and the grasping positions were evenly distributed throughout the handrail, indicating an increase in handrail dependence.
The handrail grasping ratios of p5–p6 in their 70s in Environment 2 were generally higher than those of the participants in their 20s (p1, p4) and 50s (p2, p3) in Environment 1. Furthermore, p5 and p6 grasped the handrail for approximately $80\%$ of the time when ascending, and almost all areas of the handrail were red, indicating that they were significantly dependent on the handrail when ascending the stairs. When descending the stairs, the handrail dependence of p5 decreased slightly, while that of p6 increased further, indicating that p6 tended to depend on the handrail even more.
## 4. Discussion
We developed a method to quantitatively assess the stair ascent/descent speed and handrail dependence during stair ascent/descent, with the aim of frailty assessment [6,9,10,24]. Conventional frailty assessments were conducted by a self-completion questionnaire that was performed based on measurements of daily activities in homes. Although the physical function during stair ascent and descent has been conventionally evaluated in a laboratory environment and a detailed biomechanical evaluation is possible [25,26,27,28], to the best of the author’s knowledge, this study is the first to continuously measure the stair ascent and descent behavior as well as the handrail use in a natural living environment on a daily basis. In some studies [29,30], an inertial measurement unit was attached to the body to serve as an approach that integrated wearable sensors. However, the systems cannot assess the degree of handrail dependence, which is important for frailty assessment. The developed system used both the 3D human skeletal information and point cloud information of the environment based on the information recorded using an RGB-D camera. This further ensures that the system can measure human movements and analyze the relationship between the environment and product use behavior (i.e., the degree of handrail dependence).
The measured ascent and descent speeds of p5–p6 in their 70s were significantly less than those of p1–p4. In addition, p5 and p6 can be presumed to be in a pre-frail state, given that each of their answers to the “Kihon Checklist” had a score of four. This indicates that the physical functions of p5 and p6 were less compared to those of the participants in their 20s and 50s. Furthermore, the handrail grasping ratios of p5 and p6 tended to be higher than those of p1–p4.
In addition, the descent speed of p6 was significantly less than the ascent speed. Reeves et al. showed that elderly people may meet the demands of unaided stair ascent by adopting several alternative strategies to compensate for their reduced musculoskeletal capabilities [31]. The stair descent activity helps improve physical functions because of the high muscular load [25,28]. Therefore, it is important to focus on the descent movement and evaluate the degree of dependence on the handrails for frailty assessment. In Environment 1, the grasping ratio was higher in p2, a female participant in her 50s, than in the other participants. Furthermore, her handrail dependence was particularly high when descending. Therefore, a quantitative evaluation of the handrail dependence of the physical functions of participants who were not in a state of pre-frailty and were considered to be healthy at the present stage can represent the potential level of frailty. The results indicate that it is important to distinguish between the ascent and descent movements and that the degree of dependence on handrails during the descent can be used to evaluate frailty.
## Limitations and Future Scope
This study developed a system that can assess the daily stair ascent and descent activities and the degree of dependence on handrails. Long-term measurement is necessary to detect a decline in physical function from the daily stair ascent and descent activities. In this study, measurements were taken over a period of two months. Nevertheless, even longer periods of measurement will be required to detect a decline in physical function. To capture changes in physical function over a long period of time, it is necessary to develop a detection system based on machine learning that can detect changes in handrail dependence and automatically diagnose frailty in the daily environment.
Additionally, the relationship between stair and handrail design and stair ascent and descent characteristics should be clarified by conducting measurements in a variety of environments in the future. This will enable a suitable product design of stairs and handrails to accommodate changes in the physical characteristics of the elderly.
Furthermore, the system could be expanded to biomechanical assessment. In this study, we focused on assessing the stair ascending/descending speed and handrail dependence corresponding to frailty assessment using the basic checklist, a self-administered questionnaire currently in use. However, because the system acquires the skeletal coordinates of the entire body, it will be possible to analyze the feature motions of stair ascent and descent motions in the future. The stair ascent and descent activities are known to be the most difficult physical tasks in daily activities [11], and thus they have been studied widely under laboratory conditions [27,32,33,34,35]. However, it is difficult to reproduce the natural behavior of the elderly in a controlled laboratory environment. The system developed in this study will enable a detailed assessment of frailty based on the biomechanical analysis of actual stair ascent and descent activities in a real-life environment.
## 5. Conclusions
This study developed a system to automatically and continuously measure and analyze the ascent and descent motions and handrail-use behaviors in an actual ambient living environment. An RGB-D camera was used in addition to the conventional questionnaire-based frailty assessments. Daily stair ascent and descent motions were measured in two separate houses, with two participants in their 20s and two in their 50s in the first house, and two participants in their 70s in the second house. The outcomes of the study indicated that the participants in their 70s exhibited a decreased stair ascent/descent speed compared to the other participants, and those in their 50s and 70s exhibited an increased handrail usage area and frequency, particularly during descent. The results indicate the potential of this system to detect physical frailty by ambient and continuous measurement of the daily stair ascent and descent motions.
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|
---
title: Antiseptic-Loaded Casein Hydrogels for Wound Dressings
authors:
- Leonor Vasconcelos Garcia
- Diana Silva
- Maria Madalena Costa
- Henrique Armés
- Madalena Salema-Oom
- Benilde Saramago
- Ana Paula Serro
journal: Pharmaceutics
year: 2023
pmcid: PMC9967843
doi: 10.3390/pharmaceutics15020334
license: CC BY 4.0
---
# Antiseptic-Loaded Casein Hydrogels for Wound Dressings
## Abstract
Chronic wound treatment accounts for a substantial percentage of the medical expenses worldwide. Improving and developing novel wound care systems can potentially help to handle this problem. Wound dressings loaded with antiseptics may be an important tool for wound care, as they inhibit bacterial growth at the wound site. The goal of the present work was to investigate the potential of using casein hydrogel dressings loaded with two antiseptic drugs, Octiset® or polyhexanide, to treat chronic wounds. Casein-based hydrogels are inexpensive and have several properties that make them suitable for biomedical applications. Two types of casein were used: casein sodium salt and acid casein, with the formulations being labelled CS and C, respectively. The hydrogels were characterised with respect to their physical properties (swelling capacity, water content, morphology, mechanical resistance, and stability), before and after sterilisation, and they showed adequate values for the intended application. The hydrogels of both formulations were able to sustain controlled drug-release for, at least, 48 h. They were demonstrated to be non-irritant, highly haemocompatible, and non-cytotoxic, and revealed good antimicrobial properties against *Staphylococcus aureus* and Pseudomonas aeruginosa. Steam-heat sterilisation did not compromise the material’s properties. The in vivo performance of C hydrogel loaded with Octiset® was evaluated in a case study with a dog. The efficient recovery of the wounds confirms its potential as an alternative for wound treatment. To our knowledge, this is the first time that wound dressings loaded with Octiset®, one of the most efficient drugs for wound treatment, were prepared and tested.
## 1. Introduction
Chronic wounds are a huge challenge for wound care professionals because they may take a long time to heal and frequently involve clinical complications [1,2]. Ulcers are the most common type of chronic wounds, and include diabetic foot ulcers, pressure ulcers, and venous leg ulcers. Among patients with diabetes, $2\%$ to $3\%$ will develop a foot ulcer each year, and approximately $15\%$ will develop a foot ulcer during their lifetime [3,4]. Pressure ulcers have long been recognised as a disease entity [5]. The majority of leg ulcers can be related to venous disease, but other causes are possible, such as immobility, obesity, trauma, arterial disease, vasculitis, diabetes, and neoplasia [6,7]. Surgeries on the legs, such as a hip replacement or knee replacement, can also be associated with the occurrence of leg ulcers [8]. The normal wound healing process involves a set of sequential events: rapid haemostasis, appropriate inflammation, proliferation, and maturation [9]. Chronic wounds become trapped in the inflammatory and proliferative phases, which delays healing. The epidermis fails to migrate across the wound tissue, and there is hyperproliferation at the wound margins, which interferes with normal cellular migration over the wound bed [10]. In order to optimise wound healing, a clean, healthy granulating wound base must be kept, eventual infection must be treated, and the wound should be covered with an appropriate dressing able to ensure that the wound has an adequate level of moistness [11].
Modern wound dressings have been designed to facilitate wound healing rather than just covering it [12]. Ideally, a wound dressing should remain in contact with the wound, allowing gas exchange, adequate temperature, and an electrical gradient. Moreover, it should be non-toxic, non-allergic, and non-adherent, while preventing the proliferation of pathogens [13]. Currently available commercial dressings for advanced treatment of wounds are often inadequate, may cause damage to the skin due to adherence issues, and are generally expensive. Furthermore, the design of new and more efficient alternatives requires the conjugation of appropriate materials with optimised properties, together with therapeutic strategies to obtain dynamic wound healing [14]. Accordingly, hydrogels are excellent dressing materials for several types of wounds, due to their particular properties such as high similarity to the biological tissues, hydrophilic nature, water content, and adequate flexibility [15,16,17]. Hydrogels can be formulated using a wide range of polymers, including biopolymers of food origin. The benefits of hydrogels made from such biopolymers include safety, low cost, and wide availability. Among them, those based on casein, alone or in combination with other food-grade polymers, are of particular interest [18,19,20,21]. Casein-based hydrogels are biodegradable, biocompatible, renewable, easy to obtain, inexpensive, and nontoxic. These properties together with the ability to form networks of variable tensile strength and to encapsulate, protect, and release biomolecules led casein hydrogels to receive increasing attention from researchers in the area of biomaterials [22]. The incorporation of antiseptics into wound dressings potentiates the antimicrobial action of the dressing materials, preventing the occurrence of bacterial infections in the wound bed. Particular attention has been given to antiseptics, since they may have advantages over antibiotics: they have a broader spectrum of activity and unlike antibiotics, have multiple cellular targets. According to McDonnell and Russel [23], an increase in bacterial resistance to biocides (antiseptics and disinfectants) does not necessarily means its therapeutic failure.
Although casein-based hydrogels have already been investigated as platforms to release bioactive compounds [22], only a limited number of studies have evaluated drug-loaded dressings made of this type of hydrogels [24,25]; hence, further investigation is needed. The drugs tested in the referred works were gentamicin sulphate, an antibiotic [24], and allicin, a model antibacterial [25]. To our knowledge, there are no reports in the literature about the long-term use of wound dressings loaded with the most commonly used antiseptics in topical wound treatment [26,27,28,29,30].
The present work aimed to develop antiseptic-eluting casein-based hydrogels for wound dressings. The studied antiseptics were Octiset® and polyhexanide. Octiset® is a commercial solution, whose active ingredients are octenidine dihydrochloride (1 mg/mL) and 2-phenoxyethanol (20 mg/mL). Octenidine is a cationic surfactant effective against Gram-positive and Gram-negative bacteria. It features two non-interacting cationic active centres separated by a lengthy aliphatic hydrocarbon chain (Figure 1A), which facilitate its linkage with negatively charged surfaces of the microorganisms [31]. 2-Phenoxyethanol (Figure 1B) is an aromatic ether with a 2-hydroxyethyl group substituting on oxygen. Its known antimicrobial activity derives from the inactivation of malate dehydrogenase and uncoupling of oxidative phosphorylation. Interestingly, 2-phenoxyethanol has low inhibition effects on the resident skin bacteria [32]. Octiset® is a new generation antiseptic with high efficacy for the treatment of skin wounds and mucous membranes. Polyhexanide (Figure 1C) is an antimicrobial polymeric biguanide, widely used for treating chronic wounds and burns. Its activity is often related to the attraction to negative charge phospholipids on the cells’ membrane, thereby impairing its function [33].
The composition of the produced hydrogels was optimised in order to increase their drug loading capacity. The swelling, the degradation profile, the mechanical behaviour, and the drug release of the different drug-loaded samples were assessed. Being materials of natural origin, the casein hydrogels are more susceptible to the sterilisation process, which may alter their characteristics in different ways [34]. Therefore, the effects of steam-heat sterilisation on the material properties were evaluated. Antimicrobial tests and other biological tests, such as cytotoxicity, haemocompatibility and irritability assays, were also carried out. Finally, a case study with a dog was conducted.
## 2.1. Materials
Casein sodium salt and acid casein, both from bovine milk, acrylamide (AAm), N,N’- methylenebisacrylamide (MBAAm), ammonium persulfate (APS), N,N,N’,N’ tetramethylenediamine (TEMED), N-(3-aminopropyl)methacrylamide hydrochloride (APMA), lysozyme from chicken egg white (40,000 units/ mg protein), phosphate buffered saline (PBS), NaCl, KCl, NaH2PO4, Dulbecco’s modified eagle’s medium (DMEM) (D5796), bovine calf serum, penicillin-streptomycin solution, sodium pyruvate, NIH/3T3 fibroblasts (ATCC® CRL-1658/Sigma 93061524), trypsin EDTA (ethylenediaminetetraacetic acid) solution, dimethyl sulfoxide (DMSO), ethylenediaminetetraacetic acid solution (MTT solvent), and methanol were all purchased from Sigma (St. Louis, MO, USA). NaHCO3 was purchased from Panreac (Barcelona, Spain), and NaOH pellets ($99\%$), from Merck (Darmstadt, Germany). Octiset® was purchased from Schülke (Norderstedt, Germany), and polyhexanide (polyhexamethylene biguanide hydrochloride, PHMB) $94\%$, from Carbosynth (Berkshire, UK). Mueller–Hinton Agar and Mueller–Hinton Broth were purchased from Oxoid Ltd. (Hampshire, UK). Distilled and deionised (DD, 18 MΩcm, pH 7.7) water was obtained with a Millipore system (Millipore Merck, Darmstadt, Germany).
## 2.2. Hydrogels Preparation
Casein hydrogels were prepared via free radical polymerisation of AAm and coagulation of casein micelles. Two different formulations were used: formulation CS with casein sodium salt, and formulation C with acid casein.
The preparation of the casein hydrogels was based on the method proposed by Ma et al. [ 35]. First, PAAm chains were formed by radical polymerisation of AAm. Then, casein micelles that were formed by dissolution of casein in water lost their negative surface charge through acidification and coagulated, and were integrated in the PAAm chains. Further details of the synthetic process may be found in the above-mentioned reference.
For the formulation CS, the casein solution was prepared by dissolving 1 g of the casein sodium salt in 10 mL of DD water with magnetic stirring for 4 h. The pH of the solution was adjusted to 6 by the addition of NaOH solution (1 M). After dissolution, 2 g of AAm, 134 mg of APMA, and 1 mg of MBAAm were added to 5 mL of the casein solution. After stirring, 1 mg of APS and 0.5 μL of TEMED were added as a radical initiator and crosslinking accelerator for AAm, respectively. For the formulation C, the protocol was the same with an exception in the initial step, where the casein had to be dissolved in DD water with ≈20 μL of NaOH (10 M), given the very low solubility of this casein in pure water. The mixture was then magnetically stirred overnight. It is important to point out that the pH of the solution decreased as the casein started to dissolve, reaching a pH around 6 when it was fully dissolved.
The solutions were poured into glass moulds silanised as described previously [36]. Polymerisation was done by exposing the solutions to UV light (proMa, model UV Belichtungsgerät 2, Sande, Germany) for 4 h. Then, formulations CS and C were kept in the oven at 36 °C for 22 h and 6 h, respectively. The hydrogels were carefully removed from the moulds and washed in DD water for 3 days to eliminate the free radicals.
Hydrogel disks with 10 mm diameter were cut and dried in the oven for 6 h at 36 °C to be used in all tests, except the drug loading/release experiments, mechanical tests, and the cytotoxicity assay. Sterilisation of the hydrogels was carried out in an autoclave (Uniclave 88 from AJC, Cacém, Portugal) at 121 °C for 20 min.
## 2.3.1. FTIR Analysis
The chemical structure of the dry non-loaded casein-based hydrogels was studied using Fourier transform infrared spectroscopy (FTIR), with attenuated total reflectance (ATR). We used a FTIR equipment (model Spectrum Two from PerkinElmer, Waltham, MA, USA) with a lithium tantalate (LiTaO3) mid-infrared (MIR) detector (signal/noise ratio 9300:1). The applied force was manually controlled, to ensure a good contact between the crystal (diamond crystal ATR accessory, model UATR Two) and the hydrogels. All spectra were collected at 4 cm−1 resolution and 8 scans of data accumulation and normalised using the OriginPro 8.5 software. Triplicates of each hydrogel (10 mm of diameter) were analysed.
## 2.3.2. Swelling Ratio and Equilibrium Water Content
The swelling ratio (SR) of the hydrogels in four testing liquids, DD water, PBS, Octiset®, and polyhexanide solution in PBS (0.5 mg/mL), was determined using Equation [1]. The equilibrium water content (EWC) was calculated only for the samples hydrated in DD water, through Equation [2] [37]. [ 1]SR%=wh−wdwd×100 [2]EWC%=wh−wdwh×100 The weight of the dried disks, wd, was determined, and they were then transferred into falcons (Labox, Enzymatic, Santo Antão do Tojal, Portugal) with 5 mL of the testing liquids. During the hydration process, the samples were carefully taken out of the solutions for several times, blotted with an absorbent paper, and weighted (wh). This was repeated until a constant weight was achieved. The assays were performed in triplicate.
## 2.3.3. Degradation Assay
The hydrolytic degradation of the hydrogels was carried out in PBS, while the degradation was performed in simulated exudate solution in pseudo extracellular fluid (PECF) (0.68 g of NaCl, 0.229 g of KCl, 2.5 g of NaHCO3, and 0.4 g of NaH2PO4) containing lysozyme (1 mg/mL). The dried disks were weighted, and each disk was then immersed in 5 mL of the degradation solution at 34 °C, under agitation at 180 rpm. After 24 h and 48 h, the disks were washed by immersion in DD water and dried. The dried disks were weighed, and the weight loss was calculated through Equation [3], where w0 is the weight of the dried disks and w$\frac{24}{48}$ are the weights of the sample, after 24 h or 48 h in the degradation solutions, respectively, after drying [38]. The assay was done in quintuplicate. [ 3]weight loss %=w0−w2448w0×100
## 2.3.4. SEM
The hydrogel’s surface was observed using scanning electron microscopy (SEM). Prior to the SEM analysis, samples were lyophilised and coated with a gold/palladium film in a Polaron Quorum Technologies sputter coater and evaporator (Au/Pd). After coating, the disks were analysed with an Analytical SEM Hitachi S2400 (Hitachi Ltd., Tokyo, Japan). SEM images were obtained under 100×, 3000×, and 5000× magnifications. Cross-section images were obtained under 40× and 500× magnifications using samples cracked in liquid nitrogen. The assay was done in duplicate.
## 2.3.5. Mechanical Tests
Tensile tests were performed using a texturometer (TA.XT Express Texture Analyser, Stable Micro Systems, Godalming, Surrey, UK). The hydrated hydrogels were cut using a special dumbbell-shape cutter (2.5 mm maximum width and 6 mm gauge length). The data were processed using the software TE32LiteExpress v. 6.1.15.0 (Godalming, Surrey, UK). A constant speed of 0.5 mm/s was applied. The obtained stress–strain curves allowed the calculation of the Young’s modulus and toughness. The range of strain considered for this assay was 0–$20\%$, where stress and strain are proportionally dependent, and the curves presented a linear form [39]. The experiments were carried out in quadruplicate.
## 2.4. Drug Loading and Release
The hydrogels were loaded with the drugs by soaking in Octiset® (1 mg/mL of octenidine dihydrochloride and 20 mg/mL of 2 phenoxyethanol, pH 6.4) or in polyhexanide solution in PBS (0.5 mg/mL, pH 7.5). Dried disks (with a diameter of 20 mm) were individually immersed in falcons containing 5 mL of the desired drug solution for 48 h at room temperature.
Drug release tests were performed in Franz diffusion cells [38]. The loaded disks were carefully blotted and placed surrounded by a rubber ring between the upper and lower parts of the cells, which were fixed with a clamp. The top side of the disk was left exposed to air in a confined environment. After mounting the six cells, the receptor chambers were filled with 6.5 mL of PBS, with special care to avoid air bubbles. The useful area of the samples in contact with the liquid was 76 mm2. To best mimic the in vivo conditions, experiments were done at normal human skin temperature (34 °C) [38]. At pre-determined times (every 30 min in the first hour, every hour for the remaining 7 h, and thereafter at 24 h and 48 h), 200 μL aliquots of the release solution were collected from each cell and the same volume of fresh PBS was refilled into the cell through the lateral tip. The absorbance of the collected solutions was analysed using UV-Vis spectroscopy (MultiskanTM GO Microplate Spectrophotometer, Thermo Scientific, Kandel, Germany) at characteristic wavelengths for each drug: 220 nm for 2-phenoxyethanol and 270 nm for octenidine dihydrochloride (i.e., the active components of Octiset®), and 220 nm for polyhexanide. From the absorbance values, the concentrations and the normalised cumulative mass released values were calculated.
In order to determine the amount of drug loaded into the hydrogel, a methanol extraction assay was performed following the protocol described in a previous work [40]. Briefly, drug-loaded samples were immersed in 3 mL of methanol inside glass vials. At pre-determined times (2 h, 4 h, 8 h, and 24 h), the disks were removed and placed in new vials with fresh methanol. The absorbance of the solution was assessed at each time point, the drug concentration was calculated, and the extracted drug mass was determined. The process was repeated until the methanol solution was free from the drugs. The experiments were carried out at least in triplicate.
## 2.5. Antibacterial Properties
The antibacterial properties of the hydrogels were evaluated against two bacteria: *Staphylococcus aureus* ATCC 25923 (Gram-positive) and *Pseudomonas aeruginosa* ATCC 15442 (Gram-negative), via turbidimetry. The experiment was performed under aseptic conditions (flow chamber from Bio Air Instruments, model AURA 2000 MAC 4 NF, Pero, Italy). Bacterial strains were grown for 24 h at 37 °C. An optical density of 1 McFarland (3 × 108 bacteria/mL) was achieved for *Staphylococcus aureus* and of 0.5 McFarland (1.5 × 108 bacteria/mL) for *Pseudomonas aeruginosa* by suspending the grown strains in $0.9\%$ NaCl sterile solution. Mueller–Hinton broth medium was prepared and sterilised in the autoclave at 121 °C for 20 min. Each disk was carefully blotted with absorbent paper and individually placed in a 24-well plate. A total of 500 μL of the broth medium and 10 μL of the bacterial suspension were added to each well. For the positive control, 500 μL of the broth medium and 10 μL of the bacterial suspension were added to the well (without any sample), and for the negative control, only 500 μL of the broth medium was added. The plates were incubated at 37 °C for 24 h at 100 rpm. To analyse the results, 200 μL of each well solution was extracted, and the absorbance was measured using a spectrophotometer (Platos R 496 Microplate Reader, Labordiagnostik, Graz, Austria) at 630 nm. The assays were done in quadruplicate for non-loaded (hydrated in PBS) and drug-loaded (with Octiset® or polyhexanide) CS and C hydrogels.
## 2.6.1. Irritation Assay (HET-CAM)
The Hen’s Egg test on the chorioallantoic membrane (HET-CAM) assay was performed to evaluate the potential irritation effect of both hydrogel formulations. The assay was done for drug-loaded and non-loaded samples. Fertilised hen’s eggs (Sociedade Agrícola da *Quinta da* Freiria, SA, Portugal) were incubated (Incubator, 56S, Nanchang Edward Technology Co., Ltd., Nanchang, China) at 37 °C ± 0.5 °C with 60 ± $5\%$ of relative humidity. After incubating for 9 days, the shell was cut at the air pocket in the larger end of the egg, with a rotary saw (Dremel 3000 from Breda, Netherland), removed, and the inner membrane was hydrated with $0.9\%$ NaCl. After hydration, this membrane was carefully removed in order to expose the chorioallantoic membrane (CAM).
Sterilised disks of the hydrogels were placed directly on the CAM for 5 min. Irritation of the membrane was evaluated by checking the appearance of lysis, haemorrhage, and coagulation. The assay was performed in triplicate for both CS and C hydrogel formulations. A positive and a negative control were performed by applying 300 μL of 5 M NaOH and $0.9\%$ NaCl on the CAM, respectively. The irritation score (IS) was used to quantitatively analyse the irritation potential of the tested samples, using Equation [4] [41]:[4]IS=301−TH300·5+301−TL300·7+301−TC300·9 where TH, TL, and TC represent the time (in seconds) when the first appearance of haemorrhage, lysis, and coagulation occurs, respectively.
## 2.6.2. Haemocompatibility
Blood samples were collected from healthy volunteers via venepuncture in sodium citrate anti-coagulant vacutainer tubes (Vacustest Kima, Arzegrande, Italy) under aseptic conditions in Serviços de Saúde of Instituto Superior Técnico, Lisbon, after obtaining informed consent and with the approval of the Ethical Committee of Egas Moniz (Ref. n◦$\frac{1047}{2022}$). Sterilised disks of both CS and C formulations were placed in falcons containing 5 mL of PBS, under aseptic conditions. A volume of 200 μL of blood was added to the falcons, which were incubated at 37 °C for 1 h. Distilled water and untreated PBS were used as the positive and negative control, respectively. After incubation, the samples were removed from the falcons, and the tubes were centrifuged for 10 min at 3000 rpm. The supernatant’s absorbance (Abssample) was measured at 540 nm and related with the absorbance of the positive and negative control (AbsC+ and AbsC−, respectively) through Equation [5] to calculate the haemolysis ratio. The assay was performed in sextuplicate. [ 5]Hemolysis %=Abssample−Absc−Absc+−Absc−×100
## 2.6.3. Cytotoxicity
A cytotoxicity assay using NIH/3T3 fibroblasts was performed to evaluate the cells’ response to non-loaded and drug-loaded hydrogels. The assay was performed under sterile conditions (flow chamber from Bio Air Instruments, model AURA 2000 MAC 4 NF), using porous Transwell® inserts (8.0 µm pore polycarbonate membrane Corning® Transwell®, Sigma, Saint Louis, MO, USA), and following the ISO-10993-5:2009 guidelines. The cells were cultured in DMEM, and supplemented with $10\%$ bovine calf serum, $1\%$ penicillin-streptomycin solution, and $1\%$ sodium pyruvate. The assays were performed in quadruplicate in 12-well plates. Approximately 1 × 105 cells were seeded in each well in 0.8 mL of DMEM-supplemented medium, corresponding to a cell concentration of 1.25 × 105 cells/mL. The plates were incubated at 37 °C (humidified with $5\%$ CO2) for 24 h to promote cell culture and obtain a confluent monolayer. Hydrogel disks (7 mm diameter) were sterilised in PBS or drug solution, using an autoclave (121 °C for 20 min). Thereafter, they were gently blotted with a sterile tissue, and placed in the bottom surface of polycarbonate membrane Transwell® inserts present in the plates. Negative and positive controls were made by supplementing the cells with 1 mL of DMEM, and 1 mL of DMEM with $10\%$ DMSO, respectively. The plates were again incubated for 24 h, and the MTT assay was performed to verify the viability of the cells. After incubation, both the inserts and the medium were carefully removed from the wells, and 300 μL of the MTT solution ($10\%$ MTT dissolved in serum-free DMEM) was added. Additional controls without cells were also made and supplemented with the MTT solution. The plates were then incubated for 3 h in the previous incubation conditions. After incubation, 600 μL of the MTT solvent was added to each well, and the plates were agitated on an orbital shaker for 1 h. After dissolution, 200 μL of medium was retrieved from each well, and the absorbance was read at 595 nm in a microplate reader (AMP Platos R 496, AMEDA, Labordiagnostik, Graz, Austria). Cell viability was assessed through relative quantification by normalising it to the negative control.
## 2.7. In Vivo Case Study
The therapeutic efficacy of a drug-loaded hydrogel that was selected after the previous studies was evaluated through one in vivo case study; the case study involved a 13-year-old neutered male dog (*Serra da* Estrela breed), weighing 30 kg, that was admitted to the veterinary hospital (Hospital Veterinário de S. Bento, Lisbon, Portugal) with multiple dog bite wounds. Physical examination of the dog showed a body condition $\frac{3}{9}$, hypotension, prostration, and exudative wounds on the left thoracic limb (two lesions: one caudal and another cranial) and the right pelvic limb (one dorsolateral lesion), with signs of severe pain. The animal had claudication of the left thoracic limb due to a previous identical episode. Biochemical and haemogram analyses were performed and revealed hypoalbuminemia (1.4 g/dL), compatible with protein-losing enteropathy. Initially, the animal required stabilisation with fluid therapy Ringer’s lactate (B. Braun®) through a venous catheter in the jugular (Introcan®). Analgesic, anti-inflammatory, and antibiotherapy management was performed.
The wounds on the left thoracic limb were cleaned with $1\%$ chlorhexidine (desinclor®) until the animal was stable, and cryotherapy was performed two times a day for 20 days. After stabilisation, it was possible to perform trichotomy of the injured areas using an Oster® Golden A5® shearing machine and Oster CryogenX® No. 40 shearing blade. Thereafter, cleaning of the wounds was carried out with isotonic saline Ringer’s lactate (B. Braun®) associated with $1\%$ chlorhexidine. Drug-loaded hydrogels dressings (8 × 8 cm2) were then applied to the two wounds of the left thoracic limb, gloved, and protected by $100\%$ cotton surgical sterile gauze pads (Bastos Viegas®); they were attached to the limb with adhesive (3M™ Durapore™). The dressing was covered with a second layer of elastic bandage (Bastos Viegas®) and wrapped in a third layer of self-adhesive bandage (Peha-haht®). The procedure was performed in a way to avoid clog of the injured area, ischemia, oedema, or cell death. Dressings were changed daily for the first week and then every 48 h until resolution.
Wound management of the right pelvic limb was performed vi disinfection with $1\%$ chlorhexidine associated with isotonic saline Ringer’s lactate, followed by application of $100\%$ cotton surgical sterile gauze pads (Bastos Viegas®) that were fixed to the skin with a non-woven adhesive band (Omnifix®E). This management is commonly used in clinical practice in wounds whose closure is expected to occur via second-intention healing, without expected complications.
The study was approved by the Ethical Committee (CEBEA) of Faculdade de Medicina Veterinária da Universidade Lusófona (Ref. n◦$\frac{27}{2019}$); both the ARRIVE guidelines and EU Directive $\frac{2010}{63}$/EU for animal experiments were followed.
## 2.8. Statistical Analysis
Quantitative data are represented as average values and the respective standard deviations. To infer about the statistical significance, statistical tests were performed using the software R Project v. 4.2.1. The Shapiro–Wilk test was used to verify the normality of the data. For data with verified normality, the similarity of variances was evaluated using the Levene’s test. The one-way ANOVA test and Student t-test were the parametric tests used to calculate if the sets of data were significantly different. When the equality of variances assumption was not met, the data were analysed by using the Welch’s t-test. For non-parametric data, the Kruskal–Wallis test and Wilcoxon signed-rank test were used. The Bonferroni correction was applied for pairwise comparison between groups, as required. The level of significance was set to 0.05.
## 3.1.1. FTIR Analysis
FTIR spectra of the hydrogels C and CS are compared to those of the pure components (PAAm and casein C and CS) in Figure S1 (Supplementary Information). In the spectra of the hydrogels, bands that are characteristic of both components are visible, but it is not possible to conclude about the eventual interaction between them. In the high-frequency region, the NH2 bands at 3338 cm−1 and 3159 cm−1 characteristic of the primary amide of PAAm and the band 2968 cm−1–2873 cm−1, deriving from CH2 and CH3 groups of the casein, clearly identify the presence of these components. The peak corresponding to the stretching of C=O is visible at 1646 cm−1, which is a value intermediate between the values of both components. The peak at 1608 cm−1 may be attributed to the bending of N-H in primary amide and coincides with the equivalent peak in the PAAm spectrum. The low-frequency region is more difficult to interpret due to the superposition of the peaks in the spectra of both components, although the absence of new peaks seems to indicate no decomposition of the components. Furthermore, we must stress that other components are present in the hydrogels, although in minor quantities, which may contribute to the complexity of the hydrogel spectra.
## 3.1.2. Swelling Ratio and Equilibrium Water Content
The swelling degree is a critical factor to define the applicability of wound dressings. A dressing with a high SR leads to a good absorption of biological fluids, an efficient nutrient-waste exchange, and favours cell migration [42].
Figure 2A,B shows the SR of CS and C hydrogel formulations, respectively, before and after sterilisation. Both hydrogels presented very high swelling degrees in DD water, although for formulation C, the value was about $30\%$ lower ($p \leq 0.04$). A similar behaviour was reported in other studies involving casein hydrogels [43], which may be attributed to the repulsion between the ionic charges in the polymer backbone. In the drug solutions, this repulsion is partially compensated by the attraction of the negative sites in the hydrogels and the positive groups in drug molecules, and the SR decreases although keeping high values. Variation of the ionic strength led to a decrease in the SR value in PBS for both hydrogels ($$p \leq 0.014$$ for CS and $$p \leq 0.019$$ for C). Concerning sterilisation, the most striking effect was the decrease of SR in DD water ($p \leq 0.01$ for CS and $p \leq 0.02$ for C), which was more significant in the case of the CS material; this possibly indicates an increase in the crosslinking degree of the polymer network, which induced the tightening of the hydrogels’ matrix. In contrast, sterilisation did not affect the swelling capacity of both hydrogels in PBS ($$p \leq 0.608$$ for CS, $$p \leq 0.095$$ for C), Octiset® ($$p \leq 0.271$$ for CS, $$p \leq 0.226$$ for C), and polyhexanide solution for CS ($$p \leq 0.061$$), but a slight increase occurred in this drug for C ($p \leq 0.003$). A possible explanation is that, in DD water, the effect of the repulsive interactions was attenuated by the increase in pressure and temperature during sterilisation, while in drug solutions, these repulsive interactions were already weak in the non-sterile hydrogels.
The EWC values of the non-sterile hydrogels were within the same range ($95.4\%$ ± 0.6 for CS and $92.4\%$ ± 0.3 for C) and decreased slightly to $90.0\%$ ± 0.2 for CS hydrogels, and to $90.2\%$ ± 1.1 for C samples after sterilisation ($p \leq 0.001$ for CS and $p \leq 0.05$ for C). The high water content of the dressings allows them to keep a wetted environment in the wound bed, which promotes cellular growth and accelerates the tissue regeneration [44]. Such types of materials are considered suitable for the treatment of a wide a range of wounds, e.g., wounds that leak little or have no exudate as well as those that are painful or necrotic like pressure ulcers, second-degree burns, and infected wounds [45,46].
## 3.1.3. Degradation Assay
High levels of enzymes like lysozyme and proteases were identified in infected and chronic wounds. The lysozyme concentration has been reported to be 13–24 times higher in infected wound fluid than in uninfected wounds [47,48]. This enzyme, produced by the human immune system, is capable of catalysing the hydrolysis of glycosidic bonds of mucopolysaccharides in bacterial cell walls. Furthermore, it is known that lysozyme can strongly associate with α-casein [49,50,51], and this is the reason for using lysozyme in the degradation assays. Proteases are also quite important in the wound healing process, regulating extracellular matrix degradation and deposition that is critical for wound re-epithelialisation. Proteases break down proteins into peptides and amino acids and can therefore also help destroying casein. Although they have not been used in the present work, their effect involving casein-based dressings will be investigated in future studies, as planned.
The degradation of the produced hydrogels was determined in PBS and in PECF containing lysozyme at two time points (24 and 48 h, Figure 3).
The hydrogels of both formulations presented very low weight losses in PBS. For formulation CS, the hydrolytic degradation values were $1.6\%$ ± 0.3 and $2.0\%$ ± 0.3 at 24 h and 48 h, respectively. Formulation C materials displayed slightly lower values: $0.9\%$ ± 0.2 at 24 h ($p \leq 0.001$) and $1.3\%$ ± 0.5 at 48 h ($p \leq 0.05$).
The degradation values for hydrogels of formulation CS exposed to the PECF + lysozyme solution were $5.0\%$ ± 0.3 and $5.4\%$ ± 0.2 at 24 h and 48 h, respectively. Formulation C materials displayed slightly lower values: $4.3\%$ ± 0.4 at 24 h ($p \leq 0.005$) and $4.9\%$ ± 0.7 at 48 h ($p \leq 0.05$). As expected, degradation values of the hydrogels exposed to the simulated exudate solution with lysozyme were greater than those of the hydrolytic degradation ($p \leq 0.001$ for both hydrogels). A comparison of the two hydrogels shows that the hydrogels of formulation C were slightly more resistant to degradation in both solutions than those of formulation CS, which agrees with the lower swelling capacity of this hydrogel.
## 3.1.4. SEM
The SEM images of the surfaces of both CS and C materials, before and after sterilisation, are presented in Figure 4A–D. It is possible to identify a lacy structure on the surface of non-sterile samples, which disappeared after sterilisation. Cross-section images of the same materials, before and after sterilisation, are shown in Figure 4E–H. They reveal that the lacy structure results from lumps on the material’s surface and does not correspond to the presence of pores. The harsh conditions of the autoclave process during sterilisation (121 °C, that leads to a water vapour pressure of ≈205 KPa) may induce the collapse of these lacy appearance, inducing a surface smoothing effect.
## 3.1.5. Mechanical Tests
Stress–strain curves of the non-loaded and drug-loaded hydrogels, before and after sterilisation, are shown in Figure S2, respectively, for formulations CS and C. The Young´s modulus and toughness values for CS and C hydrogels were determined in the deformation range 0–$20\%$, where stress and strain are proportionally dependent, and are shown in Figure 5. Concerning non-loaded hydrogels, both values are significantly higher for formulation C, compatible with the lower swelling capacity of this hydrogel and its higher resistance to degradation, which may be attributed to a larger crosslinking degree.
For hydrogels of formulation CS (Figure 5A,B), it is possible to identify a significant increase in the Young´s modulus ($p \leq 0.001$ for both drugs) and the toughness ($p \leq 0.05$ for Octiset®, $p \leq 0.001$ for polyhexanide) with drug loading. This implies a less elastic behaviour for the drug-loaded materials, which is in agreement with the lower SR obtained for the CS hydrogels immersed in drug solutions (Figure 2A). Sterilisation led to a slight decrease in both the Young’s modulus ($p \leq 0.001$ for both drugs) and toughness ($p \leq 0.05$ for both drugs), which was not reflected in the behaviour of the SR of these hydrogels. In the case of formulation C (Figure 5C,D), the non-loaded and the drug-loaded hydrogels present roughly the same values of the Young´s modulus ($$p \leq 0.2931$$ for Octiset®, $$p \leq 0.0508$$ for polyhexanide) and toughness ($$p \leq 0.2450$$ for Octiset®, $$p \leq 0.1620$$ for polyhexanide), despite the differences observed in their SR (Figure 2B). Sterilisation had practically no effect on the mechanical properties of this formulation.
## 3.2. Drug Loading and Drug Release
The prepared hydrogels were colourless, but after drug loading, they became whitish. The change of colour may be attributed to some drug precipitation inside the polymeric network.
The release profiles of the Octiset® components (i.e., 2-phenoxyethanol and octenidine dihydrochloride), and of polyhexanide from the hydrogels with formulation CS and C, both non-sterile and sterile, are presented in Figure 6.
Regarding CS hydrogels, the release of the drugs was in general controlled for at least 48 h. During the first 8 h, the release was fast and then it slowed down between the 24th h and 48th h. Sterilisation did not significantly affect the drug release profiles, which is in agreement with the fact that SR in the drug solutions is almost unaffected by the sterilisation. The results of the methanol extraction assay allowed to conclude that most of the loaded drugs were released. In the case of Octiset®-loaded materials, around $75\%$ of 2-phenoxyethanol and around $86\%$ of octenidine dihydrochloride were released in 48 h. This value increased to around $89\%$ for polyhexanide.
For C formulation, the results are similar, except for the Octiset® components, whose release appeared to stop at 48 h. Sterilisation also did not significantly affect the release profiles of the drugs. The percentages of the loaded drugs that were released at 48 h were around $74\%$ for 2 phenoxyethanol, $81\%$ for octenidine dihydrochloride, and $83\%$ for polyhexanide.
## 3.3. Antibacterial Properties
Figure 7 shows the optical density (%) of the solutions containing *Staphylococcus aureus* and *Pseudomonas aeruginosa* after 24 h incubation of non-loaded and drug-loaded hydrogels with formulations CS and C. The non-loaded samples did not exhibit any antibacterial properties against the tested bacteria. For both formulations, the optical density values of the wells containing those samples were high (being even slightly higher than the value correspondent to the positive control in the case of formulation CS with *Pseudomonas aeruginosa* and C with Staphylococcus aureus). Hydrogels of the formulation CS loaded with both drugs demonstrated high antimicrobial activity against *Staphylococcus aureus* and Pseudomonas aeruginosa, although polyhexanide-loaded samples appeared to be more effective. For formulation C, the hydrogels loaded with the two drugs also presented high antimicrobial activity, but no significant difference was observed either regarding the strains or the action of the drugs.
## 3.4.1. Irritation Assay (HET-CAM)
The HET-CAM assay provides a highly used and well-established prediction model for eye irritation, but it can also be performed to evaluate the irritability wound care systems. The results are shown in Figure 8.
The results were very similar for both formulations. Non-loaded hydrogels did not show any signs of membrane of lysis, haemorrhage, or coagulation (IS = 0), as observed in the negative control. The same was true for polyhexanide-loaded ones. The membranes in contact with Octiset®-loaded hydrogels of both formulations presented with signs of slight irritation (IS = 1).
## 3.4.2. Haemocompatibility
The haemocompatibility of the dressing materials is important to avoid an undesired immune response when the materials enter in contact with blood. A haemolysis index lower than $5\%$ corresponds to a highly haemocompatible material; within $10\%$ haemolysis, the material is considered haemocompatible, and for a haemolysis ratio higher than $20\%$, the material is non-haemocompatible [52,53]. The haemolysis ratios (Figure S3) of the hydrogels were 0.4 ± 0.1 for formulation CS and 0.3 ± 0.1 for formulation C, meaning that both formulations are highly haemocompatible.
## 3.4.3. Cytotoxicity
In wound dressings, cytotoxic effects would impair the viability, proliferation, and migration of cells involved in wound healing, thereby lowering the healing rate [54]. The MTT assay allows the measurement of cellular metabolic activity as an indicator of cell viability. The obtained cell viability results are presented in Figure 9.
It is important to point out that, as stated in ISO 10993-5:2009 [55], a material can be considered non-cytotoxic if the cell viability is above $70\%$. The results obtained for both non-loaded hydrogels show that they are not cytotoxic: around $93.2\%$ of cell viability for CS and $96.7\%$ for the C formulation. Regarding the Octiset®-loaded samples, cell viability values were $78\%$ for CS and $70.5\%$ for C. These results are compatible with the clinical and experimental evidence showing that octenidine-containing products are effective anti-bacterial agents, without compromising wound healing or causing significant cytotoxicity [56]. Polyhexanide-loaded hydrogels also displayed non-cytotoxicity with $82.4\%$ cell viability for the CS formulation and $72.5\%$ for the C formulation. Again, this is in agreement with literature reports about the safety, efficacy, and tolerability of polyhexanide [57].
## 3.5. In Vivo Case Study
C hydrogels loaded with Octiset® were used in the in vivo study. Although the formulations CS and C showed similar results, the facts that the preparation of the latter is much faster (6 h vs. 22 h) and its degradation is slightly lower justified the selection of C hydrogels for this study. The antimicrobial tests (Section 3.3) showed that the performance of C hydrogels loaded either with Octiset® or with polyhexanide was equivalent. In a comparative study of different antiseptics, Koburger et al. [ 26] concluded that polyhexanide and octenidine solutions had similar efficacy when a prolonged contact time with the tissues was feasible, which is the case of wound dressing treatments. Octiset® was chosen because it is a new generation antiseptic that has broad-spectrum efficacy and no known microbial resistance, similar to polyhexanide. It is safe and well tolerated, has no side effects, and is not absorbed systemically, in contrast to polyhexanide that has a high affinity for tissue structures that impairs its long-term use [58].
The in vivo performance of C hydrogels dressings loaded with Octiset® was evaluated through the evolution of the healing of the wounds on the left thoracic limb. Figure 10 shows the evolution of the cranial lesion (≈65 mm × 30 mm) in the region of the radius and ulna, which was quite remarkable. The dressings were changed daily for the first week and then every 48 h until resolution. It took only 11 days for epithelialisation to occur along the entire length of the wound. After 56 days, hair follicle growth was observed, and tissue remodelling led to an increase in the tension strength exhibited by the scar, which was not weakened. The evolution of the caudal lesion (≈45 mm × 20 mm), also in the region of the radius and ulna in the same limb, is displayed in Figure 11. Epithelialisation took 34 days to complete due to its high depth (≈10 mm) and tissue trauma. After 56 days, follicular growth was observed in part of the scar, and the initial area with greater depth of tissue damage did not show any follicular growth. Hyperpigmented areas due to melanin deposition were also observed after the complete closure of the lesion. Throughout the process, the dressing properties promoted autolytic debridement, allowing the removal of exudate, necrotic, and devitalised tissue present in the lesions, and no complications were observed during the healing course.
In order to compare the time to closure between a wound where C hydrogel dressings loaded with Octiset® were applied and another wound where only daily disinfection was performed and covered with a cotton pad, two wounds were considered: the cranial lesion of the left thoracic limb (Figure 10) and the dorsolateral lesion of the right pelvic limb (Figure 12). On day 7 of the treatment, the dimensions of the cranial wound limited by the black circle in Figure 10C (≈14 mm × 11 mm) were similar to those of caudal wound on day 5 of treatment (Figure 12B) (≈13 mm × 11 mm). Both lesions were in the same healing phase. The former one healed on day 13 of treatment while the latter healed on day 15. This analysis shows that the evolution of the cranial wound in the period of days 7–13 is equivalent to that of the caudal wound in the period of days 5–15, leading to the conclusion that the use of the dressings accelerated the healing process by 4 days.
## 4. Conclusions
The main goal of the present work was to investigate the possibility of developing novel casein hydrogel dressings to treat chronic wounds. Additionally, these dressings were loaded with antiseptics, aiming to ensure a more rapid and efficient wound care treatment. Two casein hydrogel formulations were tested: casein sodium salt (CS) and acid casein (C). The hydrogels presented with high swelling capacity, low degradation in simulated exudate solution, and adequate mechanical properties to be used as wound dressings. Although the properties of both hydrogels were similar, some differences were found. The hydrogel of formulation C was characterised by a lower SR, a lower elasticity, and a higher resistance to degradation. Autoclave sterilisation did not affect the properties of both hydrogels. When loaded with Octiset® or polyhexanide, the hydrogels were able to release the drugs in a sustained manner for, at least, 48 h. Both antiseptic-loaded materials presented good antimicrobial properties and were demonstrated to be non-irritant, highly haemocompatible, and non-cytotoxic. A case study involving a dog with multiple wounds was conducted. Three-layer dressings based on casein hydrogels (formulation C) loaded with Octiset® led to an efficient healing process. Altogether, the obtained results indicate that the developed casein hydrogels appear to be promising wound dressing materials.
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|
---
title: HS 3D-SeboSkin Model Enables the Preclinical Exploration of Therapeutic Candidates
for Hidradenitis Suppurativa/Acne Inversa
authors:
- Christos C. Zouboulis
- Xiaoxiao Hou
- Henriette von Waldthausen
- Konstantin C. Zouboulis
- Amir M. Hossini
journal: Pharmaceutics
year: 2023
pmcid: PMC9967844
doi: 10.3390/pharmaceutics15020619
license: CC BY 4.0
---
# HS 3D-SeboSkin Model Enables the Preclinical Exploration of Therapeutic Candidates for Hidradenitis Suppurativa/Acne Inversa
## Abstract
Despite the rapid development in hidradenitis suppurativa (HS) research, the immediate introduction of potent therapeutic compounds in clinical trials and the lack of definitive outcome measures have led to the discontinuation of potential therapeutic compound studies. HS is a solely human disease, and therefore, the search for preclinical human models has been given priority. The 3D-SeboSkin model, a co-culture of human skin explants with human SZ95 sebocytes as a feeder layer, has been shown to prevent the rapid degeneration of human skin in culture and has been validated for HS preclinical studies. In this work, the HS 3D-SeboSkin model has been employed to characterize cellular and molecular effects of the EMA- and FDA-approved biologic adalimumab. Adalimumab, a tumor necrosis factor-α inhibitor, was shown to target inflammatory cells present in HS lesions, inducing a prominent anti-inflammatory response and contributing to tissue regeneration through a wound healing mechanism. Adalimumab inhibited the lesional tissue expression of TNF-α, IL-3, IL-15, and MCP-3 and downregulated the secretion of IL-1α, IL-5, RANTES, MCP-2, TNF-α, TNF-β, TGF-β, and IFN-γ. In contrast, IL-6 was stimulated. The compound failed to modify abnormal epithelial cell differentiation present in the HS lesions. Patients with Hurley stage II lesions exhibited stronger expression of autophagy proteins in perilesional than in lesional skin. Adalimumab modified the levels of the pro-apoptotic proteins LC3A, LC3B, and p62 in an individual, patient-dependent manner. Finally, adalimumab did not modify the NFκB signal proteins in SZ95 sebocytes and NHK-19 keratinocytes, used to study this specific pathway. The administration of the validated HS 3D-SeboSkin model in ex vivo studies prior to clinical trials could elucidate the individual pathogenetic targets of therapeutic candidates and, therefore, increase the success rates of clinical studies, minimizing HS drug development costs.
## 1. Introduction
Hidradenitis suppurativa/acne inversa (HS) is a significant, inflammatory skin disease of the terminal hair follicle that mostly presents in the apocrine gland-bearing areas of the body [1]. The 2006 inaugural International Conference on HS, in Dessau, Germany [2,3], and the consequent establishment of the Hidradenitis Suppurativa Foundation, Inc. [3], and the European Hidradenitis Foundation e.V. [3] raised awareness for this previously obscure disease. This exposure brought the number of relevant publications from 480 to 3728 in the 16 years following these inaugural events [4]. An increased prevalence, currently estimated at $0.4\%$ worldwide and up to $1\%$ in Europe, can be attributed to more informed diagnoses of HS [5]. EMA and FDA approval of the tumor necrosis factor-α (TNF-α) inhibitor adalimumab (ADA) in 2016 provided the first therapeutic agent against inflammatory lesions of HS [6,7]. Currently, there are more han 150 clinical studies registered, with several phase 3 studies ongoing or completed [8].
Despite this rapid development, a lack of definitive outcome measures has led to failure amongst initial therapeutic candidates [9,10]. Furthermore, adequate preclinical models were until recently lacking. Given that HS is a solely human disease and there are no relevant animal models, human models are required for appropriate preclinical drug testing.
Therefore, attention is currently being devoted to improving outcome measures [11,12] and developing human HS models [13,14]. Such models contain ex vivo systems such as the 3D-SeboSkin model [15,16,17,18]. The 3D-SeboSkin model [15] comprises a co-culture of human skin explants with a human SZ95 sebocyte [19] feeder layer, shown to prevent rapid degenerative events commonly observed during the maintenance of human skin explants in culture. Furthermore, this model retains normal histomorphological characteristics concerning epidermal structure, the basal membrane, and adhesive junctions [20]. The 3D-SeboSkin model has been validated [15] by reproducing ex vivo the differential expression of HS biomarkers found in epidermal and dermal tissue as well as in the appendages of lesional and perilesional skin of HS patients in comparison to healthy skin [21,22,23].
In this work, we treated the HS 3D-SeboSkin model with ADA [7] to study the pattern of ADA efficacy in HS ex vivo. Moreover, we provided evidence that HS 3D-SeboSkin is an appropriate model for ex vivo preclinical exploration of therapeutic candidates for HS.
## 2.1. HS 3D-SeboSkin Model
The 3D-SeboSkin model, developed to maintain human skin in culture [20], has been adapted for ex vivo HS studies [15].
## 2.2. Cells
Human SZ95 sebocytes [19] and normal human keratinocytes (NHK-19) were cultured in Sebomed basal medium (Biochrom, Berlin, Germany) supplemented with $10\%$ fetal bovine serum (BSA), 50 μg/mL gentamycin, 10 ng/mL human epidermal growth factor (EGF), and 1 mM CaCl2 at 37 °C and $5\%$ CO2 until reaching sub-confluence. Prior to co-cultivation experiments, SZ95 sebocytes were resuspended in serum-free medium (Sebomed basal medium supplemented with $0.1\%$ BSA, 50 μg/mL gentamycin, 10 ng/mL human EGF, 1.5 mM CaCl2, 1.5 × 10−7 M linoleic acid (LA), and 10−6 M retinol). Two hundred thousand SZ95 sebocytes were seeded in 24-well plates and incubated overnight at 37 °C and $5\%$ CO2. The following day, the wells were washed twice with Ca2+- and Mg2+-free phosphate-buffered saline (PBS) and treated with 400 μL serum-free medium for either cell culture or direct contact co-culture experiments.
## 2.3. Skin Specimens
Following written informed consent, full-thickness skin specimens were obtained from 9 Caucasian female and 3 male patients (aged 28–59 years) with HS Hurley stage II–III during surgery. The patients did not present any other inflammatory or endocrinological disorders, including diabetes and thyroiditis, and were not pretreated for HS. Perilesional skin is defined as adjacent to HS lesional skin at a distance of ≥5 cm from the visible inflammation area. The study was approved by the Ethics Committees of the Charité–Universitätsmedizin Berlin (EA$\frac{4}{016}$/07) and the Brandenburg Medical School Theodor Fontane (E-01-20210222) and was conducted according to the Helsinki Declaration rules.
## 2.4. Co-Culture Experiments
After subcutaneous fat excision, skin specimens were cut into uniform samples with dimensions of 6 mm. HS skin explants were cultured with and without ADA (30 μg/mL; Selleckchem, Munich, Germany) for three days using the HS 3D-SeboSkin model as previously described [15,20].
## 2.5. Tissue and Culture Supernatant Protein Extraction
Full-length proteins were extracted from skin explants maintained in the HS 3D-SeboSkin model for three days and the harvested co-culture supernatants using the Qproteome FFPE Tissue Kit (Qiagen, Hilden, Germany). Protein concentration was determined using the Biorad Protein Assay (Bio-rad, Hercules, CA, USA).
## 2.6. Protein Quantification
For cytokine quantification, proteins were blotted with a Human Cytokine Antibody Array (ab133996; Abcam, Cambridge, UK). The levels of 23 inflammatory cytokines (GCSF, GM-CSF, GRO (αβγ), GRO-α, IFN-γ, IL-1α, IL-2, IL-3, IL-5, IL-6, IL-7, IL-8, IL-10, IL-13, IL-15, MCP-1, MCP-2, MCP-3, MIG, RANTES, TGF-β, TNF-α, TNF-β) were simultaneously measured. For autophagy protein quantification, proteins were blotted with the RayBio C-Series Human Autophagy Array (Raybiotech, Norcross, GA, USA). The levels of 20 human autophagy proteins (ATG12, ATG7, ATG10, ATG13, ATG3, ATG4A, ATG4B, ATG5, Beclin, BNIP3L, DDR2, GABARAP, LC3A, LC3B, LAMP1 (CD107a), p62, NBS1, RHEB, MSK1, and α-synuclein) were simultaneously measured in tissue lysates. For the detection of 45 nuclear factor “κ-light-chain-enhancer” of activated B-cells (NFκB) signal pathway proteins (ASC, BCL-10, CARD6, CD40/TNFRSF5, dAP1/BIRC2, dAP2/BIRC3, FADD/MORT1, Fas/TNFRSF6/CD95, IκBα, IκBε, IKK1/IKKα/CHUK, IKK2/IKKβ, IKKΥ/NEMO, IL-1R1, IL-17RN, IL-18RN, IRAK1, IRF5, IRF8, JNK$\frac{1}{2}$, JNK2, LTBR/TNFRSF3, Metadherin/AEG-1, MyD88, NFκB1, NFκB2, NGFR/TNFRSF16, P53, P53 (pS46), RelA/p65, RelA/p65 (pS529), c-Rel, SHARPIN, SOCS-6, STAT1p91, STAT1 (pY701), STAT2, STAT2 (pY689), STING/TMEM173, TLR2, TNFRI/TNFRSF1A, TNFRII/TNFRSF1B, TRAF2, TRAIL-R1/TNFRSF10A, TRAIL-R2/TNFRSF10B), blots of human SZ95 sebocytes and human keratinocytes were prepared with the Proteome Profiler Human NFkB Pathway Array (Bio-Techne, Wiesbaden, Germany).
The blots were imaged via a chemiluminescent imager. Blot intensity was quantified using the semi-quantitative software Image J. The ratio of evaluated cytokine to positive control was defined as the expression result.
## 2.7. Statistics
GraphPad 9 was used for data analysis in this study. All results are presented as mean ± standard error of the mean (SEM). The Shapiro–Wilk test was used to examine the distribution of the data. For statistical significance, a t-test was used where the data were normally distributed. Differences of $p \leq 0.05$ were considered as significant.
## 3.1. ADA Does Not Modify the NFκB Signal Pathway in Epithelial Cells
To detect the effects of ADA on inflammatory signaling of epithelial cells, human SZ95 sebocytes and NHK-19 cells were pre-incubated for 24 h with the pro-inflammatory fatty acid LA (10−4 M) [24] and subsequently for another 24 h with LA, ADA, or LA and ADA (30 µg/mL). After protein extraction, the levels of 45 NFκB signal pathway members were assessed by an antibody array.
Both untreated NHK-19 cells and those cells treated solely with ADA did not express NFκB signal pathway proteins. LA treatment induced low expression of several NFκB signal pathway members, including members of the TNF superfamily pro-apoptotic signal proteins, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-R1/TNFRSF10A, TRAIL-R2/TNFRSF10B, and the co-stimulator CD40/ TNFRSF5. The addition of ADA did not modify expression levels previously induced by LA (Figure 1, Supplementary Figure S1).
Human SZ95 sebocytes exhibited a markedly stronger pro-inflammatory NFκB pathway signal intensity than NHK-19 cells. Baseline expression levels of the pro-inflammatory proteins NFκB1 and CD40/TNFRSF5, the pro-apoptotic protein p53, the anti-apoptotic Fas/TNFRSF6/CD95, and the NFκB activator IκBε were detected in untreated controls. Treatment with LA, ADA, or a combination thereof did not modify the SZ95 protein expression levels (Figure 2, Supplementary Figure S2).
Interestingly, proteins that have previously been shown to be differentially expressed in HS, such as interleukin-1 receptor type 1 (IL-1R1), IL-1R antagonist (IL-17RN), and IL-18RN [23,25,26], were not regulated by ADA either in SZ95 sebocytes or in NHK-19 cells.
## 3.2. ADA Modifies Tissue Cytokine Expression in the HS 3D-SeboSkin Model
To characterize the expression of inflammatory cytokines in the HS 3D-SeboSkin model, we investigated the expression levels of 23 cytokines in the ADA-treated explants through a cytokine array. Twelve cytokines, namely granulocyte colony-stimulating factor (GCSF), GRO (αβγ), interferon (IFN)-γ, IL-1α, IL-3, IL-8, IL-15, monocyte chemoattractant protein (MCP)-3 (CCL7), RANTES (CCL5), tumor growth factor (TGF)-β, TNF-α, and TNF-β, were detected in HS-involved skin, while granulocyte–macrophage colony-stimulating factor (GM-CSF), GRO-α (CXCL1), IL-2, IL-5, IL-6, IL-7, IL-10, IL-13, MCP-1 (CCL2), MCP-2 (CCL8), and IFN-γ-induced monokine (MIG (CXCL9)) were below detection levels. ADA treatment induced a statistically significant inhibition of TNF-α ($p \leq 0.01$), IL-3 ($p \leq 0.05$), IL-15 ($p \leq 0.05$), and MCP-3 ($p \leq 0.05$), but not of GCSF, GRO (αβγ), IFN-γ, IL-1α, IL-8, RANTES, TGF-β1, and TNF-β (Figure 3).
## 3.3. ADA Modifies Cytokine Secretion in the HS 3D-SeboSkin Model
All 23 cytokines tested, GCSF, GM-CSF, GRO (αβγ), GRO-α, IFN-γ, IL-1α, IL-2, IL-3, IL-5, IL-6, IL-7, IL-8, IL-10, IL-13, IL-15, MCP-1, MCP-2, MCP-3, MIG, RANTES, TGF-β, TNF-α, and TNF-β, were detected in the culture supernatants of both the control and the ADA-treated skin explants. ADA treatment downregulated the secretion of the cytokines IL-1α ($p \leq 0.01$), IL-5 ($p \leq 0.05$), RANTES ($p \leq 0.01$), MCP-2 ($p \leq 0.01$), TNF-α ($p \leq 0.01$), TNF-β ($p \leq 0.001$), TGF-β ($p \leq 0.01$), and IFN-γ ($p \leq 0.05$) and stimulated the secretion of IL-6 ($p \leq 0.05$) (Figure 4).
## 3.4. ADA Affects Autophagy Procedures in Lesional and Perilesional HS Skin Ex Vivo in the HS 3D-SeboSkin Model
Among the 20 human autophagy proteins studied in lesional HS skin ex vivo using the HS 3D-SeboSkin model, the signals of the microtubule-associated protein light chain 3 (LC3) and p62 exhibited the strongest expression intensity (Figure 5). LC3 is the first mammalian protein described to be specifically associated with autophagosomal membranes and is detected in early autophagosomes [27]. LC3 exists in two isoforms, the cytosolic precursor LC3A and the active form LC3B, both of which were strongly expressed in HS lesional skin. Among the four HS patients studied, patients with Hurley stage II lesions ($$n = 3$$) exhibited significantly stronger expression in perilesional than in lesional skin, while the patient with Hurley III lesions exhibited stronger apoptotic signals in the lesional than in the perilesional skin.
Overall, ADA modified the levels of the pro-apoptotic proteins LC3A, LC3B, and p62 in an individual, patient-dependent manner (Figure 5, Supplementary Figure S3).
## 4. Discussion
Current studies of differential gene and protein expression have identified several candidates as targets for HS treatment [23,28,29]. Alas, published therapeutic trials provide limited information concerning the molecular mechanism of these compounds. These trials have demonstrated that ADA treatment induced a downregulation of the anti-apoptotic protein BCL2 in HS lesional skin [29]. Furthermore, a marked reduction in the B cell compartment with a significant decrease in CXCL13 and B cell activating factor (BAFF) expression levels was observed under ADA treatment [30]. Downregulation of matrix metalloproteinase (MMP)-1 and MMP-9 and upregulation of MMP-13 and tissue inhibitor of metalloproteinases (TIMP)-2 levels were detected in the circulation of HS patients treated with ADA [31]. HS patients treated with brodalumab exhibited a reduction in lipocalin (LCN)2 in the skin and IL-17A in serum levels [32]. No changes in inflammatory marker levels were observed in the lesional skin of HS patients receiving apremilast when compared with patients under placebo [28].
The introduction of human ex vivo and in vitro models has provided valuable information concerning the differential expression of genes and proteins under treatment conditions. These data support the understanding of the molecular mechanism of HS therapy candidates. The protein production of pro-inflammatory cytokines TNF-α, IFN-γ, IL-1β, IL-6, and IL-17A was significantly inhibited by ADA, infliximab, ustekinumab, prednisolone, and rituximab, but not by secukinumab [16]. IL-17A, calgranulin C (S100A12), and the activation marker human leukocyte antigen (HLA)-DR were significantly elevated in HS lesional skin and showed a decrease in expression levels when treated with apremilast in an ex vivo HS model [28]. Lenalidomide and the bromodomain and extraterminal inhibitor CPI-0610 reduced ex vivo skin levels of the Th1/Th2/Th9/Treg-associated cytokines IL-2, IL-4, IL-5, IL-9, and IL-21 and of the inflammatory cytokines/chemokines IL-8, IFN-α, macrophage inflammatory protein (MIP)-1α (CCL3), stromal cell-derived factor (SDF)-1α (CXCL12), MCP-1, and GRO-α and supernatant levels of the growth factors platelet-derived growth factor (PDGF)-1, vascular endothelial growth factor (VEGF)-D, and stem cell factor (SCF) and of the inflammatory cytokines/chemokines MIP-1α, IL-1RN, IL-6, and IFN-α [18]. Moreover, a dose-dependent decrease in B cell activation, as measured by a reduction in the proliferation marker Ki67 and the activation marker HLA-DR, was detected under ADA treatment of isolated cell cultures originating from HS lesional skin [30]. Wound healing profile changes, including the inhibition of the MMP pathway, were observed in human macrophages in vitro under ADA treatment but not under treatment with etanercept or certolizumab-pegol [31]. In our study, the HS 3D-SeboSkin model [15,20] has revealed information regarding ADA activity at the tissue and molecular levels. Additionally, this work has demonstrated the importance of similar preclinical studies of HS therapy candidates prior to their introduction in clinical trials.
The fact that ADA reduced ex vivo tissue levels of IFN-γ, IL-5, IL-15, MCP-2, MCP-3, RANTES, and TGF-β but did not modify the canonical NFκB signal pathway [33] in human skin epithelial cells (NHK-19 keratinocytes and SZ95 sebocytes) confirms prior literature concluding that anti-TNF-α therapy targets professional inflammatory cells and markedly attenuates B cell activation but with minimal effect on other inflammatory pathways and cell types [30]. These data could explain the marked decrease in inflammatory nodule and abscess count under ADA treatment [34], and the delayed response or non-response of draining tunnels [35,36].
The selective targeting of professional inflammatory cells by ADA is also supported by the following observations: strong expression of TNF-α and TNF-β in conjunction with ADA-induced downregulation of tissue levels, expression of the pro-apoptotic TRAIL-R1/TNFRSF10A and TRAIL-R2/TNFRSF10B, and inhibition of the pro-inflammatory, cell proliferation-stimulating cytokine IL-3.
In the HS 3D-SeboSkin model, ADA treatment reduced the secretion of the Th17 polarizing cytokines TGF-β1 and IL-1α but induced the secretion of IL-6. ADA did not modify the expression levels of either Th17 cytokines (e.g., IL-17, IL-22) or Th17 downstream effector mediators (e.g., IL-8, CCL-20). This may explain the effects seen under IL-6 secretion, as IL-6 is produced by monocytes, fibroblasts, endothelial cells, adipocytes, and normal human keratinocytes under the influence of IL-17F [37]. IL-6 inhibits the proliferation of regulatory T lymphocytes and activates Th17 cells, thus maintaining inflammation. IL-6 also stimulates the influx of T lymphocytes to the epidermis; moreover, it participates in the process of growth and differentiation of keratinocytes [38]. The high HS tissue levels of IL-6 have been shown to be significantly downregulated with the inclusion of SZ95 sebocytes in the 3D-SeboSkin model [20]. Although IL-6 serum levels were also found to increase in obese rats treated with ADA [39], ADA has been shown to reduce IL-6 circulating levels in long-term treatment studies of patients with HS and psoriasis [40,41].
Regenerative tissues are characterized by autophagy, particularly in the skin adnexa [42,43,44]. In our study, HS lesional skin expressed high levels of autophagosomal proteins, indicating strong regenerative tissue activity. Interestingly, the skin of patients with Hurley stage II, i.e., single scarring lesions separated by healthy tissue, exhibited significantly stronger expression of autophagosomal proteins in perilesional than in lesional skin. The skin of the patient with Hurley stage III, i.e., confluent scarring lesions, exhibited stronger apoptotic signals in the lesional skin. ADA seems to be involved in the regulation of autophagosomal proteins and induction of a wound healing profile, which is in accordance with previous in vivo and in vitro data [31,45].
## 5. Conclusions
The use of ex vivo studies prior to clinical trials for HS, such as the validated HS 3D-SeboSkin [15,20], in combination with existing molecular data [23], could increase the success of therapeutic candidates and minimize the required costs of overall drug development. Such preclinical studies could define the best phenotype for selective clinical response, as demonstrated in the present work. Moreover, the response profile of the registered biologic ADA has been characterized in the present study, namely the targeting of professional inflammatory cells involved in HS lesions and tissue regeneration through a wound healing profile.
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|
---
title: Improved Strength Recovery and Reduced Fatigue with Suppressed Plasma Myostatin
Following Supplementation of a Vicia faba Hydrolysate, in a Healthy Male Population
authors:
- Alish Kerr
- Luke Hart
- Heidi Davis
- Audrey Wall
- Seán Lacey
- Andrew Franklyn-Miller
- Nora Khaldi
- Brian Keogh
journal: Nutrients
year: 2023
pmcid: PMC9967853
doi: 10.3390/nu15040986
license: CC BY 4.0
---
# Improved Strength Recovery and Reduced Fatigue with Suppressed Plasma Myostatin Following Supplementation of a Vicia faba Hydrolysate, in a Healthy Male Population
## Abstract
Delayed onset muscle soreness (DOMS) due to intense physical exertion can negatively impact contractility and performance. Previously, NPN_1 (PeptiStrong™), a *Vicia faba* hydrolysate derived from a protein concentrate discovered through artificial intelligence (AI), was preclinically shown to help maintain muscle health, indicating the potential to mediate the effect of DOMS and alter molecular markers of muscle damage to improve recovery and performance. A randomised double-blind placebo-controlled trial was conducted on 30 healthy male (30–45 years old) volunteers (NCT05159375). Following initial strength testing on day 0, subjects were administered either placebo or NPN_1 (2.4 g/day). On day 14, DOMS was induced using resistance exercise. Strength recovery and fatigue were measured after 48 and 72 h. Biomarker analysis was performed on blood samples collected prior to DOMS induction and 0, 2, 48 and 72 h post-DOMS induction. NPN_1 supplementation significantly improved strength recovery compared to placebo over the 72 h period post-resistance exercise ($$p \leq 0.027$$), measured by peak torque per bodyweight, but not at individual timepoints. Muscle fatigue was significantly reduced over the same 72 h period ($$p \leq 0.041$$), as was myostatin expression ($$p \leq 0.006$$). A concomitant increase in other acute markers regulating muscle protein synthesis, regeneration and myoblast differentiation was also observed. NPN_1 significantly improves strength recovery and restoration, reduces fatigue and positively modulates alterations in markers related to muscle homeostasis.
## 1. Introduction
Muscle mass and sarcopenia are important factors when considering cardiometabolic health, cognitive function, the effect of anti-cancer therapies, as well as improved rehabilitation after injury or orthopaedic surgery and physical independence through ageing. While regular activity and resistance exercise are important parts of maintaining muscle health, exercise-induced muscle damage (EIMD) can occur following intense physical activity and resistance training [1]. This damage manifests as delayed onset of muscle soreness (DOMS) and can negatively impact people through muscle pain, reduced function and stiffness with a concomitant effect on recovery and performance [2]. Proposed mechanisms of DOMS include inflammation, calcium channel leakage, oxidative stressand muscle damage [3,4]. The cumulative effects of structural and systemic characteristics of DOMS can be recorded for up to 7 days post-exercise, with peak effects seen between 24 and 96 h [5]. Hence, there is significant scope to shorten this window.
Reducing the effects of DOMS is confounded by the molecular complexity, making interventions challenging. Nutritional intervention strategies have had some success addressing biomarker expression of DOMS [6]. Examples of successful interventions include protein supplementation, such as whey, which suppressed post-exercise increases in IL-6 levels in a female sarcopenic population, following 12 weeks of treatment [7], and omega-3 polyunsaturated fatty acids (eicosapentaenoic acid and docosahexaenoic acid), which significantly decreased circulating IL-6 and creatine kinase (CK) levels at 24 h post-isokinetic testing compared to pre-supplementation in endurance athletes [8]. Recently, using a countermovement jump protocol, a lemon verbena extract was shown to reduce muscle damage and improve recovery compared to placebo, post-EIMD, although inflammatory markers did not differ with treatment [9]. Similar benefits have been seen with tart Montmorency cherry promoting recovery and attenuating IL-6 and C-reactive protein expression following EIMD in trained cyclists [10]. In a healthy male population, 20 g/day of creatine, over 6 days, was shown to reduce muscle soreness and spikes in CK, while also improving range of motion following repeat resistance exercise sessions [11]. Additionally, an 8-day supplementation of pomegranate juice (650 mg gallic acid equivalents (GAE)/day and 1300 mg GAE/day) significantly improved recovery over 96 h, following eccentric exercise performed on day 4 of supplementation, in a non-resistance-trained healthy male population [12]. As these studies have shown that nutritional supplementations have exerted beneficial effects post-exercise, accordingly, we present a peptide application, where characterised bioactive peptides with defined activity are contained within a peptide network to affect relevant areas for muscle health function [13,14].
Characterising bioactive peptides in a nutrient-dense food source is a time-consuming and serendipitous endeavour, with multiple fractionation steps required [15]. Artificial intelligence (AI) offers the possibility of deciphering the dense molecular network within food, with the additional benefit of targeted discovery for a specific health need [15]. Recently, AI and machine learning (ML) techniques have identified active peptide networks/hydrolysates with characterised constituent key bioactive peptides in areas such as inflammation [16] and glucose regulation [17]. In line with this approach, AI and ML techniques were used to identify bioactive peptides which could address muscle protein synthesis, muscle breakdown and inflammation [18]. Among predicted peptides, two peptides were shown to significantly increase protein synthesis (histidine–leucine–proline–serine–tyrosine–serine–proline–serine–proline–glutamine; HLPSYSPSPQ) and reduce pro-inflammatory cytokine release (threonine–isoleucine–lsyine–isoleucine–proline–alanine–glycine–threonine; TIKIPAGT) in vitro. These efficacious peptides were identified in a hydrolysate derived from *Vicia faba* protein concentrate, NPN_1 (PeptiStrong™), as previously described by Corrochano et al., 2020 [18]. NPN_1 has been shown to address multiple aspects related to muscle health, including increased muscle protein synthesis, reduced tumour necrosis factor-alpha (TNF-α) secretion in vitro and reduced expression of genes associated with muscle atrophy [19]. In a hindlimb suspension murine model, following 18 days of NPN_1 supplementation, treated mice exhibited significantly reduced muscle loss in the suspended soleus muscle, increased mitochondrial biogenesis and myogenesis markers, as well as enhanced integrated density of type I and II muscle fibres [19]. Additionally, both constituent bioactive peptides (HLPSYSPSPQ and TIKIPAGT) contained within NPN_1 were shown to survive simulated gastrointestinal digestion with the potential to transfer across the lumen into the blood vessels. These peptides demonstrated adequate stability following in vitro incubation with human plasma, which may correlate to health benefits observed preclinically [18].
Previously, we have shown that NPN_1 induced an increase in phosphorylated S6 with a concomitant decrease in atrophy associated genes in vitro, with the effects translating into a benefit in a murine model [19]. In the present study, the objective was to investigate the effect of NPN_1 on strength recovery in a double-blind, placebo-controlled clinical trial in healthy male volunteers. Secondary to this, we also measured expression of a range of plasma myokines in both groups. We hypothesised that NPN_1 supplementation would have a beneficial effect on EIMD, and hence promote strength recovery.
## 2.1. Subjects
Subjects were recruited from internal databases at the study site, advertisements on social media, and notice boards in public buildings for a double-blind, placebo-controlled clinical trial in healthy male volunteers. A male population was chosen due to cohort availability. One hundred forty-two male subjects responded to the advertising campaign and received detailed information about the study. From these, seventy-six subjects were eligible for pre-screen. This trial was not powered, as this was a pilot trial, and population size was chosen based on similar studies carried out with dietary supplements. Thirty healthy, non-smoking, moderately active (exercise 1–3 times per week) males aged between 30 and 45 years with a BMI between 18 and 30 kg/m2 met the inclusion criteria. Detailed inclusion and exclusion criteria are presented in Table 1. Eligibility was evaluated by physical examination and interview with a consultant physician. All subjects conducted a COVID-19 exposure questionnaire and signed an informed consent form prior to any procedures, having been provided the information a week prior to consent.
## 2.2. Trial Design
This study was a double-blind, randomised parallel group trial that investigated the effects of NPN_1 supplementation on muscle strength and recovery after exhaustive exercise (NCT05159375; (www.clinicaltrials.gov; accessed on 16 December 2021), registered retrospectively). After inclusion, subjects were randomly allocated to either placebo (silicified microcrystalline cellulose; SMCC) or NPN_1 supplementation; randomisation was carried out using blocking (blocks of 4) according to the statistical analysis plan, by an unblinded contact in Nuritas Ltd. (AW, Dublin, Ireland). All participants and researchers were blinded for the duration of the study. Subjects were instructed to ingest the supplement with their first meal of the day. Baseline strength measurements were taken prior to supplementation. Fourteen days post-supplementation, EIMD was performed to induce DOMS. Strength measurements were repeated at 48 h and 72 h post-EIMD exhaustive exercise routine. Venous blood samples were obtained prior to commencement of the DOMS-inducing exercise routine and 0, 2, 48 and 72 h following completion of the routine. A graphical illustration of the trial design is displayed in Figure 1. This trial was conducted in compliance with the Declaration of Helsinki and ethical approval was granted by the Institutional Review Board “Sports Surgery Clinic Research Ethics Committee” (PN20.004.01). The study was performed from August 2021 to February 2022 at the Sports Surgery Clinic, Santry, Dublin, an independent study site that is focused on sports medicine.
## 2.3. Ingredient Production and Supplementation
NPN_1 (PeptiStrong™) is a proprietary ingredient derived from *Vicia faba* powdered protein concentrate, available upon request from Nuritas Ltd., and was produced according to Cal et al. [ 2020] for the specific purpose of this trial. Here, *Vicia faba* protein concentrate was homogenised in solution. Hydrolysis was achieved with a food-grade endoprotease controlling for enzyme-specific conditions, such as temperature and pH value (approximately pH 6). Enzymatic inactivation was achieved by raising the temperature to 85 °C; the solution was spray-dried utilising a standard spray-drying process at air inlet temperatures above 160 °C [19]. All batches of NPN_1 underwent peptidomics analysis using LC-MS/MS, outlined in Corrochano et al., 2021 [18]. Here, batches were correlated based on peptidomic profiles and to verify the presence of characterised constituent bioactive peptides which have previously been synthesised and validated in vitro for bioactivity, such as histidine–leucine–proline–serine–tyrosine–serine–proline–serine–proline–glutamine (HLPSYSPSPQ) and threonine–isoleucine–lsyine–isoleucine–proline–alanine–glycine–threonine (TIKIPAGT) [18]. SMCC was used as a placebo. NPN_1 and placebo were formulated into hydroxypropyl methylcellulose (HPMC) capsules of the same colour and size. Subjects were instructed to take 5 capsules daily, equating to a 2.4 g serving of NPN_1.
## 2.4. Strength Measurements
Strength measurements, as a primary endpoint, were taken at baseline (day 0), day 16 and day 17. Height and body mass were measured immediately prior to testing (Portable SECA 213 Stadiometer). All participants completed a warm-up consisting of 5 min cycle ergometer (Wattbike). Subjects then underwent concentric knee extension and flexion strength testing, assessed at an angular velocity of 60°/s through the range of 0–100° knee flexion using an isokinetic dynamometer (Cybex NORM; Computer Sports Medicine Inc, Stoughton, MA, USA). High relative reliability and moderate absolute reliability have been found for this protocol using the Cybex NORM [20,21], and an angular velocity of 60°/s has been found to identify the greatest strength deficits [22,23]. The participants performed a warm-up set of five repetitions of knee extension and flexion, building up from $60\%$ to $100\%$ of maximal effort. After a 60 s rest period, the participants completed two maximal effort sets of 5 repetitions, with a 60 s rest period between each set. They were instructed to push and pull as hard and fast as possible against the resistance with verbal encouragement. The non-dominant limb was tested first before repeating the procedure with the dominant limb.
## 2.5. Exhaustive Exercise Test (EET)
EET was performed on day 14 of supplementation. Height and body mass were measured immediately prior to testing. All participants completed a warm-up consistent with the strength measurements regime. Following the warm-up and a 90 s rest period, the participants completed five maximal effort sets of 8 repetitions, with a 90 s rest period between each set. Subjects were given verbal instructions to push and resist while performing the EET. The non-dominant limb was tested first before repeating the procedure with the dominant limb.
## 2.6. Fatigue Index (FI)
FI was calculated as FI = [(highest force − lowest force)/(highest force)] [24]; this exploratory analysis was calculated from strength measurements already recorded by participants. Highest force was calculated as the average torque from all repetitions from the initial maximal effort set on the isokinetic dynamometer. Lowest force was calculated as the average torque from all repetitions from the final maximal effort set on the isokinetic dynamometer.
## 2.7. Myokine Array
The MILLIPLEX multiplex assays (Merck, Darmstadt, Germany) using xMAP technology (Luminex Corporation, Austin, TX, USA) was used to analyse the concentrations of various analytes within the plasma samples. MILLIPLEX magnetic beads panels (Merck) were used to analyse 14 myokines. A full list of analytes can be found in Supplementary Table S1. All procedures were performed according to the manufacturer guidelines. Standard curves were created for each analyte, using standard concentrations depending on manufacturer guidelines for each panel. Two quality controls provided in the kits were added to each panel. Analysis of Luminex panels was performed using the Luminex 200 (Luminex Corporation) instrument; for acquisition, the xPONENT software (v.3.1.7; Luminex Corporation) was used. The median fluorescent intensity was analysed using a 5-parameter logistic curve-fitting to calculate the concentration of analytes in each sample.
## 2.8. Data Analysis and Statistics
The analysis objective was to observe differences in the strength recovery, fatigue index and plasma markers between placebo and NPN_1 supplementation. Adjudication of trial adherence was performed blinded; those who did not adhere to the inclusion/exclusion criteria throughout the trial were removed from the per protocol analysis group.
Data were analysed using GraphPad Prism Version 9. Descriptive statistics are presented numerically in terms of the mean ± SEM, and graphically using error bar plots and boxplots. All statistical tests were performed two-sided and interpreted using a $5\%$ level of significance. For exploratory purposes, appropriate additional tests were used to determine between- and within-group differences. Where appropriate, a ROUT outlier analysis was performed with a $1\%$ threshold [25]. Where appropriate, data satisfied the conditions of normal distribution and homogeneity of variances (confirmed with the appropriate plots and using Shapiro–Wilk and Levene tests, respectively). For the evaluation of treatment effects on strength recovery over the course of the study, a repeated measures ANOVA and incremental area under the curve (iAUC) analysis were performed. For the evaluation of the treatment on strength recovery at each time point, Student’s t-test was performed. Strength recovery was calculated relative to each subject’s baseline strength test pre-supplementation, expressed as peak torque/body weight. For the evaluation of treatment effects on FI and serum plasma markers over the course of the study, a repeated measures ANOVA was performed. For the evaluation of the treatment on FI and serum plasma markers at each time point, if normal distribution was satisfied, Student’s t-test was performed; otherwise, a Mann–Whitney test was performed. Due to explorative data analysis, no correction for multiple comparison was performed. The results presented below refer to the per protocol data set (PP). PP criteria were pre-defined in the protocol: missing data, adverse events or use of prohibited concomitant medication interfering with study results, and major protocol violations. As stated above, adjudication to determine adherence to the protocol was performed blindly and agreed upon by four adjudicators.
## 3.1. Trial Design
A total of 44 subjects were randomised for this trial, of which 30 completed the study (Figure 2). Eight subjects did not attend following the initial screen visit at day 0. Four subjects withdrew following the exercise session on Day 14 and two subjects did not complete the protocol.
Deviations from protocol are outlined in Table 2. If a subject exercised within 48 h of the initial exercise session on Day 14 and recorded a score of 13 or higher on the Borg Scale, they were excluded from the PP population.
Five participants were excluded from the PP population. Anthropometric data are outlined in Table 3. Age, height, body mass and BMI were evenly distributed between the two treatment groups. There were no serious adverse events reported. Non-serious adverse events included two reports of muscle tightness on isokinetic dynamometry, one case of high blood pressure which settled post-testing with no issues, and one case of total body DOMS which prevented participation in Day 16 testing. This subject recovered fully with no pain 48 h following Day 17.
## 3.2. Strength Recovery
Peak torque per bodyweight, the measure of muscle strength, was obtained at baseline (pre-supplementation), 48 h (16 days of supplementation) and 72 h (17 days of supplementation) after the exhaustive exercise routine. Inter-group analysis for pre- and post-EIMD showed that muscle strength was significantly reduced ($$p \leq 0.032$$) from baseline in the placebo group at 48 h, whereas no significant reduction in strength was observed in the NPN_1-supplemented group. By 72 h, the NPN_1 cohort showed a significant increase ($$p \leq 0.025$$) in strength from baseline values, whereas the placebo cohort did not (Figure 3a). Additionally, subjects who received NPN_1 recovered to baseline values within 48 h and increased significantly higher ($$p \leq 0.025$$) than baseline values at 72 h. However, subjects supplemented with placebo displayed a significantly ($$p \leq 0.032$$) lower recovery from baseline values at 48 h and still had not fully recovered to baseline within 72 h. To assess the effect between groups over the test period, an iAUC analysis was carried out for each participant leg, followed by ROUT analysis, with a $1\%$ threshold (Figure S1). While the total number of participants in each analysis did not change (Placebo, $$n = 10$$; NPN_1, $$n = 14$$), single data points for three participants within the NPN_1 group were removed. As shown in Figure 3b, NPN_1-supplemented subjects showed a significant increase ($$p \leq 0.020$$) in strength recovery compared to placebo over the 72 h period post-resistance exercise, while no significant change was observed at individual timepoints.
## 3.3. Fatigue Index
FI was determined by measuring the difference in mean torque of the repetitions performed in the maximal effort sets at baseline, 48 and 72 h post-exhaustive exercise routine. No differences were observed in baseline FI values between groups. Subjects supplemented with NPN_1 showed a significant ($$p \leq 0.002$$) benefit on FI (Figure 4a), leading to a significant performance benefit over the 72 h period post-DOMS induction, compared to placebo ($$p \leq 0.041$$; Figure 4b).
## 3.4. Molecular Markers of Muscle Recovery
A myokine array was performed for a range of biomarkers associated with muscle health on serum samples from subjects 30 min before exhaustive exercise on Day 14 (−30 min), immediately following exhaustive exercise (0 h); 2 h following exhaustive exercise (2 h); 48 h following exhaustive exercise; Day 16 (48 h); and Day 17 (72 h). Eight analytes of interest are shown in Figure 5; the results for the remaining myokines are shown in Figure S2. Expression of IL-6 was higher at the 0 h timepoint following NPN_1 supplementation compared to placebo (Figure 5a). IL-6 concentrations did not differ significantly over the course of the study ($$p \leq 0.138$$) and returned to baseline values within 48 h. Similarly, the concentration of IL-15 was elevated following NPN_1 supplementation compared to placebo, although not significantly over time ($$p \leq 0.159$$; Figure 5b); values for both cohorts returned to baseline within 2 h post-exhaustive exercise. Interestingly, IL-15 release was significantly higher immediately post-DOMS compared to baseline (−30 min) within the NPN_1 treatment group, with no treatment effect seen. Fractalkine and irisin exhibited similar pre/post-DOMS induction profiles within each group (Figure 5c,d). Here, release was transiently increased significantly immediately post-DOMS for both groups for fractalkine (NPN_1, $$p \leq 0.030$$; Placebo, $$p \leq 0.003$$) and irisin (NPN_1, $$p \leq 0.009$$; Placebo, $$p \leq 0.031$$). All groups returned to baseline values within 2 h following exhaustive exercise. FGF21 release was reduced following DOMS induction in the NPN_1 supplementation group; however, this was not statistically different over the course of the study ($$p \leq 0.066$$; Figure 5e). Of note, subjects within the placebo-supplemented arm recorded significantly higher than baseline values immediately post-DOMS ($$p \leq 0.0266$$). Myostatin release was significantly inhibited in the NPN_1-supplemented arm compared to placebo over the course of the study ($$p \leq 0.006$$), whereas the placebo group exhibited significantly higher myostatin release at 0 h compared to baseline values (Figure 5f). The placebo treatment arm displayed a significant increase in osteocrin/musclin release over the course of the study compared to NPN_1 treatment ($$p \leq 0.009$$; Figure 5g). A significantly higher treatment effect on osteonectin/SPARC was seen with NPN_1 treatment compared to placebo ($$p \leq 0.025$$; Figure 5h).
## 4. Discussion
In this study, NPN_1 supplementation improved strength recovery, reduced fatigue and suppressed myostatin expression in a healthy male population following EIMD. Previously, we have shown that NPN_1 induced an increase in phosphorylated S6 with a concomitant decrease in atrophy-associated genes in vitro [19]. Thus, we hypothesised that NPN_1 supplementation would have a beneficial effect on exercise-induced muscle damage, and hence promote strength recovery. Following induction of DOMS, a decrease in strength was observed in both cohorts. A significant ($$p \leq 0.020$$) recovery in muscle strength was observed following NPN_1 supplementation compared to placebo over the 72-h period post-resistance exercise. Fatigue was significantly decreased ($$p \leq 0.041$$) over the same 72-h period in the NPN_1 group compared to placebo. Additionally, the release of myostatin post-DOMs was beneficially modulated ($$p \leq 0.006$$) in the NPN_1-supplemented group compared to placebo. As a reduction in muscle damage and fatigue is known to protect muscle post-strenuous exercise [26,27], these cumulative results indicate the potential for NPN_1 to reduce the severity of DOMS and improve recovery, hence allowing a faster return to training.
Exploratory iAUC analysis showed a $54\%$ improvement in performance of isokinetic leg extension with NPN_1 supplementation compared to placebo over the 72 h after EIMD. NPN_1 supplementation significantly increased muscle strength recovery ($$p \leq 0.027$$), and accordingly, a full recovery of strength was recorded within the window when the peak effects of DOMS are typically observed (24–96 h) [5]. Different methods to induce muscle damage are used for different nutritional intervention studies. A similar EIMD protocol carried out with tart cherry (120 g/day TartVitaCherry®) in a healthy male and female population showed no significant differences for strength recovery [28], while other types of muscle damage induction have shown beneficial effects on strength recovery with tart cherry [10,29] and other nutritional supplements, such as lemon verbena [9]. In a previous study in resistance-trained individuals with several years of experience, supplementation with branched-chain amino acids (BCAA) for eight days at 0.22 g/kg/day showed no effect on muscle function after eccentric EMID; however, they did record a decrease in muscle soreness, indicating the importance of perceived benefits to supplementation [30]. In the current study, subjects within the NPN_1-supplemented arm recovered fully within 48 h and exceeded baseline values at 72 h. In contrast, the placebo-supplemented arm had lower recovery values compared to baseline at 48 h and had still not fully returned to baseline following 72 h. Resistance-type exercise is known to increase muscle protein synthesis through activation of mTOR for up to 36 h, with repeated exercise activating ribosomal activation and total RNA (ribonucleic acid) content [31]. Importantly, increased muscle protein synthesis has been shown to help induce muscle repair [32]. Previously, NPN_1 was shown to induce expression of genes involved in myogenesis (mTOR and MYF5) in a murine model of atrophy as well as p-S6 expression in vitro [18,19]. These observations indicate that NPN_1 would be a candidate for use in muscle repair or adaptation in vivo. We recently concluded a study to investigate the effects of NPN_1 supplementation on short-term immobilisation and subsequent recovery [33]. In the study, healthy males received either 10 g of NPN_1 or milk protein concentrate (MPC) twice daily whilst subjected to 7 days of one-legged knee immobilisation followed by 14 days of ambulant recovery. NPN_1 performed similarly to MPC for recovery of muscle mass and strength; however, subjects supplemented with NPN-1 regained muscle strength to the level measured at baseline, whereas the subjects supplemented with MPC did not. An important indicator of the balance between protein synthesis and protein breakdown is the muscle fractionate synthetic rate (FSR). An increase in FSR indicates that protein synthesis supersedes the rate of protein breakdown and is a measurement of muscle conditioning [34]. Of key clinical interest was the finding that NPN_1 significantly outperformed MPC in FSR, indicating a possible benefit for anabolic pathways and a possible shorter recovery period. While plant proteins have been shown to increase FSR but only to the same level as milk [35], this is a highly significant finding for a plant protein source to outperform an animal one. The increase in FSR observed with NPN_1 is not observed with the raw unhydrolysed material, indicating that the effect is mediated by the AI-predicted bioactive peptides [36]. Consequently, in line with previous studies, a peptide-specific benefit within NPN_1 supplementation for muscle protein synthesis may help stimulate strength recovery and improve recovery beyond baseline post-EIMD. This is further supported in the current study, as administration of 2.4 g of NPN_1 would not elicit nutrition-associated anabolic effects without peptide-specific signalling events on relevant pathways, and subjects would have sufficient dietary protein.
Muscle fatigue is a major symptom of DOMS. The fatigue index measurements at 48 and 72 h post-EIMD were calculated using the highest and lowest force recorded during these sets [24]. Following induction of DOMS, fatigue was significantly attenuated over each set in the NPN_1-supplemented arm compared to placebo. The reduced fatigue index recorded with NPN_1 supplementation is in line with the improved strength recovery values compared to baseline. Similarly, lemon verbena supplementation exhibited reduced fatigue; this was not calculated through a fatigue index, they inferred the benefit through attenuated maximal voluntary contraction following resistance-type exercise and complete recovery within 48 h following EIMD [9]. This study also induced DOMS differently, using a countermeasure jump protocol, and may introduce variability in DOMS induction. Importantly, the severity and consistency of exercise-induced DOMS is dependent upon the method used to induce it. Many studies use free exercise, e.g., squats or counter-jumps, to induce DOMS. These add variability from subject to subject as there is less control versus isokinetic dynamometry, which brings greater consistency to our study for DOMS induction. A major contributory factor to muscle fatigue experienced during DOMS is impaired calcium release [37]. Interestingly, NPN_1 supplementation was previously shown to increase expression of PPP3CA in a murine disuse model [19], which is induced through elevated calcium release and results in the expression of calcineurin and is an important factor in muscle regeneration following injury [38]. Additional biomarkers such as those for ATP metabolism and ROS could be beneficial to investigate to further elucidate the mechanisms involved in the improved fatigue index effect following NPN_1 supplementation.
Myokines are cytokines released by muscle cells in response to muscular contractions [39], the measurement of which in the plasma can give an indication of injury to muscle tissue. We used a myokine array to investigate the effect of NPN_1 supplementation on muscle strength recovery. We observed that several myokines were beneficially modulated immediately after the induction of EIMD in the NPN_1 group. Of note, we recorded an increase in irisin expression, which can induce glycogenesis [40], as well as a significant increase in IL-15 ($$p \leq 0.159$$), which has been linked to increased muscle mass and can promote myoblast differentiation [41]. This glycogen replenishment and possible muscle regeneration may, in part, be responsible for the improved strength recovery and the fatigue index recorded following NPN_1 supplementation. The myostatin–Smad$\frac{2}{3}$ pathway is a major signalling pathway for protein synthesis, where myostatin acts as a negative regulator [42]. Myostatin was significantly suppressed in the NPN_1 group compared to placebo over the course of the trial, as was the release of fibroblast growth factor 21 (FGF21) in the NPN_1 group at 0 and 2 h. These combined data indicate clinical evidence of attenuation of muscle breakdown with NPN_1 supplementation [43,44], albeit further work is required to identify the minimal clinically important difference in muscle strength recovery and NPN_1 supplementation in a powered trial. In this respect, it is difficult to compare the effect of NPN_1 supplementation on myostatin to other nutritional interventions such as tart cherry, pomegranate and lemon verbena, as many studies into effects on EIMD focus on inflammatory and oxidative stress biomarkers rather than muscle health biomarkers [9,45,46]. It is known that acute transient inflammation promotes healing of healthy skeletal muscle [47]. For example, IL-6 is a major regulator of myogenesis, and acute IL-6 expression can increase protein synthesis, satellite cell proliferation and can lead to an anti-inflammatory signalling cascade [47]. In similar previous studies, tart cherry [10,29] and omega-3 polyunsaturated fatty acids [8] were shown to have an overall treatment effect on attenuating IL-6 compared to placebo, whereas lemon verbena [9] and pomegranate did not produce treatment effects [45]. Interestingly, in the present study, IL-6 expression was transiently increased at 0 h post-EIMD in the NPN_1 group, which may aid in the improved strength recovery observed. As changes return to baseline quite quickly, the likely source of IL-6 is the myocyte, as opposed to an immune cell release of IL-6. The upregulation of myokines such as fractalkine, osteocrin/musclin and osteonectin/SPARC has been shown to play a role in regeneration, mitochondrial biogenesis and adaption of muscle to exercise [39,48,49]. The significant increase in expression of fractalkine ($$p \leq 0.030$$) and osteonectin/SPARC ($$p \leq 0.025$$) in the NPN_1 group may contribute to the reduced fatigue experienced following EIMD. Additionally, another important finding was the significantly higher expression of osteocrin/musclin ($$p \leq 0.009$$) in the placebo treatment arm compared to NPN_1. This contrast may indicate a mechanism of action for NPN_1 independent of osteocrin/musclin, which is an important factor to consider in future studies.
As predicted using AI, the in vitro effects observed for NPN_1 [19] have translated into a clinical benefit for strength recovery. Of note, this characterised ingredient with cell-specific signalling for protein synthesis and anti-inflammatory effects could be used in a complimentary supplement approach with other efficacious ingredients. NPN_1 supplementation may thus serve to achieve a balance between muscle protein synthesis, muscle breakdown and inflammation, inducing a quicker return to muscle homeostasis post-EIMD.
A limitation of the current study would be the comparison of NPN_1 to SMCC rather than an unhydrolysed *Vicia faba* protein, which should be addressed in future studies. An additional limitation to note is the different physiological response of male and female subjects to nutritional interventions. For example, a gender effect on blood lactate was seen in subjects following supplementation with mango leaf extract during repeated sprint exercises [50]. Therefore, it would be of interest in future studies to assess the effects of NPN_1 in a female cohort.
## 5. Conclusions
NPN_1 is a characterised plant-based efficacious ingredient that we have shown at low dose to improve strength recovery and reduce fatigue following strenuous activity. In this trial, we have further shown that NPN_1 supplementation altered the plasma concentration of myokines associated with muscle health and/or glycogen metabolism, with a subsequent benefit for strength recovery. As such, NPN_1 represents a potential supplement to promote faster recovery following strenuous activity.
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|
---
title: The Nexus of Sports-Based Development and Education of Mental Health and Physical
Fitness
authors:
- Tiejun Zhang
- Huarong Liu
- Yi Lu
- Qinglei Wang
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967856
doi: 10.3390/ijerph20043737
license: CC BY 4.0
---
# The Nexus of Sports-Based Development and Education of Mental Health and Physical Fitness
## Abstract
Physical inactivity has increased globally, particularly in developed nations. A high proportion of the human population is unable to meet the physical activity recommendation of the World Health Organisation due to hypertension, metabolic syndrome, obesity, and other medical conditions. Non-communicable diseases and mental health problems are becoming more prevalent, particularly in low and middle-income nations. This study aimed to determine the effectivenessof a mentorship programmeon university students’ mental health and physical fitness. The intervention comprised the effects of sports-based development and education on physical fitness and mental health. A total of 196 and 234 students from two universities were randomly assigned to the intervention and control groups, respectively. The primary outcomes were engagement in physical activities (number of push-ups for 1 min, the strength of hand grip (kg), and the Jump test while standing (cm)), body fat proportion and psychological resilience, self-efficacy, and relationship with family and schoolmates. Participants in the control group had access to a web-based health education game, whereas the intervention group wassubjected to intensive interventional activities for one month based on the eight principles of the National Research Council and Institute of Medicine. Data were analysed using Analysis of Variance (ANOVA) to compare the physical and mental components between the intervention and control groups. Relative to baseline, all the physical health components (push-ups, sit-ups, and jump tests), psychological resilience, relationship with family members, and self-efficacy increased significantly in the intervention compared to the control group. Body fat composition was significantly reduced in the intervention when compared tothe control group. In conclusion, the mentorship programme effectively improved the participants’ physical and psychological health and could be developed further for application in a larger population.
## 1. Introduction
Physical activity is defined as “any bodily movement that occurs with energy consumption using our muscles and joints” [1]. Physical activity contributes significantly to the development of physical and spiritual aspects of individuals by promoting community well-being, protecting the environment, and investing in future generations. Meanwhile, physical inactivity remains a global health problem [2,3].
Physical inactivity is a common risk factor for chronic diseases [4]. It increases the odds of non-communicable diseases, such as diabetes, obesity, high blood pressure, cancers and metabolic diseases. In other words, physical inactivity plays a vital role in the reduction in life expectancy and quality, while being among the highly-ranked risk factors for mortality worldwide ($6.0\%$ of deaths globally) [5,6].
Specifically, physical inactivity is considered the main cause of 20–$25\%$ of colon and breast cancers, $30\%$ of ischaemic heart disease, and $27\%$ of diabetes [6,7]. The increased prevalence of obesity has also been linked to widespread sedentary lifestyle and physical inactivity [6]. These events are supported by findings from epidemiological studies that showa 30–$50\%$ increased prevalence of major causes of mortality occurring in the physically inactive group [2]. Figure 1 presents the common consequences of physical inactivity and its link to psychologically or biologically stimulating insidious bad habits, such as low-function fitness, smoking, poor nutrition, and psycho-social distress, as highlighted by [8]. These factors may eventually increase the risk of serious illnesses such as diabetes, cardiovascular disease, stroke, kidney disease, and various cancers.
Mental health issues are now a major concern in low- and middle-income countries (LMICs). The incidence of mental disorders is increasing at an alarming rateas more people are moving to cities with and are therefore being exposed to several risk factors fordeveloping anxiety [10]. Physical inactivity is also associated withurban development and the rise of health complications globally [11,12]. As unplanned urbanisation increases, the availability of open spaces decreases, leading to a decline in physical activity [12]. A Cochrane review of PA and health wellness benefits in school-aged youngsters revealed that urbanicity positivelyimpacts risk factors for non-communicable diseases and psychological health [13].
The recent COVID-19 pandemic has also heightened the risk of mental disorders, as factors such as social isolation—studying and working at home, reduced physical interaction and contact with other individuals may be strong psychological stressors [14,15]. These factors elicit negative lifestyle alterations such as poor diet and physical activity [16]. The lack or reduction in physical activity has been associated with a higher risk of mental disorders, including depression and anxiety [17]. In contrast, a positive relationship was reported between improved psychological outcomes and physical exercise [18], as its neurobiological impacts appear to influence diverse neural mechanisms relating to anxiety and depressive disorders [19]. Despite there being no ideal dose of exercise for mitigating mental disorders that hasbeen documented, accumulated evidence from the literature suggests that the risk of mental disorders is reduced by any exercise compared to complete physical inactivity [17,18]. Aprior study also indicatedthat regular physical exercise is comparable to pharmacological measures for the management of depression and anxiety [20].
Mental disorders and other consequences of physical inactivity are profound in children, especially during adolescence [21]. Several studies have documented the benefits of a physically active lifestyle during adolescence, ranging from better muscular fitness and cardiometabolic and cardiorespiratory health to positive effects on BMI and body weight [22,23]. Additionally, improved prosocial behaviour and cognitive development among children have been linked to the positive impacts of physical activity [1]. To achieve these benefits, the WHO and US guidelines recommended that adolescents should perform at least 60 min of physical activity daily [24,25]. As a result, recent studies have advocated for interventions to promote engagement in physical activity and lifestyle behaviours to improve the mental and physical health of school-aged children and the adolescent population [26].
Overall, physical exercise appears to offer benefits in reducing anxiety and depression scores in children and adolescents, but it is difficult to draw firm conclusions due to the limited number of research findings, the clinical diversity of participants, interventions, and measurement methods [20]. In the past 15 years, the number of research studies on adolescent major depressive disorder due to physical inactivity has increased dramatically, with a significant proportion being clinical studies of medication and cognitive behavioural therapy. However, the response and remission rates have been low [27]. Additionally, the majority of positive responders post-treatment experienced many persistent symptoms, in addition to seriously impaired functioning, and high levels of relapse. More efficient therapies are required to cure this severe and chronic illness that typically lasts into adolescence and haspoor long-term consequences. Early treatment studies indicated that exercise and other therapies might effectively treat teenage major depressive disorder [28]. There are few robust analyses of existing sport-based development initiatives, and there is little proof that backs up such claims [13]. For this reason, research on evaluating dataneeds to be carried out to address these gaps.
It is critical to ascertain whether reducing depressive symptoms may be achieved with a non-medication treatment, especially in light of recent concerns regarding the long and short-term safety of selective serotonin reuptake inhibitors (SSRIs) and other antidepressants [29]. Mentorship programmes have been considered to be an effective non-pharmacological approach to ameliorating depressive symptoms and other health problems linked to physical inactivity among school-age children [30]. For instance, peer-to-peer mentoring provided by local high school students strengthened sustainable behavioural change and had positive impacts on BMI and engagement in daily physical activity [29]. However, the effectiveness of mentorship regarding sport-based development on physical and mental health has not been widely explored. This study aimed to determine the efficacyof a mentorship programme based on sport-based development on university students’ physical and mental health.
Reviews of the Intervention Impacts on Physical Fitness and Mental Health The sport-for-development intervention was the Gum Marom Kids League (GMKL), a society programme that ran for 11 weeks [31]. The primary objective of the GMKL was to employ sports to enhance peoples’ physical and mental health, subsequently making the neighbourhood a more enjoyableplace [32,33]. During the GMKL, all participants performed significantly better in all activities on Mature Fine Tailing (MFT). However, for men and women, the between-group MFT treatment effects were slightly different but not statistically significant [28]. According to the girls’ data after adaptation, individuals who received assistance fared much better than the group that did not receive any assistance [34].
The sport-for-development infrastructure positsthat sports benefit society and health [35]. Evidence shows that these arguments are not always accurate and contradict the statistical inferences that PA benefits young people’s mental well-being [32,34]. This is crucial to emphasise for governments and organisations that manage initiatives, develop policies, and engage with patients to disseminate these alerts and encourage participation in sports to increase PA and enhance health [36]. One optimistic way to look at the mental health outcomes is to assume that the adolescents involved directly in the sport-for-development intervention felt more at ease interacting with their challenges, which led to a role conflict. However, the instrument used to assess mental health was responsive, valid, and efficient for analysing depression and anxiety-like illnesses [36,37].
## 2.1. Research Design
This study was a randomised control trial involving an experimental (intervention) and a control group (no intervention). The study was conducted in Henan province, China among university students aged 17–28 years old from the Henan University of Economics and Law and Zhengzhou University, Henan province, China. In total, 430 participants were recruited and randomly assigned to either the intervention or the control group. Randomisation was performed by tossing a coin. Participants in the intervention group participated in a sports mentorship programmefrom May 2022 to June 2022.
## 2.2. Inclusion and Exclusion Criteria
This study included students from the two aforementioned universities who were between the ages of 17 and 28 years old. Students who agreed to follow the whole study process and were interested in sports were included. All students provided written consent and participation was voluntary. The students who had underlying chronic disorders, diabetes, respiratory or cardiological abnormalities, and a history of mental disorders and those who opted out in the middle of the study were excluded from this study.
## 2.3. Recruitment and Randomization
Since this study was conducted atthe researchers’ institutions, it was easy to contact the potential participants in the relevant departments for recruitment purposes. The head of the department of the Sports Ministry was contacted and briefed on the research objectives and procedures. Thereafter, the students’ contact information was obtained from the relevant office in the department. Students were also reached during face-to-face classes to inform them of the research objectives, procedures and benefits. Upon applying the inclusion and exclusion criteria, a total of 400 students were considered eligible to participate in the study.
Randomisation was performed by tossing a coin. Given the sampling frame of 400 students, a participant was randomly assigned to the control group upon obtaining a head from tossing a coin and the next student was allocated to the intervention group. This process led to a total of 236 and 194 participants in the control and intervention groups, respectively.
## 2.4. Ethical Approval
The Ethical Committee of the Henan University of Economics and Law, and Zhengzhou University, Henan province, China, approved this study. The ethical approval was assigned as 202203/HNCN$\frac{1003}{168.}$ Each participant was briefed about the study process and objectives, and the students were informed of their respective groups (either intervention or control) before starting the intervention. Participation was voluntary and only those that provided written and informed consent were recruited for the study. Apart from the expected benefits of participating in the intervention, no incentive was given for participating in this study.
## 2.5.1. Framework
This afterschool sports mentorshipcontrastswithphysical education programmesthat emphasise sporting abilities, use sports to empower adolescents, and foster life skills. The eight principles of Positive Youth Development (PYD) are sports skills, school engagement, healthy living, positive character, self-direction, teamwork, leadership, and community engagement. These are derived from the National Research Counciland the Institute of Medicine, and both served as the foundation of the intervention framework. This framework was adapted from theabove institute so that the principles would be valid and modified to suit the Chinese population. These principles guaranteed the students’ physical and mental wellbeing, a friendly and productive environment (such as supportive relationships and constructive social norms), and an appropriate programme framework for skill development. This framework was expected not to affect the participants’ mental status.
## 2.5.2. Delivery of the Intervention
The participants (aged 17–28 years old) received the intervention in small groups, which made it convenient to organizeeach day’s schedule and monitor the participants. This intimate setting provided a chance for interaction, a feeling of community, and a more supportive and youth-centred environment. Each small group of 17 students selected the sport they wanted to learn. Among the sports chosen by the students were kickboxing, basketball, and volleyball, which were based on their availability at the University. This programme adopted a different approach compared to traditional physical education sessions and was not teacher-centred. Instead of being a teacher, the mentors insteadserved as a facilitator. For instance, no established curricula specified what sporting skills should be taught. Each group’s learning routes were chosen through conversation between the mentors and the students.
The intervention was delivered by mentors, who were certified sports coaches from regional sports organisations. In addition, they received instructions on howto use PYD ideas and sports psychology throughout their prior professional training (higher diploma or bachelor’s degree). Before the intervention, the study team provided a one-day session covering PYD and youth psychology basics, safety measures for physical and mental health, the program’s guiding principles, and a semi-structured curriculum. Anenvironment that prioritises young people was emphasised. As an illustration, the mentors were instructed to assist the participants in establishing their athletic goals. Additionally, problem-solving methods specific to the world of sports were offered. These were created to encourage the development of resilience.
## 2.5.3. Structure and Components of the Intervention
The curriculum was the same for each group and was semi-structured. The intervention was split into two comparable halves (each with nine sessions), spaced apart by school holidays and examinations in December and January. Each section beganwith two sessions of warm-up and introduction, during which the mentor presentedthe selected sport through purposeful play. The students then spoke about what kind of sporting goal they would like to achieve over the following half session (45 min). After establishing their goals, the students worked on improving their sporting abilities throughout seven sessions with the help of their peers and mentors, who also provided problem-solving strategies through experiential learning. The physical activities in the programme includedpush-ups for 1 min, the strength of hand grip (kg), and a jump test while standing (cm). Participants were also instructed to rate their relationship with family and schooling activities. Self-efficacy and psychological resilience were also assessed using a structured questionnaire.
The 45-min debriefing that followed was used to consolidate skills and engage in self-reflection. The participants could also use the abilities they had learnedin other areas of their lives. Approximately $83\%$ (or 1350 min) of the programme was allotted for participating in sports or PA, while $17\%$ (or 270 min) was devoted to mentor-led instruction, presentation, and discussion. The majority of the programme was taught in classrooms. When the school could not provide the necessary location or facilities, nearby community centres were utilised.
## 2.5.4. Monitoring of the Intervention and Outcomes
Researchers and research assistants visited one quarter of the randomly chosen sessions to verify programme fidelity. The mentors were reminded if the observers noticed students who were not participating in the sessions. The testing revealed that the mentors could follow the semi-structured curriculum and PYD principles. Metrics were constructed into the physical training timetable so the group members could easily obtain and keep a record of them. All of the chosen school systems were given an evaluation day scheduled with the school principals. Throughout the week before the day set aside for the evaluation, all of the participants were informed about the procedure and given written material fortheir parents or guardians [31]. For every outcome measured, the level of involvement in the guideline and follow-up test methods was unique and individualised [28,31]. During the study period, the students were instructed not to interact with each otherin order to avoid bias.
Meanwhile, the students in the control group were asked to access a web-based health education game with 400 questions on healthy lifestyles during the study period. The university’s computer room was provided to thosestudents without internet or computer access. Similarly, students were not allowed to interact in order to minimise bias.
## 2.6. Assessment of Primary Outcomes
The primary outcomes assessed in this study are broadly categorised into three broad aspects: physical activities, physical and mental health, and relationships/self-efficacy. For physical activities, the variables considered include the overall score for physical activity, number of push-ups for 1 min, the strength of hand grip (kg), and the jump test while standing (cm), whereas body fat proportion and psychological resilience were recorded as indicators of physical and mental health, respectively. Body fat composition was estimated by assessing waist circumference as described by [38]. Prior research has reported significant correlations between waist circumference and measures of abdominal fatness measured by magnetic resonance imaging [39,40]. For the third aspect, self-efficacy and relationships with family and school were documented, as mentioned in the previous section.
## 2.7. Statistical Analysis
This study used SPSS 25 (IBM Corporation, Armonk, New York, Uniteed States) and Excel software for effective statistical analyses. All the data were subjected to normality tests based on the levels of kurtosis and skewness. As a result, all of the data conformed to the assumptions of normality tests and were considered normally distributed. The descriptive measurements were expressed as mean ± standard deviation (SD), and the changes in the parameters were calculated for in-depth analysis before and after the intervention. The study employed ANOVA analysis for the significance test. The level of significance was tested at α = 0.05.
## 3.1. Descriptive Results
Table 1 summarises the participants’ characteristics in terms of age, gender, BMI and socio-economic class. This result presents the baseline characteristics of each group.
The mean age of participants in the control and intervention groups was 22.52 (±3.60) and 22.29 (±3.15), while the BMI was 26.95 (±2.90) and 26.65 (±2.69), respectively. No significant difference ($p \leq 0.05$) was recorded for both variables between both groups. In terms of gender, $50.4\%$ ($\frac{119}{236}$) of the students in the control group were males compared to $48.4\%$ ($\frac{94}{194}$) in the intervention group. This reflects that male and female participants were randomly assigned to both groups. Similarly, no significant difference was observed between each group in terms of socioeconomic class.
## 3.2. PhysicalActivity and Specific Exercises
Table 2 presents the results for the number of push-ups for 1 min, the number of sit and ups test for 1 min, the strength of hand grip (kg), and overall physical activity. No significant difference was observed in baseline values for each parameter between the intervention and control groups. In the control group, comparisons of each parameter before and after the web-based health education game depicted no significant differences. However, the scores for all the parameters in the intervention group increased significantly post-intervention compared to the baseline values.
## 3.3. Body Fat Composition and Psychological Resilience
As shown in Table 3, body fat composition and psychological resilience did not differ between the groups at the baseline or before the intervention. While no difference was detected in each parameter before and after the web-based health education game in the control group, the intervention group experienced a significant decrease in body fat proportion and increased psychological resilience post-intervention.
## 3.4. Self-Efficacy and Relationship with Family and School Activities
Results for the self-efficacy and vital relationships with family and schoolmates are presented in Table 4. All of the variables were not significantly different between both groups at the baseline. However, the intervention group reflected a significant increase in self-efficacy and relationship with family members after the intervention, but no difference was observed in the relationship with schoolmates. In the control group, none of the parameters was significantly different between pre and post-exposure to a web-based health production game.
## 4. Discussion
This study explored the effectiveness of a mentorship programme in promoting engagement in physical activity among university students at two universities in China. Furthermore, the study investigated the impact of the intervention on specific exercise activities, self-efficacy, body fat composition, psychological resilience, and relationships with family members.
Globally, psychological health and well-being have been emphasised as crucial concerns. As a tool for navigating workplace difficulty, the idea of resilience for professionals has grown in popularity. College students confront unique challenges and are at increased risk for mental health issues. Children and adolescents are frequently at risk for depressive symptoms, including mood swings, apathy, general discontent, guilt, hopelessness, loss of interest, and loss of interest or pleasure in activities [41]. The research on this topic hasintensified (asmentioned above), asunhealthy symptoms are the leadingcause of numerous diseasesand impairments, especially among adolescents and college students.
Several studies have documented the benefits of a physically active lifestyle during adolescence, ranging from better muscular fitness, cardiometabolic and cardiorespiratory health, to positive effects on BMI and body weight [22,23]. Additionally, improved prosocial behaviour and cognitive development among children have been linked to the positive impacts of physical activity [36]. Thus, physical fitness and exercise are one of the most current strategies used to promote youth health outcomes. PAprogrammes and health promotion policies should be created to enhance cardiorespiratory fitness, muscle fitness, and speed agility. Schools may have a significant impact by recognising students with poor physical fitness and encouraging students to engage in healthy activities [29].
The mentorship programme used in this study focused on physical activities developed based on the eight principles of the National Research Council and the Institute of Medicine. Students in the intervention group were exposed to these intensive interventional activities for one month, and vital parameters such as specific exercise activities, self-efficacy, body fat composition, psychological resilience, and relationship with family members were assessed. These parameters were used as indicators of physical and mental health.
In the present study, the intervention group recorded a significant increase in self-efficacy and psychological resilience compared tothe control group. These findings are consistent with prior studies in which exercise performed independently or in conjunction with other measures was found to boost young people’s self-esteem [42]. Similarly, the relevant literaturestated that self-esteem could rise as a result of PA, at least temporarily [43,44]. Children and adolescents frequently experiencepsychological and behavioural issues, and raising one’s self-esteem may help to stop the emergence of such issues. According to the outcomes of previous studies, exercise temporarilyincreases the self-esteem of adolescents and children. This may be owing to the absence of any known detrimental effects and multiple channels for emotional release, which lead to numerous positive benefits on physical health [37]. The increase in psychological resilience experienced in the intervention group implies a strong impact on their physical and mental well-being. Previous studies revealed that resilience played a major role in mediating the link between mental and physical well-being, and encouraging resilient physical activities would be a great strategy for boosting mental health [29,45].
All of the specific exercises investigated in this study (i.e., grip (kg)) and the overall engagement in physical activity improved significantly in the number of push-ups for 1 min, the number of sit and ups test for 1 min, and the strength of the hand in the intervention group compared to the control group. These results suggest that the mentorship programme elicited behavioural change bymotivating students to engage in the physical activities and exercises chosen before the intervention. Similar findings were reported by [30], in which a 10-week school-based intervention that focused on peer-to-peer mentoring was effective in enhancing self-regulation and engagement in physical activity among high school students. Allowing students to choose the exercises of their choice appears to have a positive effect on adherence to physical activities, which is expected to improve physical and mental health [22]. This was supported in a qualitative study by [22] as increased opportunities to participate in unstructured activities were key recommendations ofmost adolescent participants in the focus group discussion. Similarly, recorded significant improvements in physical activity among adolescents following centre-based childcare interventions [46]. Overall, the significant increase in physical activity after the intervention has vital health implications. In addition to bone health, which requires high-impact weight-bearing sports, aerobic exercises that stimulate the heart and lungs should provide the greatest health advantages [27,47]. The number of push-ups for 1 min, the number of sit ups for 1 min, and strength of hand recorded in the present study are considered high-impact aerobic exercises with a positive effect on the conditions of the lungs and heart.
The intervention in the present study was delivered by experts and driven by a foundation derived from the eight principles of PYD: sports skills, school engagement, healthy living, positive character, self-direction, teamwork, leadership, and community engagement. Previous studies reporting interventions that were developed based on some of these principles have also recorded a remarkable improvement in physical activity. For instance, interventions encompassing structured activities delivered by experts and that were theory-driven were associated with a moderate to high increase in physical activity among children and students [23].
Given the significant improvement in physical activities, particularly in the intervention group, the body fat composition in the group declinedsignificantly one month after the intervention. As observed in this study, students who participated in school-based programmes including physical activities experienced a significant reduction in BMI [42,48]. These studies entailed the use of multicomponent interventions comprising components related to physical activity and diet. Similarly, the mentorship programme used in the current study is best described as a multi-component intervention which entailed physical activities and brief discussions to motivate the students toward positive behavioural change. A systematic review conducted by [39] also concluded that interventions to enhance healthy nutrition and physical activity, including mentorship programmes, had positive impacts on BMI.
The reduction in the body fat composition in the intervention group implies potential benefits for participants. For instance, previous studies have demonstrated the link between the levels of cardiorespiratory fitness and abdominal adiposity, while the former is associated with evolving risk factors for cardiovascular diseases [27,29]. Moreover, obesity and increased body fat composition are established risk factors for cardiovascular disorders. Atherosclerosis develops earlier as childhood obesity rises. To address this public health issue, it is criticaltoemphasisegood lifestyle choices and regular exercise, especially among young people. Regular exercise may directly impact systemic circulation, improve insulin and adrenalin sensitivity, boost non-insulin-dependent glucose absorption, and enhance oxidative enzymes involved in carbohydrate and fat metabolism [45]. These events may explain the positive impacts of the mentorship programmeinvestigated in this study on body fat composition.
Another important aspect explored in this study is the participants’ relationship with family members and schoolmates post-intervention. Those in the intervention group experienced a significant increase in their relationship with family members. This result is not surprising given the indications of improved physical and mental health, as discussed in the aforementioned sections. A few studies have shown that significant improvement in students’ physical and mental well-being can be reflected in their study performance and interaction with co-workers or family relatives [31,49].
The present study depicts that school students’ post-intervention life skills scores increased by employing a module for the intervention of education and collaborative teaching-learning techniques. In the phase after the intervention, higher scores were seen in most life skill domains. Including this modular life skills training in education, the curriculum will foster their personality developmentand equip them to tackle various obstacles in life. In addition, the current study demonstrated that Chinese teenage mental health and PA levels are significantly positively correlated.
## 5. Conclusions
This study revealed the effectiveness of an intervention based on a mentorship programme comprising sport-based development and discussion on mental health and physical fitness. All of the physical activities and specific exercises were significantly enhanced in the intervention group compared to the control group. Indicators of physical and mental health such as self-efficacy, psychological resilience, and body fat composition were also substantially improved in the intervention group. These findings were reflected in the students’ relationships with their family members. A similarstudy should be conducted atother universities to elucidate the interventional programs and modify them to suit the general students.
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|
---
title: Selective 5-HT6 Receptor Ligands (Agonist and Antagonist) Show Different Effects
on Antipsychotic Drug-Induced Metabolic Dysfunctions in Rats
authors:
- Anna Partyka
- Katarzyna Górecka
- Joanna Gdula-Argasińska
- Natalia Wilczyńska-Zawal
- Magdalena Jastrzębska-Więsek
- Anna Wesołowska
journal: Pharmaceuticals
year: 2023
pmcid: PMC9967858
doi: 10.3390/ph16020154
license: CC BY 4.0
---
# Selective 5-HT6 Receptor Ligands (Agonist and Antagonist) Show Different Effects on Antipsychotic Drug-Induced Metabolic Dysfunctions in Rats
## Abstract
It is estimated that in patients taking antipsychotic drugs (APDs), metabolic syndrome occurs 2–3 times more often than in the general population. It manifests itself in abdominal obesity, elevated glucose concentration, and dyslipidemia. Despite the high prevalence of this disorder, only a small percentage of patients receive appropriate and effective treatment, and none of the available methods for preventing or treating APD-induced metabolic side effects is satisfactory. A promising supplement to antipsychotic therapy appears to be ligands of the serotonin 6 (5-HT6) receptor. The present study aimed to examine the chronic effects of the selected APDs (haloperidol, risperidone, olanzapine), administered alone and in combination with a selective 5-HT6 agonist (WAY-181187) or antagonist (SB-742457), on weight gain, food intake, serum lipid profile, glucose level, and a spectrum of hormones derived from adipose (leptin, adiponectin) and gastrointestinal (insulin, ghrelin) tissue in rats. SB-742457 inhibited increased weight gain and alleviated hyperglycemia induced by APDs more strongly than did WAY-181187, but also intensified dyslipidemia. WAY-181187 tended to improve the lipid profile, but increased the glucose level. The greatest benefits were obtained when WAY-181187 or SB-742457 were co-administered with haloperidol. It is difficult to assess whether the modification of the serum levels of insulin, leptin, ghrelin, and adiponectin depended on the treatment applied or other drug-independent factors; therefore, further research is needed.
## 1. Introduction
Since the early 1950s, when the first antipsychotic drug (APD), chlorpromazine, was introduced into treatment, great progress has been made in the field of psychiatric disorder pharmacotherapy. First-generation APDs (FGAs) revolutionized psychiatric care by changing its model from inpatient to outpatient. FGAs effectively reduced delusions and hallucinations (positive symptoms), but did not improve, or even had a detrimental impact, on the negative, cognitive, and affective symptoms of schizophrenia. The introduction of second-generation APDs (SGAs) broadens the range of therapeutic indications, and SGAs are currently widely used, not only for the treatment of schizophrenia or schizoaffective disorders, but also as add-on therapies in antidepressant-resistant major depressive disorder, bipolar affective disorder, or behavioral symptoms associated with dementia. Along with the discovery and introduction of newer APDs, the profile of side effects has changed. With the increasing use of SGAs, concerns about the safety and tolerability of APDs have shifted from the stigmatizing motor disorders (extrapyramidal side effects) characteristic of FGAs to the cardiometabolic disturbances affecting health, quality of life, and lifespan [1,2,3].
Chronic use of APDs, especially SGAs, is often associated with the development of metabolic abnormalities, i.e., significant weight gain, lipid disturbance, and hyperglycemia, which increase the risk of obesity, type 2 diabetes, and cardiovascular disease, and which are associated with functional impairment, reduced quality of life, and early mortality. Among the SGAs, olanzapine and clozapine are classified as compounds with the highest potential to induce weight gain and glucose dysregulation. Quetiapine, risperidone, and sertindole belong to the medium-risk group, and the compounds with the lowest metabolic risk are aripiprazole, lurasidone, and ziprasidone [4,5,6]. Despite the high prevalence of metabolic syndrome in patients treated with APDs, only a small percentage of them receive appropriate and effective treatment. Switching to an APD with lower metabolic risk, the modification of eating and physical activity habits, and the addition of supportive drugs (such as metformin, topiramat, zonisamid, or reboxetine) are the most commonly used methods to prevent and/or mitigate the metabolic side effects of APDs. However, none of these meet the expectations of both patients and physicians [7,8]. Therefore, the search for concomitant drugs is crucial for the development of better treatment options.
The substance 5-hydroxytryptamine (5-HT, serotonin) is an important factor in the regulation of appetite and body weight, and its anorectic action is well documented. Pharmacological manipulation of 5-HT1B, 5-HT2C, and recently 5-HT6 receptors signaling, was shown to suppress feeding and body weight in rodents [9]. The 5-HT6 receptors are located in multiple brain areas, including regions associated with the regulation of food intake and energy expenditure, such as the hypothalamic nuclei (the arcuate nucleus, the ventromedial nucleus, the paraventricular nucleus, and the nucleus of the solitary tract) [10,11]. In animal models, acute and chronic administration of 5-HT6 receptor ligands, both agonists and antagonists, resulted in decreased food intake, robust and sustained weight loss in obese animals, and reduced cardiometabolic risk (for a review, see [12,13]). Genetic evidence also supports the role of the 5-HT6 receptor in energy balance regulation. The short interfering RNA-mediated silencing of 5-HT6 gene expression induces hypophagia and weight loss [14]. Mice with a non-functional 5-HT6 receptor grew normally on a standard diet, but showed resistance to obesity induced by a high-fat diet [15]. All of these data support the idea that ligands of the 5-HT6 receptor (both agonists and antagonists) can be used as adjunct compounds to moderate the adverse metabolic effects of APDs.
The present study was designed to evaluate the combination of APD with an agonist or an antagonist of the 5-HT6 receptor in order to establish whether and which of the 5HT6 ligands would serve better in improving the metabolic safety of treatment with APDs. The study aimed to investigate the effects of chronic administration of selected APDs (haloperidol, risperidone, olanzapine), administered separately and in combination with a selective 5-HT6 agonist (WAY-181187) or antagonist (SB-742457), on weight gain, food intake, and biochemical parameters (serum lipid profile and glucose level) in rats. In addition, a spectrum of hormones derived from adipose (leptin, adiponectin) and gastrointestinal (insulin, ghrelin) tissue was determined under treatment conditions. Haloperidol, risperidone, and olanzapine were selected for the study because they differ in receptor profiles, represent two classes of APDs (FGAs and SGAs), and carry a different risk of metabolic complications. It is also important that APDs selected for the study differ in their affinity for the 5-HT6 receptor; haloperidol has no affinity (Ki < 5000 nM), risperidone has moderate one (Ki = 420 nM), and olanzapine has the highest affinity (Ki = 2.5 nM) [16]. WAY-181187 [17] and SB-742457 [18] were selected as tool compounds due to their high affinity and selectivity for the 5-HT6 receptor.
To our knowledge, the effects of the addition of 5-HT6 receptor ligands to APDs in the context of increased metabolic safety have not yet been investigated.
## 2.1. Influence of WAY-181187 or SB-742457 on the Effects of Haloperidol, Risperidone, and Olanzapine on Cumulative Weight Gain in Rats
The cumulative weight gain over specific days in the treatment groups is shown in Figure 1. Repeated measures of ANOVA revealed a statistically significant interaction between the effects of haloperidol/WAY-181187 (F[13, 598] = 2.3609, $$p \leq 0.0044$$), olanzapine/WAY-181187 (F[13, 598] = 7.6837, $p \leq 0.0001$), haloperidol/SB-742457 (F[13, 598] = 4.0718, $p \leq 0.0001$), risperidone/SB-742457 (F[13, 598] = 2.1049, $$p \leq 0.0124$$), and olanzapine/SB-742457 (F[13, 598] = 2.0193, $$p \leq 0.0174$$) on weight gain. There was no statistically significant interaction between the effects of risperidone/WAY-181187 (F[13, 585] = 0.4827, $$p \leq 0.9345$$).
Bonferroni’s post hoc test showed that neither WAY-181187 nor SB-742457 significantly changed the cumulative weight gain in rats. All APDs tested clearly increased weight gain, but the significant changes were observed for haloperidol, from the 11th day, and risperidone, from the 23rd day, of compound administration. The effect of olanzapine did not reach statistical significance, with the exception of that noted on the 25th day. From the 25th day of the experiment, common administration of WAY-181187 and olanzapine induced a significant decrease in weight gain compared to that in the olanzapine-treated group. An insignificant decrease in weight gain was observed after administration of WAY-181187 with haloperidol, while the 5-HT6 receptor agonist did not change the effect of risperidone. SB-742457 reduced APD-induced weight gain, but statistically significant effects were observed after co-administration with haloperidol (from the 11th day) or olanzapine (from the 25th day).
**Figure 1:** *Effects of haloperidol, risperidone, olanzapine, WAY-181187 (A–C), and SB-742457 (D–F), administered alone and in combinations, on weight gain in rats. The results are presented as mean ± SEM; n = 9–10. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 versus the respective vehicle-treated group; # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001 versus the respective APD-treated group (two-way repeated measures of ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-181187 3 mg/kg; SB, SB-742457 3 mg/kg.*
## 2.2. Influence of WAY-181187 or SB-742457 on the Effects of Haloperidol, Risperidone, and Olanzapine on Average 48-Hour and Cumulative Food Intake in Rats
The average 48-hour food intake is shown in Figure 2. Two-way ANOVA revealed a statistically significant interaction between the effects of haloperidol/SB-742457 (F[1, 321] = 7.2353, $$p \leq 0.0075$$). In all other cases, the effects of the interaction between groups were not statistically significant (haloperidol/WAY-181187: F[1, 321] = 0.6621, $$p \leq 0.4164$$; risperidone/WAY-181187: F[1, 321] = 0.0714, $$p \leq 0.7894$$; olanzapine/WAY-181187: F[1, 321] = 1.0469, $$p \leq 0.3070$$; risperidone/SB-742457: F[1, 321] = 0.9026, $$p \leq 0.3428$$, olanzapine/SB-742457: F[1, 321] = 0.2616, $$p \leq 0.6094$$).
Post hoc analysis showed a statistically significant increase in 48-hour food intake in the haloperidol- and risperidone-treated groups compared to the vehicle-treated group. The addition of SB-742457, but not WAY-181187, to haloperidol significantly decreased this parameter compared to the group treated with haloperidol alone. In other cases, no significant effects of treatment on the measured parameter were observed.
**Figure 2:** *Effects of haloperidol, risperidone, olanzapine, WAY-181187 (A) and SB-742457 (B), given alone and in combinations, on average 48-hour food intake in rats. The average 48-hour intake in each group was calculated from all measurements taken throughout the experiment. The results are presented as mean ± SEM; n = 9–10. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 versus respective vehicle-treated group; #### p < 0.0001 versus the respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-181187 3 mg/kg; SB, SB-742457 3 mg/kg.*
Cumulative food intake over weeks in the treatment groups is shown in Figure 3. Two-way repeated measures of ANOVA did not reveal a statistically significant interaction between effects of the 5-HT6 receptor agonist and APDs (haloperidol/WAY-181187: F[3, 63] = 1.3098, $$p \leq 0.2791$$; risperidone/WAY-181187: F[3, 63] = 0.2837, $$p \leq 0.8370$$; olanzapine/WAY-181187: F[3, 63] = 1.1825, $$p \leq 0.3236$$) nor between the 5-HT6 antagonist and APDs (haloperidol/SB-742457: F[3, 63] = 2.4677, $$p \leq 0.0702$$; risperidone/SB-742457: F[3, 63] = 0.6030, $$p \leq 0.6155$$; olanzapine/SB-742457: F[3, 63] = 0.0160, $$p \leq 0.9972$$).
Neither 5-HT6 ligands changed the cumulative food intake during the observation period. Haloperidol significantly increased cumulative food intake from the third week and risperidone from the fourth week of the experiment. Olanzapine had no influence on cumulative food intake. The addition of WAY-181187 did not change the effects of APDs, while SB-742457 significantly decreased the food intake elevated by haloperidol and had no influence on the action of the other two APDs.
**Figure 3:** *Effects of haloperidol, risperidone, olanzapine, WAY-181187 (A–C) and SB-742457 (D–F), given alone and in combinations, on cumulative food intake in rats. The results are presented as mean ± SEM; n = 9–10. * p < 0.05 versus respective vehicle-treated group; # p < 0.05, ## p < 0.01 versus the respective APD-treated group (two-way repeated measures of ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-181187 3 mg/kg; SB, SB-742457 3 mg/kg.*
## 2.3. Influence of WAY-181187 or SB-742457 on the Effects of Haloperidol, Risperidone, and Olanzapine on the Lipid Profile and Glucose Concentration in the Rat Serum
The effects of WAY-181187 on APD-induced changes in the rat lipid profile are presented in Figure 4. Two-way ANOVA revealed that there was a statistically significant interaction between the effects of haloperidol/WAY-181187 on the concentration of high density lipoproteins (HDL) (F[1, 29] = 7.2513, $$p \leq 0.0117$$); haloperidol/WAY-181187 (F[1, 30] = 4.6700, $$p \leq 0.0388$$) and olanzapine/WAY-181187 (F[1, 30] = 4.8977, $$p \leq 0.0340$$) at the level of low density lipoproteins (LDL). There was no statistically significant interaction between the effects of haloperidol/WAY-181187 (F[1, 29] = 0.8147, $$p \leq 0.3742$$), risperidone/WAY-181187 (F[1, 30] = 0.0480, $$p \leq 0.8281$$), and olanzapine/WAY-181187 (F[1, 30] = 0.6026, $$p \leq 0.4437$$) on total cholesterol concentration; between the effects of haloperidol/WAY-181187 (F[1, 30] = 0.0695, $$p \leq 0.7939$$) on LDL concentration; the effects of risperidone/WAY-181187 (F[1, 29] = 3.8243, $$p \leq 0.0602$$) and olanzapine/WAY-181187 (F[1, 29] = 0.0795, $$p \leq 0.7800$$) on HDL concentration; and between the effects of haloperidol/WAY-181187 (F[1, 20] = 0.6242, $$p \leq 0.4388$$), risperidone/WAY-181187 (F[1, 20] = 0.3621, $$p \leq 0.5541$$) and olanzapine/WAY-181187 (F[1, 20] = 0.75881, $$p \leq 0.3940$$) on triglycerides (TG) concentration.
WAY-181187 alone did not significantly change the lipid profile in rats. Haloperidol and risperidone significantly increased HDL and risperidone levels, and an increase in LDL concentration was observed at the statistical significance limit after administration of risperidone ($$p \leq 0.0662$$) and olanzapine ($$p \leq 0.0729$$). The addition of WAY-181187 to haloperidol resulted in a significant decrease in HDL level and an insignificant decrease in total cholesterol level. Co-administration of risperidone and WAY-181187 caused a significant decrease in HDL concentration and an insignificant decrease in LDL concentration. The addition of WAY-181187 to olanzapine insignificantly lowered the level of LDL compared to that in the olanzapine-treated group. In other cases, no significant effects of the applied treatments on the measured parameters were observed.
**Figure 4:** *Effects of haloperidol, risperidone, olanzapine, and WAY-181187, administered alone and in combinations, on serum levels of total cholesterol, LDL, HDL, and TG in rats. The results are presented as mean ± SEM; n = 6–12. * p < 0.05, ** p < 0.01 versus the respective vehicle-treated group; # p < 0.05, ## p < 0.01 versus the respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-181187 3 mg/kg; LDL, low density lipoproteins; HDL, high density lipoproteins; TG, triglycerides.*
The effects of SB-742457 on APD-induced changes in the rat lipid profile are presented in Figure 5. Two-way ANOVA revealed that there was a statistically significant interaction between the effects of haloperidol/SB-742457 on total cholesterol concentration (F[1,27] = 12.839, $$p \leq 0.0013$$) and TG level (F[1, 19] = 9.0145, $$p \leq 0.0073$$); risperidone/SB-742457 on total cholesterol concentration (F[1, 27] = 18.724, $$p \leq 0.0002$$), HDL concentration (F[1, 27] = 12.890, $$p \leq 0.0013$$) and TG level (F[1, 19] = 5.2448, $$p \leq 0.0336$$), as well as olanzapine/SB-742457 on LDL (F[1, 27] = 8.4552, $$p \leq 0.0072$$) and TG (F[1, 19] = 12.001, $$p \leq 0.0026$$) levels. There was no significant interaction between the effects of olanzapine/SB-742457 (F[1, 27] = 2.9396, $$p \leq 0.0979$$) on total cholesterol concentration; between the effects of haloperidol/SB-742457 (F[1, 28] = 3.8313, $$p \leq 0.0603$$) and risperidone/SB-742457 (F[1, 19] = 5.2448, $$p \leq 0.0336$$) on LDL concentration; or between the effects of haloperidol/SB-742457 (F[1, 28] = 2.8607, $$p \leq 0.1019$$) and olanzapine/SB-742457 (F[1, 28] = 0.2953, $$p \leq 0.5912$$) on HDL concentration.
When administered alone, SB-742457 did not have an effect on the concentration of the lipid profile components, except for on TG, which was significantly elevated. Risperidone significantly increased HDL level. An increase in HDL concentration was also observed at the statistical significance limit after haloperidol administration ($$p \leq 0.0815$$). Administration of risperidone and olanzapine resulted in an elevation of LDL level to the statistical significance limit ($$p \leq 0.0925$$ and $$p \leq 0.0891$$, respectively). The 5-HT6 antagonist added to haloperidol caused a significant increase in total cholesterol, LDL, and TG concentrations compared to the results for the haloperidol- and vehicle-treated groups. The combined administration of SB-742457 and risperidone significantly increased the total cholesterol level and decreased the HDL concentration compared to the risperidone- and vehicle-treated groups, and increased TG concentration compared to the risperidone-treated group. Concomitant administration of SB-742457 and olanzapine resulted in a significant decrease in LDL levels compared to the olanzapine-treated group and caused a significant elevation in the total cholesterol concentration compared to the vehicle-treated group. In other cases, no significant effects of the applied treatment on the measured parameters were observed.
**Figure 5:** *Effects of haloperidol, risperidone, olanzapine, and SB-742457, administered alone and in combinations, on serum levels of total cholesterol, LDL, HDL, and TG in rats. The results are presented as mean ± SEM; n = 6–12. * p < 0.05, ** p < 0.01, **** p < 0.0001 versus respective vehicle-treated group; # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001 versus the respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; SB, SB-742457 3 mg/kg; LDL, low density lipoproteins; HDL, high density lipoproteins; TG, triglycerides.*
The effects of WAY-181187 or SB-742457 on ADP-induced changes in the rat serum glucose levels are presented in Figure 6. A two-way ANOVA revealed that there was a statistically significant interaction between the effects of haloperidol/WAY-181187 (F[1, 20] = 23.753, $$p \leq 0.0001$$), risperidone/WAY-181187 (F[1, 20] = 16.695, $$p \leq 0.0006$$), olanzapine/WAY-181187 (F[1, 19] = 20.071, $$p \leq 0.0003$$), haloperidol/SB-742457 (F[1, 20] = 36.827, $p \leq 0.0001$), risperidone/SB-742457 (F[1, 20] = 5.3723, $$p \leq 0.0312$$), and olanzapine/SB-742457 (F[1, 19] = 32.104, $p \leq 0.0001$).
Both 5-HT6 ligands and all three APDs, administered separately and in combination, significantly increased the glucose concentration compared to the vehicle-treated group. The addition of WAY-181187 to haloperidol or olanzapine did not significantly change the glucose level compared to a group treated with the respective APD, while common administration with risperidone resulted in a significant increase in the glucose concentration compared to the group treated with risperidone. SB-742457 significantly decreased the measured parameter when combined with haloperidol or olanzapine, but not risperidone, compared to the respective APD-treated group.
**Figure 6:** *Effects of haloperidol, risperidone, olanzapine, WAY-181187 (A) and SB-742457 (B), administered alone and in combinations, on the glucose level in rat serum. The results are presented as mean ± SEM; n = 5–6. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 versus respective vehicle-treated group; ## p < 0.01 versus the respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-18187 3 mg/kg; SB, SB-742457 3 mg/kg.*
## 2.4. Influence of WAY-181187 or SB-742457 on the Effects of Haloperidol, Risperidone, and Olanzapine on Insulin, Leptin, Ghrelin, and Adiponectin Levels in the Rat Serum
The effects of WAY-181187 on APD-induced changes in hormone levels in rat serum are presented in Figure 7. Two-way ANOVA revealed that there was a statistically significant interaction between the effects of haloperidol/WAY-181187 (F[1, 28] = 36.822, $p \leq 0.0001$) on insulin concentration; between the effects of haloperidol/WAY-181187 (F[1, 26] = 71.397, $p \leq 0.0001$), olanzapine/WAY-181187 (F[1, 27] = 12.084, $$p \leq 0.0017$$) on leptin level; between the effects of haloperidol/WAY-181187 (F[1, 28] = 9.5359, $$p \leq 0.0045$$) and risperidone/WAY-181187 (F[1, 28] = 23.570, $p \leq 0.0001$) on ghrelin concentration, and between the effects of haloperidol/WAY-181187 (F[1, 27] = 11.447, $$p \leq 0.0022$$), risperidone/WAY-181187 (F[1, 27] = 7.4480, $$p \leq 0.0110$$), and olanzapine/WAY-181187 (F[1, 26] = 42.976, $p \leq 0.0001$) on adiponectin concentration. There was no significant interaction between the effects of risperidone/WAY-181187 (F[1, 28] = 1.2049, $$p \leq 0.2817$$) and olanzapine/WAY-181187 (F[1, 28] = 1.7244, $$p \leq 0.1998$$) on insulin concentration; between the effects of risperidone/WAY-181187 (F[1, 27] = 2.0641, $$p \leq 0.1623$$) on leptin level, and between the effects of olanzapine/WAY-181187 (F[1, 28] = 3.1119, $$p \leq 0.0886$$)) on ghrelin concentration.
A significant increase in leptin concentration and no significant effects on the serum levels of insulin, ghrelin, and adiponectin were observed when WAY-181187 was administered alone. Haloperidol significantly increased the serum levels of insulin and leptin and decreased the concentrations of ghrelin and adiponectin. Risperidone elevated insulin, leptin, and adiponectin levels and decreased the ghrelin concentration. Olanzapine increased insulin and adiponectin concentrations and had no effect on the leptin and ghrelin levels. The addition of WAY-181187 to haloperidol resulted in a significant decrease in insulin and leptin levels and an increase in ghrelin and adiponectin concentrations compared to the group treated with haloperidol. The co-administration of risperidone and WAY-181187 caused a significant increase in leptin and ghrelin concentrations, lowered the level of adiponectin, and had no effect on the insulin concentration compared to the risperidone-treated group. The addition of WAY-181187 to olanzapine significantly lowered the ghrelin and adiponectin levels, increased the serum leptin concentration, and did not significantly modify the insulin level compared to those in the group treated with olanzapine.
**Figure 7:** *Effects of haloperidol, risperidone, olanzapine, and WAY-181187, administered alone and in combinations, on the serum levels of insulin, ghrelin, leptin, and adiponectin in rats. The results are presented as mean ± SEM; n = 6–12. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 versus the respective vehicle-treated group; # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001 versus respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; WAY, WAY-181187 3 mg/kg.*
The effects of SB-742457 on the APD-induced changes in hormone levels in the rat serum are presented in Figure 8. Two-way ANOVA revealed that there was a statistically significant interaction between the effects of haloperidol/SB-742457 (F[1, 25] = 15.849, $$p \leq 0.0005$$), risperidone/SB-742457 (F[1, 25] = 15.699, $$p \leq 0.0006$$), and olanzapine/SB-742457 (F[1, 25] = 55.656, $p \leq 0.0001$) on insulin concentration; between the effects of haloperidol/SB-742457 (F[1, 25] = 6.5380, $$p \leq 0.0170$$) on the level of leptin; between the effects of risperidone/SB-742457 (F[1, 25] = 32.796, $p \leq 0.0001$) and olanzapine/SB-742457 (F[1, 25] = 11.591, $$p \leq 0.0022$$) on ghrelin concentration, and between the effects of risperidone/SB-742457 (F[1, 25] = 33.320, $p \leq 0.0001$) and olanzapine/SB-742457 (F[1, 24] = 63.194, $p \leq 0.0001$) on adiponectin concentration. There was no significant interaction between the effects of risperidone/SB-742457 (F[1, 25] = 0.8312, $$p \leq 0.3706$$) and olanzapine/SB-742457 (F[1, 25] = 0.1240, $$p \leq 0.7277$$) on the level of leptin, between the effects of haloperidol/SB-742457 (F[1, 25] = 0.0277, $$p \leq 0.8692$$) on ghrelin concentration, and between the effects of haloperidol/SB-742457 (F[1, 25] = 3.8122, $$p \leq 0.0622$$) on the level of adiponectin.
When administered alone, SB-742457 significantly increased serum levels of insulin, leptin, and adiponectin, having no effect on ghrelin concentration. Haloperidol significantly increased the serum levels of insulin and leptin and decreased ghrelin (no statistical significance) and adiponectin concentrations. Risperidone elevated insulin, leptin, and adiponectin levels and decreased ghrelin concentration. Olanzapine increased insulin and adiponectin concentrations and had no effect on leptin and ghrelin levels. SB-742457 did not significantly influence the effects of haloperidol on insulin, leptin, and ghrelin concentration and increased the level of adiponectin compared to that in the group treated with haloperidol. The 5-HT6 antagonist significantly modified risperidone-induced changes in measured hormone levels, increasing the concentration of insulin, leptin, and ghrelin, and lowering adiponectin level in the serum of rats, compared to the risperidone-treated group. The addition of SB-742457 to olanzapine resulted in an elevation in serum leptin and ghrelin levels and a decrease in the concentration of adiponectin.
**Figure 8:** *Effects of haloperidol, risperidone, olanzapine, and SB-742457, administered alone and in combinations, on the serum levels of insulin, ghrelin, leptin, and adiponectin in rats. The results are presented as mean ± SEM; n = 6–11. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 versus the respective vehicle-treated group; # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001 versus respective APD-treated group (two-way ANOVA followed by Bonferroni’s post hoc test). Halo, haloperidol 0.5 mg/kg; Risp, risperidone 0.5 mg/kg; Ola, olanzapine 5 mg/kg; SB, SB-742457 3 mg/kg.*
## 3. Discussion
The present study is the first to demonstrate the effects of adding a selective 5-HT6 ligand (agonist or antagonist) to APDs on metabolic disorders caused by repeated administration (for 28 days) of different APDs in rats. The data obtained revealed that the 5-HT6 receptor antagonist, SB-742457, showed a stronger lowering effect than the 5-HT6 receptor agonist, WAY-181187, on increased weight gain and food intake induced by haloperidol administration. The effects of risperidone and olanzapine were modified by the 5-HT6 receptor ligands in a similar and equal way. The opposite influence of the addition of WAY-181187 and SB-742457 to APDs was observed on the lipid profile and glucose levels. The effect of the 5-HT6 antagonist was more pronounced and generally led to the intensification of lipid disorders and the reduction in APD-induced hyperglycemia, while the addition of the 5-HT6 agonist contributed to a slight improvement in the lipid profile and the aggravation of glycemic disorders. In terms of the effect of 5-HT6 receptor ligands on hormones involved in the regulation of weight gain and appetite, only the addition of WAY-181187 to haloperidol attenuated post-APD changes in their serum concentrations. Both WAY-181187 and SB-742457 contributed to the reduction in the increased level of adiponectin after risperidone or olanzapine administration, but increased the effect of these drugs on leptin and, to a lesser extent, insulin and ghrelin concentrations (Table 1).
Animal models of APD-induced metabolic side effects are widely described in the scientific literature. While researchers tend to agree on the usefulness of preclinical studies in understanding the mechanisms involved in the metabolic abnormalities induced by APDs, the metabolic changes observed in animals vary significantly depending on the species and strain of rodents, the APDs used, and their dosage, and may be inconsistent even with the same drug [19]. Accordingly, in our study, the APDs tested induced various metabolic changes to a different extent. Surprisingly, the strongest and most consistent metabolic disturbances were observed after 4 weeks of administration of haloperidol, then risperidone, and finally, olanzapine. Haloperidol caused a significant increase in food intake accompanied by an increase in weight gain, hyperglycemia, and a slight increase in total cholesterol level. A significant elevation in serum insulin and leptin levels and a decrease in ghrelin and adiponectin concentrations were also observed. Similar effects were observed after risperidone administration, except for a weaker impact on food intake and increased serum adiponectin concentration were noted, while olanzapine induced hyperglycemia, increased insulin and adiponectin levels, and showed a statistically insignificant impact on weight gain and lipid profile (Table 1). In all cases, hyperglycemia was accompanied by an increase in insulin concentration, which indirectly suggests the presence of insulin resistance, although confirmation of this phenomenon would require additional tests (for example, an oral glucose tolerance test).
In clinical practice, haloperidol is not classified as an APD that causes severe undesirable metabolic effects; however, patients gain weight during its use [4,6,20,21]. Moreover, in animal studies, haloperidol caused metabolic changes such as weight gain, hyperinsulinemia, hyperglycemia, or hypercholesterolemia; however, its effects are generally weaker than those of SGAs [22,23,24,25,26]. Clinically, risperidone is classified as an APD with a medium metabolic risk [6], inducing moderate weight gain and changes in the lipid profile and glucose level [4]. In animal studies, risperidone increased body weight [23,27,28], serum levels of total cholesterol and TG, induced hyperinsulinemia, and altered glucose metabolism [29,30]. Olanzapine has a high potential to cause weight gain, hyperglycemia, and hypercholesterolemia in humans [4,21] and is most widely used in preclinical studies on the undesirable metabolic action of APDs [19,31]. Contrary to expectations, in our experiment, olanzapine only induced statistically significant hyperglycemia and hyperinsulinemia and insignificantly increased weight gain and concentrations of total cholesterol, LDL, and TG. The lack of statistically significant differences was due to the relatively high interindividual variability in response to the drug and the high SEM associated with it. It is likely that temporary sedation occurred for several hours after olanzapine administration (our own unpublished observations), resulting in more sensitive rats with lower food intake and contributed to a greater variability of the results obtained. However, the discrepancies between the literature and our data do not seem to differ significantly [19].
The underlying mechanism of APD-induced metabolic changes is complex and includes antagonism of histamine H1, serotonin 5-HT2C/2A, dopamine D$\frac{2}{3}$, muscarinic M3, and adrenergic α1 receptors. This is still an unelucidated issue. One of the research areas concerns the role of peptide hormones such as leptin, ghrelin, and adiponectin. Leptin is secreted by adipocytes and participates in the central regulation of appetite, reducing it, and the peripheral regulation of metabolic activity, increasing the effects of insulin and improving the utilization of fatty acids in skeletal muscle [32]. In patients treated with olanzapine, marked weight gain was associated with an increase in serum leptin levels, while those treated with haloperidol did not show substantial weight gain or elevated leptin concentrations. For risperidone, clinical trials observed moderate changes in weight and leptin levels [3,33]. Animal data are less consistent. In female rats, olanzapine induced weight gain, but serum leptin levels did not differ between treatment groups [34], while in the study with clozapine, both body weight and leptin levels were increased [35]. As expected, in our study, a significant increase in serum leptin concentration was observed in the haloperidol or risperidone treated group, in which there was also a greater weight gain. Olanzapine, which caused only a slight increase in body weight compared to the control group, did not change the level of leptin.
Unlike leptin, ghrelin induces hunger by activating orexigenic hypothalamic neurocircuits, resulting in increased food intake and stimulated adipogenesis. Ghrelin is produced mainly in the endocrinal cells of the gastric glands. The level of ghrelin increases before meals, and food suppresses its release [36]. Studies in patients taking APDs are completely inconsistent and show an increase, a decrease, and no change in serum ghrelin levels [33,37]. The tendency to increase the level of ghrelin (effect at the statistical significance limit) was reported in rats fed clozapine, but not haloperidol [22]. Another study showed a significant elevation in serum ghrelin levels after treatment with long-acting injectable haloperidol or risperidone, but not with olanzapine, in rats [38]. On the contrary, in the investigations by Weston-Green et al., olanzapine significantly increased total ghrelin [39]. Our results revealed that haloperidol and risperidone decreased the serum level of ghrelin, while olanzapine did not affect it. Such contradictory reports make it difficult to discuss the results and make it impossible to draw definitive conclusions about the effect of APDs on ghrelin levels and its association with the metabolic changes induced by these drugs.
Adiponectin is an adipose-specific protein. In humans, its level is negatively correlated with body weight and insulin levels [40]. As with ghrelin, data from patients treated with APDs are conflicting; in most studies, no changes in serum adiponectin levels were reported, but there was also evidence for increased and decreased levels [3,33,41]. Similar results were obtained from animal studies that demonstrated no impact of olanzapine [42] or haloperidol [22], an increase in serum adiponectin level after olanzapine [34,43] or clozapine [22,44] treatment, as well as an increase in adiponectin mRNA in the visceral fat of rats treated with risperidone [45]. In the present study, the serum level of adiponectin was lowered only in the haloperidol-treated rats; in animals treated with risperidone or olanzapine, the peptide concentration was increased, while the insulin level was elevated in all APD-treated groups. However, we determined the total adiponectin in serum, and the studies suggest a closer correlation between high molecular weight adiponectin and insulin sensitivity [46].
Scientific data indicate that 5-HT6 antagonism rather than agonism is important for the anti-obesity effect. The 5-HT6 receptor antagonists (PRX-07034, Ro 04-6790, BVT 5182, SB 271046, and idalopirdine) significantly reduced food intake and body weight in obese rodents and promote satiety in normal-weight rats [12,13,47,48]. Similar effects showed that the partial agonists of the 5-HT6 receptor, E-6837, caused hypophagia in non-obese and diet-induced obese rats [49], and EMD 386088 induced weight loss in rats fed a high-fat diet and reduced food intake in models of excessive eating and obesity induced by the high-fat diet [50]. Our results showed that WAY-181187 and SB-742457 administered at a dose of 3 mg/kg (that is, a dose at which both ligands improved memory deficits in rats in our previous studies [51]) did not influence weight gain, food intake, or lipid profile, except for increasing the serum TG level by SB-742457. Unfortunately, both 5-HT6 ligands caused severe hyperglycemia. It seems that in the case of the 5-HT6 receptor antagonist, this effect may be the result of reduced insulin sensitivity because at the same time, a significant increase in the serum level of this hormone was observed. Both 5-HT6 receptor ligands increased serum leptin concentration. Although the lack of effect on body weight and food intake is not contradictory to the majority of literature data showing that such effects are revealed primarily in various models of obesity or after acute administration of compounds to non-obese rats, the increase in TG, glucose, and leptin concentrations contradicts the published data [13]. The 5-HT6 receptor ligands reduced adiposity and visceral fat stores, which was reflected in decreased serum leptin levels. Improvements in glycemic control were reflected in a reduction in serum insulin concentration, without a change in glucose levels. The 5-HT6 receptor ligands generally did not have an effect on TG levels, although two studies showed a decrease in serum TG concentrations [13,49]. The reason for these discrepancies may result from methodological differences. First of all, the published data pertain to obese rats, while our studies were carried out in animals of normal weight.
The results obtained suggest that the addition of a 5-HT6 receptor ligand, both an agonist and an antagonist, to an APD may beneficially modify the metabolic consequences of the chronic use of these drugs. However, this effect is not uniform and depends on both the type of ligand and the neuroleptic. SB-742457 appears to have a greater inhibitory effect on APD-induced weight gain. This finding is supported by the vast majority of reports in the literature indicating that 5-HT6 antagonism, rather than agonism, is responsible for weight loss. However, it should be noted that, when combined with olanzapine, both ligands had a similar effect. This phenomenon is difficult to explain, especially since olanzapine has the highest affinity for the 5-HT6 receptor among the studied APDs and is the antagonist of this receptor. The reduction in weight gain was related to a decrease in food intake, although statistically significant differences were obtained only when SB-742457 was administered in combination with haloperidol. The hypophagic effect of the selective 5-HT6 antagonist, SB-399885, was shown to be associated with increased activation of neurons in two hypothalamic nuclei, the paraventricular nucleus and the nucleus of the solitary tract, which promotes anorectic behavior [52]. The hypophagic effect of 5-HT6 ligands is explained by the blocking or attenuating of the action of 5-HT on γ-aminobutyric acid (GABA) interneurons in the hypothalamus, which results in reduced GABA release and a subsequent increase in the release of anorexic α-melanocyte-stimulating hormone (α-MSH) [53] and/or the inhibition of hunger-promoting agouti-related peptide (AgRP)/GABA neurons in the arcuate nucleus of the hypothalamus [52]. The favorable action of SB-742457 on weight gain and food intake was accompanied by a significant aggravation of lipid parameters, such as increased total cholesterol, LDL, and TG, relative to the respective APD-treated group. WAY-181187 did not significantly change these parameters, but showed a tendency to improve the lipid profile. Interestingly, the effect of 5-HT6 ligands on APD-induced hyperglycemia was the complete opposite; WAY-181187 exacerbated glycemic disturbances, while SB-742457 decreased glucose concentrations, however, not at the level of the vehicle-treated group. The least consistent are the data on the effect of the 5-HT6 ligands on APD-induced changes in serum hormone levels. WAY-181187 and SB-742457 acted unidirectionally or inversely, and no regularities were found in these effects in the context of hormone or APD. For this reason, it is difficult to find connections between the effect of treatment on body weight and metabolic parameters and levels of insulin, leptin, ghrelin, or adiponectin. The lack of data from the scientific reports on the effect of the combined administration of APDs with 5-HT6 receptor ligands does not allow any conclusions to be drawn. The results obtained from the haloperidol and WAY-181187 interaction experiment seem to be the most consistent. Haloperidol given alone increased weight gain, total cholesterol, and glucose levels, which were accompanied by elevated insulin concentration, decreased adiponectin, and increased leptin levels. When WAY-181187 was administered along with haloperidol, the tendency to decrease weight gain and total cholesterol was observed, and the insulin concentration was reduced, without changes in the glucose level. As expected, these changes were accompanied by an increase in adiponectin and a decrease in leptin serum concentrations.
The present study has some limitations. First, this research is part of a larger project aimed at assessing the potential benefits that can result from the combined use of APDs and selective 5-HT6 receptor ligands on metabolic side effects, cognitive impairments, and depressive- and/or anxiety-like symptoms, and the same doses were used to evaluate all these aspects. This could have been the reason for not obtaining the full spectrum of metabolic disorders induced by olanzapine. Second, for the same reason (the need to perform other animal studies and collect tissues immediately after their completion), the rats were not fasted prior to blood sampling. Therefore, the results of glucose, TG, and some hormones can be difficult to interpret. However, it should be emphasized that all experimental groups were maintained under the same conditions, and the results of the drug-treated groups were compared with those of the appropriate vehicle-treated group. Third, the research presented is preliminary and aims only to estimate whether the common administration of a selective 5-HT6 receptor agonist/antagonist with the selected APD will help mitigate its adverse metabolic effects. It would also be interesting to investigate how this pharmacological manipulation affects the daily activity and metabolic rate of animals. Finally, it is not known whether the results obtained are general and can be extrapolated to other APDs and/or other 5-HT6 ligands. In further research, it will be necessary to take into account all of the above issues.
## 4.1. Animals
The experiment was carried out in female Wistar rats purchased from the Animal House at the Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland. At the time of arrival, the animals weighed 160–180 g.
During the experiment, the rats were kept in an environmentally controlled laboratory room under the following conditions: temperature 22 ± 2 °C, humidity 55 ± $10\%$, 12 h light/dark cycles (light on at 7:00 a.m. and off at 7:00 p.m.). The rats were housed in pairs in standard plastic cages (L × W × H) 378 × 217 × 180 mm. Wood blocks, paper tubes, and strips were used to enrich the environment. The rats had free access to food (standard laboratory pellets) and tap water.
A total of 140 rats were used in the study, and each treatment group consisted of 10 randomly selected animals. Due to the large number of animals and limited laboratory space, the experiment was carried out in three turns: the first included 4 treatment groups: vehicle ($1\%$ Tween 80), haloperidol, risperidone, and olanzapine; the second consisted of 5 treatment groups: vehicle ($1\%$ Tween 80), WAY-181187, haloperidol + WAY-181187, risperidone + WAY-181187, and olanzapine + WAY-181187; and the third consisted of 5 treatment groups: vehicle ($1\%$ Tween 80), SB-742457, haloperidol + SB-742457, risperidone + SB-742457, and olanzapine + SB-742457. One animal died during the administration of the compounds; therefore, one experimental group (i.e., risperidone + WAY-181187-treated group) eventually consisted of only 9 animals. 24 hours after the last drug administration, trained personnel sacrificed the rats by dislocating the cervical spinal cord.
The research was carried out according to EU Directive $\frac{2010}{63}$/EU and Polish legal regulations (DzU 2015 item 266, as amended). All animal procedures were approved by the II Local Ethics Commission at the Institute of Pharmacology PAS in Kraków (approval No. $\frac{107}{2016}$). The 3R rule was implemented in the study. A procedure for early, humane termination of the experiment was developed in the event of significant deterioration of the animal’s health. The procedure was intended to be initiated when at least two of the following symptoms occurred: convulsions, respiratory disturbance, movement disorder, immobility, lack of water and/or food intake, muscle relaxation, or lack of touch response.
## 4.2. Drugs and Treatment
Haloperidol (TargetMol, Boston, MA, USA), risperidone (TargetMol), olanzapine (TargetMol), WAY-181187 (oxalate; Tocris Bioscience, Bristol, UK), and SB-742457 (TargetMol) were used in the experiment. Doses of APDs (haloperidol 0.5 mg/kg, risperidone 0.5 mg/kg, and olanzapine 5 mg/kg) and 5-HT6 ligands (WAY-181187 3 mg/kg and SB-742457 3 mg/kg) were selected for the experiments, based on literature review and our previous studies which presented their separate and combined behavioral effects [54]. The compounds were suspended in a $1\%$ solution of Tween 80 (Sigma Aldrich, St. Louis, MO, USA) immediately before administration and injected intraperitoneally (ip) in a volume of 2 mL/kg. The compounds were dispensed to the rats once daily between 10:00 and 11:00 a.m. for 28 days. The last injection was given 24 h before sacrifice. The control rats received $1\%$ Tween 80, on the same dosing regimen.
## 4.3. Measurement of Body Weight and Food Intake
The body weight of each rat and the food intake per cage were measured alternately, every other day, to the nearest 0.1 g using an electronic scale. Measurements were performed before drug administration.
## 4.4. Sample Collection
The animals were sacrificed by decapitation, and the blood from the trunk was collected in plastic tubes. The tubes were stored for 20 min at room temperature to allow the serum to clot. The samples were centrifuged at 300× g at 20 °C for 20 min. The serum was collected and stored at −80 °C for further biochemical analysis.
## 4.5. Biochemical Analysis
The serum concentrations of the biochemical parameters were measured spectrophotometrically using commercially available rat enzyme-linked immunosorbent assay (ELISA) kits (Bioassay Technology Laboratory, Shanghai, China, for total cholesterol, LDL, HDL, TG, and ghrelin; Mediagnost, Reutlingen, Germany, for adiponectin and leptin; Crystal Chem, Elk Grove Village, IL, USA, for insulin and glucose), according to the manufacturers’ instructions. Absorbance was measured using the Omega Star microplate reader (BMG LABTECH, Ortenberg, Germany).
## 4.6. Statistical Analysis
Statistical analysis was performed using the Statistica 13 program. Data were presented as mean ± standard error of mean (SEM). The two-way repeated measures of analysis of variance (ANOVA), with drug 1 (5-HT6 ligand) and drug 2 (APD) as between-subject factors and time as the repeated measures factor, was used to evaluate the effects of body weight gain and food intake. The results of biochemical analysis were examined by two-way ANOVA, with the between-subject factors drug 1 (5-HT6 ligand) and drug 2 (APD). The post hoc Bonferroni’s comparison test was used to compare between groups. Differences between groups were considered significant when the p-value was <0.05.
## 5. Conclusions
In conclusion, the results obtained provide us with an unambiguous answer regarding whether the addition of a selective 5-HT6 agonist or antagonist will bring more benefits concerning post-APD metabolic disorders. The greatest benefits were obtained when the 5-HT6 ligand was co-administered with haloperidol, which, unlike risperidone (Ki = 420 nM) and olanzapine (Ki = 2.5 nM), has no affinity for the 5-HT6 receptor (Ki > 5000 nM) [16]. WAY-181187 normalized haloperidol-induced changes in the serum levels of peptides regulating appetite and metabolism activity and, to a lesser extent, decreased weight gain and food intake, while SB-742457 strongly reduced weight gain and food intake and was less likely to modify hormonal changes. Generally, SB-742457 more strongly inhibited increased weight gain and alleviated the hyperglycemia caused by APDs, but it should be noted that it also intensified dyslipidemia. On the other hand, WAY-181187 tended to improve the lipid profile, but increased the glucose level. It is also difficult to assess whether the modification of the serum levels of insulin, leptin, ghrelin, and adiponectin depended on the treatment applied or other drug-independent factors (for example: weight gain, daily locomotor activity, adipose tissue content); therefore, further research is needed.
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|
---
title: Impact of Arterial Calcification of the Lower Limbs on Long-Term Clinical Outcomes
in Patients on Hemodialysis
authors:
- Takayasu Ohtake
- Ayaka Mitomo
- Mizuki Yamano
- Toshihiro Shimizu
- Yasuhiro Mochida
- Kunihiro Ishioka
- Machiko Oka
- Kyoko Maesato
- Hidekazu Moriya
- Sumi Hidaka
- Milanga Mwanatambwe
- Shuzo Kobayashi
journal: Journal of Clinical Medicine
year: 2023
pmcid: PMC9967859
doi: 10.3390/jcm12041299
license: CC BY 4.0
---
# Impact of Arterial Calcification of the Lower Limbs on Long-Term Clinical Outcomes in Patients on Hemodialysis
## Abstract
Lower limbs’ arterial calcification is significantly associated with the clinical severity of lower extremity artery disease (LEAD) in patients undergoing hemodialysis (HD). However, the association between arterial calcification of the lower limbs and long-term clinical outcomes in patients on HD has not been elucidated. Calcification scores of the superficial femoral artery (SFACS) and below-knee arteries (BKACS) were quantitatively evaluated in 97 HD patients who were followed for 10 years. Clinical outcomes, including all-cause and cardiovascular mortality, cardiovascular events, and limb amputation were evaluated. Risk factors for clinical outcomes were evaluated using univariate and multivariate Cox proportional hazard analyses. Furthermore, SFACS and BKACS were divided into three groups (low, middle, and high), and their associations with clinical outcomes were evaluated using Kaplan–Meier analysis. SFACS, BKACS, C-reactive protein, serum albumin, age, diabetes, presence of ischemic heart disease, and critical limb-threatening ischemia were significantly associated with 3-year and 10-year clinical outcomes in the univariate analysis. Multivariate analysis showed that SFACS was an independent factor associated with 10-year cardiovascular events and limb amputations. Kaplan–Meier life table analysis showed that higher SFACS and BKACS levels were significantly associated with cardiovascular events and mortality. In conclusion, long-term clinical outcomes and the risk factors in patients undergoing HD were evaluated. Arterial calcification of the lower limbs was strongly associated with 10-year cardiovascular events and mortality in patients undergoing HD.
## 1. Introduction
Accelerated atherosclerosis is one of the most important complications and plays a central role in the pathogenesis of cardiovascular disease in patients undergoing hemodialysis (HD). Lindner et al. described accelerated atherosclerosis in HD patients approximately 50 years ago [1]. Since then, much evidence concerning atherosclerotic cardiovascular complications in HD patients has been provided. Among atherosclerotic comorbidities, lower extremity artery disease (LEAD) significantly impacts mortality in HD patients [2]. In a previous study, the 1-year survival rate fell to almost $50\%$ after a major amputation in the lower limb due to LEAD [3], which was comparable to the 1-year survival rate after acute myocardial infarction (AMI) in HD patients [4].
Atherosclerosis in patients with chronic kidney disease (CKD) progresses with composite risk factors including traditional cardiovascular risk factors such as hypertension, dyslipidemia, aging, diabetes mellitus, and characteristic risk factors in CKD including oxidative stress, insulin resistance, uremic toxins, calcium–phosphate metabolism abnormality, and microinflammation [5]. An active atherosclerotic process begins in the early stages of CKD, and atherosclerotic organ damages deteriorate along with the decreasing renal function. Decreased glomerular filtration ratio (GFR) is an independent risk factor for lacunar infarction [6]. By the time of initiation of renal replacement therapy, approximately $50\%$ of patients with CKD have coronary artery stenosis, regardless of the presence or absence of symptoms and/or signs [7]. One characteristic pathophysiologic feature of atherosclerosis in CKD patients is combined injuries of intima and media in vessels, i.e., endothelial dysfunction and medial calcification. This constructs “vascular failure”, leading to several organ damages in the advanced stages of CKD. Another characteristic feature of atherosclerosis in CKD patients is “polyvascular disease”. Polyvascular disease is defined as a coexistent symptomatic arterial disease in two or three territories (coronary, cerebral, and/or peripheral arteries). As shown in our previous studies [8], many patients undergoing HD have polyvascular disease.
Historically known as Mönkeberg calcification [9], vascular calcification is a characteristic feature of atherosclerosis in HD patients. Arterial calcification in the peripheral arteries is widely distributed in all portions of the body in HD patients, and aortic and cardiac valve calcifications are also observed in long-standing HD patients. Vascular calcification progresses along with the duration of HD, and microinflammation and an abnormal calcium phosphate metabolism are significant predictors of the progression of vascular calcification in patients undergoing HD [10].
Vascular calcification significantly affects future cardiovascular events and mortality in HD patients. Coronary artery calcification has been extensively studied and is significantly associated with future cardiovascular events and/or mortality in HD patients [10,11,12,13,14,15,16]. Aortic calcification was also reported to be significantly associated with future cardiovascular events and/or mortality [17,18,19,20,21,22]. Therefore, vascular calcification has a deleterious effect on the prognosis of patients on HD.
Although coronary artery and aortic calcifications have been extensively evaluated in HD patients, arterial calcification of the lower limbs, an important characteristic of LEAD in HD patients, has not been evaluated. Previously, we quantitatively evaluated lower limbs’ arterial calcification using multi-detector computed tomography (MDCT) and reported that arterial calcification of the lower limbs was closely associated with the prevalence and severity of LEAD in HD patients [8]. However, the association between arterial calcification of the lower limbs and clinical outcomes in patients on HD has not been elucidated. Therefore, we evaluated the association between arterial calcification of the lower limbs and long-term clinical outcomes, including all-cause and cardiovascular mortality, cardiovascular events, and limb amputation in HD patients. We are the first to provide evidence that arterial calcification of the lower limbs significantly impacts long-term clinical outcomes in HD patients.
## 2.1. Patients Enrollment and Purpose of This Study
Ninety-seven HD patients who underwent non-enhanced 64-row MDCT to evaluate the calcification score (CS) of the lower limb arteries were registered in 2008, as described in our previous study [8]. Patients were followed up for 10 years, and outcomes, including all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation, were evaluated.
This study aimed to elucidate [1] the long-term clinical outcomes for up to 10 years, [2] the risk factors for long-term clinical outcomes, and [3] the impact of arterial calcification of the lower limbs on clinical outcomes in HD patients.
This study was conducted in accordance with the Declaration of Helsinki. Data were collected from electronic records, and this study was conducted after approval from the Institutional Review Board (IRB) (approval number: TGE01879-024); written informed consent was obtained from the patients included in the previous study [8]. In this follow-up study, the IRB permitted an opt-out approach. The patients could opt out after the research project was made available on our hospital website.
## 2.2. Lower Limbs’ Arterial Calcification
Patients underwent non-contrast-enhanced MDCT scanning of the arteries of the lower limbs using a 64-row MDCT scanner (SOMATOM sensation cardiac 64, SIEMENS, Germany), as previously mentioned [8]. The scoring of calcification for bilateral superficial femoral arteries (SFA) and below-knee arteries (BKA), including the anterior tibial, posterior tibial, and peroneal arteries, was performed using standardized calcium scoring software (Aquarius Net Station, TERARECON) by investigators who were blinded to the results of the patients’ clinical assessment and Fontaine’s severity classification. The CS of SFA (SFACS) and BKA (BKACS) was determined and expressed as the Agatston score, according to the method described by Agatston et al. [ 23].
## 2.3. Measurement of Ankle–Brachial Pressure Index and Toe–Brachial Pressure Index
To evaluate functional blood flow in the lower extremities, we conducted physiological measurements, including ankle–brachial pressure index (ABI) and toe–brachial pressure index (TBI). ABI and TBI were measured, as previously reported, using the ABI form (Colin, Co., Ltd., Komaki, Japan) [8]. Normal ABI and TBI were reported to be 0.9–1.3 and 0.6<, respectively, in the general population [24]. However, in our previous study, we confirmed that the best ABI cut-off value for detecting LEAD in HD patients was 1.06 [8]. Sensitivity and specificity of ABI values < 1.06 for detecting LEAD in dialysis patients were $80.0\%$ and $98\%$, respectively [8]. Therefore, an ABI cut-off value of 1.06 was used in this study. The cut-off value for TBI was <0.6, as used in our previous study.
## 2.4. Patient Assessment and Group Assignment
Information about symptoms of LEAD, including chills, numbness, ischemic claudication, and resting pain, was collected through patient interviews. The previous history of intervention (percutaneous peripheral intervention or bypass surgery) or amputation for LEAD was also recorded. All patients underwent physiological examination for skin color; warmth; pulse examination of the femoral, popliteal, dorsal, and posterior tibial arteries; and skin lesions, including ulcers and gangrene. Symptomatic information, previous history of intervention or amputation, and physiological examinations, including ABI and TBI, were used to assign limb ischemia according to the LEAD severity classification criteria set by Fontaine et al. [ 25]. Patients with ischemic symptoms with at least one abnormality among ABI < 1.06 and TBI < 0.6 or who had an apparent previous history of intervention or amputation of lower limbs were defined as having LEAD. In cases with clinical symptoms, including chillness or numbness without ABI < 1.06 or TBI < 0.6, skin perfusion pressure (SPP) was measured using laser Doppler (PAD 3000: Kaneka, Tokyo, Japan). The PAD 3000 automatically measures the SPP using the laser Doppler transmitter and detector, which were set with a pressure cuff. Two points were measured in each patient: (a) a point between the first and second metatarsal bones in the instep and (b) a front middle point in the sole. After inflating the cuff pressure to stop skin perfusion, the cuff pressure was deflated, and the point when skin perfusion restarted was measured. SPP was expressed as the pressure required to restart skin perfusion. If the SPP value was less than 50 mmHg, the patient was considered Fontaine category I. Three doctors confirmed the Fontaine category classification using the data files on ABI, TBI, and SPP findings and their clinical symptoms.
## 2.5. Clinical and Laboratory Parameters
Clinical information was collected from medical records regarding age, sex, dialysis duration, cause of renal failure, dyslipidemia, hypertension, diabetes mellitus (DM), and comorbid diseases, including ischemic heart disease (IHD) and stroke. Laboratory parameters, including serum albumin, calcium, inorganic phosphate, C-reactive protein (CRP), total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and plasma fibrinogen, were measured using blood samples at the start of the first HD of the week within 2 weeks of MDCT examination. Serum calcium levels were recorded after correcting for albumin. Medications, including antiplatelet drugs, angiotensin receptor blockers, angiotensin-converting enzyme inhibitors, statins, phosphate binders, and vitamin D, were also registered.
## 2.6. Treatment Strategy for LEAD
LEAD was treated according to the Trans-Atlantic Inter-Society Consensus Document on Management of Peripheral Arterial Disease guidelines [26]. Patients with LEAD were treated with either medications, including antiplatelet drugs, or prostaglandin I2 analogues or both. In patients with intermittent claudication, resting pain, and/or ulceration or gangrene (Fontaine II–IV), the culprit arterial stenotic/obstructive lesions were evaluated using a combination of ultrasonography, contrast-enhanced MDCT, non-contrast-enhanced magnetic resonance imaging, or angiography. Re-vascularization treatment (endovascular therapy or bypass surgery) was performed for Fontaine category II patients if the patient had severe claudication, and the re-vascularization procedure was considered mandatory.
In patients with critical limb-threatening ischemia (CLTI), re-vascularization was essentially performed to improve the blood flow in the ischemic limb. If blood flow improved to ≥40 mmHg at the SPP level, surgical debridement therapy and/or vacuum-assisted closure (VAC) were performed. Antibiotic therapy was also administered if the patients had a local infection that was confirmed by a bacterial culture test.
Limb amputation was considered in cases of intractable pain or severe infection with rapid worsening and progression to a septic state. Amputation was also considered when the patient had no optional intractable wound, and rehabilitation after limb amputation was considered mandatory for early back to social life.
## 2.7. Patient Outcomes
Clinical outcomes, including all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation, were obtained from electronic records: these outcomes were evaluated 3 and 10 years after registration. Limb amputation was registered as major or minor amputation. Major and minor amputation were defined depending on the amputation site, above or below the ankle joint, respectively. Major amputation was further divided into above-knee (AK) and below-knee (BK) amputation. All deaths during the observation period were recorded with the cause of death.
All-cause mortalities included cardiovascular deaths, deaths due to infectious diseases, and deaths due to other causes such as malignancy. Cardiovascular deaths included IHD, heart failure, sudden death, stroke, and fatal arrhythmia. Cardiovascular events included new-onset heart failure, AMI, sudden death, stroke, and arrhythmia. New-onset arrhythmia as a cardiovascular event included atrial fibrillation, ventricular tachycardia, sick sinus syndrome, grade 2 or 3 atrioventricular block, and supraventricular or ventricular extra-systole.
The association between the severity of arterial calcification in the lower limbs and clinical outcomes was evaluated using stratified SFACS and BKACS. The SFACS and BKACS were divided into three categories: i.e., low, middle, and high. SFACS was divided into low, <300 ($$n = 31$$); middle, ≥300 to <3000 ($$n = 34$$); and high, ≥3000 ($$n = 32$$). BKACS was divided into low, <100 ($$n = 25$$); middle, ≥100 to <1000 ($$n = 35$$); and high, ≥1000 ($$n = 37$$).
## 2.8. Statistical Analysis
All data were presented as mean ± standard deviation (SD). Data on each patient’s dominant side of the leg for LEAD were selected and used for ABI, TBI, SFACS, and BKACS analyses. Patients were divided into LEAD [-] patients or LEAD (+) patients, and LEAD (+) patients were further divided according to the Fontaine classification. Group mean values were compared using a two-tailed unpaired Student’s t-test or Mann–Whitney U-test. Skewed variables or variables with a wide SD, including CRP, SFACS, and BKACS, were log-transformed before statistical analysis. Categorical variables were compared using the chi-square and Fisher’s tests. Univariate Cox proportional hazard analysis was performed to identify the significant risk factors for clinical outcomes. Multivariate Cox proportional hazard analysis was performed to identify independent risk factors for the clinical outcomes. Since we had confirmed a strong positive correlation between SFACS and BKACS ($r = 0.797$, $p \leq 0.0001$) in our previous study [8], multivariate analysis was performed in 2 patterns. Model 1 included SFACS and significant variables in univariate analysis, and model 2 included BKACS and significant analysis in univariate analysis, respectively. The influence of the severity of arterial calcification of the lower limbs on patient outcomes, including all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation, was assessed using the Kaplan–Meier life table analysis and log-rank test. SPSS version 11.0 software (SPSS Inc., Chicago, IL, USA) was used for data analysis on a personal computer, and $p \leq 0.05$ was considered significant.
## 3.1. Patient Characteristics and Fontaine Group Assignment
Approximately, half of the enrolled patients ($\frac{50}{97}$ patients, $51.5\%$) had LEAD, and there were 31, 8, and 11 patients in Fontaine categories I, II, and IV, respectively (Table 1) Atherosclerotic comorbidities, including IHD and stroke, were significantly higher in patients with LEAD, irrespective of the Fontaine category. SFACS and BKACS were significantly higher in patients with LEAD than in those without LEAD, even in the early stage of LEAD (Table 1) SFACS and BKACS significantly increased along with the progression of the clinical severity of LEAD (Fontaine category I vs. Fontaine category IV, $p \leq 0.01$). TBI in LEAD patients was significantly lower than in non-LEAD patients and significantly decreased with the progression of limb ischemia. Similarly, ABI values in patients with LEAD were significantly lower than those in patients without LEAD. However, ABI did not show a concomitant decrease with the progression of limb ischemia. Antiplatelet drugs were administered to all patients with CLTI, whereas $51.6\%$ of Fontaine I patients received antiplatelet therapy.
## 3.2. Treatment of LEAD
Endovascular treatment (EVT) was performed in all Fontaine IV patients with CLTI ($$n = 11$$). The frequency of EVT for AK and BK arteries was almost the same. Distal bypass surgery (distal anastomosis in BK arteries) was performed in three CLTI patients with BK arterial occlusion in whom EVT for BK arteries was unsuccessful.
## 3.3. Patient Outcome
Worsening of limb ischemia from non-CLTI to CLTI during a 3-year follow-up period was seen in one ($2.1\%$) patient without LEAD and three ($9.7\%$) Fontaine category Ⅰ patients. Symptoms of intermittent claudication were not observed in these patients before worsening to CLTI.
Twenty-seven ($27.8\%$) and fifty-eight ($60.0\%$) patients died at the end of the 3-year and 10-year observations, respectively [Table 2]. By the end of the 3-year follow-up period, 9 ($19.1\%$) out of 47 patients without LEAD, 8 ($25.8\%$) out of 31 Fontaine category I patients, 2 ($25.0\%$) out of 8 Fontaine category II patients, and 8 ($72.7\%$) out of 11 Fontaine category IV patients died. The mortality rate was significantly higher in LEAD patients, irrespective of the Fontaine category, than in non-LEAD patients during the 3-year follow-up period. A remarkably high mortality rate was observed in Fontaine category IV patients ($72.7\%$) [Table 2].
Among 27 patients who died within 3 years, 14 ($51.9\%$), 4 ($14.8\%$), and 9 ($33.3\%$) patients died of cardiovascular causes, infectious diseases, and other causes, respectively. In 10-year all-cause deaths, the mortality rates between non-LEAD patients and patients with non-CLTI LEAD (Fontaine category I) were not statistically different. However, the mortality rate in Fontaine category IV patients was significantly higher than those in patients without LEAD and patients with early-stage LEAD. Cardiovascular deaths were the most dominant cause of death in Fontaine category IV patients in the 3-year and 10-year observation periods [Table 2].
Regarding cardiovascular events, CLTI was significantly associated with high cardiovascular events at the end of the 3-year and 10-year observations. Heart failure and arrhythmia were significantly more common in patients with LEAD than in those without LEAD during the 3-year observation period. As for limb amputation, nine limb amputations occurred during the 3-year follow-up period. The amputation rate was significantly higher in patients with LEAD than in non-LEAD patients; similarly, the amputation rate was significantly higher in Fontaine category II and IV patients than in category I patients. Four amputations were performed on Fontaine category I patients at the end of the 3-year observation period. Three patients showed sudden progression to CLTI during the 3-year follow-up period. One patient experienced an AK amputation in one leg and a minor amputation in the contralateral leg.
## 3.4. Risk Factors for 3-Year and 10-Year Clinical Outcomes
Table 3 and Table 4 show the significant risk factors for patient outcomes at 3 and 10 years, respectively. Among several variables, CRP, serum albumin, age, and a previous history of IHD, SFACS, BKACS, and CLTI were significantly associated with patient outcomes in a univariate Cox proportional hazard analysis. The univariate Cox proportional hazard analysis showed that CRP and CLTI were significant risk factors for all clinical outcomes, including all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation. SFACS was a significant risk factor for cardiovascular events during the 3-year observation period and all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation during the 10-year observation period. BKACS was a significant risk factor for all clinical outcomes at the 3-year and 10-year observations in the univariate analysis. Multivariate Cox proportional hazard analysis revealed independent risk factors for clinical outcomes at the end of the 3-year and 10-year observations. For the 10-year observation, SFACS was an independent risk factor for cardiovascular events and limb amputation, independent of CLTI.
## 3.5. Impact of SFACS and BKACS on 10-Year Clinical Outcomes
Stratified SFACS and BKACS significantly impacted cardiovascular mortality and cardiovascular events, respectively (Figure 1). The higher SFACS and BKACS groups showed significantly higher rates of cardiovascular mortality and events, respectively ((B), (C), (F), (G), $p \leq 0.01$). Stratified SFACS and BKACS showed borderline associations with all-cause mortality (although these were not statistically significant). Regarding limb amputation, the high SFACS and BKACS groups showed worse survival curves than the low SFACS and BKACS groups. However, because amputation was not performed in some groups (the low SFACS group and the low and middle BKACS groups) during the observation period, statistically significant differences were not observed in the life table analysis.
## 4. Discussion
Our study provided the first evidence that quantitatively evaluated arterial calcification of the lower limbs was significantly associated with 10-year cardiovascular events and mortality in patients undergoing HD. The risk factors for middle, and long-term clinical outcomes including all-cause mortality, cardiovascular mortality, cardiovascular events, and limb amputation were CRP, serum albumin, age, DM, presence of IHD, CLTI, and vascular calcification score, including SFACS and BKACS, obtained by a univariate Cox proportional hazard analysis. A multivariate Cox proportional hazard analysis showed that the CRP level was a strong and independent predictor of all-cause mortality, cardiovascular mortality, and cardiovascular events in a 10-year follow-up study. Vascular calcification, especially SFACS, was an independent predictor of cardiovascular events and limb amputation in the 10-year follow-up in multivariate analysis.
Only a few reports have quantitatively evaluated arterial calcification of the lower limbs and its association with clinical outcomes in CKD patients. Mizuiri et al. quantitatively evaluated the calcification score of common iliac artery (CIA) and coronary artery using MDCT in 145 non-dialysis CKD patients [27]. They evaluated the association between the vascular calcification of two different sites with the progression to renal replacement therapy. Coronary artery calcification significantly predicted the progression to renal replacement therapy. However, CIA calcification did not predict the renal prognosis. Although they quantitatively evaluated CIA calcification, they did not evaluate the association between CIA calcification and clinical outcomes, including all-cause and cardiovascular mortality, cardiovascular events, and limb amputation, as evaluated in our study. Several atherosclerotic risk factors are known to be associated with different distribution pattern in peripheral artery disease. Smoking is associated with more proximal atherosclerotic distribution (more elastic elements such as the iliac artery), whereas kidney dysfunction shows a more centrifugal lesion pattern (more muscular elements such as SFA and BKA) [28]. Distal muscular arteries may be more strongly affected in uremia by vascular calcification via the osteogenic differentiation of vascular smooth muscle cells (VSMCs). Therefore, vascular calcification in more distal arterial portion of lower limbs may better predict the clinical outcomes in patients undergoing HD as shown in our study.
HD patients with LEAD have a very high rate of atherosclerotic comorbidity, including IHD and stroke. Furthermore, more than half of these deaths were of cardiovascular origin. Therefore, adequate treatment of the target organ damage due to atherosclerosis (not only LEAD but also the cardiovascular and cerebrovascular systems) may be very important.
Drug administration was insufficient in HD patients with early-stage LEAD. This may be due to the nature of LEAD, that is, asymptomatic or very mild symptoms in its early stage, and inappropriate judgment of screening tests such as ABI (influenced by vascular calcification). As we previously provided, the cut-off value of ABI to detect LEAD may be set at 1.06 for HD patients. Vascular calcification may lead to a misunderstanding of ABI values, and many HD patients may be misdiagnosed as not having LEAD by applying normal ABI values (0.9–1.3) in the general population. Since advanced stages of LEAD result in deleterious outcomes in patients undergoing HD, early diagnosis is extremely important. Furthermore, some patients showed sudden worsening from non-CLTI to CLTI without showing gradual worsening. Therefore, although clarifying whether early drug intervention in the early stage of LEAD could prevent the progression of LEAD would be relevant, early diagnosis of LEAD may be the most important thing in HD patients.
The progression of vascular calcification via an inflammatory mechanism with a background of severe calcium–phosphate abnormalities plays an important role in accelerated atherosclerosis in patients undergoing HD. Vascular calcification and inflammation are thought to be associated. Increased uptake of phosphate by VSMCs via the Pit-1 co-transporter under elevated phosphate induces Runx2 upregulation and promotes the osteogenic differentiation and calcification of VSMCs. The inflammatory cytokine, tumor necrosis factor-alfa, elevates intracellular cyclic adenosine monophosphate, upregulates Pit-1 messenger RNA, and promotes the osteogenic differentiation of VSMCs [29]. In accordance with the primary role of microinflammation at the cellular level, microinflammation, represented by CRP, is a clinically important factor associated with vascular calcification. The CRP level was an independent factor associated with SFACS in our previous study [8]. Furthermore, CRP is strongly associated with the progression of calcium deposition in vascular cells [10]. In the present study, CRP further demonstrated its role as a strong independent predictor of future clinical outcomes, including all-cause mortality, cardiovascular mortality, and cardiovascular events.
Stratified SFACS and BKACS indicated that the higher calcification group significantly affected long-term clinical outcomes, including cardiovascular events and mortality. The higher calcification group for both SFACS and BKACS also showed worse clinical outcomes in limb amputation. Therefore, delaying or improving vascular calcification is thought to be very important for improving cardiovascular outcomes in HD patients. Several trials have been performed to delay the progression of vascular calcification using non-calcium-containing phosphate binders [30,31,32,33,34,35], optimal and strict phosphate control using non-calcium-based phosphate binders [36], low-dose active vitamin D plus cinacalcet [37], and modification of dialysate calcium concentration [38]. These trials, including our previous study [30], succeeded in delaying the progression of vascular calcification. However, delaying or improving vascular calcification has not been clearly proven to result in improved cardiovascular events and/or mortality rates in prospective interventional randomized controlled trials in dialysis patients [39,40]. In consideration of atherosclerosis as an inflammatory process, not only delaying the progression of vascular calcification but also optimally controlling the underlying pathophysiology in HD patients, such as microinflammation, may be necessary to improve the prognosis of HD patients.
As for endovascular treatment, recent advances enabled drug-eluting balloon (DEB) angioplasty for LEAD. In cases of coronary artery stenosis as well, efficacy of DEB angioplasty compared with uncoated balloon angioplasty was reported in the treatment of critical arterial stenosis and/or occlusions in lower limbs [41,42,43]. The rates of primary vessel patency, late lumen loss, and target lesion revascularization were superior in DEB angioplasty compared with uncoated balloon angioplasty, respectively [41,42]. Heideman et al. reported that long-term all-cause mortality, rates of amputation or death, and cardiovascular events or death were significantly reduced after the use of paclitaxel coated devises compared with uncoated devices for the treatment of CLTI [43]. Teymen et al. reported the efficacy of DEB angioplasty in patients with end stage renal disease [44]. However, their study was a retrospective, single-center study. Therefore, a convincing result for the efficacy of DEB angioplasty has not been obtained in CKD patients. A future, randomized, controlled interventional trial for the treatment of CLTI in HD patients with highly calcified vessels is needed to clarify the issue. DEB became commercially available in the autumn of 2018 in Japan (at the end of the follow-up in our study). Therefore, we could not evaluate the efficacy of DEB angioplasty in HD patients.
In conclusion, $60\%$ of patients on maintenance HD died during the 10-year follow-up period. The risk factors for long-term clinical outcomes were CRP, serum albumin, age, DM, presence of IHD, CLTI, and vascular calcification score, including SFACS and BKACS, by a univariate Cox proportional hazard analysis. The CRP level was a strong and independent predictor of all-cause mortality, cardiovascular mortality, and cardiovascular events in a 10-year follow-up study. Arterial calcification of the lower limbs significantly predicted 10-year cardiovascular events and mortality (but not all-cause mortality) in HD patients. Although the number of patients was rather small, and this was a single-center observational study, our study provided new insights in the field of vascular medicine. Quantitative evaluation of arterial calcification of the lower limbs using MDCT for all HD patients may not be practical. However, to understand and keep in mind the impact of arterial calcification of the lower limbs on long-term clinical outcomes may contribute to improving the quality of care provided for HD patients with LEAD. Future prospective interventional trials may be needed, regarding whether delaying or improving arterial calcification of the lower limbs may improve long-term clinical outcomes in patients undergoing HD.
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|
---
title: Increased Mitochondrial Calcium Fluxes in Hypertrophic Right Ventricular Cardiomyocytes
from a Rat Model of Pulmonary Artery Hypertension
authors:
- Anna Maria Krstic
- Amelia S. Power
- Marie-Louise Ward
journal: Life
year: 2023
pmcid: PMC9967871
doi: 10.3390/life13020540
license: CC BY 4.0
---
# Increased Mitochondrial Calcium Fluxes in Hypertrophic Right Ventricular Cardiomyocytes from a Rat Model of Pulmonary Artery Hypertension
## Abstract
### Simple Summary
In pulmonary artery hypertension, right ventricular (RV) afterload is increased, which requires the cardiomyocytes to contract with greater force against the additional pulmonary artery pressure. In response, RV cardiomyocytes increase contractile protein content to maintain greater workload, consuming larger amounts of energy (supplied by the mitochondria) on a beat-to-beat basis. Failing hearts have been described as an “engine out of fuel”, but it is unclear how the mitochondria match ATP supply to demand in hypertrophic hearts prior to failure. Therefore, our aims were (i) to measure beat-to-beat mitochondrial Ca2+ fluxes, and (ii) to determine mitochondrial abundance and function in hypertrophied cardiomyocytes prior to the onset of heart failure. To identify the early adaptive changes in energy supply prior to failure, we utilised a rat model of pulmonary artery hypertension to investigate RV cardiomyocytes during compensated hypertrophy in comparison to their normotensive controls. Mitochondrial Ca2+ fluxes were increased in hypertrophied cardiomyocytes, but no difference was found in oxidative phosphorylation between the groups. This suggests that the larger mitochondrial Ca2+ transients are a compensatory mechanism to match ATP supply to the increased energy demands of hypertrophic cardiomyocytes.
### Abstract
Pulmonary artery hypertension causes right ventricular hypertrophy which rapidly progresses to heart failure with underlying cardiac mitochondrial dysfunction. Prior to failure, there are alterations in cytosolic Ca2+ handling that might impact mitochondrial function in the compensatory phase of RV hypertrophy. Our aims, therefore, were (i) to measure beat-to-beat mitochondrial Ca2+ fluxes, and (ii) to determine mitochondrial abundance and function in non-failing, hypertrophic cardiomyocytes. Male Wistar rats were injected with either saline (CON) or monocrotaline (MCT) to induce pulmonary artery hypertension and RV hypertrophy after four weeks. Cytosolic Ca2+ ([Ca2+]cyto) transients were obtained in isolated right ventricular (RV) cardiomyocytes, and mitochondrial Ca2+ ([Ca2+]mito) was recorded in separate RV cardiomyocytes. The distribution and abundance of key proteins was determined using confocal and stimulated emission depletion (STED) microscopy. The RV mitochondrial function was also assessed in RV homogenates using oxygraphy. The MCT cardiomyocytes had increased area, larger [Ca2+]cyto transients, increased Ca2+ store content, and faster trans-sarcolemmal Ca2+ extrusion relative to CON. The MCT cardiomyocytes also had larger [Ca2+]mito transients. STED images detected increased mitochondrial protein abundance (TOM20 clusters per μm2) in MCT, yet no difference was found when comparing mitochondrial respiration and membrane potential between the groups. We suggest that the larger [Ca2+]mito transients compensate to match ATP supply to the increased energy demands of hypertrophic cardiomyocytes.
## 1. Introduction
In pulmonary artery hypertension (PAH), right ventricular (RV) afterload is increased, which requires RV cardiomyocytes to contract with greater force to eject a sufficient stroke volume. In response, RV cardiomyocytes hypertrophy, thus increasing their contractile protein content. This allows the RV to contract against greater pressures [1]. Due to this chronic increase in workload, hypertrophic hearts constantly require larger amounts of ATP to achieve an adequate cardiac output on a beat-to-beat basis. We have previously shown that, when RV hypertrophy progresses to failure, there is significant mitochondrial dysfunction [2,3]; however there are changes in Ca2+ handling that precede failure [4,5,6], which can affect both energy supply and force development. Previous evaluation of cardiomyocyte ATP, ADP, and Pi in vivo has shown that their concentrations remain relatively constant over a wide range of cardiac outputs [7]. The mitochondria play an important role in matching ATP supply to meet the ever-changing demands of the heart by utilising two key regulatory mechanisms. The first is an ADP metabolic feedback mechanism [8], and the second senses the magnitude of cytosolic Ca2+ changes during EC coupling [9]. Ca2+ can diffuse from the cytosol into the mitochondria via the voltage-dependent anion channel 1 on the outer mitochondrial membrane [10], where it then gets taken up into the mitochondrial matrix via the mitochondrial Ca2+ uniporter (MCU) on the inner mitochondrial membrane [11]. Ca2+ can then enhance the activity of various Ca2+ sensitive enzymes of the Krebs cycle, ultimately increasing ATP production [12]. Extrusion of mitochondrial Ca2+ occurs via the mitochondrial Na+/Li+/Ca2+ exchanger (mNLCX), which prevents mitochondrial Ca2+ overload and the pathological opening of the mitochondrial transition pores (mPTP) [13]. It is known that the mitochondria undergo a number of changes in the failing heart (for a review see Xu et al [14], one of which is attributed to Ca2+ overload [15]. It was thought that increased MCU Ca2+ re-uptake during relaxation could be protective by reducing arrhythmias caused by elevated levels of [Ca2+]cyto [16]. On the other hand, high levels of [Ca2+]mito can also stimulate the opening of the mPTP, which can cause significant damage to the mitochondria and disrupt ATP production, interfering with energy supply-and-demand matching [13]. Nonetheless, if the cardiomyocyte mitochondria cannot match the heart’s energetic demands, cardiac output can become compromised, which is a cardinal feature of heart failure (HF).
Prior to the onset of HF, there is an earlier state of compensatory cardiac hypertrophy. During compensated cardiac hypertrophy, cardiomyocytes require greater amounts of ATP to be produced per cell. However, it is currently unclear whether this stage is associated with an increased abundance of mitochondria per hypertrophied cell, or whether the mitochondria present are simply required to work harder to supply the ATP required. In addition, the kinetics of mitochondrial Ca2+ fluxes remain poorly understood, primarily due to the challenges of measuring mitochondrial Ca2+ in intact muscle preparations [17]. The main aim of our study was, therefore, to measure mitochondrial Ca2+ fluxes in healthy cardiomyocytes and also in hypertrophied cardiomyocytes prior to the onset of heart failure. Additionally, we aimed to determine whether cytosolic Ca2+ handling also had an impact on mitochondrial Ca2+ fluxes. Our second aim was to compare the distribution and relative abundance of the myofilaments, mitochondria, and ryanodine receptors between groups using confocal and stimulated emission depletion (STED) microscopy of fixed RV tissue sections. Our final aim was to examine mitochondrial oxidative phosphorylation during compensated hypertrophy. To achieve our aims, we utilised the monocrotaline rat model of pulmonary artery hypertension (PAH) during compensated right ventricular hypertrophy and their normotensive controls [6,18].
## 2.1. Animal Model and Ethical Approval
Pulmonary artery hypertension was induced in male Wistar rats of body weight 306.4 ± 6.6 g (mean ± SEM) by subcutaneous injection of 60 mg kg−1 monocrotaline (MCT, Sigma Aldrich, Castle Hill, Australia). Control (CON) rats were injected with the same volume of sterile saline. Post injection, rats were monitored and weighed regularly, as previously described [18]. Approval for this research was provided by the University of Auckland Animal Ethics Committee (AEC: 001807 and 001412) in accordance with the Code of Ethical Conduct of The University of Auckland and the New Zealand Animal Welfare Act 1999.
## 2.2. Cell Isolation
On the day of experimentation (30 ± 2 days post injection), the rats were euthanised, and their hearts were removed, weighed, and rapidly cannulated via the aorta. Dissociation of quiescent, rod-shaped cardiomyocytes was carried out using standard enzymatic digestion, as previously described [17]. The livers and lungs were also removed, blotted, and weighed for subsequent morphometric analysis.
## 2.3. Loading of Ca2+ Indicators
Isolated RV myocytes from each heart were divided into aliquots for the different measurements carried out. For cytosolic Ca2+, cells were loaded with 10 µM Fura-2/AM (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) dissolved in 20 µL dimethyl sulphoxide anhydrous (DMSO, ThermoFisher) with $20\%$ pluronic Invitrogen (Scientific, Life Technologies NZ, Auckland, New Zealand) for 20 min at room temperature. Cells were then washed with 1 mM Ca2+ Tyrode’s solution for at least 10 min prior to imaging. Mitochondrial Ca2+ measurements were taken in cells loaded with di-hydroRhod-2 (dhRhod-2), as previously described [17]. Briefly, a single 50 µg vial of Rhod-2 indicator (Invitrogen, Scientific, Life Technologies NZ) was dissolved in DMSO and $20\%$ pluronic in DMSO was added. The smallest possible amount of Na+ borohydride (reducing agent) was dissolved in 20 µL methanol, and 10 µL was added to the Rhod-2 vial. After 5–10 min, 1 mL of cell suspension was added to 5 µM dhRhod-2 and left for 1 h at 37 °C. Cells were then washed for at least 30 min prior to imaging.
## 2.4. Experimental Solutions and Protocols
Cytosolic Ca2+ transients were recorded in RV cardiomyocytes loaded with Fura-2 (as described in Section 2.3). Cells were field-stimulated at 1 Hz (room temperature) and continuously superfused with Tyrode’s solution containing (in mM): 140 NaCl, 4 KCl, 10 Hepes, 1 MgCl2, 10 Glucose, and 1 CaCl2 (all Sigma-Aldrich Co. Merck, Darmstadt, Germany). Myocytes were imaged using a 20× fluorescent objective lens (0.75 NA) and illuminated with alternating 340 nm and 380 nm excitation wavelengths every 5 ms using an Optoscan monochromator and a spectrofluorometric PMT-based system (Cairn, Faversham, the UK). Emitted 510 ± 15 nm fluorescence was acquired at 400 Hz using Acquisition Engine Software (Cairn, Faversham, the UK) from whole cells as a measure of cytosolic [Ca2+] fluxes. Myocytes were subjected to 1 Hz stimulation until steady state was achieved. At this point, both the flow and the stimulation were switched off, and a 20 mM bolus of caffeine (Sigma-Aldrich) in Tyrode’s solution was applied to the bath to determine Ca2+ store content and sarcolemmal NCX activity. Superfusion with caffeine-free Tyrode’s solution and stimulation at 1 Hz were then re-commenced. The response to β-adrenergic stimulation with 1 mM Ca2+ Tyrode’s solution containing 1 µM isoproterenol (ISO, Sigma-Aldrich, cat no. 16504) was then determined.
Mitochondrial Ca2+ measurements were taken from dhRhod-2 loaded myocytes using the same spectrofluorometric system described above. Cells were field-stimulated at 0.1, 0.5, and 1 Hz (room temperature) and continuously superfused with 1.5 mM [Ca2+] Tyrode’s solution containing 1 µM isoproterenol and 150 µM spermine (Cayman Chemical, Ann Arbor, MI, USA, cat no. 136587-13-8). Myocytes were illuminated with a 542 ± 10 nm excitation wavelength and emitted fluorescence was collected at 581 nm (±10 nm) from whole cells as a measure of mitochondrial Ca2+ fluxes.
## 2.5. Labelling, Fixation, and Imaging of RV Tissue Sections
For details on fixation and labelling of isolated cardiomyocytes and tissue sections, refer to the Supplementary Data file. Confocal and STED images of RV sections dual-labelled with translocator of the outer mitochondrial membrane/ryanodine receptors (TOM20/RyR2) were obtained with an Olympus IX83 Abberior Facility Line STED microscope using a 60× oil immersion objective lens (NA 1.42). To show a larger portion of the tissue being analysed, confocal images were first captured with a 70 µm × 70 µm frame size at 80 nm pixel resolution. Then, both confocal and STED images were captured from a smaller portion of the tissue section (15 µm × 15 µm frame size) at a 15 nm pixel resolution with 594 nm and 640 nm lasers simultaneously at excitation laser powers 3–$6\%$ for confocal and STED images. Power for the STED depletion laser, emitted at 775 nm, was between $6\%$ and $10\%$. Furthermore, confocal images of RV sections co-labelled for F-actin (Alexa Fluor 488 Phalloidin conjugate, 1:50, A12379, Thermofisher Scientific, Waltham, MA, USA) and mitochondria (TOM20) were obtained with a Zeiss LSM800 laser-scanning confocal microscope using a 63× oil-immersion objective lens (NA of 1.4). Images were captured at a 50 nm pixel resolution with 488 nm and 594 nm lasers simultaneously at $0.4\%$ laser power.
## 2.6. Mitochondrial Respiration and Membrane Potential
Mitochondrial respiration and membrane potential (ΔΨ) were measured in a separate cohort of saline and monocrotaline-injected rats (300–350 g; $$n = 20$$; AEC: R1403). Following rat euthanasia and cardiac excision, an RV sample was processed for high-resolution respirometry coupled to fluorometry with an Oxygraph-O2K™ respirometer (Oroboros™, Innsbruck, Austria). Approximately 20 mg of tissue was homogenised for 10 s in 25 volumes of ice-cold respiration buffer (RB; containing (in mM): MgCl2.6H2O [3], K-lactobionate [60], taurine [20], KH2PO4 [10], HEPES [20] and sucrose [110], with essential fatty acid free bovine serum albumin (BSA; 1 g L−1) and adjusted to pH 7.1 with KOH at 37 °C.). RV homogenate (1 mg mL−1) was added in duplicate to each chamber of the oxygraph containing 2 mL of RB prior to the addition of 2 µM safranine-O. ΔΨ was measured by following safranine-O fluorescence using a filter set for excitation/emission wavelengths of $\frac{495}{587}$ nm in the oxygraph fluorometers [19]. Complex I substrates were added and left to achieve a stable ΔΨ. Oxidative phosphorylation (OXPHOS) was then initiated by the addition of 0.1 mM ADP along with 5 mM glucose and 2 U mL−1 of hexokinase to keep mitochondria in a phosphorylating state [20]. Then, 0.3 mM CaCl2 was added to each chamber followed by 0.25 mM titrations to achieve free [Ca2+] from 0.39 µM to 52 µM (calculated using the MAXCHELATOR CaMgADPEGTA program). Then, 2 µM carbonyl cyanide p- (trifluoro-methoxy) phenyl-hydrazone (FCCP) was added to achieve a zero-membrane potential for safranine-O calibration. To calculate the ΔΨ, the Nernst equation (Equation [3]) was used as previously described [21]. Here, R is the gas constant, F is the Faraday constant, T is the temperature in Kelvin, and z is the valence state of safranine-O (+1). Cin is the concentration of safranine-O within the mitochondria and *Cout is* the concentration of safranine-O in the RB. CRB is the concentration of safranine-O measured in the RB at any point during the assay. Non-mitochondrial safranine-O uptake was subtracted from the total concentration of safranine-O (Ctotal − CFCCP) determined by the signal following the addition of FCCP, which did not return to baseline which is normally seen with isolated mitochondria [21]. VRB is the volume of respiration buffer (2 mL), and *Vmito is* the mitochondrial volume, which was estimated to be 3.1 μL mg−1 based on our previous assumptions [22]. [ 1]ΔΨ=RTzFlnCoutCin [2]Cout=CRB [3]Cin=CFCCP−CRBVRBVmito
## 2.7. Data Analysis
For further details of our data analysis, refer to the Supplementary Data file. Briefly, morphometric data were analysed by unpaired, two-tailed, t-tests to determine the differences in body and organ weights between groups. Cytosolic and mitochondrial Ca2+ transient data from RV myocytes were acquired using the Acquisition Engine (Cairn Research, Faversham, UK), and subsequently analysed using a custom-written IDL program (IDL version 6.2, Research Systems Inc., Boulder, CO, USA) to determine the various Ca2+ transient parameters. Parameters were subsequently analysed using two-way ANOVA for multiple comparisons between groups and interventions. Additionally, confocal images of RV sections co-labelled with phalloidin and TOM20 were acquired on Zen Blue software and subsequently analysed on Image J FIJI. Data from these images were also statistically analysed using a two-way ANOVA for multiple comparisons between groups (MCT vs. CON) and between labels (phalloidin vs. TOM20). Simultaneous confocal and STED images of RV sections immunolabelled for TOM20 and RyR2 were acquired using Lightbox Software (Abberior Instruments, Göttingen, Germany). STED images of RV tissue sections were also analysed using ImageJ FIJI to determine (i) the area of single clusters and (ii) the number of visible clusters per 1 µm2. These parameters were subsequently analysed by unpaired, two-tailed t-tests between groups. All statistical tests were performed using GraphPad Prism 9 Analysis software. The number of animals or hearts investigated is presented as “N”, while the number of cardiomyocytes is presented as “n”, unless otherwise stated.
## 3.1. Evidence of Hypertrophy from Morphometric Data
At 30 ± 2 days (mean ± SEM) post injection, CON and MCT rats were sacrificed, and morphometric measurements were obtained. Table 1 shows that the CON body weights were higher than the MCT body weights on the day of experimentation ($p \leq 0.001$). The MCT animals had higher wet/dry lung weights compared to the CON animals ($p \leq 0.01$), with no difference in wet/dry liver weights, heart weight, or tibial length between groups. The heart weight:body weight (%) was not different between CON and MCT animals ($$p \leq 0.06$$). The cardiomyocyte area was calculated by measuring the perimeter of isolated cells, as illustrated by the grey outlines around representative cardiomyocytes in Figure 1A,B. Figure 1C shows that the LV CON myocytes were larger (mean ± SEM, 3963.54 ± 159.66 μm2) relative to the CON RV myocytes (3252.55 ± 152.08 μm2, $p \leq 0.01$). However, the MCT RV myocyte area (4134.29 ± 152.56 μm2) was higher than both the CON RV ($p \leq 0.001$) and the MCT LV myocyte areas (3578.31 ± 137.93 μm2, $p \leq 0.05$). There were no differences between CON and MCT LV myocytes or CON LV myocytes vs. MCT RV myocytes.
## 3.2. Response to β-Adrenergic Stimulation
Cytosolic Ca2+ fluxes were measured in response to β-adrenergic stimulation in RV myocytes subjected to 1 µM isoproterenol (ISO). Figure 2 shows the mean ± SEM data recorded from the CON and MCT RV cardiomyocytes before ISO (−) and during response to ISO (+ISO). Figure 2A shows that ISO increased the amplitude of [Ca2+]cyto transients for CON RV myocytes (mean ± SEM $\frac{340}{380}$ ratio, 1.99 ± 0.15 a.u.) vs. before ISO (1.41 ± 0.14 a.u., $p \leq 0.01$), whereas MCT myocytes showed no change in [Ca2+]cyto amplitude in response to ISO (1.67 ± 0.16 a.u.) relative to pre-ISO (1.51 ± 0.16 a.u.). However, MCT RV myocytes had larger baseline [Ca2+]cyto transients (1.58 ± 0.46 a.u.) relative to CON RV myocytes (1.26 ± 0.31 a.u., $p \leq 0.05$) before the introduction of ISO. Figure 2B shows that CON RV myocyte [Ca2+]cyto transients had faster maximum rate-of-rise in response to ISO (0.09 ± 0.01 a.u. ms−1) compared to pre-ISO (0.06 ± 0.01 a.u. ms−1, $p \leq 0.01$). MCT RV myocytes showed no change in maximum rate-of-rise in response to ISO; yet the maximum rate-of-rise before ISO was faster for MCT cardiomyocytes (0.10 ± 0.11 a.u. ms−1) in comparison to CON (0.06 ± 0.09 a.u. ms−1). In addition, neither CON nor MCT RV myocytes showed a change in the time-to-peak fluorescence in response to ISO (Figure 2C). ISO reduced the time constant of decay in CON RV myocytes (Figure 2D) from the baseline (0.27 ± 0.02 s) to (0.22 ± 0.014 s, $p \leq 0.01$), whereas ISO had no effect on the time constant of decay of MCT RV cardiomyocytes.
## 3.3. Sarcoplasmic Reticulum Ca2+ Store Content
SR Ca2+ store content was assessed by addition of a 20 mM caffeine bolus to the solution bathing the CON and MCT RV cardiomyocytes. Figure 3A shows a representative caffeine-induced [Ca2+]cyto transient recorded from a single CON RV myocyte. The amplitude of the caffeine transient ($\frac{340}{380}$ ratio) in the absence of stimulation gave a measure of total [Ca2+]SR, while the time constant of the caffeine [Ca2+]cyto transient decay in the continued presence of caffeine gave a measure of trans-sarcolemmal Ca2+ efflux. Figure 3B shows that the MCT RV myocytes had larger caffeine-induced [Ca2+]cyto transients (0.78 ± 0.06 a.u.) in comparison to the CON RV myocytes (0.59 ± 0.03 a.u., $p \leq 0.01$). The MCT RV myocytes also showed a decreased time constant of decay (Figure 3C, 4.75 ± 0.20 s) relative to the CON RV myocytes (6.07 ± 0.42 s, $p \leq 0.05$).
## 3.4. Beat-to-Beat Mitochondrial Ca2+ Fluxes
Beat-to-beat mitochondrial Ca2+ transients (Figure 4A) were recorded in the CON and MCT RV cardiomyocytes loaded with di-hydroRhod-2. The MCT RV cardiomyocytes had larger mitochondrial Ca2+ transient ([Ca2+]mito) amplitude (ΔF/F0, Figure 4B) at 0.1 Hz (mean ± SEM, 0.033 ± 0.002 a.u.) and 0.5 Hz stimulation (0.032 ± 0.002 a.u.) in comparison to the CON RV cardiomyocytes (0.1 Hz, 0.025 ± 0.002 a.u., $p \leq 0.001$ and 0.5 Hz 0.026 ± 0.001 a.u., $p \leq 0.05$). Figure 4C,D shows no change in the maximum rate-of-rise of [Ca2+]mito and time-to-peak fluorescence in MCT RV myocytes relative to CON RV myocytes at any stimulation frequency. The MCT RV myocytes had a time-to-peak fluorescence of 0.201 ± 0.015 s at 0.1 Hz, and 0.206 ± 0.021 s at 0.5 Hz, relative to the CON RV myocytes, which had a time-to-peak fluorescence of 0.165 ± 0.011 s at 0.1 Hz and 0.166 ± 0.010 at 0.5 Hz ($$p \leq 0.15$$, Figure 4D). No difference in the time constant of fluorescence decay (Figure 4E) was found between groups, or between stimulation frequencies.
## 3.5. Mitochondrial Abundance in RV Fixed Tissue
The area of cardiomyocyte occupied by mitochondria relative to the area occupied by the myofilaments was compared in longitudinal sections from healthy and hypertrophic RV tissue sections. Figure 5 shows confocal images of representative CON and MCT RV longitudinal sections co-labelled with phalloidin (red, for F-actin) and TOM20 (green, for mitochondria). Superimposed F-actin and TOM20 labelling of both CON (Figure 5C) and MCT (Figure 5F) RV tissue showed that TOM20 labelling was parallel to, and in close association with, F-actin labelling, indicating that the myofibrils were sandwiched between mitochondria. The mean data (Figure 5G) show the fractional area of TOM20 and phalloidin labelling in tissue sections from $$n = 3$$ CON and $$n = 3$$ MCT hearts. Figure 5G shows that the MCT RV sections had increased area of F-actin labelling per myocyte (59.7 ± $1.8\%$) relative to the CON sections (43.8 ± $3.1\%$, $p \leq 0.001$), with no difference in the mitochondrial area between CON (37.2 ± $1.0\%$) and MCT (43.6 ± $0.9\%$, $$p \leq 0.16$$) per myocyte. The ratio of the mitochondrial area relative to the F-actin area was therefore less for MCT RV myocytes ($p \leq 0.001$), whereas mitochondria and F-actin occupied equal areas of the myocytes in CON sections ($$p \leq 0.11$$).
Mitochondrial and RyR2 distribution were also compared in longitudinal RV tissue sections between groups using confocal and STED microscopy (Figure 6). The large-scale confocal images show the longitudinal mitochondria (TOM20) and transverse distribution of the RyR2 in both CON and MCT tissue (Figure 6A,D), which was also evident in small-scale confocal and STED images (Figure 6B,C,E,F). However, the STED images also showed an increased number of TOM20 and RyR2 clusters (Figure 6C,F) in comparison to the confocal images for both groups (Figure 6B,E). Associations between RyR2 and TOM20 clusters were also evident in the small-scale STED images (Figure 6C,F). Mean data calculated from the STED images showed a trend towards decreased TOM20 cluster size in MCT RV myocytes (0.027 ± 0.01 µm2) relative to CON RV myocytes (0.034 ± 0.01 µm2, $$p \leq 0.07$$). Despite smaller TOM20 cluster sizes, the MCT RV myocytes had an increased number of TOM20 clusters per µm2 (Figure 6H, 14.9 ± 3.2 clusters/1 µm2 regions) vs. CON RV myocytes (11.2 ± 4.2 clusters/1 µm2 regions, $$p \leq 0.06$$). The MCT RV myocytes also showed smaller RyR2 cluster size (Figure 6I, 0.016 ± 0.007 µm2) in comparison to CON (0.022 ± 0.005 µm2, $$p \leq 0.02$$) but with no difference in the number of RyR2 clusters per 1 µm2 between groups (Figure 6J, $$p \leq 0.2$$).
## 3.6. Mitochondrial Respiration and Membrane Potential
To test for any difference in mitochondrial function between CON and MCT hearts, concurrent measurements of O2 consumption and mitochondrial membrane potential were recorded in RV homogenates in the oxygraph. The driving force for ATP production via oxidative phosphorylation is from the electrochemical potential across the inner mitochondrial membrane, the majority of which is made up of the mitochondrial membrane potential (ΔΨ). This was measured using ΔΨ fluorescence indicator safranine-O with increasing free [Ca2+]. Figure 7A shows a representative trace from the control RV homogenate. Following the addition of CI substrates, a high ΔΨ is developed which was partially depolarised following the addition of ADP, with hexokinase and glucose, which regenerates ADP to reach a steady-state ΔΨ. An initial titration of 0.3 mM CaCl2 (free [Ca2+] of 0.39 μM) depolarises the ΔΨ and stimulates the O2 flux; however, further titrations of CaCl2 result in the inhibition of O2, and ΔΨ repolarises until opening of the mitochondrial permeability transition pore (mPTP) and depolarisation of the ΔΨ. This can be accelerated by the addition of FCCP. Mitochondrial respiration was not different between CON and MCT RV homogenates for all respiratory states before or after the addition of CaCl2 (Figure 7B). After the initial addition of CaCl2, there was a small (non-significant $$p \leq 0.06$$) stimulatory effect of respiration. The developed ΔΨ did not differ between the groups and the addition of ADP and CaCl2 similarly depolarised the ΔΨ.
## 4.1. Evidence of Hypertrophy from Morphometric Data
Changes in myocardial Ca2+ were studied in hypertrophic cardiomyocytes using the monocrotaline (MCT) rat model of pulmonary artery hypertension (PAH) and their saline-injected controls (CON). Morphometric data confirmed that MCT rats four weeks post-injection were not in heart failure, and there was no difference in heart weight to body weight between CON and MCT animals on the day of experimentation. This was unexpected as the hypertrophic RV was expected to increase the mass of the whole heart. However, LV atrophy has been previously reported in MCT myocardium [18,23], which can explain the lack of change in the HW:BW ratio between groups. Furthermore, measurements of cardiomyocyte area confirmed that isolated RV myocytes from MCT were hypertrophied with larger perimeters relative to CON RV and LV myocytes, and to MCT LV myocytes (Figure 1A–C).
## 4.2. Response to β-Adrenergic Stimulation
The response of RV cardiomyocytes to the non-selective β-AR agonist isoproterenol (ISO) showed that ISO increased peak systolic [Ca2+]cyto in CON RV myocytes (Figure 2A) but not in MCT RV myocytes, although MCT RV myocytes had larger [Ca2+]cyto transients in the absence of ISO relative to CON (Figure 2A). The time-to-peak fluorescence (Figure 2C) and diastolic [Ca2+]cyto (Supplementary Figure S1) were unaffected by ISO in both groups, but only CON myocytes showed increased cytosolic Ca2+ transient kinetics during ISO (maximum rate-of-rise (Figure 2B) and time constant of decay (Figure 2D)). Overall, MCT myocytes did not show the expected response to β-AR stimulation [24,25]. The increased [Ca2+]cyto transient amplitudes from MCT in comparison to CON (in the absence of ISO) is unlikely to be a result of endogenous β-AR activation in isolated cells stored in the physiological buffer following isolation. Instead, we suggest that the diminished MCT response to ISO might be a result of the SR Ca2+ stores already being at capacity prior to β-AR stimulation. A decreased response to ISO can also be due to the distribution of β-ARs, whereby spatially diverse cAMP diffusion occurs depending on the receptor subtype that is activated. For example, activation of β1-AR induces cell-wide cAMP diffusion and PKA activation, whereas the β2-AR subtype has been shown to be present specifically in the T-tubules, inducing a more localised cAMP diffusion/PKA activation [26]. MCT-induced RV hypertrophy is associated with T-tubular disorganisation [6,27], which might affect the distribution of β2-ARs [28], thereby altering cAMP diffusion and PKA activation of Ca2+ handling proteins localised to the T-tubules (i.e., the LTCC). The blunted response to ISO might also be due to either β-AR receptor downregulation or desensitisation, which has previously been reported in hypertrophic and failing MCT hearts [6,29,30].
## 4.3. Increased Ca2+ Store Content in Hypertrophy
Caffeine increases the opening probability of the RyR2, which makes it a useful tool for measuring the SR Ca2+ content of isolated cardiomyocytes. The continued presence of caffeine in the buffer solution prevents the accumulation of SR Ca2+ [31,32], while the sarcolemmal Ca2+ removal mechanisms eventually restore cytosolic [Ca2+] concentration to the diastolic level [33]. Therefore, subjecting myocytes to prolonged caffeine provided measurements of both total SR Ca2+ store content (amplitude) and NCX trans-sarcolemmal Ca2+ extrusion (from the time constant of the caffeine transient decay, Figure 3A). NCX accounts for the bulk of trans-sarcolemmal Ca2+ extrusion, and, in the rat, only ~5–$10\%$ is normally extruded across the NCX, while MCU and Ca2+ ATPase also provide minor contributions [32]. Hypertrophic MCT RV myocytes had increased SR Ca2+ store content in comparison to the CON RV myocytes (Figure 3B), resulting in larger baseline Ca2+ transient amplitudes and faster rates-of-rise in comparison to the CON myocytes (Figure 2A,B and Figure 3B). Since measurements of cytosolic [Ca2+] were made using a ratiometric fluorescent indicator, the higher amplitude transients must, therefore, indicate an increased cytosolic Ca2+ concentration rather than merely due to the hypertrophied MCT cardiomyocytes being larger in size than CON. Caffeine-induced Ca2+ transients from MCT RV cardiomyocytes also had a decreased time constant of decay relative to CON RV myocytes (Figure 3C), providing evidence that trans-sarcolemmal Ca2+ extrusion rate (flux) via NCX activity was increased in the MCT.
## 4.4. Beat-to-Beat Mitochondrial Ca2+ Fluxes
Ca2+ uptake via the mitochondrial calcium uniporter (MCU) is one of the key regulators of ATP production in the myocardium [34]. The MCU is a low-affinity Ca2+ transporter on the inner mitochondrial membrane, which is activated at high [Ca2+]cyto, such as at the peak of the [Ca2+]cyto transient during EC coupling [9]. An influx of Ca2+ into the mitochondrial matrix enhances the activity of various Ca2+ sensitive enzymes of the Krebs cycle, which ultimately promotes ATP production [12]. Mitochondrial Ca2+ concentration fluctuates on a beat-to-beat basis, i.e., mitochondrial “transients” [17], thus relaying the cellular energy requirements directly to match supply to demand. Mitochondrial transients have a slower time-to-peak and time constant of decay relative to cytosolic Ca2+ transients (Figure 4A). In addition, MCT RV cardiomyocytes had larger mitochondrial Ca2+ transient ([Ca2+]mito) amplitudes at 0.1 Hz and 0.5 Hz stimulation in comparison to CON RV cardiomyocytes (Figure 4B). These results indicate that hypertrophic cardiomyocytes have increased mitochondrial Ca2+ uptake, probably as a result of a higher [Ca2+]cyto/[Ca2+]SR [35]. This is consistent with our cytosolic Ca2+ measurements from MCT RV myocytes (Figure 2A,B and Figure 3B). It has been suggested that hypertrophic cardiomyocytes have a compensatory mechanism whereby the mitochondria act as a buffer of cytosolic Ca2+, reducing the incidence of delay after depolarisations and spontaneous Ca2+ release events [36,37,38]. However, others have proposed that the contribution of the MCU to cytosolic Ca2+ removal is approximately $1\%$ [32,39]. The decay of [Ca2+]mito transients reported in the present study, and by others [40,41], suggests that the mitochondria only temporarily increase their Ca2+ content between myocyte contractions. Our findings showed no difference between groups in mitochondrial Ca2+ transient kinetics at the stimulation frequencies investigated (Figure 4C,D), including no changes to the time constant of decay (Figure 4E). These results suggest that mNLCX activity, which is the primary transporter for mitochondrial Ca2+ extrusion during the decay [42], was unchanged between CON and MCT RV myocytes.
## 4.5. Mitochondrial Abundance in RV Fixed Tissue
Cardiac hypertrophy is characterised by increased cell size due to a higher abundance of contractile proteins [1]. This means that hypertrophic cardiomyocytes are capable of increased work, which requires more energy than the healthy control cardiomyocytes. In the present study, confocal images showed that the fractional area of mitochondria calculated per RV tissue section was not different in MCT relative to CON, despite a $16\%$ increase in myofilament content (Figure 5A–G), as previously described [2]. Figure 5C,F show that the longitudinal labelling pattern of F-actin (using phalloidin) was distributed in parallel to, and in close association with, the mitochondria (labelled with a marker for the translocator of the outer mitochondrial membrane; TOM20). TOM20 is a subunit of the large TOM protein complex located on the outer mitochondrial membrane, with linkages to the inner membrane. Its function is to translocate nuclear-encoded proteins from the cytosol destined for the mitochondria [43]. TOM20 is highly abundant on the outer membrane, making it difficult to resolve its exact distribution when imaging with a modality beyond the diffraction limit—i.e., with confocal microscopy [44]. While confocal images did not detect a change in mitochondrial abundance between CON and MCT RV tissue (Figure 5), we further investigated mitochondrial clusters using STED imaging, which enabled improved lateral resolution from ~250 nm to ~40–60 nm.
STED microscopy of fixed cardiac tissue enabled the size and number of individual TOM20 clusters to be identified (Figure 6). A clustered distribution of TOM20 has been previously reported in super-resolution imaging of different cell types, excluding cardiomyocytes [45,46,47,48]. In addition, it has been suggested that the cluster density of TOM20 is tightly regulated and correlated with both the activity and location of the mitochondria, and that the TOM20 distribution is finely tuned to match the energetic demands of the cell [44,47]. This would mean that, since hypertrophic cardiomyocytes are larger (Figure 1B,C) and have increased [Ca2+]mito transients (Figure 4B), larger TOM20 cluster densities would also be expected. In the present study, STED microscopy showed a trend toward decreased TOM20 cluster size in MCT RV tissue when compared to the control (Figure 6G), suggesting fewer TOM20 receptors per cluster. On the other hand, MCT RV tissue also showed a trend towards an increased number of clusters per µm2 relative to CON RV tissue (Figure 6H). This contradicts the data presented in Figure 5G, which showed no absolute change in mitochondrial content between CON and MCT hearts, despite an increase in contractile protein content. This is most probably due to the lack of resolution with standard confocal microscopy. An increased number of TOM20 clusters could either mean that more mitochondria are present or that TOM20 expression is increased in hypertrophic tissue. However, TOM20 expression has previously been shown to be unaffected in pathological cardiac hypertrophy [49]. Therefore, an increase in the number of mitochondria present in hypertrophic RV tissue could explain this result. Additionally, while our STED data showed a $24\%$ increase in TOM20 clusters in hypertrophic RV tissue (Figure 6H), our functional data also showed that mitochondrial Ca2+ uptake was increased by $33\%$ in MCT RV myocytes relative to CON RV myocytes (Figure 4B). Although the STED data from the present study showed a trend towards increased TOM20 cluster numbers, we cannot determine whether the mitochondrial distribution of TOM20 differed between groups.
Furthermore, it was evident that there was some overlap between the mitochondria and the RyR2 Ca2+ release sites in Figure 6, which was expected as this enables the mitochondria to immediately sense changes [Ca2+]cyto during EC coupling [50]. The present study showed reduced RyR2 cluster size in hypertrophic RV tissue relative to the controls (Figure 6I) which could be a sign of RyR2 cluster fragmentation as reported by Sheard et al. [ 51]. These data contradict findings from other studies investigating hypertrophic tissue using super resolution imaging techniques, which showed either no change in RyR2 signal density [52] or an increased mean RyR2 cluster density [53]. Despite the smaller RyR2 cluster areas determined in MCT RV tissue, there were also no differences in the number of RyR2 clusters per µm2 between groups (Figure 6J). This indicates a possible scattered distribution of the RyR2 clusters throughout the myocyte, increasing its “nearest neighbour distance” (see Supplementary Figure S2). However, functional data from CON and MCT isolated cells presented in this study show no change in the time-to-peak fluorescence (i.e., the time of L-Type Ca2+ channel activation following cardiomyocyte stimulation to RyR2 Ca2+ release, Figure 2C) between groups. This suggests that either sarcolemmal Ca2+ fluxes are upregulated in MCT RV myocytes or the SR volume of hypertrophic myocytes is more extensive, which could overcome any irregularities of the T-tubular network.
## 4.6. Mitochondrial Respiration and Membrane Potential
Since mitochondria are responsible for producing $95\%$ of the ATP consumed by cardiomyocytes [54], they have been implicated in the energy deficits observed in models of pathological hypertrophy. Measurement of O2 flux in vitro by high-resolution respirometry is the gold standard measure for mitochondrial function. There was no difference in O2 flux measured in RV homogenates from CON or MCT hearts in any respiratory state measured. Therefore, although the MCT hearts had significant RV hypertrophy, their mitochondrial oxidative capacity was similar to the control per mg of tissue. Addition of Ca2+ to the RV homogenate had a slight stimulation of O2. Ca2+ uptake into the mitochondria through the MCU utilises the ΔΨ and may stimulate respiration flux through the ETS [55], although, at this concentration of free Ca2+ (0.39 µM) it is likely that any uptake would be through other uptake pathways that are not fully resolved [56]. The stimulatory effect of Ca2+ was similar for both MCT and control RV homogenates, suggesting that the mechanisms of Ca2+ uptake are unchanged between the groups. The Ca2+ transient is responsible for eliciting contraction and, in parallel, stimulates mitochondria [55]. However, prolonged mitochondrial exposure to high [Ca2+] triggers opening of the mPTP and irreversible depolarisation of the ΔΨ, causing cardiomyocyte death [20]. Unfortunately, for these in vitro mitochondrial assays, we could not mimic the oscillating Ca2+ conditions observed in vivo, and titration of Ca2+ above ~0.5 µM resulted in gradual inhibition of respiration before triggering the mPTP. Therefore, only one bolus of 0.3 mM CaCl2 was used in these experiments which results in a free Ca2+ concentration of 0.39 µM. We calculated ΔΨ from the uptake of fluorescent cation safranine-O which has been used previously [19,21,22]. Although it is documented to have some inhibitory effects on respiration [19], these are minimal at low safranine-O concentrations (2 µM) and are far less compared to routinely used ΔΨ indicators such as JC-1 [57] and TPP+ [58]. It could also be assumed that any inhibitory effects of safranine-O are the same for the control and MCT. The maximum ΔΨ that can be achieved in energized mitochondria is in the Leak state when no ADP is present. There was a slight (NS) depolarisation of the ΔΨ measured in MCT RV homogenate in the Leak state compared to the controls (CON: −210 ± 4 mV, MCT: −200 ± 4 mV, $$p \leq 0.09$$), suggesting that MCT RV mitochondria have a lower driving force for ATP production. However, in the phosphorylating OXPHOS state, there was no difference between groups. Given that MCT hearts will have greater energy demand due to their increased myofilament area, these data support the idea that increased mitochondrial energy supply is met by enhanced beat-to-beat mitochondrial Ca2+ uptake rather than by increased mitochondrial capacity.
## 5. Conclusions
Overall, MCT RV cardiomyocytes showed increased cytosolic Ca2+ fluxes with a blunted response to β-adrenergic stimulation, and an increased SR Ca2+ store content. In addition, MCT RV cardiomyocytes also had larger beat-to-beat mitochondrial Ca2+ fluxes, which, we speculate, indicates a compensatory mechanism developed to match ATP supply to the greater energetic demands of the hypertrophic myocytes. While confocal images confirmed an increase in contractile protein content in MCT RV tissue sections, STED microscopy also revealed an increased number of TOM20 clusters, which, in some regions, were closely associated with the RyR2 clusters. Our data show—for the first time—evidence of a link between augmented [Ca2+]mito uptake and increased mitochondrial abundance in hypertrophic cardiomyocytes. We conclude that this provides a potential mechanism by which hypertrophied cells compensate to match ATP supply to the increased energetic demands of additional contractile protein and bigger Ca2+ transients, prior to progression to heart failure.
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|
---
title: 'Pre-Pregnancy Adherence to Mediterranean Diet and Risk of Gestational Diabetes
Mellitus: A Prospective Cohort Study in Greece'
authors:
- Antigoni Tranidou
- Themistoklis Dagklis
- Emmanuella Magriplis
- Aikaterini Apostolopoulou
- Ioannis Tsakiridis
- Violeta Chroni
- Eirini Tsekitsidi
- Ioustini Kalaitzopoulou
- Nikolaos Pazaras
- Michail Chourdakis
journal: Nutrients
year: 2023
pmcid: PMC9967881
doi: 10.3390/nu15040848
license: CC BY 4.0
---
# Pre-Pregnancy Adherence to Mediterranean Diet and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study in Greece
## Abstract
Gestational Diabetes Mellitus (GDM) is a growing epidemic affecting pregnant women and their offspring. This study aimed to identify the relationship between adherence to a Mediterranean diet (MD) before conception and the risk of GDM in a contemporary Greek pregnant cohort. A prospective cohort of pregnant women was recruited at the routine first trimester visit. Nutritional intake was evaluated using a population specific validated food frequency questionnaire (FFQ). Pre-pregnancy adherence to MD was derived using two different scoring systems, the Mediterranean diet index score (MDS), and a modified version. Adjusted odds ratios (aOR) were computed using multiple logistic regression models for each score derived. Of 743 participating women, 112 ($15.1\%$) developed GDM. The MDS index showed that scoring 5–9 points (high adherence) was associated with a lower GDM incidence (aOR: 0.57 $95\%$ CI (0.32, 0.90), $$p \leq 0.02$$), while the modified MDS index showed no significant association for any level of adherence. Pre-pregnancy consumption of “meat and derivatives” and “fatty meat and processed meat” was associated with a higher risk of GDM, with both scoring systems ($$p \leq 0.008$$, $$p \leq 0.004$$, respectively). A higher adherence to a MD pre-pregnancy, especially with less meat consumption, may have a protective effect on the occurrence of GDM.
## 1. Introduction
GDM is a common carbohydrate intolerance affecting pregnant women worldwide, with different ethnic, behavioral, and cultural backgrounds [1,2]. Pregnancies with GDM are considered high-risk, as they are associated with a series of adverse outcomes, such as caesarean delivery, preeclampsia, macrosomia, preterm birth, and stillbirth [3]. Moreover, the pathophysiologic dysregulation that occurs in GDM may also have an impact in later life for both the mother and the offspring; it is a crucial determinant of healthcare cost and influences the quality of life of those affected [4,5,6,7,8]. Additionally, due to the absence of unanimous consensus among guidelines on the diagnosis and management of GDM, a number of cases may escape the appropriate attention. A recent comparative review by Tsakiridis et al. reported on the differences among the national and international guidelines regarding screening for GDM [9]. More specifically, guidelines by the International Federation of Gynecology and Obstetrics (FIGO,) the Australasian Diabetes in Pregnancy Society (ADIPS), the Society of Obstetricians and Gynecologists of Canada (SOGC), and the American College of Obstetricians and Gynecologists (ACOG) recommend screening for GDM at 24–28 weeks of gestation for all individuals, in the absence of other risk factors, whereas in the presence of additional risk factors, screening should be employed earlier. In contrast, the guideline by the National Institute for Health and Care Excellence (NICE) suggests screening at 24–28 weeks of gestation only for those that have risk factors. The Endocrine Society (ES) suggests universal screening at the first trimester for all individuals and, if negative, retesting at 24–28 weeks of gestation; the FIGO guidelines adopt this method for screening only in countries with increased risk for GDM occurrence. Finally, the American Diabetes Association (ADA) does not have specific recommendations on GDM screening. It should be noted that approximately 1–$2\%$ of all pregnancies are diagnosed with pre-gestational diabetes. Moreover, for women whose pregnancies were complicated with GDM, a glycemic test between six to twelve weeks following delivery is universally proposed.
Nutritional and lifestyle characteristics have been associated in variable degrees with proximate and/or long-term consequences for both the pregnant woman and the fetus [10]. Some studies have assessed the effect of maternal characteristics and nutritional aspects, such as the level of adherence to the Mediterranean diet (MD) during the pre-gestational or gestational period on the risk of developing GDM [11,12]. Olmedo-Requena et al. reported that high MD adherence prior to pregnancy was associated with lower incidence of GDM, whereas Assaf-Balut et al. reported that a MD pattern further supplemented with extra-virgin olive oil (EVOO) and pistachios during early pregnancy also reduced the risk of GDM. Additionally a study by Izadi et al. suggested that the higher the adherence to a lower Dietary Approaches to Stop Hypertension (DASH) or MD diet, the lower the rates of GDM are [13]. In addition, the preventive effect of physical activity both prior and also during pregnancy on lowering the incidence of GDM has been described [14,15,16]. Moreover, results of a recent umbrella review on the role of exercise in pregnancy indicated that the earlier the initiation of exercise was, the more favorable the prevention of GDM occurrence was [17]. Furthermore, the beneficial role of adherence to a MD diet in preventing or treating Type 2 diabetes mellitus (T2DM) in the general population has also been reported [18]. T2DM may have common mechanisms of pathogenesis with GDM; this has led to the hypothesis that MD may also act protectively against the pathogenesis of GDM. A number of studies conducted both in Mediterranean and non-Mediterranean populations have assessed adherence to MD or other maternal dietary patterns before pregnancy, but have reported on a variable degree of effect between MD adherence and the different dietary patterns used on the occurrence of GDM [19,20]. Study findings may vary due to the application of different tools for evaluating the adherence to MD in the non-Mediterranean populations, as their dietary habits differ from those of the Mediterranean populations [21,22,23].
Adherence to the original MD can be measured with a variety of tools, such as the Mediterranean Diet Score (MedDietScore) [24], the Mediterranean Diet Pyramid [25], the Mediterranean Diet Adherence Screener (MEDAS) [26], and many other tools developed around the world [27]. In Greece, the MDS that was developed by Trichopoulou et al. is widely used to assess adherence to the MD [28]. Modified versions have also been created to adapt to population specific dietary intakes and accommodate lifestyle changes while maintaining the primary MD categories, such as fruits and vegetables and monounsaturated fatty acids (MUFA) as the main fatty acid consumed. In the Greek field, Panagiotakos et al. also developed an index known as MedDietScore [24] based on the Mediterranean Diet Pyramid [25]. This scoring system includes 11 food groups and differs from the MDS as it includes potatoes and olive oil instead of the ratio used by the MDS for MUFA: SFA calculation, nuts are not included, while meat and poultry are considered negative factors. The effects of these diet scores on GDM risk have not to date been explored, in the same cohort, to identify potential MD score differences.
Evidence suggests that composition of gut microbiota may play a role in the modulation of glucose metabolism and might be the intermediary between gut microbiome alterations and onset of GDM [29,30]. The exact interplay between these changes is not yet clearly identified, but it is suggested that changes in the composition of the gut microbiome, along with the occurrence of insulin resistance that develops during pregnancy, may have an impact in energy homeostasis affecting intestinal permeability [31]. Additionally, a recent systematic review on the relation of gut microbiome and GDM pathogenesis revealed differences in the gut microbiome during the first trimester of pregnancy in women with post-GDM diagnosis, but no specific contributor was identified [32]. Interestingly, a current study by Pinto et al. observed that the associated GDM-changes in the gut microbiome may have preceded the occurrence of GDM by more than ten weeks before the typical diagnosis of GDM [33].
Dietary habits affect the composition of gut microbiota and have a significant impact on how the brain and behavior are modulated [34]. The synergistic effect of nutrient status, gut microbiota, and host environment play a key role in the modulation of the gut–brain axis which is responsible for health and disease. Gut microbiome influences brain function by processing the nutrient intake and by synthesizing metabolites. Altering the nutrient intake through diet can have an impact on how the brain and behavior work. High adherence to the Mediterranean diet has a beneficial effect on the gut microbiome and has been associated with promoting health [35]. Exploring the dietary patterns of women before pregnancy may further elucidate on the relationship of dietary habits and GDM occurrence.
To our knowledge, no study in the Greek population has examined the relationship of maternal adherence to MD prior to conception and its effect on GDM. Thus, the aim of this study was to evaluate the level of adherence to the MD and to a modified MD, six months prior to conception, and the associated risk of GDM in a Greek pregnant cohort.
## 2.1. Study Design and Participants
This was a prospective study targeting pregnant women that attended the 3rd Obstetrics and Gynecology Department, Aristotle University of Thessaloniki, Greece. This study included participants from a large cohort study, named “BORN2020” that commenced in Thessaloniki in 2020, and is ongoing, with the aim to collect and analyze data among women before and during pregnancy. We evaluated their adherence to MD six months prior to pregnancy. All participants were recruited at their routine antenatal visit for their ultrasound check 11+0–13+6 weeks of gestation. Of note, the national antenatal protocol recommends a universal ultrasound check at 11+0–13+6 weeks of gestation.
An approval by the Bioethics Committee of the Aristotle University of Thessaloniki was obtained ($\frac{5}{12.4.2022}$). Individuals were informed about the study and if they were positive, consent was obtained.
All pregnant women attending for their antenatal visit were eligible. Exclusion criteria were as follows: (i) age <18 years, (ii) serious pre-existing medical condition (e.g., chronic hypertension, pre-existing diabetes), (iii) women on diets that exclude specific dietary products due to medical conditions or lifestyle (e.g., vegetarian, vegan, gluten sensitivity, etc.), ( iv) previous history of GDM, polycystic ovary syndrome or acanthosis nigricans, or women on corticosteroid medication.
The results were adjusted for known risk factors of GDM, including age > 35 years and overweight or obesity, to minimize the effects of these imbalances. In our dataset, although no exclusions were employed on nationalities, all candidates were of Greek origin.
For the diagnosis of GDM, all women underwent a 75 g oral glucose tolerance test (OGTT) at 24–28 weeks of gestation, following the criteria suggested by the Hellenic Society of Obstetricians and Gynecologists (HSOG) [36], which are based on the Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) study [37]. Thus, the diagnosis of GDM was set when at least one of the measurements of blood glucose was equal or above the predefined thresholds: (i) fasting ≥92 mg/dL, (ii) 1-h ≥180 mg/dL, (iii) 2-h ≥153 mg/dL [38].
## 2.2. Variables for Assessment
Maternal anthropometric and habitual data were recorded from each participant at their visit at the antenatal clinic. Height was measured in centimeters (cm) using a stadiometer. Current weight was also measured in kilograms (kg), and pre-pregnancy weight was reported by the women. Based on BMI classification standards, women were categorized as underweight (BMI < 18.5 kg/m2), normal weight (BMI 18.5–24.9 kg/m2), overweight (BMI 25–29.9 kg/m2), or obese (BMI ≥ 30 kg/m2) [39]. Status of smoking before and during pregnancy was recorded and women were divided in past smokers, current smokers, or never smokers.
## 2.3. Assessment of Diet
Dietary assessment was performed using a locally validated FFQ, which was developed in order to evaluate the nutritional habits among pregnant women in a Greek population [40]. The FFQ was based on previous FFQs that have been developed for assessment of diet in Mediterranean populations [MEDAS (Mediterranean Diet Adherence Screener, MediCul (Mediterranean Diet and Culinary Index), and Mediterranean Oriented Culture Specific FFQ)] [41,42,43]. It contains 14 food groups consisting of 46 food items from the abovementioned FFQs, in addition to products that are commonly consumed in Greece. The FFQ was completed at the first trimester routine antenatal visit of each participant with an oral interview, carried out by trained personnel. Each interview lasted about 20 min.
Adherence to MD was calculated using two scores, the MDS derived by Trichopoulou et al. [ 28], and the modified MDS derived by Leighton et al. [ 44]. The latter was used to accommodate lifestyle changes seen in the past years, and compare potential differences between the two scores on the effect on GDM outcome. The MDS developed by Trichopoulou et al. is population specific and is calculated using a 0–9 scoring system; 0 (minimum) relates to no adherence and 9 (maximum) relates to absolute adherence. This tool categorizes foods in 9 components and includes a ratio of monounsaturated lipids to saturated lipids. Subsequently, this score was modified to include PUFA to the MUFA/SFA ratio, and included fruits separate from nuts [20].
The median was calculated for controls, and the value of 1 was assigned for those who had equal or above the mean of the consumption distribution for typical Mediterranean foods (e.g., legumes, fruit and nuts, vegetables, fish, and seafood), whereas the value of 0 was assigned if they had less than the median. On the contrary, for non-Mediterranean foods, including dairy, meat, and meat products, 1 point was awarded when consumption was lower than the median, whereas consumption higher than the median assigned 0 points. For further analysis, the scores from the sampled population achieved were divided in tertiles with the following ranges: 0–3 for low adherence, 4 for middle adherence, and 5–9 for high adherence [28]. The modified MDS by Leighton et al. [ 44] is a scoring system developed to assess MD adherence and has 14 scoring items. We chose to additionally calculate the adherence to MD with this modified version of MDS score as it is more representative of a Westernized food diet, which nowadays is becoming increasingly popular in Greece. For this modified version, scoring was dependent on the daily or weekly consumption and the values of 0, ½, or 1 were assigned. Food items were grouped in 14 categories. The MDS ranged from 0 (minimum adherence to MD pattern) to 14 (maximum adherence to MD pattern). In order to quantify the scoring system in our population and compare it with the tertiles achieved by the MDS score, population tertiles were again derived: 0–3.5 for low adherence, 4–4.5 for middle adherence, and 5–14 for high adherence. For each component of the MD scoring system, we matched the relevant answers of the FFQ we used. In the absence of an exact match for a food item, the most appropriate for comparison was chosen. For instance, avocado was replaced with olives, whereas for consumption of wine we scored 0, as we did not ask for wine consumption separately, but rather as a general question of alcohol intake.
## 2.4. Statistical Analysis
Comparison of the characteristics between GDM and non-GDM: *Continuous data* were checked for normality using the Shapiro–Wilk test and P–P plots. Mean (sd) was used to present those normally distributed and median (range) for those skewed. If normally distributed, the student t-test was utilized, and if skewed, the Mann Whitney test was used. Categorical data were presented as relative frequencies and chi-square test was used to assess distribution differences.
Food group comparison between GDM and non-GDM: Since these data were continuous variables, they were checked for normality using the Shapiro–Wilk test. Mean (sd) was used to present those normally distributed and median (range) for those skewed. If normally distributed, the student t-test was utilized, or else the Mann Whitney test was used.
Mediterranean score comparison between GDM and non-GDM: The Mediterranean score was separated into three categories using the population tertiles. These three categories were utilized together with additional characteristics (for computing adjusted OR), i.e., maternal age, BMI, smoking, gravidity, parity, and physical activity, in a multiple logistic regression model. The target binary variable of the model is the GDM outcome. From this model, adjusted odds ratios (aOR) and their $95\%$ confidence intervals (CI) were computed for the Mediterranean score categories.
Implementation: The programing language R was used for the implementation.
## 3. Results
A total of 743 pregnant women (age: 32.1 ± 4.85 years) were recruited, of which 112 ($15.1\%$) subsequently developed GDM. Maternal characteristics for the two groups are shown in Table 1. The mean maternal age (33.7 ± 4.9 vs. 31.9 ± 4.9 years, respectively, $$p \leq 0.0002$$), as well as the proportion of women aged >35 years old ($40.2\%$ vs. $25.7\%$, $$p \leq 0.003$$), were significantly higher in the GDM group. Women that smoked during pregnancy had a higher occurrence of GDM. The mean pre-pregnancy weight and BMI (25.8 ± 5.93 vs. 24.0 ± 4.55, $$p \leq 0.006$$) were higher in the GDM group. Additionally, a larger proportion of women with GDM were obese ($21.4\%$ vs. $10.6\%$, $$p \leq 0.003$$).
The food groups for each of the scores used were also compared (Table 2 and Table 3). We observed statistically significant differences for the “meat and derivatives” food group from the MDS index by Trichopoulou et al. ( $$p \leq 0.008$$) as shown in Table 2. When the modified version of the MDS index by Leighton et al. was used, a significant difference in the “fatty meat and processed meat” food group (Table 3) was observed, with consumption being higher in both cases in the GDM group. No other significant differences were found for the any of the remaining food groups in either score. These differences can be also seen in Figure 1A,B.
A score of 5–9 points using the MDS index is associated with $43\%$ lower likelihood of GDM (aOR: 0.57 [$95\%$ CI: 0.32, 0.9], $$p \leq 0.02$$) (Table 4). Using the modified version of MDS index, we did not observe statistically significant results for any level of adherence (Table 5). Additionally, the overall adherence for each group is shown in Figure 2A,B, where the differences in the adherence scores between the two groups are highlighted in red dotted ellipsoids.
The MD adherence adjusted analysis showed that women who achieved a higher MDS and were in the third tertile (score 5–9) had a $43\%$ lower likelihood of GDM compared to the first tertile (score 0–3, reference level) (aOR: 0.57 $95\%$ CI (0.36, 0.94), $$p \leq 0.02$$). Results of the analysis can be seen in Table 4. No significant effects were found with the modified MDS score when running the same model by tertile.
## 4. Discussions
To our knowledge, this is the first study that explored the pre-pregnancy MD adherence in relation to GDM occurrence among Greek pregnant women. The main findings were that: 1. high adherence to the original MD diet in the preconception period decreased the risk of GDM, irrespective of pre-pregnancy weight status and other known risk factors, whereas the modified MD had no effect and, 2. pre-pregnancy consumption of “meat and derivatives” and “fatty meat and processed meat” was associated with a higher risk of GDM, with both scoring systems.
Numerous dietary patterns have been associated with various health benefits across the world. The largest data documentation and research though, regard the dietary habits and lifestyle characteristics of populations in the Mediterranean regions [45]. Adherence to the MD has been associated with numerous health benefits for various medical conditions, such as inflammatory bowel disease (IBD) disease, non-alcoholic fatty liver disease (NAFLD), metabolic syndrome, cancer, and longevity [46,47,48,49]. Pregnancies complicated with GDM are associated with an increased risk for developing metabolic syndrome later in life [8]. A recent systematic review and meta-analysis in the non-pregnant population highlighted that adherence to the MD positively affects all parameters of the metabolic syndrome, although further research is needed to specify whether this effect is applicable among healthy and unhealthy individuals [50]. The protective effect of a MD dietary pattern on pregnancy outcomes has also been demonstrated [51].
High level of adherence to the MD before pregnancy was associated with lower incidents of GDM in this study. Previous studies report on the association of MD diet during gestation; a study conducted by Karamanos et al. included participants from 10 Mediterranean countries, including Greek participants. Individuals that had a higher Mediterranean Diet Index (MDI) score were associated with lower incidence of GDM, and moreover, controls with high MDI had a better degree of glucose tolerance [52]. A mother and child cohort, known as the Rhea study [53], which is the largest pregnant cohort in Southern Europe so far, aims to evaluate the effect of many different variables on maternal and childhood outcomes. In particular, the study collects data on nutritional aspects, obesity, neurodevelopment, and progression to asthma in children, as well as environmental and socioeconomic factors. Results of the study demonstrated that higher adherence to the MD during pregnancy was correlated, among other health benefits, with lower childhood adiposity. Moreover, environmental exposure of the mothers to organochlorine pesticides was associated with increased risk for GDM. More studies are needed to address the impact of the many possible causal factors for GDM occurrence, but dietary behavior and lifestyle is clearly underlined. Additionally, how pre-pregnancy behavioral factors are altered or not during the gestational period are areas that need further information, and are part of our ongoing cohort study. Our study collected data of the maternal characteristics and the nutritional preferences among pregnant individuals during the pre-conceptional and gestational period.
High consumption of “meat and derivatives” and “fatty and processed meat” prior to conception was associated with a higher incidence of GDM, as per our study findings. This comes in accordance with findings from other studies conducted in the pre-conception period [54,55]. A study by Sanchis et al. reported that high total meat intake, particularly red meat, was significantly associated with increased risk for GDM, while no statistical significance was identified for non-heme and total iron intake. Additionally, results from a meta-analysis reported an increased risk of GDM occurrence in individuals that consumed high levels of red and processed meat, saturated fat, and increased cholesterol intake either before or during pregnancy. Furthermore, a study conducted by Liang et al. studied the role of meat and dairy consumption a year prior to conception and also during pregnancy [56]. The study found statistical significance for GDM occurrence when the women had higher intake of total and animal protein in mid gestation. Moreover, high consumption of animal protein may impose a reduced glucose threshold for insulin secretion from the pancreatic β- cells, which will eventually lead to insulin resistance and may subsequently cause inability of the islet cells to produce enough amounts of insulin, leading to the pathogenesis of diabetes [57]. A recent systematic review reported that high consumption of saturated and trans-fat before conception and also during conception can significantly alter glucose homeostasis and pave the way for GDM development [58].
Considering the various effects that maternal pre-conception nutritional and total body fat status may impose on the glucose regulation, combined with the adding effect of the hormonal dysregulations that occur during pregnancy on the glucose homeostasis, the significance of preconception counseling on the nutritional habits of women of childbearing age should be adopted. There is abundant evidence on nutritional guideline recommendations for women during the gestational period. A recent comparative review concluded that most of these standards are in agreement, although some discrepancies still exist [59]. The period before conception should also be given attention, as many nutritional imbalances may exist not only during but also before conception as it is nowadays common of women of reproductive age to be in an over or under nutritional status and have nutritional deficits [60]. Consequently, to attain better outcomes for the pregnancy course, especially in individuals with risk factors for developing GDM, such as advanced maternal age and BMI status, obstetric history of previous GDM pregnancy, family history of GDM, or another situation that increases the risk for GDM incidence, an effective counseling approach, including nutritional behavior, should be followed in order to minimize the risk of developing GDM.
Regarding the strengths in our study, we used two scoring systems, one calculated in two separate ways, and we estimated the score by applying the traditional MDS index, as well as the Westernized version of it. The criteria for the diagnosis of GDM were unanimous, and all participants attended the same antenatal care clinic. We additionally used a culture specific semi-quantative FFQ tailored to fit the Greek dietary habits which was previously validated for use in pregnant women [40].
The study also has certain limitations. The main is the possible recall bias as women were asked to report their diet habits prior to conception. Second, for questions that we were not able to exactly match to a food group to calculate the MDS indices, we either chose a similar one, or none if the latter was not. This may have affected our results towards achieving a lower MD score. Moreover, further subgroup analyses by pre-pregnancy weight status were not performed due to the limited sample size for such analyses.
To conclude, in a Mediterranean population, higher adherence to the original MD appears to have a protective effect on the occurrence of GDM. Considering that MD is an affordable option to be adapted by low-, middle-, and high-income countries, the need for strategies towards a MD diet and recession from the Westernized dietary patterns is essential. Additionally, the benefits of adapting a MD diet pattern should also be considered by clinicians as a potential hazard reduction tool across women of reproductive age. More research is needed to analyze the impact of other lifestyle components related to the MD populations.
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|
---
title: Association between Polymorphisms of Hemochromatosis (HFE), Blood Lead (Pb)
Levels, and DNA Oxidative Damage in Battery Workers
authors:
- Willian Robert Gomes
- Paula Pícoli Devóz
- Bruno Alves Rocha
- Denise Grotto
- Juliana Mara Serpeloni
- Bruno Lemos Batista
- Alexandros G. Asimakopoulos
- Kurunthachalam Kannan
- Fernando Barbosa Jr.
- Gustavo Rafael Mazzaron Barcelos
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967888
doi: 10.3390/ijerph20043513
license: CC BY 4.0
---
# Association between Polymorphisms of Hemochromatosis (HFE), Blood Lead (Pb) Levels, and DNA Oxidative Damage in Battery Workers
## Abstract
Occupational exposure to lead (Pb) continues to be a serious public health concern and may pose an elevated risk of genetic oxidative damage. In Brazil, car battery manufacturing and recycling factories represent a great source of Pb contamination, and there are no guidelines on how to properly protect workers from exposure or to dispose the process wastes. Previous studies have shown that Pb body burden is associated with genetic polymorphisms, which consequently may influence the toxicity of the metal. The aim of this study was to assess the impact of Pb exposure on DNA oxidative damage, as well as the modulation of hemochromatosis (HFE) polymorphisms on Pb body burden, and the toxicity of Pb, through the analysis of 8-hydroxy-2′-deoxyguanosine (8-OHdG), in subjects occupationally exposed to the metal. Male Pb-exposed workers ($$n = 236$$) from car battery manufacturing and recycling factories in Brazil participated in the study. Blood and plasma lead levels (BLL and PLL, respectively) were determined by ICP-MS and urinary 8-OHdG levels were measured by LC-MS/MS, and genotyping of HFE SNPs (rs1799945, C → G; and 1800562, G → A) was performed by TaqMan assays. Our data showed that carriers of at least one variant allele for HFE rs1799945 (CG + GG) tended to have higher PLL than those with the non-variant genotype (β = 0.34; $$p \leq 0.043$$); further, PLL was significantly correlated with the levels of urinary 8-OHdG (β = 0.19; $$p \leq 0.0060$$), while workers that carry the variant genotype for HFE rs1800562 (A-allele) showed a prominent increase in 8-OHdG, as a function of PLL (β = 0.78; $$p \leq 0.046$$). Taken together, our data suggest that HFE polymorphisms may modulate the Pb body burden and, consequently, the oxidative DNA damage induced by the metal.
## 1. Introduction
Human exposure to lead (Pb) and its compounds occurs mainly in occupational settings, especially in industrial processes such as smelting, pottery, shipbuilding, Pb-based painting, Pb-containing pipes, car battery recycling, grids, firearms industry, pigments, printing, among others [1]. Some other sources, such as canned food, cosmetics, lead pipes used in water supply, and the use of certain herbal products, can also contribute to Pb exposure in humans [2]. McFarland et al. [ 3] showed that humans may also have underpredicted high-lead exposures owing to leaded paints and pipes, which tend to aggregate within communities with high rates of homes with lead service lines and lead paint in disrepair.
In Brazil, car battery manufacturing and recycling activities represent a major source of Pb contamination, and the country still lacks guidelines on the management of end-of-life Pb-acid batteries and has no law defining the collection and recycling of this type of waste [4]. The Brazilian National Institute of Metrology Standardization and Industrial Quality (INMETRO) included automotive batteries in a compulsory certification program as this represents a high risk to the environment and human health [5].
It is well-established that, following exposure, Pb interferes with enzymatic and non-enzymatic components of antioxidant defense and induces oxidative stress through several mechanisms (for review, see Lopes et al. [ 6] and Mitra et al. [ 7]). *The* generation of free radicals and ROS causes oxidative damage in lipids, proteins, and nucleic acids, culminating in cell injury and tissue dysfunction [8,9,10]. Among these, DNA oxidation is the major concern, as it may induce a variety of damages, including strand breaks and base modifications; a well-written overview of different modes of ROS-induced DNA damage has been published elsewhere [11,12].
Epidemiological data showed that genetic polymorphisms may modulate Pb body burden and, consequently, impact the toxicity of the metal [13,14]. Polymorphisms of the hemochromatosis (HFE) gene are known to cause a mild form of hereditary hemochromatosis, a disease related to a dysregulation of iron (Fe) uptake, increasing the levels of the metal in the body [15]. One hypothesis is that the HFE protein, which is responsible for regulating the absorption of Fe, is also related to the absorption of other essential and toxic metals, including Pb. In this context, variations in the gene encoding the HFE protein could also alter the Pb uptake, modulating the levels of the metal in the body [16]. Although earlier studies showed the impact of HFE polymorphisms on Pb body burden, no studies were carried out to assess the underlying effects of this polymorphism on Pb-induced toxicity.
Therefore, the present study aimed to assess the impact of HFE polymorphisms (rs1799945, C → G; and 1800562, G → A) on blood and plasma lead levels (BLL and PLL, respectively), as well their modulation on DNA oxidative damage induced by Pb, by monitoring of urinary 8-hydroxy-2′-deoxyguanosine (8-OHdG), in Pb-exposed workers from car battery manufacturing factories, in Brazil.
## 2.1. Study Population and Blood Collection
This is a cross-sectional study comprising 236 participants (men > 18 years of age) from automotive battery factories, in Paraná State, Brazil, recruited during June and July, 2015. Recruitment of participants was undertaken by a previous visit to the factories to explain the aim of the study. Written consent was given by all participants and this study has received approval for research ethics from Federal University of São Paulo.
For all participants, a questionnaire was administered to collect demographic variables such as age, dietary habits, medical history, consumption of alcoholic beverages, smoking, and occupational exposure. Participants who declared any clinically manifested diseases at the time of recruitment were excluded from the study. Moreover, all participants stated that they used personal protective equipment and followed all the company’s safety regulations, based on the guideline published by the Brazilian Ministry of Health (Health Care for Workers Exposed to Metallic Lead, 2006) [17].
Blood samples were taken on-site in the infirmary of the factories and collected in evacuated tubes (BD Vacutainer; Franklin Lakes, NJ, USA); plasma samples were obtained by centrifugation at 1000× g for 10 min. Urine samples were taken in 50 mL conical tubes (Falcon, Corning, NY, USA). Transportation of samples was carried out in dry ice to the laboratory. Samples were stored at −80 °C until further handling.
## 2.2. Blood Lead Levels (BLL) and Plasma Lead Levels (PLL) Determination
BLL and PLL were determined using an inductively coupled plasma mass spectrometer (ICP-MS; ELAN DRC II, Perkin Elmer, Norwalk, CT, USA), by following the method described in Batista et al. [ 18,19]. Samples were directly diluted (for BLL: 0.20 mL blood sample + 9.8 mL diluent; for PLL: 0.50 mL plasma sample + 9.5 mL diluent ($0.010\%$ m/v Triton X-100 and partially distilled HNO3 14 M $0.5\%$ v/v)) and injected in the ICP-MS. Standard calibration curve was prepared using matrix matching calibrant by adding 0.20 mL base blood or 0.50 mL base plasma in each calibration solution using the same diluent.
Precision and accuracy of BLL and PLL analyses were determined by analyzing certified reference material QMEQAS07B06 human blood from the National Institute of Public Health of Quebec (INSP, Wolfe, QC, Canada) and SE05-05 caprine serum from the Wadsworth Center—New York Department of Health (NYSDOH, Albany, NY, USA). For BLL, within-run and between-run precisions were 2.1 and $3.5\%$, respectively, and all obtained results were in agreement with the reference values (39 ± 2.6 µg dL−1). For PLL, within-run and between-run precisions were 3.9 and $4.7\%$, respectively, and all obtained results were in accordance with the reference values (6.8 ± 0.36 µg dL−1).
Results are expressed as µg dL−1.
## 2.3. Biochemical Parameters Related to the Redox Status
The catalase (CAT) activity was measured in peripheral blood as described by Aebi et al. [ 20]. This method is based on changes in absorbance at 240 nm due to the CAT-dependent decomposition of H2O2. The activity of the enzyme was related to hemoglobin (Hb) content (κ g Hg−1).
Total thiols (expressed as GSH) concentrations were determined in erythrocytes by addition of 5-5′-dithio-bis(2-nitrobenzoic acid) (DTNB) as described by Ellman et al. [ 21]. DTNB, a symmetric aryl disulfide, reacts with free thiols to form disulfide plus 2-nitro-5-thiobenzoic acid. The reaction product can be quantified by its absorbance at 412 nm. Results are expressed as μmol mL blood−1.
Glutathione peroxidase (GPX) activity was determined in blood spectrophotometrically. This method is based on the oxidation of NADPH, which can be measured as the decrease in absorbance at 340 nm [22]. Results are expressed in nmol NADPH min−1 g Hb−1.
A commercial kit (Hemoglobina Monotest, Inlab Diagnóstica, São Paulo, Brazil) was used to determine Hb in blood according to the manufacturer’s instructions.
## 2.4. Determination of Urinary Levels of 8-Hydroxy-2′-Deoxyguanosine
Analytical standard of 8-OHdG was purchased from Sigma-Aldrich (>$98\%$ purity; St. Louis, MO, USA) and the internal standard 15N5-8-OHdG was purchased from Cambridge Isotope Laboratories (Andover, MA, USA). Stock standard solutions were prepared in ultra-pure water, stored at low temperatures, and protected from light. Acetonitrile (HPLC grade) was purchased from JT Baker (Phillipsburg, NJ, USA) and acetic acid (HPLC grade) was purchased from Macron Fine Chemicals (Center Valley, PA, USA). High purity de-ionized water (resistivity 18.2 MΩ cm) used throughout the experiment was obtained using a Milli-Q water purification system (Barnstead International, Dubuque, IA, USA).
The urinary concentrations of 8-OHdG were measured using the method described previously by Rocha et al. [ 23]. In short, 100 μL of urine samples were spiked with 10 ng of labeled internal standard, 15N5-8-OHdG, diluted up to 0.50 mL with ultra-pure water, mixed and analyzed by high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS).
The HPLC-MS/MS analysis was performed with a Shimadzu Prominence Modular HPLC system (Shimadzu Corporation, Kyoto, Japan) interfaced with an API 3200™ electrospray triple quadrupole mass spectrometer (ESI-MS/MS; Applied Biosystems). The chromatographic analysis was carried out on a Zorbax SB-Aq column (150 mm × 2.1 mm i.d. and 3.5 μm particle size; Santa Clara, CA, USA) serially connected to a Javelin guard column (Betasil C18, 2.1 mm × 20 mm and 5 mm particle size; Thermo Electron Corp.) and acetonitrile (A): water (B), with $0.1\%$ of acetic acid (v/v) as mobile phase. The target compound was eluted by gradient elution at a flow rate of 300 μL min−1 starting at $80\%$ (v/v) B, held for 2.0 min, decreased to $25\%$ B within 2.0 min (4th min), held for 3 min (7th min), further decreased to $5\%$ B within 3 min (10th min), held for 7 min (17th min), and reverted to $80\%$ at the 17.5th min and held for 2.5 min, with a total run time of 20 min. The mass spectrometry was operated in negative ion mode. The electrospray ionization voltage was set at −4.5 kV. The curtain and collision gas (nitrogen) flow rates were set at 10 and 2 psi, respectively, and the source heater was set at 550 °C. The nebulizer gas (ion source gas 1) and the heater gas (ion source gas 2) were both set at 65 psi. The data acquisition was set at a scan speed of 80 ms and a resolving power of 0.70 FWHM. The injection volume was 10 µL. The following tandem mass spectrometry transition channels were used: 284.2 > 168 for 8-OHdG and 289 > 173 for the internal standard, 15N5-8-OHdG.
A twenty-point calibration curve at concentrations ranging 0.1–100 ng mL−1 was built for 8-OHdG. Isotope labeled internal standard (15N5-8-OHdG) was employed to compensate for possible matrix effects and analyte losses. The linearity of the calibration plots showed R2 values close to unity (>0.98). The limit of detection (LOD) was calculated as 3 times the signal-to-noise ratio and the limit of quantification (LOQ) was set 3.3 times higher than the LOD. The LOD and LOQ were 0.15 and 0.50 ng mL−1, respectively.
Urinary creatinine levels were determined by using the kit supplied by ByoSystems SA (Barcelona, Spain) on a clinical biochemistry analyzer (Mindray, model BS-200, Shenzhen, China), according to the manufacturer’s recommendations.
Results are expressed as µg of 8-OHdG per g creatinine (µg g creatinine−1).
## 2.5. Genotyping Assays
Genomic DNA (gDNA) was extracted from peripheral blood using the ReliaPrep Blood gDNA Miniprep System (Promega, Wisconsin, WI, USA) according to the manufacturer’s instructions. The quality of the DNA purification was verified by measuring the $\frac{260}{280}$ (samples were ≥1.8 and ≤1.9) and $\frac{260}{230}$ ratios (all samples > 2.0) (Nanodrop 2000, Invitrogen, Carlsbad, CA, USA). gDNA was quantified by the Qubit dsDNA BR Assay Kit (Invitrogen, California, CA, USA) in a Qubit 3.0 fluorimeter (Invitrogen, Carlsbad, CA, USA). All samples were stored at −20 °C until analyses.
HFE polymorphisms (rs1799945, C → G; and 1800562, G → A) were genotyped by TaqMan assays (Applied Biosystems, Carlsbad, CA, USA) according to the manufacturer’s instructions using an ABI 7500 Fast Real-Time PCR System thermocycler (Applied Biosystems, Foster City, CA, USA).
## 2.6. Data Interpretation
Age, duration of exposure, body mass index (BMI), BLL and PLL, 8-OHdG, CAT, GSH, and GPX were analyzed as continuous variables; alcohol consumption (yes or no), smoking (yes or no); and polymorphisms were classified as categorical variables. Participants who drank alcoholic beverages at least five times per week were considered alcohol users and those who smoke at least five cigarettes per day for the previous five years were classified as active smokers.
Hardy–*Weinberg equilibrium* (HWE) for polymorphisms was assessed by conventional chi-square test. Moreover, due to their low frequency in individuals with the homozygous variant genotype (<5 individuals), participants were classified as those with the non-variant genotype and carriers of at least one variant allele.
Kolmogorov–Smirnov’s tests were applied to verify the normality distribution of the continuous variables and those that presented skewed distribution were Box-Cox transformed as follows: exposure period (λ = 0.00), BLL (λ = 0.50), PLL (λ = 0.00); CAT (λ = 0.50); GPX (λ = 0.00), and 8-OHdG (λ = 0.50).
General multiple linear models were used to assess the impact of HFE polymorphisms on Pb body burden, adjusted for age, BMI, exposure duration, alcohol, and smoking. Since we have previously published that consumption of milk and dairy products (MDP) could modulate Pb body burden, we also included this variable in the model: participants were classified as low-MDP intake and high-MDP intake (for details, see Gomes et al. [ 24].
Furthermore, general multiple linear models were also applied to assess the impact of HFE polymorphisms on 8-OHdG, as function of BLL and PLL, adjusted for age, BMI, exposure period, alcohol, and smoking. Moreover, we have earlier reported that exposure to *Pb is* associated with alterations of biochemical parameters of the redox status, such as GSH and GPX, we also included these variables in the model [24,25].
All analyses were performed in SPSS Statistics 23 software (IBM, Armonk, NY, USA) and the results were considered significant when the p-value was ≤ 0.050.
## 3. Results
Sociodemographic characteristics, occupational Pb exposure status, BLL, PLL, redox status conditions, and urinary 8-OHdG concentrations are presented in Table 1.
Participants’ age ranged between 18 and 69 years (mean 38 ± 10 years) and the mean BMI was 27 ± 3.9 kg (m2) −1; $16\%$ of participants were active smokers, while $34\%$ declared alcohol consumption regularly. Mean BLL and PLL were 21 ± 12 and 0.60 ± 0.71 μg dL−1, respectively. The duration of Pb exposure among participants ranged from 1 month to 27 years. The measured activities of antioxidants enzymes CAT and GPX in blood were 124 ± 59.0 κ g Hb−1 min−1 and 6.5 ± 3.0 nM NADPH min−1 mL blood−1; GSH levels ranged from 0.080 to 1.0 µM mL blood−1. Mean concentrations of urinary 8-OHdG were 4.0 ± 2.4 µg g creatinine−1, with values reaching up to 24 µg g creatinine−1.
Table 1 depicts the genotype frequencies of HFE polymorphisms, as well as the variant allele frequencies; allele frequencies for both genotypes are in Hardy–Weinberg Equilibrium ($p \leq 0.050$).
Table 2 summarizes the impact of HFE polymorphisms on BLL and PLL, adjusted for age, BMI, exposure duration, smoking, alcohol, and MDP intake. A positive correlation between exposure period and BLL was found, i.e., the longer the duration of employment in the factories, the higher the BLL. However, the correlation between the exposure period and PLL did not reach statistical significance ($$p \leq 0.060$$). Concerning the relationship between HFE polymorphisms on BLL and PLL, the SNP of HFE rs1799945 influenced PLL; i.e., individuals who carry at least one variant allele (CG + GG) tended to have significantly higher PLL than those with the non-variant genotype, while no associations were found between the SNPs and BLL.
Table 3 presents the effect of HFE polymorphism on urinary 8-OHdG levels, as a function of BLL and PLL (models 1 and 2, respectively). A positive association between 8-OHdG and Pb biomarkers was found; however, statistical significance was reached only with PLL. Moreover, the HFE polymorphism rs1800562 modulated the levels of 8-OHdG, as a function of PLL; i.e., carriers of variant allele (GA) showed higher 8-OHdG concentrations than those with the non-variant genotype (GG). No associations were observed between biochemical parameters related to the redox status (CAT, GSH, and GPX) and 8-OHdG.
## 4. Discussion
The use of Pb in automotive batteries is still a cause for occupational exposure to Pb around the world. Contaminants encountered during the battery-recycling arise from battery components and these include Pb, As, and Cd, which can be released into the soil as solid waste or as wastewater during the separation of components in a water bath. In the battery recycling process, *Pb is* smelted and refined, which can release toxic vapor and particulate dust [26].
Several studies have reported high levels of BLL in workers from this type of industry; most of these studies were conducted in less developed countries. In our study, mean BLL and PLL were 21 ± 12 and 0.60 ± 0.71 µg/dL, respectively, which may be considered a moderate level of exposure, when compared to results reported in the literature. For instance, studies performed in India, Bangladesh, and Pakistan reported BLL levels of 30 ± 4.1 µg/dL, 65 ± 27 µg/dL, and 69 ± 37 µg/dL, respectively [27,28,29]. Nevertheless, adverse health effects may occur at the level of 10 µg/dL, in adults, according to the National Toxicology Program of the United States [30].
Exposure to metals such as Pb can induce oxidative stress through the generation of ROS. One of the targets of ROS is nucleic acids, and the determination of DNA oxidation, including urinary 8-OHdG levels, has been used as a tool in biomonitoring studies with humans exposed to inorganic and organic toxicants [31,32]. Moreover, epidemiological studies have shown that an increase in guanine hydroxylation is associated with a higher risk for cancer [10,33].
It is of great importance to identify a reliable effect biomarker related to toxic metal exposure that can be used for human biomonitoring studies, as it could provide evidence of early biological events that may predict adverse health outcomes [34]. For this reason, several biomarkers are currently applied to human biomonitoring studies exposed to toxic metals and they are related to DNA damage, antioxidant cell defense, and oxidative stress mechanisms, for example. DNA damage in Pb-exposed workers has been evaluated over the years through different methodologies such as chromosomal aberrations, micronucleus, and comet assays [30,34], and many of these works have demonstrated a positive correlation between occupational exposure and DNA damage; however, analysis of these cytogenetic endpoints is time-consuming, laborious, and needs meticulous techniques. The measurement of urinary 8-OHdG levels is a cost-effective approach, due to its stability in urine, the ease (non-invasive) collection of urine without special treatment or processing prior to storage, the requirement of small volumes, and the possibility of using urine samples from previous studies/biobanks [35].
PLL may better reflect the toxicologically labile fraction of circulatory Pb that is more freely available for exchange with target tissues than the metal in whole blood [36,37]. Studies have also reported an apparent severalfold variation in the relative partitioning of Pb between whole blood and plasma (or serum) for a given whole-blood Pb level. This may reflect inherent differences in the plasma Pb/whole blood Pb partitioning among individuals and/or methodologic challenges associated with the collection and analyses of samples [38]. Our results provided further support concerning these statements, since we observed an association between 8-OHdG and PLL, while this observation was not seen concerning 8-OHdG and BLL.
Few research groups investigated urinary 8-OHdG levels in individuals occupationally exposed to Pb. Pawlas et al. [ 39] showed that workers exposed to Pb (from a Pb and zinc (Zn) smelter and battery recycling plant) had significantly higher levels of 8-OHdG (41 ± 37 ng g creatinine−1; BLL 39 ± 10 µg dL−1; PLL 0.15 ± 0.066 µg dL−1) than the non-exposed group (25 ± 29 ng g creatinine−1; BLL 3.0 ± 2.9 µg dL−1; PLL 0.0080 ± 0.011 µg dL−1), in Poland. In contrast, Malekirad et al. [ 40] reported that workers exposed to the metal from a Zn and Pb mine, in Iran, and showed lower levels of blood 8-OHdG than its respective control group (8-OHdG 0.51 ± 0.049 ng mL blood−1; BLL 9.6 ± 3.2 µg dL−1 vs. 8-OHdG 0.54 ± 0.051 ng mL blood−1; BLL 5.1 ± 3.1 µg dL−1, respectively); however, it is important to highlight that BLLs found by Malekirad and coworkers [40] in the exposed group are much lower than those found in other biomonitoring studies, as stated above; moreover, the authors observed that several parameters, such as the activity of antioxidant enzymes superoxide dismutase (SOD) and glutathione reductase (GR), and total antioxidant capacity, were significantly higher in the exposed group, suggesting that compensatory effects may explain the lower blood 8-OHdG levels found in these workers.
Some studies did not show associations between Pb exposure and increased oxidative DNA damage. Neitzel et al. [ 41] assessed Thai workers exposed to toxic metals, such as Pb and Cd, from an e-waste recycling facility and did not observe a significant correlation between BLL and urine lead levels (ULL), and urinary 8-OHdG; it is important to highlight that the levels of Pb exposure were very low (BLL 3.4 ± 2.1 µg dL−1; ULL 7.5 ± 7.0 µg g creatinine−1) and, therefore, cellular antioxidant defense may be able to scavenge ROS production induced by the metal exposure. In another study, Szymańska-Chabowska et al. [ 42] assessed the impact of toxic metals, including Pb, in copper (Cu) smelters and found that workers with BLL > (median) 23 µg dL−1 showed higher levels of 8-OHdG in serum than the individuals with BLL < 23 µg dL−1, as well as the non-exposed groups, providing further support that at low levels of Pb exposure, cellular compensatory effects may counteract the oxidative damage induced by the metal.
The heterogeneity in techniques used to quantify urinary 8-OHdG makes it more difficult to compare data between studies, and chemical quantification methods are recommended as gold standard methods for biomonitoring studies [43]. Different studies indicated that urinary 8-OHdG levels may be affected by age [44], alcohol consumption [31,32], smoking [45], and BMI [46]. On the other hand, Dessie et al. [ 47] evaluating the association between exposure to heavy metals and oxidative DNA damage showed no correlation between urinary 8-OHdG levels and different demographic characteristics that normally show association such as educational status, alcohol consumption, sex, age, and body weight. Indeed, they observed interactions between different social factors and 8-OHdG, i.e., sex with age, sex with alcohol consumption, and alcohol consumption with education. Our results showed no significant associations with any of these variables, possibly because the chronic exposure to Pb predominates other lifestyle-related factors [48]. In addition, the rates of smoking and alcohol consumption were relatively low in this study, which may be a reason for the lack of significant associations, and further discussion about this issue may be speculative.
Pb-induced toxicity may be modulated by variations in uptake and elimination of the metal due to genetic variations in Pb metabolizing enzymes. In this study, we evaluated the impact of two polymorphisms in the HFE gene (rs179945 and rs1800562) on Pb biomarkers, as well as on 8-OHdG levels. Our findings showed that carriers of the variant G-allele for HFE rs1799945 (CG + GG) tended to have higher PLL than the individuals with the non-variant genotype (CC).
Previous studies showed that HFE polymorphisms are related to alterations in Pb body burden; however, data are still contradictory and appear to be related to the degree of metal exposure, as well as other intrinsic variations, which may include several gene–gene or gene–environment interactions. For example, Szymanska-Chabowska et al. [ 42] assessed the effect of HFE polymorphisms (rs179945 and rs1800562) on BLL, in Polish workers from a Cu smelter and refinery, and did not find statistically significant differences in BLL stratified by the genotypes (overall BLL 37 ± 9.0 µg dL−1); however, when the authors compared those individuals in the third quartile (BLL ≥ 44 µg dL−1), workers with the non-variant genotype (GG) showed lower BLL than the individuals with AA genotype (for HFE rs1800562). Similar results were reported in a study with 771 Chinese employees from a Pb smelter company that indicated that carriers of variant G-allele for HFE rs1799945 may be highly vulnerable to Pb toxicity [49]. In contrast, in a recent study of an Indian population of 164 lead-exposed subjects from a Pb alloy manufacturing and battery breaking and recycling facility [50], workers with the non-variant genotype (CC) for HFE rs1799945 were shown to be at risk of higher BLLs than those with the variant allele, i.e., CG (median BLL 57 µg dL−1 vs. 50 µg dL−1).
We also further assessed the effect of HFE polymorphisms on urinary 8-OHdG levels, as a function of BLL and PLL. Positive associations were found between Pb and 8-OHdG levels. Interestingly, we also observed that HFE rs1800562 polymorphism modulated the oxidative DNA damage induced by the metal; i.e., individuals with the GA genotype tended to have higher urinary 8-OHdG levels than those with the non-variant genotype (GG). Although no direct effects may be related to the HFE gene and oxidative DNA damage, it is important to highlight that several underlying interactions may be related to HFE and Pb body burden, which may impact the toxicity of the metal. One hypothesis for this finding is that high levels of Pb are related to the polymorphic alleles for the HFE gene; in this context, it is notable that since such HFE SNPs directly impact Pb concentrations in the body, one possible explanation for our findings is that high Pb concentrations are directly associated with increased oxidative stress, inducing damage to various macromolecules, such as lipids, proteins, and mostly DNA (for review see Nersesyan et al. [ 51] and Lopes et al. [ 6]); it is well known that 8-OHdG is one of the most abundant oxidized metabolites related to DNA-damage induced by oxidative stress [43].
It is well established that the adverse health effects induced by exposure to toxic compounds are also modulated by gene–environment interactions (GEI), which comprise the joint influences of genetic and environmental variables (such as sex, diet, health status, and exposure to chemicals) [52]; this approach of analysis presents some advantages since it is possible to draw scenarios where the genetic effects may increase the risk of toxicity or may be protective, as a function of the exposure. Moreover, it is known that genes may work in concert, and therefore, the effects of one gene can induce compensatory changes in others [53].
## 5. Conclusions
Our findings provide further support concerning the impact of HFE polymorphisms on Pb body burden; to the best of our knowledge, this is the first time that the underlying effects of genetic variations in the HFE gene on oxidative DNA damage induced by Pb exposure have been shown, allowing a better understanding of the molecular mechanisms related to adverse health effects induced by Pb.
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|
---
title: Beneficial and Impeding Factors for the Implementation of Health-Promoting
Lifestyle Interventions—A Gender-Specific Focus Group Study
authors:
- Felix G. Wittmann
- Andrea Zülke
- Adrian Schultz
- Mandy Claus
- Susanne Röhr
- Melanie Luppa
- Steffi G. Riedel-Heller
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9967898
doi: 10.3390/ijerph20043520
license: CC BY 4.0
---
# Beneficial and Impeding Factors for the Implementation of Health-Promoting Lifestyle Interventions—A Gender-Specific Focus Group Study
## Abstract
[1] Background: The prevalence of dementia increases and so does the number of interventions that address modifiable risk factors for dementia. Recent evidence suggests that there are gender differences in the prevalence of those lifestyle factors as well as in the effectiveness of interventions. This study aims to identify differences in factors that benefit or hinder the effectiveness of interventions since a target group’s perspective gets more relevant. [ 2] Methods: *Two focus* groups, a female ($$n = 11$$) and a male ($$n = 8$$) group, were interviewed, audio recorded and transcribed. Qualitative analyses were performed and main- and subcategories were identified. [ 3] Results: Main differences were observed including aspects of lifestyle changes (e.g., respective diet and importance of an active lifestyle) and gender-typical behavior and perception by relevant healthcare actors. [ 4] Conclusions: Identified differences might help to address and raise the efficiency of lifestyle interventions. Further, the importance of social aspects and retirement as an auspicious moment to start interventions were identified as relevant by study participants.
## 1. Introduction
Worldwide, the prevalence of people living with dementia is estimated at 55 million people [1]. The number is expected to triple up to 139 million in 2050 [1,2]. Available treatments are only able to improve cognitive function over a limited period of time and are not yet curative [3]. However, $40\%$ of the risk of dementia seems to be amenable and able to change by modification of risk and protective factors. Livingston and colleagues identified twelve such potentially modifiable risk factors. These are, among others, low education and obesity in midlife but also smoking, excessive alcohol consumption, physical inactivity or depression and social isolation [4]. This is why there is increasing interest in lifestyle interventions to modify these risk factors [5]. Furthermore, addressing these risk factors through interventions as a form of prevention is an essential part of dementia risk reduction defined by the World Health Organization (WHO) in their global action plan on the public health response to dementia [6].
The prevalence of dementia differs between genders [7,8] as well as risk factors. While there are non-modifiable risk factors as the genotype Apolipoprotein E, there is growing evidence of differences in modifiable risk factors for dementia in men and women [9]. Therefore, risk factors may differ in one or both the frequency or the strength of the effect, or are even restricted to just one sex [10]. A classic example is, as mentioned above, low education. Although it has the same effect on dementia risk for both men and women, it is historically more common in women [9] due to unequal opportunities for schooling in older cohorts. Other risk factors that enhance the risk for women are history of stroke, little physical activity and hopelessness in late life, while for men history of stroke and more severe insomnia in late life are of greater relevance [8].
Within the last few years, multi-domain lifestyle interventions have been investigated in over 40 countries. As the first randomized controlled trial (RCT) targeting cognitive function in older adults at increased risk for dementia, the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) reported positive intervention effects on global cognition, domain-specific cognitive function and further physical functioning [11]. Although the effects reported so far are rather small, there are efforts to apply a global network, the World-Wide Fingers network. It pursues the goal of optimizing the FINGER-approach and adjusting it to different regional, thus economic and cultural environments [12,13]. Additionally, growing evidence of secondary data analysis provides new knowledge about intervention-related factors and effectiveness, e.g., in several subgroups of respective trials [11].
A recently published review by Zülke and colleagues on the gender-specific effectiveness of lifestyle interventions on cognitive functions did not find significant effects of lifestyle interventions on global cognition in either male or female samples. Nevertheless, when stratifying by gender the included studies indicated a positive effect of lifestyle on cognitive functions only in women. However, there is a lack of studies for male participants or trials reporting gender-stratified results [14]. Reviewing physical activity interventions, Barha and colleagues reported higher benefits for women than men in executive processes and greater benefits of aerobic training than other exercises [15]. Finally, Sindi and colleagues did not report any significant differences between men and women for the FINGER-study. However, gender-specific analysis mentions the relevance of differences in vascular, lifestyle and psychosocial factors [8].
Evidence suggests that gender plays a crucial role in the prevalence and in modifiable risk factors in dementia. It might thus be relevant to further take gender and respective differences into account to increase the effectiveness of future lifestyle interventions. Previous studies show a slight advantage of interventions for women, while men are often underrepresented. In a paper about current developments, Röhr and colleagues filtered out first factors that might facilitate but also hinder intervention adherence [11]. The current state of research forms a stable and assertive basis for being able to align even more targeted and efficient lifestyle interventions in the future. However, to our knowledge, little is known about respective factors differing by gender. This study aims to contribute to this growing area of research by identifying factors that benefit or hinder the implementation of lifestyle interventions to modify risk factors for cognitive decline in older age as identified by older men and women, respectively. Focus group interviews separated by men and women might give information about how the uptake, the adherence and the effectiveness of interventions might be enhanced. Further, results might inform about previous problems, such as low participation in men, and might highlight the needs and requests of older people for worthwhile lifestyle changes.
## 2.1. Study Sample
Potential study participants were contacted using a pool of previous participants from other studies who had agreed to be contacted again. Participants were recruited between March and April 2022. Inclusion criteria were experiences in lifestyle changes and an age of 60 years and above. The change could either have already been experienced or be currently ongoing.
## 2.2. Study Design
Two gender-homogeneous focus groups were interviewed by a trained member of the research group. We used focus group interviews since they benefit from group dynamics and social interaction and therefore often provide deeper and richer data than individual interviews [16]. Furthermore, the focus should be on the perspective of the target groups, which is why group discussions were used. The study was conducted in accordance with the standards for reporting qualitative research recommendations (SRQR) [17].
The interviews with the focus groups both followed a semi-structured interview approach. First, questions about the importance and aspects of lifestyle changes were asked. Participants were then asked about bigger changes they already had implemented. Causes for these changes and appropriate handling were discussed. Then, the groups were asked about how they fared and which affect different circumstances had. Participants were finally asked about different factors that either facilitate or hinder appropriate changes. The focus was expanded to the differences between men and women respective of these factors.
The interviews were audio-recorded and in the next step transcribed by an external company.
Participants’ sociodemographic characteristics were assessed by a paper questionnaire. Six questions regarding gender, age, familiar situation, graduation, vocational training and employment status were surveyed.
## 2.3. Analysis
The transcripts were analyzed and revised by two researchers (F.W, A.S) independently according to Mayring and Fenzl [18]. Category formation followed both deductive (based on the interview guide) and inductive (based on the answers) approaches. After a first pre-encoding performed individually by each research assistant, categories were reviewed and aligned before they were recorded separately again. The final category system and respective example quotations were finally defined and coded in a last group discussion. Analysis was carried out using the software MaxQDA 2018 (VERBI Software, Berlin, Germany).
## 3.1. Sample Characteristics of the Focus Group Participants
We recruited 19 persons of which 8 were men and 11 were women between 60–80 years of age, with an average age of 66.3 ± 5.5 years. Participant characteristics are shown in Table 1.
## 3.2. Themes and Subthemes Identified
We identified six themes each including three to six subthemes. Table 2 shows the frequency of quotes per subcategory overall and separated by gender.
The six themes identified were aspects and triggers of lifestyle change, differences between men and women, resources and barriers as well as needs and requests. It can be seen from the data in Table 2 that women more often mentioned aspects of lifestyle change, differences, especially characteristic traits and barriers. Further, besides diseases, retirement was mentioned comparatively often but in both a negative and a positive way. The subcategories are elaborated including example quotations in Table 3.
## 3.2.1. Aspects of Lifestyle Change
Aspects of lifestyle change mentioned by the male and female focus group were quite equal in psychosocial factors and activity, whereby activity contained mostly sport and was also brought up as a remedy against pain: Statements about healthy diet were more common in the male group. The growing importance of a healthy diet was attributed to retirement age and diseases linked to aging.
Positive aspects of social contacts were highlighted in both the female and the male group. Especially family, but also acquaintances, were mentioned. Mutual help and understanding were seen as important as well as engaging oneself actively: Men further accentuated the common household and domestic peace and broached the reciprocal effect of health and social environment: An aspect mentioned only by women was an active lifestyle. Statements towards an active lifestyle contained an active way of life or self-determination, whereby being (still) able or allowed to work was considered an important factor with respective benefits: Additionally, quitting smoking came up as an aspect of a lifestyle change in the male group.
## 3.2.2. Triggers and Causes of Lifestyle Change
Triggers of recent lifestyle changes were categorised into diseases, psychosocial factors and retirement. While the extent of diseases mentioned as triggers was quite equal in general, men more often stressed diabetes as a specific disease: Statements about psychosocial factors were more often made by women than men. While women named grandchildren or the spouse as the source, men commonly named psychotherapy or group therapy as triggers of lifestyle changes.
Retirement was seen from both a positive and a negative perspective. Some women were happy about their husbands retiring because they felt it was a relief in everyday life. Men, however, mentioned the relief of being able to calm down when retiring. In addition, retirement was seen as a challenge, since both, but mainly women mentioned having fallen into an emotional chasm and having had the challenge to build up new daily structures.
## 3.2.3. Differences between Men and Women
The main category differences between men and women were subdivided into three subcategories: general differences, characteristics and behavioral differences. While women mostly stressed the different interests between men and women, they also mentioned the importance of mutual help: Also, traditional social gender roles were mentioned regarding differences: Men, however, in addition to differences, see type-related and psychological factors as important factors that transcend gender differences. Nevertheless, they also see the axis between emotional and rational orientation as clearly attributed: Supposedly typical character traits were mentioned more often by women than men. A common statement of the female group was that men are in general less emotional and open and do not seek external help when confronted with problems:
Regarding behavioral differences, the views within the women’s group were inconsistent. Regarding seeking advice or getting help, for example by seeing a practitioner, women said both that men hesitate more and need some time to finally get help from a doctor, or that they are more rigorous and get help from a medical professional directly: Men explicitly only talked about their wives when talking about women, and instead were quite in agreement about themselves being able to balance reasons better than their female partner:
## 3.2.4. Resources and Support
The first subcategory of resources was identified as social environment, which was addressed to a greater extent by women. For women, family and acquaintances were mentioned as positive resources for lifestyle changes. A point that came up several times was that in friendships and with acquaintances people sometimes come up with arguments that may not suit oneself but are nevertheless important to consider: Men more often mentioned their children and their spouse as social resources. Important factors here were social pressure: Another important factor was accolade: Besides the social environment, the healthcare system was mentioned as in some form supportive, but with different aspects highlighted in men and women. Men in general named their general practitioner as supportive, especially regarding information about preventive check-ups. Women stressed the beneficial effects of group therapy, self-help groups or group sessions on respective pain. However, also other ways of support from the health sector were mentioned:
The third subcategory of resources was psychosocial factors. Women named mainly positive attitude, self-acceptance and mutual understanding, while for men setting goals for themselves and reaching them was important.
Social factors were the last subcategory of resources. While this subcategory did not come up to a bigger extent in the group of women, men made more statements about it. *In* general, community and joint experiences were mentioned. An example is:
## 3.2.5. Barriers
Barriers to lifestyle changes were divided into four subcategories: social conditions, personal factors, healthcare system and infrastructure.
Social conditions were held as a broader subcategory and the discussions about problems regarding lifestyle changes and respective social conditions developed in different directions. Women in general mentioned missing centres of cultural and social life or specific places in the city to go to get help several times. Furthermore, financial aspects were stressed a lot: In the male group, the main problems addressed concerned societal life and the difficulty of getting along with alienation from the social or residential environment. These problems were linked to employment and persisted even after retirement.
Personal factors were addressed in both groups but to a lesser extent. Women mentioned less physical and mental strength, in part due to the loss of the partner as a turning point in life: Men mentioned demands from the environment but also on themselves as hindering: Problems regarding the healthcare system were mentioned in both groups with similar arguments and to a bigger extent by women. A mutual persuasion was that the healthcare system, insurances, but also and especially practitioners prioritize financial interests over patients. Women furthermore mentioned a lack of commitment, and the quality of their general practitioners was criticized: Infrastructure as a barrier was mentioned only in the group with female participants. Especially the urban-rural contrast turned out to be relevant. Two aspects, in particular, should be mentioned here. First, social aspects are seen negatively in the urban contexts, as cities are perceived as more anonymous:
Second, cities are seen as an advantage, and places that provide opportunities for social encounters are named here since they are only to be found in cities.
## 3.2.6. Needs and Requests
Needs and Requests were not mentioned to a big amount, but three subcategories could be identified: societal, healthcare and cultural aspects.
Statements that were mentioned within the societal subcategory are linked to aspects stressed out in the barriers category. Concrete places to go to get help are desired here as well as more social work from the community or the local authority: A more concrete example is mentioned the following: Statements on the healthcare system are also linked to barriers to lifestyle change. Little of this was mentioned, but it was coherent: more time and more information are desired from general practitioners.
Finally, cultural aspects came up in the female group. There are complaints about a lack of supply.
## 4. Discussion
Our study is the first to use a qualitative approach to examine factors that, separated by gender, impact the implementation and effectiveness of lifestyle changes in older age. In this way, we contribute findings to the current state of research, which should make it possible to carry out lifestyle interventions in a more targeted and efficient manner.
A very important aspect that was mentioned in several ways was the social environment. While it was mentioned in an equal amount as an aspect of lifestyle change in form of a supportive factor, women stressed social aspects to a greater extent as a resource. This ties in with Tomioka and colleagues who report more participation in social activities and an association with a lower decline in cognitive function only in women, not in men [20]. These results support evidence from previous research on the social environment and engagement as important aspects of aging [21,22,23], but especially, what we want to mention here, as an aspect of lifestyle changes. Enhancement of social activity was targeted only in a limited number of trials so far [14]. It can thus be suggested, that social aspects such as environment, activity and engagement could be crucial adjuncts in interventions to enforce a change in lifestyles as they are a key modifiable factor regarding cognitive performance [24]. Social activities are also often linked to other resources, e.g., combined with physical activity [25]. Similar arguments were also mentioned in our results by participants who linked social activities with different domains. These are, e.g., support, social pressure or last but not least social demands enforced by norms. In a quite new conceptual framework, Vernooij-Dassen and colleagues mention the factors of structure and function (e.g., exchanging support) and appraisal of the social environment as main aspects of social health in relation to dementia and also emphasize the relevance for interventions [26].
Some differences between men and women could further be observed regarding attitudes toward the healthcare system. First, different aspects were mentioned regarding the healthcare system as supportive or as seen as a resource. Men stressed the supportive behavior of their practitioners, for example, regarding information received about preventive medical check-ups. Women, however, did not mention their general practitioner as a resource. Instead, psychotherapy and group sessions (e.g., self-help group or group therapy for persons with chronic pain) were brought up in the female group. While problems regarding the healthcare system were quite equally mentioned, another difference could be made out by analyzing barriers that the participants named in the interviews. Both groups complained about the fact that, according to their experience and opinion, financial aspects play far too big a role in providing care and treating patients appropriately. Nevertheless, the female group came up with more barriers than men. They further mentioned a lack of support by the healthcare system, the feeling of not being taken seriously or the declining quality of practitioners. These results support an argument made by Mauvais-Jarvis and colleagues, that gender might matter in both patients and doctors behavior. According to Mauvais-Jarvis and colleagues, gender roles depict social and thus behavioral norms and may thereby influence the access to healthcare systems, help-seeking behavior and the use of healthcare systems [27]. Further, Sieverding and colleagues report gender stereotypes within the doctor–patient communication. An interesting example of the study is that women are more likely to get a psychological diagnosis, men a somatic diagnosis for the same symptoms [28].
When discussing differences in characteristics or behavior between men and women, both groups mostly agreed about men being more pragmatic and rational, dealing with problems by themselves, while women were seen as more affective, e.g., by trying to amplify efforts of positive emotions and being more open to getting help was an argument that was very strongly emphasized in both groups. This might be an addressable point for further interventions relevant to the point that men are often underrepresented in lifestyle interventions. Pagoto and colleagues discussed possible reasons for this in relation to obesity interventions. Possible reasons, the authors argue, include social norms about healthy lifestyles that are more common in women, for example, social pressure. Further, the different interest in seeking outside help is discussed. This is in line with our results, reporting women being more open to getting help. Therefore, they mentioned quite a large amount of positive aspects of group sessions or getting help from therapists, while men were being connected to self-efficacy and dealing on their own. Finally, Pagoto and colleagues report that different representations of men referred to the type of intervention. While the lowest representation of men was observed in group-based interventions, they were represented to a larger amount in self-guided interventions [29]. To raise male participation and further the effectiveness of interventions, gender as a social construct, instead of or in addition to gender only being seen as a biological marker, should be considered in future investigations towards lifestyle interventions. A way of doing so might be different types of interventions, based on different characteristics and behaviors [27].
Further differences could be recognized in aspects of lifestyle. A healthy diet was mentioned more often in the male group, which is contrary to a focus-group study by Schladitz and colleagues [23]. In addition, an active lifestyle was only mentioned in the female group as an aspect of lifestyle change. However, men emphasized that they were happy to be able to pursue their own activities, e.g., gardening, after retirement. This result is also contrary to the findings of Schladitz and colleagues who found men more focused on an active lifestyle or meaningful activities like intellectual activities, while women did not focus on an active lifestyle. Interestingly, in our findings, women mostly referred to their job as an active lifestyle. This highlights another difference in our results—the appraisal of retirement. While women mentioned positive aspects of employment, men talked overwhelmingly positive about their retirement (e.g., to calm down, having time for hobbies, being able to support their wives in domestic work and reported relaxation). Besides diseases, retirement was the trigger mentioned more frequently for a lifestyle change (cf. Table 2). This result reflects those of Motegi and colleagues. They report changes in lifestyle habits after retirement such as a reduction in drinking, an increase in walking and heavy exercises and sleep time [30]. This might be relevant for the timing of the lifestyle change and thus as a moment to implement interventions. In order to increase male participation, the starting point should be taken into consideration, as this was significantly mentioned in the male group.
Finally, a closer look needs to be taken at barriers that participants reported towards lifestyle changes. While aspects of the social and the healthcare system have already been discussed, infrastructure and cultural aspects stand out. Apart from an urban–rural gap, financial aspects are crucial in both; for people living in more rural environments, missing infrastructure makes it difficult to take advantage of offers that are usually only found in cities. The same applies to culture, such as visits to the theatre or social meeting places. Interestingly, these points were only mentioned by female participants. This fact might be explained by education and occupational history differences [14]. The observable gap between gender and socioeconomic status and resources is important and should thus be considered in lifestyle changes and lifestyle interventions since it might affect seizing health-beneficial offers (as far as not included in interventions).
Links between gender differences and lifestyle changes, respective to the implementation and effectiveness of lifestyle interventions need to be examined more closely. Clinical practice nevertheless should regard gender roles for example by implementing different types of interventions due to differences in characteristic traits and behavior or a gap between gender and socioeconomic status and resources.
This study made use of qualitative data. Therefore, we obtained valuable insights into the experiences of older people regarding lifestyle changes. Thanks to the qualitative approach, we were further able to identify factors influencing the successful implementation of lifestyle changes in advance. Nevertheless, this study has several limitations. Since the interviews were held in German, the results are only partly representative due to the non-representation of migrant or minority groups. Further, it can be assumed that the participation is based on an existing interest of the participants in the topic. The male participants were already retired, while some of the female participants were still employed. This is partly reflected in statements about retirement. Although the sample is not homogenous, sample characteristics are still comparable to those of already existing interventions.
## 5. Conclusions
This study set out to analyze factors influencing the implementation of lifestyle changes as perceived by older men and women, respectively. The results of this research show that there are gender differences in both beneficial and hindering factors. Differences were observed in aspects of lifestyle changes, with diet stressed by men and an active lifestyle in general by women. An important difference can be reported referred to the perception of the healthcare system, partly due to traditional gender roles and accompanying behavior and perception. This could be of relevance for addressing and interacting with people relevant to lifestyle interventions. Social aspects as important factors were mentioned as well as aspects of lifestyle change in form of motivation and also as resources towards changes. Since social aspects have been addressed in a far too little manner in recent trials, but are seen as very efficient and important, they should be focused on more strongly. Finally, since retirement was seen as an important trigger for changes and also as a chance for new beginnings, this might be a very fertile moment to implement lifestyle interventions. This new understanding should help to improve the involvement of older people in lifestyle interventions as well as to improve the effectiveness of future interventions.
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|
---
title: Impact of Prenatal Exposure to Maternal Diabetes and High-Fat Diet on Postnatal
Myocardial Ketone Body Metabolism in Rats
authors:
- Prathapan Ayyappan
- Tricia D. Larsen
- Tyler C. T. Gandy
- Eli J. Louwagie
- Michelle L. Baack
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967912
doi: 10.3390/ijms24043684
license: CC BY 4.0
---
# Impact of Prenatal Exposure to Maternal Diabetes and High-Fat Diet on Postnatal Myocardial Ketone Body Metabolism in Rats
## Abstract
Infants exposed to diabetic pregnancy are at higher risk of cardiomyopathy at birth and early onset cardiovascular disease (CVD) as adults. Using a rat model, we showed how fetal exposure to maternal diabetes causes cardiac disease through fuel-mediated mitochondrial dysfunction, and that a maternal high-fat diet (HFD) exaggerates the risk. Diabetic pregnancy increases circulating maternal ketones which can have a cardioprotective effect, but whether diabetes-mediated complex I dysfunction impairs myocardial metabolism of ketones postnatally remains unknown. The objective of this study was to determine whether neonatal rat cardiomyocytes (NRCM) from diabetes- and HFD-exposed offspring oxidize ketones as an alternative fuel source. To test our hypothesis, we developed a novel ketone stress test (KST) using extracellular flux analyses to compare real-time ß-hydroxybutyrate (βHOB) metabolism in NRCM. We also compared myocardial expression of genes responsible for ketone and lipid metabolism. NRCM had a dose-dependent increase in respiration with increasing concentrations of βHOB, demonstrating that both control and combination exposed NRCM can metabolize ketones postnatally. Ketone treatment also enhanced the glycolytic capacity of combination exposed NRCM with a dose-dependent increase in the glucose-mediated proton efflux rate (PER) from CO2 (aerobic glycolysis) alongside a decreased reliance on PER from lactate (anaerobic glycolysis). Expression of genes responsible for ketone body metabolism was higher in combination exposed males. Findings demonstrate that myocardial ketone body metabolism is preserved and improves fuel flexibility in NRCM from diabetes- and HFD-exposed offspring, which suggests that ketones might serve a protective role in neonatal cardiomyopathy due to maternal diabetes.
## 1. Introduction
Diabetic pregnancy, especially along with a maternal high-fat diet (HFD), exposes the developing fetus to excess circulating metabolic fuels including glucose, fatty acids and ketones, which can ultimately alter metabolism and growth during critical windows of development, resulting in both short- and long-term consequences for infants [1,2,3]. Specifically, infants exposed to maternal diabetes or maternal obesity are at higher risk of heart disease at birth and early morbidity from cardiovascular disease (CVD) as adults [4,5,6,7,8]. We created a rat model to understand mechanisms of pathogenesis and showed that late-gestation diabetes, especially alongside a maternal HFD, incites mitochondrial dysfunction, impaired cardiomyocyte bioenergetics, cardiac hypertrophy, and diastolic and systolic dysfunction in newborn offspring [9,10]. Specifically, we found that maternal diabetes and HFD alters mitochondrial number, dynamics, and ultrastructure to cause these cardiometabolic consequences [10,11,12]. Importantly, maternal HFD exacerbated cardiomyopathy and perinatal mortality in offspring born to diabetic mothers (ODM) through exaggerated maternal hyperlipidemia and offspring hyperinsulinemia, myocardial lipid droplet accumulation, and oxidative stress [10,13]. Like in humans, cardiac dysfunction in our model initially improves after birth, but reappears with changing metabolic demands in an age- and sex-specific manner, likely due to programmed complex I dysfunction followed by exaggerated mitochondrial biogenesis, oxidative stress, and impaired cell survival following metabolic stress [13,14]. Given our findings alongside emerging evidence regarding the importance of ketone body metabolism in the adult failing heart [15,16], it is important to know whether developing cardiomyocytes exposed to fetal overnutrition have impaired ketone metabolism.
Ketone bodies, including acetoacetate, acetone, and β-hydroxybutyrate (βHOB), are produced when energetic demands cannot be met by the metabolism of more readily available glucose and fatty acids. Ketone production increases moderately during physiologic conditions such as fasting, prolonged exercise, ketogenic diet, and pregnancy. Normally, circulating levels of ketones including βHOB, which accounts for $70\%$ of the total ketones, are <0.5 mM, but hyperketonemia occurs when levels are >1.0 mM and ketoacidosis occurs when levels are over >3.0 mM [15]. Pregnancy increases ketone body production, and this is exaggerated in diabetic pregnancy [15]. Although oxidation of ketone bodies plays a significant role in energy metabolism during multiple physiological states including the neonatal period [17], in utero exposure to excess circulating fuels during diabetic pregnancy incites myocardial insulin resistance, which limits fuel flexibility and could impair ketone utilization in ODM as well.
Alterations in myocardial substrate utilization and energy metabolism is a well-known contributor to the pathogenesis of adult heart disease, especially in subjects with diabetes and obesity [18,19]. Impaired insulin signaling and increased lipolysis in diabetes leads to increased myocardial fatty acid oxidation (FAO), oxidative stress, and eventually left ventricular dysfunction. This can happen outside of other vascular risks, which is a hallmark of diabetic cardiomyopathy [20]. Under pathological conditions, the failing heart relies on ketone bodies as a source of energy [16,21]. However, Brahma, et al. recently demonstrated that increased glucose availability in diabetes attenuates myocardial ketone body utilization by suppressing cardiac ketolytic utility [22]. Our previous studies demonstrate that late-gestation diabetes and HFD not only exposes the developing fetus to maternal hyperglycemia and hyperlipidemia, but also to hyperketonemia; exposed newborns exhibit myocardial insulin resistance that is similar to what is found in adult diabetic cardiomyopathy, with a metabolic switch from glycolysis to gluconeogenesis [23] and impaired glycolytic and fatty acid oxidation capacity that is in part due to complex I dysfunction [9,13]. Importantly, complex I is also critical for ketone body metabolism. Given these findings, it is important to understand the effects of prenatal exposure to diabetes and hyperlipidemia on myocardial ketone body metabolism.
The objective of this study was to determine whether neonatal rat cardiomyocytes (NRCM) exposed to the combination of maternal diabetes and HFD in utero can oxidize ketones as an alternative fuel source. To test this, we developed a ketone stress test (KST) using extracellular flux analyses that measures real-time βHOB metabolism in primary isolated NRCM. We also measured the expression of various genes responsible for ketone body metabolism and FAO in normal and exposed neonatal hearts.
## 2.1.1. Maximal and Spare Respiratory Capacity Increase Directly with Increasing Concentrations of Ketone
Respiratory capacities were measured in the presence of increasing concentrations of βHOB to determine whether control and diabetes + HFD (combination) exposed NRCM increase respiration in a dose-dependent manner. Neither basal respiration (Figure 1A) nor non-mitochondrial respiration (Figure S1A) in quiescent NRCM were significantly different between groups. In the presence of UK5099, a pyruvate inhibitor used to encourage ketone flux, NRCM were given 0 mM, 1.5 mM, or 4.5 mM βHOB then ATP production was uncoupled with FCCP to drive maximal respiration. The effects of UK5099 alone and with βHOB are detailed in Supplementary Table S5. Overall, in quiescent NRCM, OCR did not change when UK5099 was used to inhibit the mitochondrial pyruvate carrier. Ketone oxidation, defined as the ability of quiescent NRCM to utilize ketones without respiratory stimulation, was estimated as the net change in OCR from baseline to the addition of pyruvate inhibitor (UK5099) and βHOB before the addition of FCCP. While there was very little increase in OCR from the baseline, both control and combination exposed NRCM trended towards a dose-dependent increase in OCR with an increasing concentration of ketones, as shown in Figure 1B. Maximal respiration was measured after stimulating NRCM with FCCP, and spare respiratory capacity was measured as the difference between maximal and basal OCR. Control and combination exposed NRCM both had a significant dose-dependent increase in maximal respiration and spare respiratory capacity with increasing concentrations of βHOB (Figure 1C,D). Findings demonstrate that ketones can be a fuel source for NRCM, even those exposed to maternal diabetes + HFD.
## 2.1.2. The Presence of Ketones Improves Glycolysis in Diabetes + HFD-Exposed NRCM
To find out whether ketones competitively inhibit or promote glycolytic rates, we also analyzed ECAR in quiescent NRCM at the baseline, after UK5099 with or without βHOB (ketone-mediated ECAR), FCCP (maximal ECAR), glucose (glucose-mediated ECAR), and antimycin + rotenone (anaerobic ECAR). Although ECAR is considered the best estimate for glycolysis, the data should be interpreted with the knowledge that extracellular acidification depends on contributions from both lactate (anaerobic) and CO2 (aerobic). In this study, combination exposed NRCM tended to have a higher baseline ECAR than controls ($$p \leq 0.136$$ by t-test). The effects of UK5099 alone and with βHOB are detailed in Supplementary Table S6. Although UK5099, which blocks the mitochondrial pyruvate carrier, is expected to shift bioenergetics towards anaerobic glycolysis, ECAR in NRCM was not significantly different following UK5099, regardless of ketone administration. As demonstrated in a representative output graph in Figure 2, ECAR peaked after injection of FCCP, a respiratory uncoupler. This finding substantiates previous experiments, which showed that FCCP stimulates maximal ECAR in primary cardiomyocytes. This is in contrast to other cell types, which typically reach maximal ECAR in response to oligomycin, an ATP synthase inhibitor [9,13,14]. We also injected glucose after FCCP to assure that the substrate was present for glycolysis; we considered this response to be glucose mediated ECAR. Although we found no significant differences in ketone-mediated or maximal ECAR, exposure to ketones significantly increased both glucose-mediated ECAR and anaerobic ECAR in combination exposed NRCM, but not in healthy controls (Figure 3A–D). Overall, diabetes + HFD-exposed males had the greatest ability to respond to ketones, as detailed below (Supplementary Tables S7 and S8).
## 2.1.3. Ketones Improve Proton Efflux Rate (PER) in Diabetes + HFD-Exposed NRCM
To further assess the contribution of lactate (anaerobic) and CO2 (aerobic) flux to ECAR, we analyzed proton efflux rates (PER), which is the number of protons exported from cells over time. PER serves as a valuable tool for understanding glycolysis and fuel flexibility under various conditions. Total PER at baseline (Figure S1B), after βHOB, FCCP, and rotenone/antimycin A were not statistically different between groups; however, ketones tended to increase the maximal and glucose-mediated PER ($$p \leq 0.08$$ by two-way ANOVA) especially in combination exposed NRCM given 4.5 mM βHOB (Figure 4A–D). Interestingly, when the total PER was delineated by contribution, there was a dose-dependent increase in maximal PER from CO2 (aerobic respiration) alongside a dose-dependent decline in maximal PER from lactate (anaerobic glycolysis) with increasing concentrations of βHOB, and this increase was most robust in combination exposed NRCM (Figure 5A,B). Interestingly, when glucose was given as a substrate, combination exposed NRCM treated with ketones had a dose-dependent increase in glucose-mediated PER from CO2 (aerobic respiration), but no corresponding decline in PER from lactate (anaerobic glycolysis), which suggests that ketones enhance the ability to metabolize glucose (Figure 5C,D). Indeed, combination exposed NRCM treated with 4.5 mM had significantly higher glucose-mediated PER from CO2 than controls ($$p \leq 0.0002$$) and combination exposed NRCM that were not given ketones ($p \leq 0.0001$ by one-way ANOVA). The net effect of ketones on aerobic and anaerobic capacity in control and combination exposed NRCM is further illustrated in Figure 6A–C, where graphs show a rising ratio of glucose-mediated PER from CO2/lactate in the presence of ketones. Overall, our KST shows that combination exposed NRCM have improved maximal and glucose-mediated aerobic flux in the presence of ketones.
## 2.1.4. Ketones may Enhance Fuel Flexibility More Robustly in Male NRCM
Although the KST was not originally designed to examine sex-specific differences, sex is a known biological variable in developmental origins of health and disease (DOHaD) and so post-hoc analyses were done. Sex-specific comparisons of NRCM bioenergetics are detailed in Supplementary Tables S7 and S8. When analyzing males and females separately, there were no significant group differences in respiration. However, combination exposed male NRCM treated with 4.5 mM of βHOB had a two-fold higher glucose-mediated OCR compared to those not given βHOB, which trended higher even at low numbers ($$p \leq 0.088$$, $$n = 5$$–6/group). This ketone-mediated increase in respiration is likely the result of both ketone oxidation and improved aerobic glycolysis because high dose ketones also led to a more than two-fold increase in glucose-mediated ECAR, which did reach statistical significance ($$p \leq 0.049$$) by one-way ANOVA (Supplementary Table S7). Combination exposed female NRCM also tended to increase glucose-mediated OCR with 4.5 mM βHOB treatment, but less robustly. Anaerobic ECAR also increased significantly with 4.5 mM of βHOB in combination exposed female NRCMs (Supplementary Table S7). When comparing male vs. female KST results, normal male NRCM had lower anaerobic ECAR compared to females (Table S8), but maternal diabetes + HFD increased anaerobic glycolysis in males, but lowered it in females; therefore, there were no sex-related differences in the combination exposed group. Overall, findings suggest that combination exposed males may have a greater bioenergetic response to ketones as detailed in Supplementary Tables S7 and S8.
## 2.2. Maternal Diabetes + HFD Dysregulates Genes Involved in Myocardial Ketone Body Metabolism in a Sex-Divergent Manner
To determine the effects of maternal diabetes + HFD on levels of enzymes needed for ketone body metabolism, we examined the gene expression of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (Hmgcs2) and β-hydroxy butyrate dehydrogenase (Bdh1) in neonatal myocardium (Figure 7A,B). HMGCS2, the mitochondrial protein encoded by the gene Hmgcs2, is involved in the synthesis of ketone bodies [22]. Interestingly, we found sex-divergent differences in Hmgcs2 expression following maternal diabetes + HFD exposure. Compared to their control counter parts, combination exposed females had significantly lower myocardial expression of Hmgcs2 ($$p \leq 0.030$$), while males had significantly higher expression ($$p \leq 0.015$$). BDH1, encoded by the gene Bdh1, is an important enzyme responsible for the catabolism of βHOB into acetyl-CoA [22]. Again, stratification by sex revealed significantly higher Bdh1 expression in the male offspring exposed to maternal diabetes + HFD compared to their healthy male counterparts ($$p \leq 0.041$$), while Bdh1 expression in the female offspring was not different between groups (>0.999). Overall, sex-related differences in Hmgcs2 and Bdh1 expression are found only in diabetes + HFD-exposed myocardium, but not in controls (Table S9). Expression differences may explain why NRCM from combination exposed males had the greatest bioenergetic response to ketones.
## 2.3. Maternal Diabetes + HFD Increases Pparg and Pgc1a Expression in Newborn Offspring Hearts
Peroxisome proliferator-activated receptor γ (PPARG) and its coactivator-1 (PGC-1a) are transcriptional regulators of multiple genes that mediate mitochondrial biogenesis, fatty acid (FA) transport, FA utilization, and oxidative stress [24,25]. We found that the Pgc1a expression was significantly higher in combination exposed neonatal hearts (p ≤ 0.0001) compared to healthy controls (Figure 8A). Stratification by sex demonstrated an increased expression of Pgc1a in both the combination exposed male ($$p \leq 0.002$$) and female ($$p \leq 0.008$$) offspring.
Peroxisome proliferator-activator receptors (PPARs) are nuclear receptors that are subject to transcriptional coactivation by Pgc1a to play a crucial role in energy homeostasis and metabolism [26]. Among different subtypes, Pparg in the heart is activated by HFD, which reportedly causes lipotoxicity and myocardial dysfunction, but also activates ketogenic enzymes [27]. We found that the hearts of neonates exposed to maternal diabetes + HFD had significantly higher expression of Pparg compared to healthy controls ($$p \leq 0.006$$) (Figure 8B). Stratifying by sex revealed that combination exposed male hearts had a more robust increase ($$p \leq 0.041$$) in Pparg than females ($$p \leq 0.121$$) compared to their respective controls.
## 2.4. Diabetes + HFD Increases Expression of Cpt1a in the Neonatal Heart
The enzyme carnitine palmitoyl transferase 1 (CPT1) facilitates the transport of long-chain fatty acids from the cytoplasm to the mitochondria for β-oxidation [28]. Cpt1a is the predominant isoform of CPT1 in the heart at birth [29]. In our study, myocardial Cpt1a expression was higher in offspring exposed to maternal diabetes + HFD ($$p \leq 0.041$$) compared to controls (Figure 9). Interestingly, this was primarily due to higher expression in males ($$p \leq 0.026$$), whereas females did not have significant differences related to in utero exposure ($$p \leq 0.731$$).
## 3. Discussion
The heart is well-known for its metabolic flexibility. Indeed, the ability to switch the utilization of one substrate over the other under physiological conditions is key to meeting the high energetic demands for continuous contractile function, despite variable states of supply and demand [30,31]. The fetal heart tends towards anaerobic glycolytic metabolism due to the in utero physiology with relative hypoxia, lower cardiac demand, and continuous fuel supply from maternal circulation [32]. At birth, the neonate is exposed to an oxidative burst as it takes its first breaths. Afterload and cardiac output increase dramatically and the continuous fuel supply is interrupted by clamping the umbilical cord. These normal physiological changes incite a shift in myocardial metabolism towards oxidative phosphorylation, which requires postnatal mitochondrial biogenesis and reticulum networking [33]. Pathological conditions can disrupt this normal transition at birth. It is well known that fetal exposure to maternal diabetes increases the risk of ventricular hypertrophy and cardiomyopathy at birth, followed by a period of improvement, then a risk of early CVD as an adult [4,6]. Our rat model exposes the developing fetus to excess circulating fuels (glucose, fatty acids, and ketones), spurring fetal hyperinsulinemia, impaired myocardial metabolism, lipid accumulation, diastolic and systolic dysfunction, and increasing perinatal mortality through lipotoxic and mitochondria-mediated mechanisms [9,12,13,23]. Specifically, glucolipotoxicity impairs oxidation of complex I fuels in NRCMs followed by exaggerated mitochondrial biogenesis, oxidative stress, and faster cell death to cause biphasic cardiac disease, just like in humans [13].
The heart requires fuel flexibility to maintain contractile function, so it metabolizes many substrates. The heart is considered one of the highest ketone-utilizing tissues. Myocardial ketone metabolism is especially critical when there is decreased availability of other substrates [17], as found in the diabetes-exposed and insulin-resistant heart, which has impaired glucose uptake and reduced metabolic flexibility [34]. Ketones produce ATP more efficiently than glucose or fatty acid and recent studies suggest that the failing heart benefits from ketone bodies as an energy source [16,21]. βHOB, acetoacetate, and acetone are the three primary ketones in circulation, whereas βHOB is found in the highest levels [15,35]. Ketone bodies are products of fatty acid oxidation. They are synthesized via ketogenesis, then utilized within the tissues via the ketolysis pathway. Utilization of ketones under normal physiological conditions is low. However, in adult diabetic cardiomyopathy, utilization of ketones improves the prognosis of heart failure while impaired ketone utilization worsens the prognosis [31]. Given the fact that maternal diabetes + HFD cause neonatal cardiomyopathy that is similar to adult diabetic cardiomyopathy, it is important to know whether complex I dysfunction found in the diabetes-exposed neonatal heart impairs ketone body metabolism or whether ketones, which are higher in circulation during diabetic pregnancy, can be utilized by the offspring’s developing heart, especially postnatally when the continuous maternal–fetal glucose supply is interrupted by birth.
The present study used a novel KST or modified extracellular flux analyses to measure real-time βHOB metabolism in NRCM exposed to maternal diabetes and HFD. To our knowledge, this is the first study that reports the ability of the neonatal heart exposed to maternal diabetes and HFD to metabolize ketone bodies. The key finding of the study is that ketones increase respiratory capacity in a dose-dependent manner, both in controls and combination exposed NRCM. This demonstrates that ketones can serve as an alternative fuel source for the neonatal heart, even after diabetes exposure. We also showed that combination exposed NRCM, but not controls, had a ketone-dependent increase in glucose-mediated PER from CO2 (aerobic glycolysis), and there was less reliance on anaerobic glycolysis during metabolic stress with FCCP. This suggests that despite previously reported complex I dysfunction [13], NRCM exposed to maternal diabetes and HFD have an enhanced ability oxidize ketones compared to controls.
We also found that the expression of genes responsible for ketone body metabolism increase robustly in male offspring. This is of particular interest because males are notoriously at greater risk for cardiac consequences following in utero exposure to maternal diabetes + HFD [10,12,13,23]. While our current study was not specifically powered to determine differences in each sex, we feel that it is important to show the trends. Sex differences could be due to multiple factors such as hormonal influences, sex-regulated placental fuel transport, or epigenetic and mitochondrial variability [36,37,38,39,40]. Our previous studies consistently show a sex-specific difference in the exposure-related mitochondrial response, with females being relatively cardioprotected through better mitochondrial quality control while males had faster mitochondria-mediated cell death under metabolic stress [10,12,13]. The balance between mitophagy and mitochondrial biogenesis is influenced by Pparg and its coactivator Pgc1a, which were also upregulated in combination exposed neonatal hearts. Pparg is activated by free fatty acids, which trigger the increased translation of proteins needed for fatty acid uptake, formation of triglycerides, and their storage in lipid droplets [41]. While this may be a normal physiologic response in myocardium, excess fuel exposure over an extended period of time can lead to detrimental effects. Others have reported that HFD induces myocardial Pparg and fatty acid oxidation, leading to an increased reliance on FA metabolism, ketogenesis, reduced myocardial efficiency, and increased oxygen consumption resulting in lipotoxicity-mediated heart failure [27,42,43]. As a coactivator of Pparg, Pgc1a is involved in many overlapping cellular pathways, especially in mitochondrial biogenesis [44], which can exacerbate oxidative stress and lipotoxicity.
Sex steroid hormones could be one of the reasons for the observed sex-specific differences in Pparg mRNA upregulation in combination exposed offspring. It was previously shown that the administration of estradiol to ovariectomized mice exhibits a reduced level of Pparg mRNA expression in the adipose tissue [45]. Estrogen receptors can inhibit ligand-induced activation of Pparg, and the induction of estrogen receptor β (Erb) is stronger in the hearts of females than in males [46,47]. It is interesting to note that the Erb-selective ligands have a Pgc1a-dependant inhibitory effect on Pparg activity [46]. Our results are in line with these reports and also with another study where Pparg activation was directly associated -with upregulation of Hmgcs2 in male animals [27]. While increased expression of Hmgcs2 and Bdh1 is likely a compensatory and adaptive mechanism, this interesting, sex-specific effect may offer hope for the therapeutic response to ketones in males that are more likely affected. Here, we also show a significant increase of myocardial Cpt1a expression in combination exposed offspring, which may further exaggerate lipotoxicity. Others demonstrated that diabetes can increase the gene expression of Cpt1a in the heart [48]. Expression of Cpt1a in the heart is also stimulated by Pgc1a [49]. Interestingly, all of these genes play an important role in myocardial development and metabolic flexibility that is important to life-long cardiac health.
While our findings suggest that ketones may be beneficial for insulin-resistant neonatal hearts, others have reported detrimental effects of ketones on the developing heart. Poorly controlled Type 1 diabetes is a well-known cause of elevated ketones that is linked to adverse pregnancy outcomes including congenital anomalies [15]. We contend that it is important to consider whether these consequences are related to alterations in the overall diabetic milieu or to ketones alone. High ketones during pregnancy usually represent more extreme undernutrition or diabetic states, which are associated with exaggerated perturbations in many fuels, not just ketones. It is also important to consider the timing of the ketone exposure in the context of offspring development. We have previously shown that exposure to hyperglycemia during early embryogenesis is associated with teratogenesis, even in the absence of maternal diabetes or ketosis [50]. Others have demonstrated that alterations in morphogenesis can be produced by excess exposure to B-hydroxybutyrate as well [15,51]. Our experimental model is different in that it mimics gestational diabetes in humans, which occurs in the second half of pregnancy after morphogenesis is complete. Additionally, insulin was administered to keep glucose levels in a target range of 200–400 mg/dl and ketosis to a minimum. Over the course of ten years, we have not identified an increase in congenital heart defects; rather, we consistently find cardiometabolic dysfunction in the hearts of offspring exposed to late gestation maternal diabetes and HFD [10,12,13,23]. This correlates with differences in pregestational and late-gestation exposures in humans.
While this study confirms that insulin-resistant neonatal myocardium can utilize ketones as an alternative source, whether ketones are useful to help reverse the permanent effects of glucolipotoxicity during this critical window of development should be further examined. Interestingly, clinical studies revealed that the supplementation of ketones is beneficial for patients with chronic heart failure [52]. Indeed, ATP production following ketone administration was found to nearly triple in patients with heart failure [53]. Pharmacological interventions that target metabolic syndrome indirectly promote ketogenesis, which also appears to reduce the risk of adverse cardiovascular events [54,55]. Although the clinical trials with ketones in adult patients seem promising, similar studies are required to examine whether supplementing ketones to high-risk infants would be safe and beneficial for neonatal cardiomyopathy.
## 4.1. Animal Care
This study followed the guidelines set forth by the Animal Welfare Act and the National Institutes of Health Guide for the Care and Use of Laboratory Animals and was under approval from the Sanford Research Institutional Animal Care and Use Committee (Protocol #170-06-23B). All animals were housed in a temperature-controlled, light–dark cycled facility with free access to water and chow. Female Sprague–Dawley rats (Envigo, Indianapolis, IN) received control (TD2018 Teklad, Envigo; $18\%$ fat, $24\%$ protein, $58\%$ carbohydrates) or HFD (TD95217 custom diet Teklad, Envigo; $40\%$ fat, $19\%$ protein, $41\%$ carbohydrates) for at least 28 days prior to breeding to simulate a dietary “lifestyle.” Diets were selected to equate commonly attainable low-fat diets ($18\%$ of calories as fat) or HFD ($40\%$ of calories as fat) with more saturated and monounsaturated fat content. Omega 6:3 ratios were similar between diets. Female rats were bred with healthy male rats and fed a control diet and monitored by daily vaginal swab for spermatozoa. When spermatozoa were first present, timed pregnancy started as embryonic day 0 (E0). After confirming the pregnancy with an ultrasound, dams received an intraperitoneal injection of either citrate-buffered saline (Thomas Scientific, Swedesboro, NJ) diluent or 65 mg/kg streptozotocin (Sigma-Aldrich, Inc., St. Louis, MO, USA) to induce late gestation diabetes on E14. With a goal to keep blood glucose levels at 200–400 mg/dL, dams were partially treated with sliding scale insulin (regular and glargine, Eli Lilly and Co., Indianapolis, IN) two times per day. Whole blood sampling from a tail nick was done to measure glucose at least twice daily and ketones (βHOB) daily (Precision Xtra glucometer and ketone meter, Abbott Laboratories, Abbott Park, IL, USA). Dams with blood glucose < 200 mg/dL within 48 h after streptozotocin were excluded from the study. Although this model induces maternal diabetes by streptozotocin-mediated pancreatic damage, we have consistently shown that the developing offspring, our experimental subjects, are exposed to maternal hyperglycemia, hyperlipidemia, and fetal hyperinsulinemia in the last $\frac{1}{3}$ of pregnancy [9,11,12,13,56]. Dams were allowed to deliver spontaneously in order to yield offspring of both sexes from two distinct groups: controls and combination exposed (diabetes + HFD). On postnatal day 1 (P1), offspring hearts ($$n = 10$$–12 litter per group and each group comprised 5–6 male and female hearts) were collected under $5\%$ isoflurane anesthesia and immediately used for the isolation of NRCM or snap frozen in liquid nitrogen and stored at −80 °C until analysis. Maternal and offspring characteristics are given in Supplementary Tables S1 and S2.
## 4.2. Isolation of Neonatal Rat Cardiomyocytes (NRCM)
Isolation of NRCM was done as previously detailed [9,10,13]. Briefly, hearts collected on P1 were transferred to Hank’s Balanced Salt Solution on ice. After removing atria, ventricles were minced and digested with $0.1\%$ trypsin with $0.02\%$ DNase I (in 0.15 M NaCl) via 5–6 alternating cycles of stirring (5 min at 50 rpm) followed by trituration at 1–2 mL/s for 5 min. Trypsin/DNase I mix was deactivated with bovine serum (BS) before centrifuging cells at 1600 rpm at 22 °C for 10 min. Cell pellets were resuspended in DMEM-1 supplemented with $10\%$ BS and $1\%$ penicillin/streptomycin with $0.0002\%$ DNase I. Cells were seeded to uncoated 35 mm dishes, and incubated for 1 h in humidified 37 °C, $5\%$ CO2 to allow fibroblast attachment. NRCM were then gently detached, resuspended in DMEM-1, and counted with a hemocytometer using Trypan Blue before seeding to $0.1\%$ gelatin-coated Seahorse XFe24 V7 PS cell culture microplates (Agilent, Santa Clara, CA) at 150,000 cells/well for extracellular flux analyses. NRCM were allowed to adhere overnight (12–16 h) before experiments.
## 4.3. Ketone Stress Test (KST) in Isolated NRCM
Isolated NRCM on gelatin-coated XFe24 microplates were washed with XF DMEM media (Agilent, Santa Clara, CA, USA) and placed in a 37 °C incubator without CO2 for 1 h to degas. Analyses were run on a Seahorse XFe24 analyzer (Agilent, Santa Clara, CA, USA) after validating seeding density and drug dosing according to the manufacturer’s recommendation, as previously detailed [9,10,13,14]. Temperature and pH of the media was adjusted to 37 °C and 7.4, respectively. Oxygen consumption rates (OCR) and extracellular acidification rates (ECAR) were measured at baseline and following injections with: (A) 1.5 µM UK5099, a pyruvate inhibitor (R&D Systems, Minneapolis, MN, USA) and 0, 1.5, or 4.5 mM βHOB (Sigma, St. Louis, MO, USA); (B) 0.3 µM carbonyl cyanide p-trifluoromethoxyphenyl-hydrazone (FCCP) (Sigma, St. Louis, MO, USA); (C) 10 mM D-(+)-Glucose (Sigma, St. Louis, MO, USA); (D) 2 µM Rotenone (Sigma, St. Louis, MO, USA), 4 µM Antimycin A (Sigma, St. Louis, MO, USA), and 2 µM Hoechst (AnaSpec, Fremont, CA, USA) to stain remaining live cells at the end of the run for normalization. A schematic representation of the protocol is shown in Figure 2 and Figure 10. After measurements, the cells were imaged and counted using Cytation 1 Cell Imaging Multi-Mode Reader (Agilent, Santa Clara, CA, USA) for data normalization to cell count. Proton efflux rates (PER) were calculated as initially described by Mookerjee et al. [ 57] and are shown in Supplementary Table S3.
## 4.4. Quantitative Real Time PCR
RNA was extracted from newborn (P1) rat ventricles using the RNeasy Fibrous Tissue Mini kit (Qiagen, Germantown, MD, USA) following the manufacturer’s protocol. RNA integrity was assessed by electropherograms using 2100 BioAnalyzer (Agilent Technologies, Santa Clara, CA, USA) and demonstrated RNA Integrity Numbers of 9.2–10 (average = 9.8). RNA concentration was measured by Epoch spectrophotometer (BioTek, Winooski, VT, USA). Complementary DNA (cDNA) was synthesized using iScript cDNA Synthesis Kit and T100 Thermal Cycler (Bio-Rad, Hercules, CA, USA). Quantitative PCR (qPCR) was performed by TaqMan approach with Absolute Blue qPCR Mix using an ABI7500 qPCR system (ThermoFisher, Waltham, MA, USA). Beta-2-microglobulin (B2m) was used as the reference gene. B2m, Hmgcs2, Pparg, and Cpt1a probe/primer sets were obtained from ThermoFisher (Waltham, MA, USA), and Pgc1a probe/primer set was obtained from Integrated DNA Technologies (Coralville, IA, USA). Details are given in Supplementary Table S4.
## 4.5. Statistical Analysis
All statistical analyses were done with Prism 9 (GraphPad Software). Further information, including sample sizes and number of replicates, is provided in the legends accompanying each figure. Two-way ANOVA was used to detect the effects of in utero diabetes + HFD (combination) exposure, ketone dosing, and interactions. When a significant group or interaction effect was present, one-way ANOVA with Tukey post-test for individual group comparison was also determined. Unpaired t-test followed by a Mann–Whitney U test was used to examine group differences including maternal and neonatal characteristics, gene expression, and sex-specific comparisons. For all statistical tests, $p \leq 0.05$ was considered statistically significant.
## 5. Conclusions
This study used a novel KST to analyze real-time ketone body metabolism in NRCM. Importantly, we used this assay to show that even though offspring exposed to diabetic pregnancy and HFD have myocardial mitochondrial dysfunction, they can still metabolize ketones, which are known to be protective for the diabetic and failing heart in humans. Considering (i) the alarming rate of myocardial dysfunction in the infants exposed to maternal diabetes and obesity, as well as (ii) the role of ketone body metabolism in the failing hearts, this study provides critical information towards understanding the potential use of ketones for refractory cases of neonatal cardiomyopathy in these high-risk infants.
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|
---
title: Impact of COVID-19 Confinement on the Health-Related Habits of People at High
Risk of Type 2 Diabetes
authors:
- Darío Ochoa Esteban
- Carmen Martin-Ridaura
- Carmen Berlinches-Zapero
- Dolores Ruiz-Fernández
- Vanessa Sanz-Martín
- Rosario Gavira-Izquierdo
- Aitana Muñoz-Haba
- Sebastià March
- Mercedes Ceinos-Arcones
journal: Nutrients
year: 2023
pmcid: PMC9967931
doi: 10.3390/nu15040841
license: CC BY 4.0
---
# Impact of COVID-19 Confinement on the Health-Related Habits of People at High Risk of Type 2 Diabetes
## Abstract
*The* general lockdown decreed in Spain due to the COVID-19 pandemic interrupted the ALAS health promotion intervention aimed at the population at high risk of suffering from type 2 diabetes. We conducted a descriptive study in 2020 through a telephone survey and a comparison with baseline data to determine the impact of confinement on the lifestyles of the participants. We collected sociodemographic variables and conducted assessments before/after confinement on general health status and lifestyle (sleep, physical activity and diet). Additionally, weight, BMI and adherence to a Mediterranean diet were assessed. Descriptive statistical analyses, comparisons of pre–post confinement data and logistic regression were carried out. A total of 387 individuals responded. Among them, $31.8\%$ reported a worse perception of health after confinement, and 63,$1\%$ reported no change. Regarding exercise, $61.1\%$ reduced their weekly physical activity time. Regarding diet, 34,$4\%$ perceived worse quality, and $53.4\%$ reported no change, despite the fact that $89.4\%$ declared changes in their eating practices. Weight and BMI decreased by 3,$1\%$, and adherence to the Mediterranean diet improved from baseline. Confinement had a negative impact on the general health, diet, sleep and physical activity of this population (at risk of diabetes); however, weight and BMI decreased, and adherence to a Mediterranean diet improved.
## 1. Introduction
In March 2020, the WHO declared COVID-19 a global pandemic [1]. Following the increase in SARS-CoV-2 infections and observing the responses of many other countries, on March 15, 2020, a state of emergency was decreed in Spain [2]; the decree included general home confinement, which affected the majority of the population and sought to reduce the spread of the pandemic. In Spain, the confinement lasted until June, almost 100 days. It involved drastic changes in the day-to-day lives of the population; therefore, health habits were affected, as various studies have already reported [3,4,5,6]. There were significant impacts on the mental health of the population [7,8]; physical activity (PA) decreased [9]; sleep time and quality were altered [10]; and eating habits changed [11,12,13].
These impacts of general confinement applied at the population level have had important effects on society [14]. The effects that confinement may have on people with chronic diseases that are associated with lifestyle habits, for example, diabetes, or risk factors for developing chronic diseases are particularly relevant [15,16].
The high-risk intervention implemented through the ALAS programme includes individualised care and an intensive and structured group education workshop aimed at people with grade II overweight, obesity and/or a high risk of type 2 diabetes. The aim of the programme is to address and prevent these diseases by promoting changes in lifestyles, such as healthy eating, following a Mediterranean Diet and regular PA.
The programme began in 2011 and continues today. An effectiveness study was conducted with 1629 people who participated between 2016 and 2019 [17], concluding that [1] at the end of the intervention, $85\%$ had lost weight, with $43\%$ losing more than $5\%$ of their baseline weight; [2] $22.3\%$ of the people with obesity no longer presented obesity; [3] $35.1\%$ of people classified as prediabetic according to the criteria of the American Diabetes Association became normoglycaemic; and [4] the effects on weight lasted at least 6 months after the end of the intervention.
Since September 2019, prior to confinement, 533 people have enrolled in the programme. Due to social isolation measures, the programme was interrupted. The participants who had started the intervention and the workshops were confined to their homes.
The purpose of this study is to describe the impact of confinement on the lifestyles of this sample of people with excess weight and/or a high risk of diabetes who had initiated an intervention programme to modify their health status.
## 2.1. Design
This was a descriptive study conducted in Madrid from May to June 2020, when the general confinement measures were de-escalated. A questionnaire was administered by telephone to people who were implementing the intervention programme. The interviews were conducted by health professionals affiliated with the programme and served simultaneously to maintain contact with the participants. Some data collected (weight, BMI, adherence to a Mediterranean diet) could be compared with baseline data collected previously for the programme. Therefore, a pre–post quasi-experimental design was possible.
## 2.2. Participants
The target population was the 553 people who had started the workshop in the ALAS programme between September 2019 and March 2020. The inclusion criteria to enter the programme were to be over 18 years of age and have one of the following: a BMI over 30 or BMI between 27 and 30 with an abdominal circumference risk (greater than 88 cm in women or 102 cm in men) or a FINDRISC (Finnish type 2 Diabetes Risk Score) greater than 14, this instrument having been validated for the Spanish context [18]. Participants accessed the programme through municipal health centres or were referred by municipal occupational health services (aimed at city council workers).
## 2.3. Description of the Programme
The ALAS intervention, based on the Diabetes Prevention Programme [19], consists of an intensive and structured intervention lasting 6 months that includes an individual intervention programme and a group education workshop [20] of 10 sessions (2 h each), over a period of 6 months, aimed at reducing weight, improving diet and increasing PA. The specific objectives of the programme include a $5\%$ reduction in body weight, improvement in adherence to a Mediterranean diet, improvement in participation in PA and improvement in glycaemic status (for those with prediabetes).
## 2.4. Variables
The questionnaire, which combined ad hoc-designed impact measurements with validated tools, had different blocks:
## 2.4.1. Sociodemographic and Participation data
Age, gender, country of birth, marital status, education level and employment status were collected. Information was also collected on housing and cohabitants during confinement: number of cohabitants, cohabitants under 14 years of age (yes/no), cohabitants older than 65 years of age or dependents (yes/no), size of residence (square metres) and access to the internet from home (Yes/No). With these variables, the density of inhabitants per household was calculated in square metres per inhabitant.
The following variable was collected for participation in the programme: number of sessions until interruption.
## 2.4.2. Health Status and Lifestyle Data
General health status: General health status before and after confinement was assessed through a Likert-type scale with 5 response options: very good, good, fair, poor and very poor.
Health-related life habits: Diet before and after confinement was assessed using a Likert-type scale with 5 response options (from 1 (unhealthy) to 5 (very healthy)). Participants were asked about changes in 12 practices related to diet that may have occurred due to confinement (better/same/worse): quantity of food consumed; variety of foods; regularity of meal times; snacking between meals; consumption of fresh, packaged and processed foods, sweets, pastries, soft drinks and alcoholic beverages; menu planning; time dedicated to cooking; and financial ability to implement a healthy diet. A validated questionnaire on adherence to a Mediterranean diet (MEDAS 14) [21] is used as an assessment tool for the programme. The questionnaire has 14 items related to the weekly frequency of the consumption of certain products, such as vegetables, oil and legumes. Each item has a cut-off value based on recommendations, and the global scale differentiates among high, medium and low adherence to a Mediterranean diet. Regarding physical exercise, the number of days per week and the average time spent exercising before and after confinement were assessed. Sleep time (total, day and night) and sleep quality (reduced or maintained) during confinement were also investigated.
## 2.4.3. Anthropometric Data
While baseline data were collected by programme professionals taking actual measurements, weight and height during confinement were self-reported, from which the BMI was calculated.
These data were paired to baseline data (weight, BMI and diet adherence) collected through the programme at the beginning of the intervention while maintaining anonymity. Variations in weight, BMI and diet adherence before and after confinement were calculated. In addition, the percentage of people who had achieved a $5\%$ reduction in baseline weight was calculated; this variable is one of the main evaluation objectives of the ALAS programme.
## 2.5. Analysis
A descriptive analysis of all data was performed. The health and lifestyle variables were crossed, and chi-square tests and ANOVA were used to explore bivariate relationships. The factors related to the deterioration of general health or diet were adjusted using logistic regression models; the adjusted ORs are presented with the corresponding confidence intervals. The models were adjusted for all of the variables that had a significance of at least $90\%$ and whose omission did not alter the parameters of the remaining variables by more than $5\%$.
For the pre–post analysis, weight, BMI, % obesity and adherence to a Mediterranean diet were compared using t-tests. Logistic regression analysis was performed to adjust the factors related to achieving a $5\%$ reduction in baseline weight.
## 2.6. Ethical Aspects
The study complied with the principles of the Declaration of Helsinki of 2013. All participants gave their informed consent to answer the questionnaire and were informed that their collaboration was voluntary, anonymous and not conditional on their subsequent participation in the programme. The study was approved by and received ethical consent from the municipal health promotion service of Madrid Salud, which ensured anonymity throughout the process.
## 3.1. Description of the Sample
A total of 387 ($72.6\%$) of the 533 participants enrolled in the ALAS programme from September 2019 to February 2020 responded to the survey. There were no differences between the participants and non-participants in terms of age and sex, although the participants had a higher percentage of people with obesity at baseline (69.4 vs. 59.1) and therefore higher weight, waist circumference and baseline score of FINDRISK.
The mean age of the participants was 57.5 years (SD = 12.1; Rank = 18 − 86), and $77.9\%$ of the sample were women. A total of $25.6\%$ had not participated in any workshop sessions, $42\%$ had participated in 1 to 5 sessions, and $32.4\%$ had participated in 6 or more (complete intervention according to the ALAS programme protocol). The sociodemographic and housing characteristics of the sample are shown in Table 1, stratified by gender.
## 3.2. Impact on Self-Perceived Health
Before confinement, $73.9\%$ of the participants claimed to have good or very good health, with $19.4\%$ and $6.7\%$ reporting fair and bad or very bad health, respectively; during confinement, these percentages changed to $53.2\%$, $33.9\%$ and $12.9\%$, respectively. A total of $31.8\%$ of the participants reported a worse perception of their health after confinement, with $63.1\%$ maintaining their self-perception of health and $5.1\%$ reporting an increase. The worsening of the self-perceived state of health after the onset of the pandemic was related to being affected by obesity, being single, separated or divorced, and living with dependents; in contrast, living with minors was associated with preventing a deterioration in health (Table 2). When these factors were adjusted in a logistic regression model that included age and self-perceived health status before the pandemic, the effect of living with minors as a protective factor against deterioration was maintained (OR = 0.16; $95\%$ CI = 0.06−0.43), and obesity was maintained as a risk factor (OR = 2.41; $95\%$ CI = 1.36−4.28).
## 3.3. Impact on Sleep Habits
A total of $28.3\%$ of the participants reduced their total sleep time during confinement, $59.3\%$ maintained it, and $12.4\%$ increased it. Regarding sleep quality, $39.6\%$ believed that it worsened during confinement; for $53.9\%$, sleep quality remained the same, and for $6.5\%$, it improved. Sleep time at night decreased for $35\%$ of the people surveyed, was similar to that before confinement for $55.5\%$ and increased for $9.4\%$. Simultaneously, sleep time during daylight hours increased for $15.4\%$ of the people surveyed, remained the same for $75.7\%$ and decreased for $8.9\%$.
The worsening of sleep quality was related to being a woman or being unemployed ($p \leq 0.05$). Sleeping less during the day was statistically significantly related to having children or living with older dependents. The worsening of general health and diet during confinement was also significantly related to a worse quantity and quality of sleep. Age was also a factor. Younger people had greater sleep disturbances and worse sleep time and quality than did older people: $51.1\%$ of participants under 45 years of age perceived worse sleep quality during confinement, followed by those who were 45–54 years of age, $43\%$; between 55 and 64 years of age, $40.3\%$; and those over 65 years of age, $31.5\%$.
## 3.4. Impact on Physical Exercise
Before confinement, $8.1\%$ of the participants did not perform any type of weekly physical exercise; after confinement, this percentage increased to $28.6\%$, while $61\%$ decreased the time they dedicated to physical exercise, with $24.4\%$ reporting an increase and $14.6\%$ reporting no change. Participants were physically active, on average, for 5 h per week (range: 0–35; SD = 4.2) before confinement and 3.4 h on average after confinement (range: 0–35; SD = 4). Before confinement, $60.3\%$ met the recommendation of 30 min of physical exercise daily; after confinement, this percentage decreased to $40.8\%$.
The impact of confinement on PA was related to previous participation in PA (Table 3). A reduction in PA was related to greater-than-average participation in PA previously. In contrast, an increase in PA was related to participating in less PA before confinement. The participants who reported an increase in PA did so for an average of 3.9 h per week (SD = 4.3), $173\%$ (SD = 214.5) of their pre-pandemic PA time. Those who reduced their participation in PA did so by an average of 4.2 h per week (SD = 3.6), $72\%$ of the pre-pandemic PA time (SD = 28.7). These variations were significant (t-test, $p \leq 0.01$). Among the people who increased their PA, $36.7\%$ met the recommendation of 30 min per day before confinement, increasing to $84.4\%$ after confinement; for those who reduced their PA, compliance decreased from $73.8\%$ to $22.2\%$.
## 3.5. Impact on Diet
The average assessment of eating practised before confinement was 3.78 (SD = 0.89) on a scale of 1 to 5 (1: unhealthy; 5: very healthy). After confinement, the average was 3.47 (SD = 1.09), representing a significant difference (paired-samples Student’s t-test, $p \leq 0.001$). A total of $34\%$ reported a worse diet (scored worse) after confinement, $53.4\%$ maintained their diet without changes, and $12.2\%$ improved their diet. The relationship between the characteristics of the sample and the impact of confinement on the self-perception of their diet is shown in Table 4, and the adjustment by logistic regression is shown in Table 5. The negative impact of confinement on diet, adjusted for the assessment of diet before confinement (those who had a better diet experienced a greater negative impact), was significantly related to being middle-aged (45–64 years), living in a residence with less than 25 m2 per cohabitant, living with elderly individuals or dependent people and being affected by obesity.
Regarding the 12 dietary practices that were assessed (Table 6), $89.4\%$ of the participants had modified at least 1 during confinement (average of 4.3 practices changed). Modifying a practice (increasing or decreasing) was related to a self-perception of the deterioration of diet during the pandemic: $37.3\%$ of those who modified their practices reported a worse diet, and among those who did not change dietary practices, $10.3\%$ reported a worse diet.
People over 65 years of age changed their practices the least, those younger than 45 years reduced healthy practices the most, and those aged 45–54 years increased their unhealthy practices the most. All participants who lived with minors changed their eating practices: this change was significantly associated ($p \leq 0.05$) with increasing healthy practices and reducing unhealthy practices, with the exception of the financial ability to implement a healthy diet, which was significantly lower in households with minors than in the rest ($19.6\%$ vs. $7.9\%$).
Some healthy practices increased, such as spending more time in the kitchen and the consumption of fresh food, and others were reduced, such as the regularity of meal times or the variety of foods consumed. The same happened with less healthy practices: snacking between meals, the consumption of sweets and pastries, and the amount of food consumed increased, and the consumption of packaged and processed foods, soft drinks and alcoholic beverages was reduced.
## 3.6. Weight Variation, BMI and Adherence to a Mediterranean Diet
Complete pre- and post-confinement weight data were obtained for $84\%$ of the sample ($$n = 325$$). The majority ($64.3\%$) lost at least 1 kg of weight from the baseline measurement. A total of $16.9\%$ maintained their weight, and for $18.8\%$, their weight increased. On average, the surveyed population lost 2.7 kg (SD = 4.9), i.e., $3.1\%$ of their baseline weight (SD = 5.5). Among the people who gained weight, the average gain was 3.4 kg (SD = 3.1) or $4\%$ of their baseline weight (SD = 4), and among those who lost weight, the average loss was 5.2 kg (SD = 4) or $6\%$ of their baseline weight (SD = 4.1). Weight loss was related to having accessed the programme through municipal occupational health services and being initially classified as overweight (not presenting obesity). Weight loss was also inversely related to the consumption of processed foods: among the people who reduced this consumption, $89.9\%$ lost weight; among those who maintained consumption, $60.7\%$ lost weight; and among those who increased consumption, $55.3\%$ lost weight.
The variations in weight, BMI and adherence to a Mediterranean diet are shown in Table 7. Of the 322 people with complete data, $68.6\%$ were classified as affected by obesity, $25.8\%$ were overweight and $5.6\%$ were normal weight at baseline; after confinement, the classification percentages were $58.1\%$, $34.8\%$ and $7.1\%$, respectively. A total of $14\%$ had a lower classification level (from obesity to overweight or from overweight to normal weight), $84.5\%$ remained in the same classification, and $1.6\%$ increased. Among the people initially classified as affected by obesity, $16.7\%$ became overweight.
The variables that were statistically significantly related ($p \leq 0.05$) to the decrease in BMI after confinement were access to the programme through the municipal occupational health service ($27.3\%$ reduced BMI, compared to $11.9\%$ of those who accessed the programme through community health centres), overcrowding in the home ($17.3\%$ in homes with less than 25 m2/habitant, compared to $6.8\%$ in those with more than 50 m2/habitant) and employment status ($17.7\%$ in workers and $15.5\%$ in retirees vs. $2.6\%$ in unemployed and none of those who were dedicated to home care). The variation in BMI was not significantly related to the number of sessions performed, to the abandonment of the intervention or to not having performed any sessions.
Of the 287 people with complete MEDAS-14 data, $17.5\%$ had low adherence to a Mediterranean diet at baseline, $65.9\%$ had medium adherence, and $16.5\%$ had high adherence. After confinement and starting the ALAS intervention, $6.1\%$ had low adherence, $63.3\%$ had medium adherence, and $30.6\%$ had high adherence. A total of $31.4\%$ improved their adherence, $56.4\%$ maintained it, and $12.2\%$ lowered it. A total of $83.3\%$ of participants with low adherence at baseline improved.
This variation in adherence was not significantly related to the characteristics of the sample or to the variables related to the implementation of the intervention (number of sessions, dropouts, not performing any session), although the people who had participated in at least one session improved adherence more than those who had not participated in any ($34.1\%$ vs. $21.9\%$; $$p \leq 0.064$$).
Thirty-two percent [104] of the sample with complete weight data lost at least $5\%$ of their initial weight, one of the main objectives of the ALAS programme. The adjusted factors related to this objective (Table 8) were accessing the programme through municipal occupational health services, having high adherence to a Mediterranean diet, having improved menu planning, being of non-Spanish origin and living in households with 80 to 100 m2. Thirty-six percent of the people who completed three or more sessions of the ALAS workshop met the goal of a $5\%$ or more reduction in their baseline weight, with $25.6\%$ of those who did not participate in any sessions achieving the same goal; the difference was not statistically significant ($$p \leq 0.401$$ in the chi-square test).
## 4. Discussion
The results of this study indicate the important impact that general confinement has had on the lifestyles of people at high risk of having diabetes who have begun an intensive health promotion intervention. Although the majority of people maintained their self-perception of health, approximately one-third reported worse sleep and diet quality and decreased PA. Changes in feeding practices varied and had positive and negative effects. In the sample studied, there was a significant reduction in weight and therefore in BMI, as well as an improvement in adherence to a Mediterranean diet.
Although $63.1\%$ of the participants stated that there were no changes in their general self-perception of health during confinement, $31.8\%$ reported that it was worse. This negative impact of confinement on the self-perception of health in general [22,23] and mental health specifically [24] has been noted in various studies conducted in recent years. There are factors, such as the context in which confinement took place [22] or the existence of chronic diseases or previous mental health problems [25], that have been related to this negative impact; however, they were not measured in our study. For other factors that have been shown to have a relationship, such as gender, age and social position [26], and that were collected here, the relationships were not maintained after adjustment. For our participants, being affected by obesity most conditioned the negative impact. While the relationship between obesity and poor health perception is known [27], there is little evidence about the relationship between obesity and the impact of confinement, although the media and scientific publications have already highlighted people with obesity as a potentially vulnerable population in the face of the imminence of the pandemic [28].
When adjusted for other factors, living with children (regardless of gender) emerged as a protective factor against the worsening of health or diet perceptions. This is an unexpected result; it is possible that confinement offered, among many difficulties, opportunities to improve care and dedicate more time to cohabitant minors. In fact, people with children were among those who had to make the most changes in their routines during confinement [29,30]. Other studies of confinement indicate that living with minors is related to a negative impact on diet [31]; however, the previous literature is divided as to whether it worsens or improves the household diet [32,33].
Our data indicate that the majority of participants maintained their usual sleep time, while $28\%$ reduced their sleep time and $12\%$ increased it. However, up to $40\%$ reported worse sleep quality. A French study [34] and an Australian study [35] also found increases in the incidence of sleep problems compared to relevant evidence before confinement. Others [36,37] have also observed this increase, describing associated factors such as overexposure to blue light due to the increase in the use of devices and in teleworking.
Our results indicate a general decrease in the time dedicated to PA during confinement. This result is consistent with various studies in the general population conducted for the same period in Spain [38,39] and in approximately 20 studies in Italy reviewed by Zaccagni et al. [ 40]. The results also coincide with a Singaporean investigation based on data recorded automatically and continuously by bracelets [41]. In contrast, a few studies in European countries obtained contradictory results that indicate an increase in declared PA during confinement [42,43,44]. Consistent with our results, low compliance with the minimum recommended PA guidelines was also observed among the general population in Spain [39] and the United Kingdom [42].
Our data indicate that the decrease in PA was not homogeneous for all profiles: those who reported a higher level of PA before confinement experienced a strong decrease in compliance with the recommendation of 30 min of daily exercise, and for those who were less active pre-confinement, compliance with this standard significantly increased. This finding contrasts with the results of a study from Singapore [41]: i.e., people who decreased their PA the most were the most inactive before confinement, while those who were the most active pre-confinement maintained a profile with greater PA, despite a reduction.
Castañeda-Babarro [38] observed a similar reduction in PA that was more intense among originally more active individuals, a finding that could be explained by the forced closure of sports facilities during confinement and the lack of sports equipment at home. Additionally, among the most inactive people before confinement, moderate PA at home increased [43]. For the most inactive population, confinement represented an opportunity to dedicate time to PA, while those who were more active may have been limited by the inaccessibility of the spaces where they generally practised PA (gyms, swimming pools, parks, etc.).
Although half of the participants believed that there was no impact, one in three participants perceived that their diet had worsened with confinement. Several studies agree that diets were mostly maintained [5,43,45,46]. Some studies reported changes in eating habits; however, the direction of those changes is not clear [3,13]. A study by López-Moreno et al. [ 47] of the general population in Spain showed that $54\%$ changed habits, with $38.4\%$ improving and $16\%$ worsening. Additionally, Net-Santé in France [31] indicated that $56.2\%$ of participants changed their eating practices. As in our results, other studies agree that perceiving a deterioration in one’s diet is related to age [48] and BMI [49]; however, these studies do not relate this perception to the conditions of the home or to living with elderly dependents.
A study conducted in various European countries by Skotnicka et al. [ 50] concluded that people with worse eating habits before confinement experienced a more negative impact on their diets. In contrast, in our study, the results indicate the opposite. Similar results were observed in a follow-up of US and UK cohorts [4].
Among the variability in changes in eating habits, evidence from European studies supports the results obtained in our study, i.e., increased time spent cooking [3,31,43,47,48]; the increased consumption of fresh products, fruits and vegetables [3,12,31,39,43,48]; and the increased consumption of snacks and sweets [3,12,31,47,48,49,50,51]. In our study, one-fifth of the participants reduced their consumption of ultra-processed foods, a finding that is consistent with some studies [43] but that also differs from other studies that warned of an increase [3,47,52]. In our study, $18.1\%$ of the participants increased their consumption of alcohol, and $10.5\%$ reduced their consumption; therefore, the impact is not clear. In other European studies, high variability is noted in the impact on alcohol consumption [3], with results that indicate that it increases [47,48,49,50,51] and others that indicate that it decreases [12,39,43,53].
These changes in habits seem to have produced slight improvements in adherence to a Mediterranean diet [50,53], which is considered heart-healthy. In our study, a significant increase in this adherence stands out ($31.4\%$); however, the majority ($56.4\%$) did not report significant changes.
These impacts on changes in habits (eating and PA) produced weight changes in people who lived in confinement; however, these include increases and decreases. Therefore, there is substantial variability [11,31,47,48], and at the population level, there does not seem to be a significant effect [54,55]. A longitudinal study in the United Kingdom reported that there was an increase in average weight at the beginning of confinement but that weight later decreased, resulting in no impact of confinement on weight [54].
There seems to be some consensus that the people who gained the most weight were those who were previously affected by obesity or overweight [3,11,54,56]. This contrasts with the results of our sample: $68.6\%$ were initially affected by obesity, and the majority ($64.3\%$) lost at least 1 kg of weight and therefore reduced their BMI.
A total of $32\%$ of the sample achieved a reduction of $5\%$ in their baseline weight, one of the main objectives of the ALAS programme. Although the design of this study did not allow the establishment of causal relationships, several hypotheses can be proposed to explain how there was a significant reduction in weight in this sample, while most studies in Spain and nearby countries indicate that, at the population level, there was no significant impact. The participants had decided to enrol in a health education programme to modify their lifestyle; therefore, they were people in a phase of preparation for action according to the transtheoretical model [57,58] and therefore more likely to make these changes. In addition, for this population, the ALAS programme serves as a motivator and supports the implementation of change. In fact, the $32\%$ efficacy in the $5\%$ reduction in baseline weight is similar to the $34\%$ established in previous evaluations of the programme [17] for participants who did not complete the intervention. That is, the simple fact of having access to the intervention (without completing it) may promote change. For this study, intervention follow-up (number of sessions performed) did not have a significant effect. By entering the programme (an inclusion criterion in this study), participants meet for an individual session where they are weighed, measured, given questionnaires on lifestyle habits and provided information and brief advice to motivate change. This intervention and brief advice by themselves have already demonstrated some efficacy, although slight in magnitude, in promoting change [58,59,60]. Thus, although confinement seems to impact the weight of the population in a variable direction that results in modest changes at the population level, other factors were also at play in our study, such as the selection of a sample motivated to change and the fact that they were already enrolled in a health promotion programme. These last factors seem to have counteracted the effects of confinement described in other studies of the general population, particularly among people with obesity and overweight people.
Although the ALAS programme is carried out in municipal health centres, participants can either be recruited directly in these centres or start after a referral from the labour services of the city council. Those who enrol in the programme through the second path are mainly municipal officials, meaning they are civil servants, a socio-economic profile that is typically subjected to more favourable social determinants than the general population captured in universal access services. This may explain why the pre–post results of the intervention are better in the group of people who accessed the programme through an occupational health referral, as happened in the evaluation of the ALAS programme itself [17].
The study had a very high participation rate ($72.6\%$), which is very valuable, given the difficult moment in which the questionnaire was administered. This success is attributed to the following: unlike most studies conducted during confinement, instead of opting for an online questionnaire, a telephone interview was conducted by professionals from their municipal health centres. Using this approach, barriers to the accessibility of online questionnaires were overcome; therefore, our sample has a higher proportion of elderly people and people with low levels of education than do other studies conducted in Spain in the same period [23,26,29,39,47,50,53]. Additionally, our sample is of particular interest for evaluating the impact of confinement because the participants were selected precisely because they are people with obesity and/or have a high risk of developing diabetes in the next 10 years if they do not modify their lifestyles. As in most studies carried out during confinement and referenced in this work, weight during confinement, as well as some of the impacts of confinement, was self-reported. This can potentially produce some biases; these should be similar to those that occur in the general population in other studies, and therefore, they should be comparable. There were statistically significant differences in the baseline weight of the participants compared to the non-participants, and a potential participation bias was checked. In this case, the results go against the hypothesis, because those who did not participate were precisely the ones who weighed less, so we understand that there was not a significant bias. Additionally, complete pre–post data on weight were not available for 62 participants ($16\%$ of the sample). Half of these cases were due to the fact that the baseline information could not be collected due to the start of the pandemic. The other half did not know their weight during confinement, as they may not have had the instruments to measure it. We believe that these data losses are not important enough to generate a bias in the study.
## 5. Conclusions
A significant percentage of people at risk of developing chronic diseases who enrolled in the ALAS health promotion programme between October 2019 and February 2020 perceived that the confinement experienced between March and June 2020 had a negative impact on their overall health, diet, sleep habits and PA. Interestingly, when compared with baseline data, weight and BMI decreased, and adherence to a Mediterranean diet improved. This positive effect on health could be explained by the participants being prepared to change and finding motivation and support through the ALAS programme. These results suggest that the development of public health promotion programmes with high-risk populations not only has a potential direct effect on their participants but can also protect them from the effects of unforeseen adverse situations threatening the stability of their health-related lifestyles, such as general confinement in this case. This could orient policymakers to continue promoting programmes targeting specific vulnerabilities and striving to sustain these interventions even in times of emergency. Our discussion also suggests that the satisfactory evolution of the participants during confinement might be related to the fact that the participants seem to be in an adequate phase of preparation for changes in their lifestyles. This leads to the recommendation that health promotion programmes adapt their interventions at the stage of change in the participants, i.e., raise motivation among those who do not present that attitude before prescribing specific routine transformations among those who are willing to introduce changes in their lifestyles. In any case, more research is needed to strengthen these ideas.
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|
---
title: 'Impact of Vitamin B12 Insufficiency on the Incidence of Sarcopenia in Korean
Community-Dwelling Older Adults: A Two-Year Longitudinal Study'
authors:
- Seongmin Choi
- Jinmann Chon
- Seung Ah Lee
- Myung Chul Yoo
- Sung Joon Chung
- Ga Yang Shim
- Yunsoo Soh
- Chang Won Won
journal: Nutrients
year: 2023
pmcid: PMC9967932
doi: 10.3390/nu15040936
license: CC BY 4.0
---
# Impact of Vitamin B12 Insufficiency on the Incidence of Sarcopenia in Korean Community-Dwelling Older Adults: A Two-Year Longitudinal Study
## Abstract
The longitudinal effect of B12 insufficiency on sarcopenia has not yet been investigated in older adults. We aimed to study the impact of B12 levels on alterations in muscle mass, function and strength over two years. Non-sarcopenic older adults ($$n = 926$$) aged 70–84 were included. Using the Korean Frailty and Aging Cohort Study, this two-year longitudinal study used data across South Korea. The tools used for assessing muscle criteria were based on the Asian Working Group for Sarcopenia guidelines. Participants were divided into the insufficiency (initial serum B12 concentration < 350 pg/mL) and sufficiency groups (≥350 pg/mL). Logistic regression analyses were performed to evaluate the effect of initial B12 concentration on sarcopenia parameters over a two-year period. In women, multivariate analysis showed that the B12 insufficiency group had a significantly higher incidence of low SPPB scores (odds ratio [OR] = 3.28, $95\%$ confidence interval [CI] = 1.59–6.76) and sarcopenia (OR = 3.72, $95\%$ CI = 1.10–12.62). However, the B12 insufficiency group did not have a greater incidence of sarcopenia or other parameters in men. Our findings suggest B12 insufficiency negatively impacts physical performance and increases the incidence of sarcopenia only in women.
## 1. Introduction
Vitamin B12 (B12), or cobalamin, is a water-soluble vitamin B complex member. It is a coenzyme involved in DNA synthesis and in fat and amino acid metabolism in the body [1]. B12, referred to as a “neurotropic” vitamin, plays an essential role in both the peripheral nervous system and the central nervous system, including the brain and spinal cord, so a supply of B12 is fundamental for the normal function of the nervous system [2,3]. A deficiency of B12 promotes neurotoxic oxidative stress and even neurodegeneration, which could be a risk factor for cognitive impairment [4]. B12 deficiency can also lead to the development of disorders of the peripheral nerves, such as peripheral neuropathy [5]. B12 deficiency is common among older adults because of the high prevalence of malabsorption due to atrophic gastritis and long-term antacid therapy, including histamine H2 blockers or proton pump inhibitors. In addition, with aging, gastric acid secretion and pepsin levels decrease and the absorption of B12 is reduced in older patients [6,7]. Demyelinating neurologic disorders in the central and peripheral nervous system stemming from B12 deficiency in older patients and significant damage of nerve fibers could cause muscle weakness, numbness, imbalance, ataxia and even reduced skeletal muscle mass [8].
Loss of skeletal muscle mass is manifested as sarcopenia in older adults, characterized by decreased muscle strength and/or decreased physical function causing disability and even increased mortality [9]. According to a recent study in Korea, the prevalence of sarcopenia is approximately $21.3\%$ in men and $13.8\%$ in women aged 70–80 years in Korea [10]. The underlying causes of sarcopenia include nutritional (low protein intake, energy intake, micronutrient deficiency), inactivity (bed rest, low activity) and diseases (endocrine diseases, neurological disorders, cancer) [11]. Because B12 deficiency contributes to neurodegeneration, a previous study suggested that this defect may be related to sarcopenia in older adults [8]. In particular, cognitive dysfunction and peripheral neuropathy related to B12 deficiency are known to be risk factors for sarcopenia [12,13]. Our previous cross-sectional study had found that B12 deficiency may increase the prevalence of low skeletal muscle mass in older adults [14]. However, these studies were cross-sectional in nature and therefore it was difficult to investigate the longitudinal association between B12 deficiency and sarcopenia.
In this two-year longitudinal study, we aimed to examine the impact of low B12 levels on the incidence of sarcopenia in healthy community-dwelling older adults using dual-energy X-ray absorptiometry (DEXA). We used baseline data from the Korean Frailty and Aging Cohort Study (KFACS) in this longitudinal study.
## 2.1. Data and Study Population
This two-year longitudinal study used data from the 2016 to 2019 KFACS. The KFACS is a prospective cohort, a nationwide study conducted in eight medical and two public health centers across South Korea. The authors recruited community-dwelling older adults between 70 and 84 years of age for two years (2016–2017) and followed up with them after two years (2018–2019) with 4 months of allowance limitations. In the baseline survey, questionnaires, face-to-face interviews, laboratory tests and health examinations were performed at each clinical site of the study centers. A total of 3014 participants conducted a baseline examination. The mean age of participants was 76.0 ± 3.9 years (men: $47.5\%$). Among these participants recruited in 2016 and 2017, 2539 participants were followed up two years later (the follow-up rate in 2018 was $93.9\%$; in 2019 it was $96.2\%$ and 37 participants died) [15]. Among them, participants with an absence of DEXA measurements, history of stroke or hemiplegia, diagnosed cognitive impairment or dementia (Mini-Mental Status Examination [MMSE] < 20) [16], incomplete physical function test, any fracture within one-year, hip or knee replacement, cancer treatment, or dependence needs for any activities of Korean instrumental activities of daily living (K-IADL) were excluded from this study [17]. Baseline participants who satisfied any one of the following criteria were also excluded: low appendicular skeletal muscle mass (ASM); low muscle strength; low physical performance according to the Asian Working Group for Sarcopenia (AWGS) 2019 diagnostic criteria (901 participants) (Figure 1) [18].
Finally, this study included 844 non-sarcopenic older adults (382 men; 462 women) who did not meet any diagnostic criteria for sarcopenia. The demographic data and medical history, including age, sex, education years, marital status, income per month, body mass index (BMI), smoking and alcohol status, and chronic diseases or comorbidities, were obtained from each participant. Smokers were defined as participants who smoked more than one cigarette in a week and alcohol consumers were defined as participants who drank alcohol more than once a week.
The KFACS protocol was approved by the Institutional Review Board (IRB) of the Clinical Research Ethics Committee of Kyung Hee University Medical Center (IRB number: 2015-12-103) and all participants provided written informed consent.
## 2.2. Vitamin B12
Participants’ blood samples were collected at the initial visit and B12 was measured by the Architect Vitamin Kit (Abbott Diagnostics, Lake Forest, IL, USA). The participants were divided by a serum B12 concentration cut-off of 350 pg/mL, which was reported to have a protective effect on myelin synthesis in the nervous system [7,19]. Individuals with a serum B12 concentration less than 350 (<350) pg/mL were defined as having B12 insufficiency. Participants were divided into clinically relevant categories by B12 concentration: insufficiency group (<350 pg/mL, equal to <258.3 pmol/L) and sufficiency group (≥350 pg/mL, ≥258.3 pmol/L).
## 2.3. Sarcopenia
Sarcopenia was diagnosed according to the AWGS 2019 criteria [20]. Participants with a low appendicular skeletal muscle mass (ASM) and either low muscle strength or poor physical performance were diagnosed with sarcopenia.
Muscle mass: We used DEXA to measure ASM and the appendicular skeletal muscle mass index (ASM/height2, ASMI) was calculated to compare the muscle mass at a different height. The cut-off values for low ASMI were <7.0 kg/m2 for men and <5.4 kg/m2 for women [21]. Of the eight centers, four used Hologic (Hologic Inc., Bedford, MA, USA) DXA systems and four used Lunar (GE Healthcare, Madison, WI, USA).
Muscle strength: Hand-grip strength (HGS) was measured by a hand dynamometer (Jamar, Bolingbrook, IL, USA). We measured HGS twice on both sides, with the elbow extended in a standing position. The participants held the grip for 3 s with full force and the maximum value was obtained (cut-off values: men, <28 kg; women: <18 kg).
Physical performance: We used a Short Physical Performance Battery (SPPB) to evaluate the physical performance. The SPPB is a well-accepted test for assessing lower extremity function in older adults. This test includes standing balance, 4-m usual gait speed and five counts of the sit-to-stand test. Each test was scored from 0 to 4 based on the reference values from the Established Populations for Epidemiologic Studies of the Elderly, with a maximum score of 12 points [22]. Participants who could not complete the sit-to-stand test were classified as failures. According to the AWGS 2019 diagnostic criteria, a score of ≤9 points was defined as low physical performance.
## 2.4. Statistical Analysis
Continuous variables were compared using Mann–Whitney U test or a t-test and categorical variables were compared by Pearson chi-squared test. Unadjusted and fully adjusted analyses were performed by logistic regression models and odds ratios (ORs) and $95\%$ confidence intervals (CI) were calculated. Unadjusted and fully adjusted analyses were also calculated through generalized linear models and B estimates alongside their corresponding $95\%$ CI values. The analyses were adjusted for potential confounding variables including age, dyslipidemia, hypertension, osteoporosis, osteoarthritis, diabetes mellitus, depression, BMI, smoking history, alcohol history, number of medications, MMSE-KC—Korean version and hemoglobin. The Statistical Package performed all statistical analyses for Social Sciences (version 25.0; SPSS Inc., Chicago, IL, USA) and $p \leq 0.05$ was defined as statistically significant.
## 3. Results
The baseline characteristics of the participants according to initial B12 levels are presented in Table 1. Among the 844 participants, 382 ($45\%$) were men and 462 ($55\%$) were women. In men, 366 ($90\%$) were B12 sufficiency group and 40 ($10\%$) were B12 insufficiency group. In women, 478 ($92\%$) were B12 sufficiency group and 41 ($8\%$) were B12 insufficiency group. The initial SPPB score was significantly lower in the B12 insufficiency group than that in the B12 sufficiency group in women (11.37 ± 0.77 vs. 11.10 ± 0.85, $p \leq 0.05$). Initial HGS and ASMI scores were not significantly different between the groups. Other characteristics such as age, BMI, alcohol use and diabetes mellitus were significantly higher in the B12 insufficiency group in women. The prevalence of osteoporosis was significantly higher in the B12 insufficiency group in men (Table 1).
Figure 2 shows the relative percentage change of sarcopenia parameters according to the initial B12 level over two years. All sarcopenia parameters decreased at follow-up. In both men and women, there were no significant differences in the percentage change (Δ) in the HGS or ASMI. On the other hand, SPPB showed a statistically significant reduction in the B12 insufficiency group in women only.
Table 2 shows the results of the generalized linear analysis for the relative percentage change of sarcopenia parameters according to the initial B12 level. The fully adjusted generalized linear model analysis showed that SPPB in women was significantly reduced in the B12 insufficiency group compared with that in the B12 sufficiency group (B estimate = −4.85, CI = −9.11 to −0.59). HGS and AMSI in women were more reduced in the B 12 insufficiency group compared with that in the B12 sufficiency group; however, it was not statistically significant.
Logistic regression analysis for the predictive power for sarcopenia of B12 insufficiency and its parameters according to sex is shown in Table 3. In women, the B12 insufficiency group had a significantly higher incidence of low SPPB (OR = 4.38, $95\%$ CI = 2.15–8.84) and sarcopenia (OR = 5.90, $95\%$ CI = 1.55–22.43) in the unadjusted and fully adjusted model, respectively. The B12 insufficiency group had a higher incidence of low HGS and ASMI. However, it was not statistically significant.
## 4. Discussion
In this study, we investigated the longitudinal effects of B12 insufficiency on sarcopenia according to sex over two years. We found that B12 insufficiency negatively impacted physical performance measured by SPPB and increased the incidence of sarcopenia in women who were non-sarcopenic, even after adjusting for confounding factors. In contrast, B12 insufficiency had no apparent influence on the change of muscle mass, muscle strength, physical performance and incidence of sarcopenia in men.
Several studies have investigated the association between B12 levels and physical performance. However, this relationship still remains controversial. A cross-sectional study of 796 older adults investigated the association of homocysteine and B12 levels with gait and balance performance. Completed performance-oriented mobility assessments (POMA) of gait, balance and self-reports of instrumental activities of daily living (IADL) were done and the results showed that B12 level was not significantly related to POMA of balance, POMA of gait and IADL scores [23]. In addition, Vidoni et al. conducted a longitudinal analysis to assess the association of B12 serum levels with gait speed decline. B12 serum levels were not significantly associated with a decline in gait speed over an average of 5.4 years [24]. However, a few studies have found that B12 levels are related to physical performance. In a cross-sectional study of 703 community-dwelling Caucasian older women, Matteini et al. revealed that low B12 levels contributed to frailty syndrome defined by low HGS, endurance, physical activity and walking speed [25]. In addition, Oberlin BS et al. assessed whether self-reported disability (including ADL), balance and gait speed are associated with low B12 levels and reported that low B12 levels are associated with the disability in ADL and reduced mobility [26]. In this study, we found that B12 insufficiency was inversely related to physical performance as measured using the SPPB. The discrepancy between the results of a few previous studies and our study may be due to the difference in the criteria for defining B12 deficiency and the method of measuring physical performance. The definition of B12 deficiency in previous studies varied from 200 to 350 (pg/mL). While previous studies investigated the relationship between B12 deficiency and physical performance by balance, gait speed, or ADL scores, we used the SPPB, which is a group of measures combining the results of gait speed, balance and repeated chair stands. The SPPB is more complex, but can accurately and comprehensively measure physical function.
A decline in physical performance may be due to neurologic complications related to B12 insufficiency. B12 insufficiency can cause myelin damage due to deficient methylation of myelin protein. It has been reported that a lack of B12 can induce several neurologic complications, including myelopathy and peripheral neuropathy [27,28]. Subacute combined degeneration, characterized by demyelination of the posterior and lateral columns of the spinal cord, is often found in patients with low B12 levels. It commonly presents with impairment of position sense, paresthesia, ataxia and gait disturbance [29,30]. Peripheral neuropathy has also been reported as another neurological complication caused by a lack of B12. According to previous electrodiagnostic studies, patients with B12 deficiency-related neuropathy typically have a sensorimotor axonal neuron defect with some demyelinating features. In a case series of nine patients with B12 deficiency-related neuropathy, four had sensorimotor (predominantly sensory) axonal polyneuropathy and five had sensory neuronopathy [31,32]. In a previous study, peripheral neuropathy in older adults was associated with a deterioration in physical performance [33]. The effects of neurologic complications, especially in sensory nerves caused by B12 insufficiency, may have resulted in a decline in SPPB.
Although it was not statistically significant, ASMI and HGS decreased more in the B12 insufficiency group than in the B12 sufficiency group in women over two years. Previous studies have reported that low B12 levels negatively affect ASMI and HGS. Gedmantaite et al. investigated the association between diet and HGS and showed a positive correlation between B12 intake and HGS in women [34]. In a prospective study of 403 older adults aged >60 years, total skeletal mass, lean body mass and skeletal muscle mass index were lower in the B12 insufficient group than in the B12 sufficient group [8]. Furthermore, in a previous cross-sectional study of 2325 community dwellers in Korea, B12 insufficiency was associated with a high prevalence of low ASMI, but not SPPB [14]. The following explanations can explain the discrepancies in results: *As a* limitation of the previous cross-sectional study, it was difficult to clarify the longitudinal relationship between B12 insufficiency and sarcopenia over time. Since a short period of two years may not be enough for B12 insufficiency group to affect ASMI and HGS, a study of longer duration may show statistically significant results. Moreover, a previous study included all community-dwelling individuals. However, this study excluded sarcopenic participants with a risk of sarcopenia who fulfilled any one of the criteria of sarcopenia. Therefore, there was a difference in the baseline population, which may have caused discrepancies. Furthermore, in this study, analysis was performed according to sex, whereas in previous studies, analysis was not performed by sex. Because sarcopenia is defined as low ASMI and either low HGS or physical performance, the effect of B12 insufficiency on these parameters may increase the incidence of sarcopenia in women. Accordingly, the impact of B12 insufficiency seems to act on both muscle mass and physical performance but varies depending on the sarcopenic health status and sex.
In this study, B12 insufficiency negatively impacted physical performance and the incidence of sarcopenia in women only. This indicates that the lack of B12 in women significantly affects physical performance at both baseline and the degree of decline over time. Although the reason for these conflicting results between the sexes is not known, the following gonadal hormone hypotheses could partially explain. Testosterone, the male sex steroid hormone, is much higher in men than in women and it is known to play an important role in central nervous system development [35,36,37]. One of the lesser known actions of testosterone is neuroprotection by mediating neuronal differentiation and increasing neurite overgrowth via activation of androgen pathways [38]. Furthermore, previous studies have revealed that testosterone has protective effects against spinal cord injury induced by glutamate and ischemia/reperfusion and reduces the extent of spinal cord damage [39]. This suggests that axonal injury may occur only in low B12 settings as well as low testosterone levels, such as in women, suggesting that B12-induced axonal injury may be less pronounced in men with relatively high testosterone levels. Therefore, in men, B12 insufficiency alone may not be associated with sarcopenia because of the neuroprotective effects of testosterone. However, additional in vivo or randomized controlled studies are needed to support our hypothesis.
This study had several limitations. First, the intake of B12 supplements was not considered in this study. Because B12 is included in commercial multivitamin supplements, it may be helpful to investigate the effects of the intake of these supplements. Second, B12 insufficiency was defined only by serum B12 levels without considering other B12 insufficiency markers, including methylmalonic acid and homocysteine, which reflect the biochemical action of B12. Third, the amount of protein intake, nutrition status and daily physical activity of the participants were not investigated. Fourth, the number of participants in the B12 insufficiency group was relatively small (40 men and 41 women) compared to the B12 sufficiency group. Fifth, peripheral neuropathy induced by B12 insufficiency can impair physical performance. However, since we did not perform an electrical diagnostic study, such as a nerve conduction study, we could not confirm peripheral neuropathy. Finally, the two-year follow-up period was relatively short. A longitudinal study with a longer duration may demonstrate a significant effect of B12 insufficiency on other component parameters of sarcopenia.
## 5. Conclusions
In conclusion, this study was the first longitudinal cohort study to investigate the association between B12 insufficiency and component parameters of sarcopenia in non-sarcopenic older adults. In this study, we found that B12 insufficiency negatively impacts physical performance defined as SPPB and increases the incidence of sarcopenia based on the AWGS 2019 criteria only in women. On the contrary, B12 insufficiency had no apparent influence on the incidence of sarcopenia in men.
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|
---
title: Metabolite Profiling to Evaluate Metabolic Changes in Genetically Modified
Protopanaxadiol-Enriched Rice
authors:
- Ji-Eun Sim
- Sung-Dug Oh
- Kiyoon Kang
- Yu-Mi Shin
- Doh-Won Yun
- So-Hyeon Baek
- Yong-Eui Choi
- Sang-Un Park
- Jae-Kwang Kim
journal: Plants
year: 2023
pmcid: PMC9967978
doi: 10.3390/plants12040758
license: CC BY 4.0
---
# Metabolite Profiling to Evaluate Metabolic Changes in Genetically Modified Protopanaxadiol-Enriched Rice
## Abstract
Event DS rice producing protopanaxadiol (PPD) has been previously developed by inserting Panax ginseng dammarenediol-II synthase gene (PgDDS) and PPD synthase gene (CYP716A47). We performed a gas chromatography–mass spectrometry (GC–MS)-based metabolomics of the DS rice to identify metabolic alterations as the effects of genetic engineering by measuring the contents of 65 metabolites in seeds and 63 metabolites in leaves. Multivariate analysis and one-way analysis of variance between DS and non-genetically modified (GM) rice showed that DS rice accumulated fewer tocotrienols, tocopherols, and phytosterols than non-GM rice. These results may be due to competition for the same precursors because PPDs in DS rice are synthesized from the same precursors as those of phytosterols. In addition, multivariate analysis of metabolic data from rice leaves revealed that composition differed by growth stage rather than genetic modifications. Our results demonstrate the potential of metabolomics for identifying metabolic alterations in response to genetic modifications.
## 1. Introduction
Rice (*Oryza sativa* L.) is extensively cultivated worldwide and is consumed by more than half of the world’s population [1]. Rice crops can easily absorb the three major nutrients (carbohydrates, proteins, and fats), minerals and vitamins. Rice has been widely cultivated using genetic engineering to increase its nutrients and productivity. In particular, genetically modified (GM) rice has been extensively studied, focusing on developing functional rice with additional specific nutrients [2].
Panax ginseng is a well-known widely used medicinal plant. Dammarane-type triterpenoid saponins are the main pharmacologically active components of ginseng. Dammarane-type ginsenosides are classified into protopanaxadiol (PPD) and protopanaxatriol (PPT) based on their aglycone structures [3]. PPD is a ginsenoside intermediate existing in trace or undetectable amounts on ginseng root [4]. PPD exhibits various pharmacological activities with wide anti-cancer properties and is also involved in immune system regulation [5]. The artificial PPD collection from ginseng is challenging as it requires complex deglycosylation through enzymatic and chemical–physical treatments [4]. Therefore, to facilitate the absorption of medicinal components, we previously developed event DS rice that synthesizes PPD by overexpressing Panax ginseng dammarenediol-II synthase gene (PgDDS) and protopanaxadiol synthase gene (CYP716A47) driven by a rice endosperm-specific α-globulin promoter [6]. PgDDS and CYP716A47 are enzymes that activate the synthesis from squalene to PPD [7]. In a previous study, Han et al. [ 2019] demonstrated that PPD is well expressed in DS rice seeds. However, PPD was not detected in non-GM rice seeds. Ginseng is mainly used when the root is 4–6 years old, and its pharmacological components are obtained in the form of ginsenosides, not PPD. However, because the cultivation period of rice is approximately 6–7 months, pharmacological components in the form of PPD can be ingested rapidly [6,8].
A metabolomic approach can be used to evaluate the compositional changes in the developed GM rice. Metabolomics is a research field that investigates metabolic associations by identifying metabolite changes and characteristics [9]. Correlations between metabolites are the net result of enzymatic changes and cellular control of the transcriptional or biochemical events. Metabolomic approaches, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), are widely used for separating samples with biological status, quality, or genetic differences [10]. Metabolomics has been steadily used to identify intended compositional changes in GM crops [9,11,12]. Thus, the metabolomics approaches have been developed to identify predicted or unpredicted changes in metabolic networks and have become an important tool in safety assessment of GM plants. Recently, the application of metabolomics methodology has been shown to be useful for the evaluation of unintended changes to chemical compositions in GM plants such as resveratrol-enriched rice, β-carotene-enhanced soybean, and β-carotene-enhanced rice [9,11,13]. However, to the best of our knowledge, metabolomics studies of rice synthesizing PPD have not yet been conducted. Therefore, the metabolic changes resulting from the genetic modification of DS rice must be evaluated. In this study, metabolomics-based identification of the metabolic alterations in DS rice was performed.
## 2.1. Multivariate Analysis of Rice Seed
Metabolic profiling of control Dongjin rice (DJ) and GM rice (DS1 and DS8) seeds was performed by analyzing the hydrophilic and lipophilic compounds. Sixty-five metabolites were identified, including phytosterols, tocopherols, policosanols, amino acids, sugars, sugar alcohols, and organic acids in rice seeds (Tables S1 and S2). The metabolite information was submitted to MetaboLights public repository (database no. MTBLS6937). Multivariate analysis, which is used to distinguish patterns in various datasets of results [14], was performed to compare metabolite differences.
PCA can be used to assess differences in samples based on their metabolite levels. In this PCA model, two high-ranking principal components (PC) explained for $73.5\%$ of the total variance within the dataset (PC1, $55.4\%$; PC2, $18.1\%$) (Figure 1). Although clustered by groups (DJ, DS1, and DS8), the DJ and DS rice seeds were not separated in PC1 of the score plot. Therefore, a PLS-DA model was generated to identify metabolic differences (Figure 2A).
PLS-DA rotates the PCA projection to obtain the maximum separation of variables by class [1]. In this study, DJ, DS1, and DS8 rice were used as classes for model validation. R2 and Q2 are validation parameters that represent the model quality. R2 specifies the ratio of variation in data provided by the model, and Q2 specifies the ratio of variation in data predicted by the model. An R2 value closer to 1 indicates a good fit for the prediction model, and Q2 > 0.5 indicates a good predictive ability [1]. Our PLS-DA model showed an R2Y of 0.959 and Q2 of 0.885. DJ rice and the two DS rice were clustered separately by PLS1. These results reflect intentional changes caused by the genetic modification of rice seeds. To identify the metabolites contributing to separation, a loading plot was generated (Figure 2B), which showed that the levels of most metabolites (such as sucrose, sugar alcohols, amino acids, phytosterols, and tocopherols) were positive for PLS1. Metabolites with positive values in PLS1 were present at higher levels in DJ rice seeds. The value of variable importance in the projection (VIP) was used to confirm the contribution of the PLS-DA model metabolites (Figure 2C). VIP values > 1 indicated a significant contribution to the model. Metabolites such as fumaric acids, proline, tocotrienols, tocopherols and phytosterols were highly ranked in the VIP plot. Highly ranked metabolites of VIP significantly contributed to the separation between DJ and DS rice.
## 2.2. Tocopherol and Phytosterol Content in Rice Seed
To confirm the significant difference ($p \leq 0.05$) in metabolites between DJ and DS rice, one-way analysis of variance (ANOVA) was performed for metabolites with VIP values > 1.0 in Figure 2C. The false discovery rate (FDR) method was used to control for false positive outcomes across the analytes (Table S3). Significant differences ($p \leq 0.05$) in the metabolites of DJ, DS1, and DS8 rice were identified using bar graphs. Eleven metabolites were significantly different between DJ and DS rice (Figure 3). Of these, seven were lipid metabolites (including α-tocopherol, γ-tocopherol, α-tocotrienol, γ-tocotrienol, cholesterol, stigmasterol, and β-sitosterol). DJ rice produced higher levels of tocopherols, tocotrienols, and phytosterols than DS rice, indicating that fewer tocopherols, tocotrienols, and phytosterols were synthesized in DS rice that synthesizes PPD. In DS rice, PgDDS is expressed to synthesize dammarenediol-II from 2,3-oxidosqualene, and then CYP716A47 is expressed to synthesize PPD (Figure 4). PPD synthesis is a part of the mevalonate (MVA) pathway [6]. Similar to PPD, phytosterols are synthesized by the MVA pathway [15]. Therefore, PPD synthesis is correlated with phytosterol suppression. In a previous study, transgenic tobacco synthesizing PPD through the recombination of PgDDS and CYP716A47 decreased the phytosterol (stigmasterol, β-sitosterol, and campesterol) content. Because PPD and phytosterols are synthesized from the same precursor, 2,3-oxidosqualene, the lower phytosterol contents in transgenic rice may be due to the competition for precursors [7]. Our results were consistent with those of previous study [7]. In our study, phytosterol and tocopherol contents were less accumulated in DS rice, presumably due to the high precursor consumption during PPD synthesis. Furthermore, these results suggest that the contents of tocotrienols, tocopherols, and phytosterols in DJ and DS rice differ owing to the influence of genetic modification.
## 2.3. Multivariate Analysis of Rice Leaves
Rice leaves synthesize and store energy from photosynthesis and deliver it to storage organs, such as seeds. Therefore, owing to the close correlation between leaves and seeds, metabolite profiling of rice leaves was also performed by analyzing the hydrophilic and lipophilic compounds at different growth stages (8, 12, and 16 weeks). Sixty-three metabolites, including phytosterols, tocopherols, policosanols, amino acids, sugars, sugar alcohols, and organic acids, were identified in rice leaves (Tables S4 and S5). Multivariate analysis was conducted to establish differences in metabolite composition by genotype and growth stage (leaves of DJ and DS rice at 8, 12, and 16 weeks).
In the PCA model, two PCs represented $54.8\%$ of the total variance (PC1, $34.1\%$; PC2, $20.7\%$) (Figure 5A). The PCA results of the leaves were separated by growth stage rather than by genotype. A loading plot was created to identify the contribution of growth stages to metabolite separation (Figure 5B). Rice leaves at 8 weeks showed higher levels of policosanols and phytosterols than those at 12 and 16 weeks. At 12 weeks, rice leaves had high levels of monosaccharides, sucrose, malic acid, and quinic acid. At 16 weeks, rice leaves showed higher levels of proline, TCA cycle intermediates (succinic acid and fumaric acid), and tocopherols than at 8 and 12 weeks.
In this study, the rice was cultivated through the rice transplantation method. Unlike other plants, the transplantation method has mainly been used for rice cultivation as it prevents uneven germination and cold-heat damage in the initial stages of growth and is easy to manage weeds [16]. Rice is usually transplanted between 4 and 6 weeks after sowing them in seedling beds [17]. However, transplantation results in transplantation shock due to root damage and rapid changes in growth conditions. Changes in water content due to root damage can temporarily disrupt metabolic processes in transplanted seedlings and produce metabolites involved in stress response [18]. The increase in phytosterol and policosanol contents in 8-week-old leaves is presumed to be due to the transplantation stress response. Phytosterols are involved in biotic and abiotic stress responses in plants; their accumulation in plants suggests their role in providing tolerance to stress [19]. In addition, stress due to transplantation shock can affect plastid development by downregulating its activity as a plant defense response [18,20]. Our data revealed that tocopherol accumulation was minimal in 8-week-old leaves, suggesting that the non-mevalonate (MEP) pathway inside the plastid is downregulated [18,21].
After rice transplantation, the growth and development of seedlings gradually become more active after the restoration period [16]. Plants produce and store large amounts of energy through photosynthesis. During the growing stage, young leaves fix a large amount of carbon through photosynthesis, which is then used as an energy source in the form of monosaccharides for plant growth [22]. Meanwhile, organic acids such as oxalic acid, succinic acid, and citric acid are either synthesized into sucrose through gluconeogenesis or oxidized through the TCA cycle [23]. In this study, rice leaves during the restoration period produced large amounts of mono-saccharides and sucrose at 12 weeks. The 16-week-old rice, which is in the heading stage, actively synthesized energy through photosynthesis to promote grain growth [24]. Plastids were activated for photosynthesis, and a large amount of tocopherol was accumulated by the MEP pathway in 16-week-old leaves. Unlike other plants, transplanted rice leaves have different amounts of metabolites depending on the growth stage. As a result, rice leaves are presumed to be affected by the external environment or growth stage rather than by genetic modification.
## 3.1. Rice Sample Preparation
DS rice was prepared by inserting the dammarenediol-II synthase gene (PgDDS, GenBank: GU183405.1) and dammarenediol-II 12-hydroxylase gene (CYP716A47, GenBank: JN604536.1) into *Oryza sativa* L. cv. DJ rice [6]. The PgDDS and CYP716A47 genes were derived from the Panax ginseng roots. Rice was sown in seedling beds in May, and transplanted into rice fields in June using the rice transplantation method. Rice was cultivated in an isolated living modified organism (LMO) experimental area (facility registration number: RDA-AB-2013-041) at the National Institute of Agricultural Sciences located in Jeonju (latitude: 35°49′51″ N; longitude: 127°03′55″ E), Republic of Korea. Rice leaves were collected at 8, 12, and 16 weeks, and seeds were harvested at 27 weeks. DS rice expresses PPD only in seeds [6]. Two lines (DS1 and DS8) that adequately express PPD were selected based on their gene expression levels. Samples were converted into powder using a blender (HR2860; Philips, Amsterdam, Netherlands) and stored at −20 °C. PPD in DS seeds were analyzed as previously described [6]. Milled powders (100 mg) from rice grains were soaked in $100\%$ methanol and sonicated for 30 min at 40 °C. The supernatant after centrifugation was collected before injection. Analysis was performed with a Shimadzu LC system (Kyoto, Japan) equipped with a binary pump (LC-20AD), a degasser (DGU-20A), an autosampler (SIL-20A), a column oven (CTO-20AC), a PDA detector (SPD-M20A) on a YMC-Pack Pro C18 RS column (150 × 2.0 mm. D, S-5 µm, 8 nm, YMC Co., Ltd., Kyoto, Japan) at 40 °C. The liquid chromatograph–mass spectrometry ion trap/time-of-fight (LCMS–IT-TOF) (Shimadzu, Kyoto, Japan) was equipped with an atmospheric pressure chemical ionization (APCI) source in the positive and/or negative ion modes. Authentic PPD was directly subjected to the same conditions (Figure S1). The mean PPD concentrations in DS1 rice seeds were 13.00 µg/g dry weight and in DS8 rice seeds were 14.96 µg/g dry weight.
## 3.2. Extraction and Analysis of Hydrophilic Metabolites
Hydrophilic compounds (free amino acids, sugars, sugar alcohols, and organic acids) were analyzed as previously described (Table S6) [9]. A total of 10 mg of ground rice samples were added in a 2 mL tube with 1 mL of methanol:water:chloroform (2.5:1:1, v/v/v) solution. Next, 0.06 mL of ribitol (0.2 mg/mL in methanol) was added as an internal standard (IS). After vortexing, the mixtures were cultured in a thermomixer (5355 model, Eppendorf AG, Hamburg, Germany) with shaking at 1200 rpm and 37 °C for 30 min. The mixtures were centrifuged at 16,000× g at 4 °C for 5 min. The 0.8 mL of supernatant was transferred to a new 2 mL tube, and then 0.4 mL of deionized water was added. After vortexing, the samples were centrifuged at 16,000× g and 4 °C for 5 min, and then 0.9 mL of supernatant was transferred to a new 2 mL tube, incubated with a centrifugal concentrator (CC-105, TOMY, Tokyo, Japan) for 4 h and freeze-dried at −80 °C for 16 h. For methoxime derivatization, 0.08 mL of methoxyamine hydrochloride (MOX, 20 mg/mL) in pyridine was added in samples and cultured with shaking at 1200 rpm and 30 °C for 90 min. Next, 0.08 mL of N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) was treated, and the samples were incubated with shaking at 1200 rpm and 37 °C for 30 min. The sample was transferred to the insert in a gas chromatography (GC) auto sampler glass vial. The hydrophilic metabolites were analyzed with GC-TOF-MS using an Agilent 7890 B GC (Agilent, Santa Clara, CA, USA) with a Pegasus GC-TOF-MS Benchtop (LECO, St. Joseph, MI, USA). The Rtx-5MS column (30 m × 0.25 mm, 0.25-μm i.d. film thickness; Restek, Bellefonte, PA, USA) was equipped in the GC, and the helium gas flow rate was set at 1 mL/min. Then, 0.001 mL of the sample extract was injected in 1:25 ratio split mode. The inlet temperature was set at 230 °C. The oven temperature was set initially at 80 °C for 2 min, followed by ramping to 320 °C (15 °C/min) and holding for 10 min. The ion source and transfer line temperatures were set to 250 °C and 280 °C, respectively. The spectral data were scanned at 85–600 m/z. We confirmed hydrophilic compounds by standards (MSI level 1) in targeted metabolite profiling [25]. ChromaTOF software (LECO, St. Joseph, MO, USA) was used to identify the hydrophilic compounds in rice. The Chroma TOF software package was used to extract raw peaks, filter and calibrate data baselines, align peaks, perform deconvolution analysis, identify peaks, and integrate peak areas. For quantification, the ratio of the relative peak area to that of the IS was determined based on the selected ions.
## 3.3. Extraction and Analysis of Lipophilic Metabolites
Lipophilic compounds (policosanols, tocotrienols, tocopherols, and phytosterols) were detected using a previously described method (Table S7) [1]. Ground samples of 100 mg rice seeds and 20 mg rice leaves were extracted containing 3 mL of $0.1\%$ ascorbic acid in ethanol (w/v) in a 15 mL tube. Next, 0.05 mL of 5α-cholestane (10 µg/mL) was added as the IS. After vortexing, the mixture was cultured in 85 °C water basket for 5 min. A total of 0.12 mL of potassium hydroxide ($80\%$, w/v) was added for saponification and vortexed. The mixture was then cultured in 85 °C water basket for 10 min. The solution was immediately placed in an ice basket for 5 min, and 1.5 mL of deionized water and hexane was added. Subsequently, the solution was mixed for 20 s before centrifugation at 1200× g and 4 °C for 5 min. The supernatant of the solution was transferred to a new 15 mL tube. Hexane (1.5 mL) was added for re-extraction. The hexane fraction was collected in 15 mL tubes. The solution was evaporated under nitrogen gas, and concentrated using the centrifugal concentrator. For derivatization, 0.03 mL of MSTFA and pyridine were added, respectively, and the tube was incubated with shaking at 1200 rpm and 60 °C for 30 min. The lipophilic metabolites were identified using a GC-MS QP2010 Ultra system (GC-qMS) installed with the Rtx-5MS column equipped with an autosampler (AOC-20i, Shimadzu, Kyoto, Japan). The 0.001 mL of sample was injected in 1:10 split mode at an injection inlet temperature of 290 °C. The carrier gas was helium, and the gas flow rate was 1.00 mL/min. The oven temperature was maintained at 150 °C for 2 min, subsequently increased up to 320 °C (15 °C/min) and holding for 10 min. The MS ion source temperature was 230 °C, and the interface temperature was 280 °C. The mass spectra range was 85–600 m/z. Peak analysis was executed in the selected ion monitoring mode. Chromatography and mass spectra were obtained using Lab Solutions GC-MS solution software (4.20 version, Shimadzu, Kyoto, Japan). Qualitative and quantitative analyses were performed as described by our group [26]. Quantification was performed by means of tree-point calibration curves, for which the concentrations of authentic standards ranged from 0.25 to 5.00 μg.
## 3.4. Statistical Analysis
Three biological replicates of rice samples were used per group. PCA and PLS-DA were used to analyze metabolites with the SIMCA software (version 14.1, Umetrics, Umeå, Sweden). Data were normalized using unit variance scaling before multivariate data analysis. A score plot of PCA and PLS-DA was used to visualize the sample grouping, and loading plots supported the classification of groups in score plots. To estimate the differences between rice contents, ANOVA combined with Duncan’s multiple range test was performed using the statistical analysis program SAS enterprise guide 7.1 (SAS Institute Inc., Cary, NC, USA). Additionally, the FDR adjustment of raw p-values was conducted by using ‘MetaboAnalyst5.0’ (https://www.metaboanalyst.ca (accessed on 1 January 2023)). Differences were considered significant if the FDR-adjusted p-value was less than 0.05.
## 4. Conclusions
In this study, we performed metabolic profiling of DJ and DS rice. We obtained results for metabolic profiling of saponin biosynthesis in rice for the first time. PPD was detected in DS rice overexpressing PgDDS and CYP716A47 genes but not in DJ rice. Multivariate analysis of metabolite profiles segregated rice seeds based on genetic differences. Tocopherols, tocotrienols, and phytosterols contributed to this separation. ANOVA test revealed significant differences between DJ and DS rice, with DS rice having lower tocopherol, tocotrienol, and phytosterol contents than DJ rice. Because PPD and phytosterols are synthesized from squalene, the lower phytosterol content in DS rice may be due to competition for the precursor. In addition, rice leaves were separated according to their growth stages rather than by genetic modification. Because PPD is synthesized specifically in seeds, rice leaves are thought to be affected by natural variability rather than by genetic modification. Overall, these results demonstrate that metabolic profiling can be used to assess the effects of genetic modification. Furthermore, metabolic profiling can reflect the natural variability of metabolites associated with the environment. Therefore, targeted metabolite profiling is suggested as an appropriate analytical tool for the intended and unintended metabolic changes in GM rice. Additionally, it can provide valuable information for rice cultivar development.
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---
title: Approaches in Hydroxytyrosol Supplementation on Epithelial—Mesenchymal Transition
in TGFβ1-Induced Human Respiratory Epithelial Cells
authors:
- Rabiatul Adawiyah Razali
- Muhammad Dain Yazid
- Aminuddin Saim
- Ruszymah Bt Hj Idrus
- Yogeswaran Lokanathan
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967984
doi: 10.3390/ijms24043974
license: CC BY 4.0
---
# Approaches in Hydroxytyrosol Supplementation on Epithelial—Mesenchymal Transition in TGFβ1-Induced Human Respiratory Epithelial Cells
## Abstract
Hydroxytyrosol (HT) is an olive polyphenol with anti-inflammatory and antioxidant properties. This study aimed to investigate the effect of HT treatment on epithelial–mesenchymal transition (EMT) in primary human respiratory epithelial cells (RECs) isolated from human nasal turbinate. HT dose–response study and growth kinetic study on RECs was performed. Several approaches on HT treatment and TGFβ1 induction with varying durations and methods was studied. RECs morphology and migration ability were evaluated. Vimentin and E-cadherin immunofluorescence staining and Western blotting [E-cadherin, vimentin, SNAIL/SLUG, AKT, phosphorylated (p)AKT, SMAD$\frac{2}{3}$ and pSMAD$\frac{2}{3}$] were performed after 72-h treatment. In silico analysis (molecular docking) of HT was performed to evaluate the potential of HT to bind with the TGFβ receptor. The viability of the HT-treated RECs was concentration-dependent, where the median effective concentration (EC50) was 19.04 μg/mL. Testing of the effects of 1 and 10 µg/mL HT revealed that HT suppressed expression of the protein markers vimentin and SNAIL/SLUG while preserving E-cadherin protein expression. Supplementation with HT protected against SMAD and AKT pathway activation in the TGFβ1-induced RECs. Furthermore, HT demonstrated the potential to bind with ALK5 (a TGFβ receptor component) in comparison to oleuropein. TGFβ1-induced EMT in RECs and HT exerted a positive effect in modulating the effects of EMT.
## 1. Introduction
Approximately 2.7–$8\%$ of Asians and 5–$15\%$ of the worldwide population are affected by chronic rhinosinusitis (CRS). Rhinosinusitis is characterized by paranasal sinus inflammation, while the symptoms for CRS include nasal blockage, congestion, and mucus discharge. Generally, these symptoms could be alleviated by nasal irrigation, antihistamines, antibiotics, and intranasal corticosteroids [1,2]. However, prolonged inflammation in rhinosinusitis that leads to CRS can also be accompanied by nasal polyps. Given its debilitating nature, CRS generally can affect the patient’s quality of life and productivity.
The normal epithelial cell layer that covers the respiratory tract consists of ciliated, goblet, and basal cell [3]. Prolonged invasion of foreign substances and pathogens damage and injure the epithelial layer. During injury, basal cells downregulate their epithelial protein expression (E-cadherin and cytokeratin) and lose polarity. The cells will highly express mesenchymal proteins (vimentin and αSMA) and regain the ability to migrate to the injury region, proliferate, and eventually differentiate back to ciliated epithelial cells and goblet cells [4,5]. The tissue remodeling and ability of the polarized epithelial cells to gain the mesenchymal phenotype, such as migration, and then differentiate back to epithelial cells, are termed epithelial–mesenchymal transition (EMT) and mesenchymal–epithelial transition, respectively.
EMT activation involves several molecular pathways, such as the TGFβ pathway, Notch pathway, or pathways activated through growth factor binding to tyrosine kinase receptors (RTK), such as hepatocyte growth factor (HGF) and fibroblast growth factor (FGF) [6]. Among these pathways, the TGFβ pathway is the most important pathway in EMT activation. The interaction of the TGFβ growth factor with its receptors (TβRI/Alk5) and TβRII will activate the SMAD-dependent EMT pathway through phosphorylation of SMAD$\frac{2}{3}$ [7].
These molecular mechanisms are important for wound healing and normal remodeling processes. However, prolonged injury or chronic diseases will lead to modification and changes in tissue and organ components and architecture through mechanisms such as EMT, which will eventually lead to a pathological event. Evidence of tissue remodeling such as epithelial damage and basement thickening is present in patients with CRS [8]. It has been demonstrated that EMT and CRS are related [3,9,10]. TGFβ1 increased as wound repair and remodeling took place in patients with CRS [11]. Nasal polyps, which are the result of tissue remodeling, might also be present in patients with CRS [12]. EMT mechanisms have also been reported in both nasal polyps and CRS events. [ 3,12,13,14]. Tissue remodeling is largely irreversible and can cause obstructions and breathing difficulties. These issues will eventually require surgery to improve ventilation, such as functional endoscopic sinus surgery.
Therefore, the modulation of the EMT mechanism should be investigated to manage diseases. Recent studies have reported the ability of natural products to modulate the EMT pathway [15,16,17]. Commonly known as olive, *Olea europaea* (OE) is a promising natural product with proven health benefits due to its phenolic and flavonoid content [18]. Olive oil is the primary source of added fat in the Mediterranean diet, which has been associated with health benefits such as reducing neurodegenerative diseases, improving bone health, and demonstrating anti-cancer properties [19]. Several studies have reported the ability of OE phenolic compounds in EMT modulation in fibrosis and breast cancer cells. However, there have been few scientific studies on the ability of olive fruits to treat airway diseases. Interestingly, olive leaves have been used to treat asthma traditionally [20]. Other than that, OE and its active compounds can also act as antioxidant agents on lung epithelial cells and reduce inflammation in lung tissue [21,22].
Approximately 1–$2\%$ of the OE phenolic compound content comprises of oleuropein, tyrosol, and hydroxytyrosol (HT). The hydrolysis of oleuropein, which typically occurs during olive maturation, oil storage, and preparation of table olives, yields HT [23]. Besides being affected by the process, the amount of HT obtained also depends on the quality of the olive oil and the types of olive. Black olives have a total phenolic content of 16.40 g per kg of dry weight, of which 5.78 g per kg is HT itself. However, the content of HT in green olives is lower at 4.48 g kg [24].
HT is also claimed to be beneficial to health by acting as a cardiovascular health protector, antioxidant, ROS scavenger, anti-inflammatory, anti-cancer, antimicrobial, neuroprotective, prevent osteoporosis and provide skin and eye health benefits [18,23,25,26]. Besides that, HT is also a natural antioxidant with the strongest potential compared to all olive polyphenols. In addition, it also has twice the antioxidant power of coenzyme Q10 [26] Oleuropein, tyrosol and HT been shown to modulate the EMT signaling pathway through ligand binding via the ERK, AKT or WNT pathway [27]. However, there were only several studies that have highlighted the beneficial effect of HT on the modulation of EMT signaling pathway [28,29,30]. Therefore, we investigated the effect of HT supplementation on TGFβ1-induced human respiratory epithelial cells (RECs).
## 2.1. Dose-Dependent Effect of HT on RECs
We examined the dose-dependent effects of HT on normal RECs. The cells treated with up to 5 μg/mL HT maintained their viability after 24 h. However, concentration-dependent inhibition of cell proliferation was observed beginning from 10 μg/mL HT, with a median effective concentration (EC50) of 19.04 μg/mL (123.5 μM) (Figure 1A). The REC viability percentage began to decrease following treatment with 0.6 μg/mL HT (Figure 1B). The concentrations around EC50 (0.05, 0.1, 0.2, 0.5, 1, 15, 30, and 50 μg/mL) were selected for the subsequent experiment.
## 2.2. Long-Term Effect of HT on REC Growth
We supplemented RECs with HT for up to 5 days to study the effect of long-term HT exposure on the cells. The cell number increased from day 1 to day 5 following treatment with low HT concentrations (0.025, 1, 10 μg/mL). This increasing trend was similar to the increasing trend of the total cell number in the untreated REC group. However, starting from day 4, the total cell numbers of RECs treated with 0.025 and 1 μg/mL HT were significantly higher than that of the control, while the total REC number of the 10 μg/mL HT group was not significantly different from that of the control. The 15, 30, and 50 μg/mL HT groups exhibited no significant increase in total cell number (Figure 2A). Meanwhile, RECs treated with 0.025, 1, and 10 μg/mL HT did not have a significantly different proliferation rate compared with the control. The proliferation rates of the RECs treated with 30 and 50 μg/mL HT were significantly lower than that of the control, thereby suggesting that the cells had stopped proliferating (Figure 2B).
## 2.3. HT Modulates EMT Marker Expression
We evaluated the protein expression levels of the RECs to examine the effect of HT on EMT events. Figure 3 depicts the E-cadherin and vimentin expression levels in each treatment group after 72 h. The E-cadherin expression levels in the 1 μg/mL H, 1 μg/mL H+T, 1 μg/mL HT pre-treatment, and 10 μg/mL H groups were significantly higher than those in the untreated and TGFβ1-induced RECs. All HT-treated groups had significantly lower vimentin expression than the TGFβ1-treated RECs, with 10 μg/mL TGF pre-induction leading to the lowest vimentin expression. At 72 h, more than $50\%$ of the cells co-expressed E-cadherin and vimentin. However, the expression difference between the treatment groups was not significant except for the 10 μg/mL TGF pre-induction group (Figure 3).
## 2.4. HT Maintains REC Morphology
The HT concentration of 10 μg/mL was used for subsequent experiments. The morphological changes of all tested groups were evaluated through cell circularity, elongation, cell surface, and cell perimeter analyses (Figure 4). The control RECs had a circularity value of 0.792 ± 0.029, which did not differ significantly from that of the HT-treated RECs (0.686 ± 0.045). This indicated that the control RECs and HT-treated cells were round and not fibroblastic. However, the TGFβ1-induced RECs were significantly different, where they were not circular and were elongated (0.443 ± 0.298). Group H+T demonstrated a similar circularity value to Group T, albeit the increased circularity values (0.532 ± 0.068, 0.5449 ± 0.06, and 0.573 ± 0.04) indicated that the RECs were able to maintain their polygonal shape even after being cultured with TGFβ1 (Figure 4). These results were in line with the cell elongation analysis, where the RECs induced by TGFβ1 (1.693 ± 0.1173) and TGF pre-induction (1.652 ± 0.1078) were more elongated than the RECs in the other groups (C: 1.512 ± 0.06174; H: 1.52 ± 0.08025; H+T: 1.51 ± 0.07461, HT pre-treatment: 1.612 ± 0.13). Additionally, the surface area and perimeter value of the cells induced with TGFβ1 (3311 ± 394 μm2) and TGF pre-induction (2605 ± 750.3 μm2) were higher compared to that of the other groups, indicating that the cell size was increased as compared to the control RECs (569.5 ± 63.16 μm2). HT supplementation maintained the cell surface area and perimeter values in Groups HT (907.5 ± 115.2 μm2), H+T (1440 ± 381.5 μm2), and HT pre-treatment (1065 ± 138.8 μm2).
## 2.5. HT Impedes Migration in TGFβ1-Induced RECs
The migration rate of uninduced and untreated RECs was higher than that of the other groups (7115 ± 357.5 h−1). Group HT pre-treatment had the lowest migration rate (954.6 ± 121.8 h−1) compared to the other treatment groups. After 48 h, the scratch closure percentage of Groups H, H+T, and HT pre-treatment had a lower scratch closure rate (52.07 ± $4.06\%$; 33.39 ± $8.30\%$; 23.05 ± $3.53\%$, respectively) compared to the control RECs (87.9 ± $4.12\%$). Groups T and TGF pre-induction had higher scratch closure rates than the control RECs (Figure 5).
## 2.6. HT Attenuates pAKT and pSMAD2/3 Expression
RECs without TGFβ1 induction or HT treatment demonstrated higher E-cadherin expression compared to the other groups. The TGFβ1-induced RECs had lower E-cadherin expression. However, culturing the RECs with HT prevented the effect of TGFβ1 from further repressing E-cadherin expression. The expression of vimentin as a mesenchymal marker was also examined. The control RECs expressed vimentin, but their expression rate was lower than that of the TGFβ1 group, while vimentin expression was highest in Group TGF pre-induction. HT treatment caused decreased vimentin expression, which was also observed in Groups H+T and HT pre-treatment, where the addition of HT was accompanied by decreased vimentin expression as compared to the control group (Figure 6). In addition to E-cadherin and vimentin, SNAIL/SLUG expression was also observed. HT and TGFβ1 caused increased SNAIL/SLUG expression. However, Group HT pre-treatment had lower SNAIL/SLUG expression than the TGFβ1-induced group (Figure 6). Furthermore, the effect of HT on AKT and SMAD$\frac{2}{3}$ phosphorylation was studied. TGFβ1 increased the phosphorylation activity on the AKT marker protein in normal RECs while the addition of HT reduced AKT phosphorylation activity. Among the three treatment groups (H+T, TGF pre-induction, HT pre-treatment), RECs in group TGF pre-induction had high AKT phosphorylation activity even when treated with HT (Figure 6). A similar reduction pattern of SMAD$\frac{2}{3}$ marker protein phosphorylation activity was observed for the TGFβ1-induced RECs when treated with HT (Figure 6).
## 2.7. Molecular Docking of HT Acetate, HT, Tyrosol and Oleuropein
Four active compounds (HT, HT acetate, tyrosol, oleuropein) were used for molecular docking analysis to study the interaction between ligands and proteins. Among the four compounds, HT acetate had the lowest binding energy value, followed by HT, tyrosol, and oleuropein. Apart from hydrogen binding, HT acetate had the most hydrophobic interactions compared to the other compounds (ILE211, VAL219, ALA230, LYS232, TYR249, LEU260, LEU278, LEU340). However, only one hydrogen bond linked HT acetate to the amino acid LYS232 (Figure 7), while three hydrophobic interactions were recorded for HT, namely on LYS232, LYS232, and LEU260. A hydrogen bond at LYS232, LEU278, and ASP351 was observed between HT and the ALK5 receptor (Figure 7). Tyrosol interacted hydrophobically at LYS232 and LEU260 and demonstrated hydrogen binding at LYS232, SER280, and ASP351 (Figure 7). Oleuropein had the highest binding energy and had five hydrogen bonds at LYS213, GLU245, SER280, SER287, and LYS337, which bound it to the protein ALK5. In addition, there was a hydrophobic interaction between oleuropein and ALK5 at VAL219, ALA230, LYS232, LEU278, and LEU340 (Figure 7).
## 3. Discussion
The olive is a well-known fruit with health beneficial properties, such as anti-inflammatory and antioxidant functions [31]. These favorable attributes are associated with the presence of phenolic compounds, such as oleuropein, oleocanthal, HT, and tyrosol, in the olive fruit [32,33,34].
Features similar to EMT events were reported in inflammatory diseases such as CRS [14,35,36]. Persistent injury, consistent inflammation, and signaling factors, such as TGFβ activation, are among the reasons for the occurrence for tissue remodeling processes. Chronic inflammation, such as in CRS, is generally accompanied by tissue remodeling, which is important to restore the structural and physiological function of damaged tissue during healing. However, prolonged inflammation can cause pathological changes, such as extracellular matrix (ECM) deposition, goblet cell hyperplasia, subepithelial edema, epithelial layer shedding, and basement membrane thickening, which can occasionally lead to nasal polyps [8,37].
Another adverse outcome of tissue remodeling is fibrosis. Typically, during normal physiological repair, myofibroblasts aid the secretion of ECM proteins and healing, and undergo apoptosis when re-epithelization is complete. However, prolonged myofibroblast activity can cause fibrosis. EMT may contribute to the existence of myofibroblasts during fibrosis. In a mouse model study, Kim et al. [ 38] demonstrated that RECs differentiated into fibroblasts and myofibroblasts during EMT and caused fibrosis.
These transitions can be investigated by observing the changes in epithelial and mesenchymal protein markers. The expression levels of epithelial protein markers, such as E-cadherin and ZO-1, are decreased in cells undergoing EMT. E-cadherin and ZO-1 are among the important components of the epithelial adherens junction. Reductions in these protein markers suggested that epithelial cells had begun to detach from one another and migrate [39]. The expression levels of mesenchymal protein markers, such as vimentin and αSMA, increase as cells begin to change to a mesenchymal phenotype.
Previously, we observed the potential of O. europaea extracts in preventing TGFβ1-induced EMT in human nasal RECs [32]. In the present study, we examined the potential of a O. europaea phenolic compound, i.e., HT, to modulate TGFβ1-induced EMT in human RECs. We also explored approaches in HT supplementation on EMT in TGFβ1-induced human RECs.
Among the O. europaea phenolic compounds, HT modulates the EMT signaling pathway. HT is produced from the hydrolysis of oleuropein, which takes place during fruit maturation, fruit processing, and the ingestion of olive fruits [40]. The potential therapeutic effect of HT was covered extensively in a review by Hu et al. [ 23], who reported that HT has anti-cancer, cardioprotective, and neuroprotective potential in addition to being a natural antioxidant.
EMT can be divided into type 1 (occurs during development), type 2 (occurs during wound healing and fibrosis), and type 3 (occurs during cancer progression) [6]. Although the EMT outcome can be pathologically different, e.g., cancer vs. fibrosis, a common set of pathways enables EMT. HT decreased the expression levels of the WNT co-receptors LRP6, β-catenin, SNAIL, and SLUG and increased E-cadherin expression in a breast cancer cell line [30]. Furthermore, HT reduced AKT and ERK expression levels in skin cancer, colon cancer, and hepatocellular carcinoma cells [30,41]. WNT, AKT, and ERK are proteins involved in EMT. However, only a few studies to date have investigated the effect of HT on EMT diseases other than cancer. Natural products, such as wheatgrass and quercetin, can modulate type 2 EMT diseases, such as renal fibrosis and lung fibrosis [17,42], when similar pathways are targeted. Therefore, in the present study, we induced normal human RECs with TGFβ1 to mimic the EMT conditions that occur during rhinosinusitis.
Experiments on other cell types demonstrated that HT modulated EMT according to the dose and treatment approach. Nevertheless, there has been no published study on the cytotoxic effects of HT on RECs. However, the data demonstrated clearly that high HT concentrations cause cytotoxic effects. Han et al. reported that 12-h treatment with 50 μg/mL HT (324 μM) induced apoptosis in MCF-7 cells [28]. Warletta et al. reported no significant changes in growth in cells that had been treated for 24 h with 100 μM HT (15.4 μg/mL) [43], where REC viability began to decrease at 10 μg/mL HT, thereby indicating that the RECs underwent cell death at high HT concentrations. Cell growth is important for wound healing mechanisms and tissue repair. Higher concentration of HT might cause cell death; meanwhile, exposure to a low concentration of HT might not be effective in giving the intended effect. Optimal HT concentration need to be chosen to proceed with the study. Therefore, we used 0.025, 1, 10, 15, 30, and 50 μg/mL HT for the long-term growth kinetics study. HT did not exert long-term effects on RECs at concentrations < 10 μg/mL, where REC proliferation increased significantly from day 0 until day 5. However, the total cell numbers of the RECs treated with 15, 30, and 50 μg/mL HT did not increase significantly after day 1. This result was also observed in the REC proliferation rate, which decreased and was significantly lower than that in the control.
Next, we examined EMT activation in RECs via the expression of protein markers after HT treatment, where the experiment was performed with 1 and 10 μg/mL HT. These concentrations were chosen based on the slight increase in the REC proliferation rate following treatment with 1 μg/mL HT as compared with the control, and 10 μg/mL HT was selected as it represented the initial point of gradual decrease in cell proliferation. The cell viability and proliferation were not significantly different between both concentrations. However, the vimentin and E-cadherin expression of the treated cells differed between treatment approaches, suggesting that HT potentially modulates the EMT event.
In this study, six conditions were used to mimic the possible conditions during an EMT event. Group H+T emulated the event in which HT was administered simultaneously with the EMT event. TGF pre-induction mimicked the event in which EMT occurred first, followed by HT treatment. For HT pre-treatment, HT supplementation was administered throughout the period, and EMT occurred during that time.
The effects of HT treatment and the duration of exposure to these active compounds in vitro were not widely reported. Olive leaf extract (OLE), olive oil, and HT exerted protective effects on cells and animal models [44,45,46,47,48,49,50,51]. These findings demonstrated that OE and its active compounds exert a protective effect on cells if administered before the insult occurs. The effects of using natural products in pre-treatment of EMTs were widely reported [45,52,53,54]. Therefore, we examined the effects of HT treatment methods in this study.
EMT is a dynamic and reversible event. Hence, most cells generally undergo partial EMT, in which one cell can express mesenchymal (vimentin) and epithelial (E-cadherin) phenotypes. Vimentin and E-cadherin are the downstream markers of several EMT pathways, such as the SMAD, AKT and MAPK pathways [55].
In this study, TGFβ1-induced RECs demonstrated a larger surface area, larger cell perimeter, and a higher migration rate compared to untreated RECs. Furthermore, the TGFβ1-induced RECs exhibited higher vimentin and SNAIL/SLUG expression but lower E-cadherin expression. Additionally, TGFβ1 caused AKT and SMAD$\frac{2}{3}$ phosphorylation. AKT signaling pathway activation is the reason that the RECs in the TGF group were larger than the untreated RECs. Our findings were in line with those reported by previous studies, where TGFβ1 induction activated the SMAD$\frac{2}{3}$ and AKT signaling pathways in cells [56,57,58].
The effect of HT on the TGFβ1-induced RECs was clearly observed in the H+T groups, where the addition of HT aided REC size and shape retention. Additionally, HT also reduced the cell migration rate, reduced vimentin protein expression, and decreased pAKT and pSMAD$\frac{2}{3}$ expression. Decreased pSMAD2 and pSMAD3 protein expression indicated the inhibition of TGFβ1-induced EMT [6]. Lupinacci et al. reported that OLE inhibited the migration of Met5A cells with TGFβ1-induced EMT [59]. In these cells, OLE treatment successfully decreased the fibrogenic and EMT expression markers (αSMA, N-cadherin, vimentin, fibronectin), where reduced fibrogenic expression led to reduced cell motility and migration. Moreover, the authors demonstrated the ability of OLE to reduce SNAIL, pSMAD3, and pSMAD4 protein expression. OLE contains similar phenolic compounds to the extract of olive fruits, i.e., oleuropein and HT.
We also observed the effect of HT on cells that had undergone EMT. First, the RECs were induced using TGFβ1 for 48 h before HT treatment. However, HT could not restore the original REC morphology and did not impede cell migration or decrease the expression levels of the protein markers vimentin, pAKT, and pSMAD. The findings indicated that HT cannot aid the reduction of the effects of EMT in cells that have undergone EMT.
The pre-treatment effects of HT before EMTs are also studied. RECs were found to maintain cell size similar to normal RECs and stop cell migration well compared to all groups studied. In addition, TGFβ1-induced RECs treated using HT before induction were found to maintain E-cadherin marker expression, and lower expression of SNAIL/SNUG protein markers, vimentin, pAKT and pSMAD. This suggests that HT has the ability to protect cells from EMTs.
The protective effect of natural compounds in preventing or reducing the effects of EMT has been reported previously [52,53,54,60,61]. During EMT activation, ligand binding to TGFβ receptor causing formation of SMAD complex. During EMT activation, ligand binding to TGFβ receptor causes SMAD complex formation. The complex will eventually bind to the SNAIL1 promoter and activate SNAIL transcription, which will lead to suppression of the gene related to E-cadherin [6]. In TGFβ1-induced cells, curcumin pre-treatment inhibited SNAIL expression by inhibiting SMAD2 phosphorylation and inhibiting SNAIL nuclear translocation and suppressing its transcription [52]. Wang et al. [ 2019] hypothesized that amygdalin (an active compound from bitter almonds) may compete for TGFβ1 receptors, thus affecting SMAD2 and SMAD3 phosphorylation [62].
Therefore, we examined the effect of ligand binding on TGFβ1 receptor type 1 or ALK5 using in silico molecular docking. Binding energy is generated when a molecule interacts with its target, where a lower binding energy value indicates more stable attachment of the complex to the target. Several small molecules, such as LY2109761, galunisertib (LY2157299), LY364947, and SB505124, attach to ALK5 and affect its activity. ALK5 inhibitors specifically replace ATP adhesion to the ALK5 kinase domain that would originally phosphorylate SMAD2 and SMAD3. The ALK5 blockade will cause SMAD signaling pathway blockade [63]. In this study, we have reported the binding energies of hydroxytyrosol acetate (−4.37 kcal/mol), hydroxytyrosol (−3.54 kcal/mol), tyrosol (−394 kcal/mol) and oleuropein (+5.28 kcal/mol). It can be seen that HT acetate has the lowest value followed by hydroxytyrosol and tyrosol. This indicates that HT has the potential to bind to ALK5 while inhibiting the phosphorylation activity of the protein associated with it. However, when compared to known ALK5 inhibitors, such as LY364947 (−10.2 kcal/mol), SD-208 (−10.0 kcal/mol) and SB505124 (−10.2 kcal/mol) the binding energy for the tested compound is indeed lower compared to the aforementioned ALK5 inhibitors [63].
Although our understanding of the effect of HT on cells in which EMT has been induced remains incomplete, HT can nevertheless modulate an EMT event. To determine the effect of HT on EMT marker expression, the effect of the experimental conditions of our study on protein and gene expression levels should be investigated to assess the EMT status. The effect of HT on the EMT pathway should be investigated by considering the activation of specific upstream EMT markers, such as SMAD, AKT, and ERK, to determine the exact effect of HT on EMT. Furthermore, to understand HT modulation of cell survival and proliferation, the activation of downstream EMT markers, especially in the AKT pathway, e.g., GSK-3β, should be investigated.
## 4. Materials and Methods
This study was approved by the Universiti Kebangsaan Malaysia Research Ethics Committee (FF-2017-363). All methods and experiments were performed in accordance with the relevant guidelines and regulations issued by the committee.
Redundant human nasal turbinate tissues were obtained with written consent from four Asian patients who had undergone turbinectomy. The turbinate tissue was washed with Dulbecco’s phosphate-buffered saline (DPBS; Gibco, NY, USA) to remove blood and mucus. Next, the epithelial layer was separated from the tissue and minced before being digested in $0.6\%$ collagenase type I (Worthington, Lakewood, NJ, USA) for 60 min in a shaker incubator at 37 °C. After complete tissue digestion, the sample was centrifuged for 5 min at 2370× g. Then, the supernatant was discarded, the pellet washed with DPBS, and recentrifuged for 5 min at 2370× g.
The cell pellet was suspended in growth medium consisting of airway epithelial growth medium (PromoCell, Heidelberg, Germany), defined keratinocyte serum-free medium (Gibco, NY, USA) and Dulbecco’s modified Eagle’s medium:Nutrient Mixture F-12 supplemented with $5\%$ fetal bovine serum (BioWest, Nuaillé, France) in a 1:1:2 ratio and seeded into a 6-well plate (Thermo Fisher Scientific, Waltham, MA, USA). The cells were cultured at 37 °C in $5\%$ CO2 in an incubator.
The medium was changed every 2 days until the cells were 80–$90\%$ confluent. Subsequently, the REC and fibroblast co-culture was differentially trypsinized to remove fibroblasts from the culture plate. The medium was changed every 2 days until the cells were 80–$90\%$ confluent before being trypsinized in passages 1 (P1) and 2 (P2), which were used in subsequent experiments.
## 4.1. Cytotoxicity Assay
We purchased 3-Hydroxytyrosol (HT) (catalog no. H4291) from Sigma-Aldrich (St. Louis, MO, USA). The cytotoxic effect of HT was evaluated using a Vybrant™ 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) cell proliferation assay kit (Invitrogen, Waltham, MA, USA) following the manufacturer’s recommendations. The effect of short-term HT exposure on RECs was studied by growing P1 RECs in a 48-well plate and treating them for 24 h with 0.025–200 μg/mL HT. One untreated group was used as the control. Subsequently, medium from the HT-treated groups and untreated group was removed and replaced with 200 μL fresh basal medium. Three wells containing basal medium only were prepared as the blank/medium control. A total of 20 μL of MTT solution (final concentration, 0.5 mg/mL) were added to the wells, incubated for 4 h at 37 °C before 200 μL of $10\%$ sodium dodecyl sulphate–HCl (SDS-HCl) solution was added and incubated further for another 4 h. The solution in the wells was divided into two replicates, and 210 μL solution was transferred into one well of a 96-well plate before the absorbance was read at 570 nm. Several optimum concentrations (0.05, 0.1, 0.2, 0.5, 1, 15, 30, and 50 μg/mL) were chosen to be used for further experimentation.
## 4.2. Quantification of Total Cells Attached and Cell Proliferation
The treated and untreated RECs were observed for 5 days to determine the long-term effect on cell growth in the HT-treated RECs. At day 0, images of five independent fields were captured randomly. These initial points will be saved in the NIS-Elements integrated Nikon microscope software. The same point will be used to capture the same image field until day 5. The total number of cells attached to the surface and the proliferation rate were calculated and quantitated using the following equation:Total cells attached=Average cell countObjective area of the microscope Proliferation rate (h)−1=ln Total cells attached final÷Total cell attached initialTime
## 4.3. HT Supplementation and TGFβ1 Induction
RECs at approximately $40\%$ confluency were seeded and tested in six conditions (Figure 8): [1] untreated (C); [2] TGFβ1-supplemented (T); [3] HT-supplemented (H); [4] 72-h simultaneous supplementation of TGFβ1 and HT (H+T); [5] addition of HT after 24-h TGFβ1 supplementation and culturing in the presence of both factors for another 48-h (TGF pre-induction); [6] addition of TGFβ1 after 24-h HT supplementation and cultured in the presence of both factors for another 48 h (HT pre-treatment). The TGFβ1 concentration used in this study was 10 ng/mL.
These six approaches were tested to mimic possible conditions during treatment of an EMT event, i.e., an EMT event within CRS. Group H+T represented the event where the HT treatment took place simultaneously with the EMT event. TGF pre-induction mimicked the event in which EMT or disease, i.e., CRS, occurred first and was then treated with HT. For HT pre-treatment, the HT supplementation was administered before the EMT event occurred and subsequently continued concurrently with the EMT event or the disease.
## 4.4. Immunocytochemical Analysis
The RECs were treated with HT and TGFβ1 (Figure 8). Then, E-cadherin and vimentin expression levels were evaluated using immunocytochemical analysis following the method of Rabiatul et al. [ 32]. The cells were washed with DPBS, fixed in $4\%$ paraformaldehyde for 30 min (Sigma-Aldrich, USA), permeabilized for 20 min with $0.5\%$ Triton X-100 solution (Sigma-Aldrich), then blocked with $10\%$ goat serum for 1 h at 37 °C. Subsequently, the cells were incubated with 1:200 mouse anti-E-cadherin antibody (ab1416) and 1:200 rabbit vimentin antibody (ab92547; Abcam, Cambridge, UK) overnight at 4 °C. The following day, the cells were washed before being incubated with 1:300 diluted Alexa Fluor 594 anti-rabbit IgG (Invitrogen, Waltham, MA, USA) and Alexa Fluor 488 anti-mouse (Invitrogen, Waltham, MA, USA) for 1 h at 37 °C. The nuclei were counterstained with 4′, 6-diamidino-2-phenylindole (DAPI). Fluorescence images were captured with an ECLIPSE Ti fluorescence microscope (Nikon, Tokyo, Japan). The total number of cells expressing E-cadherin and vimentin was calculated from the images of five randomly selected independent fields following the equation described earlier. The images were analyzed using NIS-Elements integrated Nikon microscope software.
## 4.5. Cell Morphology Analysis
The morphological changes of all groups were evaluated through cell circularity, elongation, cell surface, and cell perimeter analyses (Figure 8). REC images from all groups were captured in five random independent fields and analyzed using ImageJ v1.53. The images were processed using the Smooth and Sharpen options before being analyzed. The parameters were selected in Analyze > Set Measurement. Then, the cell shape was traced using Freehand Selection. Next, the parameters were measured and calculated with CTRL + M. The results obtained from the process were cell surface area, cell perimeter, cell roundness, Feret, and mean Feret. Cell elongation (aspect ratio) was calculated as follows: Feret × MinFeret.
## 4.6. Cell Migration Analysis
RECs that were $100\%$ confluent were washed with DPBS before new medium was placed in the culture container. Scratches were made in the REC monolayer using a 100-µL pipette tip. Subsequently, TGFβ1 or HT was added according to the experimental requirements. The culture container was placed in the imaging system directly, where the device took pictures every 20 min at a predetermined point for 48 h. Then, the value was used to derive the migration rate and percentage of scratch closure.
## 4.7. Western Blot Analysis
The RECs were seeded into 6-well plates and treated as described earlier. The cells were lysed in radioimmunoprecipitation assay buffer containing protease inhibitors and phosphatase inhibitors. Proteins were separated by $10\%$ SDS–polyacrylamide gel electrophoresis and transferred onto nitrocellulose membranes, which were blocked with $5\%$ skim milk. The blots were incubated with primary antibodies against E-cadherin (1:1000; ab1416; Abcam), vimentin (1:1000; ab92547; Abcam), AKT (MAB2055; R&D Systems, MN, USA), phosphorylated (p)AKT (1:1000; ab38449; Abcam), SMAD$\frac{2}{3}$ (AF3797; R&D Systems), pSMAD$\frac{2}{3}$ (1:1000; ab63399; Abcam), SNAIL/SLUG (1:1000; ab180714; Abcam), and β-tubulin (1:2000; ab15568; Abcam). The blots were incubated with horseradish peroxidase-conjugated secondary antibodies [anti-mouse (1:10,000; Abcam) and anti-rabbit (1:10,000; Sigma-Aldrich)] and visualized using an enhanced chemiluminescent system through gel documentation with an Amersham Imager 600. In addition to conventional Western blotting, automated protein separation and immunoblotting of the Western blots were performed using a Jess system (ProteinSimple, Bio-Techne, MN, USA). The proteins were normalized following the manufacturer’s instructions to normalize sample loading variability.
## 4.8.1. Ligand Preparation
AutoDock 1.5.6 was used for docking to investigate ligand binding to macromolecules (receptors). The HT, HT acetate, tyrosol, and oleuropein 3D structures were obtained from the PubChem database. Then, their structural files were converted to GDP using Open Babel. Next, the PDB file was converted to PDBQT using AutoDock.
## 4.8.2. Receptor Provision
Based on previous studies, the ALK5 crystallization structure (PDB ID: 1RW8, resolution: 2.4 Å) was selected from the RCSB Protein Data Bank (PDB) database. Prior to docking, heteroatoms and water molecules were removed from the ALK5 structure. Then, polar hydrogen and Kollman charges were added using AutoDock. Next, the structure was saved as a PDBQT file.
## 4.8.3. Molecular Docking
The ALK5 grid box was determined using AutoGrid according to previous studies. The grid box parameters are as follows: grid box sizes, 16, 16, and 16; X, Y, and Z coordinates, 3.753, 15.918, and 9.96; grid point spacing, 1.0 Å. Ten confirmation modes and their respective binding forces were generated using AutoDock. The lowest binding energy yield was used for further analysis. The ALK5 protein complexes and ligands were observed using protein–ligand interaction profiler. The 2D docking for hydrogen bonding analysis and hydrophobic interactions was produced using LigPlot 1.4.5.
## 4.9. Statistical Analysis
The experiments were performed in triplicate and repeated on at least three biological samples ($$n = 3$$). Data are presented as the mean ± SEM. For statistical analysis, one-way and two-way ANOVA was used depending on the variables involved in the comparison. Tukey multiple comparison was performed, to assess the statistical significance. Statistical significance was assessed with Tukey’s multiple comparison. The statistical analysis was performed using Prism 7 (GraphPad Software Inc., San Diego, CA, USA). The results were considered statistically significant at $p \leq 0.05.$
## 5. Conclusions
HT can modulate EMT by maintaining the epithelial phenotype. However, additional studies using in vivo disease models are needed to confirm the utility of HT as an alternative treatment for airway diseases.
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|
---
title: A Combination of Acetate, Propionate, and Butyrate Increases Glucose Uptake
in C2C12 Myotubes
authors:
- Britt M. J. Otten
- Mireille M. J. P. E. Sthijns
- Freddy J. Troost
journal: Nutrients
year: 2023
pmcid: PMC9967986
doi: 10.3390/nu15040946
license: CC BY 4.0
---
# A Combination of Acetate, Propionate, and Butyrate Increases Glucose Uptake in C2C12 Myotubes
## Abstract
Background: Dietary fibers are subjected to saccharolytic fermentation by the gut microbiota, leading to the production of short chain fatty acids (SCFAs). SCFAs act as signaling molecules to different cells in the human body including skeletal muscle cells. The ability of SCFAs to induce multiple signaling pathways, involving nuclear erythroid 2-related factor 2 (Nrf2), may contribute to the redox balance, and thereby may be involved in glucose homeostasis. The aim of this study is to investigate whether SCFAs increase glucose uptake by upregulating the endogenous antioxidant glutathione (GSH) in C2C12 myotubes. Methods: C2C12 myotubes were exposed to 1, 5, or 20 mM of single (acetate, propionate, or butyrate) or mixtures of SCFAs for 24 h. Cytotoxicity, glucose uptake, and intracellular GSH levels were measured. Results: 20 mM of mixture but not separate SCFAs induced cytotoxicity. Exposure to a mixture of SCFAs at 5 mM increased glucose uptake in myotubes, while 20 mM of propionate, butyrate, and mixtures decreased glucose uptake. Exposure to single SCFAs increased GSH levels in myotubes; however, SCFAs did not prevent the menadione-induced decrease in glucose uptake in myotubes. Conclusions: The effect of SCFAs on modulating glucose uptake in myotubes is not associated with the effect on endogenous GSH levels.
## 1. Introduction
The gut microbiota plays an important role in skeletal muscle function and consequently in enhancing physical exercise performance [1,2]. Metabolites derived from microbial fermentation play an important role in the microbes–host metabolic crosstalk [3]. Saccharolytic fermentation of dietary fibers in the proximal colon by the gut microbiota leads to the production of favorable metabolites such as short chain fatty acids (SCFAs) [4]. The main SCFAs formed by the gut bacteria are acetate (C2), propionate (C3), and butyrate (C4) [5]. The molar ratio between acetate:propionate:butyrate in the large intestine is approximately 60:20:20 [6]. SCFAs are largely taken up by colonocytes, where butyrate is the main energy source [7]. SCFAs that are not metabolized in colonocytes are transported to the liver where a large part of propionate and butyrate is taken up. Acetate uptake in the liver is low, which results in the highest plasma concentration compared to the other SCFAs. The SCFAs that are not processed by the liver can be metabolized by other tissues, such as skeletal muscle [8]. The molar ratio between acetate:propionate:butyrate in peripheral blood of healthy subjects is approximately 80:10:10 [6].
Short chain fatty acids can affect skeletal muscle function in various ways including binding on membrane-bound G-protein couple receptors (GPR) 41 or GPR43, intracellularly by active transport, or passive diffusion into the cell [9,10]. Binding of SCFAs to GPR41 and GPR43 activates several intracellular pathways [11]. The pathways activated by these receptors include release of intracellular Ca2+, ERK$\frac{1}{2}$ activation, and inhibition of cAMP accumulation [11,12]. Although both GPRs are activated by SCFAs, they have different specificity and physiological function. Propionate is the most potent agonist for both GPR41 and GPR43 and acetate was selective for GPR43, whereas butyrate was active for GPR41. Through passive diffusion butyrate has been shown to inhibit histone deacetylase (HDAC). HDAC inhibitors have shown potent anti-inflammatory activity in inflammatory diseases [13].
During exercise the production of reactive oxygen species (ROS) within skeletal muscle increases [13]. Low levels of ROS that are generated during exercise promote many signaling pathways that are involved in skeletal muscle metabolism, mitochondrial biogenesis, and mitochondrial function, as well as antioxidant enzymes that regulate intracellular ROS levels [14]. These adaptations of skeletal muscle cell may lead to resistance against oxidative damage via antioxidant pathways. ROS induced activation of 5′-adenosine monophosphate-activated protein kinase (AMPK) activates the peroxisome proliferator-activated-receptor-gamma-coactivator-1α-(PGC-1α) signal transduction pathway [15]. This is important in regulating mitochondrial biogenesis and function in a PGC-1α-dependent pathway and stimulates glucose transporter 4 (GLUT4) translocation to the plasma membrane, and a concomitant increase in glucose transport [15,16].
The intracellular antioxidant capacity plays an important role in maintaining ROS levels in a physiologically compatible range. This allows ROS to serve as a signaling molecule while preventing too high ROS levels which may exert direct toxic effects [17]. However, when the cell is exposed to excessive ROS for a long period of time or in large concentrations relative to the endogenous antioxidant levels, the redox balance cannot be maintained and this may result in oxidative damage to DNA, lipids, and proteins [18]. Every cell has multiple endogenous antioxidant systems including the GSH system, thioredoxin system, different vitamins, and protective enzymes such as catalase or superoxide dismutase that can be upregulated to restore this balance. Nuclear factor erythroid 2-related factor 2 (Nrf2), a regulator of cellular antioxidant defenses [19,20], is the primary transcription factor protecting cells from oxidative stress by regulating the antioxidant GSH pathway [21]. The SCFAs propionate and butyrate have been shown to increase Nrf2 nuclear translocation in various cell types, e.g., hepatocytes and endothelial cells [22]. Through this mechanism of action SCFAs have shown to protect against oxidative stress and inflammation in diabetic mice [23].
Despite the positive effect of SCFAs on skeletal muscle metabolism and function it is questioned whether they could increase glucose uptake by regulation of the antioxidant system in skeletal muscle. Therefore, the aim of this study is to investigate if SCFAs increase glucose uptake by upregulating the endogenous antioxidant GSH in myotubes. It is hypothesized that acetate, propionate, and butyrate separately and combined in physiological ratios increase GSH, which results in increased glucose uptake in myotubes. To investigate this, a C2C12 murine muscle cell line was used. Here, we show that a mixture of SCFAs increases glucose uptake in myotubes while the observed effect is not associated with changes in endogenous GSH levels.
## 2.1. Chemicals
Acetic acid, propionic acid and butyric acid were purchased from Sigma-Aldrich (Saint Louis, MO, USA) as well as bovine serum albumin fatty-acid free (BSA), human insulin solution, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), Triton X-100 (TX-100), β-nicotinamide adenine dinucleotide reduced disodium salt hydrate (NADH), sodium pyruvate, β-nicotinamide adenine dinucleotide 2′-phosphate reduced tetrasodium salt hydrate (NADPH), sulfosalicylic acid solution (SSA), Ethylenediaminetetraacetic acid tetrasodium salt dihydrate (EDTA), reduced glutathione (GSH), oxidized glutathione (GSSG), glutathione reductase (GR), 2-vinylpyridine (2-VP), 5,5ʹ-Dithio-bis-(2-nitrobenzoic Acid) (DTNB), Potassium dihydrogen phosphate (KH2PO4), Dipotassium hydrogen phosphate (K2HPO4), human insulin solution, metformin, and menadione. Ethanol and the Pierce bicinchoninic acid (BCA) protein assay kit were purchased from ThermoFisher Scientific (Fremont, CA, USA). The Glucose Uptake-Glo assay kit was purchased from Promega (Leiden, The Netherlands).
## 2.2. Cell Culture and Treatments
A C2C12 murine myoblast cell line (ATCC; CRL-1772; Manassas, VA, USA) was cultured at passage 9–16 in growth medium (GM), composed of Dulbecco’s Modified *Eagle medium* (DMEM, Gibco, Carlsbad, CA, USA) supplemented with $9\%$ (v/v) fetal bovine serum (FBS, Gibco), and $1\%$ (v/v) antibiotics (100 ug/mL penicillin, 100 µg/mL streptomycin, Gibco). Cells were cultured in a humidified atmosphere containing $5\%$ CO2 at 37 °C until 70–$80\%$ confluency was reached.
Depending on the experiment, C2C12 myoblasts were seeded on Matrigel coated (Corning Life sciences, Corning, NY, USA) 6-well or 24-well culture plates (Greiner Bio-One, Frickenhausen, Germany) (Figure 1) at a density of 1 × 104 cells/cm2 and cultured in GM for 1.5 days until reaching ±$95\%$ confluency. After reaching ±$95\%$ confluency, cells were washed with Dulbecco’s phosphate-buffered saline (PBS, Gibco) and differentiation medium (DM) was added, which was composed of $1\%$ (v/v) heat inactivated FBS (hiFBS, Gibco) and $2.5\%$ (v/v) HEPES. DM was refreshed every day for 3 consecutive days. After 4 days of differentiation, cells were incubated for 24 h with a $3\%$ bovine serum albumin (BSA, Sigma-Aldrich) solution containing either single (acetate, propionate, or butyrate) or mixtures of SCFAs in concentrations of 1, 5, or 20 mM (Table 1).
## 2.3. Cytotoxicity Measurement
Cytotoxicity was assessed by measuring the presence of the cytosolic enzyme lactate dehydrogenase (LDH) in the medium. A $3\%$ TX-100 media solution was used to induce cell lysis, which was assumed to induce $100\%$ LDH release and served as a positive control. A 100 mM pyruvate potassium phosphate solution with 377 mM NADH was added. All LDH levels were expressed as a percentage of LDH activity as seen after cell lysis and was shown relative to the condition in which the cells were not exposed to SCFA. NADH absorption was measured at λ = 340 nm with a microplate reader every 20 s for 4 min at 37 °C and the slope of the curve was calculated.
## 2.4. Glucose Uptake Measurement
2-deoxyglucose (2-DG) uptake into C2C12 myotubes was assessed using the Glucose Uptake-Glo assay kit according to the manufacturer’s instructions. Briefly, C2C12 myoblasts were differentiated into myotubes on a 24-wells plate and were exposed to single- and mixtures of SCFAs for 24 h (Figure 1). Metformin was added to the C2C12 myotubes at a concentration of 400 µM for 24 h as a positive control. After 24 h, cells were glucose starved for 1 h and exposed to 100 nM insulin for 1 h before incubation with 2-DG (100 µM, 30 min). The reaction was stopped by adding an acid detergent stop solution. Samples were transferred to a 96 non-transparent luminescent plate and a pH neutralization solution was added. In total, 100 µL of a detection reagent containing glucose-6-phosphate dehydrogenase (G6PDH), NADP+, reductase, luciferase, and luciferin substrate was added, and luminescence was measured at a 0.3–1 s integration using a microplate reader. Changes in glucose uptake were expressed as fold change compared to controls without SCFAs and insulin exposure.
## 2.5. GSH Measurement
To determine the amount of GSH in C2C12 myotubes, cells were lysed using a 100 mM potassium phosphate solution (pH 7,5) supplemented with 10 mM EDTA containing $1\%$ TX-100 and incubated on ice for 30 min. Cells were scraped and transferred to a 2 mL Eppendorf tube. All lysates were centrifuged at 14,000× g for 10 min at 4 °C to remove cell debris. Total protein content of the supernatant was determined with a bicinchoninic acid assay (BCA) (ThermoFisher, Boston, MA, USA). In addition, 300 µL of the supernatant was mixed with 300 µL $6\%$ (v/v) SSA in milliQ water. To determine the GSH concentration, Rahman’s enzymatic recycling method was used as previously described [24]. The absorption of TNB was measured at λ = 412 nm for 10 min at 37 °C and the slope of the curve was calculated. A calibration curve of GSH and GSSG was made to determine the concentrations of GSH and GSSG over time. GSH was calculated by subtraction of GSSG from total GSH. All samples were corrected for the amount of protein measured.
## 2.6. Statistical Analysis
All values were presented as the mean ± SEM. Normality was checked with the Shapiro–Wilk test. In case of statistical significance of this test, the nonparametric Mann–Whitney test was used to test significant difference between two individual conditions. When normally distributed, a two-tailed independent sample t-test was used. At least three independent experiments were performed in duplicates as well as the analyses. Statistical tests were performed using GraphPad Prism 9.4 software (GraphPad, Prism, La Jolla, CA, USA). p-values < 0.05 were considered statistically significant.
## 3.1. Mixture 1, a Combination of SCFAs, Is Cytotoxic to C2C12 Myotubes at a Concentration of 20 mM
Exposure of C2C12 myotubes to 1, 5, or 20 mM of single SCFAs for 24 h was not cytotoxic compared to control (=0 mM SCFA) (Figure 2). However, after 24 h of exposure of the C2C12 myotubes to 20 mM of mixture 1, LDH release increased by 8.0 % ($p \leq 0.001$) compared to control (20.82 ± 0.8 % and 28.8 ± $1.4\%$ LDH, respectively) (Figure 3A), while exposing of the myotubes to 1, 5, or 20 mM of mixture 2 for 24 h did not induce changes in LDH release and, hence, in cytotoxicity compared to control (Figure 3B).
## 3.2. Exposure to 5 mM of Mixture 1 Increased Glucose Uptake in C2C12 Myotubes
The exposure of C2C12 myotubes to 100 nM insulin increased its glucose uptake by a fold change of 1.2 ± 0.2 compared to control ($p \leq 0.001$). Exposure to 400 µM metformin for 24 h, which was used as a positive control, increased glucose uptake in C2C12 myotubes with a fold change of 1.4 ± 0.06. Metformin significantly increased insulin dependent glucose uptake compared to 0 mM SCFA, which was only treated with insulin (1.4 ± 0.06 vs. 1.2 ± 0.05, respectively; $p \leq 0.01$) (Figure 4 and Figure 5)). Acetate had no effect on insulin dependent glucose uptake compared to 0 mM SCFA, which was only treated with insulin ($p \leq 0.05$) (Figure 4A), while propionate and butyrate, at a concentration of 20 mM, decreased insulin dependent glucose uptake in C2C12 with a fold change of 0.8 ± 0.07 and 0.7 ± 0.06 ($p \leq 0.01$ and $p \leq 0.001$), respectively (Figure 4B,C). Mixture 1, at a concentration of 20 mM, decreased insulin dependent glucose uptake as well 0.97 ± 0.07 ($$p \leq 0.03$$) (Figure 5A). In contrast, a 24 h exposure of 5 mM of mixture 1 significantly increased insulin dependent glucose uptake in C2C12 myotubes with a fold change of 1.6 ± 0.09 compared to control ($p \leq 0.01$) (Figure 5A). A similar increasing trend was seen for 5 mM of mixture 2 with a fold change of 1.5 ± 0.1 compared to control, however, this did not reach statistically significance ($$p \leq 0.06$$) (Figure 5B).
## 3.3. Exposure to SCFAs Increased GSH Levels in C2C12 Myotubes
A concentration of 25 µM of menadione significantly decreased GSH levels in C2C12 myotubes compared to 0 mM exposure (1.9 ± 0.1 nmol/mg protein vs 4.4 ± 0.3 nmol/mg protein; respectively, $p \leq 0.01$) (Figure 6 and Figure 7). Acetate, butyrate, and propionate, at 1, 5, and 20 mM, increased GSH levels in C2C12 myotubes compared to control (Figure 6A–C). Menadione and SCFAs did not change GSSG levels significantly compared to control ($p \leq 0.05$) (Figure 6D–F). Twenty mM of mixture 1 increased GSH levels in C2C12 myotubes compared to 0 mM exposure (6.7 ± 0.8 nmol/mg protein 4.4 ± 0.3 nmol/mg protein; respectively, $p \leq 0.001$) (Figure 7A), whereas mixture 2 did not significantly change GSH levels compared to control ($p \leq 0.05$) (Figure 7B). Both mixture 1 and 2 did not change GSSG levels compared to 0 mM SCFA exposure (Figure 7C,D).
## 3.4. Single- and Mixtures of SCFAs Did Not Prevent the Menadione-Induced Decrease in Glucose Uptake in C2C12 Myotubes
Menadione at a concentration of 25 µM, to induce oxidative stress, significantly decreased glucose uptake in C2C12 myotubes compared to control in the absence of insulin (0.48 ± 0.07 vs. 1.0 ± 0.05; $p \leq 0.001$, respectively) (Figure 8 and Figure 9). The addition of acetate, propionate, or butyrate separately or in a mixture did not prevent glucose uptake after 1 h of menadione exposure compared to control in the presence of insulin.
## 4. Discussion
We showed that a mixture of acetate, propionate, and butyrate in relative ratios of 60:20:20, at a concentration of 5 mM induced an increase in glucose uptake in C2C12 myotubes. Single SCFAs did not increase glucose uptake, while high concentrations of 20 mM propionate and butyrate even decreased glucose uptake in myotubes. Single SCFAs increased GSH levels in myotubes while the mixtures of SCFAs did not increase GSH levels. In conclusion, the effects of SCFAs on glucose uptake in myoblasts were not associated with its’ effects on endogenous GSH levels.
Skeletal muscle is thought to account for 70 to $90\%$ of insulin-stimulated glucose storage [25]. Results from mouse C2C12 and rat L6 muscle cell lines rarely demonstrate an increased fold change of 2-fold increase in glucose uptake with maximum insulin exposure [26]. These results are in line with findings from this study, in which we showed that exposure of C2C12 cells to insulin induced an increase in glucose uptake of 1.2-fold. A maximum increase in glucose uptake by a 1.6-fold change was shown by a combination of the SCFAs acetate, propionate, and butyrate in relative ratio 60:20:20. A similar trend was seen for mixture 2, in which the SCFAs were given in the ratio 80:10:10. Interestingly, the combined but not the single SCFAs increased glucose uptake significantly. Remarkably, the increase in glucose uptake induced by mixture 1 was even higher compared to metformin-induced increase in glucose uptake. Metformin increases GLUT4-mediated glucose uptake through an insulin-independent signaling pathway targeting AMPK activation and subsequently enhance GLUT4 translocation to the plasma membrane [27]. AMPK is a key regulator for maintaining homeostasis in energy metabolism [28]. It was previously established that SCFAs are able to phosphorylate AMPK in myotubes and skeletal muscle [29,30,31], likely by increasing the expression of PPAR-δ. Butyrate has been shown to increase the expression of PPAR-δ in both L6 myotubes and skeletal muscle in C57BL/6J mice in vivo [29]. However, Hernandez et al. [ 2021] showed no increase in AMPK phosphorylation following acute or chronic acetate treatment (0 up to 5 mM exposure) in human skeletal muscle cells [32]. Another mechanism of SCFAs is the inhibition of HDACs, which can be induced by passive diffusion of SCFAs into the cell. HDACs possess key roles in maintaining skeletal muscle metabolic homeostasis, regulating skeletal muscles adaptation and exercise capacity [33]. The inhibition of HDACs may also play a key role in insulin sensitivity as increased GLUT4 translocation and basal and insulin-induced glucose uptake in skeletal muscle is observed after the inhibition of HDAC in L6 myotubes [34]. This leads to an increase in insulin receptor substrate 1 (IRS1) expression and protein kinase B (PKB) phosphorylation.
Another binding target of SCFAs on skeletal muscle cells are the transmembrane G protein-coupled receptors (GPRs) that are activated by SCFAs and induce intracellular signaling cascades and cellular responses [35]. More specifically, GPR41 and GPR43, also known as free fatty acid receptor 3 (FFAR3) and FFAR2, respectively, are the best identified and studied SCFA receptors present on the skeletal muscle [36,37]. Activation of both receptors results in Gα subunit disassociates from the Gβγ subunits and couples with Gαi/o proteins which inhibits the activity of adenylate cyclase (AC) and leads to reduced generation of cyclic adenosine monophosphate (cAMP) [11]. In addition, activation of GPR43 also activates phospholipase C (PLC) via Gαq/11 and promotes activation of inositol triphosphate (IP3) receptors on the endoplasmic reticulum (ER) [37]. This results in Gαq/11-induced increase in Ca2+ release into the cytoplasm [38]. This effect was demonstrated in L6 myotubes which were exposed to acetate [39]. The effect of acetate on intracellular Ca2+ influx was inhibited in L6 myotube that were knocked down in GPR43 by transfection of GPR43 specific siRNA. Lahiri et al. [ 2019] exposed differentiated C2C12 cells to a 10 mM cocktail of SCFAs, in a similar ratio as mixture 1 (60:25:15; acetate: propionate: butyrate, respectively) and observed a significant increase in PGC-1α [40]. PGC-1α is a transcriptional coactivator that is a central inducer of mitochondrial biogenesis in cells as it can also modulate the composition and functions of individual mitochondria [41]. Although in this study relative ratios of 60:20:20 showed to improve glucose uptake, it is unknown what the effect is on mitochondrial biogenesis, as well as on the oxidative capacity. Furthermore, the contribution of each specific GPR receptor on mitochondrial biogenesis, as well as the oxidative capacity is still unknown.
Skeletal muscle glucose uptake as well as mitochondrial activation are essential for the energy homeostasis. Increased energy generation is essential for muscle contraction. In addition, SCFA binding to GPR41 and GPR43 activation leads to Ca2+ release from the ER which is also important in skeletal muscle contraction [42]. Furthermore, Ca2+ also regulates intracellular processes, such as myosin–actin cross bridging, protein synthesis, protein degradation and fiber type shifting by the control of Ca2+-sensitive proteases and transcription factors, as well as mitochondrial adaptations and respiration [42]. Butyrate-induced AMPK phosphorylation increases levels of PGC-1α in insulin-resistant hepatocytes and in mice, resulting in increased skeletal muscle glucose uptake and an increase in insulin sensitivity [43]. The affinity ranking for activation of GPR43 by different SCFAs is ordered as acetate = propionate > butyrate [11]. In contrast, for GPR41 the preferred order is propionate > butyrate > acetate. Due to the difference in binding affination for the SCFAs on the GPR$\frac{41}{43}$ insulin dependent may explain why the separate SCFAs did not increase glucose uptake, whereas in mixture 1 they seem to induce a synergistic effect on the glucose uptake. An amount of 20 mM of propionate, butyrate, and mixture 1 decreased the glucose uptake, which could be linked to an increase in cytotoxicity.
This study shows that intracellular glutathione levels in C2C12 myotubes increase after exposure to the single SCFAs; however, this did not prevent an oxidative stress-induced decrease in glucose uptake. This indicates that the glutathione synthesis pathway is activated separately from the glucose uptake pathway. In addition, 20 mM of propionate, butyrate, and mixture 1 increased GSH levels but were associated with a decrease in glucose levels. Furthermore, 20 mM of mixture 1 showed an increase in LDH release in the medium indicating cytotoxicity. Compared to 1 and 5 mM exposure of the single and mixtures of SCFAs, high levels of GSH are observed in 20 mM. This may indicate increased stress levels in the cells as stressed cells and oxidative stress itself also induce Nrf2 [44].
In the present study we showed that a specific combination of SCFAs increased glucose uptake in C2C12 myotubes. These results suggest that colonic fermentation of dietary fibers, which results in the production of different SCFAs in a specific ratio, has the potential to increase skeletal muscle glucose uptake. This may be beneficial for nutritional management of health and disease, i.e., in athletes or other people who have a need to take up more glucose by skeletal muscle. Future research should include other physiologically relevant ratios of SCFAs and identify the underlying mechanisms. This will eventually need to culminate in human clinical trials in which targeted SCFA production by gut microbiota will be modified by nutrition intervention, such as with prebiotics, to assess the in vivo implication of the currently presented results on glucose uptake. In addition, the contribution of the SCFAs on both GPR41 and GPR43 activation and its signaling pathways remains to be investigated. Furthermore, it would be of interest to investigate if our findings on increased GSH levels also apply to other endogenous antioxidant systems that are regulated by Nrf2.
In conclusion, exposure to the SCFAs acetate, propionate, or butyrate, was not associated with increased glucose uptake in C2C12 myotubes. A combination of these SCFAs in relative ratio 60:20:20 increased glucose uptake. Despite the enhancing effect of the SCFAs on GSH levels, they did not prevent a decrease in glucose uptake which was caused by menadione-induced oxidative stress, suggesting that increases in GSH levels are activated in parallel to the insulin dependent signaling pathways. This hypothesis needs further investigation and should be confirmed in clinical studies.
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|
---
title: ProCPU Is Expressed by (Primary) Human Monocytes and Macrophages and Expression
Differs between States of Differentiation and Activation
authors:
- Karen Claesen
- Joni De Loose
- Pieter Van Wielendaele
- Emilie De bruyn
- Yani Sim
- Sofie Thys
- Ingrid De Meester
- Dirk Hendriks
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9967989
doi: 10.3390/ijms24043725
license: CC BY 4.0
---
# ProCPU Is Expressed by (Primary) Human Monocytes and Macrophages and Expression Differs between States of Differentiation and Activation
## Abstract
Carboxypeptidase U (CPU, TAFIa, CPB2) is a potent attenuator of fibrinolysis that is mainly synthesized by the liver as its inactive precursor proCPU. Aside from its antifibrinolytic properties, evidence exists that CPU can modulate inflammation, thereby regulating communication between coagulation and inflammation. Monocytes and macrophages play a central role in inflammation and interact with coagulation mechanisms resulting in thrombus formation. The involvement of CPU and monocytes/macrophages in inflammation and thrombus formation, and a recent hypothesis that proCPU is expressed in monocytes/macrophages, prompted us to investigate human monocytes and macrophages as a potential source of proCPU. CPB2 mRNA expression and the presence of proCPU/CPU protein were studied in THP-1, PMA-stimulated THP-1 cells and primary human monocytes, M-CSF-, IFN-γ/LPS-, and IL-4-stimulated-macrophages by RT-qPCR, Western blotting, enzyme activity measurements, and immunocytochemistry. CPB2 mRNA and proCPU protein were detected in THP-1 and PMA-stimulated THP-1 cells as well as in primary monocytes and macrophages. Moreover, CPU was detected in the cell medium of all investigated cell types and it was demonstrated that proCPU can be activated into functionally active CPU in the in vitro cell culture environment. Comparison of CPB2 mRNA expression and proCPU concentrations in the cell medium between the different cell types provided evidence that CPB2 mRNA expression and proCPU secretion in monocytes and macrophages is related to the degree to which these cells are differentiated. Our results indicate that primary monocytes and macrophages express proCPU. This sheds new light on monocytes and macrophages as local proCPU sources.
## 1. Introduction
Monocytes and macrophages play a central role in the inflammatory response in atherosclerosis and at extra-vascular inflammatory sites [1,2,3]. In addition, these cells can interact with blood coagulation mechanisms, leading to thrombus formation or extravascular fibrin deposition [4,5]. Numerous macrophage subtypes have been identified, with IFN-γ/LPS- and IL-4-stimulated macrophages representing the opposite sites of the macrophage spectrum [2,6,7,8,9]. IFN-γ/LPS-stimulated macrophages (M1- or classically activated macrophages) are important producers of pro-inflammatory cytokines. IL-4-stimulated macrophages (M2- or alternatively activated macrophages) are producers of anti-inflammatory cytokines [2,10,11].
The intrinsically unstable carboxypeptidase U (CPU, TAFIa, CPB2) is a potent attenuator of fibrinolysis and a possible modulator of inflammation that is present in the circulation as its zymogen procarboxypeptidase U (proCPU, TAFI, proCPB2). Plasma proCPU mainly originates from the transcription of the CPB2 gene in the liver [12,13,14]. However, other cell types have been identified as (potential) additional proCPU sources. A first non-hepatically derived pool of proCPU was found in the platelets and accounts for <$0.1\%$ of blood-derived proCPU. It is synthesized by megakaryocytes and released from the α-granules upon platelet activation [15]. CPB2 mRNA was also detected in megakaryocytic cell lines (CHRF, Dami and MEG-01), primary endothelial cells (both HCAEC and HUVEC), and the human monocytic cell line THP-1 as well as in THP-1 cells differentiated into a macrophage-like phenotype and in peripheral blood mononuclear cells (PBMCs) [15,16,17,18,19]. In the promonocytic cell line U937, CPB2 mRNA expression increased after treatment with dexamethasone or M-CSF [20]. ProCPU protein was detected in the lysate of differentiated and undifferentiated Dami and MEG-01 cells and the conditioned media of differentiated Dami and PMA-stimulated THP-1 cells [16].
CPB2 mRNA was recently detected in PBMCs and it was hypothesized that the CPB2 transcripts were derived from CPB2 gene expression by monocytes and macrophages present in this cell fraction [16]. Since monocytes and macrophages provide a potential link between inflammation and thrombus formation [3], and the CPU system also plays a role in both systems, this is an interesting hypothesis. ProCPU expression has, however, not been studied separately in PBMC-derived monocytes. In addition, proCPU expression in macrophages has thus far only been studied in cell lines and not yet in primary cells that more closely mimic in vivo human physiology. Therefore, we investigated, for the first time, the expression of proCPU (on mRNA, protein and activity level) not only in the primary human monocytes, but also in different primary human macrophage subsets to gain more insights into these cells as potential sources of proCPU.
## 2.1. CPB2 mRNA Is Detected in (Primary) Human Monocytes and Macrophages
Using the validated reverse transcriptase-polymerase chain reaction (RT-qPCR) assay (Supplementary Material File S1), CPB2 mRNA expression was studied in human monocyte and macrophage cell lines and primary cells and displayed relative to the expression of the reference genes selected for accurate normalization (ARPC1a, EMC7, and TBP; Supplementary Figure S4A). The human hepatocellular carcinoma cell line HepG2 was used as a positive control given that hepatocytes are the primary source of proCPU protein in plasma. RT-qPCR results showed that CPB2 mRNA was present in all of the studied cell types, with the highest expression detected in HepG2 cells Figure 1. When comparing the CPB2 mRNA abundance in the monocytic cell line THP-1 with primary human monocytes, the expression of the CPB2 transcripts was significantly lower in the THP-1 cells compared to its primary cell counterpart. Although the magnitude of relative CPB2 mRNA expression was different between the primary monocytes and THP-1 cells, a clear and significant decrease in CPB2 mRNA expression was observed for both cell types when differentiating these cells into macrophages with M-CSF or PMA, respectively. Furthermore, activation of primary M-CSF macrophages with LPS/INF-ɣ or IL-4 resulted in differential CPB2 gene expression: LPS/INF-ɣ activation gave rise to a slightly, but not significantly higher CPB2 mRNA abundance compared to M-CSF macrophages, whereas IL-4 activation significantly lowered the expression of CPB2 transcripts.
## 2.2. ProCPU and CPU Protein Are Present in (Primary) Human Monocyte and Macrophage Medium
The presence of the proCPU protein in the concentrated conditioned medium of human monocytes and macrophages was studied by Western blotting using two different polyclonal proCPU/CPU antibodies. ProCPU purified from plasma as well as CPU obtained after activating purified proCPU by the addition of thrombin-thrombomodulin were included as positive controls. Both antibodies against proCPU/CPU reacted with purified proCPU and CPU at a MW around 58 kDa and 35 kDa, respectively (Figure 2), corresponding with the previously reported data on human proCPU/CPU [21]. Using the sheep polyclonal proCPU antibody (PATAFI-S, Prolytix), a similar proCPU immunoreactive band was detected in all of the concentrated conditioned media samples, though the apparent MW was slightly lower compared to the purified proCPU (Figure 2A). With this antibody, no CPU band was observed in the media samples. The second Western blot showed a 35 kDa CPU band for all conditioned media, but this polyclonal antibody (CP17, Agrisera) did not react with proCPU in any of the media samples (Figure 2B).
An additional Western blot experiment was performed to gain more insights into the reactivity of both polyclonal antibodies against proCPU and CPU (Figure 3). PATAFI-S was found to better recognize proCPU, while CP17 showed a higher affinity toward CPU.
In order to identify that the 35 kDa protein band detected in the conditioned media with the CP17 antibody was truly CPU and to substantiate that proCPU can be activated into functionally active CPU in the in vitro cell environment, HepG2, THP-1, and PMA-stimulated THP-1 cells were cultured in the presence of 1 mM Bz-o-cyano-Phe-Arg, a specific CPU substrate. At different time points, the medium was collected and subjected to RP-HPLC following an in-house protocol of HPLC-assisted CPU activity measurement to investigate whether the substrate had been cleaved in the cellular environment [22]. As shown in Figure 4, the cleaved substrate (Bz-o-cyano-Phe) was detected in the medium of all of the tested cell types.
Lysate from all cell types including HepG2 was also subjected to Western blot analysis. Despite all our efforts, neither proCPU nor CPU could be detected by Western blotting in any of the cell lysates using the proCPU/CPU antibody. However, the presence of proCPU/CPU inside the different cell types was confirmed by immunocytochemistry (Supplementary Material File S3).
## 2.3. ProCPU Concentration Measured in Medium of (Primary) Human Monocytes and Macrophages Is Related to Their State of Differentiation
ProCPU was measured in conditioned medium samples, with the highest levels seen in the HepG2 medium (Figure 5). The ProCPU concentration was similar in the medium of THP-1 cells and primary human monocytes and was significantly higher compared to the concentration the in medium of PMA-stimulated THP-1 cells and primary human M-CSF primed macrophages, respectively. Moreover, a slight but non-significant increase in proCPU concentration was observed after stimulation of the primary human M-CSF macrophages with IFN-γ and LPS, whereas IL-4 stimulation led to a further significant decrease in proCPU activity. In the cell lysates, the proCPU concentration was comparable in all of the studied cell types.
## 3. Discussion
The involvement of both CPU and monocytes/macrophages in inflammation and thrombus formation [3], and the hypothesis of Lin et al. that monocytes and macrophages are responsible for the CPB2 mRNA expression of PBMCs [16], prompted us to investigate the expression of proCPU in (primary) human monocytes and different (primary) human macrophage subsets to gain more insights into these cells as potential sources of proCPU. For this research, we used the human monocytic cell line THP-1 and primary human monocytes and macrophages. The THP-1 cell line has been extensively used to study monocyte/macrophage function and biology, but suffers from the disadvantage that THP-1 cells differ genetically and phenotypically from primary monocytes. Primary cells such as PBMC-derived monocytes mimic the in vivo human physiology more closely, making it often a more relevant cell culture model [23,24]. Therefore, we included the primary human monocytes and macrophages derived from these monocytes. Moreover, this study was the first to examine proCPU expression separately in PBMC-derived human primary monocytes and macrophages and not in the PBMC-fraction as a whole.
After successfully validating a RT-qPCR assay to study CPB2 mRNA expression, relative CPB2 mRNA expression was determined in human monocyte- and macrophage cell lines and primary cells. Primary human monocytes displayed considerable CPB2 mRNA expression while the expression decreased substantially after differentiating these cells into resting macrophages by the addition of M-CSF. Similar results were obtained in the THP-1 monocytic cell line and PMA-stimulated THP-1 cells. This is in line with the observations of Lin et al., although based on their results, we expected CPB2 mRNA expression to be of similar magnitude in the primary human monocytes and THP-1 cells, but this was not the case [16]. Moreover, in databases containing the results of experiments in which mRNA was determined by microarray or single cell RNA sequencing mainly in mice, very low levels of CPB2 mRNA were found in the monocytes and macrophages. Here, the abundance of CPB2 transcripts was clearly higher in the primary cells. The higher expression observed here might be due to the fact that CPB2 mRNA expression was studied specifically in monocytes and not in the whole PBMC fraction (of which monocytes make up 10–$30\%$) as Lin et al. did. Furthermore, as mentioned earlier, cell lines and primary cells may genetically differ, and this might account (in part) for the difference in CPB2 mRNA expression observed between the THP-1 cells and primary human monocytes. Moreover, it is difficult to quantitatively compare the RT-qPCR results obtained in this study and those of Lin et al. because here, the CPB2 mRNA expression was expressed relative to a pool of stable reference genes, while Lin and co-workers made use of RNA standards for absolute quantification. Nevertheless, a clear trend between the expression of CPB2 transcripts and the state of differentiation was observed for both the monocytic cell line and primary monocytes and macrophages.
Macrophages display remarkable plasticity and can change their physiology in response to environmental cues [25]. As a result, numerous macrophage subtypes with distinct functions have been identified [2,6,7,8,9,26]. In this context, we were also interested in whether the CPB2 mRNA expression was different between resting M-CSF macrophages and so called M1- and M2-macrophages, representing the opposite sidesof the diverse macrophage spectrum. Primary M-CSF primed macrophages incubated in the presence of IFN-ɣ/LPS develop into pro-inflammatory macrophages, while IL-4 differentiates monocytes into anti-inflammatory macrophages. Interestingly, activation of primary human M-CSF macrophages resulted in differential CPB2 mRNA expression: classical macrophage activation gave rise to a slightly, but not significantly higher CPB2 mRNA abundance compared to the M-CSF primed macrophages, whereas alternative activation significantly lowered the expression of the CPB2 transcripts. These observations further support that the expression of CPB2 mRNA in monocytes and (activated) macrophages are related to the degree to which these cells are differentiated and/or activated.
In the concentrated conditioned medium of all of the studied cell types, the proCPU protein was detected using a polyclonal sheep anti-human proCPU antibody (PATAFI-S). Notably, the protein band appeared at a slightly different MW compared to the plasma purified proCPU (58 kDa). Due to the concentration of the conditioned medium samples, albumin (with a MW of 67 kDa) was present in a high concentration in these samples. It is possible that this high albumin concentration affects the electrophoretic transfer of proteins with a similar MW such as proCPU. This might explain why proCPU was detected on the Western blot at an apparently lower molecular weight than expected. With this antibody, no CPU was detected in the concentrated conditioned medium samples. In an attempt to detect proCPU or CPU protein in the cellular lysate samples, Western blotting was repeated on those samples using a second proCPU/CPU antibody and the same was carried out for the conditioned medium samples. To our surprise, this polyclonal rabbit anti-human proCPU/CPU antibody (CP17) visualized a protein band at a MW of around 35 kDa in all samples, exactly at the same level as the protein band of the purified CPU. Unexpectedly, no 58 kDa proCPU band was detected on the Western blot for any of the media samples using the CP17 antibody. A similar finding with the CP17 antibody was reported by Rylander et al., who suggested that denaturation with SDS may affect proCPU more than CPU, making proCPU more rigid and less detectable with the CP17 antibody. Comparing the reactivity of both the PATAFI-S and CP17 antibody toward purified plasma proCPU and CPU on the Western blot, the PATAFI-S antibody seemed to have a higher affinity toward proCPU, while CP17 reacted better with CPU. A hypothesis is that the level of CPU in the conditioned media is too low to be detected with the PATAFI-S antibody, while proCPU is above the limit of detection for this antibody and vice versa for the CP17 antibody.
By incubating HepG2, THP-1 and PMA-stimulated THP-1 cells with a specific CPU substrate and by detecting the cleaved substrate in the cell environment, it was demonstrated that proCPU can be activated into enzymatically active CPU in the in vitro cell culture environment. This confirmed that it was truly CPU that was detected on the CP17 Western blot. To further substantiate that the liver-derived CPU and monocyte/macrophage-derived CPU possessed the same peptidase activity in a biological context, studying the activity of monocyte/macrophage-derived CPU in a functional assay is of interest. This could be conducted by using an in vitro clot lysis assay in which monocyte/macrophage-derived CPU is added to the assay, and then comparing the results with those of an in vitro clot lysis experiment to which liver-derived proCPU is added.
In addition to Western blotting, proCPU was also measured in the concentrated conditioned media using an in-house enzymatic assay. In accordance with the results of the mRNA analysis, a decrease in proCPU concentration in the cell medium was found upon monocyte-to-macrophage differentiation, and this phenomenon was seen in the monocytic cell line as well as in the primary cells. In contrast to CPB2 mRNA expression, the proCPU levels in the medium of THP-1 cells and primary human monocytes were very similar. A discrepancy between mRNA and protein abundance as observed for the THP-1/PMA-stimulated THP-1 cells was, however, frequently seen, and a theoretical understanding mostly remains elusive [27]. Aside from this, these findings support the hypothesis of Lin et al. that proCPU is expressed in monocytes and macrophages [16]. The presence of proCPU in the macrophages of atherosclerotic plaques, as detected by Rylander and co-workers, thus cannot solely be attributed to the phagocytosis of environmental proCPU by these macrophages [21]. Although their proCPU levels are low compared to the plasma proCPU concentrations, monocytes and macrophages may provide a local source of proCPU and boost proCPU concentrations, resulting in an additive effect on fibrinolysis driven by plasma proCPU [28,29]. The downregulation of proCPU levels in the cell medium during monocyte-to-macrophage differentiation suggests a more pronounced role for this enzyme in monocytes compared to macrophages. However, the exact role and significance of these cells as local proCPU sources are not clear at this time.
The incubation of primary M-CSF primed macrophages with IFN-ɣ/LPS had little influence on the proCPU levels, while alternative macrophage activation with IL-4 caused a further downregulation in the proCPU levels. The significance of the differential expression of CPB2 mRNA and the secretion of the proCPU protein by classically and alternatively activated macrophages is still also an open question. In the setting of atherosclerosis, IFN-γ/LPS-stimulated macrophages are associated with symptomatic and unstable plaques, whereas IL-4-stimulated macrophages are particularly abundant in stable zones of the plaque and asymptomatic lesions [2,10,11,21]. In addition, it was recently shown that proCPU/CPU is present in considerable amounts in carotid plaques, with the highest levels corresponding to the vulnerable part of the plaque, adjacent to an area with high macrophage/foam cell content and substantial neovascularization [21]. Based on this, we speculate that there might be a need for plaque stabilizing mechanisms in unstable, M1-rich plaques. Since CPU limits plasmin generation, thereby preventing fragmentation of the fibrin network (fibrinolysis), counteracting destabilizing effects in this environment and contributing to keeping the plaque intact, it seems plausible that the presence of higher proCPU concentrations in this environment (through proCPU expression by IFN-γ/LPS-stimulated macrophages) is one such mechanism. Following this hypothesis, it seems logical that proCPU expression is the lowest in the IL-4-stimulated macrophages. These type of macrophages are predominantly present in the stable environment of the plaque, where there is little or no need for additional plaque stabilizing mechanisms.
## 4.1.1. Cell Lines
HepG2 cells (human hepatocellular carcinoma; Sigma-Aldrich, Saint-Louis, MO, USA) and THP-1 cells (human acute monocytic leukemia, ATCC) were respectively grown in DMEM or RPMI 1640 both supplemented with $10\%$ fetal calf serum (FCS), 100 U/mL penicillin, and 100 µg/mL streptomycin. Part of the THP-1 cells was differentiated into a macrophage-like phenotype by the addition of 0.2 μM phorbol 12-myristate 13-acetate (PMA; Sigma-Aldrich) to the medium for 72 h. All cells were incubated at 37 °C under a $95\%$ air/$5\%$ CO2 atmosphere. Passage numbers 2–5 were used for HepG2 and 2–8 for the THP-1 cells.
## 4.1.2. Primary Cells
Human PBMCs were isolated from buffy coats of anonymous clinically healthy blood donors (Red Cross, Mechelen, Belgium) by Ficoll–Paque Premium gradient centrifugation. Ethical approval for the buffy coats and processes used in this study was given by the Ethics Committee UZA/UAntwerp (B300201939437) and all donors ($$n = 17$$) gave their written informed consent. Briefly, a 40 mL buffy coat was diluted in PBS (1:1, v/v), layered on top of Ficoll–Paque Premium solution (GE Healthcare, Machelen, Belgium) and centrifuged (40 min, 400× g, no brakes). PBMCs were collected from the interface and washed twice with PBS. CD14+ monocytes were enriched from the freshly isolated mononuclear cell fraction via CD14+ positive magnetic selection using CD14-microbeads (20 µL of microbeads per 107 total PBMCs; Miltenyi Biotec, Bergisch Gladbach, Germany) following the manufacturer’s protocol. MACS-purified CD14+ monocytes were then seeded at a density of 2 × 106 cells/mL in complete RPMI medium and placed in a humidified incubator with $5\%$ CO2 at 37 °C. Monocytes were either harvested after 24 h of culturing or differentiated into macrophages immediately after seeding.
For monocyte-to-macrophage differentiation, freshly isolated human CD14+ monocytes were seeded at a density of 2 × 106 cells/mL in complete medium supplemented with 20 ng/mL recombinant human macrophage colony-stimulating factor (rhM-CSF, Immunotools, Friesoythe, Germany) [30]. After 5 days of incubation, macrophages were harvested or further polarized by 2 days of incubation with 20 ng/mL rhM-CSF in combination with either 100 U/mL IFN-γ (Immunotools) and 20 ng/mL LPS (Immunotools) to obtain classically activated macrophages or 20 ng/mL IL-4 (Immuntools) for alternatively activated macrophages [30,31]. To confirm appropriate macrophage polarization by these stimulation protocols, the medium was aspirated 8 and 24 h after the start of the polarization [31]. TNF-α levels were determined in the 8 h aspirate and the IL-6, IL-1β and IL-10 levels in the 24 h aspirate using the respective ELISA (hTNF-α ELISA, hIL-6 ELISA, hIL-1β ELISA, and hIL-10 ELISA; Immunotools) (Supplementary Material File S2).
## 4.2. Conditioned Media and Cellular Lysates
Conditioned medium of the different cell types was obtained by replacing complete medium with $5\%$ of the respective complete medium and $95\%$ Hank’s Balanced Salt Solution (HBSS, Gibco, Waltham, MA, USA) 24 h before harvesting. After 24 h, the conditioned medium was collected and stored at −80 °C until further analysis. Cellular lysates were prepared by washing 2 × 106 cells twice with PBS and suspending these cells in 50 µL of the appropriate lysis buffer: lysis buffer for proCPU measurement ($1\%$ octylglucoside, 10 mM EDTA, 70 µg/mL aprotinin, 50 mM Tris-HCl pH 8.3) or lysis buffer for Western blot analysis ($1\%$ Triton X-100, 150 mM NaCl, Complete Protease Inhibitor Cocktail (Roche Diagnostics, Brussels, Belgium), 50 mM Tris pH 7.6). After 1 h on ice with frequent agitation, the samples were centrifuged at 12,000× g for 10 min at 4 °C and the cellular lysate was collected. Conditioned media and cellular lysates were stored at −80 °C. The protein content of the conditioned media and cellular lysates was determined according to the Bradford method using bovine serum albumin (Sigma-Aldrich) as a standard [32].
## 4.3. RNA Isolation and cDNA Synthesis for mRNA Expression Analysis
Total RNA was isolated from 2 × 106 cells using the SV Total RNA Isolation System Kit (Promega, Madison, WI, USA) following the manufacturer’s instructions. RNA quality and concentration were assessed by measuring the absorbance at 230, 260, and 280 nm using a UV–Visible spectrophotometer (Nanodrop 2000, Thermo Fisher Scientific, Waltham, MA, USA). Next, first-strand cDNA was synthesized starting from 2 µg of the extracted total RNA and using the Omniscript® Reverse Transcription Kit (Qiagen, Hilden, Duitsland).
## 4.4. CPB2 mRNA Expression in Human Monocyte and Macrophage Cell Lines and Primary Cells
Prior to the measurement of CPB2 mRNA expression in the different cell types, a quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) assay to study CPB2 mRNA expression was validated by applying the MIQE guidelines [33] (Supplementary Material File S1) and appropriate reference genes for relative quantification were selected (Supplementary Material File S1). Subsequently, Cq values of the gene of interest, CPB2, were determined by RT-qPCR in all of the investigated cell types and CPB2 mRNA expression was expressed relative to the previously selected reference genes [34].
## 4.5. Western Blot Analysis
Purified proCPU was obtained from human plasma as previously described [35]. Prior to Western blot analysis, the conditioned medium of at least four independent experiments/donors was pooled for each cell type and concentrated 20-fold using 10 K centrifugal filter devices (Amicon® Ultra-0.5, Merck Millipore, Burlington, MA, USA). To obtain active CPU as a control, purified proCPU was activated at 25 °C with thrombin-thrombomodulin (4 nM and 16 nM, respectively) in the presence of 50 mM CaCl2. The reaction was stopped after 20 min by adding 4X sample buffer and immediately boiling the samples. All samples were then subjected to Western blot analysis. Following electrophoresis on a $10\%$ SDS-PAGE gel, the proteins were transferred to a nitrocellulose membrane by electroblotting. Blocking of non-specific binding sites was achieved with $5\%$ BSA in washing buffer [0.05 M Tris, 0.15 M NaCl, $0.15\%$ Tween 20, pH 7.4] for 1 h at room temperature. Next, blots were incubated overnight with primary antibodies diluted in blocking buffer: polyclonal sheep anti-human proCPU antibody (PATAFI-S, Prolytix, Essex Junction, VT, USA; 1:1500) or polyclonal rabbit anti-human proCPU/CPU antibody (CP17, Agrisera, Vännäs, Sweden; 1:1500). Subsequently, secondary antibodies diluted in blocking buffer were added for 2 h at room temperature: goat anti-sheep horseradish peroxidase (HRP) (31480, ThermoFisher; 1:5000) and goat anti-rabbit HRP (65-6120, Invitrogen; 1:5000) were used. Between the different incubations, membranes were washed 6 × 5 min with washing buffer. Chemiluminescent detection was performed using the SuperSignal West Femto Substrate Kit (Thermo Fisher Scientific). The protein bands were visualized on a OptiGo viewer and Proxima AQ-4 software. Precision Plus Protein Dual Color Standards (Bio-Rad, Hercules, CA, USA) were used for MW estimation.
## 4.6. ProCPU Measurement
ProCPU concentrations were measured in both the conditioned media and cellular lysate using a previously described, in-house enzymatic assay [36] with the modification that the conditioned media samples and the cellular lysates were concentrated 3- to 4-fold prior to proCPU measurement using a 10K centrifugal filter device (Amicon® Ultra-0.5, Merck Millipore). Samples were then incubated with AZD9684 (a potent and selective small-molecule CPU inhibitor that was a kind gift from AstraZeneca; final concentration 5 µM) or an equal volume of HEPES (20 mmol/L; pH 7.4) for 5 min [37,38]. Hereafter a mixture of human thrombin (Merck), rabbit-lung thrombomodulin (Seikisui Diagnostics, Burlington, MA, USA) and CaCl2 (Merck) (final concentrations of 4 nM, 16 nM, and 50 mM, respectively) was added to quantitatively convert proCPU into the active enzyme. Subsequently, the active CPU was incubated with the selective and specific substrate Bz-o-cyano-Phe-Arg, followed by quantification of the formed product by high-performance liquid chromatography. The enzymatic activity measured in the presence of AZD9684 was then subtracted from the enzymatic activity in the absence of AZD9684 to obtain the actual proCPU concentration and to exclude that the measured activity originated from other basis carboxypeptidases or other enzymes that could be present in the samples [36].
## 4.7. Statistical Analysis
Statistics were performed using IBM SPSS Statistics 27 and figures were compiled in GraphPad Prism 9.3.1. The specific statistical tests used in this study are mentioned in the legends underneath the figures. Data are presented as the mean ± standard error of the mean (SEM). Results were considered significant if the p-value was < 0.05.
## 5. Conclusions
In this study, we confirmed the expression of CPB2 mRNA by THP-1 and PMA-stimulated THP-1 cells and showed that CPB2 mRNA is expressed in primary human monocytes isolated from PBMCs and macrophages derived from these monocytes. On a protein level, proCPU was detected in the conditioned medium of all of the investigated cell types. Moreover, it was demonstrated that proCPU can be activated into functionally active CPU in the in vitro cell culture environment. Comparison of both the relative CPB2 mRNA expression and proCPU concentrations in the cell medium between the different cell types provide evidence that CPB2 mRNA expression and proCPU secretion in the monocytes and (activated) macrophages are related to the degree to which these cells are differentiated and activated. This sheds new light on monocytes and macrophages as local proCPU sources within atherosclerotic plaques and extra-vascular inflammatory sites and the potential role of the proCPU system as a modulator of inflammation in these environments.
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|
---
title: The Influence of Winter Swimming on Oxidative Stress Indicators in the Blood
of Healthy Males
authors:
- Roland Wesołowski
- Celestyna Mila-Kierzenkowska
- Marta Pawłowska
- Karolina Szewczyk-Golec
- Łukasz Saletnik
- Paweł Sutkowy
- Alina Woźniak
journal: Metabolites
year: 2023
pmcid: PMC9967992
doi: 10.3390/metabo13020143
license: CC BY 4.0
---
# The Influence of Winter Swimming on Oxidative Stress Indicators in the Blood of Healthy Males
## Abstract
Baths in cold water are a popular physical activity performed to improve health. This study aimed to determine whether repeated cold-water exposure leads to the up-regulation of antioxidant defenses and whether or not this leads to a reduction in basal and/or acute pulses of oxidative distress in humans. The study group consisted of 28 healthy male members of the WS club (average age 39.3 ± 6.1 years). The study sessions occurred at the beginning and the end of the WS season. During the WS season, the participants took 3-min cold-water baths in a cold lake once a week. Blood samples were collected three times during each session: before the bath, 30 min after the bath, and 24 h after the bath. The activity of selected antioxidant enzymes, including superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPx), as well as the concentration of lipid peroxidation (LPO) products, including thiobarbituric acid-reactive substances (TBARS) and conjugated dienes (CD), were determined in erythrocytes. The concentration of TBARS, CD, retinol, and α-tocopherol were determined in the blood plasma, whereas the level of other LPO products, including 4-hydroxynonenal and 8-iso-prostaglandin F2α, were determined in the blood serum. The repeated cold exposure up-regulated most antioxidant defenses, and this led to an attenuation of most indicators of oxidative stress at the baseline and acute pulses in response to cold exposure. In conclusion, due to regular cold exposure, the antioxidant barrier of winter swimmers was stimulated. Thus, short cold-bath sessions seem to be an effective intervention, inducing promoting positive adaptive changes such as the increased antioxidant capacity of the organism.
## 1. Introduction
Oxygen is an element crucial for the functioning of aerobic organisms. However, all organisms that breathe oxygen are also exposed to the harmful consequences resulting from its transformations. Excess O2 can lead to the formation of reactive oxygen species (ROS), which, apart from their physiological functions, also have harmful effects [1]. In aerobic organisms, small amounts of ROS and nitrogen free radicals under physiological conditions are constantly generated under the influence of external and internal stimuli [2,3]. Oxygen homeostasis is, therefore, one of the critical conditions that must be maintained for aerobic organisms to properly function [1,4].
Oxidative stress occurs due to the increased formation of free oxygen radicals and/or weakened functioning of the antioxidant barrier [3]. An uncontrolled release of free radicals and their derivatives by damaging nucleic acids, enzymes, and biological membranes leads to the development of pathological conditions [5]. Oxygen free radicals are responsible for lipid peroxidation (LPO) [3]. This process consists of the free-radical oxidation of unsaturated fatty acids or other lipids, resulting in the formation of peroxides of these compounds [6]. In LPO, oxygen free radicals remove electrons from lipids and produce reactive intermediates that can undergo further reactions [7,8]. LPO products can cause DNA damage and directly inhibit numerous proteins [2]. Extensive peroxidation in cell membranes causes changes in their fluidity, increased permeability, reduction of membrane potential, and ultimately the rupture of cell membranes [7]. The most frequently determined markers of lipid peroxidation include thiobarbituric acid-reactive substances (TBARS) [2]. Among the TBARS, malondialdehyde (MDA), the final product of lipid degradation caused by oxidative stress, is the most important compound [2]. Among lipid peroxidation products, 4-hydroxynonenal (4-HNE, 4-hydroxy-2,3-trans-nonenal) and isoprostanes also perform an important role. 8-iso-prostaglandin F2α (F2-isoprostane; 8-isoprostane; 8-iso-PGF2α; 8-isoP) is one of the better-known isoprostanes. Isoprostanes are generated via the mechanism of free radical formation in membrane lipids. Therefore, their formation may affect the fluidity and integrity of cell membranes [9,10,11].
The antioxidant system includes antioxidant enzymes and non-enzymatic antioxidants. Superoxide dismutase SOD is an enzyme that catalyzes the dismutation reaction of the superoxide anion radical to O2 and the less reactive H2O2 [2,12]. The resulting hydrogen peroxide is then degraded by catalase (CAT) or glutathione peroxidase (GPx) [13]. In addition to enzymatic defense, small-molecular antioxidants, including vitamins, play an important protective role against the adverse effects of ROS.
Cold is often used in medicine to reduce inflammation [14]. As a result of winter swimming, physiological changes occur immediately, while repeated exposure to cold develops adaptive mechanisms that also affect health [15]. The type of cold adaptation depends on the intensity of cold stress and individual factors such as body fat percentage, general physical activity, and diet [15]. There are few studies describing the effect of single baths in cold water on the oxidant–antioxidant balance in the human organism. Exposure to cold water induces a significant stress response similar to acute exercise, with increases in cortisol, epinephrine, and norepinephrine [16]. Acute exercise and cold exposure are known to increase levels of peroxisome proliferator-activated receptor γ coactivator-1 (PGC-1α) in muscle and adipose tissue [17,18], and this is known to lead to an increase in antioxidant defense [19]. However, there is no data on the impact of regular winter swimming throughout the autumn and winter seasons. Therefore, as part of this study, it was decided to determine the tested parameters in the same people both at the beginning (October) and at the end (April) of the winter swimming season. This study aimed to determine whether repeated cold-water exposure led to the up-regulation of antioxidant defenses and whether or not this led to a reduction in basal and/or acute pulses of oxidative distress in humans.
## 2.1. Participants
This study covered a group of 28 healthy male volunteers (average age 39.3 ± 6.1 years) who were members of a winter swimming club. Only people who regularly (at least once a week) bathed in cold and icy water for at least two previous seasons took part in the study. Before and during the study, the participants did not change their eating habits or physical activity. Eligibility criteria are presented in Table 1.
The measurement of body components was carried out using the bioelectrical impedance analyzer—Tanita BC 418 MA (Tanita Corporation, Tokyo, Japan). The body composition analysis of the study participants is presented in Table 2.
The study was approved by the Bioethical Committee operating at Ludwik Rydygier Collegium Medicum in Bydgoszcz of Nicolaus Copernicus University in Toruń, Poland (approval number: KB $\frac{514}{2014}$). Subjects participating in the experiment became familiar with the assumptions of the experiment. The study participants were also informed about the possibility of resigning from participation in the experiment at any stage without giving a reason, and they gave their written consent to participate in the study.
## 2.2. Study Design
The winter swimming season usually starts in autumn and lasts until spring, so the study was divided into two stages. The first stage took place at the beginning of the season (BS), i.e., in October, while the second stage of the research took place at the end of the winter swimming season (ES), i.e., in April (Figure 1). During the season (between the first and second dates of blood collection), the participants took cold baths once a week.
In both stages of the study, the bath consisted of a 3-min immersion in a cold lake to the depth determined by the nipple line. The water temperature was 7.3 °C at BS and 6.5 °C at ES. During the bath, the study participants were dressed in swimwear (slips), a winter hat, and gloves, as is customary during winter swimming. In order to protect their feet from injury, swimmers wore special water shoes. Before entering the water, the study participants performed a short (5-min) moderate-intensity warm-up. The experiment conditions did not differ between the two stages of the study. The study participants were dressed as they were on the first day of the experiment, performed the same warm-up, and immersed themselves in the water to the same depth. Venous blood collection was carried out at a medical point, a part of the bathing infrastructure, located by the beach. Blood for testing was collected by authorized and qualified medical personnel. At each of the two study dates, blood samples were collected three times (Figure 2):
**Figure 2:** *Collecting material for research in each of the two stages of the experiment.*
The material collected for biochemical tests included venous blood specimens collected in a vacuum system from the basilic vein. For serum collection, blood samples were collected into tubes containing a clotting activator (SiO2) and a separating gel. Determination of parameters in erythrocytes and blood plasma was performed using blood samples collected into test tubes containing the anticoagulant dipotassium edetate (K2EDTA).
TBARS concentration and SOD, CAT, and GPx activities were determined via spectrophotometric methods using a Cary 60 UV-Vis spectrophotometer (Agilent Technologies, Santa Clara, CA, USA). Concentrations of vitamins A and E were determined using high-performance liquid chromatography (HPLC) with the ProStar System kit with a fluorescence detector (Varian, Palo Alto, CA, USA). In contrast, the concentrations of 4-HNE and 8-iso-PGF2α were determined using commercial diagnostic kits based on the immunoenzymatic method (ELISA) using a SPECTROstar Nano plate spectrophotometer (BMG LABTECH, Ortenberg, Germany). All tested parameters were analyzed in duplicate, and the mean values of the tests were given as a result.
## 2.3. Determination of the Activity of Antioxidant Enzymes in Erythrocytes
SOD activity in erythrocytes was determined using the method of Misra and Fridovich [20]. This method evaluates the enzyme’s inhibition of the auto-oxidation reaction of adrenaline to adrenochrome in an alkaline environment (pH 10.2). SOD activity was expressed in U/g Hb. CAT activity was determined using the Beers and Sizer method [21]. The principle of the method is based on lowering the absorbance of the hydrogen peroxide (H2O2) solution decomposed by the enzyme. CAT activity was expressed in IU/g Hb. GPx activity was determined according to the method of Paglia and Valentine [22]. This method is based on the reaction of hydrogen peroxide decomposition by GPx with simultaneous oxidation of reduced glutathione (GSH), and the results are expressed in U/g Hb.
## 2.4. Determination of TBARS and CD Concentration in Erythrocytes and Blood Plasma
The TBARS level was determined according to the methodology of Buege and Aust [23], modified by Esterbauer and Cheeseman [24]. This method is based on the reaction between lipid peroxidation products and thiobarbituric acid (TBA) in an acidic environment. MDA is the main TBA-reactive product of lipid peroxidation. Therefore, for simplicity, the level of all TBA-reactive substances can be expressed as the concentration of MDA. The concentration of TBARS in erythrocytes was expressed in nmol MDA/g Hb and, in plasma, in nmol MDA/mL of plasma. The concentration of CD was determined according to the method of Sergent et al. [ 25]. CD are formed in the process of lipid peroxidation as a result of the rearrangement of double bonds after the detachment of a hydrogen atom from the rest of the polyunsaturated fatty acid. They have a characteristic absorbance peak at 233 nm. CD concentration in erythrocytes was expressed in absorbance units per g of Hb (Abs./g Hb). In contrast, plasma concentration of CD was expressed in absorbance units per milliliter of plasma (Abs./mL).
## 2.5. Determination of Vitamin E and A Concentration in Blood Plasma
Vitamin A (retinol) and E (α-tocopherol) concentrations were determined using the HPLC method. The mobile phase was an acetonitrile–methanol solution. Vitamin concentrations were determined using the WorkStation Polaris software and expressed in µg/L.
## 2.6. Determination of the Concentration of 8-iso-PGF2α and 4-Hydroxynonenal in Blood Serum
To determine the concentration of 8-iso-PGF2α and 4-HNE, ready-made analytical kits based on the competitive enzyme immunoassay method (ELISA) were used. 8-iso-PGF2α was determined using a kit from Cloud-Clone Corp. (Wuhan, China), while a kit from CUSABIO (Wuhan, China) was used to determine 4-HNE. The determinations were carried out in accordance with the manufacturers’ instructions. The microplates were coated with monoclonal antibodies specific to the determined parameters. The concentration of the determined parameters was determined using the MARS data analysis software and expressed in pg/mL.
## 2.7. Statistical Analysis
Statistical analysis was carried out using the STATISTICA 12 PL package (Kraków, Poland). The obtained results were subjected to statistical analysis using a one-way analysis of variance (ANOVA) test and post-hoc analysis (HSD Tukey’s test). While performing the analysis, the assumptions of the ANOVA test regarding the homogeneity of variance (Levene’s test) and the evaluation of compliance of the analyzed variables with the normal distribution (Kolmogorow–Smirnov test) were considered. The results were presented as the arithmetic mean ± standard deviation (SD). Differences at the significance level of $p \leq 0.05$ were considered statistically significant.
## 3.1. The Concentration of Lipid Peroxidation Products Increases in the Blood after Cold-Water Baths, but Regular Winter Swimming Attenuates This Effect
This study showed a statistically significant increase in the concentration of TBARS in erythrocytes as a result of bathing in cold water at BS (Table 3). At BS-30, the concentration of this lipid peroxidation product was about $37\%$ higher ($p \leq 0.001$) than at BS-0, while at BS-24 it was almost twice as high ($p \leq 0.001$) than at BS-0. Statistically significant differences were observed when comparing the concentration of TBARS in the erythrocytes at BS and ES (Table 3). The concentration of the examined parameter ES-0 was about $20\%$ lower ($p \leq 0.001$) than at BS-0. Similarly, at ES-30 and ES-24, the concentration of TBARS in erythrocytes was approximately $44\%$ ($p \leq 0.001$) and $61\%$ ($p \leq 0.001$) lower, respectively, than at BS-30 and BS-24.
The study showed a statistically significant increase in the concentration of TBARS in the blood plasma of winter swimmers as a result of exposure to low ambient temperature at BS (Table 3). The concentration of this parameter increased by about $12\%$ ($p \leq 0.001$) at BS-30 and by about $17\%$ ($p \leq 0.001$) at BS-24 compared to BS-0. At ES, the changes in TBARS concentrations in the blood plasma were opposite of those at BS. At ES-30, the concentration of TBARS in the blood plasma decreased by about $13\%$ ($p \leq 0.01$), while at ES-24 it was about $43\%$ ($p \leq 0.001$) lower than at ES-0 (Table 3). In addition, the blood plasma TBARS concentration at ES-24 was lower ($p \leq 0.001$) than at ES-30. In comparing the results of the TBARS concentration measurement in plasma at BS-0 and ES-0, no difference was found. However, the concentration of TBARS in the blood plasma at ES-30 was lower by about $28\%$ ($p \leq 0.001$) than at BS-30. Moreover, this level at ES-24 was about $55\%$ ($p \leq 0.001$) lower than at BS-24 (Table 3).
The study showed statistically significant changes in the concentration of CD in erythrocytes at BS (Table 3). At BS-30, the concentration of this LPO marker was about twice as high as BS-0 ($p \leq 0.001$). At BS-24, it was more than three times higher than at BS-0 ($p \leq 0.001$). A significant increase in the concentration of CD in erythrocytes was also observed in the tests carried out at ES (Table 3). At ES-30, this concentration was about $61\%$ ($p \leq 0.001$) higher, and at ES-24 it was about $94\%$ ($p \leq 0.001$) higher than ES-0. No differences were observed in the results when measuring the concentration of CD in erythrocytes at ES and at BS (Table 3).
At BS, statistically significant changes in plasma CD concentrations were observed both at BS-30 and BS-24 (Table 3); the concentration of CD in blood plasma was almost twice ($p \leq 0.001$) and more than three times ($p \leq 0.001$) higher after than before swimming, respectively. At ES-30, the CD concentration increased by about $62\%$ ($p \leq 0.001$) compared to ES-0, and the concentration of this LPO product at ES-24 was lower ($p \leq 0.05$) than at ES-30 (Table 3). Moreover, at ES in all three blood samples, the concentration of CD in the blood plasma was lower than at the corresponding dates at BS. Plasma CD concentration was lower by approximately $38\%$ ($p \leq 0.001$) at ES-0 than at BS-0, lower by $48\%$ ($p \leq 0.001$) at ES-30 than at BS-30, and lower by $74\%$ ($p \leq 0.001$) at ES-24 compared to BS-24 (Table 3).
In this study, a statistically significant increase in the concentration of 8-iso-PGF2α was observed due to exposure to a low ambient temperature in a study carried out at BS. The concentration of this parameter at BS-30 was about $37\%$ ($p \leq 0.001$) higher, and at BS-24, it was about $25\%$ ($p \leq 0.001$) higher, than BS-0 (Table 3). At ES, changes in the concentration of 8-iso-PGF2α in the blood serum were also observed (Table 3). The concentration of 8-iso-PGF2α in the blood serum at BS-30 increased by about $30\%$ ($p \leq 0.01$) compared to BS-0. Comparing the concentration of the examined parameter at ES and BS, significant differences in the concentration of 8-iso-PGF2α in the blood serum of the subjects were observed. At ES-30, this concentration was about $37\%$ ($p \leq 0.001$) lower, and at ES-24, it was about $42\%$ ($p \leq 0.001$) lower, than BS-30 and ES-24, respectively (Table 3). The conducted studies showed no statistically significant changes in the concentration of 4-HNE in the blood serum of study participants as a result of bathing in cold water, either at BS or ES (Table 3). However, statistically significant differences in 4-HNE concentration were found when comparing the results at ES and BS (Table 3). At ES, the concentration of 4-HNE at all three tests, i.e., ES-0, ES-30, and ES-24, was about $19\%$ ($p \leq 0.001$) lower than at BS (Table 3).
## 3.2. Winter Swimming Stimulates the Erythrocytic Activity of Antioxidant Enzymes, but Has No Effect on the Blood Plasma Concentration of Vitamins A and E
Repeated cold exposure up-regulated most antioxidant defenses, and this led to an attenuation of most indicators of oxidative stress at baseline and the acute pulses in response to cold exposure. At BS, an increase in catalase activity was observed in the erythrocytes as a result of exposure to low ambient temperature (Table 4). The activity of this enzyme increased by about $18\%$ ($p \leq 0.05$) at BS-30 and by about $30\%$ ($p \leq 0.001$) at BS-24 compared to BS-0. At ES-30, no statistically significant change in CAT activity was observed, while at ES-24, the activity of this enzyme was about $17\%$ ($p \leq 0.05$) higher than at ES-0 (Table 4). In the presented study, no statistically significant differences in CAT activity in the erythrocytes were observed between BS and ES (Table 4). Moreover, no statistically significant changes in SOD activity in the erythrocytes were found due to bathing in cold water at BS (Table 4). At ES-30, the SOD activity decreased by approximately $36\%$ ($p \leq 0.001$) compared to ES-0 (Table 4). At ES-24, the activity of SOD was about $15\%$ ($p \leq 0.001$) lower than ES-0 and, at the same time, lower ($p \leq 0.001$) compared to the activity at ES-30. Comparing the activity of SOD in erythrocytes at BS and ES, statistically significant differences were observed (Table 4). At BS-0, SOD activity was approximately $68\%$ ($p \leq 0.001$) higher than at ES-0. Moreover, the activity of this enzyme at ES-24 was about $42\%$ ($p \leq 0.005$) higher than at BS-24. On the other hand, there were no changes in GPx activity in the erythrocytes 30 min after the bath (Table 4). However, at BS-24, the activity of this enzyme was higher by about $95\%$ ($p \leq 0.001$) than at BS-0. At ES, no changes in GPx activity were observed 30 min after winter swimming (Table 4). GPx activity determined in erythrocytes at ES-0 was about two-and-a-half-fold higher than at BS-0. At ES-30 and ES-24, GPx activity in winter swimmers’ erythrocytes was almost three-fold higher ($p \leq 0.001$) and twice as high than at BS-30 and BS-24, respectively (Table 4).
This study also compared the concentration of vitamins A and E in blood plasma at BS and ES. The study showed no statistically significant changes in the concentration of vitamin A in blood plasma due to bathing in cold water, either at BS or at ES (Table 4). A significant increase in the concentration of vitamin E by about $28\%$ ($p \leq 0.05$) at BS-30 compared to BS-0 was observed (Table 4). However, there were no statistically significant differences in the concentration of the tested antioxidant vitamins between BS and ES (Table 4).
## 4. Discussion
The impact of cold on the human organism has been studied for many years. However, in the existing literature, relatively few studies have focused on the effect of low temperatures on people who are not subjected to physical effort. There is no scientific evidence confirming the beneficial effects of recreational exposure to low ambient temperatures on the human organism. In this study, an attempt was made to determine whether swimming per se is a stimulus that causes a disturbance of cell homeostasis and whether regular use of this stimulus leads to adaptive changes in the body concerning markers of oxidative stress.
## 4.1. Cold-Water Baths at the Beginning of the Winter Swimming Season Stimulate Lipid Peroxidation Processes
One of the well-known adverse effects of oxidative stress in the human organism is the intensification of LPO [26]. In this study, a statistically significant increase in the concentration of LPO products, including TBARS and CD both in blood plasma and in erythrocytes, as well as 8-iso-PGF2α in the blood serum of subjects exposed to cold, was observed at BS. An increase in the concentration of these LPO products was observed both 30 min and 24 h after the cold-water bath. These changes suggest that exposure to low ambient temperatures causes a disturbance of the oxidant–antioxidant balance toward the intensification of oxidative processes. The impact of short-term exposure to cold on oxidative stress during winter swimming was demonstrated almost 30 years ago by Siems et al. [ 27], who observed a decrease in uric acid and an increase in the level of the oxidized form of GSH after a cold-water bath. Disturbance of the oxidant–antioxidant balance as a result of swimming should be associated with the fact that this activity is a strong stress stimulus for the organism because of the large surface exposed to cold water [28,29]. As cold stress builds up, the intensity of muscle tremors increases, engaging more and more muscles, accompanied by an increase in the rate of aerobic metabolism [30]. Increased oxygen consumption is associated with increased generation of ROS, which in turn may lead to an oxidant–antioxidant imbalance and increased oxidative stress [31]. However, it is assumed that increased aerobic metabolism and incomplete oxygen reduction in the respiratory chain during the activation of defense mechanisms against cold may play a vital role in this process [31].
The mechanisms of defense against the cold also include peripheral vasoconstriction, which reduces blood flow and heat loss from the organism [32]. The significant sources of increased generation of ROS during exposure to cold may include ischemia and hypoxia caused by spasms of peripheral blood vessels [33]. Ischemia may be associated with an influx of Ca2+ ions into cells [34]. This process leads to the activation of Ca2+-dependent enzymes, such as proteases and phospholipases, which in turn results in increased generation of ROS and intensification of oxidative damage. It has been proven that the increase in the production of superoxide anion radicals may be related to the intensity of ischemia [33]. In addition, reduced energy stores during ischemia lead to the accumulation of adenine nucleotides, the breakdown of lipid membrane components, and the accumulation of free fatty acids, including arachidonic acid [35]. During reperfusion, the cooled tissues are heated. During warming, arachidonic acid can be metabolized in the lipoxygenase and cyclooxygenase pathways, which can be a source of oxygen radicals [36]. Activated neutrophils can also damage endothelial cells and increase the permeability of the endothelial cell monolayer by producing ROS [37]. As a result of reperfusion, adenine nucleotides are metabolized via the xanthine oxidase pathway [38]. Elevated xanthine oxidase activity may contribute to the formation of oxygen radicals [36].
The various mechanisms described above allow us to link exposure to low ambient temperatures with increased generation of ROS and the associated intensification of the LPO observed in the presented work. The increase in the concentration of 8-iso-PGF2α, a stable and specific free radical LPO product, observed in the presented study seems to be a fascinating result. It is worth noting that this product does not accumulate in the blood, but is rapidly dissipated, as the half-life of this compound in the blood is approximately 16 min [10]. Therefore, the persistence of high concentrations of 8-iso-PGF2α in the subjects’ blood 24 h after a winter swimming session may indicate progressive LPO. Some authors have indicated that the concentration of TBARS does not necessarily translate into the concentration of MDA [10]. It is recognized that the mere measurement of TBARS concentration reflects an increase in LPO due to oxidative stress [39]. However, in this study, to assess the severity of LPO more accurately, a total of 6 LPO-related parameters were determined, including TBARS in erythrocytes and blood plasma, CD in erythrocytes and blood plasma, and 8-iso-PGF2α and 4-HNE in blood serum.
Interestingly, it should be noted that the cold-water bath did not have a statistically significant effect on the concentration of 4-HNE. It has been shown that cells exposed to mild, transient heat or oxidative stress acquire the ability to catabolize 4-HNE more quickly, making them more resistant to its harmful effects and to apoptosis induced by oxidative stress [40]. Similar mechanisms could explain the results of this study. The metabolism of 4-HNE in the human body consists primarily of its conjugation with GSH in a reaction catalyzed by glutathione S-transferases (GSTs) to form the GS–HNE conjugate [41]. The lack of changes in the concentration of 4-HNE under the influence of cold observed in this study may be due to at least partly to efficient activity of GST. This pathway has not been investigated in the presented study, which may indicate the need to continue the experiment, expanding the panel of parameters studied by including the GSH concentration and GST activity. Increased GST expression is an important mechanism to protect cells from oxidative stress-induced apoptosis [42,43].
## 4.2. Regular Winter Swimming Diminishes the Stimulatory Effect of Cold-Water Baths on Lipid Peroxidation Processes
In this study, similar to the beginning of the season, an increase in the concentration of CD in erythrocytes and blood plasma and an increase in the concentration of 8-iso-PGF2α in blood serum was obtained after a cold-water bath at the end of the season. In turn, the concentration of TBARS in erythrocytes and the concentration of 4-HNE did not change significantly. The concentration of TBARS in blood plasma even decreased due to exposure to low ambient temperatures at ES. The observed changes in the concentration of LPO products are not entirely consistent with the results of our previous research, which included a group of experienced winter swimmers and people who had not used winter baths before [44]. Participants in these studies spent 3 min in water at 0 °C; blood samples for testing were collected before entering the water and at 5 and 30 min after the bath. A decrease in the concentration of TBARS in the erythrocytes of experienced winter swimmers 5 min after leaving the water and a general tendency to decrease the concentration of TBARS in the blood after exposure to cold, also in novice winter swimmers, was demonstrated. Changes in the concentration of TBARS were explained by the rapid and effective removal of lipid peroxidation products as a result of the emerging peripheral hyperemia [44].
The results of studies on the effect of cold on the process of LPO are often contradictory. Akhalaya et al. [ 45] studied the effect of cold water on antioxidant status in an animal model. They showed that a short, 5-min exposure of mice to cold water (13 °C) caused oxidative stress, manifested by an increase in the concentration of TBARS. Similar results were obtained by Geyikli et al. [ 46], who studied the impact of a 5-min immersion in water at 4 °C on the concentration of MDA. The authors demonstrated that low temperatures increased the concentration of this LPO product in the blood serum and liver of rats. Dede et al. [ 47] also investigated the effects of cold-water immersion in rats (3 min, 10–12 °C) and observed higher serum MDA levels after immersion. Accordingly, Ivanova et al. [ 48] showed an increase in the concentration of TBARS in the blood plasma of rats after a 10-min immersion in a $10\%$ NaCl aqueous solution at −5 °C. On the other hand, Park et al. [ 49] observed no changes in the concentration of MDA in taekwondo players who, after a fight, underwent a 20-min immersion of the lower limbs up to the knees in water at 10 °C. Sutkowy et al. [ 50] used cold-water immersion as part of recovery after 30-min of exercise on a bicycle ergometer. They indicated that a 5-min immersion in water at 3 °C decreased the concentration of TBARS in the blood plasma and, therefore, probably reduced the severity of LPO. In other studies, Sutkowy et al. [ 51] also applied cold-water immersion (5 min, 3 °C) after 30-min of exercise on a cycle ergometer. They did not show any changes in the concentration of the tested LPO products (TBARS, MDA, 8-iso-PGF2α, or 4-HNE) compared to the control group subjected to passive regeneration.
Among the products of LPO determined in this study, a statistically significant increase in concentration due to winter baths, both at BS and ES, concerned only CD and 8-iso-PGF2α. It should be assumed that the peak of conjugated diene formation occurs 30–60 min after oxidative damage, after which these compounds are rapidly metabolized and cleared [52]. CD and lipid hydroperoxides are primary products of LPO, whereas TBARS (including MDA) and 4-HNE are secondary products of LPO, appearing later as a result of increased oxidative damage [53]. The lack of changes in TBARS and 4-HNE at ES may indicate that immersion in cold water did not exceed the organism’s repair capacity. It suggests that the LPO cascade was interrupted, resulting in no increase in the concentration of secondary LPO products. Moreover, the disturbance in the form of increased oxidative processes was only a temporary change.
## 4.3. Winter Swimming Stimulates Selectively the Activity of Antioxidant Enzymes in Erythrocytes, but Has No Effect on the Concentration of Vitamins A and E in the Blood Plasma
In this study, no changes in the activity of SOD were observed after cold-water swimming at BS. However, the lack of changes in the activity of this enzyme does not necessarily indicate a disturbance in the functioning of the antioxidant barrier. Blagojević [54] noticed a decrease in the activity of SOD in organisms adapted to cold. The lack of intensification of the SOD action after cold exposure limits the formation of a highly reactive hydroxyl radical, which seems to be a favorable situation. At ES, a significant decrease in SOD activity was observed 30 min and 24 h after winter swimming. These results are consistent with Geyikli et al. [ 46], who found that a 5-min immersion in 4 °C water reduced SOD activity in rat erythrocytes.
At BS, an increase in CAT activity was observed. Moreover, GPx activity also increased 24 h after the bath. A similar pattern of changes in the activity of these enzymes was also found at ES. The obtained results may indicate an increase in the concentration of hydrogen peroxide from sources other than SOD activity. Literature data on exposure to low ambient temperature on antioxidant mechanisms are ambiguous. Mila-Kierzenkowska et al. [ 44], similar to the presented study, did not observe changes in GPx activity 30 min after winter swimming. However, the authors showed a statistically significant increase in CAT activity, indicating the crucial role of this enzyme in neutralizing ROS. Park et al. [ 49] observed that a 20-min immersion of the lower limbs up to the knees in water at 10 °C increased the activity of SOD and GPx, which confirms its beneficial effect on the activation of antioxidant mechanisms [49]. Akhalaya et al. [ 45] also observed the activation of antioxidant mechanisms in the form of increased SOD and CAT activity and increased ceruloplasmin concentration in cold-exposed mice. Sutkowy et al. [ 50], in turn, did not observe changes in the activity of SOD, CAT, and GPx after immersion in cold water (5 min, 3 °C) compared to the control group subjected to passive regeneration at room temperature. Additionally, Sutkowy et al. [ 51] showed no changes in total antioxidant capacity (TAC) after using the same regeneration regimen as above. Dede et al. [ 47] observed no changes in SOD and GPx activity in rats after a 3-min immersion in water at 10–12 °C. However, they noted a decrease in the concentration of GSH, which could be the result of the intensification of oxidative processes and the consumption of this low-molecular antioxidant.
Activating small molecule antioxidants to scavenge free radicals is a slower process than activating antioxidant enzymes [55]. In this study, no changes in vitamin A concentration were observed, which suggests that it was not used to inactivate free radicals. On the other hand, an increase in vitamin E concentration was observed at BS-30 compared to BS-0. This may be due to the activation of lipid reserves as an energy source after exposure to cold. These changes seem to protect the body against excessive LPO, in which this vitamin plays a key role [13]. In the available literature, an inverse relationship was described between the intensity of the peroxidation process and the concentration of vitamin E in various tissues [52]. Vitamin E is one of the primary antioxidants involved in scavenging peroxide radicals [56]. However, the concentration of this vitamin at ES-30 and ES-24 did not differ from the ES-0 level, suggesting that LPO did not exceed the organism’s antioxidant capacity.
## 4.4. Regular Winter Swimming Improves Oxidant–Antioxidant Balance, Including Weakened Lipid Peroxidation and Increased Activity of SOD and GPx due to Adaptive Changes
One of the main goals of the research conducted as part of this study was to investigate whether regular swimming during one autumn–winter season affects the level of oxidative stress markers. The results seem to prove the development of adaptive changes consisting of reducing the concentration of LPO products and increasing the efficiency of the antioxidant barrier. The study showed that the concentration of all tested products of LPO, except for CD in erythrocytes, was statistically significantly lower at the end of the swimming season than at its beginning. Although at ES, after bathing in cold water, an increase in the concentration of some of the tested LPO markers was observed, it remained significantly lower than at BS. At ES, before entering the cold water, the concentration was lower than at BS for TBARS in erythrocytes, CD in blood plasma, and 8-iso-PGF2α. In turn, 30 min after the cold-water bath, the concentration of all analyzed markers of LPO was statistically significantly lower than at BS. Accordingly, 24 h after leaving the water, the concentration of all LPO markers was lower at ES than BS. After the whole winter swimming season, the LPO inhibitory mechanisms are more active and reduce LPO faster than at BS. The dynamics and magnitude of these changes suggest that regular cold exposure triggers mechanisms capable of quickly and efficiently clearing LPO products after cold-water immersion.
In addition, this study showed higher SOD and GPx activity at ES than at BS, whereas CAT activity remained unaltered. These results indicate a significant increase in antioxidant capacity due to regular swimming during one autumn–winter season. High SOD activity may indicate the organism’s readiness to fight the superoxide anion radical. The lack of differences in CAT activity, with higher GPx activity, may suggest the appearance of hydrogen peroxide at ES in moderately low concentrations. It also could be suggested that glutathione-dependent antioxidant mechanisms are more important for managing the oxidative stress accompanying cold-water immersion. The expression of the PGC-1α gene has been found to be increased following cold adaptation [57,58]. PGC-1α is a potent mitochondrial respiration and biogenesis stimulator. It regulates ROS metabolism and is required to induce many ROS-detoxifying enzymes, including GPx1 and SOD2 [19]. Some studies have indicated that the PGC-1α protein enhances the synthesis of antioxidant enzymes [59]. The expression of PGC-1α is increased by physiological stimuli, such as cold, leading to mitochondrial biogenesis and increased respiration. PGC-1α is crucial in linking stimuli such as cold to an internal metabolic response such as mitochondrial biogenesis via, among others, NRF transcription factors [60]. Simultaneously, PGC-1α protects the organism from oxidative stress by initiating the anti-ROS program that prevents an increase in intracellular ROS levels. PGC-1α can also be induced by ROS and plays a crucial role in the ROS homeostatic cycle [19]. This data suggests that the increase in the activity of antioxidant enzymes observed in this study due to exposure to cold might be the effect of PGC-1α up-regulation.
Moreover, in this study, no differences in the concentration of vitamins A and E were observed after the swimming season, which suggests that regular bathing in cold water does not lead to noticeable changes in the concentration of these vitamins. As mentioned earlier, cold-water baths may potentially intensify oxidative mechanisms, so it is worth ensuring optimal protection against the possible consequences of oxidative stress through appropriate diet modification, considering the proper supply of vitamins A and E of natural origin [61].
Lubkowska et al. [ 62] studied the effects of an 8-week session of regular immersion in 5 °C water on the activity of antioxidant enzymes and LPO products in rats. The control group in the study consisted of rodents immersed in water at 36 °C. The authors showed that the efficiency of the antioxidant system was higher in females, with higher SOD activity and higher GSH concentration. They also indicated that exposure to low temperatures increased LPO in tissues. The authors emphasized that regular, repeated cold exposure can be a stressor stimulating pro-oxidative processes and may lead to the emergence of adaptive mechanisms protecting against cold-induced damage [62]. In another study, Lubkowska et al. [ 63] examined the effect of regular winter swimming (2–3 times a week for 5 months) on antioxidant parameters in healthy humans. However, studies at the beginning and the end of the season used whole-body cryotherapy (3 min, −130 °C) to disturb the oxidant–antioxidant balance. At the end of the season, winter swimmers showed less significant change in total antioxidant status following bathing than they did at the beginning of the season. In contrast to the marked increase in SOD and GPx activity before the start of the study, after 5 months of winter swimming, no changes in SOD and GPx activity were observed after using whole-body cryotherapy. After the swimming season, a significant decrease in the concentration of 8-isoprostanes was also observed [63]. Kaushik and Kaur [64] studied the effect of cold on the function of the antioxidant barrier in rats. The animals were subjected to a 3-week exposure to cold at 7–8 °C, resulting in tissue-specific changes in the antioxidant defense system. Chronic exposure to cold seems to impair the functioning of antioxidant mechanisms in rats, as lower SOD, CAT, and GPx activities were observed after the cold session. However, in those studies, an increase in GST activity was observed in all tissues (except the heart), accompanied by a decrease in GSH levels, which may be attributed to an increase in conjugation with LPO products [30].
It is worth mentioning that cold can intensify the process of thermogenesis caused by muscle tremors, thus increasing ROS generation [65]. However, muscle tremors are a response that more often concerns people not acclimatized to low temperatures because, in experienced winter swimmers, non-shivering thermogenesis and vasomotor responses predominate thermoregulation [66], which confirms that winter swimming effectively induces adaptive changes.
Low levels of oxidative stress may positively affect an organism by stimulating the antioxidant response and inducing adaptation changes. It was observed in the presented study that regular winter swimming leads to an increase in the activity of the main antioxidant enzymes. Interestingly, in the experienced winter swimmers with at least two years of winter bathing examined in this study, the antioxidant barrier seems to be weaker at BS, suggesting that adaptation to low temperatures is not permanent. This may suggest the need to continue the research for more than one autumn–winter season to assess the durability of adaptation changes to cold due to regular winter swimming. The influence of cold on the human body has been studied for many years. However, the vast majority of studies on cold focus on its impact on the effectiveness of post-workout regeneration in the context of reducing the oxidant–antioxidant imbalance [31,59,61,62,63,64,65,66,67,68,69,70,71,72,73]. According to the results of those studies, physical effort of sufficiently high intensity induces metabolic stress and leads to increased generation of ROS in skeletal muscle mitochondria [74]. The influence on human basal metabolism, thermogenesis, and cold tolerance has been reported for thyroid hormones [75]. Thyroxine (T4) seems to be a critical substrate for human cold tolerance and habituation to cold, as cold adaptation causes the deiodination of thyroxine (T4), thus promoting increased blood triiodothyronine (T3) levels [76]. A probable mechanism of adaptation in winter swimmers is an increase in the level of the thyroid hormones triiodothyronine and thyroxine. However, further studies are needed to elucidate changes in thyroid hormone levels in winter swimmers, which we did not measure in this study. The results of the presented study seem to confirm the hypothesis about the beneficial effects of regularly repeated treatments using low ambient temperatures on the human organism. Manolis et al. [ 29] indicated the potential health benefits of swimming if performed carefully. The hardening mechanism consists of regular and short-term exposure to natural stimuli, such as low temperatures, resulting in an increase in tolerance to their effects [27]. In this study, participants exhibited excellent health conditions, as shown in the body composition analysis reported in Table 2. These factors may positively influence the results. It would be reasonable and interesting to extend the research to other study groups differing, for example, in body composition. It should be considered that for people with abnormal BMI values, e.g., indicating underweight or obesity, adaptive changes might look different.
## 5. Conclusions
In conclusion, regular cold exposure during the winter swimming season causes beneficial changes in oxidant–antioxidant parameters. These changes may translate into improved health and reduced risk of lifestyle diseases. The research results may contribute to the dissemination of winter swimming by demonstrating the beneficial changes caused in the human organism due to this activity. Exposure to low ambient temperatures during a few-minute cold-water bath in the autumn and winter period causes a disturbance of the oxidant–antioxidant balance towards the intensification of oxidation processes, as evidenced by the increase in the concentration of lipid peroxidation indicators in the blood of the subjects. There was no significant contribution of vitamins A and E to antioxidant defense after exposure to cold in experienced winter swimmers, which may suggest that additional supplementation with these vitamins for winter swimmers is not justified. The antioxidant barrier in experienced winter swimmers is strengthened when stimuli stimulate the organism in the form of regular, several-minute exposures to cold. In summary, regular winter swimming does not seem to be an excessive burden for the organism in terms of the intensification of oxidative processes. Moreover, performed once a week in 3- to 5-min sessions, it effectively stimulates the organism to develop adaptive changes. Thus, several-minute sessions of winter swimming once a week can be recommended as an effective method to improve health by inducing positive adaptive changes and strengthening the organism’s antioxidant barrier.
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|
---
title: Hypertriglyceridemic Waist Phenotype and Its Association with Metabolic Syndrome
Components, among Greek Children with Excess Body Weight
authors:
- Eirini Dikaiakou
- Fani Athanasouli
- Anatoli Fotiadou
- Maria Kafetzi
- Stefanos Fakiolas
- Stefanos Michalacos
- Elpis Athina Vlachopapadopoulou
journal: Metabolites
year: 2023
pmcid: PMC9968003
doi: 10.3390/metabo13020230
license: CC BY 4.0
---
# Hypertriglyceridemic Waist Phenotype and Its Association with Metabolic Syndrome Components, among Greek Children with Excess Body Weight
## Abstract
The hypertriglyceridemic waist (HTGW) phenotype is characterized by abdominal obesity and elevated serum triglycerides. We aimed to assess the prevalence of the HTGW phenotype among children with overweight or obesity and its association with indices of insulin resistance (IR) and dyslipidemia. A total of 145 children with mean age of 10.2 years (SD = 2.31 years), $97.2\%$ of whom with obesity, were analyzed. The HTGW phenotype was defined as WC > 90th Centers for Disease Control and Prevention (CDC) percentile and triglyceride levels of ≥100 mg/dL and ≥130 mg/dL for children 0 to 9 or >10 years of age, respectively. In total, $77.9\%$ of the children had a waist circumference above the 90th percentile and $22.8\%$ had elevated triglycerides. The prevalence of the HTGW phenotype in this sample was $19.3\%$. Patients with the HTGW phenotype had significantly lower levels of High-Density Lipoprotein ($p \leq 0.001$) and were insulin-resistant, as evident by an increased mean Triglycerides Glucose Index 8.64 (SD = 0.24) vs. 7.92 (SD = 0.41) for those without the HTGW phenotype ($p \leq 0.001$), and increased prevalence ($54.5\%$) of Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) in ≥2.5 in patients with HTGW ($$p \leq 0.045$$). Children with the HTGW phenotype were more likely to have increased HOMA-IR [OR 7.9 $95\%$ CI (1.94, 32.1)]. The HTGW phenotype is a low-cost and easily available index that might help to identify children with increased cardiometabolic risk.
## 1. Introduction
Obesity is recognized as a chronic disease in childhood and adolescence, affecting a rising number of children and leading to metabolic and cardiovascular comorbidities as well as long-term complications [1,2]. According to the World Health Organization (WHO), one-third of children in the WHO European region are diagnosed as being overweight or having obesity. In the Greek population, the prevalence of pediatric abdominal obesity is reported to be among the highest worldwide, and this is very concerning, as abdominal obesity is recognized as a significant predictor of cardiovascular risk [3]. Furthermore, $60\%$ of children who are overweight before puberty will retain their overweight status as young adults; in almost all developing or developed countries, the prevalence of obesity rises among children and adolescents aged 5–19 years. Thus, it is considered as one of the most serious public health issues that threatens future health and longevity [4].
Metabolic syndrome (MetS) is a constellation of metabolic abnormalities, such as central obesity, glucose intolerance, dyslipidemia and hypertension. Despite extensive research, there is no consensus for the definition and the diagnostic criteria, thus diagnosis in the pediatric population remains controversial [5]. However, clinical and metabolic alterations in MetS are linked to increased cardiometabolic risk [6]. There are various clinical and laboratory tools proposed to identify people at increased cardiometabolic risk, associated with abdominal obesity and central adiposity. Body mass index (BMI) is a simple index of weight-for-height, commonly used to classify overweight and obesity; however, waist circumference (WC) is an anthropometric measurement that shows a stronger correlation with intra-abdominal fat than BMI [1].
The hypertriglyceridemic waist (HTGW) phenotype is characterized by the simultaneous presence of enlarged WC and hypertriglyceridemia [7]. Lemieux et al. suggested the presence of an atherogenic metabolic triad for HTGW phenotype: increased serum apolipoprotein B concentrations, high serum concentrations of small dense low-density lipoprotein (LDL) and insulin resistance (IR) [7]. The HTGW phenotype is an index that can discriminate subcutaneous from visceral obesity and predict disorders, such as cardiovascular disease (CVD), metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) [7,8]. Furthermore, HTGW has been linked to insulin resistance and the subsequent development of T2DM in adults [9].
Since the introduction of the HTGW phenotype concept, there is growing interest in investigating its correlation with different components of MetS. There are numerous studies concerning the HTGW phenotype conducted in the adult population. The HTGW phenotype in adults is associated with the presence of CVD and may be an alternative to MetS to detect those at risk [10,11,12]. In a cross-sectional study in China, hypertensive adults with the phenotype had a higher prevalence of hypercholesterolemia, high LDL, low HDL and hyperuricemia, and thus an increased cardiometabolic risk [13]. Moreover, the HTGW phenotype has been correlated with prediabetes and diabetes [14,15,16,17,18], as well as with atherogenic and coronary artery disease [17,18,19]. Yu D et al., reported a link between HTGW phenotype and abnormal hepatic and renal function (higher concentrations of alanine aminotransferase (ALT) and a reduced eGFR) [20].
There is significant evidence in the literature associating HTGW phenotype among adults and metabolic risk factors; however, there are limited data concerning the prevalence of HTGW phenotype in children and adolescents and its association with metabolic comorbidities [21,22]. Bailey et al., demonstrated that the HTGW phenotype is associated with cardiometabolic risk in children and adolescents and is a more sensitive marker than waist to height ratio (WHR) for identifying subjects at risk [23].
This study aims to assess the prevalence of HTGW phenotype among children with overweight and obesity followed at a referral center in Greece and further investigate whether there is an association between HTGW phenotype and other metabolic risk factors, such as IR, hypertension, and suspected fatty liver (NAFLD). To our knowledge, there are no data regarding the prevalence of HTGW phenotype in Greek pediatric population.
## 2.1. Study Design and Population
The study included 145 children (68 males), who were investigated, in the Department of Endocrinology, Growth and Development, “P. & A. Kyriakou” Children’s Hospital, Athens, Greece between 2013 and 2016. A total of $32.4\%$ of the participants had entered puberty according to the Tanner staging. All the patients were referred for investigation and treatment of increased body weight. Children were excluded from the analysis, if they had obesity related syndromes (such as Prader–Willi, Bardet–Biedl, Down, Alström, Laron, DiGeorge and other syndromes) [24], type 1 (T1DM) or type 2 (T2DM) diabetes, chronic kidney or CVD, long-term corticosteroid use, primary hyperlipidemia, as well as any other reason for hepatic steatosis, such as medication (amiodarone, L-asparaginase, valproic acid), cystic fibrosis, HIV, hepatitis B or C, Wilson’s disease or celiac disease.
The investigations were carried out under their routine care and approval was given for the retrospective analysis of the medical record data by the Ethics Committee of the “P. & A. Kyriakou” Children’s Hospital.
## 2.2. Anthropometric Measurements and Blood Pressure
Participants’ height, weight, WC, systolic arterial pressure (SBP) and diastolic arterial pressure (DBP) were measured. Weight and height were measured by well-trained personnel while subjects were in light clothing and barefoot. Participants’ height was measured using a wall-mounted Harpenden Stadiometer Holtain Ltd. Their weight was measured with an electronic scale (SOEHNLE Professional 2755) to the nearest 0.1 kg. WC was measured twice, midway between the lowest border of rib cage and the upper border of iliac crest with the use of inextensible anthropometric tape while the child was standing with their arms at their sides and feet closed together [22]. All measurements were taken twice, and the two measurements were averaged for analysis.
SBP and DBP values were the mean of three measurements after a 5-min rest, with a 1-min interval between each measurement, and they were measured with a calibrated G-Care SP-800 sphygmomanometer. A pediatric cuff of proper size was chosen, so that its bladder width was at least $40\%$ of the arm circumference midway between the olecranon and the acromion, and it covered 80 to $100\%$ of the circumference of the arm [25]. BMI was calculated as weight (in kilograms) divided by height (in meters) squared.
## 2.3. Assays
After a 12-h fast, glucose, lipid profile, aspartate aminotransferase (AST), ALT and insulin levels were measured.
Venous samples were collected in WEGO serum vacuum tubes with a clot activator but without any other additives. Samples were centrifuged for 10 min at 3000 rpm, at room temperature (RT) except for the insulin samples that centrifuged at 20 °C. Serum glucose levels, fasting serum lipids [serum triglycerides (Tg), total cholesterol (TC), high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol], AST and ALT were measured as soon as possible, but not more than 45 min after the blood was drawn by enzymatic, colorimetric methods in a Cobas c501 chemistry analyzer (Roche Diagnostics).
The intra- and inter-assay coefficient variability (CV) of glucose measurement in our laboratory was less than $1.7\%$.
The intra- and inter-assay coefficient variability (CV) of triglycerides measurement in our laboratory is less than $1.4\%$. Fasting insulin was measured using the immunometric reaction, ECLIA (electrochemiluminescence method) Elecsys 2010, Roche Diagnostics, Greece, all conducted in a CLIA (clinical laboratory improvement amendments) approved laboratory.
## 2.4. Definitions
Childhood obesity was defined as having a BMI equal to or greater than the sex- and age-specific 95th percentile of the Centers for Disease Control and Prevention (CDC) anthropometric reference data for children and adults, 2007–2010 [1]. Furthermore, a child or adolescent ≥2 years of age was considered as overweight if their BMI was ≥85th percentile but <95th percentile [1]. Abdominal obesity was defined as WHR ≥0.5 and WC equal to or greater than the sex- and age-specific 90th percentile [26]. Triglycerides Glucose Index (TyG) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) indices were used as predictors of insulin resistance [27,28]. The TyG index was calculated as the Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2] [27]. The HOMA-IR index was calculated as fasting plasma insulin (FPI U/l) × fasting plasma glucose (FPG mg/dL)/405 [28]. A cut-off value ≥2.5 was used for HOMA-IR [29,30,31]. Elevated arterial pressure was defined as SBP or DBP ≥90th percentile [32]. ALT ≥25.8 U/L (boys) and 22.1 U/L (girls) was defined as abnormal in this study, indicating a suspected fatty liver [33]. The HTGW phenotype was defined as WC >90th CDC percentile and triglyceride levels ≥100 mg/dL for children 0 to 9 years of age and ≥130 mg/dL for 10 to 19 years old [1]. MetS was defined according to criteria by Cook et al. [ 34] in the presence of at least three of the following variables: increased WC for gender and age (≥$90\%$), increased BP for gender, age and height (≥$90\%$), FPG ≥ 100 mg/dL, HDL ≤40 mg/dL, triglycerides ≥110 mg/dL. Dyslipidemia was defined as TC ≥ 200 mg/dL and high LDL cholesterol as ≥130 mg/dL. The midpoint value for HDL cholesterol (<40 mg/dL) was used as a 10th percentile value [35].
## 2.5. Statistical Analysis
All continuous variables followed normal distribution and are expressed as mean values with standard deviation (SD), while categorical variables are expressed as absolute values and percentages in parentheses. Student’s t-tests were used for the comparison of means and Chi-square tests for the comparison of proportions. To further evaluate the association of the HTGW phenotype with insulin resistance, we stratified children included in the analysis as follows: [1] those with a normal WC and triglycerides level, [2] those with one component of the HTGW phenotype (either high WC or high triglycerides) and [3] those with the HTGW phenotype. Univariate logistic regression analyses were used to produce odds ratios with $95\%$ confidence intervals for the association of insulin resistance (HOMA-IR ≥2.5) with the HTGW phenotype as well as other anthropometric and metabolic characteristics. The variables that had significant association in univariate logistic regression models were used in multivariable model to determine the independent association with HOMA-IR. Sex was used in multivariable model regardless as a possible confounding. The same logistic regression analyses were used to assess the association of MetS with the HTGW phenotype. Statistical significance was defined as p value < 0.05. Statistical analyses were performed using STATA V13.1 (Stata Corp., College Station, TX, USA).
## 3. Results
Demographics, anthropometric and biochemical parameters of the total sample are presented in Table 1. One hundred and forty-five children ($46.9\%$ boys) with a mean age of 10.2 years (SD = 2.31 years) were analyzed. Ninety-seven point two per cent ($97.2\%$) had obesity and the rest of them were overweight. Fifty-four point five per cent (54.5) had insulin resistance, according to the HOMA-IR index. Ninety-nine per cent ($99.3\%$) of the participants had WHR ≥ 0.5. Seventy-seven point nine per cent ($77.9\%$) of the participants had a WC above the 90th percentile and $22.8\%$ had elevated triglycerides. The HTGW phenotype was present at $19.3\%$ of the sample.
As shown in Table 2, no gender or age differences were found among children with or without the HTGW phenotype. Similarly, SBP and DBP as well as WHR ≥ 0.5 did not differ among subjects with or without the presence of the HTGW phenotype. Significantly lower levels of HDL were found in cases with the HTGW phenotype compared with those without ($p \leq 0.001$). However, TC and LDL did not differ statistically significantly in the presence of the HTGW phenotype. Furthermore, among participants with the HTGW phenotype, $71.4\%$ had HOMA-IR ≥ 2.5 vs. $50.4\%$ of participants without the HTGW phenotype, which was statistically significant ($$p \leq 0.045$$). Elevated ALT was not found to be associated with the presence of HTGW ($$p \leq 0.324$$).
Finally, the mean TyG was significantly higher for those with HTGW compared to those without HTGW (8.79 ± 0.32 vs. 8.0 ± 0.37, $p \leq 0.001$).
In univariate logistic regression models, age, puberty, HTGW phenotype, SBP and HDL were significantly associated with HOMA in children with obesity. In the multivariable model, after adjustment for these confounders, the odds for insulin resistance were increased with each added HTGW component (Table 3). Children with obesity and the HTGW phenotype were 7.9 times more likely to have HOMA-IR ≥ 2.5 compared with children with obesity and normal WC and triglycerides levels.
Regarding MetS, 21 ($75\%$) patients with the HTGW phenotype met the criteria of MetS. In univariate logistic regression analyses, the HTGW phenotype and HDL were significantly associated with MetS, as was expected, while there was a trend of association with pubertal status and total cholesterol. In multivariable analysis, after adjustment for age, sex, puberty status and total cholesterol levels, the HTGW phenotype and HDL levels remained significantly associated with MetS (Table 4).
## 4. Discussion
To our knowledge, this study represents the first study in the Greek pediatric population that assessed the prevalence of the HTGW phenotype and its correlation with metabolic risk factors. In the current study, the HTGW phenotype was present in $19.3\%$ of Greek children and adolescents with overweight or obesity. No statistically significant gender or age differences were found among children with HTGW compared to those without the phenotype. There are limited data regarding the HTGW phenotype in the pediatric population. The reported prevalence of the HTGW phenotype in adolescents varies widely between $3.3\%$ in China, $6.4\%$ in Iran and $7.3\%$ in the UK [23,36,37]. A study conducted in Brazil, which estimated the HTGW phenotype in students of both genders in public and private schools, found that its prevalence was in $20.7\%$ of the total cases. Fourteen point one per cent ($14.1\%$) were identified in males and $6.6\%$ among females [21]. The great prevalence variability among the different study groups can be attributed to the different cut-off points used to assess WC. In the scientific literature, the cut-off points for the WC range were from the 70th to the 90th percentile for age and gender [23,38]. Furthermore, there is no consensus for the triglycerides’ normal range cut-off values [23,38,39]. Moreover, studies were conducted among populations of different ethnicities.
According to the present data, the HTGW phenotype was associated with insulin resistance and lower HDL levels, a combination consistent with atherogenic tendencies. Similar findings were reported for children of different ethnic backgrounds. Alavian et al. investigated 4811 Iranian school students and demonstrated that children with this phenotype were more likely to have cardiovascular risk factors, notably the overweight ones and/or those with hypercholesterolemia [38]. Esmaillzadeh et al. reported that Iranian adolescents with the HTGW phenotype were more likely to have low HDL, high LDL, hypercholesterolemia and elevated blood pressure (BP) [39]. The study of Conceição-Machado et al. also indicated the significantly positive correlation between the HTGW phenotype and low HDL-C [40].
Visceral or intra-abdominal adiposity is the most usual cause of insulin resistance and has been identified as an important predisposing factor for the development of T2DM. In this study population, the HTGW phenotype was associated with two different insulin resistance indices, the HOΜA-IR and Tyg index. Subjects with the HTGW phenotype had a greater proportion of HOMA-IR ≥ 2.5. Children with obesity and high WC or triglycerides levels had 4.27 greater odds to have HOMA-IR ≥ 2.5, whereas those with HTGW phenotype had 7.9 greater odds to have HOMA-IR ≥ 2.5 compared with those with normal WC and triglycerides levels. Moreover, the mean TyG was 8.64 (SD = 0.24) for those with the HTGW phenotype and 7.92 (SD = 0.41) for those without HTGW phenotype ($p \leq 0.001$). Limited information is available on the effect of the HTGW phenotype on insulin resistance in the pediatric population. BRAMS study indicated a strong correlation between the HTGW phenotype and IR and metabolic syndromes in Brazilian adolescents [41]. The study of Buchan et al. also demonstrated that children with the HTGW phenotype had significantly higher cardiometabolic risk scores (based on four variables: SBP, TC:HDL-c ratio, HOMA-IR and CRP) when compared with children without the phenotype [42].
WHR is a measure of abdominal obesity and body fat distribution and appears to be a strong predictor of cardiovascular risk factors among children, independently of gender and ethnic groups [43]. The research on the relationship between WHR and the HTGW phenotype in the pediatric population is very limited. Liu et al. conducted a population-based study to investigate the hypothesis that WHR can detect adolescents at increased risk of the HTGW phenotype. They demonstrated a high prevalent HTGW phenotype in subjects with increased WHR [37]. In our study, $99.3\%$ of the participants had WHR ≥ 0.5, as was expected due to our study sample. Therefore, WHR ≥ 0.5 did not differ significantly among subjects with or without the presence of the HTGW phenotype and it could not be used to discriminate the two groups.
Regarding the elevated ALT in the presence of the HTGW phenotype, we did not find any statistically significant positive association between NAFLD risk and the HTGW phenotype. Additionally, we did not prove any significant association between the HTGW phenotype and elevated BP. However, other studies in adolescents, such as those of Esmaillzadeh and Ribero, have demonstrated that the HTGW phenotype was positively associated with higher levels of BP [39,41].
Finally, according to our findings, children with obesity and HTGW phenotype are more likely to have MetS. In our study, $75\%$ of children with the HTGW phenotype met the criteria of MetS. There are limited data regarding MetS in the Greek pediatric population. Vlachopapadopoulou et al. reported a high prevalence of MetS ($12.7\%$) in a cohort of one hundred eighty-nine Greek pre-pubertal children with obesity. Moreover, increased WC, BMI, WHR and acanthosis nigricans were recognized as early clinical indicators for increased metabolic risk [44]. Papandreou et al. investigated one hundred and twenty-five subjects with obesity, aged 11–12 years, for NAFLD risk. Forty-four children ($58.6\%$) were reported to have MetS, while children with MetS and obesity had three times the higher risk of developing NAFLD [45]. To our knowledge, our study is the first to be conducted in the Greek pediatric population, providing data for the association of the HTGW phenotype with MetS, IR, lipid profile, ALT and arterial pressure among children with excess body weight. The analysis of the factors associated with metabolic risk and insulin resistance is essential to be analyzed in pediatric patients of different ethnic backgrounds in order to appreciate biologic variability.
There are limitations in this study that should be considered. The major limitation of this study is that all the participants included in this cohort originate from only one referral center. A larger number of participants would reflect more appropriately the general population. Fat distribution, insulin sensitivity and serum lipid concentrations are affected by pubertal status. Insulin resistance is more evident in adolescence and lipid levels tend to be higher. In our study, two-thirds of the participants were pre-adolescents, and the sample of adolescent participants was limited, not allowing us to compare results between the two samples and draw reliable conclusions. Furthermore, the lack of information on other risk factors, such as level of physical activity, family history and dietary habits could be a possible confounder of our results. Moreover, we recognize that the hyperinsulinemic-euglycemic clamp is the gold standard method to assess insulin resistance. However, in order to overcome this limitation, we measured two insulin resistance indices, HOMA-IR, which is a very commonly used and recognized insulin resistance index, as well as the TyG index, which has been recently appreciated. The use of two indices contributes strength to the results.
The lack of standardization of available classification and cut-off points for the HTGW phenotype, mainly in the pediatric population, as well as the ethnic differences among populations, which influence cardiometabolic parameters, impedes the comparison between different research data sets, indicating that more research is needed in this field.
## 5. Conclusions
This study provided evidence that high prevalence of the HTGW phenotype was detected among Greek children with excess body weight. The HTGW phenotype was not associated with elevated blood pressure or elevated ALT, but it increased by almost eight times the possibility of insulin resistance. It was also associated with lower HDL levels and a higher likelihood of the presence of metabolic syndrome. As the HTGW index is simple, reproducible and low cost, it is a potentially useful tool for the early identification of children who are susceptible to cardiometabolic risk. However, future research is needed for the validation of national cut-off points among different age groups in order to obtain data with greater reliability and applicability.
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|
---
title: Maternal Pea Protein Intake Provides Sex-Specific Protection against Dyslipidemia
in Offspring from Obese Pregnancies
authors:
- Todd C. Rideout
- Gabriella A. Andreani
- Jillian Pembroke
- Divya Choudhary
- Richard W. Browne
- Saleh Mahmood
- Mulchand S. Patel
journal: Nutrients
year: 2023
pmcid: PMC9968008
doi: 10.3390/nu15040867
license: CC BY 4.0
---
# Maternal Pea Protein Intake Provides Sex-Specific Protection against Dyslipidemia in Offspring from Obese Pregnancies
## Abstract
Increased consumption of dietary pulse protein has been shown to assist in body weight regulation and improve a range of metabolic health outcomes. We investigated if the exchange of casein for yellow pea protein (YPPN) in an obese-inducing maternal diet throughout pregnancy and lactation offered protection against obesity and dyslipidemia in offspring. Sixty female Sprague Dawley rats were fed a low-calorie control diet (CON), a high-caloric obesity-inducing diet (with casein protein (CP), HC-CP), or an isocaloric/macronutrient-matched HC diet supplemented with YPPN isolate (HC-PPN) in pre-pregnancy, gestation, and lactation. Body weight (BW) and metabolic outcomes were assessed in male and female offspring at weaning and in adulthood after consuming the CON diet in the postnatal period. Consumption of the HC-PPN diet did not protect against maternal obesity but did improve reproductive success compared with the HC-CP group ($72.7\%$ versus $43.7\%$) and reduced total energy, fat, and protein in maternal milk. Male, but not female, offspring from mothers fed the HC-CP diet demonstrated hyperphagia, obesity, dyslipidemia, and hepatic triglyceride (TG) accumulation as adults compared with CON offspring. Isocaloric exchange of CP for YPPN in a high-calorie obese-inducing diet did not protect against obesity but did improve several aspects of lipid metabolism in adult male offspring including serum total cholesterol, LDL/VLDL cholesterol, triglycerides (TGs), and hepatic TG concentration. Our results suggest that the exchange of CP for YPPN in a maternal obese-inducing diet selectively protects male offspring from the malprogramming of lipid metabolism in adulthood.
## 1. Introduction
With an alarming prevalence of ~$40\%$ among American adults, obesity is a critical healthcare priority as it is closely linked with metabolic dysfunction (e.g., insulin resistance and dyslipidemia) and considered a ‘gateway’ disease that substantially increases the risk of diabetes, cardiovascular disease (CVD), and cancer [1,2]. The etiology of obesity is complex, but with the recent increase in childhood obesity, there has been a re-evaluation of early-life in utero and immediate postnatal factors that may influence lifelong obesity risk. Approximately fifty percent of pregnant women in the United States are overweight or obese [3], putting not only the mothers’ health at risk but also placing a substantial health burden on future generations before they are even born. Maternal obesity fosters an adverse in utero environment and can further influence immediate postnatal nutrient and hormone exposure through altered maternal milk composition [3,4], strongly shaping fetal development and early childhood health [5]. Offspring from obese mothers exhibit a range of metabolic abnormalities including impaired regulation of appetite and energy expenditure [6], increased adiposity [7], reduced glycemic control [8], and dyslipidemia [9].
Maternal nutrition before, during, and after pregnancy is instrumental in ensuring early-life health and shaping lifelong disease risk trajectories in offspring [10]. However, nutrition amongst women of child-bearing age is suboptimal, with nutrient and calorie intake often exceeding recommendations for energy, sugar, and saturated fat and being below recommendations for micronutrients [11,12,13]. Consumption of ultra-processed foods during pregnancy has been associated with lower diet quality, including in terms of total and plant-based proteins [14]. Pregnant mothers require a higher protein intake to support fetal growth and development, and both the source and amount of dietary protein may affect pregnancy outcomes and have implications for the long-term health of offspring [15,16].
Dietary pulses, including dry beans, peas, and lentils, have an outstanding nutritional profile and are a rich source of protein (~7.7 g of protein in ½ a cup) [17]. Supplementation with pulse protein isolates, which contain not only high-quality protein but also an array of functional bioactive compounds (i.e., phenols and bioactive peptides), has been shown to have health benefits in previous rodent studies, including protection against body weight (BW) gain, increased cecal short-chain fatty acid production, and reduced blood pressure and serum cholesterol [18,19,20,21]. However, we are not aware of previous work that has examined maternal consumption of pulse proteins in obese pregnancies as a potential strategy to improve both maternal and offspring health. Therefore, the objective of this study was to examine if the exchange of casein for yellow pea protein (YPPN) in an obese-inducing maternal diet throughout pregnancy and lactation could influence pregnancy outcomes and offer protection against obesity and dyslipidemia in offspring.
## 2. Materials and Methods
Animals, diets, and design: The experimental design is presented in Figure 1. Sixty newly-weaned [postnatal day (PND 21] female Sprague Dawley rats (Charles River, obese prone, Crl:OP-CD) were brought to the Laboratory Animal Facility at the University at Buffalo and kept under controlled conditions of light (12 h light:12 h dark), temperature (18–23 °C), and humidity ($50\%$), with free access to food and water.
Following a 1-week chow-fed acclimation period, the rats were randomized to 1 of 2 semi-purified diets for a 6-week obesity induction phase (Table 1) consisting of (i) a low-calorie control diet (CON; $$n = 10$$; total energy 3.8 kcal/g; % energy from fat, 10; protein, 20; and carbohydrate, 70) (Research Diets, D12450K) or (ii) a high-caloric obesity-inducing diet with casein protein (HC-CP; $$n = 50$$; total energy 4.8 kcal/g; % energy from fat, 44; protein, 20; and carbohydrate, 35) (Research Diets, D12451).
Following the 6-week obese-inducing phase, obese HC-CP animals demonstrating an increased BW of ≥$20\%$ vs. CON females were randomized to either remain on the HC-CP diet ($$n = 20$$) or be provided with the HC diet supplemented with the YPPN isolate at the expense of casein (HC-PPN, $$n = 15$$) ($25\%$, Vitessence Pulse 1803 pea protein, Ingredion) for an additional 4 weeks prior to mating. The HC-PPN diet was formulated to be similarly matched for energy, macronutrient, and total fiber content to the HC-CP diet based on proximate nutrient analyses of the YPPN isolate (moisture, $9.4\%$; ash, $4.21\%$; protein, $71.48\%$; fat, $6.78\%$; total carbohydrate, $8.13\%$; and calories, 3.38 kcal/g).
At the end of the obese-inducing and pre-pregnancy periods (a total of 10 weeks), non-fasting tail vein blood was collected, and the rats were bred with CON-fed male breeders to establish a timed pregnancy [22]. Pregnancy was confirmed by the presence of vaginal plugs and/or spermatozoa in vaginal lavage. Maternal BW and food intake were collected weekly throughout gestation and lactation. Following delivery, litter size and weights were recorded, and the litters were adjusted to 8 pups per dam within 24 h after birth. Where possible, litters were equally matched for the number of males and females. Litter weights were recorded weekly throughout lactation.
On lactation day 15, maternal milk was collected at a fixed time, between the hours of 9:00 to 11:00 am [23,24]. Dams received an intraperitoneal injection of oxytocin (Aspen Veterinary Resources Ltd., 2 IU/kg BW) to stimulate milk secretion and separated from their pups for ~30 min. While under isoflurane anesthesia ($3.5\%$), milk was collected in a 200 µL capillary tube following manual expression of the teat using a gentle massage. The milking procedure took ~15 min, at which point the mothers were returned to their litters.
At weaning on postnatal day 21 (PND 21), 6 offspring from each group (3 males and 3 females) were randomly selected for metabolic phenotyping in a non-fasted state. Following anesthetization, blood was collected via cardiac puncture and pooled by sex for serum separation and subsequent lipid analyses. Livers were quickly excised, weighed, flash frozen in liquid nitrogen, and stored at −80 °C for further processing and analyses.
The remaining pups (one male and one female) from each litter were weaned onto the CON diet until PND120. Food intake (ad libitum) and BW were monitored weekly throughout the post-weaning period. On PND120, adult offspring were anesthetized for non-fasting metabolic characterization as described above. The rats used in this experiment were cared for in accordance with the guidelines established by the Institutional Animal Care and Use Committee. All procedures were reviewed and approved by the Animal Care Committee at the University at Buffalo.
Blood and milk biochemistry: Maternal glucose was measured using colorimetric detection (Invitrogen, Frederick, MD, USA; EIAGLUC) and insulin using ELISA (Millipore, Billerica, MA, USA; EZRMI-13K). Serum cholesterol profiles (TC, LDL/VLDL-C, and HDL-C) in newly weaned and adult offspring were determined using enzymatic analysis (BioAssay Systems, Hayward, CA, USA; EHDL-100). Serum TG (adult offspring only) concentration was measured using enzymatic analysis (Zenbio, Durham, NC, USA; STG-1NC). Maternal milk was assessed for protein using the Bradford assay (Biorad, Hercules, CA, USA), fat using creamatocrit assessment, and carbohydrate using colorimetric analyses (Biovision, Waltham, MA, USA). Total energy content of the milk was estimated based on the analyzed concentrations of protein (4 kcal/mL), carbohydrate (4 kcal/mL), and fat (9 kcal/mL).
Tissue lipid analyses: For the assessment of offspring hepatic TG, 50–100 mg of frozen tissue was homogenized in an aqueous NP-40 ($5\%$) solution, followed by heating at 90 °C for 10 min and centrifugation at 12,000× g for 2 min. TG concentration in the supernatant was measured with a commercial kit (Zenbio, STG-1-NC) according to the manufacturer’s instructions. Hepatic cholesterol was extracted and analyzed according to our previously published procedures [25,26]. Approximately 0.5 g of pulverized liver was spiked with α-cholestane as an internal standard and saponified in freshly prepared KOH–methanol at 100 °C for 1 h. The non-saponifiable sterol fraction was extracted with petroleum diethyl ether and dried under N2 gas. Sterol fractions were analyzed with a Shimadzu GC-17A gas chromatograph fitted with a flame ionization detector using a SAC-5 capillary column (30 m × 0·25 mm × 0·25 mm, Supelco, Bellefonte, CA, USA).
mRNA extraction and real-time RT-PCR: Total RNA was isolated from frozen pulverized liver tissue (~25 mg) using the RNeasy Mini Kit (Qiagen). RNA concentration and integrity were determined with spectrophotometry (260 nm) and agarose gel electrophoresis, respectively. RNA preparation and real-time RT-PCR were conducted using a one-step QuantiFast SYBR Green RT-PCR kit (Qiagen) with a Biorad CFX96 Touch real-time PCR system. Gene expression was analyzed using the 2(-delta delta Ct) method. The following validated primer sets for target and housekeeping genes were purchased from Qiagen (QuantiTect Primer Assay): β-actin (Actb, GeneGlobe ID: QT00193473), fatty acid synthase (Fasn) (QT00371210), acetyl-CoA carboxylase (Acaca, QT00190946), sterol regulatory element-binding protein 1c (Srebf1, QT00432684), and carnitine palmitoyltransferase 1a (Cpt1a, QT01798825).
Data analyses: All statistical analyses were conducted using SPSS 16 (SPSS Inc, Chicago, IL). Data were checked for normality using the Shapiro–Wilk test. Maternal outcomes were measured with a one-way ANOVA with a least significant difference (LSD) post hoc test. Litters from each dam were considered as a single observation. The main effects of maternal exposure (CON, HC-CP, and HC-PPN) and sex (male and female from the same maternal exposure) and interaction-related effects were analyzed via two-way ANOVA. If a significant main effect or interaction was detected, a one-way ANOVA with an LSD post hoc test was conducted to assess the programming responses. Data are presented as means ± SE. Differences were considered significant at $p \leq 0.05.$
## 3. Results
Maternal and pregnancy outcomes: Maternal phenotype and pregnancy outcomes are presented in Table 2. Compared with CON dams, those consuming the HC-CP and HC-PPN diets demonstrated increased ($p \leq 0.05$) BWs and caloric intakes throughout pre-pregnancy and gestation, with no differences ($p \leq 0.05$) noted between the HC-CP and HC-PPN groups.
Although no difference ($p \leq 0.05$) was observed in time to pregnancy between groups, reproductive success, defined as mothers who gave birth to a live litter without subsequent infanticide, was reduced in HC-CP mothers ($43.7\%$) versus CON mothers ($90.0\%$) but improved ($72.7\%$) in mothers consuming the HC-PPN diet. Litter size and weight and average pup weight at birth did not differ ($p \leq 0.05$) between treatment groups. Consumption of the treatment diets did not alter ($p \leq 0.05$) maternal glucose, insulin, or the glucose:insulin ratio by the end of pre-pregnancy.
Maternal milk composition: Compared with the CON and HC-CP groups, maternal milk from HC-PPN mothers had a lower ($p \leq 0.05$) fat and protein content (g/100 mL, Figure 2a) but no change ($p \leq 0.05$) in macronutrients when expressed as % energy (Figure 2b). Milk from HC-PPN mothers had a lower ($p \leq 0.05$) total energy content compared with milk from CON and HC-CP mothers (Figure 2c).
Post-weaning offspring growth and caloric intake: Following the culling of litters, the trajectories of litter weights were increased ($p \leq 0.05$) in HC-CP and HC-PPN litters versus CON litters (Figure 3a). A significant maternal diet x sex effect was observed for final BW and feed intake in adult offspring. Adult male offspring from HC-CP and HC-PPN mothers had increased final BWs (Figure 3b,c) and caloric intakes (Figure 3d) versus offspring from CON mothers; however, no difference ($p \leq 0.05$) between these 2 groups was observed. Maternal diet did not influence BW or caloric intake in female offspring (Figure 3b–d).
Offspring metabolic outcomes: Newly weaned male and female offspring from HC-PPN dams demonstrated lower serum total-C compared with the CON offspring, mainly due to a reduction in HDL-C (Table 3). Total- and LDL/VLDL-C were increased ($p \leq 0.05$) in adult male offspring from HC-CP versus CON dams but reduced ($p \leq 0.05$) in HC-PPN offspring (vs. HC-CP). Serum TG was reduced ($p \leq 0.05$) in adult male HC-PPN offspring compared with CON and HC-CP offspring; however, no effect was observed in adult females (Table 3).
Liver weights in HC-CP and HC-PPN pups on PND21 were higher ($p \leq 0.05$) than in CON pups but did not differ from each other (Figure 4a). In adult animals, male and female pups from HC-CP dams demonstrated higher ($p \leq 0.05$) liver weights (vs. CON) that were normalized to CON levels by maternal YPPN supplementation (Figure 4c). Compared with CON, liver TG was increased ($p \leq 0.05$) to a similar extent in both newly weaned males and females from HC-CP and HC-PPN dams (Figure 4b). In adult male but not female offspring, liver TG was increased in HC-CP offspring (vs. CON) and reduced in HC-PPN offspring (vs. HC-CP) (Figure 4d). No differences ($p \leq 0.05$) were observed in liver cholesterol concentrations between the treatment groups.
mRNA expression of Acaca was reduced ($p \leq 0.05$) in HC-CP offspring compared with CON offspring (males, 0.65 fold; females, 0.4 fold) but increased ($p \leq 0.05$) in both male (1.6 fold) and female (1.9 fold) offspring from HC-PPN mothers (Figure 4e) compared with those from HC-CP mothers. Furthermore, HC-PPN offspring demonstrated higher Cpt1a mRNA expression compared with HC-CP offspring in adulthood (Figure 4e).
## 4. Discussion
Using a rat model of maternal obesity, we assessed if the quality of maternal dietary protein consumption, as part of a high-calorie diet throughout pre-pregnancy, gestation, and lactation, influenced the metabolic programming of obesity and lipid metabolism in offspring. Male, but not female, offspring from mothers fed the HC diet with casein protein (HC-CP) demonstrated hyperphagia, obesity, dyslipidemia, and hepatic TG accumulation as adults. However, although we observed no influence of YPPN on offspring BW in early life or adulthood, isocaloric exchange of casein for YPPN (HC-PPN) in a high-calorie obese-inducing diet improved several aspects of lipid metabolism in male offspring including serum total and LDL/VLDL cholesterol, serum TG, and hepatic TG concentration. Reduced liver TG in HC-PPN vs. HC-CP offspring was associated with increased mRNA expression of both Acacb and CPT1a that regulate both lipid synthesis and oxidation, respectively.
It is worth noting that the metabolic improvements we observed in adult male offspring from HC-PPN mothers were independent of any change in maternal obesity status throughout pre-pregnancy, gestation, and lactation. This is perhaps surprising given that previous work reported that pea protein consumption protected against BW gain in diet-induced obese rats by reducing feed intake [18]. However, the majority of previous work has been conducted in male rats, and, in general, few investigations have examined the influence of pulse consumption specifically in maternal obese models. The lack of improvement in maternal obesity with YPPN supplementation may also explain why we did not observe any protective effects on offspring BW. Furthermore, despite no change in maternal obesity, HC-PPN mothers demonstrated a notable improvement in reproductive success compared with HC-CP mothers (72.7 vs. $43.7\%$). Maternal nutrition has been shown to greatly influence reproduction and fertility outcomes [27]. Consumption of excess refined carbohydrates can result in metabolic dysfunction including insulin resistance that may lead to hormonal and ovulatory dysfunction [28,29]. However, we observed no difference in glycemic control outcomes (glucose, insulin, and glucose:insulin ratio) between treatment groups. Although a minor amount (~$2\%$) of maltodextrin and sucrose was removed in the HC-PPN diet to account for the carbohydrate content of the YPPN, this negligible adjustment was not likely enough to significantly alter reproductive performance. Similarly, although consumption of both high- and low-protein diets [30,31] has been reported to have adverse effects on fertility measures, the HC-CP and HC-PPN diets were formulated to have a similar macronutrient profile with $20\%$ of energy from either animal (casein) or plant-based sources (YPPN). Alternatively, by influencing embryo implantation and development in the early stages of pregnancy, the source and quality of dietary amino acids may influence fertility outcomes [27,32]. A previous prospective study reported a $50\%$ reduction in the risk of ovulatory infertility with the consumption of $5\%$ total energy as vegetable versus animal protein [33]. Thus, although the mechanism is unknown at this time, results from the current study suggest that maternal YPPN consumption may be an effective strategy to improve adverse fertility issues that are commonly observed in high-fat-fed and obese rodent models [34,35].
Both the source and amount of dietary protein have been shown to influence metabolic health in previous rodent studies [36,37,38]. However, the majority of this work has been conducted in adult (mostly male) animals. In maternal models, consumption of protein-restricted diets during pregnancy and/or lactation has been shown to induce a range of metabolic complications in offspring, including stunted growth [39], pancreatic beta-cell deficiency [40], and altered organ development [41]. Interestingly, a recent study in Wistar rats suggested that metabolic dysfunction in offspring from mothers consuming insufficient and/or low-quality protein intake during the perinatal period could be reversed via the consumption of normal protein diets during the post-weaning period in offspring [42]. Similarly, excessive maternal protein consumption has been associated with both improved metabolic outcomes (i.e., sex-specific responses in glucose tolerance and obesity [16]) and adverse health responses (i.e., increased fat mass) [43]. Alternatively, relatively few studies have examined if the source of maternal dietary protein intake during pregnancy and lactation can influence offspring health. Maternal vegetable vs. animal protein consumption throughout gestation and lactation was shown to increase BW and food intake in adult male offspring fed a postnatal vegetable-based diet [44]. These responses were associated with changes in maternal milk composition including protein and leptin. We also observed changes in maternal milk composition in mothers consuming the YPPN vs. HC mothers, including reduced total energy, fat, and protein (minor).
We observed that adult male offspring from HC-CP mothers had higher body weights and food intakes than offspring from CON mothers, confirming that maternal obesity can increase the risk of obesity in offspring, at least in males. This sex-specific response has been observed in some [45,46], but not all [47,48], previous rodent model studies investigating the transgenerational impact of maternal obesity. Chang et al. [ 2019] reported that male mouse offspring born to mothers fed a high-fat diet before conception had greater weight gain and subcutaneous adipose mass compared with their female counterparts when exposed to a postnatal high-fat diet challenge [49]. Similarly, a long-term study (with a 12-month postnatal period) by Nivoit et al. reported hyperphagia and increased body weights in male Wistar rat offspring from obese mothers. Female offspring demonstrated a similar early trend in body weight; however, the difference was not significant and converged at week 52 [50]. Previous human studies may also support a sex-specific detrimental impact of maternal obesity on offspring disease risk. In a previous study examining the association between maternal pre-pregnancy BMI and childhood body composition, Andres et al. [ 2015] reported that boys, but not girls, born to obese mothers had a higher body fat composition from ages of 2 to 6 years [51]. The underlying reasons for this detrimental sex-specific response are not entirely clear, although it may be associated with the protective effects of estrogen on obesity and cardiometabolic health [52].
Carlin et al. 2020 [53] reported that maternal consumption of pea protein during gestation and lactation reduced BWs and TG (plasma and liver) in female Wistar rat offspring compared with mothers consuming cow’s milk protein. However, their model and design differed substantially from our study as the maternal diets were not obesogenic, and offspring from the pea protein groups were exposed to a postnatal model of macronutrient dietary self-selection. Nonetheless, we also observed lower hepatic TG and reduced serum LDL/VLDL cholesterol in adult male offspring from pea-protein-fed mothers. Similarly, previous studies in adult male rodents suggest that dietary pulses protein from white lupin beans improves blood lipids and reduces liver TG concentration, possibly by inhibiting hepatic SREBP1c and FAS mRNA expression [21,54]. In our study, hepatic Acaca mRNA expression was reduced in HC-CP male offspring, possibly as a negative feedback response to higher TG, but normalized to CON levels in HC-PPN males. We also observed higher Cpt1a expression in HC-PPN versus HC-CP offspring, suggesting that the reduced hepatic TG levels in this group may be mediated by an enhanced capacity for fat oxidation. However, Cpt1a mRNA was also reduced in female HC-PPN offspring without a corresponding reduction in hepatic TG. Thus, the specific mechanism(s) underlying the sex-divergent protection against dyslipidemia in male offspring from HC-PPN dams is currently not clear but may be associated with altered milk composition. Future mechanistic understanding may be advanced by examining potential changes in the maternal microbiome (within both milk and the large intestine), as protein quality has been shown to alter microbial diversity and influence a range of health outcomes in offspring [55].
## 5. Conclusions
This study examined if the exchange of casein for YPPN in an obese-inducing maternal diet throughout pregnancy and lactation altered pregnancy outcomes and offered protection from obesity and dyslipidemia in offspring. Our findings suggest that maternal YPPN consumption may be an effective strategy to improve adverse fertility issues that are commonly observed in high-fat-fed and obese rodent models. Furthermore, we observed that in the absence of any change in maternal obesity status, maternal substitution of casein for YPPN protected adult male offspring from maternal obesity-induced dyslipidemia, with improvements in blood cholesterol, serum TG, and liver TG accumulation. We conclude that maternal dietary protein quality can influence fertility outcomes and alter offspring metabolic disease risk in later life.
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|
---
title: Exploration of Nanosilver Calcium Alginate-Based Multifunctional Polymer Wafers
for Wound Healing
authors:
- Ernest Man
- Claire Easdon
- Iain McLellan
- Humphrey H. P. Yiu
- Clare Hoskins
journal: Pharmaceutics
year: 2023
pmcid: PMC9968014
doi: 10.3390/pharmaceutics15020483
license: CC BY 4.0
---
# Exploration of Nanosilver Calcium Alginate-Based Multifunctional Polymer Wafers for Wound Healing
## Abstract
Wound care is an integral part of effective recovery. However, its associated financial burden on national health services globally is significant enough to warrant further research and development in this field. In this study, multifunctional polymer wafers were prepared, which provide antibacterial activity, high cell viability, high swelling capacity and a thermally stable medium which can be used to facilitate the delivery of therapeutic agents. The purpose of this polymer wafer is to facilitate wound healing, by creating nanosilver particles within the polymer matrix itself via a one-pot synthesis method. This study compares the use of two synthetic agents in tandem, detailing the effects on the morphology and size of nanosilver particles. Two synthetic methods with varying parameters were tested, with one method using silver nitrate, calcium chloride and sodium alginate, whilst the other included aloe vera gel as an extra component, which serves as another reductant for nanosilver synthesis. Both methods generated thermally stable alginate matrices with high degrees of swelling capacities (400–$900\%$) coupled with interstitially formed nanosilver of varying shapes and sizes. These matrices exhibited controlled nanosilver release rates which were able to elicit antibacterial activity against MRSA, whilst maintaining an average cell viability value of above $90\%$. Based on the results of this study, the multifunctional polymer wafers that were created set the standard for future polymeric devices for wound healing. These polymer wafers can then be further modified to suit specific types of wounds, thereby allowing this multifunctional polymer wafer to be applied to different wounding scenarios.
## 1. Introduction
The national health service (NHS) of the United Kingdom spent in excess of £5.3 billion on wound care in 2017, but £3.2 billion of this sum was spent on wounds that did not fully heal [1]. It is quite clear that there is an incentive to develop an effective and financially sustainable wound-healing strategy that can offset these enormous costs. Effective wound-healing strategies follow the three key aspects of antibacterial activity, facilitation of increased cellular proliferation and the maintenance of a localised moist environment that supports wound regeneration [2]. Antibacterial activity and cellular proliferation can be expedited through the means of drug delivery, whilst the maintenance of localised environmental conditions relies on the use of a physical medium to help sustain and facilitate it. Despite the requirements for an effective wound-healing strategy, it is also important to consider the production costs associated with developing such a strategy. Undoubtedly, there are materials that can elicit superior therapeutic effects with respect to wound healing, e.g., epidermal growth factors [3] and collagen [4]. However, these are typically not financially viable for use for the large majority of the population, hence restricting their applicability to those who can afford it. In this regard, a multifunctional polymer device can be developed to facilitate all three aspects required for wound regeneration, whilst minimising the cost of production.
Given these specific criteria, various reagents have been tested to facilitate various aspects of wound regeneration, [2]. Nanosilver has been selected primarily for its antibacterial activity, as it provides an alternative form of antimicrobial treatments. This is highly important given the current state of antibiotic resistance in wounds [5], whereby 4.95 million deaths were associated with 88 pathogen-drug combinations in the year of 2019 [6]. Nanosilver is a well-explored field of research, especially in the aspect of antibacterial activity, where it induces antimicrobial activity through a variety of different mechanisms, such as the signal modulation of transduction pathways and facilitation of cellular toxicity through the build-up of reactive oxygen species (ROS), which leads to oxidative stress. Nanosilver also adheres onto cell walls and membranes which disrupts the permeability and stability of the membrane, as well as the particle penetration of the cell, leading to oxidative damage [7].
Alginate had been widely used as the physical medium for facilitating substance delivery and for the maintenance of a localised moist environment [8]. Hence, alginate has been well studied for regenerative medicine due to its biocompatibility, modifiability, and low cost [9]. On the other hand, aloe vera shows a myriad of regenerative properties, including the stimulation of fibroblast proliferation and migration, enhancement of wound contraction, reduction of tissue size, acceleration of reepithelisation, etc. [ 10]. These two specific reagents were also chosen for their use in fabricating nanosilver [11,12] from silver nitrate, which provides a greener alternative to standard methods of synthesis. In a standard nanosilver synthesis, reducing agents such as sodium citrate [13,14] and sodium borohydride [15] are used, followed by capping agents such as cetyltrimethylammonium bromide (CTAB) [16] and poly(vinylpyrrolidone) [17]. These additional reagents can be cytotoxic, resulting in irritation [18] and adding an additional layer of complication in materials production, such as a more rigorous wash regime to remove these cytotoxic reagents, ultimately increasing the production costs. In this regard, the use of both aloe and alginate can mitigate this problem as they are innately non-cytotoxic, thereby not requiring any stringent wash steps, which saves on production cost and time.
The primary rationale for choosing the combination of aloe, alginate and nanosilver is the possible synergy from their combined use. This would save a substantial amount of production time and cost as this would allow the nanosilver particles to be formed within the polymer. This study aims to discover possible synergies or antagonistic effects that may exist in the fabrication of wound-regenerative devices through two specific methods. This will give insight into the necessary compromises that may need to be undertaken if this synthetic method were to be employed for large-scaled production.
For the purposes of the study, two methods will be tested and compared. The first method, producing nanosilver alginate (NA), will follow the creation of silver nanoparticles through the use of alginate as the reductant and stabilising agent in a one-pot synthesis, whilst the other method, producing nanosilver aloe alginate (NAA), will explore the simultaneous use of aloe and alginate in varying concentrations, so as to determine the effects on the nanosilver produced. Samples from both methods will be tested for their cell viability, which will ascertain their potential feasibility for wound regenerative applications. For both methods, Ca2+ is used as a cross-linker to provide structural integrity to the alginate polymer, but also for the purpose of stimulating haemostasis in a wound-regeneration scenario [19].
## 2.1. Materials
HFF-1 Human foreskin fibroblasts were sourced from ATCC (Manassas, Virginia, VA, USA) trypan Blue Solution $0.4\%$ (w/v) in PBS was sourced from Corning (Corning, New York, NY, USA), trypsin-EDTA ($0.25\%$) phenol red, Dulbecco’s Modified Eagle Medium (DMEM), penicillin-Streptomycin (10,000 U/mL), Fetal Bovine Serum (FBS), L-Glutamine (200 mM), thiazolyl blue tetrazolium bromide, silver nitrate, calcium chloride pellets and sodium alginate powder were all sourced from Sigma-Aldrich (St. Louis, MO, USA). PBS Tablets were sourced from Fisher BioReagents, aloe vera gel was sourced from Holland and Barrett and Lysogeny broth (LB) (miller) was sourced from Merck (Darmstadt, Germany).
## 2.2.1. Nanosilver Calcium Alginate Fabrication
A 0.1 mL solution of 0.1 mol/L silver nitrate was added to a solution of 10 mL of $1\%$ weight: volume sodium alginate solution, which was then stirred continuously for 1.5 h. The solution (3 mL) was then poured into a small petri dish where it was then left in a LEC Medical Freezer LSFSF39UK (Prescot, Merseyside, UK) at −21 °C for 48 h. These samples were then freeze dried at 0.3 bar and −52 °C in a Christ Alpha 1-2 LD plus freeze dryer (Düsseldorf, Germany) for a duration of 72 h, before undergoing cross-linking in 10 mL 0.1 mol/L calcium chloride solution for 0.5 h per sample. After cross-linking, the alginate polymers underwent a triplicate wash with deionised water before subsequently undergoing the freeze-drying step again. This was then repeated for 1–$10\%$ weight: volume sodium alginate solution to generate 10 separate solutions.
## 2.2.2. Nanosilver Aloe Calcium Alginate Fabrication
An aloe solution (1 L of 0.1 mol/L) was produced by dissolving 100 mL of pure aloe in 900 mL of deionised water. Sodium alginate powder (2.4 g) was dissolved in 240 mL 0.1 mol/L aloe solution for 24 h to produce a $1\%$ w/v alginate: liquid aloe solution. Sodium alginate powder (12 g) was dissolved in 240 mL 0.1 mol/L aloe solution for 24 h to produce a $5\%$ w/v alginate: liquid aloe solution. Sodium alginate powder (24 g) was dissolved in 240 mL 0.1 mol/L aloe solution for 24 h to produce a $10\%$ w/v alginate: liquid aloe solution.
To each of the 240 mL alginate aloe solutions, 2.4 mL of 0.1 mol/L silver nitrate was added to create an alginate aloe silver solution which was stirred at room temperature under standard conditions for a total 24 h. A 30 mL aliquot of solution was extracted from the alginate aloe silver solution at the time points of 1 hr, 3 h, 5 h, 7 h, 9 h, 11 h and 24 h. From each of these 30 mL solution samples, 3 mL was ejected onto 10 separate mini petri dishes. These were then placed in a LEC Medical Freezer LSFSF39UK for 48 h before they were then moved to the Christ Alpha 1-2 LD plus freeze dryer for a period of 72 h under the conditions of 0.3 bar and −52 °C. After freeze drying, all of the samples were then submerged in a 10 mL 0.1 mol/L calcium chloride solution for 0.5 h before a triplicate wash with deionised water. This, in turn, created polymer wafer disks that were 2 mm, 3 mm and 4 mm in thickness with respect to $1\%$, $5\%$ and $10\%$ w/v alginate.
## 2.3.1. ICP-OES
Samples of 3 cm diameter and 0.5 cm thickness were submerged in 40 mL deionised water for 24 h under standard conditions with stirring. Supernatant (10 mL) was extracted and filtered through a 1.2 μm syringe filter to remove any alginate fragments. Supernatant (1 mL) was then removed and combined with 1 mL aqua regia before undergoing ICP analysis to determine the quantity of nanosilver that had leeched from the polymer wafer. The samples were then analysed on a Perkin Elmer Avio500 (Waltham, MA, USA) and compared to and silver ICP standard calibration.
## 2.3.2. SEM (Pore Size Measurement)
Fully desiccated polymer matrices were analysed via the secondary electron mode on a Quanta FEG Scanning electron microscope (Waltham, MA, USA) under high vacuum at 1.4 kV with a spot size of 4 at 10 kV. These were analysed using the secondary electron detector mode.
## 2.3.3. SEM (Silver Size Measurement)
NA polymer samples were fully dissolved in 40 mL deionised water within a 50 mL Corning centrifuge tube. The samples were then centrifuged in a Thermo Scientific Heraeus Multifuge X1R centrifuge (Waltham, MA, USA) for 5 min at 14,500 rpm. The supernatant was discarded, and the centrifuge tube was then filled with 10 mL absolute ethanol, thereby submerging the pellet for 10 min. The ethanol was then discarded without disturbing the pellet. The pellet was then then gently dislodged from the centrifuge tube and transferred into a glass vial where it then air dried for 1 h.
5 w/v and $10\%$ w/v NAA polymer samples were fully dissolved in 40 mL deionised water within a 50 mL Corning centrifuge tube. The samples were then centrifuged in a Thermo Scientific Heraeus Multifuge X1R centrifuge for 20 min at 14,500 rpm. The supernatant was discarded without disturbing the hydrogel pellet and another 40 mL deionised water was added to the centrifuge before undergoing centrifugation using the same parameters. The supernatant was discarded, and the centrifuge tube was then filled with 10 mL absolute ethanol, submerging the pellet for 10 min. The ethanol was discarded, and the pellet was then transported into a glass vial where it was air dried for 1 h before analysis.
Triplicate $1\%$ w/v NAA polymer samples were fully dissolved in 40 mL deionised water within a 50 mL Corning centrifuge tube. The samples were then centrifuged in a Thermo Scientific Heraeus Multifuge X1R centrifuge for 0.5 h at 14,500 rpm. The supernatant was discarded without disturbing the hydrogel pellet, where 10 mL absolute ethanol was then added into the tube and left for 5 min. Excess aloe gel was then suspended within the absolute ethanol, which was then discarded. An additional 10 mL absolute ethanol was added into the tube, submerging the pellet, and was left for 20 min. The ethanol was discarded, and the pellet was then transported into a glass vial where it is air dried for 1 h before analysis.
These samples were then analysed on a Quanta FEG Scanning electron microscope under high vacuum via secondary electron detector mode, with a spot size of 3 at 30 kV.
## 2.3.4. FTIR Analysis
Fully desiccated polymer samples were analysed using a 0.4 cm−1 resolution Nicolet iS5 coupled with the iD5 ATR attachment (Thermofisher, Waltham, MA, USA). 16 scans were taken between 4000 to 400 cm−1 per sample utilising the ATR technique after background correction.
## 2.3.5. DSC and TGA Analysis
All samples were fully desiccated prior to analysis in a Christ Alpha 1-2 LD plus freeze dryer at −52 °C and 0.3 bar for 24 h. Samples weighing between 5 and 10 mg were analysed using a Q600 SDT thermobalance (TA Instruments, New Castle, U.K) for simultaneous DSC/TGA analysis. The samples were heated at a 5 °C/min heating rate from 20 °C to 250 °C, followed by a 30 min isothermal period before a 5 °C/min cooling from 250 °C to 20 °C. All experiments were carried out under purging nitrogen at a flow rate of 75 mL/min.
## 2.3.6. Swelling Capacity and Evaporative Water Loss
Triplicate tests were conducted on all of the samples to ascertain the average swelling capacity. Samples were fully desiccated in a in a Christ Alpha 1-2 LD plus freeze dryer for 24 h at −52 °C and 0.3 bar pressure. The desiccated samples were weighed to determine their dry weight. These samples were then submerged in deionised water for a total of 24 h at room temperature and standard atmosphere before being patted down to remove excess water. The hydrated samples were then weighed to determine their maximum weight gain over the 24 h hydration period. The sample were then left to air dry at room temperature and standard atmosphere for 24 h, where weight measurements were taken at the time intervals of 2 h, 4 h, 6 h and 24 h to determine the evaporative water loss values.
## Bacterial Strain Preparation
Escherichia coli 25922 and methicillin-resistant *Staphylococcus aureus* BAA-1766 were obtained from ATCC, whereby all the bacterial strains were cultured in lysogeny broth (LB) (miller) Merck L3522 at 37 °C for 24 h in a MIR-H263-PE incubator. Optical density (OD600) was adjusted to 0.6, giving 4 × 108 bacterial cells per mL.
## Zone of Inhibition
Staphylococcus aureus and *Escherichia coli* inoculums were cultivated prior to the experiment and inoculums of approximately 2.11 × 108 CFU/mL and 1.19 × 108 CFU/mL were made up respectively [20], were then ejected and spread onto two separate lysogeny broth agar plates. Desiccated cross-linked polymer samples were hydrated in deionised water for 24 h before they were then cut out into 0.35 cm diameter disks using a circular punch. These disks were then freeze dried in a Christ Alpha 1-2 LD plus freeze dryer for 24 h at −52 °C under 0.3 bar pressure. After freeze drying, the sample discs were placed onto the inoculated agar plates in an equidistant manner prior to incubation in a Panasonic MIR-H263-PE incubator for 48 h at 37 °C. In conjunction with the NA and NAA samples, 0.35 cm diameter calcium alginate disks were also incubated with the bacterial cultures, so as to act as the control.
After the incubation period, the plates were then sprayed with a fine mist of 2.5 mg/mL 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) to highlight areas of bacterial metabolic activity.
## Cell Culture Preparation
Human foreskin fibroblasts (HFFs) obtained from ATCC were cultured in Dulbecco′s Modified Eagle′s Medium (Gibco) reinforced with $10\%$ fetal bovine serum, $2\%$ penicillin-streptomycin and $1\%$ L-glutamine. These HFFs were then incubated in a PHCbi MCO-170AICUVH-PE incubator at 37 °C at $5\%$ CO2 atmosphere until they reached a confluence of above $90\%$, at which point they were then split.
## Cell Viability Assay
A single 0.35 cm sample disk was placed into the well of a 24-well plate, resulting in a total of 5 × 24-well plates containing triplicates of every sample between NA and NAA, with the addition of 3 cell-culture-only controls. Cell medium (500 µL) was placed into each well and then subsequently incubated for 48 h in a PHCbi MCO-170AICUVH-PE incubator (PHC, Tokyo, Japan) at 37 °C at $5\%$ CO2 atmosphere. The medium contained within each plate was removed without disturbing the cells, and each well was then subsequently washed with 0.1 mL phosphate-buffered saline (PBS). trypsin-EDTA (0.1 mL, $0.05\%$) was added to each well in every plate and then incubated for 10 min at 37 °C in $5\%$ CO2. Cell medum (0.1 mL) was ejected into each well, followed by the action of pipetting back and forth to evenly distribute the cells within the media. From each well, 20 µL was extracted and mixed with 20 µL $0.4\%$ trypan blue solution. From this solution, 20 µL was extracted and ejected into an Invitrogen countess cell counting slide, which was then placed into an Invitrogen countess automated cell counter that counted the cell viability of the sample. The data obtained from this assay were then normalised against the control values, giving a relative cell viability percentage for each sample with respect to the control.
## 3.1. SEM (Polymer Matrix)
The results in Figure 1 depict the changes in pore size and topographical morphology with respect to increasing alginate w/v ratio for NA. *The* general trend from the pore size data, seen in Figure 1B, implies a very weak negative correlation with respect to pore size as a function of increasing alginate weight to volume ratio. The standard deviations for the pore sizes are generally quite large, ranging from ±11.6 to ±18.9 μm with outliers at $2\%$ and $10\%$ w/v ratio, which have a standard deviation of ±26.4 μm and ±5.7 μm, respectively. In regards to the topographical morphology the polymer samples, $1\%$ and $2\%$ w/v samples generally have a fused topography with pores that are harder to identify, whereas from 3–$10\%$ w/v samples, the pores and macrostructural alginate strands are more defined with visible undulations.
Based on the comparison of the NAA macrostructures, seen in Figure 2, it is quite clear that the higher ratio of alginate to aloe produces clearly defined pores with more consistent topographical features, as well as a flatter and more uniform morphology. Examples of this are the images in $1\%$ w/v alginate, seen in Figure 2A, where high contrast areas are very prominent. The topography generally has large contrasts in regards to the heights between the features, which are further pronounced by the fusion of the alginate strands to a large unrefined mass. These areas are generally much darker due to the secondary electrons being obstructed, thus leading to poor visibility of said area. This occurs as a result of a large height difference between the area of interest and the surrounding topographical features, which blocks the passage of electrons, leading to a significant imbalance in lighting.
On the contrary, Figure 2C, $10\%$ w/v alginate, has very defined features with uniform lighting throughout the entirety of the image, which imply that surface of these samples are significantly flatter with respect to $1\%$ w/v alginate samples. In regard to the $5\%$ w/v alginate samples, Figure 2B, there is a flatter morphology with the exception of the 1 h and 11 h samples, which have a deeper centre compared to the surrounding topography.
In terms of the comparison of these samples with respect to the changes in pore size against stirring time, Figure 2D, $1\%$ w/v, has the lowest R2 value of 0.0122, which implies no association; however, $5\%$ and $10\%$ w/v have a R2 value of 0.556 and 0.4075, respectively, which implies a weak negative correlation. Considering the large fluctuations in standard deviation between the 1 h and 9 h in conjunction with the trend data, the general consensus would imply that there is no significant correlation between pore size and the stir time.
## 3.2. SEM (Silver Nanoparticles)
Based on the SEM analysis of NA nanoparticles seen in Figure 3A and Figure 4A, the particles appear to take upon a distinct cubic morphology at the lower % w/v values; however, as the % w/v increases, the nanoparticles lose their cubic morphology and slowly take on a more disorderly morphology, resembling a mixture of slightly disfigured rhombohedrons and octahedrons. As the % w/v values increase, the distances between vertices become less equidistant, leading to deformities relative to the cubic nanoparticle shapes. Based on the size analysis of NA particles in Figure 4A, there is a weak positive correlation between nanosilver size and increasing alginate concentration. The standard deviations do not follow any particular trend and vary greatly, with the smallest standard deviation being observed in $2\%$ w/v ±22 nm and the largest being at $7\%$ w/v ±118 nm. With respect to the average particle size, the standard deviations are relatively small given the large size ranges between average particle size. The average nanosilver particle sizes from this set range between 96 nm as the smallest and 834 nm as the largest. In terms of their size implications, the particles themselves are too big to penetrate through damaged skin [21] and so may be highly applicable to cutaneous wound healing without the risk of systemic accumulation.
Figure 3B displays the nanosilver particles generated from $1\%$ w/v NAA, where the morphology of the particles takes on a spherical shape for all the samples within the stirring time of 1–24 h. Based on the size analysis in Figure 4B, there is a strong negative correlation between particle size and stirring time, where the average particle size ranges from 105.6 nm to 45.82 nm with respect to 3 h and 24 h stirring time.
In terms of the changes in standard deviation with respect to stir time, in Supplementary Figure S1A there is weak-medium negative correlation, where the smallest standard deviation is ±7.5 nm occurring at 9 h stir time, whilst the biggest is ±16.4 nm occurring at 7 h stir time.
Nanosilver particles created by $5\%$ w/v NAA, Figure 3C and Figure 4C, demonstrate a morphology that is generally cubic in nature within the stirring times of 1–24 h. The cubic shape can easily be identified; however, the edges and vertices are not necessarily equidistant within each nano-cube, with morphological inconsistencies being present within each sample. In regards to the changes in particle size with respect to stirring time, there is no significant trend given the low R2 value of 0.1112. The largest average particle sizes belong to 1 h and 24 h stirring time, giving a size of 177.3 nm and 178.8 nm, respectively. In terms of the standard deviation for this sample set, the smallest occurs at 3 h, giving a range of ±22 nm, whereas the largest occurs at 24 h, giving a range of ±38 nm. In regard to the changes in particle size standard deviation with respect to stir time, in Supplementary Figure S1B, there is a medium positive correlation between the increase in particle size standard deviation and stir time.
Particles created via $10\%$ w/v NAA, Figure 3D and Figure 4D, demonstrate a mixture of particle morphologies, where they are primarily cubic in shape, but not necessarily with well-defined edges, as some particles have a slightly rounded edge. Based on observations, it appears that there is a trend whereby the increase in stirring time shifts the morphology from a rounded cubic shape to a more refined cubic shape with sharper and straighter edges. In regards to the changes in particle size, there is a weak positive correlation between stir time and particle size, with the smallest average size being 121 nm at 1 h stirring and the largest being 257 nm at 11 h stirring. The standard deviations for these samples generally fluctuate and are relatively large with respect to the average particle size, where the smallest set of standard deviations occur at 5 h stirring giving a deviation of ±15 m, whilst the largest occurs at 24 h stirring which is ±42 nm. In terms of the changes in particle size standard deviation relative to stir time, Supplementary Figure S1C, there is a weak-medium positive correlation, suggesting an increase in particle size standard deviation as stirring time increases.
Based on the comparison between the nanoparticles produced by $1\%$, $5\%$ and $10\%$ w/v NAA, there appears to be a distinction in terms of the morphology of each sample set. $1\%$ w/v are all spherically shaped, $5\%$ w/v are distinctly cubic, whilst $10\%$ w/v span between cubic to rounded cubic. 1–$10\%$ NA samples vary between cubic, rhombohedron and octahedron-like shapes. It may be implied that that relative concentration of aloe against alginate affected the nanoparticle morphology, whereby higher ratios of aloe to alginate result in spherical nanoparticles, whilst lower ratios of aloe to alginate result in morphologies with defined vertices, such as cubes, rhombohedrons and octahedrons. This is supported by studies that only utilise aloe and silver nitrate for nanosilver formation, whereby the particle morphology of the nanosilver is spherical [22,23]. Taking into account the fact that the NAA samples $1\%$, $5\%$ and $10\%$ w/v contained 1:1, 5:1 and 10:1 ratios of aloe:alginate, respectively, it may be implied that the predominant reducing agent in $1\%$ w/v NA is aloe, given the spherically shaped nanosilver particles. Beyond the $1\%$ w/v NAA, it is unknown whether a specific alginate concentration threshold results in a predominantly alginate-driven reduction process, so as to overshadow the aloe-driven reduction mechanisms. Given the fact that the particles generated from $10\%$ w/v NA and $10\%$ w/v 1–24 h NAA are morphologically different from one another it may be assumed that the alginate and aloe work in tandem to simultaneously reduce the silver, resulting in a unique morphology that differs from aloe or alginate only reduction processes. It can be assumed that the two reduction processes do not occur separately from one another, as it would therefore result in a mixture of relatively small spherical particles and relatively large cubic/rhombic particles, which are not present.
In terms of the size comparison between all the samples, there appears to be trend in regards to the changes in particle size relative to the differing aloe:alginate ratios. Disregarding the correlations between particle size and stir time, $1\%$ w/v NAA samples had an average particle size of 78.1 nm, $5\%$ w/v NAA samples had an average of 153.4 nm, $10\%$ w/v NAA samples had an average of 167.8 nm and NA samples overall had an average of 515.3 nm. This increase in average particle size with respect to decreasing aloe concentrations may suggest that the presence of aloe can limit the size of nanosilver particles that are undergoing reduction in alginate.
Overall, in the context of wound regeneration, the NAA and NA samples are generally feasible options, as the particle sizes are above 21–45 nm, which defines the range in which nanoparticles will penetrate through damaged skin [21]. The only exception would be $1\%$ w/v NAA 24 h stir time samples, which created particles with an average size of 45.8 nm ± 7.9 nm, possibly resulting in the penetration of damaged skin. This is an important consideration as nanosilver can accumulate within the host, leading to localised cytotoxicity within certain organs such as the lungs, kidney, spleen, and brain, etc. [ 24]. *The* general negative impacts of nanosilver on mammalian cells include genotoxic effects, cytotoxic effects and anti-proliferative effects, which all have the potential to destabilise the cell genome [25]. Due to this, it is important that the correct nanosilver sizes are chosen, so as to prevent host injury.
## 3.3. ICP-OES
The ICP data indicate that both fabrication methods release differing quantities of silver into the surrounding deionised water during the course of the 24 h submersion period. Based on the data obtained for the NA samples, in Figure 5A, 1–$10\%$ w/v, there are no discernible correlations in regards to the increase in silver release with respect to increasing weight to volume ratio. If the sample data for $1\%$ w/v were to be considered outliers, then the range of silver release would be within 0.056 ppm and 0.074 ppm.
For the NAA samples, there were no discernible trends in regards to the increase in silver release with stirring time. In terms of the range of silver release values, $1\%$ w/v had a range of 0.023–0.044 ppm, $5\%$ w/v had a range of 0.024–0.042 ppm and $10\%$ w/v had a range of 0.022–0.048 ppm. Comparison between Figure 5A,B suggests that the presence of aloe, within the confines of the alginate matrix, can help to diminish the release of silver into the surrounding environment. Given the fact that each sample was made up of 3 mL extractions, whereby each extraction originated from a bulk solution containing identical quantities of silver nitrate, each sample therefore contained 56,961.7 ppm worth of silver in each alginate matrix. From these samples, less than $0.0003\%$ of the total silver content was released within the span of 24 h.
In regards to the possible effects of nanoparticle shape and size on the ICP release values, there generally appears to be no identifiable correlation. Given the randomised nature of ICP release values from the NAA samples, it can be implied that the smaller-sized nanosilver spheres are not released more readily than that of larger cuboidal nanosilver. Taking all this into account, coupled with the total release of particles relative to the theoretical amount of nanosilver formed within the sample, it may be implied that the nanoparticles are formed interstitially within the alginate matrix. The resultant nano-morphologies form in between the alginate strands, whereby the application of freeze-drying followed by cross-linking agent further constrains the nanosilver, resulting it being tightly bound within the cross-linked alginate strands, thus leading to a lower release value.
The implications of this are quite important, as it affects the efficacy of nanosilver both in terms of its maximal antibacterial effects and cytotoxicity towards mammalian cells. The release rates may be relevant for drug release applications, where nanosilver can be utilised as a drug carrier for therapeutic purposes [26]. Assuming that it may be feasible to generate drug-loaded nanosilver within an alginate matrix, whilst being able to control the release rates of nanosilver, this could therefore lead to an extendable therapeutic window for sustained drug delivery.
## 3.4. FTIR Analysis
Given the fact that the primary material is alginate, all the samples shown in Figure 6 have a similar chemical profile to sodium alginate, Supplementary Figure S2. The peak at 3000–3600 cm−1 represents OH stretching, the 2850–2980 cm−1 represents the cyclic C-H stretching, 1500–1700 cm−1 represents the asymmetric COO stretch and 1350–1500 cm−1 represents the COO symmetric stretch. 1250–1350 cm−1 represents the OCH-CCH stretch, 1050–1100 cm−1 represents the cyclic OCO stretch, 950–1150 cm−1 represents the CO stretch and 920–980 cm−1 represents CO stretch specific to uronic acids.
For all of the samples, the positions of the peaks are essentially near identical to those of pure sodium alginate, Supplementary Figure S2. In terms of the NA samples, the peak positions remained consistent between all 10 samples, indicating that the presence of nanosilver did not affect the affect the characteristics of the alginate matrix. Comparison of both sodium alginate [27,28] and aloe [29,30] spectra with existing literature indicate that both raw materials used are near identical to those found in other literature, thereby allowing for standardisation and repeatability when applying both alginate and aloe for nanosilver fabrication.
Comparison between the NA samples, Figure 6A and the NAA samples, Figure 6B–D, does not indicate any distinct differences in terms of chemical shift patterns; however, this may be due to the fact that the composition of aloe is relatively small compared to alginate. Each $1\%$ w/v sample contains 0.03 g alginate per 0.1 mol/L 0.1 mL aloe solution, $5\%$ w/v samples contain 0.12 g alginate per 0.1 mL 0.1 mol/L aloe solution and $10\%$ w/v samples contain 0.3 g alginate per 0.1 mL 0.1 mol/L aloe solution. The relative compositions imply that the effects of aloe on the chemical shift pattern would be greatest in $1\%$ w/v; however, no peaks specific to aloe were observed. Based on Supplementary Figure S2, all of the key chemical shifts present in sodium alginate are present in aloe, with some stretches being slightly shifted, i.e., 1350–1500 cm−1 COO symmetric stretch and 1250–1350 cm−1 OCH-CCH stretch shifted upwards relative to sodium alginate. The most important differentiator between aloe and alginate lies in the presence of the 1743 cm−1 peak, which represents the $C = 0$ stretching vibrational mode in the -COOCH3 carboxylic ester group of pectin [29]. Given the fact that the 1743 cm−1 OH stretch is not present within any of the NAA samples, it could be implied that the effects of aloe on the compositional nature of the polymer are negligible.
## 3.5. Swelling Capacity and Evaporative Water Loss
The swelling capacity defines a polymer’s ability to absorb and retain water within its matrix. Based on the data observed from Figure 7A NA samples, there is a moderate positive correlation in regards to the increase in swelling capacity with respect to the increase in alginate weight to volume ratio. Within this data set, $5\%$ w/v provided the lowest average swelling capacity of $492\%$, whilst $10\%$ w/v provided the highest averages swelling capacity of $752\%$.
In terms of the data from the Figure 7B NAA samples, there is no discernible trend in regards to the stirring time on swelling capacity. This implies that the effects of nanosilver formed within the matrix minimally impacts the physiochemical parameters associated with water absorption. Within this data set, the $10\%$ w/v samples provided the highest range of swelling capacity values with the lowest average value occurring at 7 h stir time, $724\%$, whilst the highest average occurred at 11 h stir time, $835\%$. $5\%$ w/v samples had the second highest range of swelling capacity values, with the lowest average occurring at 1 h stir time, $567\%$, whilst the highest average occurs at 7 h stir time, $678\%$. $1\%$ w/v samples had the lowest overall swelling capacity values, with the lowest occurring at 7 h stir time, $401\%$, whilst the highest values occur 11 h, $476\%$.
Comparison between the different fabrication methods suggests that swelling capacity is not only unaffected by the presence of nanosilver, but is also unaffected by the presence of aloe that is integrated into the polymer matrix. Due to the nature of the fabrication process, different factors such as pore size and matrix morphology can affect the surface area and volume of the polymer matrix, thereby causing fluctuations in water absorption and retention. This is reflected in Supplementary Figure S3A,B, which indicates that there are no significant correlations associated with the increase in standard deviation as a function of increasing alginate w/v and increasing stirring time.
Examination of the data from Figure 8A indicates a medium negative correlation between relative weight loss and increasing alginate weight to volume ratio. It should be noted the fluctuations in standard deviation are most prominent after the $8\%$ w/v mark, where $8\%$ and $9\%$ w/v have a range of approximately ±$15\%$ weight loss, whilst $10\%$ w/v has approximately ±$10\%$ standard deviation.
The samples with a w/v ratio of less than $8\%$ all have standard deviations that are substantially smaller, with a range between 0.74–$3.7\%$. Given the fact that the samples with a lower w/v ratio generally retained less water, it could then be implied that that the lower standard deviation of evaporative water loss is as a result of the vast majority of water being lost, leaving only water that is deeply bound in the matrix. This would therefore explain why 8–$10\%$ w/v samples had a large range of standard deviations, as the rate of evaporation loss was enough to remove all the water contained within the pores of the matrix. It should also be noted that differences in the topography and morphology of the matrix can affect the total surface area, which in turn can affect the rate of evaporative water loss. Based on the data from NAA, Figure 8B, the relative evaporative weight loss of $1\%$ w/v and $5\%$ w/v is quite similar, falling within the range of 82–$86\%$, coupled with standard deviation values between 1 and $4\%$. For $10\%$ w/v, the average values fluctuate between 71 and $75\%$ relative weight loss, but the standard deviation is ±5 to ±$9\%$, which is substantially larger than those of the fluctuations in $1\%$ and $5\%$ w/v. *The* general implication is that the presence of aloe and nanosilver within the alginate matrix imparts minimal effect on evaporative water loss.
Overall, both NA and NAA samples provided substantial swelling capacity values, which is highly important in regards to its application in wound healing, specifically in the aspect of exudate absorption [31].
## 3.6. DSC and TGA
The thermal properties of the samples were studied using a combined DSC/TGA analysis. Based on the DSC and TGA data from Figure 9, all the samples were thermally stable up to approximately 200 °C, with no observable differences between different silver or aloe content. This implies that nanosilver and aloe did not affect the thermal properties of the alginate polymer. From the DSC analysis of NA samples Figure 9A, an endothermic event occurs between 224 and 232 °C, which coincides with the sudden weight loss event for these samples. This is likely due to thermally induced structural decomposition, such as the dehydration of -OH groups in alginate. Such decomposition events are observed in all the other samples; however, the range of occurrences differ between each sample type.
For all NAA samples ($1\%$ w/v, $5\%$ and $10\%$ w/v), as shown in Figure 9B–D, slightly higher thermal stability was shown (up to around 210–218 °C) in that the endothermic dip is broader and lower in magnitude compared to that observed from the NA samples. This result suggested that aloe possibly reduces the intensity of the endothermic event of alginate, but further investigation would be required. Comparing these DSC data with those of pure aloe and sodium alginate, Supplementary Figure S4A, NA closely resembles that of pure sodium alginate. In contrast, none of the samples bear any resemblance to the DSC profile of aloe, suggesting that the NAA samples were not simple physical mixtures of aloe and alginate.
Regarding the TGA analysis, Figure 9E–H, all samples retain a similar profile, with the major weight change event occurring just beyond 210 °C. When comparing the TGA profiles of all the samples with pure aloe and sodium alginate, Supplementary Figure S4B, all the samples resemble that of sodium alginate, with a single weight change event, whereas aloe has two weight loss events. In this regard it can be implied that the effect of aloe on the thermal properties of nanosilver alginate is generally quite low.
## 3.7. Zone of Inhibition
Based on the results presented in Figure 10 and Figure 11, it can be implied that the zone of inhibition is generally larger in NAA samples compared to NA samples.
Figure 11A depicts $1\%$ w/v ratio having a relative zone size range between 1.38 and 2.02 mm radius, $5\%$ w/v ratio ranges between 0.35 and 1.08 mm and $10\%$ w/v ratio ranges between 0.25 and 1.35 mm, where the relative zone size is the difference between the zone of inhibition size and the sample disc size. From this specific data set, we can conclude that there are no overall identifiable trends relating the zone of inhibition size to increasing stir time. This also applies to NA samples, Figure 11B, where the zone of inhibition range is between 0.12–0.95 mm, which is coupled with an extremely low R2 value, implying no that there are no significant correlations relating the zone of inhibition size with the increase in alginate weight/volume ratio.
Taking into account the data presented by the nanoparticle SEM micrographs in Figure 3, it can be suggested that the relative zone size ranges are as a result of the nanoparticle size and shape. From the NAA samples, $1\%$ w/v has the largest zone of inhibition of 1.38–2.02 mm radius, which is associated with spherical nanoparticles that have a size ranging between 45.8 nm to 105 nm. $5\%$ w/v and $10\%$ w/v NAA samples have a smaller zone of inhibition radii of 0.35–1.08 mm and 0.25–1.35 mm, respectively. For these two samples, the nanoparticle morphology is generally cubic, with their size ranging between 125.7 and 178.8 nm and 121.2 and 257.1 nm, with respect to $5\%$ w/v and $10\%$ w/v. This is also present in NA samples, which have a morphological mixture of cubes rhombohedrons and octahedrons, ranging from 96.1–985.5 nm, which is associated with the zone size range of 0.12–0.95 mm. This association can also be further linked to the ICP data from Figure 4, which implies that NAA samples all have roughly the same release values as one another but are still generally less than that of the NA samples. Overall, it appears that the spherical nanosilvers are able to elicit stronger antibacterial effects than their cuboidal counterparts; however, this may be due to their smaller average size, which may allow for improved penetration, as well as an increase in contact area, leading to improved antibacterial effect [32].
In terms of the data for the E. coli zone of inhibition experiments, the general consensus suggests that the concentration of nanosilver released may have been too low to inhibit the growth of E. coli, or that the size and morphology of the particles were simply ineffective against the bacterium.
This is supported by the fact that nanosilver has been shown to elicit antibacterial effect on E. coli [33,34,35], where the primary mechanisms include the use of reactive oxygen species (ROS) generated from the nanosilver, coupled with the increase in NAD+ to NADH ratio within the bacteria which leads to internal ROS production [36]. Generally speaking, the zone of inhibition was not present for the E. coli samples and showed signs of the bacteria invading the sample discs, as shown by the accumulation of MTT dye in some of the samples, thereby implying a lack of effective antibacterial activity. Based on the results, it could be implied that MRSA is generally more sensitive to nanosilver compared to E. coli with respect to their relative response. Given the fact that the polymer samples were desiccated prior to their placement on the agar surface, they could therefore be hydrated prior to placement, so as to pre-establish the interface needed to facilitate nanosilver release, which in turn my increase the release rate over the 24 h period.
## 3.8. Cell Viability
In terms of the relative average cell viability results for both NA and NAA samples, Figure 12, there appears to be a large fluctuation in values, with the lowest averaging around the $70\%$ viability mark, whilst the highest averages around $120\%$ viability. For $10\%$ w/v NAA samples, the typical average is around $98.4\%$, whilst $5\%$ w/v and $1\%$ w/v have a typical average of $91.7\%$ and $91.6\%$ average respectively, Figure 12A. The highest viability values for $10\%$ w/v, $5\%$ w/v and $1\%$ w/v are $120.9\%$, $107.1\%$ and $122.5\%$, respectively, whilst the lowest values are $67.6\%$, $70.88\%$ and $84\%$, respectively.
In terms of the standard deviation of the NAA samples, $10\%$ w/v NAA generally has the lowest standard deviations with an average of ±$9.4\%$ and is quite concise with its range between ±$5.4\%$ and ±$16.2\%$. $1\%$ w/v NAA has an average standard deviation of ±$13.4\%$ and is the most concise with a range of ±9.7 and ±$20.3\%$. $5\%$ w/v NAA has the highest average of ±$16.2\%$ with the largest range of ±$9.7\%$ to ±$26.9\%$. For NA samples, Figure 12B, the values average around $95.8\%$, with the largest and smallest averages being $125.8\%$ and $69.8\%$, respectively. The range of standard deviations is quite large for this sample set, with $7\%$ w/v being ±$33.7\%$, whilst the smallest is observed at $10\%$ w/v, ±$7.9\%$. Based on the data from Figure 12A,B, there does not appear to be any significant trends between relative cell viability and the parameters of stir time and alginate weight to volume.
Comparison of cell viability with respect to nanosilver can be observed in Figure 13A,B, which generally indicates that the $1\%$ w/v NAA samples and the $10\%$ w/v NAA samples have a higher cell viability than $5\%$ w/v NAA samples, whilst NA samples are on average above $80\%$ viability.
Taking into consideration the release rates, in conjunction with the nanosilver particle size and morphology, it appears that the cytotoxic effects of nanosilver have been mitigated to an extent. This may be due to the fact that the nanosilver was made interstitially between the alginate molecules, thereby reducing the HFF’s exposure to the particles. In a standard nanosilver loading experiment, the silver is loaded into the medium via diffusion, thus saturating the carrier. When the carrier is then placed into the cell medium, the initial release of nanosilver may be acute, leading to cell death as it is up taken by the cell culture [37]. In the case of NAA and NA samples, it may be suggested that the release rates of nanosilver are below the acute toxicity level, thereby implying that the intracellular accumulation of ROS is below the threshold that causes oxidative stress and thus cell death.
It should be noted that the viability results of the trypan blue method are affected by the fact that the calcium alginate polymer breaks down as it is incubated alongside the cell culture. It has been shown that fibroblasts can utilise external calcium sources to increase their proliferative capabilities [38,39,40]; however, in this instance, the calcium that is utilised is sourced from within the alginate polymer where it acts as the cross-linker holding the matrix together. As the calcium ions are consumed by the fibroblasts, the alginate begins to break down, leading to the formation of small calcium alginate fragments. Despite the PBS cleaning step, some of these smaller alginate fragments remain within the well, which then absorbs the trypan blue. Given the fact that these calcium alginate fragments can be as small as the trypsinised fibroblast cells, this can then result in a large number of false negatives during the cell counting process, as the automated cell counter identifies these alginate fragments as dead cells, leading to a cell viability percentage that is skewed downwards, away from the true value.
Amongst the cell viability percentages present within Figure 12, there are some values above the $100\%$ normalised cell viability threshold, which can be explained by the polymer acting as Ca2+ source, resulting in increased HFF proliferation, whereas the control is lacking one. Based on the light microscopy images in Figure 14, we can clearly see that the presence of the alginate polymer affects the migration and proliferation of HFF cells. Figure 14A shows the control well without any polymers, where the HFF cell growth patterns are generally of a slightly lower density and well spaced out. On the contrary, Figure 14B–D are examples of wells containing the polymer nanosilver samples, where the red ring indicates the location of where the HFF cells were bound to the alginate polymer, prior to the polymer’s detachment. Figure 14B,D, gives an example of HFF growth patterns near the peripheral edges of the alginate molecule, whereas Figure 14C demonstrates the growth pattern of HFF cells where they are bound to the face of the polymer. Based on the observations, it is quite clear that the cell density increases as it localises towards the polymer, acting as an anchor point, thereby holding the polymer to the plate. This cellular localisation, increased proliferation and migration may be explained by the fact that the alginate matrix not only acts as another interface for cellular adhesion in the Z axis, but also Ca2+ for cell growth. In the control well, the proliferation and migration of cells are limited to the X and Y axis, resulting in limited growth as the two-dimensional surface area becomes more crowded with cells. The introduction of the alginate matrix adds an extra Z dimension which gives more directional growth potential for the HFF cells. The images in Figure 14B–D show that once the cells are seeded, the populations growing on the surface of the well connect with the ones on the polymer, leading to increased cell growth as the HFF can now grow upwards towards the polymer via the fibroblast bridge. Given the fact that the polymer is suspended within the cell media and is therefore free to float around, the minute vibrations of the incubator may be enough to cause the polymer to undulate slightly and therefore provide a subtle mechanical stimulus for increased fibroblast growth [41].
Aloe was included as a regenerative agent for enhancing fibroblast proliferation; however, the data comparison between Figure 12A,B, suggests that the effects of aloe were negligible. There are three possible reasons for this. The first reason is that the concentration of aloe is too low to elicit an effect, the second reason may be that the aloe is too deeply incorporated into the alginate matrix’s architecture, thereby preventing it from being released and the third reason may be due to the fact that the proliferative effects of Ca2+ simply overshadowed that of aloe.
Overall, it can be assumed that the presence of a calcium alginate matrix is able elicit a multitude of advantages in regard to increased fibroblast growth, which in turn leads to a higher turnover of live cells relative to dead cells and thus a high degree of cell viability. These advantages include, Ca2+ release, three-dimensional cellular migration, and mechanical stimulation, all of which appear to be able to mitigate the cytotoxic effects of nanosilver particles of varying sizes and morphologies.
## 4. Conclusions
In this study, we have demonstrated two simple methods of alginate-facilitated nanosilver synthesis to form a multifunctional polymer wafer for wound healing. Both methods generate samples that can elicit controlled nanosilver release, which display antibacterial effects towards MRSA whilst providing high degrees of skin cell viability, as well as being able to retain a high swelling capacity for exudate absorption. The inclusion of Ca2+ acts as a cross-linker which maintains the structural integrity of the alginate polymer, whilst acting as a source of Ca2+ release for fibroblast proliferation and host haemostasis. Both methods generate nanosilver particles of varying sizes and morphologies, with the smaller spherical nanosilver showing the greatest antibacterial efficacy. However, when applied to cell viability and the physiochemical characteristics of the polymer, the effects of nanoparticle size and morphology were negligible. Generally speaking, the release rates of nanosilver are lower than that of commercial products [42], but they were still able to elicit effective antibacterial activity. Based the data generated from this study, $1\%$ w/v NAA samples with a stir time of less than 24 h are suggested as the most viable options for wound regeneration, as their particle size is above the penetration threshold of damaged skin, whilst providing the greatest antibacterial efficacy. This therefore suggests that the simultaneous utilisation of aloe and alginate for silver reduction is advantageous for wound regenerative applications Future experiments could aim to modify the current polymer matrix by increasing the nanosilver release rate and whilst adding other regenerative agents into the polymer, so as to increase its antibacterial and cellular proliferative capacity. Other suggestions include the replacement of Ca2+ with other cations for cross-linking, or perhaps the simultaneous utilisation of multiple cations instead [43], so as to explore the possible therapeutic release effects towards wound healing.
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|
---
title: 'Workplace Health Promotion Embedded in Medical Surveillance: The Italian Way
to Total Worker Health Program'
authors:
- Nicola Magnavita
journal: International Journal of Environmental Research and Public Health
year: 2023
pmcid: PMC9968016
doi: 10.3390/ijerph20043659
license: CC BY 4.0
---
# Workplace Health Promotion Embedded in Medical Surveillance: The Italian Way to Total Worker Health Program
## Abstract
In 2011, NIOSH launched the Total Worker Health (TWH) strategy based on integrating prevention and health promotion in the workplace. For several years now, in Italy, this integration has led to the creation of workplace health promotion embedded in medical surveillance (WHPEMS). WHPEMS projects, which are also implemented in small companies, focus each year on a new topic that emerges from the needs of workers. During their regular medical check-up in the workplace, workers are invited to fill in a questionnaire regarding the project topic, its outcome, and some related factors. Workers receive advice on how to improve their lifestyles and are referred to the National Health Service for any necessary tests or treatments. Results collected over the past 12 years from more than 20,000 participants demonstrate that WHPEMS projects are economical, sustainable, and effective. The creation of a network of occupational physicians who are involved in WHPEMS projects could help to improve the work culture, health, and safety of workers.
## 1. Introduction
The Total Worker Health (TWH) Program, defined “as policies, programs, and practices that integrate protection from work-related safety and health hazards with promotion of injury and illness-prevention efforts to advance worker well-being” [1], was launched by NIOSH in 2011 as a new public health strategy that quickly gained support in several countries. The TWH approach provides a comprehensive framework for enhancing worker well-being, health, and safety. *The* general well-being of employees is improved by adopting an integrated approach that prioritizes safety and simultaneously undertakes other workplace initiatives (such as healthy work design, employee training and development, accident and sickness prevention efforts, etc.). The principles of TWH, summarized in a handbook published in 2016 [2], provide an up-to-date preventive strategy that is compatible with traditional occupational safety and health prevention procedures but also acknowledges the potential importance of job-related issues for the health of employees, their families, and their communities.
In order to promulgate this strategy, NIOSH has set up Centers of Excellence for Total Worker Health to provide the scientific data required to create new solutions for TWH challenges. The research carried out at these centers produces new information and proposes creative solutions to problems currently encountered by modern enterprises. Through nonfunded collaborations with governmental and nonprofit organizations, NIOSH has also established a TWH partnership program that aims to increase the visibility and impact of TWH initiatives by publicly acknowledging the efforts companies make in order to advance THW research and practice.
The development and application of TWH principles have been the subject of considerable debate among prevention operators since the new approach can lead to ethical dilemmas. Many believe that decision-making should be based on ethical constructs [3], but the new model has often been seen to be implemented amid a climate of corporate supremacy and in pursuit of a relentless neoliberal agenda. As a result, integration attempts have sometimes failed to effectively combine wellness with safety and health and have instead placed a focus on individual worker responsibility for health [4]. Moreover, there is no agreement on which program components should be considered “TWH,” how much emphasis should be placed on organizational work settings, or which organizational or individual outcomes are the most important [5]. To clarify these fundamental points, four factors have been proposed for consideration: (i) coordination and interaction of workplace programs across domains; (ii) assessment of both work and nonwork exposures; (iii) emphasis on interventions to make the workplace more health-promoting; and (iv) essential participation of workers in prioritizing and planning intervention to foster self-efficacy. Basically, TWH involves organizational change designed not only to incorporate two managerial functions with specific objectives, legal obligations, and internal incentives and resources but also to steer the firm toward salutogenesis [5].
Furthermore, there is little concrete evidence of the obstacles and enabling factors involved in the acceptance, implementation, and sustained maintenance of TWH initiatives [6]. Methods such as ROI (return on investment), which are used to assess the effectiveness of programs, need to be carefully evaluated since their application has led to substantial criticism [7]. In particular, a thorough study has not been made regarding the effectiveness of TWH interventions in small businesses that require outside help to expand or enhance current workplace health and safety initiatives [8]. As suggested by Rohlman et al. [ 9], at least eight key points should be considered: value and return on investment (ROI), organizational factors, program design, employee engagement, low-cost strategies, evaluation, and integration.
The US initiative has aroused interest in several countries that have tried to adapt the philosophy of TWH to different national conditions. For example, Germany has adopted “workplace health management,” a comprehensive approach to safeguard, advance, and manage employees’ health at work [10]. The models followed by German companies include four subcategories of intervention: “occupational health and safety” and “reintegration management” include legally required procedures, while “workplace health promotion” and “personnel development” share similarities with TWH but are tailored to meet specific company requirements.
In Italy, the Ministry of Health, through the National Prevention Plan (NPP) for the 5-year period 2020–2025 [11], has made explicit reference to the TWH approach in the Central Support Line No. 3, “Activation of technical tables for the strengthening of the overall health of the worker according to the Total Worker Health approach.” On 15 June 2022, the Italian Society of Occupational Medicine (SIML) approved the creation of a working group on health promotion that would assist occupational physicians in creating workplace health promotion initiatives in keeping with the TWH approach and would establish a link between general practitioners (GPs) and occupational physicians (OPs) [12].
While there is little doubt that health promotion is part of the occupational health mission and that OPs and GPs share the same public health goals, collaboration between these different professional categories is far from automatic and requires programs, resources, and guidelines. Reports of experiences in the USA showed that resource shortages, the organizational structure of safety and health services, and incompatible techniques were obstacles to an OP–GP partnership, whereas knowledge of TWH methodologies, proximity to TWH Centers of Excellence, and leadership initiatives acted as facilitators [13].
However, a transfer of the US experience to other social contexts must take into consideration differences in health and social care systems. In the USA, healthcare is predominantly private. Companies provide resources for employee healthcare through insurance policies; consequently, they have a vested interest in reducing disease among their employees in order to cut insurance costs. On the contrary, the Italian National Health Service (NHS) guarantees free healthcare for all, and workers’ insurance against accidents and occupational diseases is compulsory. Companies contribute through taxation to the NHS and the National Institute for Social Security (INPS) and pay compulsory insurance to the National Institute of Insurance for Accidents and Occupational Diseases (INAIL). Therefore, they do not have an immediate economic return from a reduction in injuries or illnesses. Furthermore, in Italy, over $92\%$ of active enterprises are small or very small and employ $82\%$ of workers [14]. These conditions underlie the great difficulty in finding resources to support health promotion programs, particularly in small and medium-sized Italian businesses. On the other hand, Italy has numerous occupational physicians (around 5500) who annually take care of 14 million workers by carrying out approximately 10 million examinations per year [15]. This situation increases the possibility of conducting health promotion programs in the workplace.
For many years, our university has developed techniques that enable health promotion programs to be disseminated during health surveillance activities in the workplace. This article describes the workplace health promotion method embedded in medical surveillance (WHPEMS), which has been applied by occupational physicians, also in small companies. By exploiting the unique characteristics of the Italian NHS that offers free and universal access, this method has limited the need for resources and has been able to envisage and implement the integration criteria of prevention and promotion postulated by the NIOSH. The purpose of this article is to provide OPs with a simple, effective, and economical method of promoting health in the workplace. The manuscript aims to present in detail an initiative in the methodology applied in occupational settings.
## 2. Materials and Methods
The essential prerequisite for carrying out successful workplace initiatives is the management of occupational risks. In order to implement the integrative approach to the concept of occupational health, which is the basis of the TWH, it is essential, first of all, to provide for the prevention of occupational risks. Only when this is achieved is it legitimate to plan the promotion of workers’ health. Our school adopted the A.S.I.A. (assessment, surveillance, information, audit) model [16] for risk management., According to this model, the various phases of risk assessment, surveillance of workplaces and workers, and occupational information and training must be closely linked and shared among all prevention operators. The identification of crucial aspects in the system must result in investigations or audits designed to suggest action for improving the work environment. In small companies, in particular, risk management requires a significant contribution on the part of the occupational physician, who participates personally in the various phases of the process. In fact, the intervention of an occupational physician in the workplace is essential for identifying the workers’ health needs.
WHPEMS interventions are conducted every year in accordance with a proposal based on indications previously provided by the workers. The occupational physician collects this information during visits to the workplace when he/she invites workers to describe their work cycle, identify any critical issues, and by means of participatory ergonomic groups (in Italian, Gruppi di Ergonomia Partecipativa, G.E.P.), make proposals for workplace improvement [17]. The G.E.P. technique, which is taught by our school and is freely accessible, consists of working with small groups of workers to improve the working environment, processes, and procedures. The groups are made up of all workers who contribute to supplying a product, for example, in a hospital ward, from doctors, nurses, and ancillary personnel, and at a petrol station by the owner, yard workers and cashiers, and so on. All contribute to describing their work and identifying critical points in relation to each for which they suggest possible solutions. The simplest and cheapest shared solutions are proposed by the doctor to the company. The interviews with the workers also serve the doctor to identify the topics of the promotion campaigns.
Over the years, chosen topics have concerned pathologies with a particular impact on productivity and determinants of well-being. Consequently, headache disorders (one of the main causes of years lived with disability globally) [18], musculoskeletal disorders [19], and syncope (responsible for a significant increase in the risk of occupational accidents and termination of employment) [20] have been investigated. Symptoms associated with air quality [21,22,23] and with the low quality of work organization [24] have also been studied due to their high prevalence. In other cases, the search for strategies to increase work engagement and reduce burnout and occupational stress [25,26] has been the main objective. The close relationship between occupational stress and sleep disturbances [27] and between workplace violence and stress [28] has led to a project designed to promote sleep quality [29] and another for encouraging nonviolent behaviors [30]. Aging and its consequent effect on working attitudes [31,32] prompted another project, supported by a comparison with European experiences in the framework of an international collaboration [33,34,35]. The pandemic caused by the SARS-CoV-2 virus led us to evaluate the onset of post-COVID-19 syndrome in workers [36,37] and seek ways of promoting their recovery. In 2022, we addressed the issue of eating disorders [38,39], and at the request of workers, in 2023, we will develop the logical continuation of this project with a program aimed at encouraging the spread of the Mediterranean diet [40].
Workers are invited to participate in WHPEMS action during their regular medical examination in the workplace. There is no sampling because all those undergoing health surveillance are invited to participate. Workers are free to accept or refuse, but the vast majority agree to provide the requested data and are eligible for the promotion. Those who agree to participate sign a consent form and receive a questionnaire made up of three parts: the first investigates the topic of the promotion action; the second measures possible outcomes; while the third measures possible confounders, mediators, and modulators of the relationship observed. For example, since a consistent amount of scientific evidence indicates that increased adherence to the Mediterranean diet is associated with favorable mental and physical health outcomes [41,42], the 2023 program will aim to promote the Mediterranean diet. The questionnaire, which can be completed on paper or online, is made up of questions that refer to the three aforementioned areas: (i) a 14-point Mediterranean Diet Adherence Screener (MEDAS) [43] to evaluate the degree of adherence to the Mediterranean diet and provide advice for the workers; (ii) an analysis of lifestyles, metabolic parameters, and mental health with the General Health Questionnaire [44] as outcomes; and (iii) an evaluation of occupational stress using Siegrist’s effort/reward imbalance model [45,46], of sleep disorders with the Sleep Condition Indicator [47], and of trauma with the Violent Incident Form [48] as possible cofactors in the relationship. The questionnaire form can be provided upon request to doctors who intend to apply this program in their companies. Workers’ responses can also be collected online. No charge is required for these services, which are aimed at improving health in the workplace and also in other companies.
Workers receive immediate health promotion advice from the occupational physician and guidance on where to access NHS facilities for diagnostic tests or necessary treatments. After processing the data contained in the questionnaires, the occupational physician transmits the results in a collective anonymous form to the employer, the protection service manager, and the workers’ safety representatives so that eventual collective promotion measures can be adopted.
## 3. Results
Over the past 12 years, the occupational physicians in our occupational health unit have conducted the WHPEMS programs reported in Table 1. More than 20,000 workers have participated, and over 1000 of them have contacted their GPs or other NHS facilities.
Although it was not obligatory to join the programs, most workers participated. In cases where screening revealed a disease, the medical examinations performed immediately after completing the questionnaire were used to expand the workers’ medical history, investigate comorbidities, and evaluate any alterations. Workers were invited to start or continue their diagnostic/therapeutic pathway at the NHS. In these cases, the OP took the opportunity to contact the worker’s GP, to whom he/she sent a letter via the worker, indicating the data emerging from the examination and the patient’s possible needs. The worker was invited to provide information on the evolution of his/her pathology that would, however, be further checked by the OP during the worker’s next routine examination. In most cases, when OPs detected only incorrect habits or risky behaviors, contact with the worker was used to reinforce the salutogenic approach by pointing out the advantages of correct lifestyles.
The data collected through questionnaires were processed electronically. The results of each survey were reported to the companies, the corporate prevention service, and the workers’ safety representatives in order to contribute to the growth of the work culture. Besides offering workers advice and providing companies with useful indications, WHPEMS activities have enabled researchers to produce some scientific publications [49,50,51,52,53,54,55,56,57,58,59,60,61,62,63]. Furthermore, by annually reiterating surveys on the same cohorts of workers, it has been possible to carry out longitudinal studies to clarify the causal link between exposure to risk and damage to health [64,65].
## 4. Discussion
The experiences conducted by our occupational medicine unit over a period of several years and summarized in this paper indicate that including health promotion in prevention activities required by law presents characteristics worthy of attention. First of all, since this method makes use of an existing health and safety service, it is very economical because it does not require companies to make a significant commitment of economic resources. Furthermore, it does not interfere with the work of OPs. On the contrary, it guarantees an important supply of data for analyzing workers’ health conditions. Usually, a lack of resources is reported to be the most common obstacle to WHP programs, whereas strong management support is held to be the most common facilitator of this type of intervention [66]. The modest quantity of resources required by this method makes it possible to apply WHPEMS projects even in small businesses. The well-being of workers is of great interest to companies because research data demonstrate that health promotion initiatives that also focus on the physical work environment and organizational structure of the workplace can significantly influence job-related outcomes, including absenteeism [67]. The best method of freeing resources for health promotion is to raise the standard of occupational health at work. In fact, the true goal of occupational medicine is to improve workplace health. This can be accomplished more effectively by adopting a broad strategy that considers occupational risks, technical and medical knowledge, ergonomic workplace modifications, and behaviors and lifestyles that may encourage the development of diseases and consequently limit working capacity. One of the most important characteristics of projects is continuity: frequently, a project can only be sustained if it helps to recover resources or significantly increases production. Many ventures fail if they are not consistently financed, although there are a few exceptions to this general norm. In the Netherlands, some projects continued after national funds had run out because companies recognized their value and decided to continue them by financing the experience themselves [68]. In Italy, an incentive for the implementation of health promotion programs is represented by the fact that companies that carry out interventions supplementary to the obligatory prevention of occupational damage can request a reduction in the insurance premiums they have to pay to the National Institute (INAIL). This immediate economic benefit largely exceeds the very modest expense of WHPEMS programs and ensures that any other benefit of the intervention that should occur in the future due to reduced absenteeism, increased productivity, etc., will be a net gain. Furthermore, companies derive image benefits from WHPEMS programs. For example, one of the companies in which we carried out the interventions was awarded for best practices in the 2007 European campaign “Lighten the load” and in the $\frac{2016}{2017}$ European campaign “Safer and healthier work at any age—occupational safety and health in the context of an aging workforce.” A second interesting characteristic of this method is its sustainability, demonstrated over a period of more than 12 years. Promotion continuity depends on two factors: corporate social responsibility and the motivation of workers. WHPEMS interventions give companies a tangible demonstration of their social responsibility. It is important to encourage corporate social responsibility because workplace health promotion and company social responsibility are related. They have mutually beneficial effects based on leadership that respects autonomy and voluntary participation accompanied by recognition of specific goals that comply with the parameters of company sustainability policies [69]. Worker participation is another factor related to sustainability. The decision to choose “positive” salutogenic objectives that change from year to year is designed to increase motivation, which is difficult to achieve if the objective is always the same and of a negative nature, e.g., avoiding drinking, smoking, taking drugs, etc. The salutogenic approach plays a significant role in research and practice related to public health and health promotion. This approach might help to solve some of today’s most pressing public health issues (e.g., the promotion of mental health) and might produce a sound theoretical foundation for health promotion [70,71].
The third aspect is the participatory nature of WHPEMS. Workers contribute by proposing topics that become the subject of promotion projects and also by responding to their doctor’s advice. Research has shown that the participatory approach is a good example to follow for promoting health [72]. Choosing topics shared with workers ensures that program goals are relevant to workers’ health and that they will derive the greatest benefit for their own health.
A further interesting characteristic of WHPEMS projects is that they enable researchers to systematically collect interesting occupational medicine variables, such as perceived occupational stress and workplace violence. The latter is considerably underreported in workers’ spontaneous reports [73]; however, a survey based on questionnaires makes it possible to collect experiences in a systematic way. Information on violence experienced and perceived stress is highly sensitive material; the fact that it is collected as a collateral aspect of an investigation targeting other clinical problems may reduce the risk of overreporting, a phenomenon often linked to compensation expectations [74,75,76]. The surveys we conducted made it possible to investigate very delicate aspects such as occupational stress and violence in the workplace. As discussed above, the implementation of WHPEMS interventions is an advantage for companies and workers. It is also a great advantage for the occupational doctor, who has the possibility of improving the health of workers and earning an optimal relationship with them. It is useful to remember that the occupational doctor is not chosen by the workers and does not enjoy the fundamental doctor–patient relationship on which medicine is based. By implementing WHPEMS programs and improving working life and work culture, he/she can gain the trust and cooperation of workers.
Lastly, by creating a real flow of information between OPs and GPs, the WHPEMS method avoids duplicating activities and wasting resources during public health action. In a health system in which resources are limited, waste is ethically unacceptable. Regular mandatory health surveillance in the workplace makes it possible to evaluate the effectiveness of promotional interventions. Numerous requests have been made to overcome obstacles such as organizational, interpersonal, and structural barriers that can hamper cooperation between OPs and GPs, and suggestions have been put forward in order to successfully achieve this aim [77].
The recent COVID-19 pandemic has shown how important the relationship between OPs and GPs is in disseminating and sustaining good practices. It has been observed that when public health shocks occur, policymakers can encourage pertinent learning processes by supporting knowledge and education to raise people’s understanding of preventive health practices [78]. A change in living behavior may have resulted from the lockdown, during which residents were advised to spend as little time outside their homes as possible and work from home. This life-changing event may have altered lifestyle choices, which have a crucial role in the development and progression of illnesses [79]. By implementing health promotion strategies, communities may be better able to avoid, identify, and contain epidemic threats. They may also improve the effective allocation of scarce resources to high-impact public health systems [80]. This could be of the utmost importance for dealing with any other emergencies in the future. For example, in the case of post-COVID-19 syndrome, maintaining or regaining post-COVID-19 workability might reasonably follow a typical biopsychosocial framework enhanced to account for the cyclical nature of the symptoms. This should include adaptable, ongoing, longer-term return-to-work planning that addresses several levels of workability barriers, produced jointly by employees and line managers with assistance from OPs, GPs, and an improved organizational culture [81].
A limitation of the advantageous WHPEMS method is the considerable effort needed to plan the annual project and carry out a statistical analysis of the data collected. To overcome this limitation, the occupational medicine unit of the Catholic University of the Sacred Heart makes its project available to all OPs and provides free data processing to interested researchers. The aim of this work was to introduce a method for carrying out health promotion interventions that would be accessible to OPs, even in small companies. Despite the numerous actions undertaken worldwide, there is still little and inconsistent evidence regarding the effectiveness of strategies for improving the implementation of health-promoting policies and practices in the workplace [82]. We are convinced that a simple, cheap, and effective method such as the one proposed can significantly improve occupational health promotion actions.
## 5. Conclusions
The aforementioned WHPEMS method, based on continuous health promotion within regular health surveillance activities conducted in the workplace, offers many advantages such as cost-effectiveness, sustainability, and a participatory approach, all of which recommend extensive application. Moreover, it is a valid tool for collecting useful information for the surveillance of workers and for improving work environments. It also provides a solid foundation for creating a two-way information flow between occupational physicians and NHS doctors. The critical issues inherent in this method, as in all health promotion programs, concern the need to analyze evidence, design the survey correctly, and process the results. Our university gives occupational physicians access to experiences gained in over 12 years of promotion activities and aims to create a network for all those interested in promoting health in the workplace.
## 6. Patents
The A.S.I.A. method for risk management and the Participatory Ergonomics Groups (G.E.P.) method are registered trademarks of the author and are freely accessible by all prevention operators who intend to apply them in the workplace.
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|
---
title: 'Pregnancy Outcomes in SARS-CoV-2-Positive Patients: A 20-Month Retrospective
Analysis of Delivery Cases'
authors:
- Andreea Moza
- Elena S. Bernad
- Diana Lungeanu
- Marius Craina
- Brenda C. Bernad
- Lavinia Hogea
- Corina Paul
- Cezara Muresan
- Razvan Nitu
- Daniela Iacob
journal: Medicina
year: 2023
pmcid: PMC9968024
doi: 10.3390/medicina59020341
license: CC BY 4.0
---
# Pregnancy Outcomes in SARS-CoV-2-Positive Patients: A 20-Month Retrospective Analysis of Delivery Cases
## Abstract
Background and Objectives: The SARS-CoV-2 infection brings supplemental risks for pregnant women. Due to controversial hesitancy, their vaccination rate was lower in 2021 compared to the general population. In addition, access to maternal care was reduced during the pandemic. We conducted a retrospective cross-sectional analysis of the health records data over 20 months (1 April 2020 to 20 November 2021) aiming to explore the outcomes in SARS-CoV-2-positive cases referred for delivery to a tertiary public hospital in Western Romania. Materials and Methods: Women with SARS-CoV-2 infection diagnosed for the first time at the moment of birth who delivered singletons after 24 weeks of gestation, and had a clear immunization status were included in the analysis. Results: Out of the 97 patients included in the study, 35 ($36\%$) had undergone ARN-based vaccination. Five cases of maternal death were recorded (all unvaccinated). Our retrospective exploratory analysis showed that the presence of COVID-19 symptoms in the SARS-CoV-2-positive patients made a significant impact on the delivery hospitalization, with a median hospital stay increase from 5 to 9 days (Mann–Whitney test, $$p \leq 0.014$$): longer hospitalization was recorded in the symptomatic cases irrespective of their vaccination status. No other adverse outcomes, such as gestational age at delivery, C-section rate, 5 min Apgar index, or birth weight were associated with the presence of symptoms. Conclusions: Our clinic maintained safe maternal care for the COVID-19 patients during the analyzed period. Vaccination of the expectant women was beneficial in SARS-CoV-2-positive patients by lowering the risk of COVID-19 symptoms, with subsequent implications on the newborns’ health and maternal attachment.
## 1. Introduction
COVID-19, a coronavirus disease that has spread globally, increasing morbidity and mortality, has not eluded women of reproductive age. Studies suggest a diminution of fertility in infected women, although it seems to be reversible so far, making pregnancy a more susceptible condition in cases of COVID-19 illness in the women of reproductive age [1,2,3]. There was an increased contextual risk of infection for pregnant women illustrated by the governments’ response stringency index (GRSI) or the overall health system performance as measured by the World Health Organization [4,5].
COVID-19 can seriously affect pregnant women, who are acknowledged to be at higher risk for severe disease when they are symptomatic [1,2,4,5,6]. Pregnancy complications can occur in COVID-19 patients, such as maternal or fetal death, pre-term birth, or caesarian section (C–section) due to the maternal medical condition. According to available evidence, pregnant women are especially vulnerable to severe COVID-19 complications like acute respiratory distress syndrome, acute renal failure, thrombo-embolic events, and other unfavorable cardiac events [7]. As a result, these women are more prone to invasive ventilation, hospitalization in an intensive care unit (ICU), or to extra-corporeal membrane oxygenation [8]. Infected pregnant patients in poor health may require induction of labor, resulting in premature birth with all of its consequences [9].
While large systematic reviews fail to demonstrate vertical transmission, some papers (mostly case reports) shed some light on this subject [10,11,12].
Most congenital infections are asymptomatic, but cases of neonatal pneumonia, thrombocytopenia, altered liver function, feeding difficulties, cardiac arrhythmia, and thrombosis were reported. Furthermore, retinal and choroidal abnormalities in the newborn have also been reported [12,13,14,15]. In spite of this, even in the absence of vertical transmission, maternal infection can have an indirect effect on the developing fetus. Histopathological examinations of the placenta have shown vascular abnormalities, particularly in the decidua, as well as thrombi in the fetal arteries, alterations that can determine fetal hypoxia [16].
Vaccines have been developed, and national as well as international authorities, organizations, or health agencies all over the world have recommended the RNA-based vaccines for pregnant or lactating women: Comirnaty (developed by BioNTech, Germany and Pfizer, USA), and Spikevax (previously known under the name of the manufacturing company, Moderna) [17,18,19,20]. Despite the fact that vaccination did not offer full protection against SARS-CoV-2 and the infection and the occurrence of high rates of hesitation (particularly due to the uncertain influence on the fetus and the woman’s future fertility), promising results have been reported regarding vaccine effectiveness [21,22,23]. In addition, prevention of hospitalization was reported in vaccinated pregnant patients, with no additional pregnancy-related risks [22,24,25,26,27,28]. All over the world, 120 countries have recommended COVID-19 vaccine in pregnancy. Along with other 62 countries, Romania’s position was and remained that COVID-19 vaccination of pregnant or lactating women is ”permitted” as of 10 November 2022 [29].
During the first three waves of the COVID-19 pandemic, the Department of Obstetrics and Gynecology of the Clinical County Hospital of Timisoara, a tertiary hospital affiliated with the “Victor Babes” University of Medicine and Pharmacy, hospitalized all COVID-19 patients from Western Romania with obstetrical or gynecological problems [30]. While effectiveness of the health services is a complex challenge encompassing multicriterial aspects, finding the workable practices appropriate to the pandemic crisis increased the demands on the hospital’s management and every healthcare worker, especially the young trainees [31,32]. In this worldwide pandemic crisis, our hospital as a whole, and staff at all levels, faced disruptive challenges to their efforts to continue providing the healthcare services and preserving safe maternity and neonatal care and paying attention to all pregnant women, especially to those with chronic pathologies or pregnancy-related comorbidities [33,34,35].
Taking all the above into consideration, we conducted a retrospective exploratory analysis on the patients‘ health records aimed at debriefing the clinical activity’s effectiveness in providing seamless obstetrical services for SARS-CoV-2-positive patients. This secondary data analysis covered both the initial period, when no vaccine was available, and the first 10 months after vaccines became available to the general population in Romania. In this latter period, professional organizations recommended vaccination for pregnant women. General maternal and neonatal outcomes were used as performance indicators in this study. Maternal outcome was measured in the study using the following parameters: severity of lung disease on admission on computer tomography, need for intensive care, intubation and extracorporeal membrane oxygenation, and maternal death. The rate of c-section due to severe maternal disease and the rate of prematurity, as well as the rate of intrauterine demise, were used to evaluate the neonatal outcome. The possibility of vertical transmission of the coronavirus was also investigated.
## 2.1. Study Design and Population
This was a retrospective study with cross-sectional design encompassing the first three waves of the pandemic: 1 April 2020–20 November 2021. It occurred in a single tertiary medical center, the Department of Obstetrics and Gynecology of the Clinical County Hospital of Timisoara, Romania, which was one of the facilities that by the decree of the Health Ministry of Romania hospitalized all infected COVID-women with obstetrical or gynecological problems from west side of the country.
During the time frame of the study, there was a period (beginning on 1 April 2020 and ending on 31 May 2020) in which the Obstetrics and Gynecology Department of the Clinical County Hospital of Timisoara admitted only patients with confirmed SARS-CoV-2. After this period of time, the admittance of uninfected patients was allowed, but in a restricted number, and the unit was primarily focused on the management of SARS-CoV-2-infected patients. In this timeframe, 397 women were discharged after receiving treatment for SARS-CoV-2 infection. Some of these patients had a gynecological health issue, some were discharged while pregnant, and others were discharged after delivery. 278 patients were discharged from the hospital in the postpartum period, out of a total of 397 patients.
The purpose of the study was to investigate the outcomes of women with SARS-COV-2 infection at the time of birth as well as whether immunization status affected the outcomes of the mother and the newborn. Data were retrieved from patients’ records.
The decision to query the hospital’s data base utilizing the discharge diagnosis as the primary criteria was made in order to include the infected patients who required urgent delivery in other institutions before laboratory confirmation. These patients, as well as their newborns, were transferred to this referral department as soon as the SARS-CoV-2 RT-PCR test was available (transfer usually took place less than 8 h after delivery).
Only women who had singleton pregnancies and delivered after 24 weeks of gestation were included in this study.
Patients whose records do not mention their immunization status or who had prior SARS-CoV-2 infection were excluded from the study. After applying the exclusion criteria there were a total of 97 individuals who were eligible for the study. All patients were Caucasian.
The flow diagram of this study is depicted in Figure 1.
## 2.2. Outcome Measures
The analysis included the patients’ socio-demographic data and general characteristics, such as age, weight, weight gain during pregnancy, smoking status, number of previous pregnancies and deliveries, and the duration of hospitalization. Maternal comorbidities and management, or COVID-19-related complications (severity of lung disease, admission in the intensive care unit, ECMO, intubation requirement, and maternal death) were also included. Recorded information on paraclinical investigations was included when available (missing data was an issue for this information). No imputation was done for the missing data.
Obstetrical and neonatal outcome metrics included the following indicators: gestational age at delivery, gender of the newborn, maternal death, intrauterine fetal demise (IUFD), C-section (overall and due to COVID-19 complications), birth weight, 5 min Apgar index for the newborn, and whether or not the newborn had COVID-19.
## 2.3. Data Analysis
Descriptive statistics included the observed frequency counts (percentage) for categorical variables and median (interquartile range with Tukey’s hinges) for numerical variables. For the maternal age, the mean and standard deviation were also included in the descriptive table. All numerical variables were non-normally distributed (Shapiro–Wilk statistical test was employed for checking the normality of the distributions). Univariate non-parametric statistical tests were applied to compare the distribution of numerical data across two or multiple groups, as appropriate (either Mann–Whitney U or Kruskal–Wallis tests, respectively). The chi-square statistical test (either asymptotic, Fisher’s exact test, or Monte Carlo simulation with 10,000 samples) was applied to check the statistical significance of the association between the categorical variables.
The statistical analysis was conducted at a $95\%$ level of confidence and a $5\%$ level of statistical significance. All reported probability values are two-tailed.
Statistical analysis was performed with the statistical software IBM SPSS v.20 and open-source R v.4.0.5 packages.
## 3.1. COVID-19 Symptoms in SARS-CoV-2-positive Women
Sixty-two patients ($64\%$) were unvaccinated, and all of them had COVID-19 symptoms at hospital admission. Respiratory symptoms were the most commonly reported by unvaccinated patients ($\frac{40}{62}$). These included rhinorrhea, sore throat, cough, and dyspnea. Eleven patients showed neurologic involvement of SARS-COV-2 infection, including ageusia, anosmia, and agnosia. Twenty-one patients reported malaise. Ten patients had fever, and three had vomiting. Out of the 35 women who underwent at least one dose-vaccination, 12 ($34.29\%$) had COVID-19 symptoms. Most frequent symptoms in vaccinated women were rhinorrhea ($\frac{10}{12}$), followed by neurologic symptoms ($\frac{5}{12}$), cough ($\frac{3}{12}$), and dyspnea ($\frac{1}{12}$).
All vaccinated patients had received Comirnaty (developed by BioNTech and Pfizer).
Overall, the difference in proportion of symptoms was highly significant: Monte-Carlo-simulated chi-square test, $p \leq 0.0001.$ Figure 2 illustrates the distribution of the patients in the two groups corresponding to the vaccination status, with their respective number of symptomatic and asymptomatic cases.
## 3.2. Maternal Characteristics
Table 1 presents the socio-demographic and clinical characteristics of the 97 patients included in the analysis. Missing data were specified when this issue occurred.
The duration of hospitalization varied among the patients, ranging from 3 to 33 days in unvaccinated patients, between 3 and 22 days among symptomatic vaccinated patients, and no more than 15 days in asymptomatic vaccinated patients. Overall, asymptomatic patients had a shorter hospitalization compared to the symptomatic ones, irrespective of their vaccination status (Mann–Whitney statistical test; $$p \leq 0.032$$).
There were no differences concerning the other characteristics of the patients, except for the initial weight and their body mass index: the vaccinated pregnant women in the study were significantly heavier.
Table 2 shows the comorbidities and treatments of the study patients, including the vitamin and iron supplements. Although we found no differences between the three groups, a high percentage of patients with at least one comorbidity is noticeable.
## 3.3. Laboratory Findings in SARS-CoV-2-Infected Patients
Table 3 presents the results of paraclinical investigations at admission.
## 3.4. Management of COVID-19 Disease
On computer tomography, 14 ($22.58\%$) unvaccinated patients had signs of lung lesions at the time of admission. The percentage of affected lung parenchyma ranged from $15\%$ to $80\%$: $15\%$ (1 patient), $20\%$(2 patients), $30\%$(2 patients), $35\%$(1 patient), $40\%$(4 patients), $60\%$(2 patients), $70\%$(1 patient), and $80\%$(1 patient). In the immunized group, one patient displayed signs of pulmonary deterioration, with $30\%$ of lung parenchyma being affected by COVID-19.
Table 4 presents the summary statistics of COVID-19 complications.
Low levels of oxygen in the blood were treated with high flow oxygen therapy or extracorporeal membrane oxygenation if necessary. Due to their poor health condition, 13 women were admitted to the intensive care unit (ICU). One of them was immunized against COVID-19, but all the other were not. Seven ($11.3\%$) of the unvaccinated women were placed on high flow oxygen therapy, and two ($3.2\%$) were placed on extracorporeal life support. In seven cases, the deterioration of the patient’s health entailed intubation (all belonged to the unvaccinated group). Endo-tracheal intubation lasted from 2 to 29 days. In contrast, none of the women in the vaccinated group needed intubation.
## 3.5. Pregnancy Outcomes
Gestational age at the moment of delivery varied from 25 weeks to 42 weeks. The overall percentage of prematurity was $25.7\%$ (25 out of the 97 subjects in the study). Table 5 shows the obstetrical and neonatal outcomes in these 97 subjects.
More than half of the patients underwent a C-section delivery, and for many of them the surgical solution was chosen based on their medical condition, namely due to the COVID-19 complications.
Severe obstetrical outcomes occurred in the unvaccinated patients: there were 5 cases of postpartum maternal death due to COVID-19. All had anemia, but 2 out of the 5 patients also had additional comorbidities: thyroid disease and pregnancy-induced hypertension (1 patient) and gestational diabetes (1 patient). These patients’ ages ranged from 19 to 37 years, with 3 of them being over 35. In most of them ($\frac{4}{5}$), the infection occurred during the third trimester (33–38 weeks of gestation), but one of the patients had a 25-week pregnancy. All of them were admitted to ICU and received high flow oxygen therapy. In all cases, delivery was recommended due to the mother’s severe COVID-19 disease, resulting in live neonates. All neonates tested negative for SARS-CoV-2 infection at birth and remained that way for the duration of their hospitalization.
Among the studied 97 patients, there were 3 cases of intrauterine fetal death/demise (IUFD) in the third trimester, at 28, 30, and 31 weeks of gestation. All stillbirths were diagnosed at hospital admission and occurred in unvaccinated patients.
No evident risk factors for IUFD were detected in any of the cases, but one pregnant woman arrived to the hospital with severe COVID-19 disease (computer tomography showed $70\%$ lung destruction). Pathology reports were not available.
There were two cases of COVID-19 infected newborns, both of unvaccinated mothers. They were born at 37 and 38 weeks of gestation, respectively. Due to the risk of uterine rupture on a previous uterine scar, one was delivered via C-section, whereas the other was delivered vaginally. The neonates were asymptomatic at birth and progressed well during their hospitalization.
## 4. Discussions
This analysis described the pregnancy outcomes of 97 patients who had a positive RT-PCR test for SARS-CoV-2 infection at the time of delivery. The main objective of this study was an exploratory assessment of maternity care over a period of 20 months of the COVID-19 pandemic. It also aimed to ascertain the supposed difference between the vaccinated and unvaccinated SARS-CoV-2-positive patients in regard to the pregnancy outcomes.
The rate of vaccination in our sample of pregnant women was lower than in the general population. This might be explained by Romania’s position on COVID-19 vaccination while pregnant or lactating, which was less stringent than that of other countries [4,29]. Because of the small size of the study lot, we were unable to determine the prevalence of symptoms among the vaccinated; however, a recent study conducted in New York City reported that $21\%$ of patients were symptomatic [36].
Due to the specific alteration of the immune system, pregnant women are considered to be less likely to develop symptoms if infected, but factors such as BMI > 25, presence of chronic health conditions, advanced maternal age, or belonging to socially disadvantaged groups are known to be associated with symptomatic COVID-19 disease [37,38,39,40]. In the analyzed period, there were five cases of maternal death, all in the unvaccinated patients. Three of these women were of advanced maternal age.
We found that the ICU rate was also associated with the unvaccinated status, but the numbers were too low to reach statistical significance. Only one vaccinated patient needed to be admitted to an intensive care unit due to a severe infection; all the other 11 patients had mild symptoms. On the other hand, the study design and the probable lack of statistical power prevented us from having a straight answer to possible consistency with other findings that reported no relation between their vaccination status and ICU admission [41]. Lowering the risk of complications entails consistent improvement of the chance for mother–child attachment [42].
The risk of infection was reported to decline quickly after the first vaccination dose (in 10 days), and maternal antibody response should be taken into account after vaccination [43]. Prabhu et al. reported specific immunoglobulin IgM and IgG in $71\%$ of cases, only IgG in $16\%$ of cases, and no immunoglobulin was found in $13\%$ of patients [44]. Our secondary data analysis did not allow retrieving comprehensive information on the vaccination scheme (i.e., whether completed or not). Worldwide fatality rates among pregnant patients infected with SARS-COV-2 varies widely [1].
While some studies reported a very low ($0.2\%$) mortality rate in pregnant patients, other studies reported a death rate as high as $12.7\%$ ($\frac{1858}{15105}$ pregnant patients) [45,46]. These wide margins might be related to the national stringency regarding the pandemic measures and to the overall health systems’ performance and level of national income [1,4,5]. In Romania, COVID-19 vaccination while pregnant or lactating was “permitted”, as opposed to highly recommended in other countries; therefore, one would expect a lower rate of vaccination in pregnant women compared to the general population [30].
The current literature on vertical transmission of the COVID-19 infection is still in the early stages. Despite evidence of placental histology and newborn immunological blood tests, the rate of reported congenital COVID-19 infection is very low, ranging from $3.2\%$ to $8.40\%$ [11,47,48]. In a previous study, our team also reported cases of possible vertical transmission [49]. When the newborns experience COVID-19 symptoms, they are likely to require respiratory support or to be transferred to a neonatal ICU, particularly if their mothers are symptomatic, too [50].
Despite the low rate of vertical transmission, poor neonatal outcomes such as intrauterine fetal growth restriction or fetal distress was more frequently found in case of maternal COVID-19 disease [51,52,53]. While poor maternal oxygenation could be blamed for this issue, most studies point to the abnormal functionality of the fetoplacental unit [54]. Abdel Massih’s review on SARS-COV-2-associated placental insufficiency concluded that $20\%$ of the infected neonates had signs of intrauterine hypoxia. Moreover, placental damage was observed negative RT-PCR newborns, probably as a response to maternal cytokine storm [55]. When compared to uninfected cases, histologic findings suggestive of vascular malperfusion such as chorioangiosis, intramural fibrin deposition, vascular ectasia, and perivillous fibrin deposition were strongly associated with SARS-CoV-2-positive pregnancies [54]. Additionally, thrombosis of the fetal chorionic plate and decidual arteries were more commonly seen in the placentas of infected women [54].
Studies show vaccination in pregnancy benefits both the fetus and the newborn, as a result of the passive transplacental passage of antibodies. Upon sampling blood from the umbilical cord of vaccinated women after delivery, Collier et al. identified IgG antibodies against the receptor binding domain (RBD) of SARS-CoV-2, against S protein as well as neutralizing antibodies [40]. Nonetheless, the detection of antibodies in the newborn’s blood depends on the number of the vaccine doses ($43.6\%$ vs. $98.5\%$), as well as on the latency between the last dose and the birth (the longer the latency, the higher the transfer) [40,56]. In the current analysis, 2 out of the 59 live newborns of unvaccinated mothers tested positive for SARS-CoV-2 infection. Among the vaccinated patients (35 in total), none tested positive. We could not confirm the congenital viral infection according to the WHO recommendations of RT-PCR on the placental tissue or detections of specific viral particle in the placenta (possible only with an electronic microscope); on the other hand, the neonates were sampled right after birth and the attending staff took strict precautions to avoid contamination [57].
## Limitations
The main limitation of this analysis stems from the cross-sectional design and the secondary use of data from the patients’ records, with limited information and multiple missing values. Conceptualized as an exploratory analysis, no a priori statistical power analysis was conducted; therefore, the risk of type II statistical error (i.e., the false negative rate) in some findings remains a caveat.
Additionally, the analysis comprised limited data from one single clinic, but this is a tertiary public maternity affiliated to the largest university of medicine and pharmacy from the western part of Romania, to which most complicated or problematic cases in the region are referred.
Nevertheless, despite its limitations, this timely report contributes to the growing body of evidence in regard to the benefits of vaccination for pregnancy outcomes.
## 5. Conclusions
Our clinic provided safe maternal care for pregnant COVID-19 patients during the analyzed pandemic period.
The results reported in the present study suggest that vaccination of the expectant women has a beneficial role in SARS-CoV-2-positive patients by lowering the risk of COVID-19 symptoms, with subsequent favorable implications on the newborns’ health and maternal attachment.
Apart from the undeniable limitations, the strength of this debriefing analysis consists of its contribution to the medical evidence towards the benefits of vaccination in pregnancy. It also confirmed the robustness and effectiveness of the maternity services in this region during the first pandemic waves, when the healthcare systems were heavily disrupted worldwide.
The hard lessons learnt during the COVID-19 pandemic can help to improve maternity care, and their promotion may mediate still pending changes in health policies. They can inform decision making at all levels in regard to prioritizing limited resources in the context of the national stringency of public health policies and also guide individual pregnant women in their personal decision about COVID-19 vaccination or vaccination in general.
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|
---
title: 'Polyacrylamide Hydrogel Containing Calendula Extract as a Wound Healing Bandage:
In Vivo Test'
authors:
- Lindalva Maria de Meneses Costa Ferreira
- Elanne de Sousa Bandeira
- Maurício Ferreira Gomes
- Desireé Gyles Lynch
- Gilmara Nazareth Tavares Bastos
- José Otávio Carréra Silva-Júnior
- Roseane Maria Ribeiro-Costa
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9968031
doi: 10.3390/ijms24043806
license: CC BY 4.0
---
# Polyacrylamide Hydrogel Containing Calendula Extract as a Wound Healing Bandage: In Vivo Test
## Abstract
Hydrogel is a biomaterial widely used in several areas of industry due to its great biocompatibility and adaptability to biological tissues. In Brazil, the Calendula plant is approved by the Ministry of Health as a medicinal herb. It was chosen to be incorporated in the hydrogel formulation because of its anti-inflammatory, antiseptic and healing effects. This study synthesized polyacrylamide hydrogel containing calendula extract and evaluated its efficiency as a bandage for wound healing. The hydrogels were prepared using free radical polymerization and characterized by Scanning Electron Microscopy, swelling analysis and mechanical properties by texturometer. The morphology of the matrices showed large pores and foliaceous structure. In vivo testing, as well as the evaluation of acute dermal toxicity, was conducted using male Wistar rats. The tests indicated efficient collagen fiber production, improved skin repair and no signs of dermal toxicity. Thus, the hydrogel presents compatible properties for the controlled release of calendula extract used as a bandage to promote cicatrization.
## 1. Introduction
Skin injuries caused by trauma and other accidents often lead to a range of health complications and sometimes death [1,2]. Wound healing for skin wounds is a physiological process that depends on molecular and cellular mechanisms. The process is divided into three phases: the inflammatory, proliferative and remodeling phase [3,4,5,6]. Acceleration of healing requires the maintenance of wound sterility, pain reduction, elimination of exudate, possibility of gas exchange, ease of handling and reduction in the number of dressing applications [7,8]. Although there are several treatment options on the market for the treatment of skin wounds, most tend to be expensive for the patient, due to the long-term treatment required [8,9]. Ideal dressings have the following criteria: providing and maintaining a moist environment, protecting the wound against secondary infections, allowing gas exchange, providing thermal insulation, being free of toxic particles or contaminants, handling excess exudate, being elastic, having a low cost, durability, flexibility and mechanical strength [8,10,11]. The main advantage of modern bandages is their ability to retain and build a humid ambient around the injury in order to encourage the cicatrization process [6,10,12]. Several skin bandages have been designed using advanced technologies, and are regarded as suitable options, including: fiber bandage wraps, gauze, medical film and hydrogels [9,10,13,14,15].
Hydrogels are three-dimensionally reticulated polymeric matrices that have the ability to absorb large amounts of water and biological liquids [16,17,18,19]. Due to their great capacity to absorb water, the presence of cavities and their smooth firmness, they mimic natural living tissues more than any other class of biomaterials [20,21]. They are widely used in the treatment of wounds, promoting autolytic debridement, thus maintaining a moist environment around the wound, which accelerates cicatrization [22,23,24]. The properties of these biomaterials, such as their biocompatibility, high oxygen permeability, wound moisture retention and absorbability, all help to increase patient compliance [22,25]. The smooth nature of hydrogels allow them to be easily removed from the skin without causing any irritation or additional damage [22,26,27]. However, the practical applications of hydrogels as bandages are still currently limited, due to their poor mechanical strength and stability [3,28]. The development of a new hydrogel with superior properties becomes necessary for application in the skin wound healing process. The use of hydrogels as dressings for wound treatment applications has been reported in several studies [29,30].
Among the polymers utilized in hydrogel formulations, polyacrylamide (synthetic) and methylcellulose (natural) stand out [29,31]. Polyacrylamide (PAAm) has low toxicity and is economical. It is synthesized using free radical polymerization in aqueous solution, or solid state crystalline acrylamide polymerization using ionizing radiation [32,33]. The main characteristic of the PAAm hydrogel is its degree of swelling, which gives great flexibility and cohesion, and which provides a granulation and epithelializing effect which is an ideal property for a dressing [23,34]. Methylcellulose (MC) originates from the methylation process of the natural polymer cellulose. When MC is cross-linked in the PAAm network with irreversible covalent bonds, a resistant biomaterial is created, which has the great advantage of being simple and cheap, thus favoring its economic viability [35,36]. The combination of the two polymers with different characteristics result in the formation of a new polymer with advanced mechanical strength, biocompatibility and biodegradability [3,37,38].
Ideal dressings also need to exhibit anti-inflammatory, healing, antioxidant and antibacterial activity [39,40]. Calendula officinalis L. or calendula, belongs to the Asteraceae family. It is native to southern Europe and was used not only for decorative purposes but also as a medicinal herb [41,42,43,44]. Among the bioactive compounds found in the species, it contains carotenoids, lycopene, phenolic acids, hydroxycinnamic acids (p-coumaric, caffeic, chlorogenic acids), flavonoids (rutin) and coumarins (esculetin) [44,45].
The presence of phenols in the species contributes to its high antioxidant potential [46,47]. Calendula has widespread therapeutic applications, which include tissue re-epithelialization and general wound healing action. [ 43,48]. Thus, this study is aimed at developing a polyacrylamide-based hydrogel containing calendula extract to be used as a dressing for wound healing.
## 2.1. Preparation of Hydrogel
White hydrogels and the hydrogel containing the calendula extract had a gelatinous and translucent appearance. However, the hydrogel containing the extract had a yellow hue, obtained from the calendula extract (Figure 1). The white hydrogel showed to be visibly resistant and with intensified color.
## 2.2.1. Morphology Analysis
Scanning Electron Microscopy (SEM) micrographs of the $7.2\%$ HDSC (without calendula extract) and $7.2\%$ HDCC (with calendula extract) are shown in Figure 2. The photomicrographs of the matrices without the addition of the extract showed clear pores and foliaceous structure, characteristic of the three-dimensional network the hydrogels [23]. The $7.2\%$ HDSC showed large pores, having irregular and non-uniform shapes (Figure 2). The porous structure has the potential to absorb exudate exiting the wound, in addition to helping to diffuse nutrients and healing promoters to the site, while still maintaining an appropriate moist environment [9].
The photomicrographs of the matrices containing the calendula extract showed that there was a filling of all pores in the polymer matrix. The addition of the extract altered the shape and structure of the pores. The structure of hydrogels $7.2\%$ acrylamide found in this research was observed in a previous study by Gyles at al. [ 23]. Where the morphological characteristics shown in the hydrogel matrix containing calendula extract were similar to the study which showed the incorporation of *Aloe barbadensis* extract [23], and another study which showed the incorporation of Aloe arborescens aqueous extract within the hydrogel matrix [49], the present study suggests that the hydrogel matrix can be compatible for the incorporation of plant extracts.
## 2.2.2. Swelling Studies
The hydrogels $7.2\%$ HDSC and $7.2\%$ HDCC were evaluated for the degree of swelling, the results are shown in Figure 3. In this study, the values for $7.2\%$ HDSC ranged between $715\%$ and $2500\%$ while the $7.2\%$ HDCC values ranged from $318\%$ to $1979\%$. The swelling behavior of a hydrogel is one of the most essential characteristics for bandages as it provides a moist environment in the wound area, in addition to being directly related to the ability to absorb wound exudate, prevent infections and facilitate the healing process [50,51].
Polyacrylamide absorbs water through the formation of hydrogen bonds using osmosis as the mechanism of action. In addition, methylcellulose has hydroxyl groups, which also account for greater water absorption by the hydrogel [23]. The experiment lasted a period of 72 h, and its swelling profile was not constant, which consequently could lead to an even greater water absorption. The porous structure of the hydrogel may also have influenced an increase in water absorption. There was a significant increase in the hydrogel size during the swelling process, the polymer matrix became more flexible and absorbed a large amount of water at room temperature. The hydrogels with and without the calendula extract showed a great capacity for water absorption, HDSC swelled to $2500\%$ and HDCC to $1979\%$ in 48 h.
The incorporation of the extract in the polymer matrix did not change the profile of the hydrophilic property of the polyacrylamide hydrogels. The water absorption behavior found in this study is similar to previous studies by Gyles et al. [ 23], Xue et al. [ 24] and Zakerikhoob et al. [ 10]. The polyacrylamide hydrogels, due to their great water absorbing potential, are characterized as an efficient biomaterial when applied directly to the wound for hydration.
## 2.2.3. Mechanical Properties by Texturometer
Mechanical resistance is a very important property in hydrogels that are used as bandages for wound treatment. Good mechanical strength maintains its integrity when skin tissue is damaged by external forces and protects the wound [52]. The mechanical properties of the hydrogels were evaluated in terms of tensile strength and deformation rate (Figure 4). The $7.2\%$ HDSC showed a tensile strength value of 0.64 ± 0.04 N and deformation 185.5 ± $9.19\%$. The $7.2\%$ HDCC showed a tensile strength value of 0.75 ± 0.36 N and deformation 201.7 ± $28.22\%$. The commercial product used as a control showed a tensile strength value of 0.55 ± 0.03 N and deformation 307 ± $25.3\%$. Mechanical strength values of 1.447 ± 0.108 N (pH 2.2 buffer), 0.786 ± 0.081 N(DW), 0.779 ± 0.117 N(PBS) and 0.553 ± 0.061 N (SWF) in hydrogel films were reported by Singh et al. [ 53]. The $7.2\%$ HDSC and $7.2\%$ HDCC showed low mechanical resistance and high deformation rate; however, their values were higher than the commercially sold product used in the study as a control.
The preliminary test of the mechanical property of hydrogels did not show a positive result as expected, with a concentration of $7.2\%$ polyacrylamide. The mechanical strength of hydrogels can be improved with the addition of reinforcing agents, subsequent complexation of ions and strong covalent crosslinking during synthesis methods [54]. Although the result was not what was expected, it leaves room for optimizing the formulation, perhaps with an increase in the concentration of the polymer that presents this property of improving the resistance of hydrogels or the insertion of a second polymer that has this characteristic, such as alginate of sodium.
## 2.3.1. Acute Dermal Toxicity Test
Acute toxicity tests are preliminary in evaluating the safety of a product and predicting possible adverse effects. In this study, there was no evidence of changes in the specimens observed. The animals maintained constant weight, the skin showed no signs of toxicity, and no systemic alteration, indicating toxicity, was observed. The food/water ratio remained the same, without any changes in behavior of animals. After 24 h hydrogel was removed from the animals and no macroscopic change was observed (Figure 5).
Cascone and Lamberti [29] observed that the use of polyacrylamide in the hydrogel synthesis did not present a risk, as it is a commonly used biomaterial in the pharmaceutical industry. Methylcellulose, a natural and biocompatible polymer is also included in its composition, making up a part of the three-dimensional structure. The skin to which the hydrogel was applied showed a better appearance, indicative of better tissue hydration. Water retention is an essential property for a wound bandage, as it keeps the wound hydrated and facilitates exchanges, in addition to promoting the healing process (Figure 5) [20,51].
## 2.3.2. Evaluation of Hydrogel Action in Healing Process
The efficacy of hydrogel as a wound healing agent was investigated in vivo (Figure 6). Analysis was performed using the ischemia-reperfusion model to create a pressure wound. The rats were randomly divided into groups, where they were treated using the following: saline solution (negative control), SAF-gel® (positive control), $7.2\%$ HDSC and $7.2\%$ HDCC. Tukey’s test was used to compare group results. The analysis was conducted by measuring the initial necrotic area and taking it away from the necrotic area after treatment. The results showed a significant reduction in wound circumference, as a result of wound contraction in the sample treated groups. The tested hydrogels presented positive effects on the tissue regeneration process, as observed in the reduction in wound size in the treated groups. The $7.2\%$ HDCC showed the most significant decrease in wound size which was equivalent to the SAF-gel® positive control with around $50\%$ reduction in the total ulcer size (Figure 6). It is believed that hydrogels directly contribute in the tissue repair process. The edema extravasation was measured by the volume of exudate formed at the wound site. The treated groups with $7.2\%$ HDCC and $7.2\%$ HDSC group presented a significant decrease in volume of exudate produced, in comparison to the negative control group. $7.2\%$ HDCC and HDSC did not show any significant difference to the positive control SAF-gel®, which was probably due to the high concentration of polyacrylamide, known to have positive effects on wound granulation and epithelialization (Figure 6A).
In Tukey’s multiple comparison test, negative control and SAF-gel® showed a statistically significant difference ($p \leq 0.001$). Negative control and $7.2\%$ HDSC showed a statistically significant difference ($p \leq 0.001$). Negative control and $7.2\%$ HDCC showed a statistically significant difference ($p \leq 0.001$). SAF-gel® and $7.2\%$ HDSC showed a statistically significant difference ($p \leq 0.001$). SAF-gel® and $7.2\%$ HDCC were not statistically different. $7.2\%$ HDSC and $7.2\%$ HDCC showed a statistically significant difference ($p \leq 0.001$) (Figure 6A).
Hydrogels are designed for the facilitation of the debridement and hydration of necrotic tissues or devitalized areas, in addition to facilitating exudate removal, stimulating tissue granulation, epithelialization and the filling of cavities. The reduction in the volume of exudate demonstrated a possible anti-inflammatory activity of the hydrogels and that result could be directly linked to induced cellular edema. The $7.2\%$ HDCC and HDSC can be used as dressings for the treatment of tissue injuries, such as pressure injuries (Figure 6B) [55,56].
In Tukey’s multiple comparison test, negative control and SAF-gel® showed a statistically significant difference ($p \leq 0.01$). Negative control and $7.2\%$ HDSC showed a statistically significant difference ($p \leq 0.05$). Negative control and $7.2\%$ HDCC showed a statistically significant difference ($p \leq 0.01$). SAF-gel® and $7.2\%$ HDSC were not statistically different. SAF-gel® and $7.2\%$ HDCC were not statistically different. $7.2\%$ HDSC and $7.2\%$ HDCC were not statistically different (Figure 6B).
In assessing the cell migration, the reduction in the number of cells in the lesion site indicates the anti-inflammatory potential. An amount of $7.2\%$ HDCC and HDSC decreased the total number of cells compared to the other groups presented (Figure 6C), this indicates that hydrogels have an effect on decreasing the cell migration process, a fact that corroborates their anti-inflammatory action. The macrophage is the most important inflammatory cell in this phase and is maintained from the third to the tenth day, along with phagocytes bacteria, debrided foreign bodies and the development of granulation tissue. High phagocytic activity of macrophages was observed after trauma [6].
In Tukey’s multiple comparison test, negative control and SAF-gel® were not statistically different. Negative control and $7.2\%$ HDSC showed a statistically significant difference ($p \leq 0.01$). Negative control and $7.2\%$ HDCC showed a statistically significant difference ($p \leq 0.001$). SAF-gel® and $7.2\%$ HDSC showed a statistically significant difference ($p \leq 0.05$). SAF-gel® and $7.2\%$ HDCC showed a statistically significant difference ($p \leq 0.01$). $7.2\%$ HDSC and $7.2\%$ HDCC were not statistically different (Figure 6C).
In the evaluation of nitric oxide (NO) activity, there was no interference of NO production in the different formulations, thus showing that calendula has no activity against NO production (Figure 6D).
## 2.3.3. Histopathological Evaluation
The histological analysis of wound healing, which indicates the structural or qualitative characteristics of tissues and cellular infiltrates, was performed. The negative control group, treated only with saline solution, showed a depletion of the skin layers, representing the invasiveness of the lesion. The positive control (SAF-gel®) demonstrated a reduction in the rate of cellular infiltrates and an organization of tissue layers. The group treated with $7.2\%$ HDSC and the group treated with $7.2\%$ HDCC (Figure 7) had low levels of cellular infiltrates and good tissue organization, which was similar to that of the positive control.
The sections stained with HDCC $7.2\%$ and the HDSC $7.2\%$ group had similar results to the SAF-gel®, which showed tissue organization and a significant reduction in cellular infiltrates (mainly macrophages and leukocytes) to the injured tissues.
The evaluation of collagen by skin staining was conducted using the Picrosirius–Hematoxylin technique. The collagen fibers were stained, and the different types were analyzed for organization of tissue restoration (Figure 8).
The $7.2\%$ HDCC and $7.2\%$ HDSC (Figure 8) showed a significantly red contrast represented by the collagen fibers present, this result was similar to results of the positive control. Treatment with $7.2\%$ HDCC and $7.2\%$ HDSC appeared to contribute directly to the tissue restoration process, highlighting the possible anti-inflammatory and healing potential, confirming its use in future applications as a dressing for tissue injuries.
This research showed that calendula extract, associated with the polyacrylamide hydrogel matrix, can be effective in the treatment of skin wounds, because it provides perfect conditions for faster, more effective wound healing. The bandage made from the formulation also showed a reduction in the amount of exudate as well as macrophage proliferation. Afrin et al. [ 57] and Zhang et al. [ 58] also confirmed the efficiency of hydrogels in the wound healing process in an in vivo study. The anti-inflammatory action observed in the results was attributed to flavonols (specifically rutin) present in the calendula extract. This anti-inflammatory activity is scientifically proven and has been shown to be efficient for healing skin wounds, making it ideal to be used as a bandage. This study confirms the importance of the hydrogel matrix as a release mechanism [59], for drug substances, extracts [60] and liposomes loaded with resveratrol [61]. There is a possible application of this release mechanism in the pharmaceutical and cosmetic areas. Given the positive results obtained, future studies will involve performance tests to characterize the hydrogel, in addition to studies that prove the mechanism of action of the flavonoids responsible for promoting anti-inflammatory action.
## 3.1. Materials
Acrylamide ≥ 99 % (AAm), Sodium persulfate ≥ 98 % (SP), methylcellulose viscosity: 15 cP (MC), N,N,N,N-tetramethylethylenediamine $99\%$ (TEMED), N,N′-Methylenebisacrylamide 99 % (MBAAm) were purchased from Sigma-Aldrich (St. Louis, MO, USA). All chemicals and solvents of analytical reagent grade were obtained from LabSynth (São Paulo, Brasil).
## 3.2. Preparation of Calendula Extract
The calendula extract was obtained using the percolation method. One kilogram of the plant drug was placed in the hydrothanic solution at $70\%$ and left to be macerated for 72 h. After this period, the mixture was percolated for 5 days. The extracted solution was concentrated using a rotary evaporator (Buchi R-210, Geneva, Switzerland) at a controlled temperature (40 ± 2 °C) until all the solvent was evaporated. The remaining crude extract (CE) was placed in an amber flask and maintained under refrigeration until the analysis [62].
## 3.3. Synthesis of Hydrogel
White hydrogels (HDSC) and hydrogels with calendula extract (HDCC) were synthesized using free radical polymerization. The synthesis was carried out in aqueous solution, adding the monomer AAm $7.2\%$ m/v, $0.5\%$ MC m/v, the crosslinking agent MBAAm (8.55 µmol·mL−1). The reaction initiator was then placed in the reaction medium, sodium persulfate (SP) (3.38 µmol·mL−1) and the catalyst TEMED (3.21 µmol·mL−1). For the synthesis of HDCC, calendula extract was incorporated at a concentration of 100 mg/mL before being added to the reaction medium containing the reaction initiator sodium persulfate and the catalyst. The solution was placed under nitrogen (N2) atmosphere for 20 min [23]. The hydrogels were then placed on dialysis for 3 days in distilled water and the water was changed every 24 h. The hydrogels were lyophilized for the in vivo study and analysis of the degree of swelling. In order to carry out the scanning electron microscopy analysis, the hydrogels were micronized (Pulverisette 14 Fristch, Idar-Oberstein, Germany) with a 500 µm mesh.
## 3.4.1. Surface Morphology Analysis
The morphological analysis of the hydrogels was performed using the Scanning Electron Microscope (LEO-ZEISS, 1450 VP, Jena, Germany). The micronized hydrogels were deposited on a sample holder with the aid of carbon adhesive tape and coated with a layer of gold (Au) 15 nm thick for 1.5 min and observed in secondary electrons and magnification 1400× [23].
## 3.4.2. Swelling Assay
The $7.2\%$ HDSC and $7.2\%$ HDCC were immersed in deionized water until they reached swelling equilibrium. After blotting off the excess water, their weights were recorded and denoted as Weq. The hydrogels were stored at 37 °C while the tests were being conducted. Their weights were measured and recorded at predetermined time intervals [63]. The swelling behavior of the hydrogels was obtained using the following equation:[1]Swelling behavior (%)=WtWeq×$100\%$ where Wt and Weq represent the time-dependent and initial ($t = 0$ min) weight of hydrogels, respectively.
## 3.4.3. Mechanical Properties by Texturometer
The mechanical properties of $7.2\%$ HDSC, $7.2\%$ HDCC and SAFGel® control were evaluated by tensile test using a texturometer (Brookfield CT-3 Texture Analyzer, Berlin, Germany). The hydrogels were fixed on 4 mm diameter roller grip probes and compressed at a speed of 0.5 mm/s until ruptured. The analysis was performed in triplicate [64,65].
## 3.5.1. Animal Test Subjects
Wistar adult male rats weighing between 200 and 300 g were used in the experiment obtained from the Animal Facility of the Federal University of Pará. The animals were kept in individual cages at temperature (24 ± 3 °C), standard forage, fed with food and water ad libidum and light/dark cycle of 12 h.
## 3.5.2. Acute Dermal Toxicity Test
Seventeen healthy rats were divided into the 4 groups used for each dose (2 animals being used as control). Twenty-four hours before the experiment, the hairs on the dorsal region of the animals’ trunk were removed by epilation, about $10\%$ of the total body surface area, keeping the animal’s skin without damage (Figure 9). Samples of HDSC and HDCC measuring approximately 5 cm2, were applied to the animal’s dermis and kept in contact with the animal’s skin for 24 h. After this period, samples been removed and effects on the dermis were evaluated. The animals were observed for 14 days, then submitted to euthanasia, under the administration of a lethal dose of thiopental [66].
## 3.5.3. Ulcer Formation
The biocompatibility study of the hydrogels was carried out using the ischemia and reperfusion pressure ulcer model. Thirty-two adult male rats were separated into four groups. All the test rats underwent the cycles of ischemia and reperfusion to form the wound and treated with HDSC, HDCC, negative control (saline solution) and positive control (SAFGel®). The wound was created after epilation using a surgical procedure where a sterilized steel plate was inserted into the animal’s dorsal region. The animals were anesthetized with an anesthetic solution of ketamine (20 mg/mL), xylazine (4 mg/mL), acepran (2 mg/L) and diazepam (0.3 mg/mL, diluted in saline solution). Volume of 200 µL was administered for every 100 g of animal. Twenty-four hours after insertion of the plate, 4 cycles of ischemia and reperfusion were performed per day, consisting of 2 h of ischemia and 30 min of reperfusion. The pressure was applied using a 2 × 1 × 1 cm magnet of 1250 Gauss [67]. The treatment lasted for three days, after which the animals were submitted to euthanasia, under the administration of a lethal dose of thiopental [66].
## Exudate Formation Assessment
The exudate was collected through an incision at the wound site and removal of the steel plate. After that, 1 mL of saline solution was placed in the place where the plate was and later, with the aid of an automatic pipettor, the volume total was withdrawn and accounted for [67].
## Cell Migration Assessment
After the exudate volume assessment, 20 µL of exudate was removed to count the cell migration in the necrotic region. The exudate was diluted using PBS; 20 µL of exudate to 180 µL of PBS ($\frac{1}{10}$). Twenty microliters was collected and diluted using 180 µL of methylene blue ($\frac{1}{10}$). The total number of cells was quantified in a Neubauer chamber [67].
## Necrotic Tissue Area Analysis
The area of necrosis (2 × 1 cm2) and the total area (4 × 2.5 cm2) were photographed using a digital camera Samsung (Samsung, Manaus, Brazil, 12.1 megapixels), and the ratio between these areas was presented as a percentage (%) after complete removal from the injured area. The images were analyzed using the Image J 1.3.1 program (National Institute of Mental Health, Bathesda, MD, USA), suitable for calculating areas [67].
## Nitric Oxide Activity Evaluation
The production of nitric oxide from the exudate supernatant was evaluated through the quantification of its metabolite nitrite, using the Griess Reagent method [68]. After 10 min of reaction, the samples were read at a wavelength of 540 nm. The nitrite concentrations in the samples were determined through the factor obtained from the standard curve, with serial dilutions of sodium nitrite conducted at known concentrations. To exclude interference from protein accumulation in the exudate during analysis by the ELISA reader, samples were centrifuged for 5 min at 3000 rpm before the conduction of the standard procedure [68].
## Hematoxylin and Eosin Evaluation
The effect of the hydrogel dressing on the lesions, was evaluated using histology. The injured tissues were preserved in formaldehyde ($10\%$) for 24 h, and then cryoprotected in sucrose ($20\%$). The samples were embedded in paraffin, the sections were prepared using a microtome and stained with hematoxylin/eosin. The histological sample from the cryostat were soaked in alcohol ($99\%$, $95\%$ and $70\%$), washed with running water (5 min), smeared with hematoxylin (10 min) and washed again under running water (5 min). The tissue was then dappled with eosin (5 min), washed with running water (5 min) and dehydrated in $70\%$, $95\%$, $99\%$ and absolute alcohol. The samples were then cleared in xylol I and II (5 min), after which they were mounted on slides for microscopic analysis [69,70].
## Collagen Evaluation Using Picrosirius Red
Histological sections of 40 µm were rinsed using running water, and the Picrosirius dye was placed on the tissues (30 min). The slides were washed under running water (3 min), and after drying they were covered with Hematoxylin Carazzi (1 min) and washed under running water again (5 min). After staining, the slides were analyzed under brightfield microscopy [67].
## 3.6. Statistical Analyses
The data was analyzed using mean, standard deviation and analysis of variance (ANOVA). F-test was used to compare the samples and the differences between means were detected by the Tukey using Graphpad Prism 7.0. A p-value less than 0.05 was considered statistically significant.
## 4. Conclusions
Polyacrylamide hydrogel synthesized in association with the calendula extract showed advantages in its use as a dressing for wound healing. The application of the hydrogel in the in vivo study promoted tissue regeneration and accelerated the healing process, positively regulating the expression of the main growth factors and reducing the production of pro-inflammatory factors. Results also showed an increase in the number of collagen fibers. The production of collagen fibers occurred through fibroblasts, the staining demonstrates the increase in birefringence of this material, qualitatively demonstrating an increase in newly formed collagen fibers and this, based on the healing cascade, is associated with intense fibroplasia in the tissue. No signs were seen of dermal or systemic toxicity. In addition, the polyacrylamide biomaterial bandages were easy to apply and remove from lesions after treatment. Although in some parameters of evaluation of the healing activity of HDSC and HDCC they were similar, it is believed that the study was promising. An increase in calendula concentration can heighten the efficiency of the wound healing process, as calendula is a species well known for its healing and anti-inflammatory potential. The positive results contribute to the technological development of the product, which is expected to be used in the future in the creation of a topical herbal therapy application for wound treatment.
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|
---
title: 'The Positive Effect of 6-Gingerol on High-Fat Diet and Streptozotocin-Induced
Prediabetic Mice: Potential Pathways and Underlying Mechanisms'
authors:
- Kunli Wang
- Linghua Kong
- Xin Wen
- Mo Li
- Shan Su
- Yuanying Ni
- Junlian Gu
journal: Nutrients
year: 2023
pmcid: PMC9968036
doi: 10.3390/nu15040824
license: CC BY 4.0
---
# The Positive Effect of 6-Gingerol on High-Fat Diet and Streptozotocin-Induced Prediabetic Mice: Potential Pathways and Underlying Mechanisms
## Abstract
The purposes of the present work are to assess how 6-gingerol (6G) positively influences serum glucose regulation in mice with prediabetes triggered by streptozotocin (STZ) plus a high-fat diet (HFD) and to clarify its underlying mechanisms. An analysis of prediabetic symptoms and biochemical characteristics found that 6G intervention was significantly associated with reduced fasting glucose levels, alleviated insulin resistance, better glucose tolerance, hepatic and pancreatic impairment, and dyslipidemia. For the recognition of the target gut microbiota and the pathways linked to 6G’s hypoglycemic function, a combination of hepatic RNA and 16S rRNA sequencing was employed. Specifically, 6G significantly improved the dysbiosis of the gut microbiota and elevated the relative abundances of Alistipes, Alloprevotella, and Ruminococcus_1. Furthermore, 6G supplementation inhibited gluconeogenesis and stimulated glycolysis by activating the PI3K/AKT axis, which also repressed the oxidative stress through Nrf2/Keap1-axis initiation. In addition, Spearman’s correlation analyses reveal a complex interdependency set among the gut microbiota, metabolic variables, and signaling axes. Taken together, the hypoglycemic effect of 6G is partially mediated by altered gut microbiota, as well as by activated Nrf2/Keap1 and PI3K/AKT axes. Thus, 6G may be used as a candidate dietary supplement for relieving prediabetes.
## 1. Introduction
Recently, with lifestyle changes, the global prevalence of diabetes has reached alarming levels. By 2045, the estimated number of adults suffering from diabetes will be 700 million, and type 2 diabetes mellitus (T2DM) will be the most prevalent form of diabetes [1]. For T2DM, impaired fasting glycemia and impaired glucose tolerance (IGT) constitute the high-risk symptoms of prediabetes [2,3]. Notably, patients with IGT represent over $80\%$ of the entire prediabetic population, and in the absence of appropriate interventions, T2DM progression occurs in more than $70\%$ of IGT cases every year [4,5]. Therefore, effective interventions for prediabetes are a desirable way of delaying or preventing T2DM occurrence. Due to the side effects of antidiabetic drugs, finding and developing natural hypoglycemic substances and adjusting metabolic homeostasis have become safe and feasible nutritional strategies for the prevention of T2DM.
Gut microbiota composition and dysfunction exhibit a tight linkage to the onset and evolution of prediabetes and T2DM [6]. Dysbiosis of gut microbiota has been found to produce peptidoglycan and lipopolysaccharide, which can enter the bloodstream and cause inflammation in the body, ultimately leading to insulin resistance and prediabetes [7]. Interestingly, studies have reported that functional foods and their bioactive constituents (e.g., plant-derived polyphenols) might be capable of altering the composition of gut microbiota, thereby helping regulate host physiology and metabolism [8,9]. Therefore, intervention for gut microbiota using plant active ingredients may be a key tool in prediabetes management. Furthermore, through the mediation of lipid metabolism, glucose homeostasis, and protein synthesis, the PI3K/AKT pathway can play a vital function in cellular physiology, whose imbalance is a cause of T2DM and developing obesity [10]. Nuclear transcription factor erythroid 2-associated factor 2 (Nrf2)/Kelch-like ECH-related protein l (Keap1), the most critical pathway of antioxidant defense, is closely associated with improving the body’s antioxidant capacity and reducing inflammation [11]. This pathway exerts a pivotal effect on T2DM development [12]. Therefore, it is necessary to discover natural active substances that have regulatory effects on both pathways and their downstream related pathways.
As a common spice and herbal medicine, ginger (Zingiber officinale Roscoe) has been reported to promote body metabolism, regulate blood glucose, and improve obesity [13,14]. Its chief bioactive constituent is 6G (6-gingerol) [15,16,17], which is capable of entering the blood without causing structural alteration or disruption [18]. Additionally, 6G has been shown to ameliorate HFD-induced dysglycemia in obese rats [19] and to inhibit HFD-induced adipocyte inflammation in obese zebrafish [18]. Thus, 6G is considered a small-molecule compound that can exert metabolic regulatory effects in vivo. However, the mechanism by which 6G improves glycemia in prediabetes is unclear. This study aims to assess 6G’s ameliorating actions on prediabetes induced by HFD/STZ among mice and to clarify the mechanisms behind such actions. The present findings are expected to offer some experimental data on 6G as an ingredient for functional foods.
## 2.1. Preparation of 6G Samples
First, 6G (CAS: 23513-14-6, ≥$98\%$ HPLC purity) was procured from Yuanye Biotechnology in Shanghai, China. Following an initial dissolution in $2\%$ dimethyl sulfoxide (DMSO), the 6G was diluted to 2.5 mg/mL using saline and then subjected to a 10 min ultrasonication. This freshly prepared solution was readily usable.
## 2.2. Animals and Experimental Design
The source of the male C57BL/6J mice, which were aged 4 weeks, was the Vital River Laboratory Animal Technology in Beijing, China. We incubated these mice routinely at 25 ± 2 °C with 45–$65\%$ RH under a 12 h light and 12 h dark cycle. The mice were all fed and watered ad libitum. Each animal experiment, which was approved by the Ethics Committee of Beijing Vitalstar Biotechnology Co. LTD (Beijing, China; approval code, VST-SY-201912), was conducted following the National Research Council Guidelines.
Figure 1A illustrates the holistic design of the experimentation. Following a 1-week acclimatization, the mice were randomly divided into two groups and fed different diets. Supplementary Table S1 details the energy densities and ingredients of the aforementioned diets. For partial mice, after a 6-week feeding of a normal chow diet (NCD; D12450J, with 10 kcal% fat; Research Diets, New Brunswick, NJ, USA), the mice were randomized into two groups. One group continued to be fed NCD (NC group, $$n = 8$$), and the other group was fed NCD supplemented with 6-gingerol (NC+6G group, $$n = 8$$). For the remaining mice, a 4-week feeding of HFD (D12492, supplemented with 60 kcal% fat, Research Diets, New Brunswick, NJ, USA) was implemented initially, and after a 12 h fast, the prediabetic mice were induced by administering the STZ solution (freshly prepared; 100 mg/kg body mass) inside the peritoneum. Fasting blood glucose (FBG) was performed on the mice on day 14, post-injection. Following the sampling of venous blood from the murine tail, a blood glucose meter (Ascensia, Shanghai, China) was utilized to determine the levels of blood glucose. In the current work, mice with FBG in the 3.2–6.2 mM range and 2-h postprandial glucose (2h-PG) in the 7.8–11.1 mM range were deemed as fulfilling the prediabetes (IGT) criteria with two tests and a screening [20,21]. The mice satisfying the prediabetes criteria were randomized into the DC (prediabetic control) group ($$n = 8$$) receiving HFD and 2 other prediabetic groups receiving HFD plus an additional 10 mg/kg·body weight (BW) 6-gingerol (w/w, HFD+6G, $$n = 8$$). During the dosage choice, our prior work was consulted [22]. Throughout the experiment, food ingestion was documented twice weekly, while body mass was documented on a weekly basis. One week before the experimental completion, the mice were gavaged. Six hours later, they were arranged in the metabolic cages, and, following defecation, fecal samples were directly gathered into disinfected conical tubes. Afterward, liquid nitrogen was used to immerse these fecal samples, followed by a −80 °C preservation for subsequent analyses. Upon experimental completion, blood was sampled from the retro-orbital vascular plexus following an overnight abrosia, which was subjected to a 10 min dissociation (3000 rpm) at 4 °C to derive the sera. Instantly thereafter, the sera were preserved at −80 °C for more detailed biochemical assays. After blood collection, the mice were sacrificed, and their tissues and organs were harvested.
## 2.3. Biochemical Analysis
An automatic biochemistry analyzer (Hitachi, Tokyo, Japan) was utilized to determine the levels of serum biochemical variables, such as the total cholesterol (TC), triglyceride (TG), high- and low-density lipoproteins (HDL/LDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and FBG. Commercially available ELISA kits (Jiancheng Bioengineering Institute, Nanjing, China) were utilized to examine the levels of fasting serum insulin, IL-6 (interleukin 6), and TNF-α (tumor necrosis factor α). Assessment of serum LPS concentrations was accomplished following the instructions of a commercially available ELISA kit (Enzyme-linked Biotechnology, Shanghai, China).
## 2.4. Oral Glucose Tolerance Test (OGTT)
Three days prior to experimental completion, an OGTT was conducted according to a prior procedure [23]. Briefly, a $25\%$ solution of glucose dextrose (2 g/kg·BW) was orally administered to the mice fasted for 6 h. Separately at 0, 15, 30, 60, 90, and 120 min after glucose administration, the levels of blood glucose were assessed using a blood glucose meter. For the glucose tolerance evaluation in this study, the areas under the curve (AUCs) of the blood glucose levels were estimated over a 120 min period.
## 2.5. Histology and Immunofluorescence Staining for Tissue Section Analysis
Following the killing of the mice, their hepatic and pancreatic tissues were immobilized in paraformaldehyde ($4\%$), paraffin-embedded, and subsequently sectioned to a 5 µm thickness, followed by hematoxylin and eosin (H&E) staining as per the standard procedure. Thereafter, an Eclipse-ci microscope (Nikon, Tokyo, Japan) was utilized to observe the slides and acquire micrographs. For immunofluorescence, the paraffin-embedded pancreatic sections were deparaffinized, antigen recovered, heated, and blocked. After overnight incubation of the slides using Mouse Anti-Insulin (primary) antibody at 4 °C, an extra 2 h incubation proceeded with Anti-Mouse IgG (secondary; Alexa Fluor 488) antibody at ambient temperature. The samples were coated with DAPI (ProLong®GoldAntifade Reagent, Waltham, Massachusetts, USA) anti-fading reagent, and then a BK-FL fluorescent microscope (Chongqing, China) was utilized for their observation.
## 2.6. Real-Time PCR (RT-PCR) Analysis
Extraction of the total RNA from the hepatic tissue was accomplished following the protocol of TRIZOL reagent (Invitrogen, Carlsbad, CA, USA). Quantitative and qualitative ratiometric analyses of the RNA were conducted with the aid of a Nanodrop 2000 (Thermo Scientific, Wilmington, NC, USA). Reverse transcription of the RNA into cDNA was then carried out using a corresponding High-Capacity kit from Tiangen Biotech. SYBR Green (Shanghai, China) was used to conduct RT-PCR, with which the expression of DEG was relatively quantified. PCR conditions were as follows: 10 min at 95 °C, 10 s at 95 °C, 10 s of annealing at 60 °C, and 10 s of extension at 72 °C, a total of 40 cycles [24]. Regarding the relative mRNA levels of the genes, the 2−ΔΔCT approach was adopted for their estimation, while β-actin was employed as an internal reference for their normalization. Table S2 details the relevant primers.
## 2.7. Western Blot Analysis
The experiments were conducted according to a previously reported study [25]. A 100 mg:1 mL lysis buffer involving a protease suppressor was used for the dissolution of the hepatic tissue. The determination of the protein levels was accomplished per the instructions of a BCA protein assay kit (Pierce, Rockford, AZ, USA). This was followed by isolation of the lysates on the SDS-PAGE gels and subsequent shifting onto the PVDF membranes (0.22 µm). A 1 h blockage of these membranes proceeded in Tris-buffered saline (TBS) involving skimmed milk ($5\%$) and Tween-20 ($1\%$) at room temperature, followed by a 1 h incubation with monoclonal primary antibodies against AKT and p-AKT (1:1000; Beyotime Biotechnology, Shanghai, China) as well as against β-actin, G6P, GK, Nrf2, PEPCK, and Keap1 (Cell Signaling Technology, Danvers, Massachusetts, USA). After incubation, the membranes were thrice washed, followed by an extra 2 h incubation using a 1:2000 dilution of anti-rabbit secondary antibody (Cell Signaling Technology) at 37 °C. Visualization and assessment of Western blot images were accomplished using densitometric scanning (Image Quant TL7.0, GE Healthcare, Chicago, Illinois, USA), where the loading control adopted was β-actin.
## 2.8. Gut Microbiota Analysis
A Mag-Bind Soil DNA Kit (E.Z.N.A; OMEGA, GA, USA) was utilized to extract the genomic DNA from the fecal specimens. Thereafter, to exploit the primers 806R (50-GGACTACHVGGGTWTCTAAT-30) plus 338F (50-ACTCCTACGGGAGGCAGCAG-30), PCR amplification was conducted targeting the 16S rRNA gene’s V3–V4 regions. The PCR products were subjected to purification via a QIAquick PCR Purification Kit (QIAGEN, Valencia, USA). With a MiSeq platform (Illumina, San Diego, CA, USA), sequencing and assessment of the purified amplicons were carried out.
QIIME (V 1.91) was used as a quality filter for the raw FASTQ files after the accomplishment of sequencing. Then, the operational units (OTUs) were clustered by employing UPARSE (7.0.1090, http://www.drive5.com/uparse/, accessed on 10 March 2022), where the similarity cutoff was set at $97\%$. Mothur V.1.30.1 was utilized to conduct the alpha-diversity analysis. Chao1 and Ace were adopted to estimate the richness of the communities, while the Simplon and Shannon indices were adopted for the diversity evaluation. The differences between microbial communities were quantified using principal coordinate analysis (PCoA). For the effect-size assessments of the relevant abundance of specific differential bacteria, linear discriminant analysis (LDA) scores were derived on the basis of the linear discriminant analysis effect size (LEfSe); http://huttenhower.sph.harvard.edu/galaxy/root?tool_id=lefse_upload, accessed on 11 March 2022) was used ($p \leq 0.05$ and LDA score > 3.0) [26]. Data were analyzed online on the freely available Majorbio Cloud Platform (www.majorbio.com, accessed on 10 March 2022).
## 2.9. Statistical Analysis
Data were all expressed as means ± SDs (standard deviations). Univariate analysis of variance (ANOVA) and Tukey’s post hoc test were employed for the analysis of all the experimental outcomes. Furthermore, differences at $p \leq 0.05$ indicated statistical significance. Statistical analysis was performed using SPSS 20.0 (IBM, New York, NY, USA).
## 3.1. Effects of 6-Gingerol Supplementation on Body Weight and Energy Intake
Figure 1B shows the body-mass changes for every group following the prediabetic mice modeling. We found persistent weight gain among the DC group mice compared with the NC and NC+6G groups, and 6G supplementation significantly prevented weight gain (Figure 1C). In addition, 6G supplementation had no effect on the total energy intake in the normal and prediabetic mice during the 12-week experimental period (Figure 1D).
## 3.2. Effects of 6-Gingerol Supplementation on Blood Glucose Metabolism
For the hypoglycemic efficacy assessment of the 12-week treatment with 6G, we determined the FBG, OGTT, and fasting serum insulin (FSI) of every group. The DC group exhibited pronouncedly higher levels of FBG compared to the NC group (12.06 ± 0.92 vs. 5.01 ± 0.12 mmol/L). Mice were deemed as suffering from T2DM when their FBG exceeded 11.1 mmol/L [27]. Therefore, our findings agree with the former work [28] that long-term continuous feeding of HFD following administration of streptozotocin in the DC group can lead to the development from prediabetes to T2DM. The DC+6G mice exhibited drastically decreased FBG than the DC mice. Additionally, higher HOMA-IR and FSI were noted among the DC mice compared to the NC mice, while supplementation with 6G led both of the metrics to decline markedly (Figure 1F,G). Furthermore, the results of the OGTT and AUC demonstrate a serious impairment of glucose tolerance among the DC mice (Figure 1H,I). Supplementation with 6G significantly improved glucose tolerance and insulin resistance.
## 3.3. Effect of 6-Gingerol Supplementation on Serum Parameters
The serum ALT, AST, LDL, TG, and TC levels in the DC group were pronouncedly higher than those in the NC group (Table 1), while 6G treatment markedly reduced the levels of the other indicators except LDL. The level of HDL had also been improved by 6G treatment. Furthermore, 6G led to significantly decreased IL-6, LPS, and TNF-α levels in both the normal and prediabetic mice. This suggests that 6G not only improves the health status of normal mice but also alleviates HFD/STZ-induced metabolic endotoxemia and systemic low-grade inflammation.
## 3.4. Effect of 6-Gingerol Supplementation on the Histopathology of Liver and Pancreatic Tissues
As shown in Figure 2A, the NC mice had normal, neat, and clear hepatic histology, and there were obvious nuclei in the center of the hepatocytes. In addition, 6G supplementation in normal mice did not adversely affect their liver tissue. Serious impairments of liver tissue were noted among the DC mice, including massive hepatocyte steatosis, inflammation infiltrates, and cytoplasmic vacuolization. However, 6G supplementation greatly attenuated the histopathological changes (Figure 2A). These results suggest that 6G supplementation can attenuate hepatocyte injury induced by a high-fat diet and STZ to a certain extent.
According to the results of the pancreatic H&E staining, the pancreatic islet structure was normal for the NC+6G and NC groups (Figure 2B). The DC group had an atrophic structure of the islets, necrotic β-cells in the pancreas, and a destroyed β-cell population. However, the islet structure impairment and necrosis of the β-cells were alleviated prominently with 6G supplementation. Immunofluorescence staining of the pancreatic tissue showed that the pancreatic islets in the NC group and NC+6G group had round or ovoid cell clusters scattered among healthy glandular follicle cells with clear cell borders (Figure 2C). The DC group exhibited a distinctly reduced area and brightness of the pancreatic islets in contrast to the NC group, and the pancreatic islet morphology was irregularly atrophied, suggesting that the pancreatic islet β-cells were apoptotic. The DC+6G group displayed increases in the islet brightness and area in contrast to the DC group, suggesting that the intervention of 6G had a protective effect on the pancreatic islet β-cells.
## 3.5. Effects of 6-Gingerol Supplementation on Hepatic-Glucose-Metabolism-Related and Oxidative-Stress-Pathway-Related mRNA and Protein Expression
It is well established that the PI3K/AKT axis is implicated in insulin-mediated hepatic glucose metabolism, while GK, PEPCK, and G6P are key proteins in glycolysis and gluconeogenesis. The DC+6G group exhibited pronouncedly upregulated PI3K and AKT mRNA levels in contrast to the DC group after the 6G treatment (Figure 3A). At the protein level (Figure 3B,C), the expression of both AKT and p-AKT after 6G treatment was significantly upregulated. GK, the key protein for glycolysis, was also upregulated after 12 weeks of 6G intervention, while key proteins for gluconeogenesis PEPCK and G6P were downregulated after 6G supplementation. Notably, the protein expression level of GK was elevated in the normal mice supplemented with 6G.
Nrf2/Keap1 plays a protective role in antioxidant damage mainly by upregulating antioxidant genes and reducing redox stress. Activation of Nrf2 may be a way to ameliorate oxidative stress. After 12 weeks of 6G intervention, both the protein and mRNA expression of Nrf2 and Keap1 were improved in the prediabetic mice (Figure 3D–F). In addition, 6G supplementation also improved the hepatic protein and mRNA levels of Nrf2 and Keap1 among the normal mice.
## 3.6. 6-Gingerol Supplementation Changed the Gut Microbiota
To investigate the underlying mechanisms of the hypoglycemic effect of 6G, this study assesses the effects of 6G supplementation on the composition and relative abundance of gut microbiota with 16S rRNA sequencing. A total of 1313 859 sequences were generated by setting the mean length to 401–440 base pairs (Figure S1A). A total of 730 OTUs were derived according to $97\%$ similarity (Figure S1B), which can be categorized as 140 genera, 56 families, 32 orders, 19 classes, and 10 phyla. As suggested by the Shannon and rarefaction graphs of the samples (Figure S1C,D), the bacterial communities were detected clearly and distributed homogeneously, and the amount of data sequenced was sufficient. Supplementation with 6G can significantly change gut microbiota diversity (both Shannon and Simpson) (Figure 4A,B). However, insignificant intergroup differences were found in the ACE and Chao1 indices of the gut microbiota (Figure 4C,D), suggesting that 6G had no effect on richness. Afterward, a principal co-ordinates analysis (PCoA) was accomplished on the unweighted UniFrac distances (Figure 4E). As revealed by the results, the gut microbiota composition was significantly altered under the combined HFD/STZ induction and 6G supplementation.
Further, the gut microbiota structures in the four groups were analyzed at different classification levels (Figure 5). Combined HFD/STZ induction led to significant phylum-level alteration of the dominant microbial communities (Bacteroidetes and Firmicutes) (Figure 5A), while after supplementing 6G, the abundance of the dominant microflora returned to normal. Additionally, the Firmicutes-to-Bacteroidetes (F/B) ratio was downregulated after 6G intervention in the normal or model mice (Figure 5A). At the family level, higher abundances were noted in Lachnospiraceae, Ruminococcaceae, and Desulfovibrionaceae following treatment with HFD/STZ (Figure 5B), while the abundances of Bacteroidales_S24-7_group and Bacteroidaceae were lower. The abundances of Bacteroidaceae and Desulfovibrionaceae were significantly up- and downregulated, respectively, after 6G intervention. According to the genus-level observations, the NC+6G and DC+6G groups exhibited considerably higher relative abundances of Ruminiclostridium_9 when compared to the NC and DC groups (Figure 5C).
## 3.7. The Changes in Key Phylotypes of the Gut Microbiota That Responded to 6-Gingerol Supplementation
The cladogram generated from the LEfSe analysis indicated that 6-gingerol supplementation altered the bacterial taxa specifically (Figure 6A). In addition, LDA scoring was performed to identify discriminative features (Figure 6B,C). Among the NC mice, we observed abundance elevations in a few bacterial genera, such as the genera Bilophila, Odoribacter, and Anaerotruncus. As for the DC group, enrichment of the gut microbiota was noted in the genera Oscillibacter and Tyzzerella. Furthermore, both the NC+6G and DC+6G groups are characterized by a higher content of the Alistipes, Alloprevotella, and Ruminococcus_1 genera.
## 3.8. Correlations among the Critical Gut Microbiota, Biochemical Parameters, and Signaling Pathways
To probe deeper into the correlations among the crucial gut microbiota, biochemical parameters, and key hepatic gene expression, a Spearman correlation assessment was performed (Figure 7). As revealed by the assessment, there were negative associations of Alistipes, Alloprevotella, and Odoribacter with TNF-α, and Alistipes also showed a negative correlation with AUC and IL-6. In addition, Odoribacter, Bilophila, and uncultured_bacterium_g_Bilophila showed a negative correlation with FG, and Oscillibacter and Tyzzerella showed a positive correlation with FG.
As for the correlation of gut microbiota with hepatic gene expression, we noticed significant positive associations of Alloprevotella, Alistipes, and Ruminococcus_1, which were enriched with 6G supplementation, with the level of AKT. Alloprevotella and Alistipes also showed a negative correlation with PEPCK expression. Moreover, Odoribacter was linked significantly positively to AKT and GK expression and showed a negative correlation with PEPCK expression.
## 4. Discussion
During the development of diabetes, prediabetes is a high-risk state, and with appropriate interventions, the progression to diabetes can be reversed, and blood glucose can even be restored to normal levels [29]. Numerous studies have demonstrated the metabolic modulating function of ginger [13,14,24,30]. Our previous study showed that ginger oleoresin has the function of regulating blood glucose metabolism in mice, and 6G comprises the biggest proportion of active ingredients in ginger oleoresin [22]. As far as we know, the present work is the first to offer evidence that supplementation with 6G, an active substance in ginger, helps to improve HFD/STZ-induced prediabetes.
In this study, progressive weight gain was noted among the DC mice following HFD feeding, while supplementation with 6G was effective in controlling weight gain, independent of food intake. Agreeing with the former findings of [31], 6G’s hypoglycemic activity is proven by the evident declines in AUC and FG. In addition, 6G was effective in improving liver and pancreas damage. In mice with prediabetes triggered by HFD/STZ, 6G supplementation significantly restored glucose tolerance, ultimately avoiding the worsening of prediabetes. Next, this study has further investigated the underlying mechanism by which 6G improves blood glucose levels in prediabetic mice by revealing the effects of 6G on the expression of hepatic key genes and the composition of gut microbiota.
The liver is a crucial organ for keeping bodily glucose homeostasis [32]. Glucose metabolism in the liver consists of glycolysis, gluconeogenesis, glucose transport, glycogen synthesis, and catabolism [33]. Through the translocation facilitation of glucose transporter 4, glucose transport can be upregulated by 6G [34]. However, evidence for the regulation of other key glucose metabolic pathways by 6G is still lacking. Regulation of these key pathways is achieved via the insulin-mediated PI3K/AKT axis [35]. Hence, we have further unraveled the possible mechanisms for glucose metabolism regulation by 6G by exploring how supplementation with 6G specifically influences the PI3K/AKT axis as well as its downstream effectors.
As indicated by extensive evidence, the foremost factors in the PI3K/AKT axis are AKT and PI3K [35]. For instance, AKT has high levels of expression in the liver and other conventional insulin target tissues, and its positive role in reducing blood glucose and improving insulin sensitivity has been reported [36]. Both of these factors were upregulated in our current study, suggesting PI3K/AKT-axis initiation by the supplemental 6G. Then, the levels of the critical genes in glycolysis (e.g., G6P) and gluconeogenesis (e.g., GK and PEPCK) were determined to further elucidate the biological processes and target genes implicated in 6G’s hypoglycemic function. Studies have shown that through expression regulation of these enzymes, dietary intervention can enhance glucose metabolism [37,38]. For example, by regulating the hepatic levels of glucose-metabolizing enzymes (e.g., PEPCK and G6P), undaria pinnatifida polysaccharides reduced blood glucose [39]. Through the regulation of hepatic G6P and GK levels, millet dietary intervention regulated blood glucose [40]. In our work, upregulation of GK was noted in the hepatic tissues for the 6G intervention group, implying the proglycolytic function of 6G supplementation in the diabetic murine liver tissues, which was achieved with glycolysis upregulation. Meanwhile, G6P and PEPCK expression was downregulated in the liver, indicating that 6G also downregulated hepatic gluconeogenesis.
Given that oxidative stress exacerbates T2DM, antioxidant therapy has gained more attention [41]. It has been shown that the Nrf2 pathway is inhibited in response to oxidative stress stimuli and impaired islet function is exacerbated, possibly mediated by PI3K/AKT [42]. In addition, natural active components in plants, such as sulforaphane, can effectively modulate Nrf2 [43]. In this study, Nrf2 and Keap1, key genes in the Nrf2 pathway, were regulated after 6G intervention, indicating that the Nrf2/Keap1 pathway was improved.
There is now accumulating evidence that the onset and progression of T2DM are closely linked to the gut microbiota [44,45], whose role in prediabetic disease development is thus pivotal. Therefore, apart from the possible direct effect of 6G on the liver in regulating hepatic glucose metabolism, the effect of 6G on gut microbiota was also investigated in the case of prediabetic mice. Here, 6G was found to restore the HFD/STZ-disrupted composition of the gut microbiota and facilitate certain specific bacterial growth in the mice intaking HFD and NCD. The abundance of Bacteroidaceae in the prediabetic model mice was upregulated after 6G intervention. Downregulation of Bacteroidaceae may contribute to the occurrence of T2DM [46]. In addition, 6G supplementation restored the HFD/STZ-induced enrichment of Desulfovibrionaceae, which cause intestinal inflammation through the production of endotoxins (such as LPS). This finding agrees with previous research reporting the ability of a plant-based diet to decrease Desulfovibrionaceae abundance upregulation due to HFD [14,47]. Furthermore, 6G intervention altered key phylotypes in each group at the genus level. As mentioned in the Results section, three species, the Alistipes, Alloprevotella, and Ruminococcus_1 genera, were present in the key communities in the NC+6G and DC+6G groups, suggesting that 6-gingerol supplementation significantly upregulated three OTUs. Sshort-chain fatty acid (SCFA)-producing bacteria like Alistipes, Alloprevotella, and Ruminococcus_1 [10,48,49,50] were enriched after 6G supplementation. Inverse correlations of these SCFA-producing bacteria with insulin resistance, inflammation, and obesity have been reported [51,52]; moreover, these bacteria may enhance host antidiabetic effects.
As demonstrated by the results of a correlation analysis of environmental factors, the specific gut microbiota were negatively associated with the physiological and biochemical correlates of prediabetes and were associated with factors pertaining to PI3K/AKT expression, gluconeogenesis, and glycolytic pathways. Therefore, our outcomes imply that apart from impacting prediabetes markers, gut microbiota may also be correlated with critical hepatic gene expressions. As supported by increasing evidence, gut microbiota (e.g., Alistipes, Rikenella, and Odoribacter) influence key hepatic gene expressions and are positively linked to factors pertaining to the PI3K/AKT and AMPK/SIRT1 axes [10,53,54]. In the present study, the upregulation of Alistipes and Alloprevotella and the downregulation of Odoribacter all alleviated prediabetic symptoms, upregulated the PI3K/AKT and glycolytic pathways, and downregulated glycoisomeric pathways. However, no correlation between the Nrf2/Keap1 pathway and gut microbiota was found. It may be that the 6G intervention affected the metabolism and composition of the gut microbiota and that there was portal venous transport of the metabolites to the liver, which has an impact on the expression of key genes. However, the metabolites of 6G after metabolism by the gut microbiota and the role of metabolites in the regulation of blood glucose still need to be further explored.
The last thing to point out is that although 6G has a good ability to regulate blood glucose, the current experimental results do not prove that 6G can be used in clinical trials immediately. The basic characteristics of 6G pharmacokinetics such as absorption and metabolism in vivo need to be further explored. On the basis of these results, we will explore the possibility of 6G being developed into drugs or functional foods.
## 5. Conclusions
Conclusively, we discovered herein that 6G intervention reduced HFD/STZ-induced weight gain and improved metabolic syndrome symptoms such as hyperglycemia, lowered glucose tolerance, dyslipidemia, insulin resistance, damage of liver and pancreatic tissues, and low-grade systemic inflammation. The 16S rRNA sequencing analysis demonstrated that 6G supplementation led to prominent alterations in the gut microbiota composition, including increases in Bacteroidaceae, Ruminiclostridium_9, Alistipes, Alloprevotella, and Ruminococcus_1 and decreases in Desulfovibrionaceae. In addition, 6G regulated blood glucose through PI3K/AKT pathway initiation and suppression of the relative PEPCK and G6P levels, while having a facilitative effect on the Nrf2/Keap1-mediated antioxidant pathway. This evidence suggests that 6G does not exert its protective effect against prediabetes through a single pathway but rather through the body’s overall metabolic balance through the regulation of gut microbiota and the critical hepatic gene levels. Therefore, 6G has great potential as an adjuvant therapy strategy for prediabetes. In addition, using the present study as a basis, further research is needed to explore the metabolites of 6G after metabolism by gut microbiota and the role of metabolites in the regulation of blood glucose.
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|
---
title: Optimal Heart Rate Control Improves Long-Term Prognosis of Decompensated Heart
Failure with Reduced Ejection Fraction
authors:
- Ming-Lung Tsai
- Shu-I Lin
- Yu-Cheng Kao
- Hsuan-Ching Lin
- Ming-Shyan Lin
- Jian-Rong Peng
- Chao-Yung Wang
- Victor Chien-Chia Wu
- Chi-Wen Cheng
- Ying-Hsiang Lee
- Ming-Jui Hung
- Tien-Hsing Chen
journal: Medicina
year: 2023
pmcid: PMC9968049
doi: 10.3390/medicina59020348
license: CC BY 4.0
---
# Optimal Heart Rate Control Improves Long-Term Prognosis of Decompensated Heart Failure with Reduced Ejection Fraction
## Abstract
Background and Objectives: An elevated heart rate is an independent risk factor for cardiovascular disease; however, the relationship between heart rate control and the long-term outcomes of patients with heart failure with reduced ejection fraction (HFrEF) remains unclear. This study explored the long-term prognostic importance of heart rate control in patients hospitalized with HFrEF. Materials and Methods: We retrieved the records of patients admitted for decompensated heart failure with a left ventricular ejection fraction (LVEF) of ≤$40\%$, from 1 January 2005 to 31 December 2019. The primary outcome was a composite of cardiovascular death or hospitalization for heart failure (HHF) during follow-up. We analyzed the outcomes using Cox proportional hazard ratios calculated using the patients’ heart rates, as measured at baseline and approximately 3 months later. The mean follow-up duration was 49.0 ± 38.1 months. Results: We identified 5236 eligible patients, and divided them into five groups on the basis of changes in their heart rates. The mean LVEFs of the groups ranged from $29.1\%$ to $30.6\%$. After adjustment for all covariates, the results demonstrated that lesser heart rate reductions at the 3-month screening period were associated with long-term cardiovascular death, HHF, and all-cause mortality (p for linear trend = 0.033, 0.042, and 0.003, respectively). The restricted cubic spline model revealed a linear relationship between reduction in heart rate and risk of outcomes (p for nonlinearity > 0.2). Conclusions: Greater reductions in heart rate were associated with a lower risk of long-term cardiovascular death, HHF, and all-cause mortality among patients discharged after hospitalization for decompensated HFrEF.
## 1. Introduction
A high resting heart rate is an independent risk factor for all-cause mortality, cardiovascular mortality, and cardiovascular events among the general population [1,2] as well as among patients with cardiovascular disease, coronary artery disease, hypertension, heart failure, and diabetes [3,4,5,6,7,8,9]. The relationship between heart rate and adverse outcomes may be mediated by the effects of heart rate on coronary blood flow, cardiac contractility, and energy expenditure [7,10]. Reducing a patient’s heart rate can reduce afterload, relieve left ventricular wall stress, and increase the stroke volume of the left ventricle, thus improving the patient’s heart function and alleviating their cardiovascular symptoms [11]. These findings suggest that physicians should implement interventions to reduce the heart rates of patients with HFrEF and improve their clinical outcomes.
Numerous studies have explored the effects of heart rate control on patients with heart failure. A randomized controlled trial involving patients with HFrEF, the Ivabradine and Outcomes in Chronic Heart Failure (SHIFT) study, demonstrated that reductions in heart rate due to ivabradine benefit patients with HFrEF who have heart rates of >70 bpm, despite receiving guideline-directed therapies, including beta blockers [12]. The rates of major adverse cardiovascular events, namely hospitalization for heart failure (HHF) and cardiovascular death, were significantly lower in the ivabradine group than in the placebo group, especially among the patients with higher baseline heart rates.
The importance of heart rate monitor and control have been addressed in major guidelines [13,14]; however, the relationship between heart rate reductions and health outcomes have not been thoroughly evaluated. In addition, few studies have analyzed the long-term outcomes of heart rate control for patients discharged after hospitalization for decompensated HFrEF. We conducted this study to evaluate the effect of heart rate reductions on the long-term outcomes of patients with HFrEF discharged from the hospital through an analysis of records from multiple healthcare institutions.
## 2.1. Data Source
This study was conducted using the Chang Gung Research Database (CGRD), a de-identified database managed by the largest healthcare provider in Taiwan, the Chang Gung Memorial Hospital (CGMH) healthcare system. The CGMH system is multi-institutional, comprising seven healthcare institutions (four tertiary academic medical centers and three teaching hospitals) across Taiwan. The use of data from the CGRD as the basis for accurate estimates in medical studies has been validated [15]. The Chang Gung Memorial Hospital Institutional Review Board approved this study and waived the requirement for informed consent. The patients’ records were anonymized and de-identified before analysis. For data generated before 2015, we used the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for diagnosis, whereas for data generated after 2016, we used both the ICD-9-CM and the ICD Tenth Revision (ICD-10-CM). More information regarding the CGRD has been published in other articles [15,16]. This study was conducted in accordance with the principles outlined in the Declaration of Helsinki [17].
## 2.2. Study Group and Cohort
From the CGRD, we retrieved the records of patients admitted for decompensated heart failure with a left ventricular ejection fraction (LVEF) of ≤$40\%$, from 1 January 2005 to 31 December 2019. The index date was the date when each patient was discharged after index heart failure admission. Each patient’s LVEF was determined on the basis of the echocardiography report generated during the index admission. Each patient’s baseline heart rate was defined as their first heart rate recorded after the index admission. The first recorded heart rate at admission is the condition before medications or treatments for heart failure control. Each patient’s follow-up heart rate was defined as their heart rate recorded at the 3-month screening period in the outpatient department. Clinically, physicians may frequently adjust the medication and treatment for a short period after discharge. It was noted that the medications prescribed for heart failure were less changed until a period of 2–4 months after discharge. Thus, we chose the 3 months after discharge as the screening period. Patients were excluded if they were aged younger than 20 years, had a baseline heart rate of <70 bpm, had a diagnosis of atrial fibrillation or atrial flutter before or during the index admission, or did not survive to discharge. Patients who died, presented with heart failure exacerbation and required readmission before the 3-month screening period, had follow-up periods of <90 days, or lacked follow-up heart rate measurements, were also excluded (Figure 1). A total of 5236 patients with decompensated heart failure and an LVEF of ≤$40\%$ requiring hospitalization with follow-up durations of over 3 months were determined to be eligible for inclusion.
## 2.3. Covariate Measurements
The covariates of interest were demographic characteristics (age, sex, smoking status, and body mass index), baseline vital signs (systolic and diastolic blood pressure and heart rate), number of HHFs in the previous year, number of HHFs in the previous 3 years, comorbidities (coronary artery disease, myocardial infarction, hypertension, dyslipidemia, diabetes mellitus, chronic kidney disease, dialysis, stroke, chronic obstructive pulmonary disease, peripheral arterial disease, and liver cirrhosis), medications used during the index admission (angiotensin-converting enzyme inhibitors [ACEIs] or angiotensin receptor blockers [ARBs], beta blockers, and 11 others), laboratory test results (serum creatinine levels and 15 others), echocardiography results, in-hospital events, and heart failure medications taken within 3 months of discharge (Table 1 and Table 2). The echocardiographic parameters of interest were the LVEF, left ventricular end-diastolic diameter, left ventricular end-systolic diameter, left atrium diameter, and mitral regurgitation severity. The in-hospital covariates during the index admission were hospital stay (in days), intensive care unit (ICU) stay (in days), episodes of shock (use of inotropic agents, intra-aortic balloon pumps, or extracorporeal membrane oxygenation), intubation, episodes of acute coronary syndrome, and percutaneous coronary interventions. The heart failure medications of interest were beta blockers, ivabradine, digoxin, ACEIs/ARBs, angiotensin receptor–neprilysin inhibitors (ARNIs), mineralocorticoid receptor antagonists (MRAs), and loop diuretics.
## 2.4. Outcome Definitions
The primary outcome was a composite of cardiovascular death or HHF during follow-up. The secondary outcomes were cardiovascular death, HHF, and all-cause mortality. HHF was defined as unscheduled hospitalization during which the patient required at least one treatment, which may have included diuretics, nitrites, or inotropic agents. The patients’ dates, places, and causes of death were linked to the Taiwan Death Registry database. The definition of cardiovascular death encompassed death due to acute myocardial infarction; sudden cardiac death; and death due to heart failure, stroke, cardiovascular procedures, cardiovascular hemorrhage, or other cardiovascular causes [18]. The follow-up period was defined as the period from the date of the index hospitalization to the date of death, outcome occurrence, or loss to follow-up or 31 December 2020, whichever occurred first.
## 2.5. Statistical Analysis
We categorized each patient into one of six ordinal groups on the basis of change in their heart rate from discharge to the 3-month screening period (decrease of ≥30 bpm, decrease of 20–29 bpm, decrease of 10–19 bpm, decrease of 0–9 bpm, increase of 1–10 bpm, and increase of >10 bpm). The associations among the baseline characteristics of the patients in the groups were tested using the Cochran–Armitage test for categorical variables, the general linear model for continuous variables, and the Jonckheere–Terpstra test for obviously skewed data (e.g., B-type natriuretic peptide levels). The association between the changes in the patients’ heart rates and their risk of outcomes was assessed using a Cox proportional-hazards model. The linear trend across the ordinal groups on the risk of outcomes was tested. In addition, we obtained the hazard ratios and corresponding confidence intervals using the ≥30-beats-per-minute decrease group as the reference group. We adjusted for all the covariates listed in Table 1 and Table 2 except the follow-up duration, including baseline heart rate and heart failure medications taken within 3 months of discharge, in the multivariable model.
Since the cut-off values used to group the patients were subjective and arbitrary, we explored the possibility of a nonlinear relationship between changes in heart rate and risk of outcomes by treating heart rate reduction as a flexible restricted cubic spline. The locations of knots were set to the 5th, 35th, 65th, and 95th percentiles. We adjusted for the covariates in the restricted cubic spline model. Since our data set had some missing values, the Cox models (including the restricted cubic spline model) were calculated using the complete data after single expectation–maximization imputation. R (version 4.0.4, R Project for Statistical Computing) and the “rms” package (version 5.1 to 3.1) were used to generate the restricted cubic spline model. SAS (version 9.4, SAS Institute) was used for other statistical analyses. A two-sided p-value <0.05 was considered statistically significant.
## 3.1. Patient Characteristics and Baseline Demographics
A total of 5236 patients were eligible in our analysis. The mean (± standard deviation) age was 63.0 ± 15.5 years, and nearly $70\%$ of the patients were male. Of note, $15.9\%$ of the subjects had been admitted for heart failure in the previous year. The most prevalent comorbidity was hypertension ($67.4\%$), followed by coronary artery disease ($57.3\%$), diabetes ($48.2\%$), dyslipidemia ($42.3\%$), and chronic kidney disease ($39.7\%$). The most common medications prescribed for heart failure during the index admission were ACEIs/ARBs ($86.3\%$), loop diuretics ($84.1\%$), and beta-blockers ($81.7\%$). The mean baseline LVEF was 30.2 ± $7.2\%$, and about one-thirds ($33.6\%$) of the patients had moderate or severe mitral regurgitation. The mean hospital days was 13.1 ± 12.7 days, and the mean ICU duration was 1.8 ± 3.7 days. During the 3-month screening period after discharge, the most common medications prescribed for heart failure were ACEIs/ARBs ($69.2\%$), beta-blockers ($66.4\%$), and loop diuretics ($65\%$). Of note, the average follow-up duration was 49.0 ± 38.1 months.
The results of patients’ characteristics and baseline demographics are listed in Table 1 and Table 2. More than half of the patients had diagnosed coronary artery disease ($51.9\%$ to $61.2\%$) and hypertension ($63.4\%$ to $69.2\%$), and $39.8\%$ to $50.6\%$ of the patients had diabetes mellitus. Most ($74.1\%$ to $86.1\%$) had no records of previous HHFs in the 3 years preceding the index admission. Most of the patients received standard treatments, including ACEIs/ARBs ($83.8\%$ to $90.1\%$) and beta blockers ($75.0\%$ to $86.8\%$), during the index hospitalization. Most ($80.7\%$ to $90.9\%$) of the patients were prescribed loop diuretics. The mean LVEFs of the different groups ranged from 29.1 ± $7.7\%$ to 30.6 ± $7.0\%$. The patients’ hospital stay ranged from 11.9 ± 10.9 to 15.1 ± 11.6 days, of which the ICU constituted 1.2 ± 3.0 to 3.0 ± 4.6 days. In both cases, the most days were spent in the ≥30-bpm decrease group. Some of the patients experienced episodes of shock ($12.0\%$ to $23.2\%$) or respiratory failure ($1.2\%$ to $4.3\%$) during the index hospitalization. Heart failure medication coverage at the 3-month screening period was lower than that at admission (56.8–$76.3\%$ vs. 78.1–$86.8\%$ for beta blockers, and 66.4–$75.7\%$ vs. 87.6–$90.1\%$ for ACEIs/ARBs).
## 3.2. Changes in Heart Rate by the 3-Month Screening Period and Long-Term Outcomes
The primary outcome was the composite of HHF and cardiovascular death. The secondary outcomes were all-cause death, cardiovascular death, and HHF. The occurrences of the outcomes in each of the heart rate reduction groups are illustrated in Supplemental Table S1. According to the unadjusted Model 1, the occurrences of composite events increased significantly from the 10- to 19-bpm decrease group to the >10-bpm increase group (p for linear trend < 0.001, Model 1 in Table 3). The HHF also exhibited benefits among the patients’ whose heart rates decreased by ≥20 bpm (p for linear trend < 0.001). With adjustment for all the covariates except heart failure medications taken within 3 months of discharge, the model revealed significant dose–response relationships between heart rate reduction and the four outcomes of interest. The results indicate that smaller decreases in heart rates from discharge to 3-month screening period were associated with less favorable prognoses (a higher risk of all outcomes; p for linear trend < 0.05, Model 2 in Table 3). The results remained unchanged when we adjusted for heart failure medications taken within 3 months of discharge (p for linear trend < 0.05, Model 3 in Table 3).
The adjusted (fitted) survival rates of the patients are illustrated in Figure 2A–D. The possibility of a nonlinear relationship between heart rate reduction and risk of outcomes was further explored using the restricted cubic spline model. The results indicate that the relationship between heart rate reduction and risk of outcomes was linear p for nonlinearity > 0.2, Figure 3A–D). We also evaluated the association between heart rate at the 3-month screening period and risk of outcomes (Supplemental Tables S2–S4). Unsurprisingly, a higher heart rate was significantly associated with less favorable outcomes.
## 4. Discussion
We analyzed the long-term outcomes of patients with heart failure requiring hospitalization whose heart rates changed by various degrees during the study period. The results of this study indicate that optimal heart rate control can help patients with HFrEF avoid cardiovascular death, HHF, and all-cause mortality in the long term.
Our study demonstrated that heart rate reduction strategies may influence the long-term outcomes of patients with HFrEF. The patients whose heart rates decreased by ≥20 bpm after discharge (relative to their baseline heart rate at admission) had significantly more favorable prognoses. The results were consistent after we adjusted for the patients’ baseline characteristics and heart failure medications. Heart rate has often served as a monitoring target or predictive factor in studies on heart failure treatment [12]. A higher heart rate may indicate a more unstable condition. Analyses of data from European registries have revealed that patients have elevated heart rates when experiencing acute heart failure requiring admission [19,20]. However, the prognostic value of heart rate in acute heart failure remains controversial. One trial that enrolled patients hospitalized for acute heart failure identified baseline heart rate as a predictive factor for short-term adverse events [21]; however, Bertomeu-Gonzalez et al. observed that higher sinus rhythm heart rates at admission were not significantly associated with mortality [22]. Studies on the results of the Efficacy of Vasopressin Antagonism in Heart Failure Outcome Study with Tolvaptan (EVEREST) trial revealed that heart rate at admission is not correlated with long-term all-cause mortality in patients with HFrEF in sinus rhythm [20,23]. A higher baseline heart rate may be an indicator of sympathetic overactivity, greater oxygen consumption, a lower myocardial coronary perfusion time, and endothelial inflammation [7,24]. Nevertheless, previous literature has suggested that baseline heart rate alone is an insufficient prognostic indicator for patients with heart failure.
Kurgansky et al. enrolled 51,194 patients with HFrEF with an LVEF of ≤$35\%$ in sinus rhythm from the US Veterans Affairs healthcare system. They discovered that a higher heart rate, both at the time of diagnosis and during follow-up, was strongly associated with an increased risk of adverse outcomes, [25] independent of the use of beta blockers. However, the results of our study indicate that the change between follow-up and baseline heart rate is more important. Our study differed in some respects from the large cohort study of Kurgansky et al. First, we enrolled patients hospitalized for HFrEF; therefore, the cardiovascular symptoms experienced by the patients may have been more severe. The higher MRA and loop diuretic use rates in our study also indicated the severity of patients with decompensated HFrEF. In addition, we enrolled patients with basal heart rates of ≥70 bpm, and excluded those with atrial fibrillation or atrial flutter. Another study conducted by Kotecha et al. revealed that using ß-blockers reduces mortality in patients of sinus rhythm with heart failure, irrespective of resting heart rate. Patients with heart rate <70 bpm were also enrolled in this meta-analysis [26]. Similarly to Kurgansky’s research, a higher resting heart rate at baseline and during follow-up increases mortality; however, patients without beta-blocker treatment experienced higher cardiac events. Proper treatment of heart rate for patients with heart failure of sinus rhythm could be beneficial. Our study also directed to the necessity of heart rate control. The beta-blocker usage rate at 3 months was highest in the ≥30-beats-per-minute decrease group, revealing a better long-term prognosis. However, the mean baseline heart rate of the ≥30-beats-per-minute decrease group was significantly higher than the mean across all the groups (113.9 bpm, $p \leq 0.001$). This group had more favorable long-term prognoses, including lower rates of mortality and HHF. The results suggest that the heart rate decreases in the 3 months after they began treatment was more important than the baseline heart rate of a patient with HFrEF. The benefits of heart rate reduction remained significant, even after adjustment for baseline heart rate, age, ejection fraction, heart failure medications, and other covariates.
Heart rate control has been used as a treatment modality for heart failure for decades. As the standard treatment, beta blockers lower a patient’s heart rate, improve their sympathetic tone, reduce myocardial oxygen consumption, and control arrhythmia, resulting in more favorable clinical prognoses [13]. The beneficial effects of beta blockers strongly depend on their heart rate-reducing properties [27,28]. Ivabradine can be used to further reduce the heart rates of patients with HFrEF with sinus rhythm heart rates over 70 bpm, and help such patients achieve more favorable clinical outcomes, including a lower risk of mortality, especially when a patient’s heart rate can be reduced by ≥15 bpm [12,29]. One post hoc analysis of the EVEREST trial revealed that heart rates of ≥70 bpm after discharge are associated with an increased risk of mortality [23]. Nevertheless, heart rate reduction targets have rarely been discussed in the literature. Using our unadjusted models, we determined that a heart rate reduction of ≥20 bpm has significant benefits in terms of preventing the composite outcome of HHF and cardiovascular death. After adjustment for all covariates, the benefits remained significant. The overall mortality rate of the patients whose heart rates decreased by ≥30 bpm was significantly lower than that of the patients whose heart rates decreased by <10 bpm.
Compared with the patients enrolled in a previous study of registry data, [30] the patients in our study received more guideline-directed treatments during the index admission period, including beta blockers (78.1–$86.8\%$), ACEIs/ARBs (83.8–$90.1\%$), and MRAs (34.6–$48.4\%$). During the follow-up period, the medication coverage rates (for beta blockers, ACEIs/ARBs, and MRAs) decreased. ACEIs/ARBs or MRAs may have been discontinued in our study because of hypotension or impaired renal function, since patients were with poor LV systolic function (EF 29.1–$30.6\%$) or impaired renal function (Cr 2.0–2.2 mg/dL, eGFR 58–63). Beta blockers can have negative inotropic effects on cardiovascular hemodynamics, which causes many physicians to hesitate to prescribe or increase the dosage of such medications. Some physicians may change their patients’ prescriptions from beta blockers to other agents or discontinue beta blockers because their patients are intolerant to such medications. Finally, the ≥30-bpm decrease group had the fewest long-term cardiac events, but had the lowest mean LVEF (29.1 ± $7.7\%$, $p \leq 0.001$), highest mean initial heart rate (113.9 ± 18.0 bpm, $p \leq 0.001$), longest mean hospital and ICU stays, and highest incidence of shock events during the index admission period. These patients also had higher coverage rates of guideline-directed medications, including ACEIs/ARBs, beta blockers, ivabradine, and MRAs, during the follow-up period. The better guideline-directed medications coverage rate may be another reason for why this group achieved more favorable outcomes than did the other groups. However, after adjustment for all the covariates, including heart failure medications, greater heart rate reductions were still significantly associated with more favorable outcomes, including lower rates of overall mortality, and a lower incidence in the composite outcome of HHF and cardiovascular death. Our results are similar to those of a study by Hamill et al. that indicated that time-updated heart rates are more strongly related with cardiovascular outcomes than are baseline heart rates [31]. In the present study, only $20\%$ of the patients (1062 of the 5236) had heart rates of <70 bpm at the 3-month screening period, indicating that heart rate management is often overlooked in the treatment of patients with chronic stable heart failure. Our study highlights the need to draw attention to this problem in the medical community, and to encourage early adoption of heart rate-lowering treatment strategies.
## 5. Limitations
Although this study provides key insights into the long-term clinical outcomes of heart rate control in patients with heart failure after hospitalization, it has some limitations. Firstly, because of the retrospective nature of this study, the different heart rate groups may have had inherent differences. The retrospective design also limited our ability to enroll patients randomly, and may have caused selection bias. Patients’ underlying conditions could have also altered the heart rate, including infection, inflammation, bleeding, or sepsis. Therefore, in our analysis, we adjusted for all the available covariates that may have been related to the outcomes. Secondly, heart rate was a key parameter in this study; however, data related to daily variations in the patients’ heart rates during follow-up were not collected. Heart rate from the in-hospital Holter devices would perhaps have been more reflective of the actual state. However, patients admitted with decompensated HFrEF seldom received Holter for heart rate recording in daily practice. This is also the limitation of the real-world retrospective analysis. Furthermore, the heart rate at admission was the condition before adequate and proper treatment. We recorded the heart rate upon admission as the baseline to compare; however, it could have been overestimated. Thirdly, undertaking physical activity and rehabilitation programs after acute exacerbations of heart failure may strongly affect a patient’s prognosis; however, information on the patients’ daily physical activity habits or rehabilitation statuses were unavailable in our database. Furthermore, this study only included patients in sinus rhythm; therefore, the effect of heart rate control on patients with atrial fibrillation still warrants further investigation. Finally, medication noncompliance may have occurred, and the information we obtained on the drugs prescribed to the patients may not have reflected the patients’ actual use of the drugs.
## 6. Conclusions
In this study, greater reductions in heart rate from discharge until the 3-month screening period were associated with a lower incidence of cardiovascular death, HHF, and all-cause mortality among patients discharged after hospitalization for decompensated HFrEF. Researchers should comprehensively evaluate guideline-directed therapies to determine which is most effective in helping patients achieve a target heart rate reduction and, in turn, more favorable long-term prognoses.
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title: Ketogenic Diet Applied in Weight Reduction of Overweight and Obese Individuals
with Progress Prediction by Use of the Modified Wishnofsky Equation
authors:
- Gordana Markovikj
- Vesna Knights
- Jasenka Gajdoš Kljusurić
journal: Nutrients
year: 2023
pmcid: PMC9968058
doi: 10.3390/nu15040927
license: CC BY 4.0
---
# Ketogenic Diet Applied in Weight Reduction of Overweight and Obese Individuals with Progress Prediction by Use of the Modified Wishnofsky Equation
## Abstract
Ketogenic diet is often used as diet therapy for certain diseases, among other things, its positive effect related to weight loss is highlighted. Precisely because of the suggestion that KD can help with weight loss, visceral obesity, and appetite control, 100 respondents joined the weight loss program (of which $31\%$ were men and $69\%$ were women). The aforementioned respondents were interviewed in order to determine their eating habits, the amount of food consumed, and the time when they consume meals. Basic anthropometric data (body height, body mass, chest, waist, hips, biceps, and thigh circumferences) were also collected, in order to be able to monitor their progress during the different phases of the ketogenic diet. Important information is the expected body mass during the time frame of a certain keto diet phase. This information is important for the nutritionist, medical doctor, as well as for the participant in the reduced diet program; therefore, the model was developed that modified the original equation according to Wishnofsky. The results show that women lost an average of 22.7 kg (average number of days in the program 79.5), and for men the average weight loss was slightly higher, 29.7 kg (with an average of 76.8 days in the program). The prediction of expected body mass by the modified Wishnofsky’s equation was extremely well aligned with the experimental values, as shown by the Bland-Altman graph (bias for women 0.021 kg and −0.697 kg for men) and the coefficient of determination of 0.9903. The modification of the Wishnofsky equation further shed light on the importance of controlled energy reduction during the dietetic options of the ketogenic diet.
## 1. Introduction
In recent years, obesity became a serious global health crisis with prevalence increasing nearly threefold from 1975 to 2016 [1]. Research indicates the connection between obesity and numerous diseases and health complications, such as cardiovascular diseases, various types of cancer, type 2 diabetes, hypertension, polycystic ovary syndrome (PCOS), and many others [2,3]. It is important to emphasize that obesity can be prevented by establishing a balanced diet, adequate physical activity, and changes in behaviour and lifestyle [4]. Understanding the principles of energy balance is crucial [5] in approaching the global problem of the western countries: obesity. The concept of energy balance is based on the law of conservation of energy (energy conservation law: energy state of the organism = entered energy–expended energy), which states that energy cannot disappear or be created from nothing, but can only change its forms [6]. The source of energy in human diet are foods and drinks, with the main energy donors: carbohydrates, proteins, fats, and alcohol and the energy consumption varies throughout the day, but also throughout the lifespan [7].
Our organism strives for a state of energy balance and possesses regulatory mechanisms for this purpose. Regulation implies a complex physiological control system that includes neuronal and hormonal signals from the gastrointestinal tract, pancreas, and adipose tissue that reach the hypothalamus and the autonomic nervous system that innervates muscles, organs, and adipose tissue [5]. It was proven that this integrated regulatory system has stronger protection mechanisms for the loss of body mass than for the prevention of excess energy accumulation, and therefore there is a greater chance for the success of increasing body mass than reducing it [8]. The reduction in body mass is the result of a negative energy balance, i.e., increased energy consumption compared to intake [6]; however, sole reduction in energy intake does not result in continuous (infinite) and proportional loss of body mass. Reduction requires temporary changes in diet and physical activity, while long-term maintenance requires permanent changes, which seems to be more difficult [9] because studies show that 35 to $80\%$ of individuals, who reduced at least $10\%$ of their initial body mass, fail to maintain the reduced body mass for more than a year [10].
As successful reduction in body mass is classified, intentional loss of at least $10\%$ of the original body mass is maintained at that level for at least one year. The criterion of $10\%$ was set because already then the risk of diabetes and cardiovascular diseases was significantly reduced [11]. So, with the aim of a better understanding of an observed problem, models are developed, among which mathematical models were developed to try to understand the non-linearity of body mass loss during energy reduction as one of approaches in dealing with obesity. Numerous mathematical models were designed for the purpose of predicting body mass loss, which differ from each other according to the concept of how energy is stored and consumed [12]. The first such model, which combined all the knowledge about calories and energy metabolism developed for predicting the expected body mass based on the timeframe of energy intake reduction is the Wishnofski model from 1958 [13]. Doctor Max Wishnofsky researched energy from food, how it is stored in the body, and by what amount it is necessary to reduce energy intake in order to lose 1 kg of body mass [14]. He designed a regression model that was supposed to serve as a universal measure for assessing body mass change based on an energy intake reduction in a known time frame and with a caloric equivalent of one pound of lost or gained body mass of 3500 kcal (for 1 kg–approximately 7700 kcal) [12]:[1]Weight loss [lb]=Es[kcal/day]·t [days]3500 [kcallb] where: Es—imposed daily deficit in energy stores (reduced energy intake or increased exercise generated energy output), [kcal/day]; t—duration of the diet [days].
Studies show that different diet patterns influence diet changes and maintain reduced body weight [2,15], and one of them is the ketogenic diet, which is characterized by a significant reduced intake of carbohydrates (<30 g/day) and standard protein intake (1.2–1.5 g/kg of ideal body weight or 1.0–1.2 g/kg of fat free mass) [16]. This diet is also often used in diet therapy of obesity, type 2 diabetes mellitus, migraines, polycystic ovary syndrome, and even epilepsy [17,18,19,20,21,22]. There are several types of eating patterns within the keto diet. A standard ketogenic diet implies that fats make up $70\%$ of the daily energy intake (DEI), proteins $20\%$, and carbohydrates only $10\%$. In addition to the standard one, the cyclic ketogenic diet includes periods of carbohydrate compensation (after every 5 days the diet is followed by 2 days with increased carbohydrate intake), a targeted ketogenic diet that allows the addition of carbohydrates during periods of intense physical activity (25 to 50 g half an hour before training), and a high-protein ketogenic diet that is similar to the standard diet, but the macronutrient intake ratio is changed (fats: proteins: carbohydrates = 60:35:5) [23].
According to all of the above, the aim of this paper is to demonstrate the usefulness of the Wishnofsky equation based on collected data of people on a ketogenic diet. Several requirements were studied, the most important of which is the accuracy of predicting the course of body mass loss over a certain period of time, as well as different phases during the energy restriction and macronutrient intake based on the ketogenic diet guidelines.
## 2. Materials and Methods
In the study were included 100 healthy adults ($31\%$ of them are males) from Skopje, North Macedonia, enrolled in the program of weight reduction by following keto diet principles. Their anthropometric data (weight, height, circumferences of: chest, waist (two places: (i) narrowest part and (ii) at the navel region), hips, biceps, and thighs), diet habits before the diet, and some basic information related to their food intake were collected in an individual interview with a nutritionist. During the interview were collected such data as frequency of consumption of some nutrition dense food (fruit and vegetables) as well as caloric food (sweets, salty snacks, seeds, and nuts) and beverages (carbonated drinks vs water). The time of meal consumption was also recorded. The measurements were collected since April 2022. All respondents signed the agreement that their data can be used exclusively for scientific purposes, and the principles of the GDPR were respected.
Observed anthropometric parameters of the participants were collected following the recommendation of Casadei and Kiel [24] and they are given in Table 1.
In addition to the anthropometric parameters, for each subject, anamnesis was taken about the basic state of health, as well as the number and type of meals and the time of consumption. At the first medical examination, the subjects’ body mass, body height, and circumferences of arm, leg, waist, and hips were measured. The initial body mass index (BMI) was expressed as the ratio of the body mass to the square of the body height, and the target body mass for each subject was obtained in the range for the targeted normal BMI (20–25 kg/m2).
At each follow-up examination, subjects’ body mass and circumference were measured to monitor progress. In the case of adequate progress, the allowed energy intake is increased, i.e., the person moves to the next phase of the ketogenic diet. However, if at some point there is a stagnation of progress or an increase in body mass, the subjects are returned to the previous phase and their energy intake is reduced.
The Wishnofsky equation was used because it depends on the phase of the body mass reduction process, and was modified because during the ketogenic diet were included seven different phases (Table 2) and the average energy nutrient composition for the last phase is given in the supplementary Table S1 for menus created by a dietitian and medical doctor.
According to the energy intake of different phases, the Wishnofsky equation (Equation [1]) was modified as follows:[2]W(t)=W0−0.454∗ΔEB∗t3500 [3]Wtj=Wtj−1−0.454∗EBi∗tj3500 where W0—initial body mass [kg]; W(t)—expected body mass [kg] after t days where the energy intake was reduced for ∆EB (reduced daily energy intake [kcal/day] compared to the required one); Wtj−1—initial body mass for the new ketogenic diet phase ($i = 1$, …, 7), the ketogenic diet phase (i) can be repeated several times ($j = 1$, …, n) and the last one ends when Wtj = Wd (desired body mass). When calculating EBi, the mean values of the energy range of the different phases of the ketogenic diet were used (Table 2).
The flow chart (Figure 1) presents the ketogenic diet implementation process from the initial body mass (W0) to the desired one (Wd). Patients start with 800 kcal in phase I until they reach $48\%$ of the difference between initial body mass (W0) and the desired (Wd). After this phase, the energy intake is increased to 900 kcal (Phase IIa). By reaching $64\%$ of the difference between initial body mass (W0) and the desired one (Wd), the daily energy intake is upgraded to 1000 kcal (IIb phase). In phase III, the patient reached less than $80\%$ of the difference between W0 and Wd, and the daily calorie intake is than 1150 kcal. In phase IVa, the patient reached less than $85\%$ of the difference (W0–Wd) with 1300 kcal per day. Phase IVb, starts when the patient reaches $90\%$ of the difference between initial body mass and desired (W0–Wd) with 1400 kcal per day. The last phase (phase V) increases the energy intake to 1500 kcal when the achieved body mass is less the $5\%$ from the desired one.
As variables are indicated values for body masses that were recorded for the patient after each examination at a certain diet phase, Wtj, j is the number of check controls, while other primary parameters are: W0 as the initial body weight, Wd as the desired body weight, and previously mentioned EB as intake of energy during the day.
Patients who are over-weighted, but still not obese, and where the difference between the initial body mass and the desired one (W0–Wd) is less than $48\%$, the diet is directed immediately into the second phase of the diet ($i = 2$: Phase IIa). If this is not the case, the diet plan will start with the first phase. The third phase is approached when the patient reaches $80\%$ of the desired weight loss. In the remaining stages, the patient loses the remaining $20\%$ of body mass.
In addition to all measurements, the expected body mass during each examination was also calculated using the Wishnofsky equation (based on the body mass recorded at the previous examination, the number of days since the previous examination, and the energy intake in that phase). None of three variables used in the calculation are a constant; body mass differs each time, and energy intake also changes analogously, i.e., the phase of the ketogenic diet. The number of days since the previous examination is different for each person.
At the end of the research, the data were statistically processed and the actual situation and progress were compared with the prediction based on the Wishnofsky equation.
All calculations were conducted by use of MS Excel. Calculated were the (i) minimal and maximal values in the observed data set, (ii) standard measure of central tendency (mean, mode), and (iii) standard deviation (SD) as a measure of dispersion. Relative frequencies (as percentage) were used in the display of results related to the eating habits of people involved in the weight loss program. Box-whiskers plot was used to show the progress of body mass loss and the reduced body mass index. The Bland–Altman chart is used to show the effectiveness of predicting body mass using the modified Wishnofsky equation. A simple linear regression was used to show the agreement of body mass data in a certain phase of the ketogenic diet with the exact body mass measured during the regular examination.
## 3. Results
During the first examination, an interview was conducted (with each subject) in which data were recorded on the frequency of overweight and/or obesity in the family (Figure 2), their eating habits, i.e., the frequency and time of eating (Table 3), and certain types of food (Table 4).
From the prevalence of obesity in the family, differences in the answers of the male and female population are visible; however, research by [25] Sattler and associates [2018] shows that it is weight-based stigmatization with motivation to exercise and physical activity in overweight individuals in connection with different genders.
Information on the frequency of consumption of certain foods (sweet, salty, and seeds) and drinks was a source of information on the quality of eating habits (Table 3). Only one third of female and $48.39\%$ female subjects consumed non or less than 50 g of sweets per week, while chips (including other salty snacks) were consumed by over $50\%$ of subjects, regardless the gender is consuming in amounts less than 50 g/week. Unfortunately, it is a devastating fact that the amount of fruit and vegetables consumed during the week is limited to small amounts, indicating that energy-rich food, with low nutritional density, dominates their diet. Higher intake of fruits and vegetables increased weight loss [26]. In the investigated group, the frequency of consuming vegetables was significantly lower, although it can be consumed as a side dish, salad, etc. The following finding is related with the regional consumer habits, including high consumption of nuts and seeds. In the conversation during the interview, it was clear that seeds and nuts are consumed between meals in uncontrolled amounts, although the average caloric contribution in 100 g is in the range of 400–600 kcal [27].
Consumption of beverages shows an exceptional representation of carbonated beverages compared to water, which is consumed most often in the amount of 1–2 L in the male population ($38.71\%$). Carbonated mineral water is also included in CO2 beverages. Over-weighted and obese individuals have higher demand on fluid intake, and improved hydration is a commonly used strategy by nutritionists to prevent overeating with the goal of promoting a healthy weight among patients [28]. It is a worrying fact that almost $56.52\%$ of women and even $74.19\%$ of men in the group of respondents do not consume water on a daily basis.
However, it is not only the combination of poor nutrition that is related to the problem of excessive body weight or obesity of the respondents, there is also the number of meals and their distribution during the day (Table 4).
In order to additionally determine the frequency of the most common number of meals in the respondents’ answers, the mode value was also calculated. Female subjects have more meals (mode value is 3 vs. 2 of the male population, respectively). Late meals dominate (second meal at around 4 pm) while the first meal is extremely late (regardless of gender, around 10 or 11 am) and a lot of them have late night meals (around midnight).
The participants reduced their daily energy intake, guided by the ketogenic diet principles. Successful progress of the subjects can be seen in Table 5.
Such an approach in body weight reductions requires numerous examinations (6.8 for females and 8 for male subjects) and a long period of time in the program (79.5 and 76.8 for female and male subjects, respectively).
The reduction in all measured circumferences is dominantly in the waist and hip region for both genders (more than 20 cm reduction).
Although the average body mass that was planned and achieved differs for both genders (Table 5), the success can be seen in Figure 3, indicating the achievement in body mass loss, as well as for the decrease in the body mass index. The first impression is that the male subjects failed to achieve the expected body mass index of normal nutrition. However, the male population more actively accepted physical activity, especially exercise, and therefore their body mass index is slightly higher due to an increase in muscle mass.
An accurate perception of the expected body weight after a certain time of reduction in energy intake is necessary for people who are on a weight loss program, but also for nutritionists who lead the program in order to design the appropriate next step of the weight management program [29]. Therefore, last results are devoted to the efficiency of the modified Wishnofsky equation in predicting expected body mass after a certain phase of their diet. It is suggested to use correlations and regressions to assess the agreement between the two quantitative measurement methods, as in our case with the experimental values of body mass, and the predicted one by use of modified equation by Wishnofsky. Correlation will give an insight into the relationship between one variable and another, but will not indicate differences, and thus is not an ideal method for assessing comparability between methods. An alternative is the Bland–Altman graph, which as a basis for quantifying the agreement between two quantitative measurements offers the study of the relationship of the mean difference in the limits of agreement. The Bland–Altman graph defines intervals of agreement, and acceptable limits must be defined in advance, based on the set goals [30]. Our agreement is presented in Figure 4. For both genders, the bias values are very close to zero (−0.697 kg and 0.021 kg) for male and female measures, respectively. The error is 0.0614 in prediction of male body mass and 0.058 in predicting female body mass of a certain phase of the ketogenic diet. A certain proportion of outliers (Figure 4., dots outside the area of limits of agreement (±1.96 × SD)) is visible, which is dominantly the result of non-adherence to the principles of the keto diet, and precisely the difference between the expected body mass (>$5\%$) vs. the measured body mass during the control examination, which is the indication of relapse. In the supplement material, Figure S1 shows the repetition of ketogenic diet phases for one relapsed participant who started the program from the beginning for three times. The disproportion between the expected body mass (calculated by the modified Wishnofsky’s equation) and the measured mass is evident, and greater than ±$5\%$. Here, it must be emphasized that none of the input data of the respondents were taken as an outlier (precisely the extreme values, such as the body weight of 237 kg of a male person) that influence the increase in the error. For this reason, the regression line of the experimental values of body masses and those obtained by the modified model is shown (Figure 5).
The last efficient test is presented with the regression line of the body masses measured during the examinations and those predicted by the use of the modified equation of Wishnofsky (Figure 5), and it is clear that, even with outliers in the data set, there is still an extremely strong connection between the observed data (R2 = 0.9903).
## 4. Discussion
In order to avoid the yo-yo effect and preserve weight loss progress, Wing and Phelan [31] defined six key strategies that should be followed: (i) increased level of physical activity (1 h/day), (ii) change in eating habits in the context of avoiding energy-rich foods and foods rich in fats, (iii) regular breakfast (latest in 2 h after waking up), (iv) regular monitoring of body mass, (v) constant eating pattern, and (vi) reacting to minor mistakes by correcting them in a timely manner so that they do not cause a greater return of lost body mass and causing a negative impact on the weight loss progress. Theoretically, thebasic principle of losing weight is quite simple: spend more energy than you take in. However, while the fact is that we have to reduce our calorie intake, it is important to know the exact source and amount of calories eaten, and whether the body can be influenced in the tendency to lose and later to restore the balance. The primary “fuel” of the human body is glucose, i.e., carbohydrates. Therefore, when glucose stores are low, as is the case during a ketogenic diet, the central nervous system must find an alternative source of energy [4]. Then, the energy source becomes ketone bodies–acetoacetate, beta-hydroxybutyrate, and acetone. These molecules are the product of ketogenesis that takes place in the mitochondrial matrix in the liver. Under normal conditions, they are found in the body in very low concentrations (<0.3 mmol/L). Given that they are similar in structure to glucose, they have the ability to use a glucose transporter to cross the blood–brain barrier to be used as an energy source when they reach a concentration of 4 mmol/L in the body. The described state of elevated levels of ketone bodies in the body is called “ketosis” [32].
It is believed that this mechanism forces the body, due to the lack of glucose, i.e., carbohydrates in the diet, to consume fat reserves and thereby reduce the amount of fat tissue and total body mass. In addition, Ketone bodies serve as an alternative energy source for brain metabolism [33]. Bypassing the traditional ways of releasing energy through glycolysis in favour of using ketone bodies has a significant effect on the body, and although the entire mechanism is not fully understood, it is clear that bypassing the metabolism of carbohydrates in the brain can also lead to positive health effects, such as a reduced frequency of epileptic seizures [5,34].
The ketogenic diet guidelines show that the basis of the diet should be fats. Unsaturated fatty acids are allowed, such as nuts, seeds, avocado, tofu, and olive oil, but a higher intake of saturated fatty acids is emphasized, such as butter, animal fat, coconut oil, butter, etc. Proteins are the next macronutrient when considering the share of daily energy intake. There are no big differences in the recommendations of protein sources, but poultry meat, fish, and red meat are recommended in larger quantities than eggs, cheese and milk, and dairy products. In the end, carbohydrates remain [16,23]. As can be seen in our investigated group, the (i) time of consumption and (ii) the number of meals are also important issues related to being overweight. A study conducted among Japanese women showed that those who consumed late dinners or bedtime snacks were more likely to skip breakfast, which explains the late first meal of the investigated subjects. The same study concluded that having a late dinner or bedtime snack is associated with a higher probability of being overweight/obesity [35]. Low-carb vegetables are allowed, i.e., green leafy vegetables, broccoli, cauliflower, Brussels sprouts, asparagus, peppers, onions, garlic, cucumber, mushrooms, etc. In addition to vegetables, fruits contain a high proportion of carbohydrates, and therefore only berries are recommended [36]. Extensive literature overview in the meta-analysis conducted by Arnotti and Bamber [26] investigated the fruit and vegetable consumption in overweight or obese individuals (3719 participants), and it was shown that the effect was large (−2.81 kg; $p \leq 0.001$). Lipid metabolism, which is a key factor in planning body mass reduction, is an extremely complex process, and models are available that simulate its development with the aim of understanding its biological processes [37]. The models can also be used to optimize and define sustainable diet indicators where the ketogenic diet shows success [38,39]. In order to help both nutritionists and people who are on a weight loss program, a modified model of weight gain from the Wishnofsky equation was proposed. Having a perception of what to expect after a certain period of reduced energy intake is more than encouraging for participants in the weight loss program [25]. Decades after Wishnofsky’s equations, different mathematical models were created for predicting expected body mass in a certain time frame based on the law of conservation of energy, and those models differ according to differences in the understanding of what energy consumption entails and what the energy state of the organism entails [40]. The main requirement of a model is its simplicity and acceptable error [37,38,39]. Our results show that the prediction of expected body mass during the reduction keto diet using the modified Wishnofsky equation is extremely well aligned with the actual progress of people in the weight loss program, regardless of gender. The modification of the equation that includes changes in the phases of energy intake during the ketogenic diet is important because it is not a linear relation of body mass loss, but a non-linear process that is taken into account in this way. An extremely important factor is the time (t) of a certain phase of the diet in which a person establishes control over eating habits and continues with a further constant decrease in body weight. Deviations greater than $5.8\%$ in women and $6.1\%$ in men are an indicator of non-adherence to the basic principles of the diet, and are a corrective factor for the person on a diet and their nutritionist, because one of the goals is certainly the prevention of the “yo-yo” effect in the respondents. Thus, the so-called confidence interval values in the Bland–Altman graph will indicate the above and that the modified Wishnofsky equation did not successfully predict the expected body mass. This effect was confirmed in his research by Thomas and colleagues [13], who state that the use of the Wishnofsky’s equation is a rule that is easy to apply, but can lead to an error in predicting body mass loss; however, in the absence of simple and most understandable solutions, it is also an acceptable smaller error [39] in the expected value of body mass during the weight loss program.
As with each method, this model has also a disadvantage: it does not explain the metabolic adaptations that occur in the body, and it also does not take physical activity as an input in the calculations. The average BMI for the male population was slightly higher than 25 kg/m2, but according to the findings of Weber and co-worker [21], ketogenic diet helped in preserving muscle mass in patients with cancer, and the study of Pasiakos and coworkers [41] conducted on adults varying levels of dietary protein on body composition during energy deficit concluded that consuming dietary protein at levels exceeding recommendations may protect fat-free mass during short-term weight loss. The physical activity in obese people [25] will also affect the increase in muscle mass and consequently affect the BMI, although BMI does not distinguish muscle and fat mass. The focus is exclusively on the energy intake and the time frame of its reduction. Given the limited time period of this research, future research should include physical activity as well as the energy intake during the stabilization of energy intake after the restriction, because the potential of the model was confirmed also for those who had phases in which they returned to increased and inappropriate energy intake.
## 5. Conclusions
The implementation of supervised body weight loss, with the guidelines of the ketogenic diet, is primarily focused on the reduction in carbohydrates and energy. The proportion of body mass loss is dictated by the sequence of phases of the diet, and with medical supervision, the third phase (of 1300 kcal) of the diet occurs after 60–$80\%$ of the target body mass loss (Wt-W0). For the patient, cognition of the flow and duration of the diet itself is extremely important, and it is necessary to use tools such as prediction equations for body mass loss over a certain period of time. Body mass loss in different phases of the ketogenic diet can be effectively predicted by applying the equation by Wishnofsky, which represents a simple mathematical model that relatively accurately predicts the course of body mass change. It does not require a large number of input variables, which makes it useful for clinical practice, as well to monitor the progress and helping in creating an effective program for body weight loss, especially due to the large problem of obesity in the world.
Given that the modified model of Wishnofksy’s equation is proposed for predicting body mass reduction, taking into account that the person adheres to the prescribed guidelines and certain energy intake, the errors that occur are the result of the selection and procedures of the subjects, not the model itself. In this paper, an algorithm for the flow of the phases of the keto diet is generated. Following this algorithm leads to a reliable result of the desired weight. This is a good start for further research, as the next step would be to create a program that generates a variety of food and satisfies this algorithm model.
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|
---
title: Chemical and Biological Review of Endophytic Fungi Associated with Morus sp.
(Moraceae) and In Silico Study of Their Antidiabetic Potential
authors:
- Mohamed M. M. AbdelRazek
- Ahmed M. Elissawy
- Nada M. Mostafa
- Ashaimaa Y. Moussa
- Mohamed A. Elanany
- Mohamed A. Elshanawany
- Abdel Nasser B. Singab
journal: Molecules
year: 2023
pmcid: PMC9968060
doi: 10.3390/molecules28041718
license: CC BY 4.0
---
# Chemical and Biological Review of Endophytic Fungi Associated with Morus sp. (Moraceae) and In Silico Study of Their Antidiabetic Potential
## Abstract
The chronic nature of diabetes mellitus motivates the quest for novel agents to improve its management. The scarcity and prior uncontrolled utilization of medicinal plants have encouraged researchers to seek new sources of promising compounds. Recently, endophytes have presented as eco-friendly leading sources for bioactive metabolites. This article reviewed the endophytic fungi associated with Morus species and their isolated compounds, in addition to the biological activities tested on their extracts and chemical constituents. The relevant literature was collected from the years 2008–2022 from PubMed and Web of Science databases. Notably, no antidiabetic activity was reported for any of the Morus-associated endophytic fungal extracts or their twenty-one previously isolated compounds. This encouraged us to perform an in silico study on the previously isolated compounds to explore their possible antidiabetic potential. Furthermore, pharmacokinetic and dynamic stability studies were performed on these compounds. Upon molecular docking, Colletotrichalactone A [14] showed a promising antidiabetic activity due to the inhibition of the α-amylase local target and the human sodium-glucose cotransporter 2 (hSGT2) systemic target with safe pharmacokinetic features. These results provide an in silico interpretation of the possible anti-diabetic potential of Morus endophytic metabolites, yet further study is required.
## 1. Introduction
Type 2 diabetes mellitus (Type 2 DM) is considered one of the most prevalent metabolic disorders, affecting approximately $90\%$ of diabetic patients [1,2]. Many medicinal plants are used in managing diabetes [3,4]. The advantage of the use of medicinal plants is due to their availability, cost-effectiveness, and higher safety [5,6,7,8]. The extensive and uncontrolled utilization of medicinal plants may add to the ecological burden in terms of overutilization of endangered and rare species and in disturbing the ecological balance [9]. In this context, endophytes associated with medicinal plants present an eco-friendly alternative source of bioactive metabolites, given that endophytes may cross talk with the host medicinal plants in terms of their biosynthetic routes or that they may be the original producers of some active ingredients, or at least may provide the host organisms with extra chemical defense to cope with the surrounding stress conditions [10,11,12,13]. The abundance of endophytic fungi within the host medicinal plants may be associated with the pharmacological actions linked to the plant part used [14]. For example, endophytic fungal metabolites associated with Syzygium cumini L. showed significant amylase inhibitory activity, which could be utilized in discovering new antidiabetic bioactive molecules [15]. Many fungal metabolites belonging to different classes were evaluated for their antidiabetic activities [16,17,18].
Genus Morus (Moraceae) comprises 17 species and 2 subspecies, distributed among temperate and tropical climates. Morus alba, rubra, and nigra are the most commonly known species [19]. In traditional medicine, the leaves, roots, bark, stems, and fruits of Morus plants are used to treat rheumatism, coughs, and inflammation. The main key bioactive chemical constituents of *Morus genus* plants have been reported as flavonoids, benzofurans, stilbenes, and Diels–Alder adducts that exhibit multiple bioactivities [20]. Moreover, *Morus* genera plants reported free radical scavenging, hypolipidemic, antioxidant, antibacterial, antiviral, and anti-inflammatory activities and were used as astringents and emollients [21]. Morus plants showed in vivo and in vitro antidiabetic potential with few side effects by inhibiting α-glucosidase in normal rats [22,23,24,25]. The antioxidant properties demonstrated by many plants participated at least in part in their promising bioactivities [26,27]. Metabolites such as rutin and quercetin-3-O-β-D-glucoside isolated from M. alba improved glucose uptake and have a positive effect on lipid accumulation in adipocytes for the management of Type 2 DM [28]. Four compounds, namely Morusalone A-D, were isolated from M. alba and have a mixed biosynthetic origin of polyketide, shikimic acid, and terpenoid. Their structure is close to endophytic fungi polyketides and showed potent protein tyrosine phosphatase 1B inhibitory activity (PTP1B), which is involved in the negative regulation of insulin and regulation of type 2 DM [29]. M. nigra revealed twelve phenolic compounds of α-glucosidase; the inhibitory activities of nigranol B and sanggenol H showed the most potent activity [28,30]. The major components of total flavonoids of M. nigra in in vivo study showed a reduction un prediabetes progressing to type 2 DM [31]. The antidiabetic in silico studies on Morus plants reported the local α-glucosidase inhibitory activities of prenylated flavone; Kuwanon C, 2-arylbenzofuran flavonoids; Moracin M and Stilbenoids; and Oxyresveratrol [32]. Ficus is a large important genus in the family Moraceae [33]. Ficus religiosa was associated with endophytic fungi that showed α-amylase enzyme inhibitory activity while the most potent fungal extract was *Cochliobolus lunatus* followed by *Abdopus aculeatus* and Penicillium sp. [ 34].
In the course of our interest in the research on the bioactive metabolites from endophytic fungi, we herein present a summarized review of the fungal endophytes associated with different species of Morus (Moraceae), focusing on the isolated 2ry metabolites and covering the period from 2008 to 2022. Since the antidiabetic role of natural products such as M. alba was reported mainly through local enzymatic inhibition of the α-glucosidase enzyme [35,36], no antidiabetic studies were reported on Morus-associated endophytes, thus encouraging us to perform in-silico molecular analysis to demarcate the activity of the previously isolated endophytic fungal metabolites associated with Morus species as prospective antidiabetic agents. The study was expanded to explore the antidiabetic activity through the local targets α amylase and α/β glucosidase [32,37,38,39] in addition to the systematic antidiabetic prospects of one of the emerging systemic targets for Type 2 DM, which is hSGT2, responsible for glucose reabsorption in kidneys [40,41]. The selection of hSGT2 was due to its structural similarity to several isolated compounds from Sophora flavescens with antidiabetic activity such as Sophoraflavanone G (A) and Kurarinone (B), which possessed IC50 of 4.10 and 1.70 M, respectively, on hSGT2, as well as known inhibitors Canagligfozin (C) and Empagliflozin (D) [42,43].
## 2.1. Endophytic Fungi Associated with Morus Species
Reviewing the literature as shown in (Figure 1 and Figure 2), 115 endophytic fungal isolates were reported from *Morus alba* leaf, stem, and root tissues; 95 ($82.6\%$) isolates were identified, and 20 ($17.4\%$) isolates were reported as unidentified. The most abundant identified genera of isolates reported from M. alba were 25 ($26.3\%$) isolates of Fusarium and 16 ($16.8\%$) isolates of *Alternaria* genera followed by a medium abundance of Phoma ($8.4\%$), Colletotrichum ($7.4\%$), Aspergillus ($6.3\%$), and 5 ($5.3\%$) isolates for each genus, Macrophomina, Penicillium, and Scytalidium [44,45,46,47,48,49,50], while one endophytic fungal strain was reported for each *Morus* genera, Botryosphaeria sp. for M. nigra [51] and Phomopsis sp. for M. cathayana [52]. However, M. macroura was reported to be associated with seven undefined endophytic fungal strains [19]. All endophytic fungal strains associated with *Morus* genera were reported from different locations worldwide: South Korea, China, Indonesia, Brazil, Pakistan, and the Czech Republic.
## 2.2. Chemistry of Endophytic Fungal Metabolites Associated with Morus Species
A few works have reported the isolation of metabolites from endophytic fungi associated with *Morus* genera (Table 1 and Figure 3). A new anthraquinone, 1,3-dihydroxy-2,8-dimethoxy-6-methyl anthraquinone [1], was reported from the ethyl acetate extract (EtOAc) of Colletotrichum sp. JS-0367, isolated from the leaves of M. alba L. Moreover, three known anthraquinones, 1-hydroxy-2,3,8- trimethoxy-6-methyl anthraquinone [2], 1,2-dihydroxy-3,8- dimethoxy-6-methyl anthraquinone [3], Evariquinone [4] [44] and three quinone derivatives, epoxyquinophomopsin [5] and epoxyquinophomopsins A [6] and B [7], were isolated from the EtOAc extract of endophytic fungus Phomopsis sp. AZ1a from M. cathayana [52,53]. A new γ-pyrone, 6-((9‵R,11‵R, E)-13-hydroxy-9,11-dimethyloct-7-en-7-yl)-2-methoxy-4H-pyran-4-one [8] and a known γ-pyrone, fusarester D [9], were isolated from the EtOAc extract of Fusarium Solani JS-0169, isolated from the leaves of M. alba L. in addition to four known naphthoquinones: karuquinone B [10], javanicin [11], solaniol [12], and fusarubin [13] [47]. Three new colletotrichalactones, Colletotrichalactone A [14], Colletotrichalactone B [15], and Colletotrichalactone 3A [16], polyketides with a $\frac{5}{6}$/10-fused ring system, were isolated from the EtOAc extract of Fusarium Solani JS-0169, isolated from the leaves of M. alba L. [46]. A new oxazole-type compound, named macrooxazole E [17], and macrooxazole C [18], macrooxazole A [19], and macrooxazole B [20], in addition to furoic acid, 5-hydroxymethyl-2-furan carboxylic acid [21], were isolated from the EtOAc extract of Phoma sp. JS0228, isolated from the leaves of M. alba L. [48]. Endophytic naphtoquinone derivatives and vanillin derivatives with benzaldehyde, 4-hydroxy-3-methoxy, or 2,5-disubstituted moieties were reported in the inhibitory activities against glucose production [54]. The unusual Colletotrichalactone polyketides with a $\frac{5}{6}$/10-fused ring system and naphthoquinone derivative moieties may be promising targets for antidiabetic potential.
## 2.3.1. Reported Biological Studies on Endophytic Fungal Extracts
A few studies have reported the biological evaluation of the endophytic fungal metabolites associated with *Morus* genera. The endophytic fungi crude EtOAC extracts of Aspergillus sp. A204, Colletotrichum sp. C103, and Penicillium sp. P306 associated with M. alba showed a broader antifungal spectrum [45]. M. alba endophytic fungi EtOAc extracts of Phoma sp. MJ76 and Chaetomium sp. showed inhibition of human immunodeficiency virus-1 (HIV-1) replication using β-galactosidase and p24 antigen in vitro assays on cell lines developed from human cervical epithelial carcinoma (TZM-bl cells) and peripheral blood mononuclear cells (PBMC) [49]. The EtOAC extract of M. nigra endophytic fungus *Botryosphaeria fabicerciana* (MGN23-3) showed antioxidant activity using a DPPH assay and selective antibacterial activity on gram-positive bacteria using an in vitro plate dilution method revealed by determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) [51].
## 2.3.2. Reported Biological Studies on Isolated Endophytic Fungal Metabolites
The isolated endophytic fungal compounds associated with M. alba and M. cathayana reported neuroprotective, antioxidant antimicrobial, antimalarial, glucose inhibitory, hemolytic, and cytotoxic activities as shown in (Table 1). Compounds [1], [4], [11], and [13] revealed protective effects using murine hippocampal HT22 cell death induced by glutamate and strongly attenuated glutamate-mediated apoptotic cell death [44,47]. Compounds [11], [12], [13], [14], [16], [18], and [20] showed anti-proliferative activity while compound [16] showed strong antioxidant power [46,48]. Compounds [11] and [13] showed antibacterial and antimalarial hemolytic activities [56]. Compounds [18] and [20] revealed antibiofilm inhibitory and destructive activities [58]. Naphthoquinones metabolites [11] and [12] presented a glucose inhibitory activity [54]. M. cathayana endophytic fungi, Phomopsis sp., revealed potential tyrosine kinase inhibitory activity of compound [6] [52,53].
## 3.1. Pharmacokinetic Profiling
As shown in (Figure 4 and Table 2), the predicted pharmacokinetic properties of the evaluated compounds revealed their high potential for gastrointestinal (GI) absorption due to their reasonable solubility. Additionally, nearly all compounds lacked permeability to the blood–brain barrier and cytochrome P2D6 (CYP2D6) inhibition, thus expanding their safety profiles, except compound [9]. In accordance with our analysis, the high absorbability increases the potential for targeting hSGT2. Additionally, this lack of central presence adds to the benefits of these compounds through the elimination of possible side effects owing to central permeability.
## 3.2. Molecular Modelling
Based on the pharmacokinetic results, the antidiabetic potential of the compounds was investigated locally and systematically through screening of action against α amylase, α/β glucosidase enzymes, and human sodium-glucose cotransporter 2 (hSGT2). Autodock Vina successfully performed the docking process of the select compounds in three targets, α amylase (PDBID: 2QV4), β glucosidase enzymes (PDBID: 2XWE), and hSGT2 (PDBID: 7VSI) for screening of their potential in antidiabetic therapy while MOE08 was used for α glucosidase (PDBID: 3A4A) after unsuccessful attempts using Vina. The docking protocol was validated through docking of the co-crystallized ligand in each receptor, followed by comparing the co-crystallized pose and docked pose and calculation of RMSD between them. As shown in (Figure 5), α amylase with co-crystallized acarbose showed an RMSD of 1.22 Å, while α and β glucosidase RMSD was 0.67 and 1.95 Å, respectively. Similarly, empagliflozin, which is co-crystallized in hSGT2, had an RMSD of 1.01 Å.
All compounds demonstrated favorable binding to the three selected targets as evidenced by the obtained negative values of docking scores in kcal/mol in (Table 3). For comparative analysis of the antidiabetic abilities of the evaluated compounds, acarbose was used as a reference for inhibitory activity on α amylase and β of glucosidase, while empagliflozin was used as an hSGT2 reference inhibitor.
## 3.2.1. α Amylase Interaction
Both acarbose and tested compounds demonstrated negative bind scores hinting at the favorable interactions with the enzyme. Acarbose showed the highest affinity with a score of −9.70 kcal/mole, while [14], [3], [4], and [2] demonstrated the highest affinities of −8.80, −8.50, −8.50, and −8.40 kcal/mol, respectively. Upon inspection of 2D interactions, it becomes clear that the hydrophilic nature of acarbose enables it to form multiple hydrogen bonds with several α amylase residues such as Trp59, Tyr62, Gln63, His101, Asn105, Ala106, Val107 Thr163, Arg195, Glu233, and Asp300 (Figure 6). Although the compounds were able to interact with common amino acids such as Trp59, Tyr62, Thr163, Glu233, and Asp300, they were less able due to the more lipophilic characteristics of the compounds. However, the top-scoring compounds compensated for this deficiency through the formation of hydrogen bonds with other amino acids in the binding site, namely, Leu162, Leu165, Asp197, Asp198, and Asp305 (Figure 7 and Figure 8).
## 3.2.2. α and β Glucosidase Infarction
α/β glucosidases contributed to the treatment of type 2 DM by breaking down the glycosidic by the α isoform and the aryl and alkyl glycosides, disaccharides, and small oligosaccharides by the β isoform [32,59]. The binding of acarbose to the α and β isoforms was −8.97 and −8.70 kcal/mol, respectively. Although the compounds showed favorable binding in both cases, the binding was stronger in the β isoform in nearly all instances suggesting a partial preference for β rather than α. The hydrophilic nature of acarbose enables it to form multiple hydrogen bonds with several α glucosidase residues such as Tyr72, Tyr158, Phe178, Arg213, Asp215, Asp242, Gln279, Pro312, His351, Asp352, and Arg442 (Figure 8). Additionally, ionic interactions were observed as well with Tyr158 and Asp242 in addition to one hydrophobic bond with Arg315 (Figure 9). Among the tested compounds, only [20] and [19] were the ones with the closest scores of −6.96 and −6.58 kcal/mole, respectively. Although [20] maintained two similar ionic interactions with Asp215 and Arg462, its less hydrophilic nature only accommodated the formation of a lower number of hydrogen bonds than acarbose, which explains its lower score. This observation becomes more evident upon inspection of the interactions of [19], which has fewer hydrophilic groups capable of the formation of hydrogen bonding (Figure 10 and Figure 11).
On the other hand, the docking results against β glucosidase were more intriguing. [ 15] marginally outperformed acarbose with scores of −9.10 and −8.70 kcal/mol, respectively. Additionally, compounds [14] and [16] attained nearly similar scores, achieving −8.60 and −8.50 kcal/mol, respectively. A closer inspection of the interactions explains why [15] achieved this score. Upon closer inspection, it binds more tightly to β glucosidase, the distance of the hydrogen bonds formed is optimal, ranging from 2.19 to 3.59 Å, and the hydrophobic bond was 3.76 Å with Tyr313. In contrast, acarbose formed hydrogen bonds ranging from 2.71 Å to 4.14 Å. Additionally, the binding of acarbose creates unfavorable binding and steric tension with Trp179 and Glu340 (Figure 12). The combined effects of these two factors rationalize the marginal superiority of [15] over acarbose.
The impact of this unfavorable binding and hydrogen bond distance becomes more evident when viewing interactions of compounds [14] and [16] (Figure 13 and Figure 14). In the case of [14], despite the short distance hydrogen bonds, there is unfavorable interaction with Glu235. On the other hand, there are no unfavorable interactions with [16], but the hydrogen bond distances are longer.
## 3.2.3. hSGT2 Interaction
Glucose reabsorption via the kidney is one of the contributing factors in type 2 DM, and as such, targeting this process is an intriguing prospect in antidiabetic therapy [60]. Human sodium-glucose co-transporter proteins are responsible for this machination and as such hSGT2 (PDBID: 7VSI) was selected, which also contained co-crystallized empagliflozin and was used for validation and comparison [61]. As shown in (Figure 15), the sugar moiety of empagliflozin is involved in many hydrogen bond interactions with Asn75, Phe98, Glu99, Ser287, and Lys321. Additionally, several hydrophobic interactions were also observed with His80, Leu84, Val95, Phe98, Tyr290, and Phe453. This plethora of interactions resulted in empagliflozin scoring −11.60 kcal/mol.
Although no compound was able to outperform empagliflozin, the closest binding was observed with [6] and [19], both scoring −8.80 kcal/mol. Several members scored −8.70 kcal/mole [7, 8] and [20], and only [14] scored −8.50 kcal/mol. The 2D interactions of both [6] and [19] reveal their interactions with His80 and Tyr290 (Figure 16 and Figure 17). Individually, [6] interacted with certain five amino acids as empagliflozin (Asn75, His80, Phe98, Tyr290, and Gln457) in addition to Leu283 while [19] interacted with only four similar amino acids (His80, Glu99, Ser287, and Tyr290) and Val157.
## 3.3. Molecular Dynamic Simulations and Generalized MMGBSA Calculations
Extensive investigation of the binding modalities and stability under realistic physiological settings was performed using molecular dynamic simulations. The proteins were simulated for 50 ns with and without the compounds using the Schrodinger Maestro package. The root mean square deviation (RMSD) of the protein–ligand complexes was calculated to ascertain the stability of the binding interactions, while the root mean square deviation (RMSD) of the ligands was used to assess the conformational changes the ligands undergo over the estimated simulation time period. Additionally, the root mean fluctuation (RMSF) of the amino acid residues and their contact with ligands was computed.
Analysis of the free amylase’s trajectory reveals a relatively uniform behavior, as demonstrated by the nearly plateaued RMSD value of 1.40 Å (Figure 18). On the other hand, the effect of binding of compound [14] is observed as a consistent decrease in RMSD, indicating restriction of enzymatic movement and binding stability. Similarly, the same conclusion can be drawn when comparing the RMSF values of amino acid residues in the presence and absence of [14] and finding that fluctuations are restricted. In addition, [14] demonstrated conformational uniformity throughout the entire procedure with an RMSD of 0.80 Å.
As shown in Figure 19, α-amylase trajectory analysis revealed the interaction of [14] with Trp59 and Glu233 continuously in addition to the appearance of several other interactions with Asp197 and Ala198.
Trajectory analysis of the free α and β glucosidase shows relative homogeneity in behavior as demonstrated by its near plateau of RMSD at around 1.40 and 1.45 Å, respectively (Figure 20 and Figure 21). On the other hand, the effect of binding of compounds [20] and [15] is observed as a consistent decrease in RMSD, implying the restriction of enzymatic movement and the stability of binding. Similarly, the same observation can be drawn when examining the RMSF values of the amino acid residues in the presence and absence of compounds, in which residues show limitation in fluctuations when [20] and [15] were present. Finally, both [20] and [15] exhibited conformational uniformity throughout the process as well with RMSD values of 0.75 and 0.70 Å, respectively.
Analysis of the various interactions of [20] across the whole simulation duration (Figure 22) illustrated the consistency with previous docking, in that the two vicinal hydroxyl groups were involved with Asp69 in addition to His112 and Arg442 throughout the simulation. On the other hand, several hydrophobic interactions of [15] were revealed with Tyr313 and Phe347.
Similarly, analysis of molecular dynamic simulation of the hSGT2 without any ligand demonstrated a plateau RMSD around 3 Å, while both [6] and [19] reduced RMSD to 2.40 and 2.10 Å, respectively. Their binding was also reflected in RMSF values as shown in (Figure 23). Finally, both compounds [6] and [19] exhibited conformational uniformity throughout the process as well with RMSD values of 0.50 and 0.90 Å, respectively.
Interactions of [6] and [19] were also analyzed throughout the simulation interval (Figure 24); interactions with Phe98 and Tyr290 were the most frequent in both cases. However, individually, the hydrophilic nature of [6] enabled the formation of hydrogen bonds Thr153 and Asp158.
Another tool for assessing the stability under solvated conditions as in physiological systems is the calculation of binding free energy. Among these tools, Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) is one of the most frequently used methods deployed. The difference in solvent (water) interaction energy with the free receptor, free ligand, and complex is used to calculate the GB and SA energy terms. The molecular mechanics energy obtained from the interaction between the receptor and the ligand under the considered force field is used to compute MM [62]. The lower the predicted binding free energy of a ligand–protein complex, the more stable the complex will be and the greater the ligand’s activity and potency (Table 4). For all simulations, the complexes maintained close energy scores at the beginning and end. This consistency of the binding energies of the targets to different compounds hints at stable binding throughout the simulation.
## 4.1. Eligibility Criteria for the Review
Studies were selected according to the isolated bioactive compounds from endophytic fungi associated with Morus species from 2008 to July 2022 and the biological activities conducted on these compounds during this period. The search spanned several databases such as PubMed and Web of Science.
## 4.2. Pharmacokinetic Profiling
The ADME profile provided by the SwissADME website (www.swissadme.ch; accessed on 6 September 2022) is an excellent web-based tool for the prediction of pharmacokinetic parameters [63,64]. Compounds were imported and predicted as demonstrated by the previous literature [65].
## 4.3. Molecular Docking
The selected targets were obtained from a protein data bank (PDBID: 2QV4, 3A4A, 2XWE, and 7VSI) [35,66,67,68,69]. The compounds and proteins were prepared and converted to the appropriate format using Open Babel and PyRx [70,71]. The docking was performed using Autock Vina software (1.2.0) and MOE08 [72,73]. Root mean square deviation (RMSD) was calculated and the interactions were viewed using Biovia Discovery Visualizer 2021 [74,75,76,77,78].
## 4.4. Molecular Dynamic Simulations and Generalized MMGBSA Calculations
The Schrodinger Desmond package was utilized for simulations of molecular dynamics utilizing the “OPLS4” forcefield for 50 ns, as detailed in previous studies [79]. The solvation was performed using “TIP3P” water molecules using an “Octadecahedron” solvation box. The binding free energy of the examined protein–ligand complexes was computed using the MM-GBSA method, which integrated molecular mechanics (MM) force fields with a Generalized Born and Surface *Area continuum* solvation solvent model using the Schrödinger Prime software [80,81].
## 5. Conclusions
The chronic nature of diabetes mellitus and its crippling effects on the quality of life drives the research for the identification of new agents to improve antidiabetic management. Traditional medicine provides an enormous source of medicinal plants and phytochemicals with established use. However, the environmental burden of using these plants increases the importance of finding alternative sources of bioactive molecules from eco-friendly endophytic fungi. Taking advantage of the antidiabetic effects of Morus plants, this study sought to explore the Morus endophytic fungal metabolites responsible for this property. The previous literature revealed a total of twenty-one compounds under this criterion. The pharmacokinetic properties of the compounds were calculated to narrow down the potential targets and ascertain their safety. The compounds showed safe properties with high intestinal absorption, low blood–brain barrier permeability, and no interactions with cytochrome P2D6. Expanding on these data, we evaluated the compounds’ antidiabetic properties through their capability to affect local and systemic targets in the form of α/β glucosidase and human sodium-glucose cotransporter 2 (hSGT2), respectively. The compounds showed promising potential against all targets with varying degrees in terms of binding scores as well as the stability of such interactions. One of the most promising agents is Colletotrichalactone A [14]; it inhibited α amylase and both isoforms of glucosidase with a greater preference for β than α. Moreover, it was among the top-scoring agents that inhibited hSGT2. This highlights its potential in antidiabetic management locally and systematically. Another candidate is Colletotrichalactone B [15] which outperformed acarbose inhibition on β glucosidase. The result of our study provides an in silico interpretation of the antidiabetic potential of Morus endophytic metabolites as well as providing sufficient evidence for future research on these agents and linking their pharmacological actions to the host, assuming that endophytic fungi are a more eco-friendly leading source of promising bioactive compounds than plant sources.
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|
---
title: RPE-Directed Gene Therapy Improves Mitochondrial Function in Murine Dry AMD
Models
authors:
- Sophia Millington-Ward
- Naomi Chadderton
- Laura K. Finnegan
- Iris J. M. Post
- Matthew Carrigan
- Rachel Nixon
- Marian M. Humphries
- Pete Humphries
- Paul F. Kenna
- Arpad Palfi
- G. Jane Farrar
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9968062
doi: 10.3390/ijms24043847
license: CC BY 4.0
---
# RPE-Directed Gene Therapy Improves Mitochondrial Function in Murine Dry AMD Models
## Abstract
Age-related macular degeneration (AMD) is the most common cause of blindness in the aged population. However, to date there is no effective treatment for the dry form of the disease, representing 85–$90\%$ of cases. AMD is an immensely complex disease which affects, amongst others, both retinal pigment epithelium (RPE) and photoreceptor cells and leads to the progressive loss of central vision. Mitochondrial dysfunction in both RPE and photoreceptor cells is emerging as a key player in the disease. There are indications that during disease progression, the RPE is first impaired and RPE dysfunction in turn leads to subsequent photoreceptor cell degeneration; however, the exact sequence of events has not as yet been fully determined. We recently showed that AAV delivery of an optimised NADH-ubiquinone oxidoreductase (NDI1) gene, a nuclear-encoded complex 1 equivalent from S. cerevisiae, expressed from a general promoter, provided robust benefit in a variety of murine and cellular models of dry AMD; this was the first study employing a gene therapy to directly boost mitochondrial function, providing functional benefit in vivo. However, use of a restricted RPE-specific promoter to drive expression of the gene therapy enables exploration of the optimal target retinal cell type for dry AMD therapies. Furthermore, such restricted transgene expression could reduce potential off-target effects, possibly improving the safety profile of the therapy. Therefore, in the current study, we interrogate whether expression of the gene therapy from the RPE-specific promoter, Vitelliform macular dystrophy 2 (VMD2), might be sufficient to rescue dry AMD models.
## 1. Introduction
Age-related macular degeneration (AMD) is a devastating and progressive degenerative disorder of the macula leading to loss of central vision. It is the leading cause of blindness in the elderly in the developed world, affecting ~$10\%$ of people over 65 years of age [1]. AMD is a multifactorial condition with genetic and environmental factors known to contribute to the disease, with age being the greatest risk factor. Twin studies estimate the heritability of AMD at between 46–$71\%$ [2]. AMD is generally divisible into 2 distinct forms: neovascular (wet) and non-exudative (dry), accounting for 10–$15\%$ and 85–$90\%$ of cases, respectively [3].
In early dry AMD, drusen are formed between the Bruch’s membrane (BM) and the basal lamina of the retinal pigment epithelium (RPE). In the late stage, the condition may progress to geographic atrophy (GA), characterised by atrophy of the photoreceptors, RPE and choriocapillaris in the macula. GA typically initiates in the perifoveal macula, but subsequently may expand into the cone-dominated fovea, with associated loss of central vision [4].
Another hallmark feature of AMD is chronic inflammation. Indeed, an analysis of drusen from post-mortem eyes of AMD patients demonstrated the presence of components from the complement system [5,6]. Variants in multiple complement factor genes have been linked to increased complement system activation in AMD [7]. While not all mechanisms are understood, it is known that in AMD the RPE and choriocapillaris provide less oxygen and glucose to photoreceptor cells, contributing to their death [8]. The RPE functions as an outer blood—retinal barrier, is a scavenger of photoreceptor outer segments and is important in the maintenance of retinal homeostasis, supporting photoreceptors. Electron microscopy of RPE from donor AMD patients revealed fewer and smaller mitochondria, suggesting defects in mitochondrial biogenesis and fusion, as well as abnormal mitochondrial membranes and disrupted cristae [9,10]. Indeed, RPE from AMD patients displayed reductions in autophagic flux [11], mitochondrial respiration and ATP production [11,12], and elevated levels of ubiquitin-binding protein p62 [13]. Proteomics on RPE from AMD patients showed elevated levels of mitofilin, which aids in maintaining cristae integrity, and increases in several mitochondrial chaperones, which assist with the import and folding of nuclear-encoded proteins into the mitochondria [14,15,16]. These findings strongly suggest the pivotal role that mitochondrial dysfunction in RPE plays in AMD disease progression. Notably, the RPE is exposed to high levels of reactive oxygen species (ROS) due to the significant metabolic demands of the retina [17,18]. Evidence is accumulating that elevated ROS, as well as mitochondrial dysfunction in the RPE, leads to organelle dysfunction, impaired mitophagy, DNA mutations, protein and lipid damage, and reduced respiration and/or generation of toxic lipid-derived adducts, and contributes to RPE and photoreceptor cell death in dry AMD [19,20,21,22,23,24,25,26,27,28,29].
The field of AMD has been greatly hampered by the lack of suitable disease models. Aged rodent models simulate aspects of dry AMD; however, none fully mirror AMD [29]. Notably, non-primate retinas have no macula, which limits their morphological commonality, and therefore their utility as model systems. The Cfh−/− mouse [30,31] has been used for AMD studies since the discovery that CFH polymorphisms are frequently associated with AMD [7,32,33,34,35]. Aged Cfh−/− mice have been shown to display impaired visual function, thinning of the outer nuclear layer and abnormal BM, while in other studies thickening of BM and basal laminar deposits (BlamDs) were reported [31,36,37]. BM deposits in Cfh−/− mice may be due to competition between CFH and lipoproteins for binding to BM, leading to lipoprotein accumulation [37]. We recently reported that aged Cfh−/− mice displayed abnormal cone morphology, with disorganised outer segment membranes. Additionally, cone inner segments contained abnormal mitochondria that were irregular in shape and generally smaller than mitochondria in adjacent rod inner segments [38]. Others have shown that Cfh−/− mice have decreased plasma C3 levels [31]. Interestingly, when CFH was silenced in vitro in an RPE cell line, increased inflammation, metabolic impairment and vulnerability towards oxidative stress were observed [39]. More recently, the same group silenced CFH in an RPE cell line, which was co-cultured with either primary retinal explants from the porcine visual streak, an area akin to the human macula, or with a human macula. The co-cultured retinal cells exhibited signs of degeneration (with rod cells seemingly being the first to suffer) and changes in mitochondria and lipid composition [40].
In contrast to the Cfh−/− model of dry AMD, chemically-induced models of AMD such as the well-established sodium iodate (NaIO3)-induced model [41,42,43,44] do not require aging. NaIO3, a strong oxidising agent, causes catastrophic damage to the RPE, leading to photoreceptor loss and reduced retinal function, including reduced electroretinogram (ERG) amplitudes [38,43,45,46,47,48].
In AMD both the RPE and photoreceptors have been shown to display mitochondrial complex 1 deficiency [16,26,46,47,48,49,50,51]. Complex 1, a component of the mitochondrial electron transport chain (ETC), is a 45-subunit complex, 7 of which are mitochondrially encoded [51]. We have recently demonstrated significant therapeutic benefit in a variety of dry AMD models with a gene therapy, ophNdi1 [38]. OphNdi1 is a modified gene from S. cerevisiae, NDI1, which has been optimised to express more efficiently in mammalian cells (patent no. 10220102). Encoded by a single nuclear gene, NDI1 performs a similar function to mammalian mitochondrial complex 1. OphNdi1, delivered subretinally via recombinant adeno-associated virus $\frac{2}{8}$ (AAV$\frac{2}{8}$), was shown to provide significant and robust benefit in the Cfh−/− and NaIO3-induced murine models and two cellular models of dry AMD [38]. The study was the first to show functional benefit in vivo in murine models of dry AMD, using a gene therapy which directly targets mitochondrial dysfunction. In the study, AAV$\frac{2}{8}$-ophNdi1 was driven from generic CMV and CAG promoters so that ophNdi1 was expressed in both RPE and photoreceptor cells. In contrast, in the current study, we evaluated whether targeted treatment of the RPE with ophNdi1 was sufficient to provide benefit to dry AMD models, since it is thought that AMD may initiate in the RPE prior to photoreceptor cells [52]. In addition, restricting ophNdi1 expression to the RPE may reduce potential off-target effects in other cell types; thereby, in principle, improving the potential safety profile of the therapy. Hence, in this study we replaced the generic promoter (CMV or CAG) with a vitelliform macular dystrophy (VMD2) promoter, which, in the context of the eye, is known to restrict gene expression to the RPE [53], creating VMD2-ophNdi1. VMD2-ophNdi1 was expressed from recombinant AAV$\frac{2}{8}$ (AAV$\frac{2}{8}$-VMD2-ophNdi1; Figure 1) and its therapeutic potential was investigated in the Cfh−/− genetic and NaIO3-induced murine models of AMD. Primary porcine RPE (pRPE) models of dry AMD were also utilised; these were either insulted with NaIO3 [38] or loaded with retinylidene-N-retinylethanolamine (A2E) and insulted with blue light [47]. A2E is a toxic bisretinoid byproduct of the visual cycle and a major component of drusen, which is known to lead to RPE dysfunction and cell death in vitro and in vivo [47,54,55,56].
## 2. Results
In order to estimate the dose of AAV$\frac{2}{8}$-VMD2-ophNdi1 (Figure 1A) that might be effective in murine RPE, we generated an AAV$\frac{2}{8}$ vector expressing VMD2 promoter-driven enhanced green fluorescent protein (EGFP) gene (AAV$\frac{2}{8}$-VMD2-EGFP; Figure 1B) which could be compared in vivo to a similar CMV-driven EGFP vector (AAV$\frac{2}{8}$-CMV-EGFP). Two-month-old 129 S2/SvHsd mice were subretinally injected with 3 × 109 vg of either AAV$\frac{2}{8}$-VMD2-EGFP or AAV$\frac{2}{8}$-CMV-EGFP. Relative EGFP protein expressions from the two promoters were determined in mouse retinas four weeks post-injection. EGFP expression from the VMD2 promoter was restricted to the RPE, whereas the CMV promoter efficiently drove EGFP expression in the RPE and the outer nuclear layer containing the photoreceptors (Figure 1C–E). Levels of EGFP fluorescence in the RPE were evaluated using fluorescent microscopy and were estimated to be 6.5-fold higher from the CMV than from the VMD2 promoter. Therefore, to account for this differential in expression, doses of AAV$\frac{2}{8}$-VMD2-ophNdi1 used in the current study, in both in vitro and in vivo models, were 6.5-fold higher than doses of the non-specific CMV promoter [38].
Two-month-old 129 S2/SvHsd mice were subretinally injected with 3 × 109 vg of AAV$\frac{2}{8}$-CMV-EGFP and AAV$\frac{2}{8}$-VMD2-EGFP (Figure 1A). Four weeks post-injection, eyes were enucleated, fixed in $4\%$ PFA, cryosectioned, and processed for and analysed by fluorescent microscopy. Green and blue represent EGFP and DAPI (nuclear counterstain) fluorescence, respectively. Panels C and D were displayed using the full intensity range of EGFP fluorescence. Panel E corresponds to the same microscopy image as panel D; however, in panel E, the displayed EGFP fluorescence intensity range was focused on the lower intensity values, which enabled the visualisation of lower EGFP levels. EGFP fluorescence intensity levels were evaluated in the RPE for both promoters and levels were found to be ~6.5-fold lower from VMD2 compared to CMV.
## 2.1. Rescue in pRPE Cell Models
To determine whether the VMD2 promoter-driven ophNdi1 therapy could rescue cell models of dry AMD, insulted primary pRPE cells were utilised. Primary pRPE cells isolated from $$n = 3$$ adult pigs were transduced with AAV$\frac{2}{8}$-VMD2-ophNdi1 (MOI = 3.4 × 106), insulted with 6 mM NaIO3 and compared to control cells. Cells were fixed 24 h post-insult and analysed with immunocytochemistry for 8-OHdG (oxidative stress marker), CPN60 (mitochondrial marker), phalloidin (selective for F-actin) and Hoechst (nuclear stain). NaIO3-treated cells exhibited high levels of oxidative stress and absence of actin filaments compared to non-insulted cells, indicating severe stress and reduced viability. In contrast, insulted cells transduced with AAV$\frac{2}{8}$-VMD2-ophNdi1 appeared more similar to non-insulted controls. Furthermore, mitochondrial staining was more intense and punctuated in insulted cells that had not received therapy, likely indicating mitochondrial dysfunction. Mitochondria of AAV$\frac{2}{8}$-VMD2-ophNdi1-treated cells insulted with NaIO3 were more similar to non-insulted control cells, although staining was still somewhat elevated (Figure 2A–O).
The bioenergetic response to AAV$\frac{2}{8}$-VMD2-ophNdi1 treatment was also profiled in pRPE cells, isolated from $$n = 3$$ adult pigs. Cells were seeded (1.375 × 104 cells/well) in XFe96 Seahorse plates and transduced with AAV$\frac{2}{8}$-VMD2-ophNdi1 (MOI = 3.4 × 106). After 28 h, cells were insulted with 30 μM A2E and insulted with blue light for 3 h. A mitochondrial stress test was subsequently performed (Figure 2P–S, Table S1). The A2E/blue light insult reduced basal and maximal oxygen consumption rates (OCRs), spare respiratory capacity (SRC, the difference between maximal and basal OCRs; $p \leq 0.01$) and ATP production in primary pRPE cells. Notably, treatment of A2E-insulted cells with AAV$\frac{2}{8}$-VMD2-ophNdi1 increased basal and maximal OCRs, and ATP production (ANOVA and post-hoc Tukey; Figure 2P–S, Table S1).
## 2.2. Rescue of the Cfh−/− Mouse
AAV$\frac{2}{8}$-VMD2-ophNdi1 clearly rescued morphological and bioenergetic damage in the A2E/blue light and NaIO3-induced pRPE models of dry AMD (Figure 2). To interrogate whether rescue could also be achieved in vivo with VMD2-ophNdi1, two-month-old Cfh−/− mice were subretinally injected with 4.5 × 108 vg AAV$\frac{2}{8}$-VMD2-ophNdi1 ($$n = 13$$) in one eye. The contralateral control eye received an equal volume (3 μL) of PBS. At 8 months of age electroretinography was performed on injected mice. Notably, eyes treated with AAV$\frac{2}{8}$-VMD2-ophNdi1 showed significantly greater Rod b (53.0 ± 26.0 μV versus 97.7 ± 36.2 μV, Figure 3A), Max b (111.4 ± 49.0 μV versus 178.7 ± 68.3 μV, Figure 3B) and single flash cone (SFC) b (19.8 ± 8.2 μV versus 24.4 ± 9.2 μV, Figure 3C) responses than contralateral eyes, indicating benefit in both rod and cone photoreceptor cells, in treated versus control eyes (paired t-test; Figure 3A–C). At 7 months, ROS levels in live cells from treated and untreated dissociated Cfh−/− retinas were compared ($$n = 10$$ mice) using a CellRoxTM assay. This assay measures ROS predominantly in photoreceptors cells, as the RPE is not isolated with the neural retina during sample collection for this assay. Notably, ROS were significantly reduced in treated samples compared to control samples (91.4 ± $8.9\%$ versus 100 ± $8.4\%$ respectively; $p \leq 0.05$, paired t-test, Figure 3D). In addition, at 8 months, mice were sacrificed, their eyes fixed and retinal histology performed. Cone cells in retinal sections were stained with Arr3 immunohistochemistry and quantified (Figure 3E,F). Outer nuclear layer (ONL) thickness was measured and was 41.87 ± 15.67 μm and 49.64 ± 7.762 μm ($$n = 6$$; $$p \leq 0.0795$$; paired t-test; Figure 3G) in control and treated retinas, respectively. However, this difference was a trend. Cone numbers were also determined in retinas and were 150.3 ± 52.6 cones/mm and 169.8 ± 11.6 cones/mm ($$n = 6$$; $$p \leq 0.46$$; paired t-test; Figure 3H) in control and transduced samples, respectively; however, this minor increase in cone numbers in treated retinas was not significant.
## 2.3. Rescue of the NaIO3-Induced Mouse
Notably, AAV$\frac{2}{8}$-VMD2-ophNdi1 provided clear functional benefit in aged Cfh−/− mice and reduced ROS levels. However, histological benefit could not be demonstrated. Given the multifactorial nature of AMD, involving genetic and environmental factors, and limitations of available models, it was valuable to assess AAV$\frac{2}{8}$-VMD2-ophNdi1 in an additional murine model, the NaIO3 model. Four-month-old 129 S2/SvHsd mice received 4.5 × 108 vg AAV$\frac{2}{8}$-VMD2-ophNdi1 subretinally in one eye and 1.0 × 108 vg of AAV$\frac{2}{2}$-CAG-EGFP, as a marker, in both eyes. Two months post-injection, mice received 22 mg/kg NaIO3 via tail vein to induce acute and severe oxidative damage in the RPE, mimicking aspects of dry AMD. ERG and OKR analyses were performed one week and four weeks post-NaIO3 insult, respectively. ERG readings in NaIO3-insulted mice were reduced to the extent that only Max b responses remained reliably recordable. Max b readings in treated versus untreated eyes were 185.3 ± 154.9 μV versus 121.8 ± 44.9 μV, respectively. However, this difference was only a trend ($$n = 7$$, Figure 4A). AAV$\frac{2}{8}$-VMD2-ophNdi1-treated eyes displayed significantly better OKR tracking responses than control eyes (0.234 ± 0.0652 μV cyc/deg versus 0.171 ± 0.0492 cyc/deg, respectively; $$n = 7$$, $p \leq 0.005$, paired t-test, Figure 4B).
An additional group of mice was subretinally injected with 4.5 × 108 vg AAV$\frac{2}{8}$-VMD2-ophNdi1 and 1.0 × 108 vg AAV$\frac{2}{2}$-CAG-EGFP in one eye and PBS containing 1.0 × 108 vg AAV$\frac{2}{2}$-CAG-EGFP in contralateral eyes and was insulted with 50 mg/kg NaIO3 delivered via tail vein at two months post-treatment. Retinas were fixed 7 days post-insult, cryosectioned and stained for Arr3 (cone-specific marker; Figure 4C). Cones were quantified; however, numbers were similar in treated and untreated eyes: 124.8 ± 11.3 cones/mm and 129.1 ± 21.1 cones/mm, respectively ($$n = 7$$, $$p \leq 0.56$$, paired t-test). OKR responses suggest that ophNdi1 provided some benefit. However, treatment was not sufficient to rescue ERG or histology significantly from this severe NaIO3 insult.
## 3. Discussion
We have previously shown that subretinally injected AAV-delivered ophNdi1 provided robust functional benefit and increased mitochondrial function in the Cfh−/− and NaIO3-induced mouse models of dry AMD. Additionally, increased cellular bioenergetics and reduced cellular stress markers were found [38]. In the prior study, ophNdi1 expressed from a recombinant AAV$\frac{2}{8}$ vector was driven from a ubiquitous CMV or CAG promoter and therefore was expressed in multiple retinal cells, including RPE, rod and cone photoreceptor cells; the cells lost in advanced dry AMD. In the current study, a higher absolute dose of AAV$\frac{2}{8}$-VMD2-ophNdi1 (4.5 × 108 vg) was utilised to match the effective dose range of AAV$\frac{2}{8}$-CMV-ophNdi1 (1 × 107 vg and 7.5 × 107 vg) and achieve comparable levels of expression of ophNdi1 from the RPE-specific VMD2 promoter, which was estimated to express ~6.5-fold less than the CMV promoter in RPE cells (Figure 1C–E).
There is strong evidence that AMD may initiate in the RPE, causing subsequent dysfunction in photoreceptor cells and ultimately, in GA, cell death in RPE and photoreceptor cells. However, this order of events is by no means definitively established. Differentially expressed genes have been identified in both RPE and cells of the neural retina and in both peripheral and macular regions of post-mortem AMD patient eyes [57]. In addition, rod photoreceptor cells also show early functional and histological signs of degeneration, as early signs of AMD include parafoveal scotomas and scotopic sensitivity; the parafoveal area is dense in rod photoreceptor cells [58]. Physiological abnormalities in cones in early dry AMD have also been widely reported and are indicative markers of the severity of dry AMD [59]. The morphological changes in cones in early dry AMD are, however, more subtle and include abnormal immunoreactivity to cone opsin, in combination with swelling of and altered immunoreactivity in the cone distal axon [60]. Thus, based on these features, many researchers believe that photoreceptor cell dysfunction may possibly occur in parallel with, or even prior to, dysfunction in the RPE/Bruch’s membrane complex [61]. Hence, the exact sequence of disease progression remains somewhat obscure.
Experimental therapies for AMD have focused on preservation of photoreceptor cells, RPE or both [62,63,64,65,66,67]. However, clearly, in terms of optimising efficacy and safety and reducing possible off-target effects, there may be a therapeutic advantage to restricting expression of a gene therapy to cell types underlying the condition, with the aim of preventing the disease from progressing to other retinal cells. The aim of the current study was to determine whether expression of ophNdi1 solely in RPE is sufficient to rescue a variety of AMD cell and murine models. Primary RPE cells were insulted with either NaIO3 or A2E/blue light. AAV$\frac{2}{8}$-VMD2-ophNdi1 was shown to rescue these cellular models using assays for ROS, cell viability, mitochondrial morphology and mitochondrial function (OXPHOS), in a similar fashion to CAG-driven ophNdi1 (Figure 2), indicating that the VMD2 promoter is functional and efficient in primary RPE cells.
In the Cfh−/− mice, ERG readings were significantly improved, and ROS levels reduced by, AAV$\frac{2}{8}$-VMD2-ophNdi1 treatment, as had also been seen in a previous study utilising AAV$\frac{2}{8}$-CAG-ophNdi1 in this model [38]. However, in contrast to AAV$\frac{2}{8}$-CAG-ophNdi1, AAV$\frac{2}{8}$-VMD2-ophNdi1 did not rescue cone numbers in the model, whereas the ONL showed a trend towards being thicker in treated eyes (Figure 3). Additionally, in the very acute and severe NaIO3-induced murine model of dry AMD, only OKR benefit could be demonstrated with AAV$\frac{2}{8}$-VMD2-ophNdi1 (Figure 4), whereas AAV$\frac{2}{8}$-CAG-ophNdi1 had previously provided OKR, ERG and histological benefit [38]. The data in these dry AMD models highlight the involvement of both the RPE and photoreceptors and suggest that expression of the ophNdi1 gene in both RPE and photoreceptors may be preferable to that in RPE alone.
Whether a higher dose of AAV$\frac{2}{8}$-VMD2-ophNdi1 would have provided similar benefit to CMV-driven ophNdi1 in the NaIO3-induced mice was not investigated in the current study, as the dose used with the VMD2-driven therapy was already 6-fold higher than the highest dose of CMV-driven ophNdi1 used previously. Note that there is an increasing focus in the field of virally-delivered gene therapy on lowering dose requirements of AAV gene therapies, thereby reducing the risk of immune responses.
It is notable that an allied experimental approach has been explored previously for ABCA4-linked Stargardt disease (STGD1) in genetically modified mice. In the study, the ABCA4 gene was expressed in the RPE, but not photoreceptors, providing partial rescue of the disease and suggesting a role for both the RPE and photoreceptors in the pathogenesis of STGD1 [68]. Both that study and our own highlight the value of differential promoter constructs to explore the relative contributions of different cell types to the pathogenesis of disease and the optimal target cell population in therapeutic interventions.
In summary, while AAV$\frac{2}{8}$-VMD2-ophNdi1, which only expresses in RPE, did provide some benefit in two murine models of dry AMD, AAV$\frac{2}{8}$-CMV-ophNdi1, which expresses in RPE and rods and cones, amongst other cell types, provided more robust and consistent benefit using a variety of functional and histological assays. It remains unclear which cells are affected first in dry AMD, RPE or photoreceptor cells. However, ubiquitous and RPE-specific promoter-driven gene therapies can be used to interrogate the contribution of different cell types to disease pathogenesis and the optimal target cell population for a therapy. In the current study, the data from two murine models suggests that using a general promoter to drive expression of ophNdi1 and boosting mitochondrial function in both RPE and photoreceptor cells is more beneficial than targeting the RPE alone.
## 4.1. Study Design
An optimised complex I equivalent gene, ophNdi1 driven from an RPE-specific promoter, VMD2, was delivered via recombinant AAV$\frac{2}{8}$ to models of dry AMD: the Cfh−/− mouse, NaIO3-induced mouse and primary pRPE cells insulted with NaIO3 or A2E/blue light. Functional benefit was determined using physiologic readouts, ERG and OKR. Histological analysis and cellular assays included mitochondrial function, ROS and morphological readouts.
## 4.2. Plasmid Construct, AAV Production and Analysis of Relative Expression Levels
A 547 bp region of the VMD2 promoter was PCR-amplified from DNA using the following primer pair and was cloned upstream of ophNdi1 [38] using SacI and EcoR1. VMD2 F primer −585: 5′ CATGAGAGCTCAATTCTGTCATTTTACTAGGGT 3′ and VMD2 R primer +38: 5′ CATGAGAATTC GGTCTGGCGACTAGGCTGGT 3′ [53]. The same promoter region was PCR-amplified with the following F primer and the same R primer as above and the product cloned upstream of an EGFP gene. VMD2 F −585 NotI: 5′ CATGAGCGGCCGCAATTCTGTCATTTTACTAGGGT 3′. VMD2-ophNdi1 and VMD2-EGFP were packaged into recombinant AAV$\frac{2}{8}$ (AAV$\frac{2}{8}$-VMD2-ophNdi1 and AAV$\frac{2}{8}$-VMD2-EGFP), and their viral titres determined as described [38]. Expression of EGFP from the CMV [69] and VMD2 was compared in murine retinas by subretinally injecting adult 129 S2/SvHsd mice with 3 × 109 vg of either AAV$\frac{2}{8}$-VMD2-EGFP ($$n = 3$$) or AAV$\frac{2}{8}$-CMV-EGFP ($$n = 2$$). Mice were sacrificed 1 month post-injection, eyes fixed in $4\%$ PFA, cryosectioned and analysed by fluorescent microscopy as described [69]; mean EGFP fluorescence intensity levels were determined in the RPE.
## 4.3. Cellular Models
Primary pRPE cells were isolated from mature pig eyes ($$n = 3$$ pigs) and maintained in culture [70]. Cells numbering 5.0 × 104 were seeded into XFe96 Seahorse plates ($$n = 3$$; Agilent, Santa Clara, CA, USA). A minimum of 5 wells were transduced with AAV$\frac{2}{8}$-VMD2-ophNdi1 (MOI = 3.4 × 106) 24 h later. At 28 h post-transduction, transduced and untransduced cells (>15 wells per group) were insulted with 30 μM A2E (Orga-Link, Magny-les-Hameaux, France) and maintained for 3 h under blue light of ~1 mW/cm2 (80–90 Lux) at 430 nm. Cells then underwent a mitochondrial stress test and readings were normalised to total protein as described [38]. Mitochondrial stress tests on RPE from 3 pigs (RPE1-3) were performed on 3 separate occasions. Cells numbering 7.5 × 104 pRPE (from $$n = 3$$ pigs) were seeded onto 8-well imaging slides (Miltenyi Biotec, Bergisch Gladbach, Germany). At 5 h post-seeding, cells were transduced with AAV$\frac{2}{8}$-VMD2-ophNdi1 (MOI = 3.4 × 106). At 28 h post-transduction, cells were insulted with 6 mM NaIO3 and at 24 h post-insult cells were fixed in $4\%$ paraformaldehyde in PBS at RT for 20 min. Cells were stained and analysed as described [38].
## 4.4. Subretinal Injections, Electroretinography and Ros Assay
All animal work was performed in accordance with the European Union (Protection of Animals used for Scientific Purposes) Regulations 2012 (S.I. no. 543 of 2012) and the Association for Research in Vision and Ophthalmology (ARVO) statement for the use of animals, and approved by the animal research ethics committee in Trinity College Dublin (Ref. no. $\frac{140514}{240320}$). C57BL/6J, Cfh−/− on a pure C57BL/6J background and 129 S2/SvHsd mice (Harlan Laboratories, Blackthorn, UK.) were maintained under specific pathogen-free conditions. Injections were performed on two-month-old mice as described, except that anaesthesia comprised of ketamine and medetomidine (57 mg/kg and 0.5 mg body weight, respectively) and, following injection, an anaesthetic-reversing agent (Atipamezole Hydrochloride, 1.33 mg/kg body weight) were delivered by intraperitoneal injection [71]. An amount of 4.5 × 108 vg of AAV$\frac{2}{8}$-VMD2-ophNdi1 was injected into Cfh−/− mice, while contralateral eyes received the same volume (3 µL) of PBS. At 8 months, ERG responses from treated eyes were compared to fellow eyes ($$n = 13$$ mice; paired t-tests). Mice were analysed histologically at 8 months of age as described ($$n = 6$$) [38]. At 7 months post-injection, mice were sacrificed, retinal cells were dissociated and a CellRoxTM Green Reagent (Invitrogen, Waltham, MA, USA) ROS assay was performed using a flow cytometry assay, as described [38]. Median levels of CellRoxTM, representing relative ROS levels, were recorded. Paired t-tests of the means were performed to compare medians of treated versus untreated eyes of Cfh−/− mice ($$n = 10$$ mice).
## 4.5. NaIO3-Induced Murine Model
Two-month-old 129 S2/SvHsd mice were subretinally injected in one eye with 4.5 × 108 vg AAV$\frac{2}{8}$-VMD2-ophNdi1 and 1.0 × 108 vg AAV$\frac{2}{2}$-CAG-EGFP [72], and in the other eye with 1.0 × 108 AAV$\frac{2}{2}$-CAG-EGFP in PBS. At 5 months, mice were injected via tail vein with 22 mg/kg NaIO3 in $0.9\%$ NaCl2. Mice underwent ERG analysis at 7 days and OKR analysis at 4 weeks post-insult ($$n = 7$$) [71,73]. OKR spatial frequency thresholds were measured blind on three occasions using a virtual optokinetic system (OptoMotry, CerebralMechanics, Lethbridge, AB, Canada). Treated and untreated eyes were compared using paired t-tests. Additionally, mice received 50 mg/kg NaIO3 in $0.9\%$ NaCl2 via tail vein. Retinas were processed for histology 7 days post-insult as described ($$n = 7$$) [38].
## 4.6. Statistical Analysis
Statistical analysis was performed using GraphPad Prism (version 9.4, GraphPad Software, Boston, MA, USA). t-tests and ANOVA with post-hoc Tukey were considered significant at $p \leq 0.05.$
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|
---
title: Synthesis and Characterization of Hierarchical Zeolites Modified with Polysaccharides
and Its Potential Role as a Platform for Drug Delivery
authors:
- Agata Wawrzyńczak
- Izabela Nowak
- Natalia Woźniak
- Jagoda Chudzińska
- Agnieszka Feliczak-Guzik
journal: Pharmaceutics
year: 2023
pmcid: PMC9968069
doi: 10.3390/pharmaceutics15020535
license: CC BY 4.0
---
# Synthesis and Characterization of Hierarchical Zeolites Modified with Polysaccharides and Its Potential Role as a Platform for Drug Delivery
## Abstract
Hierarchical zeolites are aluminosilicates with a crystal structure, which next to the micropores possess secondary porosity in the range of mesopores and/or small macropores. Due to their ordered structure and additional secondary porosity, they have aroused great interest among scientists in recent years. Therefore, the present work concerns the synthesis and characterization of hierarchical zeolites with secondary mesoporosity, based on commercial zeolites such as MFI (ZSM-5), BEA (β) and FAU (Y), and modified with polysaccharides such as inulin, hyaluronic acid, and heparin. All materials were characterized by various analytical techniques and applied as a platform for delivery of selected drug molecules. On the basis of X-ray diffraction (presence of reflections in the 2θ angle range of 1.5–2.5°) and low-temperature nitrogen sorption isotherms (mixture of isotherms of I and IV type) additional secondary porosity was found in the mesopore range. Additional tests were also conducted to determine the possibility of loading selected molecules with biological activity into the aforementioned materials and then releasing them in the therapeutic process. Molecules with different therapeutic options were selected for testing, namely ibuprofen, curcumin, and ferulic acid with anti-inflammatory, potentially anticancer, antioxidant, and skin discoloration activities, respectively. Preliminary studies have confirmed the possibility of using hierarchical zeolites as potential carriers for bioactive molecules, as the loading percentage of active substances ranged from 39–$79\%$ and cumulative release for ibuprofen reached almost $100\%$ after 8 h of testing.
## 1. Introduction
In the last few years synthesis, characterization and application of hierarchical zeolites have become an object of interest for a growing number of scientists. In addition to micropores, hierarchical zeolites are characterized by having a secondary porosity in which there are pores of diverse sizes, i.e., supermicropores, mesopores or macropores [1].
Hierarchical modification of zeolite is assumed to reduce steric hindrance by introducing secondary porosity (mesopores and macropores). This allows the particle sizes of the reactants to be increased to a range that is needed for a given reaction. There are two types of active sites in materials with secondary porosity: active sites accessible from the external surface through secondary channels to the entrance of the microporous network (they have almost no steric hindrance), and active sites located at the entrance to the microporous network (they potentially have several steric limitations and limit accessibility for large molecules) [2].
The contribution and properties of secondary porosity, i.e., specific surface area, pore size and distribution, as well as pore volume, depend on the method of synthesis of hierarchical zeolites. So far, many diverse methods of obtaining hierarchical zeolites have been described, therefore, their classification may be a challenging task. Generally, the synthesis procedures for obtaining hierarchical zeolites can be divided into two main groups, namely bottom-up and top-down [2]. Bottom-up includes the following methods: hard templating, soft templating, non-templating, zeolization of materials or assembly of nanometer-sized zeolites [3]. On the contrary, top-down methods consist of dealumination, desilication, or recrystallization [2,4,5]. *In* general, the variety of methods developed to date for synthesis of hierarchical zeolites relies on aggregation, extraction, and crystallization processes [6].
Despite the large number of hierarchical zeolites available today, they can be divided, according to their origin and secondary porosity, into pure zeolitic phases and composites. Pure zeolitic phases or so called true hierarchical zeolites are obtained when the secondary porosity is localized within the zeolitic phase. In this case, the secondary porosity is present either within the zeolite crystals or in the intercrystalline spaces. In the case of composites comprising a zeolitic phase and a nonzeolitic phase the hierarchy in zeolites is due to additional phases. The nonzeolitic phase typically serves as a carrier or binder that holds the zeolite crystals together. When this phase is the carrier, secondary porosity is derived from the carriers [3].
In this study selected polysaccharides were used to modify hierarchical zeolites based on commercial materials such as MFI (ZSM-5), BEA (β), and FAU (Y). Polysaccharides, also known as complex sugars, are polymeric compounds with the following general formula (C6H10O5)n, placing them in the group of macromolecular compounds. The polysaccharide chain can take a simple (linear) or branched form. Complex sugars formed on the basis of one type of monosaccharides are called homopolysaccharides (homoglycans). These are, for example, starch, cellulose, and glycogen. On the other hand, polysaccharides composed of various types of monosaccharides can be found under the name of heteropolysaccharides (heteroglycans). They include, among others, hyaluronic acid, heparin, and inulin, namely polysaccharides used in the course of this work [7].
Hyaluronic acid (HA), classified as a glycosaminoglycan (GAG), was first isolated from the vitreous body of the cow’s eye by Karl Meyer and John Palmer in 1934 [8,9]. Despite the presence of the word “acid” in the name it is not an acid but an unbranched biopolymer composed of repeating disaccharides that include D-glucuronic acid and N-acetyl-D-glucosamine (Figure 1) [10,11]. The bonds in the HA molecule are alternating β-1,3 and β-1,4-glycosides [10,11]. Both compounds are spatially related to the glucose molecule, which in the beta configuration allows all of its bulky groups to be in sterically favorable equatorial positions, while all small hydrogen atoms occupy sterically less favorable axial positions. Therefore, the disaccharide structure is energetically very stable [12].
HA is one of the most hydrophilic (water-loving) molecules in nature and can be referred to as a natural moisturizing agent [12]. Thanks to its ability to bind water, hyaluronic acid swells so that the tension state of the extracellular matrix increases in direct proportion to the volume of water taken up. Due to this property, it is very often used in the cosmetic industry [8,13,14]. Moreover, in physiological solution the HA backbone stiffens due to a combination of the chemical structure of the disaccharide, internal hydrogen bonds, and interaction with the solvent. Therefore, hyaluronate solutions exhibit very unusual rheological properties. [ 8,12,13,14].
Inulin is a polysaccharide composed of glucose and fructose molecules [15]. In 1804, it was first isolated from the perennial plant *Inula helenum* (i.e., Oman the Great of the Asteraceae family), by Valentin Rose, a prominent German researcher [16]. The inulin chain is linear (Figure 1), with fructose molecules joined by β-1,2-glycosidic bonds. At the end of the chain there is a glucose molecule. The number of fructose units is determined by the origin and the harvest time of the plants in which inulin is present, and varies from 10 to 70 [17]. This polysaccharide occurs in the form of a white powder that dissolves well in warm water, while it precipitates from a solution at 0 °C [18].
Inulin’s unique and flexible structure and its stabilizing and protective effects make it an excellent polysaccharide with a wide range of applications. Three hydroxyl groups attached to each fructose unit serve as an anchor for chemical modification. This in turn helps to increase its bioavailability, improve cellular absorption, and achieve long-lasting, targeted effects [19,20].
Heparin (Figure 1) was isolated from canine liver cells by Jay McLean. It is an organic compound of the polysaccharide group composed of mucopolysaccharides and sulfonated glycosaminoglycans. The structure of heparin is linear and is composed of polymers in the range of 3000 to 30,000 Daltons including monosaccharides. Heparin molecules contain outward-facing anionic groups with a negative charge [21,22].
Heparin is a natural anticoagulant that counteracts intravascular blood clotting. In this case mechanism of action includes stimulation of antithrombin, clotting factor IXa, and Xa, and reduction of aggregation and adhesion of thrombocytes [23].
To the best of our knowledge, hierarchical zeolites modified with heparin, inulin, or hyaluronic acid have not been obtained up to date. Generally, there is little work involving the synthesis of porous materials modified with the aforementioned compounds. Examples of the synthesis of such materials were published by Ojeda et al. [ 24] and Ari and Sahiner [25]. The first group proposed the synthesis of metal-modified mesoporous starches using a simple microwave-assisted method involving gelation of the parent polysaccharide and addition of the metal precursor, followed by solvent exchange and drying [24]. Paper by Ari and Sahiner reported chemically crosslinked superporous inulin cryogels made by cryogelation using divinyl sulfone, and ranging from $75\%$ to $150\%$ of inulin repeating units [25].
The use of polysaccharide-based systems as drug carriers could be profitable due to the high diversity of polysaccharides and their natural origin. They can create biocompatible and biodegradable systems with a broad range of both biological and chemical function-alternatives. These primarily include protection of therapeutic agents by by-passing the reticuloendothelial system, stabilizing biomacromolecules, and enhancing the bioavailability of incorporated small-molecule active ingredients. Therapeutic transport is a key to the utility of polysaccharide molecules: they move drugs from the site of administration to specific tissues through binding and mucosal transport and by using chemical, size and receptor targeting [26,27]. So far, polysaccharide-based materials were used as carriers in the combination with: hydrogels [28,29], zeolites [30] or lipid nanoparticles [31].
The interest in bioactive compounds is related to their potential use as food, chemical, cosmetic, or pharmaceutical additives [32]. In the present study, ibuprofen, curcumin and ferulic acid were used as bioactive compounds. Ibuprofen, which belongs to the group of non-steroidal anti-inflammatory drugs (NSAIDs) exhibits analgesic, antipyretic and anti-inflammatory effects. Curcumin is a natural medicinal substance belonging to the group of polyphenols, showing anti-inflammatory effects and potentially anticancer properties [33,34]. In turn, ferulic acid, which belongs to the group of phenolic acids, shows antioxidant and anti-inflammatory activity [35,36].
A prerequisite for effective and beneficial therapy is the delivery of a biologically active agent to the appropriate site in the body and its release, preferably in a controlled manner [37]. One way to release the active ingredient in a controlled manner is by using carriers of active ingredients [38,39]. To date, the following have been used as carriers of the active substance: carbon materials [40], polymeric materials [41] and, increasingly, porous materials such as zeolites [42,43].
The purpose of the presented work was to assess the suitability and possibility of using hierarchical zeolites based on commercial zeolites such as MFI, FAU and BEA modified with polysaccharides as carriers of active substances: ibuprofen, curcumin, and ferulic acid.
## 2.1.1. Synthesis of Unmodified Hierarchical Zeolites Based on Zeolite MFI (ZSM-5), BEA (β) or FAU (Y)
The preparation of unmodified hierarchical zeolite MFI (ZSM-5), BEA (β) or FAU (Y) was based on dispersing weighed amount (0.75 g) of commercial zeolite of ZSM-5 (Acros Organics B.V.B.A., Geel, Belgium), β (Alfa Aesar, Ward Hill, MA, USA) or Y (Alfa Aesar, Ward Hill, MA, USA) type in a mixture containing 150.00 g of distilled water, 1.875 g of ammonia (StanLab, Lublin, Poland), 90.00 g of ethanol (StanLab, Lublin, Poland), and 0.525 g of cetyltrimethylammonium bromide (CTABr) (Fluka Analytical, Buchs, Switzerland). This process was carried out in a polyethylene bottle, for a period of 30 min, at 65 °C, using an ultrasonic bath. After 30 min, 0.84 g of tetraethyl orthosilicate (TEOS) (Aldrich Chemistry, Saint Louis, MO, USA) was added to the solution as a source of silicon. The entire solution was then stirred on a magnetic stirrer for 4 h at 65 °C.
After this time, the precipitate obtained was filtered on a glass funnel using a filter paper, washed with a mixture of distilled water and ethyl alcohol in a volumetric ratio of 1:1, and left to dry in air at room temperature. After drying, the precipitate was calcined in order to remove the templating agent (CTABr). The calcination was carried out for 5 h at 550 °C.
## 2.1.2. Synthesis of Hierarchical Zeolites Modified with Inulin
The synthesis of hierarchical inulin-modified zeolites based on commercial zeolites such as MFI, BEA, or FAU initially proceeded in a manner similar to that of the synthesis of pure hierarchical zeolites. However, inulin (Chemat, Gdańsk, Poland) was added as a modifying compound in the amount of 0.05 g together with 0.84 g of the silicon source (TEOS). Thereafter, the course of the reaction was similar. An extraction process was used to remove template (CTABr) from inulin-modified materials. For the extraction process 0.50 g of the obtained material was mixed with 50.00 mL of ethanol and 0.50 mL of HCl solution. The whole mixture was stirred on a magnetic stirrer for 24 h at 65 °C using a reflux condenser. The precipitate was filtered on a glass funnel equipped with filter paper, washed with ethanol, and dried in air at room temperature.
## 2.1.3. Synthesis of Hierarchical Zeolites Modified with Hyaluronic Acid
The process of synthesis of hierarchical zeolites based on commercial zeolites type ZSM-5, Beta, or Y, modified with hyaluronic acid, was similar to that of hierarchical materials modified with inulin (Section 2.1.2), only when adding 0.84 g TEOS, 0.05 g of hyaluronic acid (Chemat, Gdańsk, Poland) was added instead of inulin. The remaining course of the synthesis of hyaluronic acid-modified materials was analogous to that described above.
## 2.1.4. Synthesis of Hierarchical Zeolites Modified with Heparin
The process of synthesis of hierarchical zeolites based on commercial types of zeolites such as ZSM-5, β, or Y, modified with heparin, was analogous to the synthesis of materials described in Section 2.1.2 and Section 2.1.3, only during the addition of 0.84 g of TEOS, 0.05 g of heparin (Biosynth Carbosynth, Staad, Switzerland) was added instead of inulin or hyaluronic acid. The remaining course of synthesis of heparin-modified materials, was analogous to those described above.
## 2.2. Designation of Materials Used in the Work
Table 1 shows the designations of the materials synthesized and characterized in this paper.
## 2.3. Characterization of the Obtained Hierarchical Zeolites
The hierarchical zeolites synthesized were subjected to physicochemical characterization by the following techniques:Elemental analysis;X-ray diffraction (XRD);Low-temperature nitrogen adsorption/desorption measurements;Transmission electron microscopy (TEM)
## 2.3.1. Elemental Analysis
The determination of the elemental composition of the synthesized catalysts was performed in the Department of Chemistry, Adam Mickiewicz University in Poznań, with the use of the Vario EL III (Elementar Analysensysteme GmbH, Langenselbold, Germany) elemental analyzer apparatus. The measurement method involves the catalytic combustion of the sample (10–20 mg) at 1200 °C and analysis of the composition of combustion gaseous products, which is based on differences in their thermal conductivity.
## 2.3.2. XRD—X-ray Diffraction
X-ray diffraction studies were performed using a Bruker AXS D8 Advance (Bruker, Billerica, MA, USA) diffractometer with a Johannson monochromator and a LynxEye stripline detector. The CuKα radiation source generated a wavelength of λ = 0.154 nm. Measurements were made in the low angle range of 2ϴ = 0.6–8.0° (with 0.02° accuracy) and in the high angle range of 2ϴ = 6.0–60.0° (with 0.05° accuracy).
## 2.3.3. Low-Temperature Nitrogen Adsorption/Desorption Measurements
The measurements were performed using a Quantachrome Autosorb iQ apparatus (Quantachrome Instruments, Boynton Beach, FL, USA). Prior to the actual measurement, the samples were degassed under vacuum at 110 °C for 24 h. The sorption isotherms were obtained at −196 °C, in the relative pressure range p/p0 from 0.02 to 1.00.
## 2.3.4. Transmission Electron Microscopy (TEM)
Microscopic images of the materials were taken using a transmission electron microscope JEOL JEM-1200 EX II (JEOL, Akishima, Tokyo, Japan) operating at 80 kV.
## 2.4. Active Substances Loading
250 mg of the carrier (functionalized hierarchical material) was poured with 5.00 mL of ethanol ($99.8\%$, POCh) and then 150 mg of the active substance (ibuprofen, curcumin or ferulic acid) were added. The suspension was stirred on a magnetic stirrer for 24 h. After this time, the whole was filtered and the product obtained was air-dried. Once the loading of the active substance to the hierarchical materials was completed, the loading percentage of the active substance on the carrier used was calculated (% LOAD). The efficiency of the loading of the active substance in the hierarchical zeolite structure was calculated on the basis of Equation [1]. [ 1]% LOAD=initial amount of active substance gmass of the complex active substance+carrierg×$100\%$.
Equation [1] is a formula for the calculations of the percentage of active substance loading on the carrier [44].
## 2.5. Release Profiles of Active Substances
20 mg of the carrier loaded with an active substance was weighed into the vial and the mixture of 20.00 mL of phosphate buffer (pH 5.8) and 5.00 mL of permeation promoter (glycerin or ethanol) was added. The process was carried out at room temperature for 24 h with absorbance measurements of the released active substance performed every 30 min for the first 2 h and then every 1 h. The release rate of the active substance was determined by UV-Vis measurements using a Varian Cary 50 Bio UV-Vis spectrophotometer. The characteristic wavelengths corresponding to the maximum absorbance of the used active substances in a given solvent were as follows: (a) ibuprofen: 272 nm; (b) curcumin: 425 nm; (c) ferulic acid: 319 nm. The percentage of the release of active ingredients from carriers was calculated with Equation [2] [45]:[2]% release=ApAwmwmg x CwVwml1DwVpmlmpmg×$100\%$ where: Ap—absorbance of the sample (a.u.), Aw—absorbance of standard (a.u.), mw—a mass of standard (mg), mp—a mass of active substance contained in the sample (mg), Cw—purity of standard (a.u.), Dw—dilution of standard (a.u.), Vw—the volume of standard solution (ml), Vp—the volume of acceptor fluid (mL).
Equation [2] is the formula to calculate the percent of release of active substances from the carrier [45].
## 2.6. Leaching Tests
Leaching tests for modifying agents (polysaccharides) were performed in the case of all the materials obtained. The following procedure was applied: 20 mg of polysaccharide-modified support was weighed in a glass vial, a mixture of 20.00 mL of phosphate buffer (pH 5.8) and 5.00 mL of glycerol (permeation promoter) was added. It was stirred for 24 h. After this time, materials were filtered, dried and characterized using elemental analysis.
## 3.1. Elemental Analysis
To determine the exact qualitative composition of the hierarchical zeolites obtained, an elemental analysis was performed.
The percentages of nitrogen, carbon, hydrogen, and sulfur in the hierarchical zeolites synthesized, which were evaluated by means of elemental analysis, are shown in Table 2. It was observed that the percentages of nitrogen are significantly higher for zeolites modified with heparin and hyaluronic acid when compared to the pure hierarchical materials. This may be due to the fact that heparin and hyaluronic acid have nitrogen atoms in their structure. At the same time, it confirms the effectiveness of modification of the obtained materials with these molecules. Additionally, an increase in the percentage of C and H atoms was observed in comparison to that for commercial and hierarchical unmodified materials. This is due to the fact that during the synthesis of these materials modifying agents were used, i.e., inulin, heparin and hyaluronic acid which are organic molecules, giving the obvious rise in the content of C and H atoms.
Leaching tests were carried out to verify whether leaching of modifiers (polysaccharides) into the acceptor fluid may occur during the release process. The results obtained on the basis of elemental analysis (Table 2) indicate that the content of C, H, N and S in the tested materials after 24 h of mixing with acceptor fluid (phosphate buffer + glycerol) does not change significantly. It can be estimated that leaching does not exceed $2\%$, which indicates that the molecules of the modifying agents are quite firmly bound to the zeolite matrix.
## 3.2. XRD—X-ray Diffraction
One of the main methods for identifying nanometer-sized objects, such as self-organized structures, is X-ray diffraction (XRD). XRD is mainly used to determine the structure of the substance under study. Therefore, when testing the surface of substances, the XRD method complements the information obtained using transmission microscopy. It also enables the observation of phase transitions and catalytic reactions taking place on the tested surface. It is especially used in the case of heterostructures and multilayered systems, concerning layers of thickness up to nanometers. Obviously, XRD is not a technique that allows complete characterization of porous materials; therefore, to evaluate the physicochemical properties of the materials obtained based on commercial zeolites such as MFI (ZSM-5), BEA (β), and FAU (Y) in addition to the XRD method, other tests were also carried out.
For the materials synthesized in this work, intense and broad reflections at 2θ~1.5–2.5° were recorded in all diffractograms taken in the low angle range (Figure 2A–C), which confirms the acquisition of additional mesoporous structure in the obtained catalysts. In the above-mentioned diffractograms in the low-angle range, the occurrence of additional reflections can also be observed, at an angle of 2θ < 2.5°, which indicates a more ordered structure of the obtained hierarchical zeolites. Similar results were described previously by Feliczak-Guzik and co-workers and Ramezani and co-workers [44,46]. Comparing the diffractograms of the materials before and after extraction, one can observe that the diffractograms of the materials after extraction are characterized by more intense (sharper/less stretched) reflections at the angle 2θ~1.5–2.5° The interplanar spacing is a result of the statistical distribution of geometrically disordered pores.
On the other hand, the diffractograms in the high angle range obtained for the synthesized materials (Figure 3A–C) in most cases confirmed the preservation of the crystal structure of the used microporous commercial zeolites of MFI (ZSM-5), BEA (β), and FAU (Y) types. Only in the diffractogram obtained for hierarchical zeolites based on FAU zeolite modified with inulin and hyaluronic acid (Figure 3C) and for the material based on zeolite ZSM-5 modified with hyaluronic acid (Figure 3A), after the extraction process, it was noticed that the crystal structure of commercial zeolite was not preserved, indicating destruction of the crystal structure of the starting materials or the amorphization of the surface to extended levels resulting from the performed modification process.
In summary, all the low-angle diffractograms of the obtained catalysts, presented below, confirm the obtaining of additional secondary porosity (reflection 2θ~1.5–2.5°). This phenomenon is observed when the template is used to construct the ordered mesopores [47]. On the other hand, thanks to the diffractograms in the high angle range, the structure preservation of the starting commercial zeolites was confirmed in most cases.
## 3.3. Nitrogen Adsorption/Desorption Isotherms
From sorption studies, textural properties can be determined for newly synthesized hierarchical materials based on commercial zeolites such as MFI (ZSM-5), BEA (β), and FAU (Y), namely specific surface area, total pore volume, micropore volume, mesopore volume, average pore size, and pore size distribution.
On the basis of nitrogen adsorption/desorption isotherms (Figure S1 in Supplementary Materials) for commercial materials, viz: BEA (β) and FAU (Y), type I isotherms may be observed according to the International Union of Pure and Applied Chemistry (IUPAC), which is characteristic of microporous materials, was reported [48]. The commercial MFI (ZMS-5) zeolite is characterized by adsorption/desorption isotherms of mixed type I and IV, the latter being characteristic isotherm for mesoporous materials, which would indicate that it was not a typical microporous material already at the time of purchase.
In the case of the modified hierarchical materials, the presence of a mixture of isotherms, both type I and type IV, was noted. The type IV isotherm is characterized by the presence of three ranges:in the first one, there is a linear increase of adsorbed nitrogen while the pressure p/p0 has a low value; this correlates with monolayer adsorption deposited on the pore walls;in the second range, there is a rapid increase in adsorbed nitrogen for medium pressures p/p0, which is a capillary condensation effect occurring in the mesopores;in the third range, there is a gradual, linear increase in p/p0 in the high-pressure region, which results in nitrogen adsorption on the outer surface of the material, i.e., in the spaces between the pores.
The obtained results confirm the obtaining of hierarchical materials with secondary porosity, in the mesopore range. It can also be observed that, depending on the type of polysaccharide used to modify the pure zeolite, there is a slightly different increase in the total amount of adsorbed nitrogen, which may indicate an increase in the textural properties. For modified materials in the high relative pressure region, a rapid increase in adsorbed nitrogen can also be observed, indicating the formation of a secondary porosity called textural [49,50]. Similar results were described earlier by Ramezani and co-workers [46].
The very narrow pore size distribution is characteristic for commercial microporous materials of type MFI (ZSM-5), BEA (β), and FAU (Y). For all three types of materials, the largest and virtually the only pore size distribution is for pores with a width of 0.5 nm, which is within the size limit assigned to microporous materials. A narrow pore size distribution is also evident for synthesized polysaccharide-modified materials, but the pore widths for inulin, heparin, and hyaluronic acid modified materials range from about 2.5 nm to about 12 nm. For hierarchical materials based on MFI type zeolite (ZSM-5) modified with hyaluronic acid and inulin a larger pore size distribution can be observed, with a pore width of about 2.5 nm compared to heparin modified materials. A large pore size distribution can also be observed for inulin-modified materials, with a pore size of about 8.0 nm. On the other hand, for the materials based on zeolite BEA (β), the distribution of the pore size is similar for the three modified materials. For the materials based on the FAU (Y) zeolite, the pore size distribution varies from about 2.5 nm to 4.0 nm.
The selected textural properties of the hierarchical materials based on the commercial zeolites MFI (ZSM-5), BEA (β), and FAU (Y) are shown in Table 3.
The polysaccharide-modified and unmodified hierarchical zeolites exhibit properties typical of materials having porosity in the mesopore range. These include:high specific surface area, which varies from about 400 to 830 [m2/g];high porosity, in which the total pore volume is as high as 0.66 [cm3/g];homogeneous pore size, where the pore width ranges from 3.0 to 3.5 nm.
Unmodified materials had the largest specific surface area (Table 3). Polysaccharide-modified materials, on the other hand, showed similar specific surface area, ranging from 405 to 641 m2/g. The smallest total pore volume, and the largest micro pore volume, was observed for commercial materials such as MFI (ZSM-5), BEA (β), and FAU (Y). However, for the materials synthesized in this study, the presence of a high total pore volume, low micropore volumes, and increased mesopore volumes was observed compared to the initial microporous materials, which indicates that a hierarchical structure of the obtained materials was obtained.
In conclusion, based on the textural properties of the materials obtained (Table 3), the presence of secondary porosity (mesoporosity) can be confirmed for both polysaccharide-modified and unmodified materials.
## 3.4. Transmission Electron Microscopy (TEM)
Images taken by transmission electron microscopy (TEM) for polysaccharide-modified materials are shown in Figure S2 (supporting information). For all the materials obtained, it can be observed that all the oval-shaped particles are very loose and porous. These particles, 10–20 nm in size, are grouped into irregularly shaped clusters ranging from 100 to 400 nm in size.
## 3.5. Active Substances Loading and Release Profiles
The active substances loading into hierarchical zeolites was calculated using Equation [1]. The results of the analysis of ibuprofen, curcumin, or ferulic acid loading in the zeolite carrier are included in Table 4.
The loading percentage of all active substances ranges from 39–$79\%$. The loading percentage of ibuprofen and ferulic acid in a given carrier depends on the specific surface area of the material and its mesoporous volume, that is, the higher the specific surface area and the mesoporous volume, the higher the loading percentage. However, that is not the case for curcumin, where the loading percentage is quite similar for each carrier tested, regardless of its textural parameters. This may be caused by the steric hindrance created by the curcumin molecule, which is the largest molecule among all active substances tested and thus it may be difficult for it to penetrate deeper regions of pores. Furthermore, it may be observed that when comparing ibuprofen and ferulic acid, in most cases higher values of % LOAD were obtained for the latter molecule. An explanation for this may be the highest polarity of ferulic acid among all molecules tested by us, for which the logP is 1.57, while for ibuprofen and curcumin the value of this parameter is 3.97 and 3.29, respectively. The trend due to differences in the polarity of the active substance molecules is most evident in the case of unmodified zeolites, while for polysaccharide-functionalized carriers it becomes somewhat less apparent, probably due to the additional influence of the steric factors induced by polysaccharide molecules.
During presented studies the release profiles of three active substances, such as ibuprofen, curcumin, and ferulic acid from polysaccharide-modified hierarchical zeolites into the acceptor fluid (phosphate buffer, pH 5.8) were evaluated. Acceptor fluid, also called medium, is a liquid into which transmembrane diffusion of the active substance from the formulation under study takes place. The selection of the acceptor fluid should be guided by the measure of its similarity to the physiological conditions (temperature, pH value) of the skin. Note that the pH value of healthy skin is in the range of 4.5–6.5 [51]. Therefore the phosphate buffer with pH 5.8 was selected during our studies.
Additionally, glycerin was used as a permeation promoter and in the case of ferulic acid also ethyl alcohol.
Glycerol and ethanol were used as permeation promoters. These are chemicals that increase the penetration of the active ingredient through the skin. They can increase permeation of active substances by removing the hydrolipidic layer and partially dissolving the lipids of the intercellular cement of the epidermis [52,53,54]. To determine the release profile of ferulic acid two permeation promoters were used, since satisfactory results were not obtained in the glycerin-infused acceptor fluid.
UV–Vis spectrophotometry enabled the determination of the profile of release of bioactive substances from the carrier into the acceptor medium. The result of the release of the active substance from hierarchical materials is a change in its concentration in the acceptor solution; hence the amount of the released active substance may be assessed by measuring the change in absorbance over time, according to the Lambert-Beer law. In addition, the release process was conducted using a multipoint assay, which provided information on changes in the amount of released active substance at several time points.
The in vitro release profiles of the active substance are presented as a time-dependent curve of the percentage release of the active substance. The results of the controlled release of the active substances from hierarchical zeolites based on commercial zeolites are shown in Figure 4, Figure 5, Figure 6 and Figure 7.
Based on the results of the release of ibuprofen from hierarchical zeolites (Figure 4), it can be concluded that all polysaccharide-modified materials showed higher release rates compared to unmodified materials. Previously, the same tendency was observed after the modification of the surface with amine groups, i.e., the structure of mesoporous molecular sieve of SBA-16-type modified with chitosan significantly affects the release rate of furosemide [55]. A correlation was observed between the release rate of ibuprofen and the type of polysaccharide used during the synthesis of hierarchical zeolites. The sample of BEA zeolite modified with heparin (2_B_h, surface area 611 m2/g and total pore volume of 0.46 cm3/g), showed the fastest ibuprofen release rate of 100 % after 8 h, while the release rate from the other materials depended on the structure of the commercial zeolite used during the preparation of the hierarchical zeolite. The trend in percentage release of ibuprofen from the zeolite used indicated a positive influence of heparin and inulin molecules, and was as follows:MFI-based hierarchical zeolite: 1_ZSM-5_i; 1_ZSM-5_h; 1_ZSM-5; 1_ZSM-5_khBEA-based hierarchical zeolite: 2_B_h; 2_B_i; 2_B_kh; 2_BFAU-based hierarchical zeolite: 3_Y_h; 3_Y; 3_Y_kh; 3_Y_i Furthermore, it was observed that the release of ibuprofen proceeded in two stages; some ibuprofen molecules were adsorbed on the outer surface of the materials. Their release occurred early in the course of the process. In contrast, molecules that were inside the pores of the hierarchical zeolites were slowly released into the acceptor fluid. Besides, the highest release rate for most materials was obtained for the heparin-modified samples. This suggests that the ibuprofen molecules in these materials were mainly adsorbed on their external surface, making them more accessible [56]. Moreover, heparin molecule is the smallest one among polysaccharides used, thus it does not block significantly the loading and releasing of the active substance from the pores of zeolites.
A large number of silanol groups located on the surface of the mesopores and at the entrance to micropores make zeolitic materials heterogeneously active in the interactions with the “guest” molecules. In this case the molecules of the active substance, i.e., ibuprofen, preferentially deposit inside the mesopores and at the entrance of micropores in the form of a thin film [57,58].
The curcumin release profiles of from modified hierarchical materials have been shown in Figure 5.
As observed, the release percentage of curcumin from the carriers under study is less than $5\%$. Such a low value may be due to the fact that the relatively large curcumin molecule, once deposited in the pores of the carriers, may have trouble desorbing from inside the pores. The peculiar behavior of the curcumin molecule could already be observed during the measurement of the loading percentage. The degree of this parameter was significantly lower than that of other active substances (Table 4). The obtained release profiles (Figure 5) may indicate that curcumin molecules, once deposited in the pores, become blocked due to a certain steric hindrance. In addition, it can also be observed that for MFI-based and BEA-based hierarchical zeolites the release percentage is slightly higher than for FAU-based zeolite. This may be due to the fact that in the case of the latter carrier, which has the highest proportion of mesopores (mesopore size: 3.4 nm, Table 3), during the introduction of curcumin, the molecules of this compound may have diffused deeper into the pore system and then may have been blocked there, also by the introduced polysaccharides. On the other hand, in the case of carriers with smaller mesopore sizes, that is, 3.0 and 3.2 for MFI-based and BEA-based zeolites, respectively (Table 3), due to the more difficult accessibility of the deeper portions of the pores, the curcumin adsorption may have occurred to some extent on the carrier surface and in the pore inlets. It is likely that this part of the loaded curcumin is first released in the case of these two zeolite materials (Figure 5b). Therefore, the release of curcumin from modified hierarchical zeolites based on commercial zeolites of MFI and BEA-type showed an initial burst-type release within the first 30 min of the process. A similar relationship was not observed for materials derived from the FAU-type commercial zeolite. This type of release may be related to the surface-bound curcumin molecules on the surface of the carriers used [59].
Ferulic acid release studies were carried out using acceptor fluid at pH 5.8 with the addition of two different permeation promoters, that is, ethanol or glycerol. The percentage of ferulic acid released from the modified hierarchical zeolites is pictured in Figure 6 (glycerin) and Figure 7 (ethanol).
## 4. Conclusions
In the present work, unmodified and modified hierarchical materials with polysaccharides such as inulin, hyaluronic acid, and heparin, with secondary porosity (hierarchical zeolites), based on commercial materials such as MFI (ZSM-5), BEA (β) and FAU (Y) were obtained. Thorough physicochemical characterization of all the hierarchical materials obtained was carried out. In addition, they were also applied as platforms for controlled loading and release of active ingredients with anti-inflammatory activity, namely ibuprofen, curcumin, and ferulic acid. It has been proved that the degree and rate of release of the active substance depends on the matrix of the porous material (the highest percentage of release, close to $100\%$, was obtained for ibuprofen loaded on heparin-modified BEA-based hierarchical zeolite). The introduction of polysaccharides containing extra OH groups into zeolitic structures allows for acquisition of additional sites available for binding molecules of active substances, as shown during our studies. In most cases, polysaccharide-modified zeolites seem to be a better platform for drug delivery than their unmodified counterparts. Significant influence of the type of the polysaccharide on the loading and release profile of curcumin, ibuprofen, and ferulic acid has also been demonstrated: in most cases heparin seems to be the most influenceable modifying agent.
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|
---
title: Increasing Bioavailability of Trans-Ferulic Acid by Encapsulation in Functionalized
Mesoporous Silica
authors:
- Gabriela Petrișor
- Ludmila Motelica
- Denisa Ficai
- Cornelia-Ioana Ilie
- Roxana Doina Trușcǎ
- Vasile-Adrian Surdu
- Ovidiu-Cristian Oprea
- Andreea-Luiza Mȋrț
- Gabriel Vasilievici
- Augustin Semenescu
- Anton Ficai
- Lia-Mara Dițu
journal: Pharmaceutics
year: 2023
pmcid: PMC9968071
doi: 10.3390/pharmaceutics15020660
license: CC BY 4.0
---
# Increasing Bioavailability of Trans-Ferulic Acid by Encapsulation in Functionalized Mesoporous Silica
## Abstract
Two types of mesoporous materials, MCM-41 and MCM-48, were functionalized by the soft-template method using (3-aminopropyl)triethoxysilane (APTES) as a modifying agent. The obtained mesoporous silica materials were loaded with trans-ferulic acid (FA). In order to establish the morphology and structure of mesoporous materials, a series of specific techniques were used such as: X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Brunauer-Emmet-Teller (BET), Fourier Transform Infrared Spectroscopy (FTIR) and thermogravimetric analysis (TGA). We monitored the in vitro release of the loaded FA at two different pH values, by using simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). Additionally, *Staphylococcus aureus* ATCC 25923, *Escherichia coli* ATCC 25922, *Pseudomonas aeruginosa* ATCC 27853 and Candida albicans ATCC 10231 were used to evaluate the antimicrobial activity of FA loaded mesoporous silica materials. In conclusion such functionalized mesoporous materials can be employed as controlled release systems for polyphenols extracted from natural sources.
## 1. Introduction
As many bioactive substances can often exhibit unwanted effects at high concentrations, while only scanty drug concentrations with low efficacy are arriving at target tissue, various encapsulation methods and drug carriers have been developed [1,2].
Through the morphological control and the functionalization of inorganic nanoparticles, various advances in science have been developed so that delivery systems are more efficient in the transport of different drugs [3,4,5,6,7,8]. Mesoporous silica nanoparticles (MSNs) represent a new research opportunity for the development of controlled release systems [4,9]. The improvement of the transport systems of active substances in the body led to the development of new drug delivery systems. In the development of these systems, the goal is to keep the drug dose under control, a slow release, targeted release to the area of interest [10,11,12]. Due to the physico-chemical properties of mesoporous silica (very high pore numbers and specific surface), it allows high loading capacity, good compatibility and easy functionalization [13].
Starting from inorganic precursors, mesoporous silica can have different structures, such as MCM (Mobile Composition of Matter), SBA (Santa Barbara Amorphous), TUD (Technische Universiteit Delft), HMS (Hollow Mesoporous Silica) or MCF (Meso Cellular Form) [14,15]. The MCM family was the first type of mesoporous material synthesized since 1992, which include among other silica types, the hexagonal mesoporous MCM-41 and the cubic mesoporous arranged MCM-48 [16]. The major difference between the two materials is related to the arrangements of the pores. If MCM-41 has the pores arranges uniaxial, the MCM-48 has the pores arranged in a three-dimensional fashion and thus, the release of the active components will be unidirectional for MCM-41 or in all directions for MCM-48 [17].
Surface functionalization of mesoporous silica is one of the methods by which the interaction between drugs and mesoporous silica is improved for better efficiency in targeted delivery [18,19]. Covalent bonding between functional groups and silica can be achieved by grafting and co-condensation, post-synthesis and direct incorporation methods [20,21,22]. The most common functionalization methodology of the mesoporous silica surface are made with groups such as: amine (3-aminopropyl)triethoxysilane, thiol (3-mercaptopropyl)trimethoxysilane and sulfonic acid (trimethyl[propyl]ammonium chloride) [23,24,25,26].
The structure of mesoporous silica allows it to be loaded with drugs, polyphenols or more complex natural agents such as natural extracts [27,28,29]. Polyphenols are given special attention due to their pharmacological properties and because they are extremely numerous found in various plants, fruits and vegetables [30,31,32,33,34] while their biological activity is very wide. The porous structure of the silica-based materials allows a high loading capacity with various drugs or bioactive substances (e.g., antimicrobials, polyphenols) and further facilitate the controlled release by gradual unloading into the target tissue. By achieving this slower release of the drugs from the pores of the silica particles, a steady concentration of the released substance can be maintained, ensuring a reliable biological activity for longer times [35]. Due to the proven potential of biologically active agents, such as specific polyphenols, in preventing or mitigating the onset of chronic diseases, considerable interest has been shown in the development of dietary supplements containing polyphenols and/or consumer products rich in polyphenols [36,37].
Polyphenols are extremely important components of the human diet due to their special properties such as antioxidant activity, free radical scavenging abilities and the ability to function as antibiotics (exerting anti-diarrheal, anti-ulcer, and anti-inflammatory effects) and to alleviate tissue damage induced by oxidative stress associated with chronic diseases [38,39,40].
Ferulic acid (FA) is part of the phenolic acid class and is a derivative of cinnamic acid frequently found in numerous plants [41,42]. One of the most important roles of FA is that it has a strong antioxidant activity, but it has multiple pharmacological activities such as antimicrobial, antibacterial, anticancer, anti-inflammatory, antidiabetic, etc. [ 43,44,45,46,47,48]. Ferulic acid is a powerful antioxidant ingredient found in many vegetables, fruits and grains. It absorbs UV rays and protects the skin from the harmful effects of ultraviolet radiation, especially erythema and skin irritations. If it is used together with vitamin C and vitamin E, it potentiates the antioxidant effects, the removal of their pigment spots and the stability of the cosmetic product formula.
The aim of this study was to synthesize mesoporous materials, namely MCM-41 and MCM-48, and to functionalize them by grafting with amino groups following the reaction with (3-aminopropyl)triethoxysilane (APTES). The obtained materials were loaded with trans-ferulic acid to observe the loading capacity of mesoporous silica. After obtaining all the materials, they were investigated to determine the pore volume and surface area with Brunauer-Emmet-*Teller analysis* and the structure of the materials with X-ray diffraction (XRD). The morphology of the synthesized, functionalized and loaded materials was analysed through Scanning Electron Microscopy (SEM), and the identification and estimation of the loading quantity with trans-ferulic acid was determined by Fourier Transform Infrared Spectroscopy (FTIR) in connection with thermogravimetric analysis (TGA). The materials loaded with trans-ferulic acid were subjected to a in vitro release study in two simulated biological fluids with different pH to observe their release profiles. The FA loaded mesoporous silica materials were tested to evaluate the antimicrobial activity on four strains *Staphylococcus aureus* ATCC 25923, *Escherichia coli* ATCC 25922, *Pseudomonas aeruginosa* ATCC 27853 and Candida albicans ATCC 1023. The natural agents, such as polyphenols, could be good candidates in the treatment of infections especially when the infections involve resistant bacteria and common antibiotics are not efficient. Moreover, these silica particles loaded with polyphenols have an additional advantage because the residues (faces) does not generates microbial resistance.
## 2.1. Materials
Mesoporous silica was prepared starting from tetraethyl orthosilicate (TEOS) as silica precursor, cetyltrimethylammonium bromide (CTAB) as template agent, ammonia (NH3) and absolute ethanol, all from Merck (Darmstadt, Germany). According to the ratio between the components, two mesoporous systems (MCM41 and MCM48) were obtained as we previously presented in [35,49]. In this paper, a special attention was paid to the influence of the functionalisation and thus, both types of MCM materials were functionalized with (3-aminopropyl)triethoxysilane (APTES) purchased from Sigma Aldrich (St. Louis, MO, USA), while the loading of the mesoporous materials was done with trans-ferulic acid (FA, ≥$98\%$) solution in acetone (both from Sigma Aldrich).
Release study was performed in simulated intestinal and gastric solutions obtained by mixing sodium chloride (NaCl) purchased from Sigma Aldrich, sodium hydroxide (NaOH, 1 N), hydrochloric acid (HCl, 2 N) purchased from S.C. Silal Trading SRL (București, Romania) and potassium dihydrogen phosphate (KH2PO4, ≥$98\%$) from Carl Roth (Karlsruhe, Germany).
All the substances were used without further purification in all performed experiments together with distilled water (dw).
All strains tested in this study were obtained from the Microorganisms Collection of the Department of Microbiology, Faculty of Biology & Research Institute of the University of Bucharest.
## 2.2. Equipment
Mesoporous materials, of MCM-41 and MCM-48 types, and APTES functionalized mesoporous silica, as well as the trans-ferulic acid loaded mesoporous samples, were characterized by modern, usual techniques. X-ray powder diffraction (XRD) diffractograms were recorded by using CuKα radiation with a Panalytical X’Pert Pro MPD instrument. A Thermo IN50 MX instrument was used to record the FTIR spectra in attenuated total reflectance mode (ATR) for all the samples. The recorded spectra were used to carried out the study of the structural features of the MCM supports as well as the drug delivery systems. BET analysis (the N2 adsorption isotherms) was performed on a NOVA 2200e Gas Sorption Analyzer (Quantachrome, Boynton Beach, FL, USA), at 77.35 K and relative pressure p/p0 = 0.005–1.0. Before measurements, the materials were outgassed for 4 h at 110 °C under vacuum. The surface morphology of the samples was examined using a QUANTA INSPECT F electron microscope equipped with a field emission gun and an energy dispersive (EDS) detector, on samples covered with silver. Thermogravimetric analyses were recorded using a Netzsch 449C STA Jupiter instrument in the 20–900 °C temperature interval, in an open crucible, under a dynamic atmosphere of dry air (50 mL/min). A heating rate of 10 °C/min was employed.
The controlled release of trans-ferulic acid from the obtained mesoporous materials was evaluated with an Agilent 1260 Infinity High Performance Liquid Chromatograph equipped with Diode Array Detector (HPLC-DAD). Ultrapure water and acetonitrile (HPLC grade, Sigma Aldrich) were used as mobile phase and separation was performed on an Aqua C18 column (250 × 4.6 mm, 5 μm).
## 2.3. Preparation and Functionalization of Mesoporous Materials
Both mesoporous materials, MCM-41 and MCM-48, used as a support for functionalization and further loading, were synthesized using the soft template method starting from proper ratio of TEOS and CTAB (Figure 1). The synthesis was carried out under the same conditions, the working conditions being described in our previous work [49].
The functionalization of mesoporous silica was done following the method [50], using (3-aminopropyl)triethoxysilane as coupling agent. One gram of each mesoporous material (MCM-41 and MCM-48), was dried in the vacuum drying oven at a temperature of 23 °C for 3 h. After drying, 100 mL ethanol was added and the suspensions were sonicated for one hour. 125 μL of APTES was added to each suspension and left to reflux for 24 h and sonicated for one hour. The obtained suspensions were filtered and left to dry.
## 2.4. Adsorption of Trans-Ferulic Acid
To load the obtained mesoporous materials, a saturated solution of 0.4 g of trans-ferulic acid (FA) in 4 mL of acetone was prepared. 1 g of mesoporous material was added in a glass vessel and kept under vacuum, 2 mbar, for 30 min. After this period of time, the saturated solution of trans-ferulic acid was added stepwise (in three successive steps) to enter the pores of the material. After drying at 60 °C mesoporous materials loaded trans-ferulic acid were obtained as presented in Table 1. In all cases, the FA was loaded in a 0.4:1 ratio (w/w) to the mesoporous support materials.
## 2.5. In Vitro Release Study
The release profiles of the materials loaded with trans-ferulic acid were evaluated in two simulated biological fluids, simulated gastric fluid (SGF, pH = 1.2) and simulated intestinal fluid (SIF, pH = 6.8) [35,51]. The release of the trans-ferulic acid from the mesoporous materials (functionalized or not with APTES) was done in SGF and SIF (140 mL) solution considering 50 mg mesoporous supports loaded with trans-ferulic acid. Throughout the study, the solutions were kept under magnetic stirring at 37 ± 2 °C. Samples were taken at predetermined time intervals and FA concentration was quantified by high performance liquid chromatography.
## 2.6. Antimicrobial Activity
Staphylococcus aureus ATCC 25923, *Escherichia coli* ATCC 25922, *Pseudomonas aeruginosa* ATCC 27853 and Candida albicans ATCC 10231 were used to evaluate the antimicrobial activity of silica mesoporous materials.
## 2.6.1. Quantitative Determination of Antimicrobial Activity
The minimum inhibitory concentration (MIC) evaluation was made by using the decimal microdilution method in a liquid medium: Nutrient Broth for bacterial species and Sabouraud for fungal species. In this sense, suspensions of microbial cells are made in a sterile physiological buffer (PBS) using 18–24 h cultures, reaching a standard density of 1.5 × 108 CFU/mL (colony forming units/mL) for bacterial species, respectively 3 × 108 CFU/mL for Candida sp. Decimal dilutions are made from each nanoparticle suspension, followed by inoculation with a standard microbial suspension (medium liquid volumetric ratio: microbial suspension = 10:1). Following the same steps, the blank/control (C) samples are performed: sterility and microbial growth. The 96-well plates are incubated at 37 °C for 24 h. The determination of MIC values was performed both by macroscopic observation and by reading at 620 nm (the suspensions are transferred to a sterile plate because the initial plate contains precipitate/NPs deposited on the bottom of the well and would interfere with the absorbance of the medium) [52,53,54].
## 2.6.2. Semi-Quantitative Evaluation of Microbial Adherence to an Inert Substratum
The evaluation of the inert substrate adhesion potential of the tested strains was carried out by the crystal violet staining method. After 24 h of incubation, 96-well plates are washed thrice with phosphate buffered saline solution and fixed with cold CH3OH (5 min). After its removal, the dried plates are stained with $1\%$ crystal violet solution (15 min). The excess dye is removed by washing, and in order to determine the MAIC values (minimum adhesion inhibition concentration), the dye included in the cells adhered to the walls of the well is dissolved with $33\%$ acetic acid. Spectrophotometer readings will be performed at 490 nm with the BioTek Synergy™ HTX ELISA Multi-Mode Reader (BioTek, Winooski, VT, USA) [52,53,54].
## 3. Results and Discussions
All the materials, including pure supports as well as the loaded mesoporous materials were characterized by the appropriate physico-chemical methods.
## 3.1. X-ray Diffraction
All four diffraction patterns recorded at low angles on the mesoporous MCM-41 materials, Figure 2, present the typical arrangement for these materials. The strong diffraction peak from 2.43°, is attributed to the [100] crystallization plane, while the other less intense peaks correspond to the [110], [200] and [210] crystallization planes, characteristic to the hexagonal mesoporous MCM-41 structure. These peaks are consistent with literature data [55].
From the XRD data it can be seen that the functionalization of MCM-41 with APTES does not alter the ordered mesoporous structure of silica, but a slight shift and decrease in the intensity of the peak feature of the [100] crystallization plane is observed [56,57]. This is due to the formation of a silica layer bearing aminopropyl moieties on the surface and in the pores of the mesoporous material as a result of the hydrolysis and condensation reactions that take place during the functionalization reaction. At the same time, the pores of the mesoporous material decrease in size and this is also visible in XRD.
In addition, it is observed that the loading of MCM-41 and MCM-41_APTES materials with trans-ferulic acid, carried out under vacuum, does not alter the ordered mesoporous structure of the silica, but induces a considerable decrease in the intensity of the peaks and alters the shape of the peak characteristic for the [100] crystallization plane, due to the absorption of trans-ferulic acid. Due to the specific pattern of the XRD spectra it is expected that FA is mostly loaded inside the pores [35].
The X-ray diffractograms obtained for MCM-48 based materials, Figure 3, present the characteristic [211] peak at 2.52°, while the other three important peaks, [220], [420] and [332] are positioned at higher 2Θ values. This arrangement is characteristic to the cubic structure of MCM-48 [58]. The X-ray diffraction data obtained for MCM-48 materials functionalized with APTES, indicates a slight shift of the peak corresponding to the [211] crystallization plane [57,59] due to the formation of a silica layer on the surface and in the pores of the mesoporous material as a result of the reactions of hydrolysis and condensation occurring during functionalization reaction. At the same time, the pores of the mesoporous material decrease in size.
For the mesoporous materials that were loaded with ferulic acid, the XRD data indicates a considerable decrease in the intensity and the degree of crystallinity, in addition to the shift of the [220] and [211] characteristic peaks. All these information, the decrease in intensity, the crystallinity degree and the characteristic peaks shifting, may indicate the loading of polyphenols in the pores of the mesoporous material, but also a strong interaction between the two components.
## 3.2. Specific Surface Area—Brunauer-Emmet-Teller Adsorption Isotherms
Following the functionalization process of the mesoporous material MCM-$\frac{41}{48}$ with APTES, it can be seen from BET data (Table 2) that the specific surface area slightly decreases from 1365 m2/g for MCM-41, to 1014 m2/g for the material MCM-41_APTES and from 1582 m2/g for MCM-48, to 1555 m2/g for the material MCM-48_APTES as a result of the deposition of APTES on the surface of the mesoporous nanoparticles, which causes the material’s pores to become narrower as a consequence of the functionalization. The overall surface area of these mesoporous materials has two components, the external surface area of the spherical particles, with a small contribution—less than 1 m2/g, and the internal surface area of the cylindrical pores, which assure the very high surface area. Because during the loading process, the FA will enter inside the pores of the material, filling them, the BET determined specific surface area will drastically decrease, roughly by a factor of 3. As a consequence of the FA loading, the pore size decrease, and some of them even disappear when the loading degree is high, therefore, the overall specific surface area decreases considerable.
In the case of MCM-41_APTES, the functionalization with APTES leads to a decrease of the determined BET surface area of 1.34 times, while after FA loading, in the case of MCM-41_APTES_FA the decrease is 3.36 times. In the case of MCM-48, a higher BET surface area is observed compared to MCM-41, but after functionalization the BET surface area for MCM-48_APTES slightly decreases (by 1.01 times). After loading with FA the BET surface area for MCM_48_APTES_FA decreases by 3.08 times.
Analysing the data from Table 2, we can conclude that the BET data are in good agreement with the XRD analysis, indicating that the FA is adsorbed inside the pores of the mesoporous materials.
## 3.3. Fourier Transform Infrared Spectroscopy
In order to characterize the structure, the FT-IR spectra of MCM-41, MCM-41_FA, MCM-41_APTES and MCM-41_APTES_FA (Figure 4). In the FTIR spectra of MCM-41 mesoporous materials the most important peaks of characteristic vibrations can be identified. The broad bands between ~3200–3400 cm−1 correspond to the associated silanol (Si-OH) surface groups and adsorbed hydrogen-bonded water molecules. The bands at 1239 cm−1 and 1057 cm−1 can be assigned to the stretching vibrations of the asymmetric Si-O-Si units, while the band from ~980 cm−1 is associated with silanol groups of MCM-41. The stretching vibrations of the symmetric Si-O-Si units can be identified as the band at 807 cm−1 and the peak from 440 cm−1 is generated by the Si-O-Si moiety’s deformation vibrations [60,61].
The characteristic peaks for Si-O-Si bonds from the APTES functionalized mesoporous material, shifted to slightly higher wavelengths, can be identified in the FTIR spectrum (Figure 4). In addition, the bands characteristic of the functional groups in the APTES structure are present. The presence in the FTIR spectra of the band at 2980 cm−1, characteristic of the three methylene (propyl) groups clearly proves the functionalization of MCM-41.
Unfortunately, the bands associated with NH2 cannot be identified because of the lower molar absorptivity and lower content. Additionally, the bending vibration bands characteristic of the N–H bond normally present around 714 cm−1, the symmetric bending vibration band characteristic of the –NH2 group and the stretching vibration band corresponding to the C–N bond normally present around the value of 1000–1200 cm−1 cannot be highlighted as a result of the overlap with the vibration/stretching bands characteristic of Si–O–Si bonds in the range 1000–1130 cm−1 and that of Si–CH2 stretching in the range of 1200–1250 cm−1 [58].
By loading MCM-41 and MCM-41_APTES with trans-ferulic acid, a series of new bands appear in the FTIR spectra (Figure 4), between 1300–1800 cm−1, being associated with the presence of FA into the mesoporous material. The peaks from 1684 cm−1 and 1700 cm−1 are associated with the stretching vibrations of the functional groups C=O and –OH, from FA. The peaks from ~1360 cm−1 and 1629 cm−1 (for MCM-41_FA) and 1387 cm−1 and 1630 cm−1 (for MCM-41_APTES_FA) are assigned to the stretching vibration of the bond between the aromatic nucleus and the carboxyl moiety in the FA [35]. The observed shifts can be explained considering the interactions which appears between the support and trans-ferulic acid.
In the FTIR spectra recorded for the MCM-48 type mesoporous materials (Figure 5), one can also observe the most important vibration peaks, characteristic for the Si-O-Si network, at ~1239 cm−1, 1054 cm−1, 978 cm−1, 810 cm−1 and 436 cm−1, the other features being similar with those of MCM-41 corresponding materials.
## 3.4. Scanning Electron Microscopy (SEM)
SEM micrographs (Figure 6) recorded for the mesoporous materials based on MCM-41 indicate that particles have variable size of hundreds of nanometres and a spherical morphology. When compared to the bare MCM-41, SEM images of MCM-41_FA and MCM-41_APTES_FA show some minor heterogeneities on the external surfaces of the mesoporous silica spheres, which can be attributed to the deposition of ferulic acid. Considering their incidence, and low content, it can consider that the ferulic acid (FA) is mostly deposited into the pores of the mesoporous materials. At high magnification (100,000×), it could be clearly observed that the SEM images of the MCM-41 sample were more translucent compared to the samples modified with APTES or loaded with ferulic acid (FA). These observations are in good agreement with the XRD and FTIR data, but also with the BET analysis [35].
SEM micrographs (Figure 7) recorded for the mesoporous materials based on MCM-48 indicate the presence of quasi-spherical silica particles with sizes in the 150–400 nm interval. In addition, similarly to MCM-41 based samples, we can consider that FA is mainly loaded inside the pores.
## 3.5. Thermogravimetric Analysis
The thermal stability of the samples, both consisting of mesoporous materials and materials loaded with polyphenols, was studied by thermogravimetric analysis. Firstly the TG curves for MCM-41 (Figure 8) and MCM-48 (Figure 9) permits the determination of some parameters like surface density of adsorbed H2O molecules or -OH moieties, calculated as indicated in [35,49] (Table 3). The recorded mass loss up to 200 °C (1st mass loss) is generated by the elimination of physically adsorbed H2O molecules, from particles surface or from inside the pores. The 2nd mass loss, in the interval 200–900 °C is generated by the condensation of silanol moieties (Si-OH) which leads to the silica densification.
The successful functionalization of the MCM samples with APTES is indicated by the different TG/DSC curves shape for the functionalized mesoporous materials MCM-41_APTES (Figure 8) and MCM-48_APTES (Figure 9) vs. bare support. The sample are presenting a small mass loss up to 305 °C because of elimination of water molecules adsorbed on the surface of nanoparticles and condensation of –OH moieties. The process is similar with that of bare MCM-41 or MCM-48, but with higher intensity, indicating a better adsorption capacity. APTES has a boiling point of 217 °C but no thermal effect is recorded up to 300 °C, indicating the successful bonding between MCM and APTES. After 305 °C the samples are suffering a degradation process, with the main mass loss being recorded up to ~700 °C. This is an oxidation process of the organic part as indicated by the strong exothermic effects with peaks at 313 and 309 °C respectively.
The MCM-41_FA and MCM-41_APTES_FA samples present a weak endothermic peak with onset at 170.3 and 168.2 °C respectively, assigned to the melting of loaded FA. Same type of endothermic effect is present on DSC curve of MCM-48_FA sample, with onset at 170.3. For the MCM-48_APTES_FA sample the effect is not visible, only a small inflexion point at 144.8 °C being detected. The lack of a clear melting effect and the smaller temperature recorded as an inflexion on DSC curve for the MCM-48_APTES_FA sample indicates stronger interactions between FA and the mesoporous support in this case. The relevant data are presented in Table 4.
The results indicate that the APTES functionalization has an impact especially on estimated load on MCM-48_APTES_FA vs. MCM-48_FA, decreasing the FA loaded amount from ~32 to ~$26\%$.
## 3.6. In Vitro Release Study
Release curves of FA from mesoporous materials and functionalized mesoporous materials are shown in Figure 10. As can be seen, all unmodified mesoporous materials loaded with FA had a fast release profile of up to 70–$80\%$ (within six hours) compared to mesoporous materials functionalized with amino groups and loaded with FA that had a slower release profile of up to 40–$60\%$ (within 24 h) [35]. From this difference between the release profiles, it can be clearly observed that the functionalization with aminopropyl groups considerably reduced the release rate of the active substance. Considering also, our previous works [35,49] it is obvious that the chemical surface modification with APTES or other silanization agents can be a good solution to induce a better tuning capacity of the release of these polyphenols for specific applications, including food supplements. As can be seen in the study, the release rate depends on the interactions of the functional group with the substance, which means that the use of different silanization agents bearing (-NH2, -COOH, -SH) could be exploited in tuning the delivery characteristics of the trans-ferulic acid [62]. The functionalization of the mesoporous materials with aminopropyl moieties has an important impact on both the release profile and rate over the first six hours. It can see that the release is slightly increasing over this period of time and this can be, most probably explained by the development of strong hydrogen bonds between the NH2 (amino moieties of the MCM support) and OH and COOH (of trans-ferulic acid)—also visualized in FTIR as a ~28 cm−1 shift of a specific band of COOH. Depending on the pH, even electrostatic interactions can appear, amino groups being susceptible to protonation, especially at pH < 7.2 while carboxyl groups are susceptible to deprotonation at pH > 7. As indicated by the experimental data presented in [63] the normal gastrointestinal transit time can be divided in three intervals: first 2–5 h are spent in the stomach, followed by 2–6 h of release in small intestine and 10–60 h in the large bowel. By coupling these times with the data obtained from release profiles in SGF and SIF, we can state that between 20–$40\%$ of FA will be released in the stomach (depending on actual transit time), with additional 20–$40\%$ of loaded FA being release in the small intestine. Additional FA quantities can be released in large bowel as a function of the actual transit time. In addition, after FA loading, the APTES functionalized MCM-41 or MCM-48 particles can be embedded in a mucoadhesive system [64,65], that will allow modulation of residence time and FA recovery [66]. Furthemore, by comparing with antimicrobial drugs, such as antibiotics, the negative environmental impact is low as these systems don’t lead to antimicrobial resistance.
In both, SGF and SIF, even after 24 h, the cumulative release of FA from the silanized mesoporous samples remain still below that from the bare mesoporous systems at 6 h, proving that aminopropyl groups have an important impact over the release rate. In SGF, the delayed nature of the delivery of FA is also observed but the difference between the cumulative releases of FA from the silanized samples comparing with the bare mesoporous samples is lower.
By comparing the MCM-48_FA with MCM-48_APTES_FA system, the first observation is that the release curves are similar in both simulated biological fluids, SGF and SIF. Unlike the systems containing MCM-48, the systems based on MCM-41 present a different behaviour. MCM-41_FA, had a faster release profile in the simulated intestinal fluid while and MCM-41_APTES_FA had a slower release when compared to MCM-48 materials.
## 3.7. Antimicrobial Activity
The mesoporous silica materials were tested to evaluate the antimicrobial activity on four strains *Staphylococcus aureus* ATCC 25923, *Escherichia coli* ATCC 25922, *Pseudomonas aeruginosa* ATCC 27853 and Candida albicans ATCC 1023.
## 3.7.1. Quantitative Evaluation of Antimicrobial Activity
The lowest concentration at which the tested samples still can inhibit the microbial growth represents the minimum inhibitory concentration (MIC). The obtained values (mg/mL) are presented in Table 5.
The quantitative results for the silica-based mesoporous materials indicated the highest sensitivity against P. aeruginosa which is an important observation, considering that this species is frequently involved in healthcare associate infections. It can be observed that the materials loaded with ferulic acid negatively influence the growth of pathogens strains tested, compared to the controls. The MCM-41_APTES_FA and MCM-41_APTES samples determined the highest sensitivity of S. aureus, P. aeruginosa and C. albicans, with MIC values ranging from 0.01 and 0.001 mg/mL. The MCM-41_APTES_FA presented the best antimicrobial activity against Gram-positive and Gram-negative bacteria tested in this study. Overall, a synergic effect between mesoporous materials and ferulic acid can be observed.
A recent study [67] also observed the bacteriostatic effect of ferulic acid against Gram-positive and Gram-negative bacteria. Also, Borges et al. [ 45] determined the antibacterial activity of ferulic acid against S. aureus, E. coli, P. aeruginosa and L. monocytes. The MIC values are 1 mg/mL for E. coli and P. aeruginosa, and 1.25 mg/mL for S. aureus. Ferulic acid produced changes in membrane properties, especially hydrophobicity changes, decreasing negative charge and damage to molecular mechanisms.
## 3.7.2. Semi-Quantitative Assessment of Microbial Adherence to the Inert Substratum
In Table 6 are presented the minimum inhibition concentrations (mg/mL) for adherence to the inert substratum, for the silica-based mesoporous materials.
As indicated by the MIC and MAIC values (Table 5 and Table 6), S. aureus, E. coli and P. aeruginosa are the most sensitive strains. The lowest values of MAIC range from 0.001 and 0.1 mg/mL in the case of silica-based mesoporous materials. Among all the studied samples, MCM-41_APTES_FA prevented the adherence of pathogen strains to the inert substratum, respectively, the development of the mature and stable biofilm, and presenting the most pronounced inhibitory effect. The samples functionalized with APTES and/or loaded with ferulic acid present a better bacteriostatic effect on the strain’s growth than mesoporous silica. Accordingly, with the previous assays, it seems that ferulic acid not only determined the damage to cell growth but also MCM-41/MCM-48 functionalized with APTES induced the hydrophobicity changes and the bacteriostatic effects. Furthermore, ferulic acid, as a dietary polyphenol, improves the modulation of gut microbiota [68,69] and the antimicrobial activity of silica-based mesoporous materials loaded with ferulic acid and, in vitro release profiles, confirms the potential for these materials as food supplements. In future, we want to continue this study with biocompatibility assay and the influence of these materials on probiotic bacteria/intestinal microbiota.
## 4. Conclusions
In this study, two types of functionalized mesoporous materials, MCM-41 and MCM-48, were synthesized by the soft-template method using (3-aminopropyl)triethoxysilane (APTES) as a modifying agent. The BET, TGA and XRD analyses indicate that mesoporous materials were obtained and further functionalized with APTES. The as obtained functionalized mesoporous materials were loaded with trans-ferulic acid using the vacuum assisted loading technology and found that the loading mainly occurs within the pores. The APTES functionalized mesoporous materials exhibited comparatively loading capacity when compared with the simple MCM-41, but smaller values for MCM-48. Strong interaction between the functionalized support and trans-ferulic acid are proved by a strong FTIR shift of about 28 cm−1 of the carboxyl group, and lower melting temperature of the loaded FA. Due to these strong interactions, the release rate of FA decreased significantly in both SIF and SGF, which can be beneficial allowing the development of sustained drug delivery systems of biological active agents, including polyphenols, for antimicrobial, antibacterial, anticancer, anti-inflammatory or antidiabetic purposes. The use of ferulic acid, instead of a specific antibiotic, has the advantage that the release into the nature of the residual polyphenol (FA not released within the gastrointestinal tract) will not have a negative environmental impact.
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|
---
title: Characterizing and Quenching Autofluorescence in Fixed Mouse Adrenal Cortex
Tissue
authors:
- Nawar Sakr
- Olga Glazova
- Liudmila Shevkova
- Nikita Onyanov
- Samira Kaziakhmedova
- Alena Shilova
- Maria V. Vorontsova
- Pavel Volchkov
journal: International Journal of Molecular Sciences
year: 2023
pmcid: PMC9968082
doi: 10.3390/ijms24043432
license: CC BY 4.0
---
# Characterizing and Quenching Autofluorescence in Fixed Mouse Adrenal Cortex Tissue
## Abstract
Tissue autofluorescence of fixed tissue sections is a major concern of fluorescence microscopy. The adrenal cortex emits intense intrinsic fluorescence that interferes with signals from fluorescent labels, resulting in poor-quality images and complicating data analysis. We used confocal scanning laser microscopy imaging and lambda scanning to characterize the mouse adrenal cortex autofluorescence. We evaluated the efficacy of tissue treatment methods in reducing the intensity of the observed autofluorescence, such as trypan blue, copper sulfate, ammonia/ethanol, Sudan Black B, TrueVIEWTM Autofluorescence Quenching Kit, MaxBlockTM Autofluorescence Reducing Reagent Kit, and TrueBlackTM Lipofuscin Autofluorescence Quencher. Quantitative analysis demonstrated autofluorescence reduction by 12–$95\%$, depending on the tissue treatment method and excitation wavelength. TrueBlackTM Lipofuscin Autofluorescence Quencher and MaxBlockTM Autofluorescence Reducing Reagent Kit were the most effective treatments, reducing the autofluorescence intensity by 89–$93\%$ and 90–$95\%$, respectively. The treatment with TrueBlackTM Lipofuscin Autofluorescence Quencher preserved the specific fluorescence signals and tissue integrity, allowing reliable detection of fluorescent labels in the adrenal cortex tissue. This study demonstrates a feasible, easy-to-perform, and cost-effective method to quench tissue autofluorescence and improve the signal-to-noise ratio in adrenal tissue sections for fluorescence microscopy.
## 1. Introduction
Fluorescence microscopy is an imaging technique that allows the excitation of fluorescent molecules and the detection of the emitted signal over a wide range of wavelengths [1]. Fluorescence microscopy has several advantages over other types of microscopy, including the ability to selectively visualize one or more target molecules in the studied material with high sensitivity and signal-to-noise ratio [2,3]. Advances in fluorescent microscopy have transformed our understanding of biological processes. However, despite the development of numerous new methods for tissue processing and fluorophore imaging, the signal-to-noise ratio remains a recurrent issue in clinical and experimental investigations that use fluorescence microscopy for diagnostic and research applications. One of the primary sources of noise in fluorescence microscopy is autofluorescence (AF). Autofluorescence is the endogenous and exogenous fluorescence that occurs in cells and tissues across a broad range of excitation and emission wavelengths and is unrelated to the specific signal obtained during a fluorescence-based assay [4,5,6]. Exogenous AF results from chemically modified molecules due to tissue processing and fixation procedures [7]. The endogenous AF originates from naturally fluorescent intracellular molecules, such as flavins, flavoproteins, and lipofuscin-like substances [5,8]. Moreover, red blood cells and extracellular tissue components, mainly collagen and elastin, are common causes of AF [5,6,9,10]. AF can obscure or interfere with the signal from labeled cells and tissue sections [10,11], complicating sample examination and interpretation of results, particularly in quantitative studies.
The number of naturally fluorescent molecules varies in different tissue types, making some tissues more autofluorescent than others [12,13]. Adrenal glands are endocrine organs characterized by high lipid content [14,15]. Cells of the adrenal cortex accumulate large amounts of lipid droplets, which serve as storage for cholesterol esters, the precursors of steroid hormones [16,17,18]. Some lipids exhibit AF and complicate the use of fluorescence microscopy in adrenal tissue [19,20]. In addition, the adrenal cortex of various species is rich in autofluorescent pigments. These cortical pigments are typically lipofuscin depositions [15,21,22,23,24]. Lipofuscin, also known as the age pigment, is a yellow-brownish lipid pigment that accumulates in the lysosomes of the cells as they age. The most characteristic feature of lipofuscin is AF. Due to its broad excitation and emission spectra, the lipofuscin AF spectrum overlaps with those of commonly used fluorochromes [4,25,26]. Therefore, the large amounts of fluorescent molecules in adrenal tissue with broad excitation and emission wavelengths are problematic for fluorescence microscopy. Reducing adrenal tissue AF is necessary to distinguish specific labels from AF and improve the signal-to-noise ratio. Several strategies have been applied to diminish AF of fixed tissues, such as photobleaching, chemical treatments, dyes that stain specific tissue components, and combinations of these treatments [27,28,29]. However, AF reduction efficiency differs depending on tissue type and processing method, and, to date, no general formula for quenching AF in various tissue types is currently available [11,29]. A systematic study to analyze AF reduction methods in mouse adrenal cortex tissue has yet to be performed.
In the current study, we characterized the AF in PFA-fixed mouse adrenal cortex tissue sections. We addressed the difficulties of using fluorescent microscopy caused by the observed AF. We compared the effect of several reported treatments for AF reduction on the AF profile of mouse adrenal cortex, such as trypan blue, copper sulfate, ammonia/ethanol, Sudan Black B, TrueVIEWTM Autofluorescence Quenching Kit, MaxBlockTM Autofluorescence Reducing Reagent Kit, and TrueBlackTM Lipofuscin Autofluorescence Quencher. We further evaluated the subsequent tissue immunofluorescence and enhanced green fluorescent protein (EGFP) detection using confocal laser scanning microscopy. Our results show that using TrueBlackTM Lipofuscin Autofluorescence *Quencher is* the best approach to quench adrenal tissue AF while allowing the detection of target fluorescent labels.
## 2.1. Evaluation of Autofluorescence in Mouse Adrenal Tissue
We analyzed the autofluorescence spectrum of the PFA-fixed mouse adrenal cortex tissue sections using the Olympus FluoView™ FV3000 confocal microscope in lambda scan mode. We collected the emission spectra of the adrenal cortex at 405 nm and 488 nm excitation wavelengths. The normalized emission intensity showed a broad AF emission at 405 nm and 488 nm excitations, with a central emission peak between 475–485 nm and 545–555 nm, respectively (Figure 1a). The intensity of AF was higher at 405 nm excitation compared to 488 nm (Figure 1c,d). Confocal laser scanning microscope (CLSM) images at 488 nm excitation wavelength showed a bright green AF across the adrenal cortex. The observed AF was brighter in the zona fasciculata of the adrenal cortex than in the zona reticularis and adrenal capsule. The AF originated from the cortical cells rather than extracellular tissue components. The intracellular autofluorescent molecules were widespread throughout the cytoplasm and less in the nuclei of the cortical cells (Figure 2a).
To assess if the observed AF might complicate the detection of specific fluorescent labels in the adrenal cortex, we compared the AF spectra at 405 nm and 488 nm excitation with those of commonly used fluorophores obtained from the database of fluorescent dyes (www.fluorophores.tugraz.at, accessed on 26 November 2022). The wide spectrum of AF at 405 nm excitation interferes with the emission of 4′,6-diamidino-2-phenylin-dole (DAPI), enhanced blue fluorescent protein (EBFP), and enhanced cyan fluorescent protein (ECFP), usually excited at 405 nm wavelength (Figure 1b). The AF spectrum at 488 nm excitation showed to interfere with the emission of enhanced green fluorescent protein (EGFP), Alexa fluor 430, and Alexa fluor 514, usually excited at 488 nm wavelength (Figure 1b). Therefore, the broad adrenal cortex AF interferes with detecting and quantifying several fluorescent labels in the blue and green channels of CLSM.
## 2.2. The Effect of Tissue Treatments on Adrenal Cortex Autofluorescence
In order to reduce the AF of the mouse adrenal cortex tissue sections, we tested the efficacy of seven treatments previously described to decrease AF in multiple cells and tissue types (Table 1). The lambda scan showed that all the applied treatments altered the AF profile at both 405 nm and 488 nm excitations. Trypan blue (TRB) treatment decreased the maximum intensity of AF at 405 nm excitation by $12\%$ ± $2\%$ (SE) (Figure 1c,e). At 488 nm excitation, TRB did not reduce AF intensity but shifted the AF emission to longer wavelengths (Figure 1d,f and Figure 2a). Copper(II) sulfate (CuSO4), ammonia/ethanol (NH3), and TrueVIEWTM Autofluorescence Quenching Kit (TrueVIEW) reduced AF maximum intensity by $68\%$ ± $0.8\%$ (SE), $70\%$ ± 2 (SE), and $70\%$ ± $3\%$ (SE), and by $52\%$ ± $1\%$ (SE), $65\%$ ± $2\%$ (SE), and $62\%$ ± $2\%$ (SE) at 405 nm and 488 nm excitations, respectively. These treatments did not shift the AF emission, and we still observed a central peak of AF emission similar to untreated tissue sections at 405 nm and 488 nm excitations (Figure 1c–f). Figure 2a shows that CuSO4, NH3, and TrueVIEW reduced the overall background AF. NH3 was the most effective among these treatments in reducing the green wavelength AF. However, it did not eliminate the adrenal cortex AF, and autofluorescent granules were still observed after treatment with NH3.
Sudan Black B (SBB), TrueBlackTM Lipofuscin Autofluorescence Quencher (TrueBlack), and MaxBlock™ Autofluorescence Reducing Reagent (MaxBlock) further reduced the AF maximum intensity by $88\%$ ± $0.3\%$ (SE), $93\%$ ± $0.1\%$ (SE), and $95\%$ ± $0.03\%$ (SE), and by $82\%$ ± $0.7\%$ (SE), $89\%$ ± $0.04\%$ (SE), and $90\%$ ± $0.07\%$ (SE) at 405 nm and 488 nm excitations, respectively (Figure 1e,f). Emission line graphs showed no central peak of AF emission after treatment with TrueBlack or MaxBlock (Figure 1c,d). SBB reduced AF from the tissue regions showing intense dark staining with SBB. However, AF was still observed in the less stained tissue regions (Figure 2). In contrast, both TrueBlack and MaxBlock reduced the overall AF from the entire adrenal cortex and produced a more homogeneous background. Both treatments mainly stained the cytoplasm of the cortical cells and reduced the cytoplasmic AF to levels lower than the nucleic AF. This staining pattern resulted in slightly brighter nuclei than cytoplasm in the adrenal cortex treated with TrueBlack and MaxBlock (Figure 2a).
## 2.3. Reduction in Autofluorescence from Pigment Accumulations in the Mouse Adrenal Tissue
The autofluorescent lipofuscin accumulates in the adrenal tissue as mice age. The presence of pigment-laden cells containing large amounts of autofluorescent lipoid pigments further complicates the elimination of AF from aged mice’s adrenal tissue. We examined the AF of adrenal tissue sections from aged mice. In addition to the high intracellular AF, we observed several irregularly shaped granules with high-density fluorescence across all observed channels. These granules varied in size and scattered in the adrenal cortex and the corticomedullary junction (Figure 3). We treated the adrenal tissue sections from aged mice with TrueBlack or MaxBlock, which showed the highest efficacy in decreasing AF of the adrenal cortex from younger mice (Figure 1c–f and Figure 2a). CLSM images showed that both treatments quenched the fluorescence from the autofluorescent accumulations. The reduction of this intense AF did not require increased incubation time or working concentration. We noticed a more intense dark staining of these granules and the cortical cells compared to the cells from younger mice (Figure 2b). TrueBlack and MaxBlock specifically stained the cortical cells’ cytoplasm and, to a lesser extent, the nuclei and adrenal medullary cells (Figure 3), similar to findings from younger mice’s adrenal tissue sections (Figure 2b).
## 2.4. The Effect of TrueBlack and MaxBlock Treatments on the Detection of Fluorescent Labels in the Mouse Adrenal Cortex
AF is problematic for fluorescence-based assay in tissue sections. Intrinsic fluorescence interferes with or even masks the specific signals from fluorescent labels. Reducing tissue AF without affecting fluorescent tags is necessary to obtain valid data. To evaluate the applicability of AF treatments in immunofluorescence (IF), we treated adrenal tissue sections with TrueBlack or MaxBlock before (pre-treatment) or after applying the antibodies (post-treatment) for indirect IF. We immunostained the 21-hydroxylase typically expressed in the mouse adrenal cortex and used secondary antibodies conjugated to Alexa Fluor 594 to visualize the 21-hydroxylase staining. We detected the fluorescence signals in the 570–670 nm range at 561 nm excitation and used the 500–540 nm detection range at 488 nm excitation to evaluate the efficacy and stability of AF reduction treatments throughout the immunostaining procedure.
CLSM images obtained using the same acquisition settings showed that Alexa Flour 594 signals were detectable in adrenal tissue sections pre-treated with TrueBlack or MaxBlock (Figure 4a,e). In contrast, the post-treatment of immunostained sections with either TrueBlack or MaxBlock masked most of the fluorescence signals from the conjugated antibodies. Post-treatment with MaxBlock had the most negative effect on the IF in the adrenal cortex. ( Figure 4c,g). We stained tissue sections with DAPI after AF treatments. The treatment of adrenal tissue with TrueBlack or MaxBlock did not mask the fluorescent signals from DAPI in the adrenal cortex. However, DAPI fluorescence was slightly brighter in sections treated with TrueBlack than those treated with MaxBlock (Figure 4a,c,e,g). These findings suggest that in comparison to MaxBlock, TrueBlack treatment has a less adverse effect on the specific fluorescence in IF. Nevertheless, both treatments quenched the adrenal cortex AF at 488 nm excitation when applied before or after immunostaining.
Lastly, we evaluated the effect of TrueBlack treatment on the native fluorescence of enhanced green fluorescent protein (EGFP). We applied TrueBlack to PFA-fixed frozen adrenal tissue sections from mice injected with recombinant adeno-associated virus vectors carrying the EGFP gene (rAAV-EGFP). The treatment of tissue sections with TrueBlack did not quench the fluorescence of EGFP. We detected EGFP native fluorescence in a number of cells stained with TrueBlack (Figure 5a,b). We enhanced the EGFP fluorescence by indirect immunostaining after TrueBlack treatment and applied secondary antibodies conjugated to Alexa Fluor 488. We detected the fluorescence of stained EGFP from various cells stained with TrueBlack. In most cells, the fluorescence intensity was higher in the cells’ nuclei than in the cytoplasm (Figure 5c,d). Altogether, these results suggest that treatment with TrueBlack eliminates AF of the adrenal cortex while having a minimal effect on the fluorescence of fluorophore-conjugated antibodies and EGFP.
## 3. Discussion
In this study, we demonstrated that the mouse adrenal cortex emits intense AF in the commonly used channels in CLSM. Adrenal tissue AF was widespread in the cortical cells and had broad excitation and emission spectra. The observed AF spectrum interferes with the spectra of many fluorescent proteins and dyes commonly used in fluorescence microscopy (Figure 1a–d and Figure 2a), complicating the detection of fluorescent labels and possibly leading to false positive results. The adrenal cortex AF was brighter at 405 nm and 488 nm excitations compared to longer excitation wavelengths, as shown in Figure 3. Therefore, we used 405 nm and 488 nm excitations to evaluate the efficiency of different tissue treatments against adrenal cortex AF. Several previously described AF-reducing agents decreased the AF of the adrenal cortex. MaxBlock and TrueBlack were the most effective treatments for quenching the intracellular AF at different excitation wavelengths. Other treatment methods, including SBB, NH3, CuSO4, and TrueVIEW, reduced the AF to a certain extent but did not eliminate the AF of the adrenal cortex (Figure 1e,f and Figure 2a).
Moreover, TrueBlack and MaxBlock treatments quenched AF of pigment accumulations, exhibiting bright AF across multiple CLSM channels (Figure 3). The pre-treatment of adrenal tissue sections with TrueBlack for IF masked the intrinsic AF but not the specific fluorescent signals from the immunolabels (Figure 4a). Similarly, treatment with TrueBlack did not interfere with detecting EGFP in adrenal tissue sections (Figure 5a,c).
The adrenal cortex AF originated mainly from the cortical cells’ cytoplasm (Figure 2a). Cortical cells are known to accumulate lipid droplets containing cholesterol esters for steroid biosynthesis [14,16,17,18]. Some lipid compounds exhibit AF depending on their molecular properties [30]. In addition, the adrenal cortices are rich with intracytoplasmic lipofuscin, which builds up in the lysosomes of cells as they age [15,24]. AF is a distinctive feature and is regarded as a reliable marker of lipofuscin [31,32,33]. Lipofuscin fluorescence emission spectra show considerable heterogeneity due to differences in chemical composition [34]. Hence, the lipofuscin and high lipid content are possible causes of the broad intracellular AF observed in the mouse adrenal cortex. In addition to the endogenous AF sources, fixation with paraformaldehyde can contribute to the AF observed in the adrenal cortex. Crosslinking fixatives such as formaldehyde and glutaraldehyde are major sources of exogenous AF [6,10,27]. During tissue fixation, aldehydes react with the amine groups of proteins and amino acids to form fluorescent complexes known as Schiff bases [7,35].
The reduction in adrenal cortex AF with TrueBlackTM Lipofuscin Autofluorescence Quencher (TrueBlack) and SBB further suggests that lipofuscin and lipids are potential AF sources. TrueBlack is a commercial AF quenching reagent that reduces tissue sections AF from lipofuscin and less efficiently from other sources like red blood cells and extracellular components. TrueBlack has been used for AF reduction in a wide range of human and mouse tissue types, such as the brain [36,37,38,39], retina [40,41], heart [42,43], lung [44,45], and liver tissue [46,47]. SBB is a superlipophilic diazo dye used for staining a wide variety of lipids [48,49] and some proteins [50]. SBB shows a high affinity to lipofuscin in frozen and paraffin-embedded tissue sections [51,52]. Therefore, it has been used to reduce AF from lipids, lipofuscin, and lipofuscin-like substances in various tissue types [4,6,11,13,27,29,53,54,55]. The proposed mechanism is that SBB masks the autofluorescent structures without chemically interacting with the components of these structures [4,29,53]. Similar to TrueBlack and SBB, MaxBlockTM Autofluorescence Reducing Kit (MaxBlock) primarily stained the cytoplasm of cortical cells (Figure 2b), quenching the AF of the adrenal cortex. MaxBlock is a commercialized AF treatment designed to reduce background AF on paraffin-embedded and frozen tissue sections. It has been used to diminish AF in several tissues, such as the liver [56], heart [57], lung [58,59], pancreas [60], and skin [61] tissues.
Although SBB is a more cost-effective AF treatment than TrueBlack and MaxBlock, SBB preparation is laborious and requires longer incubation time to reduce AF of the adrenal cortex. TrueBlack and MaxBlock are ready-to-use reagents that showed more efficiency in reducing AF of the adrenal cortex, resulting in a more homogeneous nonfluorescent background (Figure 1c–f and Figure 2a). Moreover, SBB introduces some AF in the red and far-red channels. SBB is incompatible with antifading agents that preserve the fluorescent labels for long-term storage and analysis [53] and may have adverse effects on the fluorescence of specific labels in tissue IF [4,27].
The commercial TrueVIEW Autofluorescence Quenching Kit (TrueVIEW) reduces tissue AF via treatment with an aqueous solution of nonfluorescent, hydrophilic molecules. These negatively charged molecules bind electrostatically and diminish AF from non-lipofuscin sources such as red blood cells, collagen, elastin, and aldehyde fixation [62]. TrueVIEW has been used to reduce AF in various tissues [63,64,65,66]. TrueView reduced the AF of adrenal cortex cells (Figure 1c–f and Figure 2a), suggesting that lipofuscin and other hydrophobic molecules are not the only sources of AF in the adrenal cortex.
Copper(II) sulfate (CuSO4) was reported to reduce tissue AF from lipofuscin [4,67], red blood cells [68,69], and other sources [28,69,70,71]. The chemical mechanism of Cu2+ quenching of AF is not precise. It is suggested that Cu2+ acts as an electron scavenger that receives electrons from the autofluorescent molecules by collisional contact and circumvent the fluorescence emission [72]. In our study, CuSO4 treatment did not eliminate the adrenal cortex AF (Figure 2a), similar to previous reports in some tissue types [27,73]. CuSO4 may also have a negative effect on IF signals when used at high concentrations [4,27]. However, we did not investigate the impact of this treatment on IF in adrenal tissue.
NH3 reduces tissue AF by dissolving negatively charged lipid derivatives and phenols, hydrolyzing weak esters, and deactivating pH-sensitive fluorochromes [6,29]. In previous reports, NH3 reduced AF in bone marrow, kidney, and placenta tissue sections [6,13,28]. Meanwhile, it failed to quench AF in the brain [29], liver, and pancreas tissue [13]. NH3 was ineffective against the AF of lipofuscin granules in the myocardial tissue [6]. In our study, NH3 reduced the general background AF but did not eliminate the AF of fluorescent granules in the adrenal cortex (Figure 1c–f and Figure 2a).
Trypan Blue (TRB) diffuses into permeabilized cells and distributes uniformly in the cell nucleus and cytoplasm. If used in optimized concentration, TRB reduces AF when dye molecules are at a proper orientation and distance to autofluorescent molecules or when bound to autofluorescent molecules [74]. Contrary to previous reports [28,74,75], TRB did not diminish the AF of the adrenal cortex (Figure 1c–f and Figure 2a), possibly due to the use of a suboptimal concentration or the omission of permeabilization step in order to process all the tissue sections equally before applying the AF treatments. However, consistent with the previous reports [74,75], TRB shifted the AF spectrum of the adrenal cortex to longer wavelengths. We did not further optimize the TRB treatment protocol as the induced AF in the longer wavelengths makes TRB a less suitable option than other tested treatments.
The lipofuscin accumulates in the lysosomes of aged cells because it cannot be eliminated by degradation or exocytosis [76]. Adrenal cortices of aged mice and rats accumulate large amounts of lipofuscin [15,24]. Excessive lipofuscin accumulations can result from the degeneration of cortical cells, dietary and steroid imbalances, and administration of some exogenous chemicals [14]. In addition, mouse adrenal tissue may contain pigment-laden cells. These pigmented cells are usually scattered in the adrenal cortex or at the corticomedullary junction. They are thought to be a consequence of the regression of the transient cortical X-zone [14,77]. The pigment-laden cells cluster as the mouse ages and can coalesce to form multinucleated giant cells. The pigmented cells from animals of different ages show similar histochemical staining properties and exhibit orange-yellow primary fluorescence [78]. Thus, the presence of these highly autofluorescent aggregates with various sizes, pigment concentrations, and localizations decreases the signal-to-noise ratio and complicates the interpretation of fluorescence microscopy results.
We tested whether TrueBlack or MaxBlock, which eliminated the AF from the smaller intracellular autofluorescent structures, may reduce the AF from pigment accumulations. Both TrueBlack and MaxBlock quenched the AF from the bright autofluorescent accumulations in the adrenal cortex and in the corticomedullary junction (Figure 3). The adrenal cortex and the pigment accumulations showed more intense cytoplasmic staining with both TrueBlack and MaxBlock than in younger mice (Figure 2b). The staining intensity is possibly proportional to intracellular lipofuscin content, which increases as the mice age. These findings highlight the effectiveness of both TrueBlack and MaxBlock in quenching the AF from dense AF aggregates in the mouse adrenal glands of different ages that might be challenging to eliminate using other AF treatments.
The major limitation of tissue AF reduction treatments is their effect on the specific fluorophores used to visualize target molecules. Several AF quenching methods may quench assay-specific signals [4,27,28,74]. TrueBlack and MaxBlock have been used to treat AF in various tissue types. However, in most tissues, AF originates from specific intracellular or extracellular tissue components that have a defined localization within the tissue, and masking this AF with non-fluorescent dyes does not affect the IF signals from other parts of the tissue. In contrast, autofluorescent molecules are widespread across the adrenal cortex, with high density in the cytoplasm of most cells. This wide distribution causes intense dark staining across the adrenal cortex after treatment with AF-reducing dyes (Figure 2b).
We investigated the effect of the staining with TrueBlack and MaxBlock on IF signals from the cortical cells. The pre-treatment of adrenal tissue sections with TrueBlack before IF had a mild effect on the fluorescence of conjugated antibodies (Figure 4a). Conversely, post-treatment with MaxBlock had the most adverse impact on IF signals (Figure 4g). We also tested if TrueBlack treatment interferes with the fluorescence of enhanced green fluorescence protein (EGFP). EGFP is a versatile biological marker for visualizing protein localization, monitoring transgenic expression, and tracking specific cell types in the adrenal cortex. The broad excitation and emission of AF in the adrenal cortex interfere with detecting EGFP (Figure 1b). We visualized the fluorescence of both native and immunolabeled EGFP in cortical cells stained with TrueBlack in fixed frozen adrenal tissue sections (Figure 5). These findings suggest that TrueBlack treatment is compatible with IF and EGFP fluorescence in adrenal tissue sections, as it diminishes tissue AF without masking the fluorescent signals from fluorescent labels.
Lastly, it is worth noting that the signal of fluorescent labels from treated adrenal cortical cells may be inversely related to the staining intensity of these cells with AF-reducing dyes. The concentration of the dye for AF reduction, incubation time, and tissue content of autofluorescent materials possibly determine the staining intensity of treated tissue sections and, hence, the interference with the detection of specific fluorophores. A significant advantage of TrueBlack over other ready-to-use reagents is the ability to optimize both working concentration and incubation time. TrueBlack is provided as a 20X solution that can be diluted in ethanol according to the required dilution, usually 1X, according to the manufacturer’s instructions. However, TrueBlack has been used in different concentrations [10,79,80] and incubation times [41,81,82] for AF reduction. The ability to optimize TrueBlack treatment is helpful when treating tissues rich with autofluorescent material, such as the adrenal glands, to avoid IF signal masking by intensive dark tissue staining. As mentioned before, the lipofuscin levels in the adrenal cortex can vary with age, diet, hormonal imbalances, and other factors. We recommend testing different concentrations and incubation times with TrueBlack to reach the best balance between tissue AF reduction and target fluorophore visualization and to achieve the required signal-to-noise ratio.
## 4.1. Animals
The animals were housed and utilized for experimental procedures in compliance with Directive $\frac{2010}{63}$/EU and the recommendations of the local Bioethical Committee of Lomonosov Moscow State University.
## 4.2. Tissue Sections
Eight week old C57BL/6J mice were anesthetized and sacrificed under full anesthesia with isoflurane (Miralek, Moscow, Russia). Adrenal glands were dissected and immersed in $4\%$ PFA (PanReac AppliChem ITW Reagents, Barcelona, Spain) in PBS for 16 h at 4 °C [83]. The adrenal glands were washed three times with PBS for 15 min each, transferred to a solution of $15\%$ sucrose in PBS for 24 h at 4 °C, and then moved to a solution of $30\%$ sucrose in PBS for 48 h at 4 °C. The adrenal glands were then embedded and frozen in Tissue-TekTM O.C.T. Compound (Sakura Finetek, Warsaw, Poland). Sections of 12 μm were cut and mounted onto Polysine adhesion slides (Thermo Fisher Scientific, Waltham, MA, USA). Tissue sections were stored in the dark at −20 °C for subsequent use.
Archival $4\%$ PFA-fixed frozen tissue sections from aged mice and mice injected with recombinant AAV vector carrying the gene of enhanced green fluorescent protein (rAAV-EGFP) were previously prepared similarly and stored in the dark at −20 °C till usage.
## 4.3. Tissue Treatment for Reducing Autofluorescence
Frozen mouse adrenal tissue sections were thawed for 30 min at RT and washed with PBS two times, 10 min each, to remove O.C.T. The tissue sections were then treated separately with tissue AF treatment methods (Table 1) at room temperature. Sudan Black B (SBB, Dia-m, Moscow, Russia) was prepared as $0.1\%$ (W/V) in $70\%$ ethanol, as described previously [27]. Sections were incubated with the SBB solution sealed airtight in the dark for 20 min, and then dipped briefly in $70\%$ ethanol once before washing with PBS. A solution of 10 mM copper(II) sulfate (CuSO4) in 50 mM ammonia acetate, pH 5, was prepared and applied to sections for 90 min [27]. Ammonia/ethanol (NH3) was prepared as $0.25\%$ (V/V) ammonia (PanReac AppliChem ITW Reagents, Barcelona, Spain) in $70\%$ ethanol and applied to tissue sections for 1 h [29]. A fresh $0.05\%$ (W/V) trypan blue (Paneko, Moscow, Russia) in PBS solution was prepared and applied to slides for 15 min [28]. The 20X TrueBlack solution (TrueBlackTM Lipofuscin Autofluorescence Quencher, Biotium, Fremont, CA, USA) was diluted to 1X in $70\%$ ethanol and applied to tissue sections for 1 min. After each of these treatments, the slides were washed with PBS 3 times for 15 min each. TrueVIEW Reagent (TrueVIEWTM Autofluorescence Quenching Kit, Vector Laboratories, Burlingame, CA, USA) was prepared according to manufacturer instructions, applied immediately to sections for 3 min, and then washed once with PBS for 5 min. MaxBlockTM Autofluorescence Reducing Reagent Kit (MaxVision Biosciences, Bothell, WA, USA) was applied according to manufacturer instructions. Tissue sections were incubated with MaxBlockTM Autofluorescence Reducing Reagent (Reagent A) for 1 min, washed according to manufacturer instructions, incubated with Post-Detection Conditioner (Reagent B) for 5 min, and then washed according to manufacturer instructions. After each treatment, the slides were mounted onto coverslips with a polyvinyl alcohol mounting medium with DABCOTM antifading (Sigma-Aldrich, St. Louis, MO, USA). The slides treated with TrueVIEWTM Autofluorescence Quenching Kit were mounted with VECTASHIELD Vibrance Antifade Mounting Medium (Vector Laboratories, Burlingame, CA, USA) according to the manufacturer’s instructions. The slides were stored at 4 °C in the dark for subsequent examination.
## 4.4. Autofluorescence Emission Spectra and Images Acquisition
For each treatment and control group, the AF emission spectra were acquired in a λ-spectral mode from the adrenal cortex tissue sections ($$n = 4$$) using the confocal microscope Olympus FluoView™ FV3000 (Olympus, Tokyo, Japan) with a UPLXAPO40X, 0.95 NA dry objective (Olympus) using the following settings: OneWay capture; 512 × 512 pixel format; Airy disk, 1 AU; line averaging, 2. Tissue sections were excited with a 405 nm laser diode (OBIS 405 nm LX 50 mW, Coherent, Singapore) and a 488 nm laser diode (OBIS 488 nm LS 20 mW, Coherent, Singapore) at $100\%$ laser power while using the excitation dichroic mirror (ExDM) BS$\frac{10}{90.}$ ExDM BS$\frac{10}{90}$ allows approximately $10\%$ of the power of the selected laser to pass through the mirror, and $90\%$ of the emitted light back through. Emission data were collected using the gallium arsenide phosphide (GaAsP) photomultiplier tube (PMT) high-sensitivity spectral detector. The PMT settings were as follows: detector voltage, 650 V; gain, 1; offset, 3. We used detection ranges of 415–745 nm and 515–745 nm at 405 nm and 488 nm excitations, respectively. The detection bandwidth and the detection step size were 10 nm. The Olympus FluoViewTM FV3000 ‘Series analysis’ tool was used to analyze the emission data [84], and the average intensity values were exported for further analysis. Images demonstrating AF levels in the green wavelengths and transmitted images were acquired at excitation of 488 nm and detection range 500–600 nm, with a UPLXAPO40X, 0.95 NA Dry objective using the following settings: OneWay capture; 2048 × 2048 pixel format; Airy disk, 1 AU; line averaging, 5. The images were exported without enhancements or manipulations.
## 4.5. Immunofluorescence
Adrenal tissue sections were thawed at RT for 30 min and washed with PBS two times, 10 min each, to remove O.C.T. After that, the sections were permeabilized with PBS containing $0.1\%$ Triton X-100 (AppliChem GmbH, Darmstadt, Germany) for 10 min, and then blocked with PBS containing $10\%$ goat serum (Abcam, Cambridge, UK) for 2 h at RT in a humidified chamber. The tissue sections were incubated with the primary antibodies diluted in PBS containing $1\%$ BSA (Dia-m, Moscow, Russia), $0.25\%$ Triton X-100, and $0.25\%$ Tween-20 (Bio-Rad, Hercules, CA, USA) for 16 h at 4 °C. After incubation, the sections were washed twice with PBS containing $0.1\%$ Triton X-100 and Tween-20 for 10 min each. The tissue sections were incubated with the secondary antibodies diluted in PBS containing $1\%$ BSA, $0.25\%$ Triton X-100, and $0.25\%$ Tween-20 for 2 h at RT in a humidified chamber, and then washed two times with PBS containing $0.1\%$ Triton X-100 and Tween-20, 10 min each.
Tissue sections were stained with 0.5 µg/mL 4′,6-diamidino-2-phenylindole (DAPI) for 10 min, washed with PBS for 10 min, mounted onto coverslips with polyvinyl alcohol mounting medium with DABCOTM antifading, dried overnight, and stored in the dark at 4 °C until examination. Images of IF were acquired with the confocal microscope Olympus FluoView™ FV3000 UPLXAPO60XO, 1.42 NA Oil Immersion Objective.
TrueBlack and MaxBlock AF reduction treatments were applied either after the blocking step (pre-treatment) or after the incubation with secondary antibodies (post-treatment). For pre-treated sections, Triton X-100 and Tween-20 were excluded from all the solutions after applying TrueBlack or MaxBlock without changing the buffers’ other ingredients.
The primary antibodies used for IF were Anti-CYP21A2 antibody (1:500, ab232701, Abcam) and GFP polyclonal antibody (1:500, A10262, Invitrogen, Eugene, OR, USA). The secondary antibodies used for IF were goat anti-rabbit IgG H&L (Alexa FluorTM 594) (1:1000, ab150080, Abcam) and goat anti-chicken IgY H&L (Alexa FluorTM 488) (1:1000, ab150169, Abcam).
## 4.6. Data Analysis
The average intensity values at 405 nm and 488 nm in λ-spectral mode were imported into GraphPad Prism software version 8.0.1. ( GraphPad Software, Inc., San Diego, CA, USA) In order to examine the adrenal cortex AF spectral shape, the emission data for untreated control were normalized, and the mean normalized intensity and the standard deviation were plotted. The mean normalized intensities of untreated control at 405 nm and 488 nm excitation were compared with emission spectra of fluorescent proteins and synthetic fluorescent dyes publicly available in the database of fluorescent dyes (www.fluorophores.tugraz.at, accessed on 26 November 2022) to assess the degree of AF interference with the commonly used fluorophores in fluorescence microscopy. After each AF treatment, the means of average emission intensity values were plotted at 405 nm and 488 nm excitations and visually examined for differences in emission intensity and spectrum shape.
In addition, the mean, standard deviation, and standard error for the maximum emission intensities at 405 nm and 488 nm excitations were calculated for each AF treatment. Maximum intensities were compared using one-way ANOVA with Tukey’s multiple comparisons test for pairwise comparisons of treatments. Statistical significance was indicated by letters in superscript. Treatments that share the same letter are not different from each other, while treatments not sharing a letter are significantly different. The percentage difference of maximum intensity at 405 nm and 488 nm excitation between each treatment and the untreated control with the standard error of the mean was calculated to evaluate each treatment’s efficiency in reducing mouse adrenal cortex tissue AF.
## 5. Conclusions
In this study, we assessed the characteristics of adrenal cortex tissue AF and examined several treatments for diminishing the observed AF. We found TrueBlack to be efficacious in quenching AF in the mouse adrenal cortex while preserving the signals of specific fluorescent labels. This study provides a practical method for identifying and eliminating AF during fluorescence-based assays in mouse adrenal tissue sections.
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---
title: Adherence to the Mediterranean Diet Association with Serum Inflammatory Factors
Stress Oxidative and Appetite in COVID-19 Patients
authors:
- Mahsa Mohajeri
- Reza Mohajery
- Arrigo F. G. Cicero
journal: Medicina
year: 2023
pmcid: PMC9968085
doi: 10.3390/medicina59020227
license: CC BY 4.0
---
# Adherence to the Mediterranean Diet Association with Serum Inflammatory Factors Stress Oxidative and Appetite in COVID-19 Patients
## Abstract
Background and Objectives: The Mediterranean diet’s bioactive components are suggested to strengthen the immune system and to exert anti-inflammatory actions. This study investigated the association between adherence to the Mediterranean diet with serum inflammatory factors, total antioxidant capacity, appetite, and symptoms of COVID-19 patients. Materials and Methods: This cross-sectional study was conducted among 600 Iranian COVID-19 patients selected by a simple random method. The ten-item Mediterranean diet adherence questionnaire was used to assess diet adherence. At the beginning of the study, 5 cc of blood was taken from all patients for measurement of serum interleukin 1β) IL-1β), tumor necrosis factor (TNF-α), malondialdehyde (MDA), high sensitivity C-reactive protein (hs-CRP) and total antioxidant capacity (TAC). A human ELISA kit with serial number 950.090.096 produced by the Diaclone Company was used to test this cytokine using the sandwich ELISA method. Results: One hundred and five patients presented a high adherence and 495 patients presented a low adherence to the Mediterranean diet. The incidence of fever, cough, diarrhea, taste changes, and pneumonia severity index were significantly lower in patients who adhered to the Mediterranean diet more than other patients. Serum levels of tumor necrosis factor (5.7 ± 2.1 vs. 6.9 ± 2.8 $$p \leq 0.02$$), interleukin 1 beta (3.2 ± 0.02 vs. 4.9 ± 0.01 $$p \leq 0.02$$), high-sensitivity C-reactive protein (17.08 ± 4.2 vs. 19.8 ± 2.5 $$p \leq 0.03$$), and malondialdehyde (5.7 ± 0.2 vs. 6.2 ± 0.3 $$p \leq 0.02$$) were significantly lower in patients who adhered more to the Mediterranean diet than other patients. Conclusion: The Mediterranean diet can improve the symptoms and elevated serum inflammatory factors in COVID-19 patients, so clinical trial studies are suggested to confirm this effect.
## 1. Introduction
COVID-19 was identified as a pandemic by the World Health Organization on 11 March 2020 [1]. Optimizing] respiratory functioning is the major strategy, particularly in cases where the lower respiratory tract is involved [2,3]. The development of COVID-19 may be greatly influenced by inflammatory responses, according to the last studies’ results [4,5]. Rapid SARS-CoV-2 viral multiplication, cellular damage, and inflammatory responses can attract macrophages and monocytes and cause the production of cytokines and chemokines [6,7,8]. Cytokine storms and aggravations are induced following the attraction of immune cells and activation of immunological responses by these cytokines and chemokines. Several inflammatory indicators can be used to track and identify illness severity and mortality with some degree of accuracy. The high risks of developing severe COVID-19 are strongly associated with inflammatory markers such as procalcitonin (PCT), serum ferritin, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and interleukin-6 (IL-6) [9,10]. Furthermore, it has been demonstrated that elevated serum amyloid A (SAA) levels play a role in the pathogenesis of COVID-19 and may be used as a biomarker to track the course of the illness. However, these findings are still debatable because other studies have not shown a change in the levels of IL-6, SAA, ESR, or CRP [11,12,13,14].
The Mediterranean diet (MD) is distinguished by a high intake of fruits, nuts, vegetables, legumes, and cereals (which in the past were largely unrefined), a high intake of olive oil but a low intake of saturated lipids, a moderately high intake of fish (depending on the proximity of the sea), a low-to-moderate intake of dairy products (and then mostly in the form of cheese or yogurt), a low intake of meat and poultry [15,16]. It is because of the preventive impact that the MD exhibits against a variety of chronic illnesses, including a beneficial effect on overall mortality, cardiovascular disease, and certain cancers, that high adherence to it has been associated with a higher health status [17,18]. The MD has also been suggested as one of the factors influencing these populations’ lifespans. The metabolic syndrome (MetS), certain of its components, and type 2 diabetes have been demonstrated to be negatively correlated with following a healthy eating pattern such as MD [19,20,21]. Due to the nutritious nature of this food pattern, it can also be effective in strengthening the immune system and preventing and controlling infectious diseases. An increasing body of research indicates that the MD’s anti-inflammatory qualities may contribute, at least in part, to its protective benefits [22,23,24].
Considering the importance of dietary pattern’s role in the prevention and control of COVID-19 complications, this study investigated the relationship between adherence to the Mediterranean diet and dietary inflammatory factors, appetite, and oxidative stress in COVID-19 patients.
## 2.1. Study Participants
This cross-sectional study was conducted among 600 COVID-19 patients aged ≥30 years old in Iranian hospitals. Sampling was carried out by a simple random method and using patient file numbers. Six hundred adult patients that met the inclusion criteria out of a total of 670 COVID-19 patients were enrolled in the research (Figure 1). The study included patients who were referred to the COVID-19 outpatient clinics of the Iranian hospital between January 2022 and March, having both calculated tomography (CT) scans of the thorax displaying moderate or severe involvement of the lower respiratory tract (as per radiologist diagnosis), and positive real-time reverse transcriptase–polymerase chain reaction (RT-PCR) tests in oro-nasopharyngeal swab samples. Patients with COVID-19 who had particular diseases, such as chronic liver or kidney diseases, or who were hesitant to participate in the study were excluded. Control patients with chronic diseases other than the skin-ones were also excluded from the study.
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Ardabil University of Medicine Sciences on 17 January 2022 (IR.ARUMS.REC.1400.293). Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper.
## 2.2. Biochemical Measurements
At the beginning of the study, 5 cc of blood was taken from all patients for measurement of serum interleukin 1β) IL-1β), tumor necrosis factor (TNF-α), malondialdehyde (MDA), high sensitivity C-reactive protein (hs-CRP) and total antioxidant capacity (TAC). A human ELISA kit with serial number 950.090.096 produced by the Diaclone Company, Besançon, Frane, was used to test this cytokine using the sandwich ELISA method.
RANDOX’s RANSOM kit was utilized by the suggested procedure to assess the total antioxidant capacity employing spectrophotometry on an Abbot auto-analyzer at 600 nm. A particular substrate is incubated with peroxidase and hydrogen peroxide to form a radical substrate cation, which results in a persistent green-blue color that can be detected at a wavelength of 600 nm. This is the foundation for the measurement. The TAC is expressed in mmol/L. Immunoturbidimetric employed the Pars test diagnostic kit to measure the hs-CRP protein. Following the kit’s instruction manual, 200 L of reagent 2 comprising mouse monoclonal and goat polyclonal antibodies against human CRP antibody was added after placing 20 L of serum and 200 L of reagent 1 at 37 °C for 5 min. With the Abbot auto-analyzer set to 500 nm in mg/L, absorption was recorded at 30 and 90 s. Using kits from Bender Medical Systems, interleukins 1 were quantified by ELISA (Vienna, Austria).
## 2.3. Appetite Assessment
A subjective assessment and an objective indicator for measuring appetite were taken into consideration in this study. To measure a subject’s sensations of hunger, desire to eat, and the likelihood of intake and fullness, a visual analog scale (VAS) was utilized (for subjective parameters). Food greasiness was added to the VAS to gauge the degree of food greasiness. To measure the experience before or after eating, a scale of 0 to 10 was used; the greater the number, the stronger the sensation. The subjects were in charge of their own experience.
## 2.4. Mediterranean Dietary Pattern Assessment
To calculate adherence to the MD, the ten-item, ten-point MEDAS (Mediterranean Diet Adherence Screener) [25], which has been scientifically verified, was used. With the use of the MEDAS questionnaire, the level of adherence to the MD was scored. Participants in the research were split into two groups based on their MEDAS scores: those who adhered to the MD less frequently (0–9) and those who adhered more frequently (10+). The frequency and proportion of replies that were positive to consuming each food were summed.
## 2.5. Statistical Analysis
Statistical analyses were performed with STATA Version 14.0 for windows. All continuous variables were reported as the mean ± standard deviation. Inflammatory markers were compared between groups of adherence to the MD. Differences between group means were tested using an independent T-test. The Association between inflammatory markers and adherence to the MD was also assessed using multivariate regression. In all analyses, a p-value, of less than 0.05 was considered statically significant. Due to the difference in the study groups sample sizes, to validate the results of the T-test, the means difference of the variables and the confidence interval of all the variables were checked.
## 3. Results
Table 1 shows the general characteristics of the participants. None of the enrolled patients was vaccinated before infection. The mean ± SD of study patients was 52.9 ± 6.8 years old. Fifty percent of patients were male and $49\%$ were female.
In Table 2, the results of positive answers to the MEDAS questionnaire are shown. In terms of positive response to the regular consumption of olive oil (97 vs. 67 $$p \leq 0.04$$), fruits (105 vs. 89 $$p \leq 0.04$$), vegetables (103 vs. 94 $$p \leq 0.02$$), legumes (104 vs. 79 $$p \leq 0.01$$), and fish/sea foods (101 vs. 61 $$p \leq 0.02$$), there was a significant difference between people who adhere more to the Mediterranean diet and people with less adherence to the Mediterranean diet.
The status of symptoms and complications of COVID-19 based on the level of adherence to the Mediterranean diet is shown in Table 3.
The incidence of fever [50 ($47.6\%$) vs. 482 (92.5) $$p \leq 0.02$$], cough [38 ($36.1\%$) vs. 380 (76.7), $$p \leq 0.01$$], dyspnea [62 (59.04) vs. 392 (79.1) $$p \leq 0.02$$], diarrhea [44 (41.9) vs. 280 (56.5) $$p \leq 0.02$$], taste changes [23 (21.9) vs. 365 (73.7), $$p \leq 0.05$$], blood pressure and pneumonia severity index [70.4 ± 6.3 vs. 73.4 ± 2.4, $$p \leq 0.04$$] were significantly lower in patients who adhered to the Mediterranean diet more than in patients with less adherence.
The results related to the comparison of appetite in the study patients are shown in Table 4. The amount of desire to eat was higher in patients with more adherence to the Mediterranean diet than in patients with low adherence ($60\%$ vs. $23\%$ $$p \leq 0.02$$). About $31\%$ of patients with greater adherence to the Mediterranean diet rarely felt full after eating, while only about $8\%$ of patients with low adherence to the Mediterranean diet tended to eat more food after the main meal.
The status of serum inflammatory markers in COVID-19 patients according to adherence to the MD has been shown in Table 5. Serum levels of TNF-α (5.7 ± 2.1 vs. 6.9 ± 2.8 $$p \leq 0.02$$), interleukin 1 beta (3.2 ± 0.02 vs. 4.9 ± 0.01 $$p \leq 0.02$$), hs-CRP (17.08 ± 4.2 vs. 19.8 ± 2.5 $$p \leq 0.03$$), and MDA (5.7 ± 0.2 vs. 6.2 ± 0.3 $$p \leq 0.02$$) were significantly lower in patients who adhered more to the Mediterranean diet than other patients. The level of serum total antioxidant capacity in patients with greater adherence to the Mediterranean diet (0.8 ± 0.02) was significantly higher than in other patients (0.6 ± 0.04) ($$p \leq 0.04$$).
Table 6 shows the association of adherence to the MD with inflammatory markers in COVID-19 patients. There was a significant negative association between adherence to the Mediterranean diet and serum inflammatory factors in COVID-19 patients. The serum TNF-α in patients with more adherence to the MD was 1.32 units less than in other patients (coeff. = −1.32, $$p \leq 0.02$$). The serum level of hs-CRP in patients who adhered more to the Mediterranean diet was 1.89 units less than in other patients (coeff. = −1.89, $$p \leq 0.01$$). More adherence to the Mediterranean diet leads to a decrease of 1.34 units in the serum level of MDA (coeff. = −1.34, $$p \leq 0.04$$) and 1.08 units (coeff. = −1.08, $$p \leq 0.04$$) in the serum level of interleukin-1 beta in COVID-19 patients. The total antioxidant capacity in patients with greater adherence to the Mediterranean diet was 2.04 units higher than in other patients (coeff. = 2.04, $$p \leq 0.03$$).
Considering the intake of some specific food classes, the adherence of men to the Mediterranean diet is significantly lower than the one of interviewed women (p ≤ 0.05) (Figure 2). At the same time, the serum levels of the measured inflammatory parameters was significantly higher in men than in women (p ≤ 0.05), in particular in subjects non-adherent to the Mediterranean diet (Figure 3).
## 4. Discussion
For the first time, this study has shown that adherence to the Mediterranean diet has a significant negative relationship with the symptoms of COVID-19 and serum inflammatory markers among COVID-19 patients. Given the scientific plausibility supporting the positive benefits of an appropriate food intake on the immune system, it is hypothesized that a high-quality dietary pattern may offer protection against COVID-19. However, there is still little information about the association between long-term, sustained good food habits, such as the Mediterranean diet, and the risk of SARS-CoV-2 infection. Barrea et al. [ 26] pointed out the importance of the Mediterranean diet in improving the health of patients with COVID-19. He pointed out that the presence of olives, olive oil, fruits, and vegetables in this food pattern is one of the important things that affect the recovery process of COVID-19 patients. In another study, Greene et al. [ 27] examined the association between adherence to a Mediterranean diet and COVID-19 cases and deaths using an ecological study design. They observed that Mediterranean diet adherence was negatively associated with both COVID-19 cases and related deaths across 17 regions in Spain and that the relationship remained when adjusted for factors of well-being. They also observed a negative association between Mediterranean diet adherence and COVID-19-related deaths across 23 countries when adjusted for factors of well-being and physical inactivity. The anti-inflammatory properties of the Mediterranean diet are likely due to the polyphenol content of this diet. The study mentioned that there are confounding factors unrelated to dietary factors driving COVID-19 cases and related deaths. Perez-Araluce et al. [ 28] indicated that people with intermediate adherence to the Mediterranean diet had less risk of developing COVID-19. Another review study conducted by Anna Lucia Fedullo [29] showed that following the Mediterranean diet before and throughout pregnancy may have a protective impact by lowering gestational diabetes mellitus and gestational weight gain and enhancing the immune system’s response to viral infections such as as COVID-19. Inverse relationships have been shown between respiratory disorders, inflammation, and thrombosis with the Mediterranean diet, which includes olive oil, fish, honey, fruits, vegetables, and herbs. It is probable that a phytochemical mixture, such as those found in the Mediterranean diet, has stronger effects than a single molecule. It was indicated that chronic disease patients who follow a Mediterranean diet, as a whole, experience less PAF-induced platelet aggregation. The Mediterranean diet has been mentioned as a possible COVID-19 preventive diet, and it is stated that following this dietary pattern reduces mortality and duration of stay in hospital in patients ≥60 years old [30,31,32,33].
The increased serum levels of inflammatory factors are one of the important reasons for the COVID-19 incidence. Del Valle et al. [ 34] found that high serum interleukin-6, interleukin-8, and TNF-α levels at the time of hospitalization were strong and independent predictors of patient survival. While some inflammatory markers measures in this current study are acute phase reactants, some, such as total antioxidant capacity, may represent a chronic baseline state than acute change with a new illness. Yaghoubi et al. [ 35] reported that total antioxidant capacity levels were considerably lower in COVID-19 patients compared with healthy individuals ($p \leq 0.05$) and also between patients with mild and severe diseases ($p \leq 0.05$). Their findings suggest that COVID-19 patients may be susceptible to depleted total antioxidant capacity.
The results of the present study confirmed the negative association between adherence to the Mediterranean diet and serum levels of hs-CRP, TNF-α, and interleukin-1β. Similar to our result, Sureda et al. reported that the high plasmatic inflammatory markers are closely correlated with low adherence to the Mediterranean dietary pattern [36]. Christina Chrysohoou [37] investigated how the Mediterranean diet affected blood levels of C-reactive protein, white blood cell counts, interleukin-6, tumor necrosis factor-α, amyloid A, fibrinogen, and homocysteine. His study results indicated that the levels of coagulation and inflammatory indicators were found to be lower in people who followed a conventional Mediterranean diet. The focus of a typical Mediterranean diet is on fresh, in-season vegetables, fresh salads, tomatoes, eggplant, cucumber, cabbage, rocket, radishes, garlic, onion, spinach, and lettuce are some examples of these. The most significant sources of phenolic compounds (mostly flavonoids) in the Mediterranean diet are vegetables. Vegetables also include dietary fiber, potassium, vitamin A, vitamin C, vitamin K, copper, magnesium, vitamin E, vitamin B6, folate, iron, thiamine, niacin, and choline, etc. [ 38,39]. Fruits and vegetables, legumes, olives, olive oil, and nuts are all parts of the Mediterranean diet that help blood inflammation reduction [40,41]. A dietary pattern with more fruits and vegetables has an association with low serum inflammatory factor levels. Corinna Koebnick et al. [ 42] evaluated the relationships of diet, obesity, and adipokine in Mexican Americans, and indicated that in comparison to those who consumed more fruits and vegetables and less sugar-sweetened beverages, those who had a diet high in sugar-sweetened beverages had greater levels of adiposity, CRP, leptin, and MCP-1 but lower levels of SFRP-5. Dietary patterns with more sugar-sweetened beverages but with fewer fruits and vegetable consumption cause high Adipokine profiles that lead to pro-inflammatory status. Other components of the Mediterranean diet are olive oil and olives. Consumption of these foods is associated with a decrease in inflammatory indicators [43,44]. *In* general, the results of all studies indicate the anti-inflammatory effect of the Mediterranean diet, so following this dietary pattern is recommended for the prevention and control of infectious diseases, especially COVID-19 [45].
Among other results of this study, there was a significant difference in the symptoms of COVID-19, including fever, cough, diarrhea, pneumonia severity index, and appetite among patients with different adherence to the Mediterranean diet. The incidence of COVID-19 symptoms in patients who adhered more to the Mediterranean diet was lower than in other patients. Consistent with our results, Perez-Araluce et al. [ 28] assessed the Mediterranean diet association with the risk of COVID-19 in the “Seguimiento Universidad de Navarra” cohort participants. This study results indicated that participants with intermediate adherence to the Mediterranean diet (3 < MDS ≤ 6) had significantly lower odds of COVID-19 incidence (multivariable-adjusted OR = 0.50, $95\%$ CI: 0.34–0.73), and those with the highest adherence (MDS > 6) had the lowest risk (multivariable-adjusted OR = 0.36, $95\%$ CI: 0.16–0.84, p for trend < 0.001) as compared with subjects with MDS ≤ 3. Angelis et al. [ 46]. mentioned that adherence to the Mediterranean diet has a main impact on cardiovascular diseases and other cardio-metabolic disorders, like diabetes that predisposes to COVID-19 infection and related outcomes.
This diet is distinguished by a combination of highly complex carbohydrates in fiber (found in cereals, legumes, vegetables, and fruits), polyunsaturated fatty acids with antiatherogenic and anti-inflammatory properties (found in olive oil and nuts), and bioactive substances with antioxidative properties such as flavonoids, phytosterols, terpenes, and polyphenols [37]. A well-balanced intake of micronutrients, such as vitamins and minerals, which are rich in this diet, helps to prevent malnutrition and immune deficiencies [32]. Several chemicals must be consumed together for proper immune system function. Nutrient-rich meals, such as MD, can reduce the elevated serum inflammation factors caused by nutrient-poor and high-calorie diets. Additionally, adhering to MD is associated with the restoration of the microbiota aerobiosis as Bacteroidetes and certain favorable *Clostridium groups* [47]. Considering that the composition of the intestinal flora indicates health, following a healthy food pattern such as the Mediterranean diet can strengthen the body’s immunity by maintaining the proper composition of the intestinal flora. [ 48] In fact, several nutritional intervention trials based on MD have collected the most important health benefits that this diet creates, including decreases in serum lipid levels; protection against oxidative stress; decreases in inflammation; platelet aggregation; modulation of hormones and growth factors implicated in cancer pathogenesis; and modulation of microbial metabolism, promoting the proper functioning of the host metabolism as well [49]. More research is being carried out now to prevent diseases, including cancer, CVD, metabolic disease, and even viral disorders. Here, we will give an overview of how MD’s most important elements affect the immune system’s regulation and the gut flora. MD is primarily characterized by its abundance of fruits, as well as by the availability of aromatic plants and spices to season food (dried herbs like oregano, rosemary, and thyme, for example), as well as seeds (cumin, sesame, etc.), olives, and nuts, all of which are high in a variety of polyphenols. Three important phenolic chemicals that are part of the MD are important to mention: hydroxytyrosol (HT), which is found in EVOO, resveratrol (RSV), which is found in red grapes, and quercetin (QUE), which is found in tea [23]. Higher HT concentrations decrease the levels of oxidized LDL and triglycerides and have a small effect on the expression of genes associated with oxidative-stress [50]. In high-fat diet (HFD)-induced obese mouse models, HT is still being investigated as a nutraceutical. It is being used to observe how this particular EVOO component reverses inflammatory parameters (elevated TNF-, IL-1, and IL-6) and inhibits the activation of TLR-4 and NK-kB pathways, which are related to intestinal permeability in obesity. The phenolic components in EVOO, such as HT, also boost the development of Bifidobacteria, which contribute to the anti-inflammatory effects in the gut. *In* general, it can be concluded that adherence to the Mediterranean diet and consumption of anti-inflammatory foods strengthen the body’s immunity and can be effective and important in the prevention, control, and treatment of symptoms and complications of chronic and even infectious diseases, especially COVID-19 [51].
The use of dietary questionnaire data and the cross-sectional design of this study were this study’s limitations, even though it was the first study that examined the association between adherence to the Mediterranean diet and inflammatory factors, appetite, and symptoms of COVID-19. An adequately powered, long-term, randomized clinical trial should be carried out to confirm our preliminary observation. Moreover, some inflammatory markers measured in this study are acute phase reactants, so in a next study, other markers like total antioxidant capacity (TAC) may better represent chronic baseline state than acute change with a new illness.
## 5. Conclusions
There is an inverse relationship between adherence to the Mediterranean diet and the symptoms and complications of COVID-19, and patients who followed the Mediterranean diet more in the past had less fever, cough, diarrhea, and lung infection. There was a negative relationship between adherence to the Mediterranean diet and serum inflammatory factors in COVID-19 patients. Long-term clinical studies among patients suffering from various infectious diseases, especially pneumonia and COVID-19, are needed to prove this relationship.
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|
---
title: Ischemic Stroke Causes Disruptions in the Carnitine Shuttle System
authors:
- Leonidas Mavroudakis
- Ingela Lanekoff
journal: Metabolites
year: 2023
pmcid: PMC9968086
doi: 10.3390/metabo13020278
license: CC BY 4.0
---
# Ischemic Stroke Causes Disruptions in the Carnitine Shuttle System
## Abstract
Gaining a deep understanding of the molecular mechanisms underlying ischemic stroke is necessary to develop treatment alternatives. Ischemic stroke is known to cause a cellular energy imbalance when glucose supply is deprived, enhancing the role for energy production via β-oxidation where acylcarnitines are essential for the transportation of fatty acids into the mitochondria. Although traditional bulk analysis methods enable sensitive detection of acylcarnitines, they do not provide information on their abundances in various tissue regions. However, with quantitative mass spectrometry imaging the detected concentrations and spatial distributions of endogenous molecules can be readily obtained in an unbiased way. Here, we use pneumatically assisted nanospray desorption electrospray ionization mass spectrometry imaging (PA nano-DESI MSI) doped with internal standards to study the distributions of acylcarnitines in mouse brain affected by stroke. The internal standards enable quantitative imaging and annotation of endogenous acylcarnitines is achieved by studying fragmentation patterns. We report a significant accumulation of long-chain acylcarnitines due to ischemia in brain tissue of the middle cerebral artery occlusion (MCAO) stroke model. Further, we estimate activities of carnitine transporting enzymes and demonstrate disruptions in the carnitine shuttle system that affects the β-oxidation in the mitochondria. Our results show the importance for quantitative monitoring of metabolite distributions in distinct tissue regions to understand cell compensation mechanisms involved in handling damage caused by stroke.
## 1. Introduction
Ischemic stroke is one of the major causes of death worldwide and accounts for more than $80\%$ of all stroke incidents [1]. To study ischemic stroke, middle cerebral artery occlusion (MCAO) is the most commonly used mouse model and it involves physical obstruction of blood flow towards part of the brain using an intraluminal suture [2]. The obstruction of blood flow that is the signature of stroke has detrimental effects on the homeostasis of cells and results in inflammation, oxidative stress, ionic imbalance, excitotoxicity, and finally apoptosis [3]. The oxidative stress induced due to the release of high intracellular levels of Ca2+, Na+ and adenosine diphosphate (ADP) is deleterious for the mitochondria. Since mitochondria are the cells’ primary energy production stations this is largely affected by ischemic stroke.
The mitochondria can produce energy through the oxidation of fatty acids (FAs), which is an alternative when the essential nutrients, such as glucose, are not available to the brain cells. However, β-oxidation, the process of oxidizing FAs to produce acetyl-CoA, is not as favorable as glucose oxidation because it requires $15\%$ more oxygen, produces superoxides, and generates less ATP [4]. Nevertheless, up to $20\%$ of energy requirements can be provided by FA oxidation in brain [5].
Oxidation of long-chain (C14-C20) FAs is a multistep process that requires their transport into the mitochondria. Specifically, they are imported through the carnitine shuttle system while the shorter-chain (C3-C12) FAs simply diffuse through the mitochondrial membrane [6,7]. Once the FAs are activated and in the form of acyl-CoA esters, they are coupled with carnitine through the enzyme carnitine palmitoyltransferase 1 (CPT1) and transported through the outer mitochondrial membrane. Following, the acylcarnitines (ACs) are transported across the inner mitochondrial membrane using the carnitine-acylcarnitine translocate (CACT). Finally, carnitine palmitoyltransferase 2 (CPT2) catalyzes the decoupling of the carnitine moiety from the acylcarnitines in order to produce fatty acyl-CoA that can enter the cycle of β-oxidation for energy generation. By use of individual acylcarnitines concentration, or their ratios to carnitine, several studies have assessed the activity of CPT1 and CPT2 in biological systems [8,9,10,11,12].
The energy status of biological systems monitored through analysis of carnitine and ACs is typically performed by coupling liquid chromatography (LC) to mass spectrometry (MS) [12,13,14]. Although such approaches are highly robust and sensitive, the necessary sample homogenization prohibits the determination of analyte distribution within selected parts or regions of the tissue. An attractive alternative is therefore to use mass spectrometry imaging (MSI) techniques, which can provide localized information on ACs and thereby directly assess the cells’ energy status in intact tissue sections [15,16,17]. Nanospray desorption electrospray ionization (nano-DESI) is an MSI technique that uses a localized liquid extraction of analytes from the tissue surface. In short, the analytes are desorbed from the tissue into a liquid bridge flowing between two fused silica capillaries positioned in front of the mass spectrometer [18,19]. Following, the desorbed analytes are transported through the second fused capillary towards the inlet of the mass spectrometer and ionized by electrospray or pneumatically assisted (PA) electrospray due to vacuum inside the MS or the Venturi effect, respectively [20]. By moving the sample under the liquid bridge, data are continuously acquired for subsequent construction of 2-D maps showing analyte distributions in the tissue. Each pixel on the constructed 2-D maps corresponds to the intensity of a selected ion from each scan event through the data acquisition. In nano-DESI, quantitation is enabled by addition of standards to the nano-DESI solvent and challenging analytes can be targeted by addition of reagents for reactive chemistry [21,22,23,24].
Here, we have employed PA nano-DESI MSI to study the energy status of the damaged cellular region in ischemic stroke by mapping the distribution of ACs in the MCAO stroke model. The distributions and annotations of endogenous ACs were confirmed using deuterated standards and fragmentation patterns. Finally, we report the increased activity of CPT1 and CPT2 in the brain hemisphere damaged by ischemic stroke compared to the healthy hemisphere. Overall, our results suggest impaired transportation of FAs through the carnitine shuttle system due to ischemia.
## 2.1. Chemicals and Materials
Methanol and formic acid (98–$100\%$) were purchased from Merck (LC-MS grade). Deionized water (18.2 MΩ) was obtained from an in-house MilliPore purification system. L-carnitine-HCl-(methyl-d3) (referred to herein as C-d3) and octadecanoyl (18,18,18–d3)-L-carnitine-HCl (referred to as C18-AC-d3) were purchased from Larodan AB (Solna, Sweden). D-Glucose-6,6-d2 (referred to as glucose-d2), phosphatidylcholine 11:$\frac{0}{11}$:0 (PC 22:0) and oleic acid-d9 were purchased from Merck.
## 2.2. Pneumatically Assisted (PA) Nano-DESI
The PA nano-DESI probe was constructed using fused silica capillaries (50 µm ID and 150 µm OD Polymicro Technologies LLC, Pheonix, AZ, USA) fixed in an in-house developed 3D printed casing that kept the primary and the secondary capillary in position [20]. A backpressure of 2.5 bar nitrogen gas was used for pneumatically assisted nanospray. The solvent was methanol:water 9:1 v/v and $0.1\%$ formic acid spiked with known concentrations of internal standards and was delivered through the primary capillary using a syringe pump (Legato 180, KD Scientific, Holliston, MA, USA) [22,25]. Dataset A was acquired at a flowrate of 0.5 µL min−1 with the solvent containing 0.2 µM c-d3, 0.2 µM C18-AC-d3, 30.5 µM glucose-d2 and 4 µM PC 22:0. Dataset B was acquired at a flowrate of 0.3 µL min−1 with the solvent containing 0.4 µM C-d3, 0.1 µM C18-AC-d3, 30.5 µM glucose-d2, 2 µM oleic acid-d9, and 4 µM PC 22:0.
## 2.3. Middle Cerebral Artery Occlusion Mouse Model
All animal experiments were performed by Creative Biolabs Inc. (Shirley, NY, USA) and MCAO brains from mice were purchased and sectioned in our facilities. Specifically, MCAO was induced in 8–10 weeks old male C57BL/6 mice for 1 h followed by 2 h of reperfusion prior to sacrificing the animals and removing the intact brain. Three flash frozen MCAO mouse brains were purchased and sectioned coronally using a Leica CM1900 cryotome (Leica Microsystems) at 10 µm thickness. The tissue sections were thaw-mounted on regular glass slides and stored at −80 °C until analysis. In total, 17 tissue sections from three animals were analyzed, 8 in dataset A and 9 in dataset B.
## 2.4. Mass Spectrometry Imaging
The glass slide with the tissue section was mounted on an X-Y-Z motorized stage (Zaber Technologies Inc., Vancouver, BC, Canada) that was controlled by a custom designed LabVIEW program [26]. The sample was moved at a rate of 0.04 mm s−1 along the x-axis direction with a step along the y-axis of either 150 µm or 75 µm for improved spatial resolution through oversampling [27]. The calculated pixel size along the x-axis was ~24 µm based on the scan rate of the mass spectrometer (1.7 scans s−1) and the stage scanning speed (40 µm s−1). Along the y-axis, the pixel size is determined by the stepping size of the stage. The data were recorded using a QExactive mass spectrometer (Thermo Fischer Scientific, Bremen, Germany) in the positive ion mode between m/z 70–1000 with an electrospray voltage of 3.5 kV applied directly on the syringe delivering the solvent. The mass spectrometer was operated at resolution of 140,000, ion transfer capillary temperature of 300 °C, automatic gain control (AGC) target of 1e6, maximum injection time of 300 ms with a typical injection time (IT) of 2 ms, and S-lens RF level of 50.
## 2.5. MS/MS of Carnitine Standards and Endogenous Carnitines
For identification of endogenous carnitines in the tissue, a Parallel Reaction Monitoring (PRM) method was set up in the positive ion mode with an inclusion list comprised of various putatively identified ACs and added standards (Table S1). The AGC target of each MS/MS event was 2e5 with a maximum inject time of 300 ms and an isolation window of 0.4 m/z. Higher-energy collisional dissociation (HCD) was applied in a stepped manner (at normalized collision energies (nCE) from 10 to 30). For the MS/MS experiments with PA nano-DESI, the conditions were the same as for acquisition of dataset B. The probe was positioned on an ischemic area of an MCAO mouse brain tissue section and slightly moved in the area to continuously desorb endogenous molecules.
## 2.6. Data Processing and Statistical Analysis
After data collection, Thermo RAW files were converted to mzML files using MSConvert (Proteowizard) [28]. The mzML files were processed using MATLAB R2022a (MathWorks, USA) with in-house developed scripts for obtaining the intensity of target m/z values from each data file within 5 ppm of mass error tolerance. For ion image normalization, the intensity of the endogenous ion in each pixel was divided by the intensity of the appropriate internal standard. Region of interest (ROI) of areas corresponding to the healthy and the ischemic part of the tissue were selected using the in-house script for further interrogation. The ischemic ROI was selected using ions known to accumulate [23,29,30], verified by overlaying with the optical image, and the healthy ROI was selected as mirror with a similar amount of pixels (Table S2). The average intensities of selected ions were obtained from each ROI and statistical analysis was conducted using a two-tailed Wilcoxon rank sum test. For statistical analysis, data within the 5th and 95th percentile of the dataset were considered.
## 3.1. Matrix Effects between Healthy and Ischemic Region Are of Equal Magnitude
Matrix effects in MS are inherently challenging, especially in MSI where a pre-separation step is omitted. In principal, matrix effects during ionization result in ion suppression or ion enhancement and two types can be observed; alkali metal ion related and molecular composition related [21]. Imaging with nano-DESI enables internal standards to be included in the nano-DESI solvent for quantitation and to study matrix effects, such as ion suppression. The magnitude of ionization suppression during imaging was studied using the two standards C18-AC-d3 and C-d3. Following, the amount of suppression was calculated using the absolute difference between the average intensity of one standard in a tissue area (Itissue in Equation [1]) and the average intensity of the same standard on an area on glass (Iglass in Equation [1]), divided by its intensity on a glass area (Equation [1]). % Suppression = (|Itissue − Iglass|)/Iglass × 100[1] The average tissue intensities were obtained from the areas shown in Figure 1a, where blue corresponds to the healthy region and green to the region damaged by ischemic stroke (Table S3). From Equation [1], it follows that an analyte with zero intensity on the tissue area would have $100\%$ suppression and that an analyte that is not affected by ion suppression would have $0\%$ ion suppression and thereby a conserved intensity on the tissue compared to the glass. The results show a slightly overall higher suppression of ~$12\%$ for the C18-AC-d3 compared to C-d3 on the tissue in both the healthy and ischemic areas (Table S4). However, importantly, neither standard shows a difference in ionization suppression between the two regions (Figure 1b).
## 3.2. Use of Internal Standards Allows for Robust Relative Quantification of Endogenous Molecules
The inclusion of appropriate internal standards in the PA nano-DESI solvent also allows for relative quantitation of detected endogenous analytes. This is typically achieved using a one-point calibration where the intensity ratio of the analyte to the internal standard (Iend/IIS) is multiplying with the concentration of the internal standard (CIS, µM) [31] (Figure S1). Furthermore, the detected moles (nend) in each mass spectrum can be calculated by including the solvent flowrate (F, µL min−1) and the scan time between two subsequent scan events (ST, milliseconds) (Equation [2]). nend = (Iend/IIS) × CIS × F × ST, [2] Here, we demonstrate that by accounting for the solvent flow rate, the quantitative approach can accommodate datasets acquired with different flow rates and concentrations of the internal standards. In particular, we show that there is no significant difference between the detected amounts of endogenous carnitine and C16-AC for datasets A and B despite the different flow rates and concentrations of internal standards during acquisition (Figure 1c,d). Overall, this is of importance when comparing datasets acquired under slightly different conditions.
## 3.3. Identification of Endogenous Acylcarnitines through MS/MS
Annotation of analytes with mass spectrometry imaging mainly relate to product ion formation in MS/MS experiments, therefore, the fragmentation patterns of the protonated standards C-d3 and C18-AC-d3 were studied. Both standards show the main fragmentation sites around the head group [14,32], despite their differences in size. Furthermore, product ions associated with the C18-AC-d3 acyl chain are only detected at low abundances (Figure 2a,b, Figure S2 and Figure S3). However, when investigating different HCD levels, it is clear that the C-d3 and C18-AC-d3 have different fragmentation efficiency of the respective sites.
At HCD nCE of 20 units, C-d3 predominantly loses the trimethylamine group and leaves a base peak product ion at m/z 103 (Figure 2a and Figure S2). For C18-AC-d3, the dominating product ion is instead formed from the loss of both the trimethylamine group and the acyl chain, which leaves the product ion at m/z 85 (Figure 2b and Figure S3). Additional product ions of C18-AC-d3 are in much less abundance, including the product ion at m/z 372, which is produced through the same fragmentation pathway as the m/z 103 of C-d3.
At nCE of 30, the distribution of product ions for C-d3 is shifted and the deuterated trimethylamine group at m/z 63 becomes most abundant while the m/z 103 has the lowest relative abundance among the product ions. For C18-AC-d3, the dominating product ion of is still the m/z 85. However, at much lower abundances the resemblance to the fragmentation pattern of C-d3 is high with an increased abundance of the trimethylamine group at m/z 60 (Figure 2b insert). It seems that the presence of the acyl chain in C18-AC-d3 induces a more efficient fragmentation towards the product ion m/z 85. Overall, compared to C-d3, the larger ACs appear to fragment less efficiently at lower HCD (20 nCE), which indicates a structure-related stability during the activation step of the HCD process. Importantly, these differences in fragmentation efficiency are crucial for annotating ACs based on MS/MS and for obtaining the highest sensitivity in selected reaction monitoring (SRM) or multiple reaction monitoring (MRM).
Based on our findings, thirteen endogenous ACs were annotated directly from tissue using a PRM method with stepped HCD. The precursors of the inclusion list, the detected m/z value, the characteristic fragments, and the assignments of carnitines detected directly from the tissue section are summarized in Table S1.
## 3.4. PA Nano-DESI MSI of MCAO Stroke Model
Imaging with PA nano-DESI MSI readily provides ion images of carnitine and ACs with various chain lengths. In addition to the thirteen identified endogenous acylcarnitines, the tissue could include ACs with –OH modifications or acyl chain between 6 and 11, and over 18. ( Figure 3 and Table S1). Generally, the detected intensities of C3-, C4-, C5-, C12- and C14:1-AC were lower compared to the other ACs. All ion images in Figure 3 are normalized to its closest related internal standard, the small endogenous C-C5 to the C-d3 and the larger C12-C18 to the C18-AC-d3, although no difference in distribution can be observed depending on normalization (Figure S5 and Figure S6). Two different trends of distributions in brain tissue are observed (Figure 3 and Figure S4). Specifically, carnitine and C2-AC localize similarly throughout the brain section with higher localization in the regions of hypothalamus (HY) and thalamus (TH). The rest of the detected ACs are found mainly in white matter regions (corpus callosum, cc) and in caudoputamen (CP).
The ischemic area of the tissue is located in the right hemisphere of the brain and specifically in the caudoputamen (CP) (Figure 3, Figure S4 and Figure S5). This was confirmed both by the decreased abundance of K+/Na+ adduct ratios of standard PC 22:0 as well as the optical image (Figure S7) [21,23,33]. Upon visual inspection, long-chain ACs such as C14-, C14:1-, C16-, C16:1, C18-, C18:1-, C18:2- have a higher abundance in the ischemic region, with the most notable difference in the ion image of C18-carnitine. However, to fully realize the metabolite differences inflicted by ischemia, the average detected amounts need to be assessed from a larger dataset through ROI analysis.
## 3.5. Region of Interest Analysis
To enable statistical comparison of the localization of metabolites in the tissue, ROI analysis was performed by selecting the ischemic and the healthy regions and averaging the intensities of the metabolites of interest. Following, the raw average intensities of each endogenous molecule were converted to detected moles per pixel using the respective internal standard and Equation [2]. Statistical comparisons of 16 tissues sections were performed using a Wilcoxon rank sum test (two-tailed) and one section was removed as an outlier. The results show that C4-, C14-, C16-, C18-, C18:1-, C18:2-AC and LPC 16:0 are accumulating 1.26- to 2.3-fold in the ischemic region (Figure 4, Figure S8 and Table S5). Additionally, carnitine, C2-, C3-, C5-,C12-AC, and free FAs 18:1 and 18:2 were found at similar amounts in the healthy and ischemic regions (Figure S8 and Figure S9). Finally, glucose was found to be significantly decreased in the ischemic region (Figure S8).
Since ACs are actively transported into the mitochondria for subsequent β-oxidation (Figure S10), the enzymatic activity of CPT1 and CPT2 was calculated based on the concentration of individual ACs [6,9,34]. Specifically, the ratio of (C16-AC + C18-AC)/carnitine was used for CPT1 and (C16-AC + C18:1-AC)/C2-AC for CPT2. It was found that the activity of both CPT1 and CPT2 was elevated in the ischemic region (Figure 4). Furthermore, it was found that β-oxidation, determined using the ratio of C2-AC/carnitine, was conserved despite ischemia (Figure 4).
## 4. Discussion
The onset of ischemic stroke keeps essential nutrients such as oxygen and glucose from reaching the ischemic region, which causes cell damage and forces cells to use alternative strategies for energy [35]. The use of internal standards and annotation with MS/MS in combination with MSI enables the simultaneous assessment of ischemic stroke on thirteen detected AC species. In energy generation through β-oxidation, long-chain ACs (C12-C20) are important for introducing activated long-chain FAs into the mitochondria (Figure S10) [6,34]. The detected accumulation of C14-, C16-, C18-, C18:1- and C18:2-AC in this study is a well-known indicator of disrupted transportation and oxidation of FAs [12,13,34]. This suggests that ischemic stroke causes metabolic dysfunctions in the carnitine shuttle system that limit the use of long-chain FAs for energy production and ultimately cell survival [12]. Additionally, accumulation of C4-AC in the ischemic area provides evidence that short-chain FA metabolism is also disturbed [36,37]. In particular, the accumulation of the short-chain C4-carnitine in hypoxic-ischemic encephalopathy has been previously linked to mitochondrial failure and reported as a result of inhibition or defects of short-chain acyl-CoA dehydrogenase [36,37].
By assessing enzymatic activity using the ratio of acylcarnitines to free carnitine or acetylcarnitine [6,9,34], our data provide evidence for increased activity of CPT1 and CPT2 in the ischemic region of the tissue and no change in β-oxidation (Figure 4). This clearly demonstrates that the carnitine shuttle system is disrupted; although the point of disruption cannot be distinguished. Generally, it would be reasonable to assume that increased amounts of long-chain acylcarnitines is a consequence of increased CPT1 action and a decreased CPT2 activity [38,39,40]. However, this is not supported by our data (Figure 4). Nevertheless, it cannot be ruled out that the net effect we observe is due to an increased CPT2 activity on top of an even higher activity of CPT1. CPT1 is the rate-limiting enzyme in the carnitine shuttle system and its increased activity could be justified by the lack of its natural inhibitor; malonyl-CoA [41,42,43]. Malonyl-CoA is produced mainly via the metabolism of glucose but with the evidenced decreased amount of glucose in the ischemic area, it can be expected that the levels of malonyl-CoA are also reduced (Figure S8) [41,44]. Consequently, inhibition of CPT1 would be limited and result in the detected accumulation of long-chain acylcarnitines. Furthermore, an increased activity of CPT1 can lead to excess conversion of the long-chain FAs 18:1 and 18:2 to the corresponding acylcarnitines, which would explain the lack of FA 18:1 and 18:2 accumulation in our data (Figure S8) [13]. It would be of interest in future work to monitor the enzymatic activities in the carnitine-shuttle system during ischemia to further elucidate the main contributing step to the disruption and elucidate contributions from the previously reported isoforms [41]. Gaining a deeper understanding of the molecular mechanisms activated during stroke will greatly contribute to future targeting of enzymes for treatment and damage alleviation.
## 5. Conclusions
It is well known that stroke is a detrimental condition for cell survival. By imaging with PA nano-DESI MSI we show that C4-AC and long-chain ACs accumulate in the ischemic region of the brain after MCAO. By quantifying thirteen carnitine species, we estimate the enzymatic activity of the carnitine transporting enzymes CPT1 and CPT2 by calculating carnitine ratios. Despite our finding that both CPT1 and CPT2 are increased in the ischemic region, we hypothesize that the activity of CPT1 is more elevated due to the lack of its natural inhibitor malonyl-CoA that is usually formed through commonly used energy generating pathways. Overall, our findings are consistent with prevailing theories using bulk analysis and show for the first time the additional dimension of the distinct distributions and abundances of long-chain ACs in ischemic stroke brain tissue.
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|
---
title: 'Human Hepatocyte Nuclear Factors (HNF1 and LXRb) Regulate CYP7A1 in HIV-Infected
Black South African Women with Gallstone Disease: A Preliminary Study'
authors:
- Suman Mewa Kinoo
- Pragalathan Naidoo
- Bhugwan Singh
- Anil Chuturgoon
- Savania Nagiah
journal: Life
year: 2023
pmcid: PMC9968087
doi: 10.3390/life13020273
license: CC BY 4.0
---
# Human Hepatocyte Nuclear Factors (HNF1 and LXRb) Regulate CYP7A1 in HIV-Infected Black South African Women with Gallstone Disease: A Preliminary Study
## Abstract
Female sex, high estrogen levels, aging, obesity, and dyslipidemia are some of the risk factors associated with gallstone formation. HIV-infected patients on combination antiretroviral therapy (cART) are more prone to hypercholesterolemia. Bile acid synthesis is initiated by cholesterol 7-alpha hydroxylase (CYP7A1) and regulated by hepatocyte nuclear factors (HNF1α, HNF4α, and LXRb). The aim of this study was to evaluate the expression of HNF1α, HNF4α, LXRb, and miRNAs (HNF4α specific: miR-194-5p and miR-122*_1) that regulate CYP7A1 transcription in HIV-infected Black South African women on cART and presenting with gallstones relative to HIV-negative patients with gallstone disease. Females ($$n = 96$$) presenting with gallstone disease were stratified based on HIV status. *The* gene expression of CYP7A1, HNF1α, HNF4α, LXRb, miR-194-5p, and miR-122*_1 was determined using RT-qPCR. Messenger RNA and miRNA levels were reported as fold change expressed as 2−ΔΔCt (RQ min; RQ max). Fold changes >2 and <0.5 were considered significant. HIV-infected females were older in age ($$p \leq 0.0267$$) and displayed higher low-density lipoprotein cholesterol (LDL-c) ($$p \leq 0.0419$$), CYP7A1 [2.078-fold (RQ min: 1.278; RQ max: 3.381)], LXRb [2.595-fold (RQ min: 2.001; RQ max: 3.000)], and HNF1α [3.428 (RQ min: 1.806; RQ max: 6.507] levels. HNF4α [0.642-fold (RQ min: 0.266; RQ max: 1.55)], miR-194-5p [0.527-fold (RQ min: 0.37; RQ max: 0.752)], and miR-122*_1 [0.595-fold (RQ min: 0.332; RQ max: 1.066)] levels were lower in HIV-infected females. In conclusion, HIV-infected women with gallstone disease displayed higher LDL-c levels and increased bile acid synthesis, which was evidenced by the elevated expression of CYP7A1, HNF1α, and LXRb. This could have been further influenced by cART and aging.
## 1. Introduction
The advent of combination antiretroviral therapy (cART) in human immunodeficiency virus (HIV) treatment was one of the most significant advances in modern medicine. The HIV epidemic went from a public health crisis to a chronic treatable disease as cART markedly extended the life expectancy of infected individuals. While the large scale rollout of cART has made a positive impact on the outcomes of HIV morbidity and mortality, there now emerges an unprecedented population of people aging with HIV [1,2,3]. This has led to a new phenomenon—an “epidemic within an epidemic”—with metabolic disorders becoming increasingly prevalent in HIV-positive individuals on cART. These range from acute to chronic adverse effects, with the most common being cardiovascular disease, lipodystrophy, diabetes, and metabolic syndrome [4,5,6,7,8]. Altered glucose metabolism and hypercholesterolemia are hallmarks of HIV patients on chronic cART [6,8,9]. Kato et al. [ 2020] reported higher low-density lipoprotein (LDL) levels in HIV-positive patients on antiretroviral therapy (ART) relative to ART-naïve patients [6]. Elevated circulating LDL cholesterol (LDL-c) contributes to several of the metabolic syndromes, including symptoms observed in people on cART. Despite the established prevalence of metabolic syndromes and altered cholesterol homeostasis in this population, there is a dearth of knowledge on gallstone disease, a disease closely linked to both these factors [10].
Cholesterol gallstones, the result of biliary cholesterol superseding its saturation point, causing cholesterol microcrystal formation [11], account for ~$80\%$ of all gallstones in Western populations [12]. The etiology of gallstone formation involves an interplay between genetic and environmental factors. Risk factors include obesity, female sex, high estrogen levels, aging, diabetes, and metabolic syndrome [13,14]. Historically, gallstone disease was the most prevalent in North America, South America, some European populations, and India [15]; however, the rapid rate of urbanization, high fat diets, and the influence of HIV on non-communicable diseases has produced a paradigm shift, warranting more investigation into developing countries and Sub-Saharan Africa [14]. Data collected in South Africa suggest a steady increase in gallstone disease in the Black African population over the past ten years [16,17]. Considering the HIV endemic setting, very little is known regarding HIV-positive patients on cART with gallstone disease [18].
Gallstones are the result of a shift in equilibrium of the triad of cholesterol, bile acid, and lecithin, favoring bile to exist in a lithogenic rather than a liquid state [11]. Bile acid synthesis is initiated by the rate-limiting enzyme cholesterol 7-alpha hydroxylase (CYP7A1) [19]. This enzyme is a member of a superfamily known as cytochrome P450 (CYP) monooxygenases which catalyze reactions in xenobiotic metabolism, steroid synthesis, and fatty acid metabolism. CYP7A1 catalyzes the conversion of cholesterol to 7-alpha-hydroxycholesterol, initiating bile synthesis. The CYP7A1 enzyme is regulated via multiple pathways, including a negative feedback loop from the hepato-enteric circulation of bile acids [20]. As CYP7A1 regulates the first step of bile acid synthesis, it has been extensively investigated in relation to gallstone formation. Several studies have evaluated genetic variations in the CYP7A1 gene in relation to gallstone disease risk, with stronger links found to genetic predisposition in males compared to females [21,22,23,24], while a deficiency in the enzyme is associated with gallstone formation [25,26]. Considering that females are disproportionately affected by gallstone disease, and they make up the demographic at highest risk for new HIV infections in South Africa, alternative molecular mechanisms need to be investigated.
The transcription of the CYP7A1 gene is regulated by transcription factors in response to fluctuations in bile acid and cholesterol. Hepatocyte nuclear factors (HNFs) are a group of transcription factors—predominantly expressed in the liver—that maintain metabolic homeostasis through the regulation of genes involved in glucose, cholesterol, and fatty acid metabolism [27]. Hepatocyte nuclear factor 1 alpha (HNF1α) and hepatocyte nuclear factor 4 alpha (HNF4α) are HNFs that respond to bile acid levels: HNF4α binds directly to CYP7A1 [28], while HNF1α binds to CYP7A1 regulators—hepatic bile acid binding protein and Farnesoid X receptor (FXR) [29]. MicroRNAs (miRNAs), namely miR-194-5p and miR-122*_1, are chiefly regulated by HNF4α in the liver [30,31]. Liver X receptor α/β (LXR α/β) is closely related to FXRs and binds to the liver x receptor element (LXRE) of the LXR target genes. Among these target genes are regulators of reverse cholesterol transport, the most prominent being ATP-binding cassette (ABC-) G1, ABCG5, and ABCG8. The activity of these cellular efflux pumps determines cholesterol flux, thus regulating CYP7A1 activity in response to hepatic cholesterol concentration [32,33].
Nuclear factors such as HNFs and LXRs are key upstream regulators of hepatic cholesterol metabolism and bile acid synthesis. The dysregulation of these transcriptional regulators leads to pathogenic outcomes that underlie metabolic disorders. This present study sought to evaluate the expression of hepatic nuclear factors (HNF1α, HNF4α, and LXRb) and miRNAs (HNF4α specific: miR-194-5p and miR-122*_1) that regulate CYP7A1 transcription in HIV-positive Black South African women on cART and presenting with gallstones relative to HIV-negative patients with gallstone disease.
## 2.1. Patient Recruitment
This study utilized a case-series design comparing the hepatic expression of cholesterol regulating genes in HIV-positive (case) and HIV-negative (control) patients presenting with symptomatic gallstones. Ethical approval was obtained from the University of KwaZulu Natal (UKZN) Biomedical Research Ethics Committee (BREC) (BE$\frac{276}{16}$). Patients undergoing cholecystectomy for gallstone disease (biliary cholic, cholecystitis, jaundice, and gallstone pancreatitis) at King Edward VIII Hospital, Durban, KwaZulu Natal, South Africa, from January–December 2017 were recruited. In total, 96 Black South African women provided informed consent (standard consent form in two official main languages, i.e., English and isiZulu) for the retrieval of a liver biopsy and the recording of patient clinical parameters, including age, race, BMI, family history of gallstones, and comorbidities (HIV, hypertension, diabetes, hypercholesterolemia). The study was carried out in accordance with the institutional guidelines.
Following the analysis of clinical parameters in all subjects, five HIV-negative (control) and five HIV-positive (cases) were selected for mRNA analysis to identify if hepatic nuclear factors were differentially regulated. All patients selected were of Black African ethnicity and female gender, with no co-morbidities (diabetes and hypertensive statin therapy, hepatitis infection, or tuberculosis treatment). All HIV-positive patients were on fixed dose combination (FDC) therapy, with CD4 counts above 500 cells/mm3 and undetectable viral loads. The FDC regimen consisted of 3 drugs, namely two nucleoside reverse transcriptase inhibitors (NRTIs) drugs [tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC)] and one non-nucleoside reverse transcriptase inhibitor (NNRTI) [efavirenz (EFV)]. Common second-line agents used were protease inhibitors (PI) [lopinivar/ritonavir (Aluvia) or atazanavir/ritonavir]. None of the patients were on integrase strand transfer inhibitor (InSTI) [dolutegravir (DTG)] based therapies.
## 2.2. RNA Extraction and Real Time Quantitative PCR (RT-qPCR)
Liver tissue (1 cm × 1 cm) was submerged in RNAlater® Stabilization Reagent (Qiagen, Hilden, Germany) in 2 mL cryovials at collection and stored at −80 °C until RNA isolation. RNA was extracted using a chloroform-based method using *Qiazol lysis* buffer (Qiagen), per the manufacturer’s instructions. The purity and concentration of the crude RNA was assessed using the Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The crude RNA was standardized to a concentration of 1000 ng/μL and stored at −80 °C until further use.
Thereafter, 1 µg of the standardized RNA sample was used for complementary DNA (cDNA) synthesis using PCR. The miScript RT II kit (Qiagen) (miRNA gene expression studies) and QuantiTect Reverse Transcription kit (Qiagen) (gene expression studies) were used to create cDNA, per the manufacturer’s instructions.
Messenger RNA quantification (CYP7A1, HNF1α, HNF4α, and LXRb) and miRNA quantification (miR-194-5p and miR-122*_1) were performed using the Applied Biosystems Viia7 Real-Time PCR System (Thermo Fisher Scientific).
MiRNA expression studies were performed using the miScriptTM SYBRTM Green PCR kit (Qiagen, Hilden, Germany) and specific miScript Primer Assays for the above-mentioned miRNAs (Qiagen), according to the manufacturer’s instructions. Human RNA, U6 small nuclear 2 (RNU6-2), was used as a housekeeping gene.
Messenger RNA gene expression studies were performed using the PowerUp™ SYBR™ Green Master Mix (Thermo Fisher Scientific) and specifically designed primer sequences for the above-mentioned genes (Inqaba Biotec, Ibadan, Nigeria), according to the manufacturer’s instructions. The sense and antisense primer sequences for the above-mentioned genes are shown in Table 1, along with their annealing temperatures. *Housekeeping* genes GAPDH and 18SrRNA were concurrently quantified for normalization of the results.
## 2.3. Statistical Analysis
Comparisons of clinical parameters between HIV-negative (control) and HIV-positive (cases) patients presenting with gallstones were conducted by performing a Mann–Whitney U Test. All data were analyzed using the GraphPad Prism 7 statistical software package. A result of $p \leq 0.05$ was considered statistically significant.
RT-qPCR analysis of mRNA levels was performed using the QuantStudio 7 Pro Real-Time PCR Systems Software (Thermo Fisher Scientific). Messenger RNA and miRNA levels were reported as relative fold change, expressed as 2−ΔΔCt (RQ min; RQ max). Fold changes relative to the HIV-negative controls of >2 and <0.5 were considered significantly different, based on the calculation described above.
## 3.1. Clinical Characteristics of Patients
The analysis of the clinical parameters is summarized in Table 2. The HIV-positive group was significantly older than the HIV-negative controls ($$p \leq 0.0267$$). The results show that the HIV-positive group had a lower BMI, with overall higher levels of total cholesterol, triglycerides, high density lipoprotein cholesterol (HDL-c), and significantly higher low-density lipoprotein cholesterol (LDL-c) ($$p \leq 0.0419$$).
## 3.2. Hepatic CYP7A1, LXRb, HNF1α, and HNF4α Gene Expression
RT-qPCR analysis showed that the hepatic mRNA levels of CYP7A1 were significantly higher in women with HIV and gallstone disease relative to women with gallstone disease alone [2.078-fold (RQ min: 1.278; RQ max: 3.381)] (Figure 1). The transcriptional regulators of CYP7A1 were subsequently quantified: LXRb [2.595-fold (RQ min: 2.001; RQ max: 3.000)] (Figure 2A) and HNF1a [3.428-fold (RQ min: 1.806; RQ max: 6.507] (Figure 2B) mRNA levels were concomitantly higher in the HIV-positive women compared to the HIV-negative control group. Hepatic HNF4a mRNA levels were lower in HIV-positive women [0.642-fold (RQ min: 0.266; RQ max: 1.55)] (Figure 2C).
## 3.3. Hepatic miR-194-5p and miR-122*_1 Gene Expression
Hepatic miRNAs regulated by HNF4α were quantified by RT-qPCR. Both miR-194-5p [0.527-fold (RQ min: 0.37; RQ max: 0.752)] (Figure 3A) and miR-122*_1 [0.595-fold (RQ min: 0.332; RQ max: 1.066)] (Figure 3B) were observed at lower concentrations in HIV-positive women compared to HIV-negative women with gallstone disease.
## 4. Discussion
Gallstone disease is triggered by several risk factors, including female sex, aging, obesity, high estrogen levels, and dyslipidemia [13,14]. Within the context of an African population, age, waist circumference, and LDL-c were risk factors for gallstone disease in Sudanese individuals [34]. In Black South African women, BMI and continuous exposure to a Western lifestyle (characterized by high fat intake and low dietary fiber intake) were the main risk factors for gallstone disease [16].
Long-term use of cART has been linked to a number of metabolic diseases; however, there is a paucity of data on its association with gallstone disease in black South Africans [9,10,11,12]. It has been demonstrated in other populations that the accumulative exposure to atazanavir/ritonavir for over 2 years is associated with a 6.29-fold increase in the risk for incident cholelithiasis [18,35,36,37], while other studies report an increased rate of cholelithiasis ($9.8\%$) in HIV-positive patients on protease inhibitor (PI)-inclusive cART [38]. HIV-infected patients on cART are more susceptible to hypercholesterolemia [6,9]. Despite newer integrase inhibitor (II) antiretroviral drugs showing lower lipid abnormalities than previously used PI-based ART, abnormalities in lipid concentration still occur, and this may be reflective either of the viral effects itself, chronic ART use, or persistent immune activation in HIV infection [39].
Atazanavir, ritonavir, and indinavir significantly decreased CYP7A1 mRNA levels in rodent hepatocytes, indicating an effect of cART on the bile acid synthesis pathway [40,41]. A substantial amount of evidence dating back as far as 1975 [42], along with more recent evidence, has demonstrated that a deficiency in CYP7A1 [43], genetic variations in the CYP7A1 gene [44], and the inhibition of CYP7A1 with lipid lowering drugs such as fibrates [45], result in increased cholesterol excretion in bile, which increases the risk of gallstone formation [22,26]. Relative to Admirand’s theory, lower CYP7A1 activity compromises the conversion of cholesterol to bile acid, resulting in increased cholesterol excretion and decreased bile acid excretion, favoring gallstone formation [11]. In Chilean Hispanic and Mapuche subjects (known to have one of the highest incidences of gallstones worldwide), an increase in CYP7A1 expression [46] and an increase in bile acid excretion [47] resulted in a higher incidence of gallstone formation. Our study showed that HIV-positive patients on cART displayed higher hepatic CYP7A1 mRNA (Figure 1), suggesting a possible response to the impaired enterohepatic circulation of bile acids in HIV-positive patients [48]. It is worth noting that the studies demonstrating a cART-mediated reduction in CYP7A1 mRNA levels have been conducted in PI-type antiretroviral drugs [40,41], while the patients in this study are on NRTI/NNRTI-based therapies. Further, the chronic inflammatory impact of HIV infection in conjunction with cART use must be considered as a factor influencing CYP7A1 expression. The accelerated aging phenotype observed in HIV-positive populations is a likely contributor to increased CYP7A1 mRNA levels [49,50,51]. This finding warranted investigation into the transcriptional regulators of CYP7A1, namely HNF1α, HNF4α, and LXRb.
The regulation of CYP7A1 by HNF1α has been studied extensively in mice, and it was found to downregulate CYP7A1 indirectly by binding to FXR receptors [29,52]. In a murine study, HNF1α was found to be a transcriptional regulator of FXR, and when HNF1α was inhibited, it resulted in the downregulation of FXR, with resultant gallstone formation [53]. Moschetta et al. [ 2004] reported that FXR knockout mice that were fed a lithogenic diet displayed an increased susceptibility to developing gallstones. The administration of the FXR agonist to the gallstone-susceptible mice decreased their susceptibility to gallstone formation [54]. Similar findings were reported elsewhere [55]. However, in a study by Chen et al. [ 1999], it was demonstrated that unlike in rodents, where HNF1α regulates CYP7A1 by binding to FXR, in humans HNF1α binds directly to CYP7A1 and increases its transcriptional activity, thus having the opposite effect to that observed in rodents [56]. Similar to the findings from Chen et al. [ 1999], in our study, HIV-infected patients with gallstones displayed increased expression of CYP7A1 and HNF1α compared to their HIV-negative counterparts with gallstones, indicating that HIV may have an effect on HNF1α and CYP7A1.
Another hepatic nuclear factor, HNF4α, binds directly to CYP7A1. Bile acids cause a negative feedback loop, resulting in the downregulation of CYP7A1, not only via HNF1α and FXR, but also HNF4α, which has a direct binding site on CYP7A1. Normally, HNF4α binds and upregulates CYP7A1; however, there is evidence that bile acids can downregulate CYP7A1 transcription by reducing the transactivation potential of HNF4α [28]. In our findings, however, among HIV-positive patients with gallstones, HNF4α was reduced in comparison to the levels in HIV-negative patients, yet CYP7A1 was upregulated. This demonstrates that HNF4α on its own is not a regulator of CYP7A1 in the pathogenesis of gallstones in HIV-positive patients. This mirrors the results of other studies that demonstrated that HNF4α, together with LRH-1, COUP, TFII, and PCG-1α, is required for the upregulation of CYP7A1. HNF4α on its own is not capable of this [57,58]. Bacterial endotoxins, proinflammatory cytokines [59], TNF-α, and interleukin-1 produced by macrophages in the liver [60] are known to decrease the activity of CYP7A1. De Fabiani et al. [ 2001] demonstrated that HNF4α is the target transcriptional factor mediating the effects of these proinflammatory cytokines on CYP7A1 [28]. HIV-positive patients undergo a phenomenon of persistent inflammatory response, which may account for the decrease in HNF4α levels [61]. It must be noted that the HIV-positive group was older than the uninfected control group, with lower BMIs (Table 2). Aging is associated with the decreased expression of HNF4 and consequently, lower bile synthesis through the downregulation of CYP7A1. Bertolotti et al. [ 2008] demonstrated these findings in liver biopsies [62]. While BMI has not directly been linked to hepatic nuclear factors, a high fat diet has been shown to upregulate HNFs. Our previous paper on cholesterol signaling showed that despite having a lower BMI, this group displayed mRNA profiles similar to those expected in people with higher BMIs [63].
HNF4α is a key regulator of hepatic microRNAs miR-122 and miR-194. MiR-122 is found in abundance in the liver and plays an important role in regulating metabolic pathways, including fatty acid synthesis and cholesterol biosynthesis [31]. MiR-194 play a key role in hepatic cell functions [30]. In our study, HNF4α expression was lower in the HIV-infected group, which correlated with the decreased expression of miR-194-5p and miR-122*_1. This suggests that HNF4α may have more of an impact on microRNA expression in the liver than the CYP7A1-mediated bile acid synthesis pathway.
LXR agonists have been shown to bind to LXRE on mouse CYP7A1, causing its upregulation [64]. LXRE binds both LXRa and LXRb; however, LXRa binds more strongly than LXRb; thus, LXRa knockout mice exhibit more cholesterol accumulation. However, human CYP7A1 does not contain LXRE, and is thus shown not to be upregulated by LXRa agonists and seems to be more affected by diet-induced hypercholesterolemia due to its inability to convert cholesterol into bile salts [65]. Goodwin et al. [ 2003] demonstrated a downregulation of CYP7A1 by LXR in response to cholesterol loading [66]. Again, there is the implication that the regulation of the enterohepatic circulation may be a result of this downregulation as a compensation mechanism to decrease cholesterol absorption (by decreasing bile acid production) following a high cholesterol diet; however, in humans, this compensatory mechanism has been shown to be inefficient [67]. In our study, the findings are in keeping with those from mice studies in which an LXRb increase co-existed with an upregulation of CYP7A1, indicating that LXRb might well be a regulator of CYP7A1 and gallstone formation in these group of patients compared to that noted in HIV-negative patients with gallstones. Again this may be due to the underlying dysfunction of enterohepatic terminal ileum absorption in HIV-positive patients, causing LXRb to increase CYP7A1 in an attempt to produce more bile acid for absorption [68].
## 5. Conclusions
In summary, HIV-infected women with gallstone disease displayed higher LDL-c levels and increased bile acid synthesis, which was evident by the elevated expression of CYP7A1, HNF1α, and LXRb. This could have been further influenced by cART and aging. HNF4α, which is known to cause the upregulation of CYP7A1, was suppressed with the upregulation of CYP7A1 and LXR, known to cause the downregulation of CYP7A1 in humans as opposed to mice, having the opposite effect on HIV-infected women.
The best theoretical explanation for this is an interruption in the enterohepatic circulation, as evidenced by HIV-positive patients known to have chronic inflammatory and relative malabsorptive disorders of the ileum, which may result in the upregulation of CYP7A1 to produce more bile salts. This is the most probable explanation for gallstone formation in HIV-positive patients; however, this hypothesis requires validation with further trials and a larger sample size. A limitation of this study is the small sample size used, as well as the fact that the age in the HIV-positive group was significantly higher than that in the control group. However, these preliminary findings can be the foundation for future studies that expand on sample size and compensate for the age discrepancy. Further, proof of concept can be performed by the inhibition of the investigated genes in in vitro or animal models to gain mechanistic insights into the individual players in the pathogenesis of gallstone disease in HIV infection. In conclusion, whole genome sequencing studies can provide a better understanding/insight into gallstone disease in Black African women.
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|
---
title: Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and
Taste-Dependent Dopamine Responding
authors:
- Alexia Duriez
- Clémence Bergerot
- Jackson J. Cone
- Mitchell F. Roitman
- Boris Gutkin
journal: Nutrients
year: 2023
pmcid: PMC9968091
doi: 10.3390/nu15041015
license: CC BY 4.0
---
# Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste-Dependent Dopamine Responding
## Abstract
Seeking and consuming nutrients is essential to survival and the maintenance of life. Dynamic and volatile environments require that animals learn complex behavioral strategies to obtain the necessary nutritive substances. While this has been classically viewed in terms of homeostatic regulation, recent theoretical work proposed that such strategies result from reinforcement learning processes. This theory proposed that phasic dopamine (DA) signals play a key role in signaling potentially need-fulfilling outcomes. To examine links between homeostatic and reinforcement learning processes, we focus on sodium appetite as sodium depletion triggers state- and taste-dependent changes in behavior and DA signaling evoked by sodium-related stimuli. We find that both the behavior and the dynamics of DA signaling underlying sodium appetite can be accounted for by a homeostatically regulated reinforcement learning framework (HRRL). We first optimized HRRL-based agents to sodium-seeking behavior measured in rodents. Agents successfully reproduced the state and the taste dependence of behavioral responding for sodium as well as for lithium and potassium salts. We then showed that these same agents account for the regulation of DA signals evoked by sodium tastants in a taste- and state-dependent manner. Our models quantitatively describe how DA signals evoked by sodium decrease with satiety and increase with deprivation. Lastly, our HRRL agents assigned equal preference for sodium versus the lithium containing salts, accounting for similar behavioral and neurophysiological observations in rodents. We propose that animals use orosensory signals as predictors of the internal impact of the consumed good and our results pose clear targets for future experiments. In sum, this work suggests that appetite-driven behavior may be driven by reinforcement learning mechanisms that are dynamically tuned by homeostatic need.
## 1. Introduction
Seeking and consuming nutrients is essential to survival and the maintenance of life. Animals living in dynamic and volatile environments must develop complex behavioral strategies to obtain the necessary nutritive substances. This has been classically viewed in terms of homeostatic regulation, where complex nutrient-seeking behaviors are triggered by physiological need. Animals also seek nutrients in advance of acute need. How animals acquire nutrient-directed behaviors has most often been examined through the lens of reinforcement learning (RL) theories. In RL, subjects acquire information about signals from the environment that are associated with the receipt of reward [1]. Importantly, RL signals are distributed throughout the brain [2,3]. Similarly, physiological need impacts a wide array of brain circuits that regulate behaviors motivated by nutrient rewards [4,5,6]. Intriguingly, the vast majority of RL theories do not treat the physiological origins of primary reward seeking, nor do they speak to how nutrients and their associated values are modulated by internal state. To maximize survival, physiological needs should augment signals that drive RL to promote learning in environments that offer access to essential nutrients. Thus, the reinforcing value of a nutrient, and consequently the degree to which an RL-based agent can learn from actions that acquire said nutrient, should be modulated in an appetite-dependent manner.
An essential area for exploration is thus the degree to which homeostatic and reinforcement learning processes are coupled in the central nervous system. RL processes have been most closely associated with mesolimbic circuitry, namely the midbrain DA neurons and their major target, the striatum [7,8,9]. While debate remains as to the role of DA in RL [10], it is increasingly clear that midbrain DA neurons and their responses to essential nutrients are modulated by physiological state, through direct hormonal influence [11,12,13,14] or via interactions with homeostatic and/or related circuits [15,16,17,18,19,20]. A particularly powerful example of the impact of physiological need on motivated behavior and DA signaling is sodium appetite. Sodium appetite is a natural behavior [21] whereby a sodium deficit generates sodium-seeking behaviors and selective consumption of sodium over other nutrients. Under homeostatic conditions, rodents avoid consumption of hypertonic sodium solutions. However, sodium depletion (via injection of a diuretic/natriuretic, e.g., furosemide) or removal of the adrenal glands [22] induces avid consumption of hypertonic sodium solutions and appetitive taste reactivity [23]. Importantly, phasic DA responses to the taste of a hypertonic sodium solution are dynamically sensitive to sodium balance [16,17]. As with behavior, the DA response in sodium-depleted rats is blocked by lingual application of the epithelial sodium channel blocker amiloride [16] and is selective for sodium solutions [17]. Lithium chloride, a notable exception, is equally preferred [17,24], likely due to sodium taste fibers responding to lithium as well (but not potassium) [25]. These data argue strongly that information related to the current state of sodium balance is communicated to midbrain DA neurons to regulate brain signals thought to drive RL. Taken together, these data pose a major challenge to current state of the art RL theories, and novel RL models need to be developed that account for the impact of physiological need and the role of gustatory information on reward learning. Sodium appetite is an ideal paradigm to address this issue.
We recently put forth a homeostatic reinforcement learning (HRRL) framework that was developed to study how animals learn need-based adaptive behavioral strategies in their environment to obtain rewarding outcomes [26,27]. The HRRL agent learns to maximize the total cumulative reward by performing actions and predicting the impact of their outcome on its internal state. This framework relies on a new definition of rewards: the rewarding value of an action is a function of the predicted impact on the difference between the current internal state and the ideal one (i.e., “setpoint”). The function that links the internal states to rewards is called the drive function. In other words, the reinforcing value of a stimulus is modulated by the degree to which it alleviates or exacerbates a physiological need. In this way, HRRL joins the predictive homeostatic regulation and reinforcement learning theories by positing that minimizing deviations from a homeostatic setpoint and maximizing reward are equivalent. In other words HRRL synthesizes RL algorithms with the drive reduction theories of motivation [28]. HRRL has been used to simulate the consumption of various resources and reproduce experimental data. It can also be used to represent complex behavior such as anticipatory responding, binge eating [26] and cocaine addiction [29]. Interestingly, it can be shown mathematically that HRRL agents show predictive allostatic behavior and HRRL accounts for the incentive salience proposals: the internal state of the HRRL agents is dynamically changed according to upcoming challenges and the action values (incentives) are modulated dynamically by the internal state of the animal.
Here, we show that the HRRL model can account for sodium-seeking behavior and DA signaling in rats. We first required the HRRL models to reproduce behavioral data showing that sodium-deprived rats preferred sodium and lithium over potassium solutions. We then showed that such HRRL agents also reproduce the dynamics of DA signals. We then used the models to make several predictions about satiety-dependent modulation of behavior and how exposure to lithium may only modulate the behavior and the reinforcing value sodium.
## 2.1.1. State Space Representation
The internal state is considered a continuous variable that can be represented at each time t by a point in a homeostatic state space. As theorized by Keramati and Gutkin [26], this state space has one dimension per homeostatic variable. The ideal internal state is the equilibrium point of the homeostatic state space. This point we call the setpoint represents the internal state that maximizes the chances of survival (satiety). It is denoted by H* = (h1*, h2*, …, hN*). In this study, the state space has only one dimension, corresponding to the internal sodium level.
## 2.1.2. Reward Calculation Mechanism
The HRRL theory provides a function called the drive, which takes as its argument the degree of departure from a “satiety” point and has a unique minimum at that setpoint. The drive is a function of the deviation of the animal’s internal state Ht from its homeostatic setpoint H* (Figure 1). In a homeostatic state space with one dimension, the drive is given by the following expression [26]:[1]DHt=h*−htnm where t represents the time, m and n are free parameters that influence, non-linearly, the mapping between homeostatic deviations and the rewarding value of their reduction.
As an animal performs an action, its internal state is modified by the outcome Kt of the action. The homeostatic reward is defined in a non-circular way, as the reduction in the homeostatic distance from the setpoint caused by the outcome Kt. [ 2]r, Kt=DHt−DHt+1 [3]rHt,Kt=DHt−DHt+Kt The reward associated with taking an action from state Ht resulting in an outcome Kt that transitions the internal state to Ht+1 is positive if the subsequent internal state (Ht+1) remains below or equal to the setpoint However, if the animal is currently at its setpoint (i.e., Ht=H*), the reward value obtained with the outcome *Kt is* negative: the outcome is negatively reinforcing.
## 2.1.3. Taste Value Estimation Mechanism
We hypothesize that animals sense the rewarding value of a tastant through the gustatory information they receive before experiencing its post-ingestive qualities [26]. The reward is thus computed by the animals’ orosensory approximation of the nutritional value Kt given the amount of solution they consumed. This estimate of the outcome, based on the orosensory properties of the stimulus, is denoted by Kt^. The reward therefore becomes:[4]rHt, Kt^=DHt−DHt+Kt^ We further hypothesize that Kt^ is not constant. In our model, Kt^ is learned with a learning rate ϵ through tasting the corresponding solution and experiencing its impact on the internal sodium level Ht. We introduced this aspect since it has been suggested that assigning a reinforcing value to a taste of food requires that the animal experiences its nutritional impact [32]. According to this study, hungry animals learn that a taste stimulus is predictive of a need-reducing reward by experiencing the association between these two properties of food. We consider that Kt^ also has an innate non-zero initial value, which is supported by recording of DA transients: the first NaCl infusion already elicits a DA response [16]. [ 5]Kt^=Kt−1^+ϵδk [6]δk=Kt−Kt^ It has been shown that in the absence of prior experience, sodium-depleted rats cannot discriminate between sodium and lithium chloride [17]. We therefore hypothesize that taste information alone is insufficient to distinguish between sodium and lithium in the absence of any post-ingestive impact on D. In our model, this means that, for naïve animals, sodium and lithium have the same Kt^, which represents the estimated impact of a sodium-like tasting solution on the internal state.
## 2.1.4. Action Value Estimation Mechanism
With the Q-learning method, rats estimate the value v of each choice as they discover which actions are more rewarding than the others [33] *Once a* rat executes an action a and the homeostatic reward r is computed, the value va of this action is updated using the reward prediction error (RPE), δr, with the learning rate ϵ [26]. [ 7]va ← va+ϵδr [8]δr=r(Ht, Kt^)−va−cost The cost is a penalty we introduced in this model associated with the energy cost of approaching the sipper tubes and consuming any of the solutions. By decreasing the reward prediction error term (RPE), it reduces the reinforcing value of an action, and thus the motivation of the agent to pursue that action in the future. We assume that the cost of approaching and drinking from a sipper tube is a priori encoded in the rats’ representation of their environment.
δr is the RPE signal that is purportedly encoded by midbrain dopaminergic neurons (e.g., see [34]). We therefore monitor the RPE by sampling DA fluctuations in the Nucleus Accumbens (NAc). A positive RPE in our model corresponds to a phasic DA response in the NAc. The RPE signal is negative when the predicted reward is superior to the actual one. The RPE can also be negative for actions that yield no reward due to the energy cost associated with performing said action.
## 2.1.5. Action Choice Mechanism
The probability of taking an action ai is proportional to its estimated value vai, according to the softmax rule [33]:[9]Ptai=expβvai∑iNaexpβvai *Na is* the number of possible actions, such as drinking sodium chloride or drinking nothing. The probability distribution over the possible actions is the stochastic policy used by the simulated rats to choose their next action. 𝛽 is a parameter used to modulate the probability of selecting actions with different estimated values. A high beta causes the selection probabilities to diverge faster. For extreme betas, this can make the action choice almost deterministic (i.e., greedy). Conversely, a low beta makes the probabilities change more slowly, and actions are therefore selected more randomly. *In* general, 𝛽 controls exploration versus exploitation behaviors.
## 2.1.6. Trial Schedule
A new trial begins every 15 s. At the beginning of a trial, the rats choose an action based on the learned stochastic policy. The outcome of the action is added to the internal state. [ 10]Ht=Ht−1+Kt The new drive, then the homeostatic reward, are calculated. The RPE is computed, then the value of the action performed is updated. Meanwhile, the values of the other actions remain unchanged. The error δk in the approximation of *Kt is* also computed, allowing Kt^ to be updated. The policy is then updated using the new action values. Finally, the internal state loses a small quantity of sodium, to simulate grossly the dynamics of sodium in a real organism:[11]Ht←Ht−loss
## 2.1.7. Optimal Parameters
We first used an ad hoc procedure to adjust the free parameters of the model to yield a qualitative agreement with the data and to determine physiological ranges that would indeed produce such appropriate model behavior. The “Simulation-Based Inference” approach was then employed to find optimal parameter distributions, within a range of possible biological values estimated with the search by hand, for the algorithm to return a desired output [30]. The parameters used in the simulations in the manuscript were then sampled from the modes of those distributions to produce individual simulated animals (agents).
For clarity we briefly review the SBI methodology. The Simulation-Based Inference method uses an algorithm called “Sequential Neural Posterior Estimation” (SNPE). SNPE requires three inputs [30]: SNPE returns for each parameter a probability distribution over its range of possible values. The values with a high probability are consistent with the observation. Simulation-Based Inference was used to determine the values of the setpoint H*, the learning rate ϵ, the rate of exploration 𝛽, the fixed outcome K of every drink taken by the rats, the loss and the cost. In total, 2000 samples were drawn from 1000 batches of 1000 simulations via the SNPE method to obtain the distributions (Figure 1B). Each parameter was assigned the average value of the distribution, as an approximation for the value with the highest probability.
For each simulated agent, we recorded the evolution of multiple parameters or values: [1] the probability of consuming one solution over another, [2] the amount of ingested sodium chloride, [3] the predicted nutritive value associated with the taste of sodium, [4] the reward prediction error signal and [5] the choices made throughout the simulated experiments. Individual agents were endowed with parameters that were sampled from the peaks of the posterior distributions (see above), hence, representative instantiations of optimal parameter sets. The agents were then used to show how the studied variables evolve depending on the solutions available and the initial internal state. Interagent variability was introduced to calculate the statistics (e.g., averages) of the relevant variables over several different individual agents (to match the experimental data). *To* generate individual agents, we sampled the free parameter distributions within the ranges giving the highest probability of the agreement with the data. This way we obtained a simulated cohort of animals, model agents, for which we could compile response statistics. The free parameters of the HRRL model are the setpoint, the learning rate, the exploration rate and the loss of sodium between each trial. For each of these parameters and individual agents, values were randomly sampled within a range in which the probability of the learning algorithm output, to be consistent with the behavioral data from Fortin and Roitman [17], was around its maximum (approx. 1 std of the peak, see Figure 1B).
## 2.2. Statistical Analysis
In the simulated experiments, several variables were calculated in 14 simulated rats having access to potassium and 15 simulated rats having access to lithium: the probability of choosing each of the available solutions at the end of the experiment, the average reward prediction error throughout the experiment, the predicted nutritive value of one lick of NaCl or LiCl (Kt) and the number of trials necessary to reach the optimal sodium level. For each of these variables, the averages of the two groups were compared with a two-tailed Welch’s t-test. The preference scores for potassium group ($$n = 14$$) and lithium group ($$n = 15$$) were compared using a two-tailed Student’s t-test. The cumulative consumption between the two groups was compared with a two-tailed Student’s t-test. This analysis aims to reproduce analysis methods used by Fortin and Roitman [17].
## 3. Results
We first optimized the free parameters of the model (see Methods) to generate a cohort of individual agents whose simulated behavior reproduces the results of the 10 min two-bottle intake test conducted by Fortin and Roitman [17]. The parameters sampled and optimized were the setpoint, the learning rate, the exploration rate and the quantity of sodium lost between each trial. They were tuned for the potassium preference score of the simulated sodium-deprived agents to be as close as possible to the experimentally observed values. Our goal was to capture the preference scores for the different salt solutions as a function of the animal’s internal state and choices in the experiment. To illustrate the results, we picked a parameter set (see Appendix A Table A1) with nearly optimal parameter values producing a simulated individual “rat” (N.B. for the rest of the manuscript we will denote such simulated animal by agent). Figure 2 shows the behavior of such an individual agent throughout the experiments, and indicates that the model accounts for the qualitative observations made by Fortin and Roitman [17] on the preference for sodium and lithium over potassium. In Figure 2A, the evolution of the probability for an agent with optimized free parameters to consume either NaCl, KCl or nothing (left column), and the evolution of the probability for the same agent to consume either NaCl, LiCl or nothing (right column) are shown. In both simulations, the agent was initialized with a simulated depleted sodium internal state variable. As expected, when sodium and potassium are available, the probability of consuming NaCl increases greatly, while the probability of KCl consumption decreases and becomes lower than the chances of drinking nothing. This suggests that sodium-depleted agents selectively target the taste of sodium in their strategies to regulate their sodium level (as seen in the experiment). On the other hand, the probability of consuming NaCl or LiCl remains around 0.4, higher than the probability of drinking nothing. This indicates that the taste of sodium and lithium are both expected to restore sodium balance.
The individual choices made by the agent are also shown in Figure 2A(a,e). This allows us to understand how the preference for sodium relative to a non-sodium salt evolves depending on the learned subjective value of each solution and the deviation from the setpoint (Figure 2A(b,f)). We can make an inference about the dynamics of DA signaling in the NAc by studying the reward prediction errors (RPEs) of the agents during the simulated experiments (Figure 2A(c,g)). Notice that NaCl and LiCl consumption gives rise to positive RPE signals, which correspond in our model to the experimentally observed positive DA responses in the NAc. Note that in the NaCl/LiCl task, the RPE signals are rapidly quenched, as the agent rapidly learns that both of these outcomes have an equal orosensory quality. We also tracked how the approximation of sodium nutritive value may evolve throughout the experiments (Figure 2A(d,h)). We can see that when NaCl and KCl are present, the value of NaCl choice increases (the value of KCl decreases, result not shown), whereas in the NaCl/LiCl task, the value of NaCl stays relatively constant since their orosensory quality is equal. Indeed, our HRRL agent simulations show how DA dynamics are linked to internal state fluctuations, and also how the animals’ learned estimation of the nutritional value is based on gustatory information.
The model quantitatively reproduced the experimental results [17] for the amount of ingested liquid and the individual preference for sodium, lithium or potassium. Figure 2B(a,b) show that the average amount of liquid ingested during the experiment and the preference scores for the non-sodium solutions obtained with the simulations are consistent with the experimental values. We further confirmed qualitative observations for simulated individual agents (shown in Figure 2A): at the end of the 10 min experiment, rats (as well as the simulated agents) with access to NaCl and LiCl ($$n = 15$$) are, approximately, equally likely to drink either of the two solutions. Rats with access to NaCl and KCl ($$n = 14$$), however, are unlikely to drink KCl, with a choice probability close to zero (see Figure 2B(c)).
Based on the behaviorally validated model, we asked what would be predicted for the dopaminergic signal (in our model this corresponds to the PRE) and the predicted value associated with the sodium gustatory cue during the final part of the experiment. Figure 2B(d) shows that the inter-individual-average phasic DA signal strength (as measured experimentally by the DA concentration) in the NAc during the 10 min experiment is higher when KCl is available than when LiCl is present as a choice, while in Figure 2B(e) we show the average predicted value of a lick of sodium (or lithium) associated with the corresponding taste for the model agents at the end of the 10 min simulated experiment. The true nutritive value of one lick of sodium is indicated with a dotted line. Our simulations predict that rats learn the true value of sodium associated with its taste when NaCl and KCl are available. However, their estimate is equal to about half of the true value when NaCl and LiCl are available. This higher value of the rats’ estimated value of sodium and lithium when KCl is available may explain why the average RPE is also higher in this condition as compared to the LiCl-available condition (Figure 2B(d)). On the other hand, when NaCl and LiCl are both available, the taste-dependent rewards are equally distributed between the two solutions, and hence the RPE for NaCl is reduced and a positive RPE is misattributed to the LiCl choice (in the sense that it is based purely on the taste information and not on the internal impact). Hence LiCl acquires a positive predicted value at the expense of the NaCl choice.
We then set out to see if the behavior-optimized model could also account for experimentally observed NAc DA responses to intraoral NaCl delivery in sodium-depleted rats and how this response develops as the animal continues to consume NaCl. Figure 3 shows a simulated agent with parameters optimized to account for the experimental behavioral preference scores, as in the previous simulations. We can see that the simulated agents’ RPE signals are qualitatively consistent with the experimentally observed DA responses. Cone et al. [ 16] measured the average DA response evoked by ten intraoral infusions of NaCl in sodium-depleted rats ($$n = 5$$). They observed that the first five infusions evoke larger DA responses than the last five. Figure 3A shows the simulation results for the same experiment alongside the summary data from Cone et al. In order to simulate this experiment, we first measured the RPE for the naïve depleted model during the first five simulated trials of exposure to NaCl stimulus, then during the last five trials. The model was “depleted” by initializing the internal state significantly below the optimal value (variable Ht = 2). NaCl delivery was simulated as a series of 10 trials where the agent receives the palatable sodium reward. In the model, the impact of NaCl on the internal state was simulated by a dose-dependent shift in the internal state variable (here of Kt= 0.3819 per injection) and increase in the taste signal by ϵδk, with δk = Kt−Kt^ (see methods). The results were averaged over five agents whose free parameter values were randomly sampled as previously presented. To compare the RPE with biological results, we referred to Cone et al. ’s experiments [16]. With their data, we calculated the baseline DA concentration for each trial and each rat as the average DA concentration during the 4 s preceding the NaCl infusion period. We subtracted this baseline from the DA concentration values during the 4 s infusion period. Then, for each rat, we computed the average peak of the DA concentration increase over the first and the last five trials. These two variables were finally averaged over the five rats. In order to compare the DA signal strength to the RPE, we normalized the DA signal from the first five trials and the RPE from the first five trials to unity. Consistent with the experimental results, we observed a decrease in the response between the first group of trials and the last. Indeed, Welch’s t-test showed that the difference between the average responses to the first five trials and to the last ones was significant ($$p \leq 6.93$$ × 10−7). Moreover, the differences between the simulation and the experimental results were not statistically significant (Welch’s t-test; see p-values on the figure). We then asked if the model can also account for the differential taste dependence of the phasic DA response. Fortin and Roitman [2018] tracked the average DA response of sodium-depleted rats during 10 intraoral infusions of NaCl, of KCl, of LiCl or of water and found that NaCl and LiCl evoke a strong DA response, while KCl does not. We simulated an analogue experiment. Figure 3B compares the simulated and experimental results. Note that in our simulations we left out the response to water since that would, in the simulations, lead to a null result. With the experimental data from Fortin and Roitman [17], we computed the peak of the DA concentration during the 4 s infusion period and subtracted the average DA concentration measured during the 4 s before the infusion onset as a baseline. This baseline was computed for each rat. We then averaged the DA increase over the rats. For the simulated data, we computed the average RPE signal evoked by 10 infusions of each solution. The results were averaged over six or five agents whose free parameter values were randomly sampled as previously. The baseline is null in our model. Then, in order to compare the DA data to the RPE, we normalized the response to NaCl to unity. We showed that in our simulations NaCl and LiCl are also the only solutions triggering a DA signal. Welch’s t-test showed that the differences between the simulation and experimental results are not statistically significant.
We further reasoned that the original 10 min two-bottle intake test used by Fortin and Roitman [17] may not give enough time for the acutely sodium-depleted rats to reach sodium satiety (or in terms of our model—to reach the optimal settling point of its internal state that corresponds to the minimum of the drive function). In order to study rat behavior when their sodium internal state approaches and reaches the optimal balance, we simulated the two-bottle intake test over a period that was sufficiently long for the agent to reach the satiation state. Figure 4A shows simulations for the evolution of behavior and DA dynamics when the agents approach satiety and become replete in sodium. Figure 4A(a,e) show the evolution of the probability for a simulated individual with optimized free parameters to drink either NaCl, KCl or nothing (a), and the evolution of the probability to drink either NaCl, LiCl or nothing (e). Interestingly, in both simulated conditions, the reduction in the consumption of NaCl or LiCl appears to anticipate satiety: the probability to drink starts to decrease before the amount of NaCl ingested (shown in Figure 4A(b,f)) makes the individual reach satiety. We then tracked the RPE particularly when agents approach the replete state. In this case, consuming NaCl deviates the internal state away (beyond) from the setpoint. This deviation translates into a negative RPE. In our model, assuming that the baseline of DA outflow is sufficiently low, this corresponds to no DA being released in the NAc (should the baseline be high, the negative RPE would be interpreted as a phasic decrease in DA outflow). This is consistent with the fact that in sodium-repleted animals, intraoral infusions of hypertonic sodium chloride evoke no DA signal in the NAc: the DA concentration does not change from the baseline [16,17]. We also note the tell-tale oscillatory pattern in the RPE/DA over trials for the replete condition. This may be explained as follows: a small amount of sodium is lost between each trial; therefore, after having reached a replete state for the first time, as the agents have learned not to consume NaCl, the internal state can move below the setpoint again. When this happens, NaCl becomes rewarding again, which corresponds to the positive peaks of the RPE. The dynamics of RPE and the sodium-consumptive choice frequency are then determined by the physiological processes that regulate sodium loss.
When there is access to lithium chloride in the replete state, consuming this solution does not change the sodium internal state, but it can still be a punishment, similar to drinking sodium, since the two solutions acquire the same predictive value due to taste similarity. As in the 10 min experiment, Figure 4A(d,h) indicates that the value of the predicted nutritional value of sodium associated to its taste, Kt^, is learned when rats have access to NaCl and KCl. On the other hand, when rats consume both NaCl and LiCl, the long-term value of Kt^ oscillates around the value learned in the first 10 min of the experiment (equal to half the real nutritional value of one lick of NaCl).
In Figure 4, the right panels show the average results for this simulated experiment, which could be tested with new experiments. First, Figure 4B confirms the qualitative observation from Figure 4A that in the replete state, the probability to drink nothing is much higher than the probability to drink one of the two solutions (NaCl or LiCl). Interestingly, agents with access to NaCl and LiCl ($$n = 15$$) appear to be slightly more likely to consume NaCl than agents in the other condition ($$n = 14$$). This is likely because the agent’s estimation of the nutritive value of sodium (under LiCl-NaCl access) is lower than under NaCl-KCl access (Panel 4e). Thus, consuming NaCl in a replete state under LiCl-NaCl access is a weaker punishment than for agents with access to NaCl and KCl. We are also interested in the amount of liquid agents consume during the experiment, in each condition (Figure 4C). It appears that more liquid is consumed when NaCl and LiCl are the solutions available. This can be linked to the fact that more trials are necessary for the agent to reach satiety in this condition (Figure 4D). Finally, in Figure 4E, the agents appear to learn the true value of sodium associated to its taste when NaCl and KCl are available. However, their estimate is equal to approximately half of the true value (indicated by a dotted line) when NaCl and LiCl are available.
Evidence suggests that gastric distension is an early inhibitory signal of water ingestion in thirsty rats (Hoffmann et al., 2006). Hoffmann et al. show that dehydrated rats will almost continuously drink water or saline, yet stop drinking after 5 to 8 min before reaching satiety. The oropharynx is also likely to be involved in the anticipatory control of drinking behavior, by signaling the amount of water consumed (Zimmerman et al., 2017). Considering these results on thirst, we can hypothesize that animals would stop drinking before reaching sodium homeostasis because of early inhibitory signals. Arguably, an experiment where rats would consume sodium until fully replete would probably need to be conducted in several sessions to study the choices of the rats at different levels of internal sodium to avoid potential confounding due to gastric distension. This way, within a session, if rats stop drinking the solutions, we may assume it is because their internal need is satisfied and not because of sickness.
Therefore, we chose to simulate such experimental conditions by representing the extended two-bottle intake test as a series of short sessions. This different representation also allows us to zoom into the first and last minutes of the long experiments and compare depleted and repleted behaviors. Figure 5 shows example data for the first and the last sessions of each version of the experiment (with NaCl and KCl or with NaCl and LiCl). In panels a, b and c, the data are collected from a sodium-depleted rat with access to NaCl and KCl, while in panels d, e and f, the data are collected from a sodium-depleted rat with access to NaCl and LiCl. As we can see in Figure 5A, during the first session the probability of drinking NaCl increases significantly with sodium deprivation (left). During the last session, the rats are replete, so the choice not to drink anything is the most frequent one (right). In Figure 5B, the choices of the rats are represented, and in Figure 5C, we can see the reward prediction error signals evoked by the outcomes of these choices. We can observe that during the first session, KCl evokes a negative reward prediction error signal because it has an energy cost in our model. This means no DA is released in the NAc, which is consistent with Fortin and Roitman’s result [17] that KCl does not evoke a DA response in the NAc. During the last session, sodium chloride triggers a weak negative reward prediction error as the rat is replete in sodium. This corresponds to the absence of DA release in the NAc observed by Fortin and Roitman in sodium-repleted rats receiving intraoral NaCl infusions [17]. Interestingly, when we simulate an experiment where NaCl and LiCl are available, the probabilities of drinking NaCl and LiCl remain similar throughout the first and last sessions (Figure 5D). We can see the actual simulated choices in Figure 5E. We then can also track the reward prediction error signals evoked by the outcomes of these choices (see Figure 5F). We note that during the first session, LiCl and NaCl both evoke positive reward prediction error signals, consistent with Fortin and Roitman’s results [17]: intraoral infusions of NaCl and LiCl both trigger DA signals in the NAcs of sodium-depleted rats. Drinking LiCl makes the predicted nutritive value associated with the taste of sodium (and lithium) decrease, which is why after several successive licks of LiCl, the reward prediction error is negative in response to LiCl and NaCl. Drinking NaCl increases the predicted value of the sodium taste, making the taste of sodium more rewarding. Licks of NaCl thus increase the reward prediction error signal. During the last session, the rats reach the setpoint, so they drink sodium much less often. However, since rats lose some sodium after every trial, their internal sodium level can fall below the setpoint. In that case, NaCl and LiCl evoke a positive reward prediction error signal.
Finally, we wondered what our model would predict for the drinking behavior of rats in the presence of only KCl or LiCl. In particular, would sodium-depleted rats keep drinking LiCl, which appears to have the same taste as sodium, to try to satisfy their need? Conversely, would these rats eventually learn that LiCl has no impact on their sodium balance? We used the model to simulate the condition where only KCl or LiCl is available to sodium-depleted rats. Before this experiment, these two rats were trained while sodium-depleted as in the experiments described above: the rat with access to KCl could choose from NaCl and KCl and learned not to drink either as it became replete in sodium. The rat with access to LiCl could choose between NaCl and LiCl and also learned not to drink either once it became replete in sodium.
In order to see clearer what happens in the agent behavior and the corresponding agent internal variable (i.e., the RPE), we show examples of individual behavior and DA dynamics in Figure 6F,G. Figure 6F describes the experiment in which only KCl is available. The individual choices are shown in the middle panels. The reward prediction error dynamics are represented in Figure 6, bottom panels. As we can see in the top panel, the individual agent’s probability to consume KCl smoothly decreases (null behavior probability decreases) because of the energy cost it imposes without any internal state benefit. Due to this cost, the KCl choice leads to negative RPE signals, which would correspond experimentally to an absence of DA release in the NAc. By the last session, the rat is much more likely to drink nothing (with a probability of about 0.8) than to drink KCl (with a probability of about 0.2). The probability of engaging with KCl is not null even after extended exposure because it represents the probability of making an exploratory decision. During the last session, sodium chloride triggers a weak negative reward prediction error in the model as the agent is replete in sodium. This may correspond to the absence of DA release in the NAc observed by Fortin and Roitman in sodium-repleted rats [2018]. Panels Figure 6D–F describe the experiment in which only LiCl is available. In Figure 6G, on the left, we show the evolution of the probability to drink LiCl or nothing over time during the first session. On the right: the probability during the last session is shown. We can see the evolution of the relevant probabilities. We first notice that the probability of drinking LiCl is higher than that of drinking nothing only during the first session and a part of the second one. At the end of the last session, the difference in probability between drinking LiCl and nothing is similar to the one between drinking KCl and nothing, during the last session. The middle panels show the individual choices made. The bottom panels show the reward prediction error dynamics. It appears that, during the first session, the rat learns that LiCl does not increase its internal sodium level and imposes an energy cost. The reward prediction error signals in response to LiCl are first positive and become negative as the rat learns the value of lithium.
Figure 6 gives example data, represented over the entire duration of the experiments to show evolutions more clearly. It also gives average data that can be tested with future experiments. Figure 6A shows the evolution of the probability for the rat to drink KCl or nothing over time (left), and the evolution of the probability for the rat to drink LiCl or nothing over time (right). Figure 6B represents the reward prediction error signal of the same rats over time. This different representation gives us a global view of the evolution of the behavior of these individual rats throughout the whole experiment. Figure 6C shows the average predicted value of a lick of sodium or lithium based on its taste for rats at the end of the 25 min experiment. The true nutritive value of one lick of sodium is indicated with a dotted line. This estimate is equal to half of the true value when KCl is available because it does not change in the absence of exposure to NaCl or LiCl. When LiCl is available, this value is close to zero ($$p \leq 2.02$$ × 10−30). Figure 6E confirms that at the end of the experiment, rats are on average just as unlikely to drink LiCl ($$n = 15$$) as they are to drink KCl ($$n = 14$$), which does not taste like NaCl.
These average data allow us to propose an explanation for the individual behavior in Figure 6A,B. The agent in panel a has already learned it is not worth it to drink KCl (the action value is initialized with the value the rat previously learned to satisfy its need in sodium). The probability of consuming potassium thus quickly drops to about 0.2. The agent in Figure 6B has learned not to drink LiCl as it has kept its associated action value learned while sodium replete. This agent discovers through an exploratory decision that lithium is rewarding because of the previously learned Kt^ value, but lithium does not increase the internal state, so Kt^ decreases to 0. The reward prediction error signal therefore becomes negative in our model when the agent consumes LiCl, which has a cost but no homeostatic reward. Thus, the probability of consuming lithium quickly decreases to about 0.2. In Figure 6D, we chose to represent the total liquid consumed during each version of the experiment. It appears that rats drink more liquid when they have access to LiCl than when KCl is the available solution ($$p \leq 0.001$$).
## 4. Discussion
In this contribution, we show how sodium-directed behaviors and DA responses evoked by sodium and non-sodium stimuli following the induction of sodium appetite, can be accurately described by the homeostatic reinforcement (HRRL) theoretical framework. To do so, we optimized a simple HRRL agent to learn about the consequences of consuming different sodium (NaCl)- and non-sodium (KCl, LiCl)-containing solutions across various states of sodium balance. We show that the behavior of the HRRL model agents closely reproduced experimental data in which sodium-depleted rats were given access to NaCl, KCl or LiCl. Much like the rats, following the induction of sodium appetite, our HRRL agents strongly preferred solutions that contained sodium or lithium over potassium. We then examined the reward prediction error signals on single trials for the HRRL agents in response to consumption of salt-containing solutions. In our HRRL model, the RPE signal should correspond with phasic DA release in the NAc during sodium appetite. We show that the HRRL RPE is strongly modulated by internal state and the properties of the salt stimulus, which aligns well with experimentally observed DA signals in the NAc of sodium-depleted rats that are exposed to NaCl, LiCl and KCl. As in rats with sodium appetite, the HRRL RPE signals were positive for sodium tasting salts (NaCl and LiCl) under deplete conditions and attenuated as the agent approached a sodium-repleted state. Furthermore, the HRRL RPE for KCl was negligible, which also matched the experimentally observed phasic DA release.
We then used the HRRL framework to model sodium-seeking behavior in prolonged salt discrimination experiments, where sodium-depleted rats are allowed to consume sodium to satiety. Interestingly, our simulated agents began to reduce their consumption of NaCl before becoming sated. This suggested that the agent behavior reflects the anticipation of a future replete state and makes this as a prediction for the experiments. We further observed that after extensive experience with salt solutions while sodium depleted, the HRRL agent that had access to sodium and potassium chloride could predict the nutritive value of a lick of NaCl based on its taste. However, the estimated value of NaCl consumption was halved when the HRRL agents had access to both sodium and lithium chloride, which have been shown to taste similarly. We finally investigated the drinking behavior when only lithium chloride was available. Recall that lithium chloride tastes similar to sodium chloride but cannot restore the lost sodium. Our simulations predict that sodium-deprived rats learn that lithium chloride does not fulfill their sodium deficiency and thus should stop consuming it. Our simulation results can be tested with experiments that could give further insight into homeostatic state regulation, goal-directed behavior, reinforcement learning and how these phenomena depend on mesolimbic DA signaling.
In our HRRL framework, we modeled the state of sodium balance through a drive function that represents the deviation between the agents’ current state and an idealized homeostatic setpoint. In the model, the source of this sodium drive is ambiguous. However, in biological systems, sodium need is sensed via distributed neural systems. There are aldosterone-sensitive neurons in the nucleus of the solitary tract (NTS) that express 11β-hydroxysteroid dehydrogenase type 2 (HSD2+) that are activated by sodium depletion [35]. Activation of NTS HSD2+ neurons can drive sodium consumption in sodium-repleted mice, whereas inhibition reduces sodium consumption in depleted animals [36]. Importantly, NTS HSD2+ neurons project to other hindbrain areas such as the parabrachial complex (PB) and pre-locus coeruleus (pre-LC), which contribute to sodium appetite in distinct ways [37,38]. In addition to the NTS, sodium need is also sensed by neurons in the subfornical organ (SFO), which respond to changes in blood osmolality, among other things [39], and has been shown to regulate sodium appetite [40]. Notably, NTS HSD2+ neurons and SFO neurons that respond to osmolality challenges may influence sodium appetite through synergistic influences on neurons in the Bed Nucleus of the Stria Terminalis [41]. Thus, in biological systems, state sensing, even for a single nutrient, is subject to complex multi-pathway regulation. This is to say nothing of how multiple competing needs interaction to influence behavior. In our HRRL models, the drive function was one-dimensional, as the current state of sodium balance was the only input under consideration.
In addition to sensing challenges to sodium balance to tune drive states, another key aspect of sodium appetite is the ability to detect sources of sodium in the environment. In the HRRL model, a “tastant” was evaluated by comparing its estimated reward value with the current state of sodium balance. If the agent was below an ideal setpoint, the tastant was evaluated as positively reinforcing. Otherwise the tastant was evaluated negatively as it further exacerbated deviations from homeostasis and cost energy to approach and consume. In vivo, sensing sodium primarily begins via Na+ selective epithelial sodium channels (eNACs), which are critical for sodium detection and discrimination [42,43,44]. Sodium taste information is relayed to the brain via the chorda tympani (CT; [45,46]) and CT transection disrupts the expression of sodium appetite [47,48]. Interestingly, CT responses to sodium solutions are augmented by sodium appetite [25], suggesting that changes in sodium balance can exert widespread effects on taste processing, even outside the CNS.
In the CNS, sodium appetite alters sodium taste responses in numerous brain areas, including hindbrain structures such as the NTS [49,50] and PB [51] as well as circuits linked to reinforcement learning such as the striatum [52] and the mesolimbic DA system [16,17]. Such widespread changes in sodium taste processing likely contribute to the robust changes in the consummatory responses and affective orosensory evaluation of sodium-containing solutions typically observed in sodium appetite [23,53].
Linking the gustatory properties of sodium-containing stimuli (taste, phasic) with sodium need (state, tonic) is essential for sodium appetite. Changes in the physiological state (tonic) serve to bias the organism’s behavioral repertoire towards sodium-seeking behaviors such that sodium intake is invigorated when tastants that contain sodium are identified. For example, consummatory responses such as bursts of licking, which are thought to reflect the palatability of a taste stimulus [54], increase following sodium depletion [53]. Prior work suggests that taste sensing and state interact in an additive fashion [53], but if either is disrupted, the expression of sodium appetite is impaired [36,55].
Perhaps the key feature of the HRRL framework is that by incorporating a drive function that tracks deviations from homeostasis into a traditional RL-based agent, this enabled us to model the taste–state interactions that drive both current and future sodium-seeking behaviors associated with sodium appetite. At the moment of consumption (e.g., when an RPE is triggered), it is likely that state-dependent changes in taste information are relayed to DA neurons via the PB and pre-LC, both of which innervate the VTA [38]. PB neurons express cFos following sodium consumption in sodium-depleted rats and this corresponds with reduced cFos staining in NTS HSD2+ neurons [5]. Moreover, pre-LC FoxP2+ neurons that receive efferents from the NTS are strongly implicated in sodium appetite [56] and project to the VTA [17]. By tuning RPEs according to the current state of the animal, the HRRL model may mimic PB and pre-LC influences on VTA DA signaling that track physiological need.
Future work could explore whether the HRRL model also captures longer term plasticity in reinforcement circuits associated with sodium appetite. For example, sodium appetite is augmented by a single prior experience with sodium depletion [57], while repeated depletions increase the need for free sodium intake long after sodium levels are replenished [58,59]. In terms of RPE signaling, mesolimbic DA neurons appear to encode sodium cues as reward predictive only after extensive experience with cue–sodium pairings while sodium depleted [16]. However, after such associations are learned, phasic DA release to the sodium cue is only observed when the animals are in a state of need [16]. It is likely the HRRL model would already account for this in its underlying math. Another challenging issue is how the proposed drive function is encoded in neural activity and how multiple drives may be prioritized with respect to each other (see also the discussion on multiple constraint satisfaction above).
An interesting point to consider in light of our results is whether the taste can be considered as another conditioned stimulus (CS) whose predicted impact of the consumed unconditioned stimulus (US) on the internal state is learned. A study on DA in mice consuming sucrose draws conclusions supporting this hypothesis [32]. According to this study, a taste evokes a DA response only if the animal has associated through prior learning this taste with a nutritional value. In other words, the hedonic property of taste cannot alone be responsible for reinforcement. The study suggests that taste acts as a conditioned stimulus predictive of a food reward. This implies that the association between a taste and a nutritional value can be extinguished by giving the animal extensive experience with the taste in the absence of a value (an artificial sweetener instead of sucrose, for example). When it comes to sodium, however, taste does not seem to act simply as a conditioned stimulus and appetite appears to be regulated by a more complex interplay of both innate and learned mechanisms. This is reflected in our model by the non-linear drive function and the non-zero initial value of Kt^. However, in our simulations, it is possible to extinguish seeking behavior towards the sodium taste after the exposure of sodium-depleted rats to LiCl. This suggests that the subjective value attached to sodium taste can be modified with learning, which should be investigated with new experiments.
Intriguingly, a recent proposal suggests that gustatory information could act as a hedonic predictor of the long-run worth of a good [60]. This suggestion appears at first glance to be compatible with our work; for example, just as with the gustatory “hedonic” account in our simulation, the gustatory “reward/value” rapidly leads to the motivation of consumption behavior and is ultimately dominated by the nutritive lack of impact for LiCl with the end value converging to zero.
Our model, as all computational models, faces several limitations: the actions are necessarily chosen and performed by the agent at discrete and regular time steps. Moreover, the solutions are consumed at a fixed volume. A continuous time model, in which the internal state of the agent has to be constantly regulated with actions that maintain its homeostasis, would be closer to reality. Indeed, the temporality of physiological regulation is important as the deviation from the setpoint must be reduced as soon as possible. We have previously shown that taking the shortest path to reach the setpoint optimizes fitness and that HRRL agents learn to preemptively avoid life-threatening excursions far from the homeostatic optima [61].
The proposed framework remains quite an abstract algorithmic model: how it relates to the neural circuitry mechanistically remains to be studied. For example, as discussed above, the circuits that mediate taste–state interactions in the brain are multi-faceted and could be communicated with the DA system through many convergent pathways. Another challenge that remains is how one might observe the drive function? A hint of predictive internal state encoding has been shown experimentally (see discussion above and [4]); however, it is not clear if such neural traces represent the internal state itself or the drive function necessary for learning and generating the behaviors. In fact, perhaps the drive function properties could be a key to individual differences in homeostatically motivated learned behaviors. Thus, understanding how one may measure the properties of the drive function from behavioral observations remains a key challenge.
In conclusion, we showed that a homeostatic reinforcement learning theory can account for behaviors motivated by sodium appetite. A recent study also put forth a similar argument [62]—focusing on a different dataset, they showed that HRRL agents can match two-bottle test behavior for sodium and water choices. Here, we critically extend these ideas to show that the HRRL framework can also quantitatively account for the taste- and state-dependent DA responses, arguing that such DA signaling may in fact be causal for the learning of such appetitive behaviors.
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|
---
title: 'Protective Effect of Neutral Electrolyzed Saline on Gentamicin-Induced Nephrotoxicity:
Evaluation of Histopathologic Parameters in a Murine Model'
authors:
- Nomely S. Aurelien-Cabezas
- Brenda A. Paz-Michel
- Ivan Jacinto-Cortes
- Osiris G. Delgado-Enciso
- Daniel A. Montes-Galindo
- Ariana Cabrera-Licona
- Sergio A. Zaizar-Fregoso
- Juan Paz-Garcia
- Gabriel Ceja-Espiritu
- Valery Melnikov
- Jose Guzman-Esquivel
- Iram P. Rodriguez-Sanchez
- Margarita L. Martinez-Fierro
- Ivan Delgado-Enciso
journal: Medicina
year: 2023
pmcid: PMC9968118
doi: 10.3390/medicina59020397
license: CC BY 4.0
---
# Protective Effect of Neutral Electrolyzed Saline on Gentamicin-Induced Nephrotoxicity: Evaluation of Histopathologic Parameters in a Murine Model
## Abstract
Background and Objectives: Gentamicin (GM) is a nephrotoxic aminoglycoside. Neutral electrolyzed saline (SES) is a compound with anti-inflammatory, antioxidant, and immunomodulatory properties. The objective of the present study was to evaluate whether kidney damage by GM can be prevented and/or reversed through the administration of SES. Materials and Methods: The study was carried out as a prospective, single-blind, five-arm, parallel-group, randomized, preclinical trial. The nephrotoxicity model was established in male BALB/c mice by administering GM at a dose of 100 mg/kg/day intraperitoneally for 30 days, concomitantly administering (+) SES or placebo (physiologic saline solution), and then administering SES for another 30 days after the initial 30 days of GM plus SES or placebo. At the end of the test, the mice were euthanized, and renal tissues were evaluated histopathologically. Results: The GM + placebo group showed significant tubular injury, interstitial fibrosis, and increased interstitial infiltrate of inflammatory cells compared with the group without GM. Tubular injury and interstitial fibrosis were lower in the groups that received concomitant GM + SES compared with the GM + placebo group. SES administration for 30 days after the GM administration periods (GM + placebo and GM + SES for 30 days) did not reduce nephrotoxicity. Conclusions: Intraperitoneal administration of SES prevents gentamicin-induced histologic nephrotoxicity when administered concomitantly, but it cannot reverse the damage when administered later.
## 1. Introduction
Drug-related nephrotoxicity is a cause of acute kidney injury (AKI) in patients hospitalized in intensive care units (ICUs) [1]. Six months after presenting AKI induced by nephrotoxic drugs, $70\%$ of patients present evidence of residual kidney damage: reduced glomerular filtration rate, hyperfiltration, proteinuria, or hypertension [2]. Aminoglycosides are a group of antibiotics still widely used at the hospital level, due to their low cost and broad bactericidal effects [3]. Cumulative aminoglycoside use is associated with long-term renal impairment [4]. Gentamicin (GM), a drug belonging to the aminoglycoside family, is known to be nephrotoxic [5,6]. Most studies have reported rates of nephrotoxicity between 8 and $26\%$, and it is estimated that $21.4\%$ of pediatric patients admitted to ICUs receive GM [7].
In preclinical studies, gentamicin-induced nephrotoxicity is characterized by histologic changes, including tubular injury, tubular atrophy, and interstitial fibrosis [8,9,10,11,12]. Such effects are known to be triggered by the nitrosative and oxidative stress induced by the aminoglycoside [13,14].The administration of compounds with anti-inflammatory and antioxidant activity to reduce GM-induced nephrotoxicity has been effective [15,16], albeit their clinical efficacy is inconclusive [17].
Neutral electrolyzed saline (SES) is a neutral-pH solution that has demonstrated anti-inflammatory and immunomodulatory properties [18], as well as antiseptic activity [19,20]. SES is produced from a saline solution of sodium chloride and is activated by a controlled electrolysis process, which produces reactive species of chlorine and oxygen (ROS). The ROS that are generated are oxidizing chlorine species, such as hypochlorous acid (HOCl), and oxidizing oxygen species, such as hydrogen peroxide (H2O2). In addition, molecular hydrogen (H2) is generated during the process (pat. no. MX330845B).
In vitro, activated saline solution participates in an anti-inflammatory mechanism at the cellular level, inhibiting the secretion of TNF-α, IL-6, and MIP-1 [18]. Furthermore, SES has been reported to have an immunomodulatory and anti-inflammatory effect capable of increasing the number of total platelets and leukocytes in patients with COVID-19 [21]. Molecular hydrogen, an SES compound, has also been reported to have a pulmonary antifibrotic effect [22]. On the other hand, electrolyte-reduced water, with an alkaline pH and a significantly higher concentration of H2 than SES, has been used in hemodialysis as a dialysis solution, reducing oxidative stress and the proinflammatory cytokine profile [23]. However, the latter study did not analyze whether molecular hydrogen prevented histopathologic alterations [23]. It is also well-established in the literature that SES can improve wound healing, not only because of its benefits as an antiseptic, but also due to its effects as an anti-inflammatory and cell-proliferation substance, through the mediation of oxidative and inflammatory responses [24,25,26]. This suggests that, to some extent and according to its components, SES or any of its components can protect against nephrotoxic agents. However, whether its potential beneficial effect is only preventive or whether it is also therapeutic (capable of reversing damage) has not been proven histologically, nor has it been evaluated.
Based on these premises, the present study aims to analyze the prophylactic and/or therapeutic effect of neutral electrolyzed saline in a murine model of gentamicin-induced nephrotoxicity.
## 2.1. Study Design
The study was carried out as a prospective, single-blind, 5-arm, parallel-group, randomized, preclinical trial (see Figure 1), according to the “ARRIVE Essential 10” guidelines for Animal Research [27].
## 2.2. Sample Size
The sample size was calculated using the formula based on incidence assessment [28], as previously reported [29]. The minimum number required to establish comparisons was nine animals per group. In this study, 53 mice were randomly divided into five groups.
## 2.3. Animals, Inclusion Criteria, and Randomization
Inclusion criteria were male BALB/c mice (Envigo, Coyoacan, Mexico City, Mexico) aged 12–14 weeks and weighing 20–30 g. Elimination criteria were any experimental subject that died during the study period or that developed any other type of illness. The animals were kept under suitable conditions at 21 ± 2 °C in a 12 h light/dark cycle, with food and water provided ad libitum. As previously reported, the mice were fed a high-fat diet to promote a renal and systemic inflammatory environment [30,31,32]. The mice were kept in cages, with a maximum of 5 mice per group. Fifty-three mice were divided into five parallel groups using a randomized block design [33] (see Figure 1).
## 2.4. Ethics
This study was approved by the Research Ethics Committee of the Colima State Institute of Cancerology (Colima, Colima, Mexico) (protocol no. CIIECAN/$\frac{06}{19}$). The animals were handled following institutional guidelines and the official Mexican norm that regulates the use of laboratory animals (NOM-062-ZOO-1999) [34], in addition to the Guide for the Care and Use of Laboratory Animals prepared by the National Academy of Sciences of the USA [2011] [35]. Furthermore, all the animals were euthanized by decapitation according to the American Veterinary Medical Association Guidelines for the Euthanasia of Animals, 2020 Edition [36].
## 2.5. Reagents, Animal Model, and Intervention
The gentamicin used was Genkova® (SON’S, SA de CV, Puebla, Puebla, Mexico). Esteripharma provided a neutral electrolyzed saline solution (Atlacomulco, State of Mexico, Mexico) of parenteral-application quality (Homestec) [37], which was SES neutral pH, $0.0020\%$ active chlorine® [37]. Physiologic saline solution for intravenous application was used as the placebo.
The nephrotoxicity model was established in male BALB/c mice by administering GM at a dose of 100 mg/kg/day for 30 days intraperitoneally (IP), administering SES or placebo (150 µL/mice/day, IP) concomitantly, and later administering SES or placebo for another 30 days. Five groups were formed: [1] GM + SES-after placebo (to assess the protective effect of SES); [2] GM + placebo-after SES (to assess whether SES reversed the damage through its application after the GM-application period); [3] GM + SES-after SES; [4] GM + placebo-after placebo (to assess the maximum kidney damage caused by GM); and [5] Placebo-after placebo (reference of the absence of damage caused by GM). After the completion of the experiment, the mice were euthanized by decapitation (day 61). The dose of SES administered per day in the mouse model was equivalent to that given to human patients intravenously in a previous clinical trial, in which an 80 mL dose of SES per day was shown to have an anti-inflammatory and immunomodulatory effect on patients [21]. Using a calculator that estimates the dose scale between species of different body weights via exponential allometry (http://clymer.altervista.org/minor/allometry.html; accessed 2 February 2023) [38], a dose of 150 µL/day for the mice was found to be a dose equivalent to 80 mL/day in humans. This calculation considered an exponent of 0.80, as well as an average weight of mice and humans of 25 g and 70 Kg, respectively. The concomitant GM + SES-application period was 30 days. Blood samples were obtained afterward, and the serum was separated for IL-6, creatinine, and urea quantification. A Mouse IL-6 ELISA Kit RAB0308 (Sigma-Aldrich, Saint Louis, MO, USA) was used according to the manufacturer’s instructions, and the analyses were performed in triplicate. Serum creatinine and urea were determined using an automatic biochemical analyzer (Cobas c111, Roche®, Miguel Hidalgo, Mexico City, Mexico). The kidneys were simultaneously dissected for histologic processing. The researcher who performed the histopathologic assessment was blinded.
In the present study, GM was administered for 30 days because that application period is capable of causing permanent destruction of some of the tubules that reflect fibrosis [39,40]. The recovery period after the final GM application was 30 days, after which the mice were euthanized for histologic analysis. That time period was chosen because acute histologic changes have been reported to be fully reversed between 3 and 30 days after the cessation of GM administration, and so changes that remain after 30 days can be considered chronic and permanent [39,41]. It is important to point out that nephrotoxicity from administering GM for up to 30 days, despite being able to cause histologic lesions, does not alter blood urea nitrogen or creatinine because of glomerular-filtration-rate preservation due to a process of necrosis and cell regeneration [40]. Therefore, the mouse model analyzed in the present study represents early (preclinical) chronic kidney disease [42], considering that the common histopathologic features can predict renal failure [43].
## 2.6. Histopathologic Processing and Assessment
The tissues were fixed in a solution of $10\%$ formaldehyde for at least 24 h. Renal tissue was embedded in paraffin. Tissue sections (5 µm) were prepared using a microtome and mounted on slides. Masson’s trichrome stain (Merck KGaA, Darmstadt, Hesse, Germany) was used to detect interstitial fibrosis. In addition, hematoxylin–eosin staining (Merck KGaA, Darmstadt, Hesse, Germany) was also carried out to detect tubular injury (blebbing of the apical membrane into the tubular lumen, cell fragments within the tubular lumen, flattening of the tubular epithelium, or loss of nuclei), tubular atrophy, and interstitial infiltrate of inflammatory cells [44]. Hematoxylin–eosin and Masson’s trichrome staining were performed according to standard procedures. Slices were evaluated via images captured with a Moticam 1080 digital camera (Motic China Group Co Ltd, Xiamen, Fujian, China) attached to a Moticam BA310E optical microscope (Motic China Group Co Ltd, Xiamen, Fujian, China) with 10× and 40× objectives. All images were captured under the same conditions of light and exposure.
Renal histopathologic lesions were calculated as the percentage of the total area observed under the microscope [45]. The total area of the renal tissue cut was considered $100\%$, and the percentage of the cortical area affected by tubular injury, interstitial fibrosis, tubular atrophy, and interstitial infiltration of inflammatory cells was quantified. Additionally, the total percentage of the renal cortex tissue altered histopathologically was calculated and was the result of the sum of the percentages of tubular injury, tubular atrophy, fibrosis, and inflammatory infiltrate in the renal cortex. Tubular injury was defined as the flattening of the tubular epithelium with calcified or noncalcified cellular fragments within their lumens, blebbing of the apical membrane into the tubular lumen, or loss of nuclei [44]. Interstitial fibrosis was defined as increased extracellular matrix separating tubules in the cortical area [46], demonstrated as the blue-stained areas on Masson’s trichrome stains [47]. Tubular atrophy was defined by thick, irregular tubular basement membranes, with decreased diameters of tubules [46]. Interstitial infiltrate of inflammatory cells was defined as an excess of inflammatory cells within the cortical interstitium [46]. The evaluations were carried out blindly by two anatomopathologic experts.
## 2.7. Statistical Analysis
The data distributions were not normal (except for serum creatinine and urea values), according to the Kolmogorov–Smirnov test, making the statistical analyses non-parametric. Therefore, the interquartile mean (IQM) was used as a measure of central tendency [48], and the 25th and 75th ranks and percentiles (Q1 and Q3, respectively) were used as measures of dispersion. The descriptive statistics were performed using Excel version 2101 (Microsoft 365, Redmond, WA, USA). For the inferential statistics, the Kruskal–Wallis test was used to analyze the histopathologic differences between groups, with a post hoc analysis using the Mann–Whitney U test. The comparison of serum creatinine and urea levels was analyzed using ANOVA, with a Bonferroni post hoc test. The statistical tests were performed using IBM SPSS version 20 software (IBM SPSS, Chicago, IL, USA), with statistical significance set at $p \leq 0.05.$
## 3. Results
Significant differences were found in tubular injury ($p \leq 0.001$), interstitial infiltrate of inflammatory cells ($p \leq 0.001$), and interstitial fibrosis ($p \leq 0.001$), when the intergroup analysis (Kruskal–Wallis tests) was carried out. However, no difference was observed in tubular atrophy ($$p \leq 0.400$$).
The post hoc analysis was made with the Mann–Whitney U test to explore each pair (Table 1). The control group showed normal kidney tissue with no tubular injury or interstitial fibrosis. Gentamicin produced significant tubular injury and interstitial fibrosis (GM + placebo-after placebo) compared with the group without gentamicin ($p \leq 0.001$, for both analyses), confirming the validity of the animal model (Table 1 and Figure 2).
The group in which neutral electrolyzed saline was administered concomitantly with gentamicin had significantly less tubular injury and interstitial fibrosis than the gentamicin plus placebo group (GM + placebo-after placebo) ($p \leq 0.001$, for all groups). The comparison of the GM + placebo-after SES vs. GM + placebo-after placebo groups showed that there was no beneficial effect of neutral electrolyzed saline when administered after the end of the gentamicin administration period ($$p \leq 0.104$$ for tubular injury, and $$p \leq 0.872$$ for interstitial fibrosis) (Figure 2).
There was an increase in the interstitial infiltrate of inflammatory cells in all groups that received gentamicin, regardless of whether SES was administered, compared with the group without gentamicin (Table 1 and Figure 2). It is striking that there were more inflammatory cells in the groups with concomitant administration of neutral electrolyzed saline and gentamicin (GM + SES-after placebo $$p \leq 0.017$$, and GM + SES-after SES $$p \leq 0.036$$) compared with the group that received gentamicin and placebo (GM + placebo-after placebo) (Table 1 and Figure 2). The total percentage of histopathologically altered renal cortex tissue showed that the concomitant administration of SES and GM was capable of significantly preventing kidney damage (Table 1).
Serum IL-6 values were determined at the end of the study in the groups: [1] Placebo-after placebo (IQM = 14.9 pg/mL, Q1–Q3 = 7.6–23.0); [2] GM + placebo-after placebo (IQM = 5.6 pg/mL, Q1–Q3 = 4.9–7.3); and [3] GM + SES-after placebo (IQM = 28.6 pg/mL, Q1–Q3 = 9.9–41.2). Using the Mann–Whitney U test, differences in the groups were determined, and it was found that IL-6 levels were significantly lower in the group that only received GM compared with the group that received GM + SES concomitantly ($$p \leq 0.028$$) and compared with the placebo-only group ($$p \leq 0.046$$). Meanwhile, the group that received GM + SES showed no significant differences from the group that received only placebo ($$p \leq 0.173$$). Table 2 shows a comparison of the serum values for creatinine and urea. In an intergroup analysis via ANOVA, only creatinine levels were different between groups. In the post hoc analysis, creatinine was significantly elevated in the GM + placebo-after placebo group compared with the GM + SES-after placebo ($$p \leq 0.004$$), GM + SES-after SES ($$p \leq 0.006$$), and GM + placebo-after SES groups ($$p \leq 0.025$$), with no differences between the rest of the groups ($p \leq 0.05$ for the rest of the comparisons). The placebo-after placebo group showed no statistically significant differences with respect to any of the groups ($p \leq 0.05$ for all comparisons).
## 4. Discussion
Gentamicin administration in an animal model generated tubular injury, interstitial infiltration of inflammatory cells, and renal interstitial fibrosis. The tubular injury and interstitial fibrosis were significantly reduced by the concomitant administration of neutral electrolyzed saline (SES), but there was no beneficial effect when SES was administered after gentamicin application. With the concomitant administration of SES and GM, low serum creatinine levels were also maintained compared with the group that received GM alone. In conclusion, neutral electrolyzed saline mainly had a prophylactic (nephroprotective) effect rather than a therapeutic (reversible) effect on gentamicin nephrotoxicity. The only beneficial effect of administering SES in a period after GM administration was the maintenance of serum creatinine levels that were significantly lower than those of the group that received GM alone.
The gentamicin nephrotoxicity model of the present study generated renal histologic alterations as previously reported [8,9,45,49,50]; however, unlike other investigations, no tubular atrophy was found [45,51]. In addition, doses of gentamicin similar to those in other investigations were administered in our model, but they were applied for 30 days—a period longer than that used in most previous studies [52,53]. Gentamicin nephrotoxicity models differ among studies in terms of dose (80–150 mg/k/day), administration route (subcutaneous or intraperitoneal), and administration time (ranging from 4 to 21 days) [54,55,56,57,58,59]. In the present study, gentamicin doses of 100 mg/k/day were used intraperitoneally for 30 days plus the administration of a high-fat diet to increase the renal and systemic inflammatory environment [30,31,32]. Tubular injury, tubular atrophy, interstitial inflammatory cell infiltrate, and interstitial fibrosis were reported quantitatively as the percentage of the total area of the renal cortex occupied by each lesion. Other studies have used semiquantitative scales that consist of the previous percentage evaluation of histologic lesions and subsequent reports in stages [60,61]. Therefore, the use of a model with a more favorable environment for kidney damage and more precise histologic measurements of kidney damage than those that have featured in previous studies [62,63] can be considered a strength of our investigation. However, the damage we observed was not very extensive, which is an aspect to be considered in future research.
Alternative nephrotoxicity animal models, such as those related to chemotherapeutic drugs like cisplatin, allow clear histopathological damages and have also been studied to evaluate the nephroprotective effect of electrolyzed saline. Oral administration of this substance to cisplatin-induced-renal-injury mice showed a significant nephroprotective effect due to the inhibition of lipidic peroxidation and an increment in antioxidant defense activity. The histopathological analysis of intoxicated mice without electrolyzed saline treatment showed moderate hydropic changes and extensive injury to tubular cells, while histopathological changes in the mice treated with electrolyzed saline revealed lower levels of edema and trace levels of tubular injury [64].
In all cases, the results on nephroprotection due to neutral electrolyzed saline are consistent with previous findings which showed that antioxidant and anti-inflammatory substances can generate a similar effect [65,66]. Inflammation and the exacerbated production of free radicals are known processes involved in the pathogenesis of gentamicin nephrotoxicity [14,67]. The production of proinflammatory cytokines leads to renal structural deterioration, including deterioration due to tumor necrosis factor-alpha (TNF-α), which is involved in the induction of loss of tubular cells secondary to tubular necrosis [54], and IL-6, levels of which increase after induction by GM [68]. The above takes place within the acute period of kidney damage. In addition, gentamicin increases transforming growth factor-β (TGF-β) levels in the renal cortex [36] and serum malondialdehyde levels [69].
Crocin has previously been shown to have protective effects against gentamicin-induced nephrotoxicity in rats; it has been postulated that this is due to its antioxidant and anti-inflammatory properties [45]. Similarly, molecular hydrogen is a potent anti-inflammatory [70] and antioxidant [71] which prevents the low intrarenal oxygenation induced by gentamicin [23]. Additionally, the administration of hydrogen-rich saline has an antifibrotic effect on the skin (on sclerodermatous skin lesions) [72], lungs [17], and liver and decreases circulating TNF-α [70]. All these findings are consistent with the results of the present investigation.
A possible explanation of the nephroprotective effects of neutral electrolyzed saline could be its ability to reduce inflammation [18]. Recently, a preclinical study showed that administering neutral electrolyzed saline in a rheumatoid arthritis model reduced IL-6 levels in a dose-dependent manner [73]. Additionally, molecular hydrogen, which is a component of neutral electrolyzed saline, has previously been reported to reduce levels of malondialdehyde (a marker of lipid peroxidation) and TGF- β1 (a profibrotic cytokine) [22], which would generate a nephroprotective and antifibrotic effect [61,74,75].
Nevertheless, the role of IL-6 in the evolution of kidney damage, determined through its serum levels, seems to be different in the acute and recovery phases. Elevated IL-6 serum levels during an acute process of renal damage are associated with worse renal function and/or pathohistologic changes in animal and human models [68,76], but the role of IL-6 in renal function recovery appears to be very different. Several animal studies suggest that IL-6 regulates antioxidant factors and modifies oxidative stress to protect the kidneys. Even in humans, a higher IL-6 level has been associated with a higher rate of complete renal recovery in survivors with acute kidney injuries admitted to intensive care units [76]. The present study found that IL-6 levels were significantly lower in the animals that received GM alone than in the placebo-only ($$p \leq 0.046$$) or gentamicin + SES ($$p \leq 0.028$$) groups. Low levels of IL-6 in the group with the greatest kidney damage is consistent with the idea that IL-6 is essential to the recovery process of that organ [76]. The group with concomitant administration of GM + SES did not show this decrease in serum IL-6, and although its values were higher than those in the group that received only placebo (healthy animals), the differences were not significant.
It is important to note that the tested dose of neutral electrolyzed saline could not reverse kidney damage when a subsequent toxic agent was administered. The reversal of already established interstitial fibrosis is documented in reports using other therapies; however, in those studies, gentamicin was administered at a dose of 80 mg/kg/day for 8–10 days [12,77], whereas in our study it was administered for 30 days.
Also noteworthy is the high number of inflammatory cells in the kidney tissues of the mice with fewer histologic lesions due to the nephroprotective effect of neutral electrolyzed saline—a result consistent with the findings of previous studies. The simultaneous administration of L-arginine with gentamicin was reported to contribute to the absence of tubular necrosis and mononuclear cell infiltration associated with tubular regeneration [78]. Carvacrol demonstrated a nephroprotective effect by reducing tubular necrosis without reducing interstitial leukocyte infiltration [79]. Cucumis melo seed extract prevented tubular necrosis, and, depending on the dose, the degree of interstitial infiltration of inflammatory cells was maintained or decreased [16]. These results suggest that the role of the interstitial infiltrate of inflammatory cells in the groups with neutral electrolyzed saline may have been due to renal repair mechanisms rather than deleterious effects, but such a hypothesis needs to be tested in future research. Studies have also shown a reduction in the renal inflammatory infiltrate related to [45,54,80] a decrease in tubular necrosis, interstitial fibrosis, and other histologic lesions of interest. There is a fine line between the component of the interstitial infiltrate induced by nephrotoxicity and inflammation, the fibrotic response, and its possible reparative effect [81,82]. Therefore, studies on this topic and the influence of neutral electrolyzed saline are necessary.
In our research, the mice were fed a high-fat diet (HFD) that contributed to inflammation and renal interstitial fibrosis coupled with gentamicin-induced nephrotoxicity. HFD increases renal cortical mRNA levels of proinflammatory markers (MIP-1α (macrophage inflammatory protein-1α), TNFα, and IL-6) and profibrotic markers (TGF-β1) and increases renal macrophage infiltration [30]. These data could explain the presence of the interstitial infiltrate of inflammatory cells in all the groups, including the control. Therefore, when interpreting the results of the present study or comparing them with future research, the type of diet given to the animals should be taken into account.
Our study has several limitations. First, varied doses of neutral electrolyzed saline, enabling the evaluation of the minimum effective dose to obtain the nephroprotective effect, were not tested. Second, the cellular phenotype of the interstitial component was not characterized. Therefore, the exact role of the interstitial inflammatory cell infiltrates in the murine model of gentamicin-induced nephrotoxicity was not demonstrated. Third, the mouse model utilized represented early (preclinical) chronic kidney disease, with maximum percentages of interstitial fibrosis or tubular injury of $25\%$, without elevated serum creatinine or urea levels. Future investigations with models that represent more advanced renal disease are necessary. Other studies should demonstrate how neutral electrolyzed saline protects against toxic agents, such as gentamicin, as well as analyze oxidative stress parameters and molecular/biochemical data.
## 5. Conclusions
Our results show that the concomitant administration of neutral electrolyzed saline significantly reduces the nephrotoxic histologic changes caused by gentamicin. However, its administration after toxic damage does not reverse said renal histopathologic lesions. Future research is necessary to analyze the potential clinical use of neutral electrolyzed saline to prevent kidney damage due to toxic agents.
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|
---
title: Construction of Tongue Image-Based Machine Learning Model for Screening Patients
with Gastric Precancerous Lesions
authors:
- Changzheng Ma
- Peng Zhang
- Shiyu Du
- Yan Li
- Shao Li
journal: Journal of Personalized Medicine
year: 2023
pmcid: PMC9968136
doi: 10.3390/jpm13020271
license: CC BY 4.0
---
# Construction of Tongue Image-Based Machine Learning Model for Screening Patients with Gastric Precancerous Lesions
## Abstract
Screening patients with precancerous lesions of gastric cancer (PLGC) is important for gastric cancer prevention. The accuracy and convenience of PLGC screening could be improved with the use of machine learning methodologies to uncover and integrate valuable characteristics of noninvasive medical images related to PLGC. In this study, we therefore focused on tongue images and for the first time constructed a tongue image-based PLGC screening deep learning model (AITongue). The AITongue model uncovered potential associations between tongue image characteristics and PLGC, and integrated canonical risk factors, including age, sex, and Hp infection. Five-fold cross validation analysis on an independent cohort of 1995 patients revealed the AITongue model could screen PLGC individuals with an AUC of 0.75, $10.3\%$ higher than that of the model with only including canonical risk factors. Of note, we investigated the value of the AITongue model in predicting PLGC risk by establishing a prospective PLGC follow-up cohort, reaching an AUC of 0.71. In addition, we developed a smartphone-based app screening system to enhance the application convenience of the AITongue model in the natural population from high-risk areas of gastric cancer in China. Collectively, our study has demonstrated the value of tongue image characteristics in PLGC screening and risk prediction.
## 1. Introduction
Gastric cancer is the second leading cause of cancer death in China, and more than $80\%$ of patients are diagnosed at an advanced stage [1]. Patients with precancerous lesions of gastric cancer (PLGC), including intestinal metaplasia and dysplasia [2,3], suffer a higher risk of gastric tumorigenesis, with an annual incidence of 0.25–$6\%$ [4,5,6]. Screening and conducting reasonable health surveillance for patients with PLGC in the natural population would make great contribution to facilitating the early prevention of gastric cancer.
Current screening methods suffer from some challenges, including invasiveness and relatively low accuracy, which limits their applications in population screening. On the one hand, although gastroscopy and biopsy are the gold standards for gastric disease diagnosis [7], these methods remain inefficient and unfeasible for gastric disease screening [8]. As previous studies indicated, approximately half of the patients screened with gastroscopy are non-atrophic gastritis, and the early diagnosis rate of gastric cancer remains less than $20\%$ [1,9]. On the other hand, the application of serum markers that are commonly used as screening factors in various gastric cancer risk assessment methods, such as pepsinogen I/II and gastrin-17 [10,11,12], has been limited for risk screening in natural populations due to the high sensitivity and specificity thresholds required [13]. In addition, it is not cost-effective to use either serum pepsinogen test screening or endoscopy as they difficulty in their practical application [14]. Screening high-risk groups for gastroscopy could triage patients and effectively improve the utilization efficiency of medical resources. Thus, considering the requirements of large-scale screening, screening methods with a high cost-effectiveness ratio and high accuracy are urgently needed to enhance their popularization [15].
As non-invasive indicators, tongue image characteristics have been used for the surveillance of a broad spectrum of diseases, inspired by the diagnosis experience in traditional Chinese medicine (TCM) [16,17,18,19,20]. Tongue image characteristics, including shape, color, and tongue coating, are believed to reflect the health condition, or the severity and progress of disease, especially for digestive diseases as the tongue is anatomically connected to the digestive system organs. For example, recent studies have indicated that tongue image characteristics show correlations with gastroscopic observations and could be used to predict gastric mucosal health [21,22]. In addition, it was revealed that tongue surface and color characteristics could be used as indicators to assist in gastric cancer diagnosis [23,24]. Moreover, morphological markers based on tongue images are considered to be valuable for risk screening for other diseases, such as diabetes, fatty liver disease, and COVID-19 [17,25,26,27]. From the pathologic and etiologic perspectives, the distribution of microorganisms on the tongue coating has also been found to be related to gastric diseases, which helps uncover non-invasive microbial markers for gastric disease risk screening [28,29,30]. The above studies demonstrate the great potential of tongue image characteristics in assisting disease screening. Therefore, uncovering the risk characteristics of tongue images is potentially valuable for constructing PLGC screening models.
Recently, deep learning techniques are widely used in building biomedical image-based disease screening and prediction models [31,32,33,34,35,36,37]. For example, some studies have applied deep learning to predict diverse cancer types, including prostate cancer and rectal cancer, based on medical images [33,38]. Using tongue images, some studies have applied deep learning techniques to identify risk features in tongue images for the detection of diseases such as stomach cancer and diabetes [23,39]. Therefore, deep learning techniques could be a pivotal tool to uncover the risk characteristics from tongue images, and further constructed a machine learning-based screening model.
Therefore, to improve the efficiency of screening patients with PLGC, particularly in natural populations, this study aimed to build a machine learning-based PLGC screening model which introduces tongue image information on the basis of existing risk indicators. In detail, we firstly explored the tongue image characteristics of patients with PLGC and integrated them with canonical screening indicators to develop a PLGC screening model called AITongue. We then evaluated its screening effect by external validation in an independent cohort and finally explored its potential value as a risk predictor of PLGC in a follow-up cohort. To our best knowledges, the AITongue model we have developed should be the first tongue image-based machine learning model for PLGC screening and risk prediction. We believe that our study will pave the way to addressing the urgent need for non-invasive PLGC screening in clinical practice.
## 2.1. Patient Enrollment, and Data Collection
Patients were enrolled in this study at the China-Japan Friendship Hospital and Yijishan Hospital of Wannan Medical College from 2015 to 2022. The experimental protocol was established according to the ethical guidelines of the “Declaration of Helsinki” and was approved by the Human Ethics Committee of the Institution Review Board of Tsinghua University (protocol code 20200069). Inclusion criteria: At least 18 years of age, clear language skills, no barriers in communication and willingness to accept clinical investigation and sign informed consent. Exclusion criteria: The presence of heart, cerebrovascular, liver, kidney, hematopoietic system diseases.
## 2.2. Gastroscopy and Histological Examination
Using video endoscopes (Olympus Corp), upper gastroscopic examinations were performed by two gastroenterologists. Tissue samples for biopsy were reviewed blindly by the two pathologists according to the criteria proposed by the Updated Sydney System and the Chinese Association of Gastric Cancer [40,41]. The results of each biopsy were reported as normal, superficial gastritis, chronic atrophic gastritis, intestinal metaplasia, intraepithelial neoplasia, or gastric cancer, and each participant was assigned a global diagnosis based on the most severe gastric histologic finding among any biopsy. Helicobacter pylori (Hp) infection status was determined by enzyme-linked immunosorbent assay for plasma IgG [42].
## 2.3. Data Pre-Processing and Data Structuring
As the pivotal step for data pre-processing, a deep-learning model was constructed to identify and segment tongue bodies in raw images while excluding face and background information. Here, we trained the tongue body recognition and locating model using the YOLOv5 model and 180 tongue images that were labeled by TCM physicians with a square frame using “labelImg” software [43]. The YOLOv5 model is a common deep learning model for target detection which can accurately identify and locate the position of specific objects after training. Furthermore, using this model, we carried out tongue body recognition and cutting on tongue images, reshaped the images to 224 × 224, and formed a pre-processed tongue body image dataset. In this way, we could segment the tongue from the complex background to reduce the impact of the background on classification and improve accuracy. Python (3.7.0) and PyTorch were used for the tongue image preprocessing. Using this model, the tongue images were detected and cut into tongue body images for subsequent analysis.
Additional clinicopathological characteristics of the enrolled patients were obtained from electronic medical records. The obtained characteristics included basic information (gender, age) and symptom characteristics (xerostomia, bitter taste, gastric distention, stomach pain, etc.). All the above indicators were structured as two-category labeled data. Among them, age was divided into >50 and ≤50 years based on the median of age distribution. Multiple interpolation methods were used to fill in the missing data. Tongue labels (fissure, etc.) were assigned by physicians.
## 2.4. PLGC Screening Model Construction
The PLGC screening model was constructed following two main steps: image classification with a deep learning model, and data integration with a logistic regression model.
Firstly, the image classification model was constructed with the ResNet50 deep learning model [44]. The ResNet50 model has a wide range of applications and good performance in the field of image classification as it can introduce the residual blocks. In our study, the residual blocks of the ResNet50 model are structured as two bottlenecks (BTNK), designated as BTNK 1 and BTNK 2. Their structure diagram is shown in Supplementary Figure S1, where CONV is the convolution block, BN is the batch normalization block, and *Relu is* an activation function in the bottleneck. After the ResNet50 module, tongue images were classified into two categories: high-risk and low-risk.
A logistic regression model was then used to predict the PLGC screening results by integrating the tongue image classification results and the clinicopathological indicators. Logistic regression models have good performance in the integration of a small number of variables and robust prediction of classification tasks, resulting in their wide application in disease classification and risk prediction research.
## 2.5. Statistical Analysis
All analysis procedures were performed using Python (3.7.0) and the sklearn package. Tongue diagnostic labels (TDL) and clinical symptoms with statistical significance ($p \leq 0.05$) by both univariate and multivariate analyses were included in the model. The significance of each factor adjusted for gender and age was calculated in the multivariate analysis. Binary logistic regression was used to construct the screening models. Chi-square tests were applied to calculate the significance of the independent variables for PLGC. Pearson’s correlation coefficient was applied to evaluate the correlation between the independent variables. Accuracy, sensitivity, specificity, recall, precision, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were used as evaluation metrics to evaluate model performance.
AUC-ROC curves are performance measures for classification problems under various thresholds. ROC is a probability curve, and AUC represents the degree or measure of separability. The horizontal coordinate of the ROC curve is the false positive rate (FPR), and the vertical coordinate is the true positive rate (TPR). The calculation formula is as follows. TPR=TPTP+FNFPR=FPFP+TN TP, FP, TN, and FN represent true positives, false positives, true negatives, and false negatives, respectively. In the classification task, the model represents the prediction and ground truth. The higher the AUC, the better the classification performance of the model.
## 3.1. The Overall Design of Our Study
In our study, a total of three cohorts of patients were enrolled with undergoing gastroscopy and pathology. These included a development cohort, validation cohort, and follow-up cohort. Here, two categories, including PLGC and non-PLGC, were derived for each patient based on pathological diagnosis (Table 1). In detail, we developed the PLGC screening model and performed an internal cross-validation on the development cohort, which consisted of 325 patients, including 55 PLGC and 270 non-PLGC patients. We then performed external validation on the validation cohort, which had a total of 1995 patients, including 171 PLGC and 1824 non-PLGC patients. It should be noted that we also evaluated the risk prediction value of the PLGC screening model on the follow-up cohort, in which only non-PLGC patients were enrolled at the baseline timepoint, and were further classified as Pro or non-Pro according to the pathological lesions at the endpoint after a mean follow-up time of 22 months (Figure 1).
## 3.2. Construction of AITongue Model with Integrating Tongue Image Characteristics
After preprocessing the tongue images with deep learning (Figure 2a), a PLGC screening model, which we named the AITongue model, was constructed in the development cohort by integrating the tongue image and clinicopathological characteristics, as shown in Figure 2b. Here, the tongue images were classified into two categories: high-risk and low-risk. The AITongue model took the categorized results, and canonical gastric cancer risk indicators (age, gender, and Hp infection) as the input, and the PLGC prediction results as the output.
Firstly, we examined the screening value in terms of inclusion of tongue image characteristics in the development cohort. Through a five-fold cross-validation, it was shown that the AITongue model exhibited good performance in distinguishing PLGC from non-PLGC patients, with an accuracy of 0.69 and an AUC value of 0.75. In contrast, the screening model only including baseline indicators (age, sex, Hp) exhibited an accuracy of 0.60, with an AUC value of 0.69 (Figure 2c,d). Thus, it was revealed that the screening performance was improved by $8.7\%$ with the inclusion of tongue image characteristics (Figure 2d), indicating the contribution of tongue image characteristics in PLGC screening.
We then further investigated and interpreted the tongue image characteristics with PLGC screening potential. Through performing correlation analysis between image risk classification (high vs. low-risk) obtained by the deep-learning model and TDL labels generated by TCM experts, we found that five of the TDLs were statistically significant ($p \leq 0.05$), namely greasy, fissured, dark, coating (yellow), and coating (thick). This indicated, to some extent, the medical significance of the risk features found in tongue images and suggests that there may also be some value of TDLs for PLGC screening (Table 2).
## 3.3. External Validation of PLGC Screening
We then validated the performance in PLGC screening of the AITongue model in the independent validation cohort. To enhance the robustness and application value of our model, the five representative TDLs that included greasy, fissured, dark, coating (yellow), and coating (thick), rather than the whole image characteristics, were selected as inputs for the AITongue model. Of note, it was found that these five TDLs, along with gender and age, showed significant correlations with PLGC in both univariate and multivariate analyses (Table 3, Table S2), supporting their value as input parameters for AITongue.
It was found that the AITongue model showed a comparably discriminative performance in the independent validation cohort compared with that of the development cohort. Here, the AITongue model exhibited an accuracy of 0.64 and AUC of 0.75 in distinguishing PLGC from non-PLGC patients. In contrast, the model with only including baseline indicators (age, sex, Hp) showed an accuracy of 0.53 and AUC of 0.68 (Figure 3). Thus, we could conclude that the discriminative performance between PLGC and non-PLGC has been significantly enhanced by $10.3\%$ (0.68 vs. 0.75, $p \leq 0.01$, Figure 3) by introducing tongue image characteristics. The results furtherly validated the effectiveness of tongue image characteristics for PLGC screening.
In addition, we also focused on clinical symptom characteristics and investigated their screening value for PLGC and confounding effects for the AITongue model [45].
First, we investigated the screening value of symptom characteristics by analyzing their associations with PLGC. As a result, three symptom characteristics (xerostomia, bitter taste, belching) showed significant correlations with PLGC in both univariate and multivariate analyses, whereas the others, including stomach pain, bloating, chilliness, and loose stools, did not show significant correlations (Supplementary Table S2).
Further, we incorporated these three symptom characteristics into the AITongue model to evaluate the enhancement of introducing symptom characteristics for PLGC screening. The validation cohort was used as training data to construct a logistic regression model and a five-fold cross-validation was performed. It showed a small improvement in the discrimination between PLGC and non-PLGC after introducing symptom characteristics (0.76 vs. 0.73, Figure 4). These results indicate that the introduction of clinical symptom characteristics could improve the screening efficiency of PLGC, with a slightly lower effect than tongue image characteristics. In addition, there was a low correlation between tongue image and symptom characteristics (Supplementary Figure S2), which indicates that tongue image characteristics might be independent factors from clinical symptom characteristics in terms of PLGC screening.
## 3.4. Evaluation of the Validity of Tongue Image Characteristics for Risk Prediction of PLGC
PLGC risk prediction is pivotal for gastric cancer early prevention. Thus, we further explored the value of the AITongue model in predicting the risk of PLGC. Here, we enrolled a cohort of non-PLGC patients and conducted a long-term follow-up surveillance, in which patients were divided into progressive (Pro) and non-progressive (non-Pro) groups, respectively, according to endpoint pathological diagnosis (Table 1). Using the AITongue model to score the PLGC risk for each patient in the follow-up cohort, we found that risk scores from the Pro group were significantly higher than those from the Reg group. The AUC value was 0.71, which showed a significant increase ($10.94\%$, 0.71 vs. 0.64, $p \leq 0.01$) compared with that derived from the model only including baseline indicators (Figure 5). In addition, we performed a univariate analysis of the TDLs for risk prediction of PLGC (Supplementary Table S3). It was found that the TDLs showed limited value for PLGC risk prediction, although they have an enhanced effect on PLGC screening. Therefore, tongue image characteristics are potentially valuable in PLGC risk prediction.
## 4. Discussion
We found that H. pylori infection was weakly correlated with PLGC and non-PLGC, although Hp infection is the most prominent risk factor for GC. Similar results have been found in other studies on the prediction of gastric cancer risk [46,47]. In this study, PLGC was analyzed using symptoms. We found only a small proportion of symptoms correlated with PLGC, and their screening efficiency was not high, which is consistent with the findings of other studies [48,49].
Tongue diagnosis is an important part of the four diagnoses in TCM. In TCM theory, the characteristics of tongue images are quantified into various categories for the diagnosis of diseases [50,51]. In this study, we not only found that helpful feature information for PLGC screening could be extracted through a deep learning model, but also found that these features were related to some categories of tongue diagnosis in traditional Chinese medicine. This suggests that some categories of Chinese tongue diagnosis have interpretable morphological characteristics for PLGC screening and for tongue images of high-risk categories.
Our proposed method has better performance than another study of screening of PLGC. Wang et al. developed a model with non-invasive indicators for PLGC screening based on 290 patients with gastritis, and the AUC was 0.728 ($95\%$ CI: 0.651–0.793), whereas the AUC of our method was 0.76 [52].
It is neccessary to adopt cost-effective methods to conduct the large-scale screening for gastric cancer risk in the natural population. Even though gastroscopy and pathological tests are the gold standard for the diagnosis of gastric diseases, they are not suitable for the natural population. The method we developed introduces tongue image information on the basis of conventional and invasive indicators, which improves the accuracy, reduces the difficulty of operation and improve its feasibility for application.
The study has some limitations. The data source was biased compared with the natural population. Due to the need for accurate information on the stage of gastritis, the data for establishing the system all came from patients with gastric disease, which had a certain deviation compared with the natural population. We have developed a smartphone-based app screening system to enhance the application convenience of the AITongue model in the natural population (Supplementary Figure S3). In further studies, more samples would be collected from natural populations to reduce bias, and larger external validation should be conducted.
## 5. Conclusions
Screening patients with PLGC is important for the prevention and treatment of gastric cancer. In this study, we analyzed the tongue image characteristics associated with PLGC and based on this, constructed a PLGC screening model on a development cohort. It was then externally validated in an independent validation cohort and used to evaluate the capability for risk prediction of PLGC in a follow-up cohort. Our study demonstrates the value of tongue image characteristics in PLGC screening and its potential for risk prediction.
The screening model constructed in this study could improve the accuracy of PLGC screening. Tongue image characteristics were validated for their value in PLGC screening and risk prediction, which may drive tongue image characteristics as a new risk indicator in the future. By extracting tongue image characteristics through deep learning techniques, this study proposes a new approach for non-invasive PLGC screening and shows the possibility of its use in large-scale applications.
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|
---
title: Argon Humidification Exacerbates Antimicrobial and Anti-MRSA kINPen Plasma
Activity
authors:
- Ramona Clemen
- Debora Singer
- Henry Skowski
- Sander Bekeschus
journal: Life
year: 2023
pmcid: PMC9968137
doi: 10.3390/life13020257
license: CC BY 4.0
---
# Argon Humidification Exacerbates Antimicrobial and Anti-MRSA kINPen Plasma Activity
## Abstract
Gas plasma is a medical technology with antimicrobial properties. Its main mode of action is oxidative damage via reactive species production. The clinical efficacy of gas plasma-reduced bacterial burden has been shown to be hampered in some cases. Since the reactive species profile produced by gas plasma jets, such as the kINPen used in this study, are thought to determine antimicrobial efficacy, we screened an array of feed gas settings in different types of bacteria. Antimicrobial analysis was performed by single-cell analysis using flow cytometry. We identified humidified feed gas to mediate significantly greater toxicity compared to dry argon and many other gas plasma conditions. The results were confirmed by inhibition zone analysis on gas-plasma-treated microbial lawns grown on agar plates. Our results may have vital implications for clinical wound management and potentially enhance antimicrobial efficacy of medical gas plasma therapy in patient treatment.
## 1. Introduction
Microorganisms are the foundation of life by keeping homeostasis on a large scale in ecosystems and on a small scale in cooperating commensal and symbiotic behavior in animals and plants. However, some microorganisms or a lack of host organisms’ defense can lead to severe infection and compromised organ function, including in the skin [1,2]. For instance, if wounds become infected or the wound’s host is deprived of the ability to clear the infection, chronification and ulceration occur, leading to hampered wound healing and long-term reduction of quality of life [3,4]. There are many different approaches to clearing wound infection and supporting wound healing available on the market [5,6]. About ten years ago, one particular technology was approved for treating non-healing and infected wounds in Europe, cold physical plasma [7]. The leap innovation of this technology was the ability to generate partially ionized gases in ambient air operated at body temperature so that no thermal harm was provoked when treating cells and tissues. The treatment with cold physical plasma has been shown to reduce the number of microorganisms in wounds [8,9]. A recent randomized, controlled clinical trial [10] suggested that cell-stimulating mechanisms also promote wound closure besides the known antimicrobial activity of gas plasma technology [11]. However, it remains established that reactive oxygen species (ROS) are a major mechanism of gas plasma therapy in vivo [12].
Antimicrobial effects of cold (body-temperature) gas plasma devices were described in the mid-1990s for the first time [13], with historic plasma medicine applications dating back to the turn of the 19th to 20th century [14]. Today, it is known that the share of ultraviolet (UV) and VUV radiation in this effect is relatively negligible, at least for plasma jets [15,16]. Similar findings were made for the portion of electric fields to the effects observed. Many studies have revealed and summarized the antimicrobial effects of gas plasma-derived ROS [17,18]. This was found mainly by adding antioxidant molecules or enzymes, such as N-acetylcysteine and catalase, to the samples, finding that many of the gas plasma-derived effects were reversed. However, only a few have convincingly shown how to optimize antimicrobial effects of existing gas plasma devices [19,20]. With many device configurations, especially gas plasma jets, the resulting ROS mixture expelled depends on the feed gas composition. For instance, partially opposing chemical pathways can be forced by modulating the presence and quantity of nitrogen or oxygen in the immediate surrounding or feed of plasma jets [21,22].
It is known that the gas plasma jet kINPen is the only device certified for medical conditions worldwide [11]. The device is operated with argon gas feed gas. However, to date, no study has convincingly shown an antimicrobial efficacy optimization of this argon plasma jet. To this end, we tested several feed gas conditions and identified humidity as a promising approach with the potential to optimize current wound healing therapeutic strategies based on commercially available gas plasma technology. Nitrogen, oxygen, or humidified argon were added to dry argon gas as feed gas conditions, as nitrogen and oxygen provoke the increased generation of reactive nitrogen and oxygen species, respectively, while humidity was shown to increase the levels of hydroxyl radicals [23].
## 2.1. Culture of Microorganisms
Several types of microorganisms were used in this study, and all were received from the German Collection of Microorganisms and Cell Cultures (Leibniz Institute DSMZ, Braunschweig, Germany). Among them were bacteria, such as Escherichia (E.) coli (DSMZ reference numbers 21182, 22664, 5645, and 1125), Pseudomonas (P.) aeruginosa (DSMZ reference numbers 110864 and 50071) and species (DSMZ reference number 21482), Staphylococcus (S.) aureus (DSMZ reference number 799), and S. epidermidis (DSMZ reference number 20044), and yeast, such as Candida (C.) albicans (DSMZ reference number 1386). Microorganisms were cultured in broth as indicated suitable for each strain type, as DSMZ instructions recommended before gas plasma exposure (Figure 1a).
## 2.2. Feed Gas Alterations and Gas Plasma Treatment of Microorganisms
The atmospheric pressure argon plasma jet kINPen (neoplas, Greifswald, Germany) was utilized in this study. This device’s electrical and chemical characteristics have been described in detail before [24]. Its excitation frequency is approximately 1 MHz, and its nominal output power is about 1 W. It has been operated at one standard liter per minute of argon gas (purity: 4.6; Air Liquide, Bremen, Germany). For exposure of samples, such as microbial cultures placed in flat-bottom 96-well plates (Sarstedt, Sarstedt, Germany), the setup was as previously described [23]. Briefly, the gas plasma jet was installed (Figure 1a) on a computer-controlled xyz-stage (CNC step HIGH-Z edition). The distance of the jet to the treated liquid (0 mm, conductive mode [25]), the jet’s relative position to the well (always: centered), and the exposure time (see legends) were precisely controlled and monitored using appropriate CNC-compatible software. For the addition of oxygen (purity: 4.5; Air Liquide) and nitrogen (purity: 4.5; Air Liquide), a panel of mass flow controllers and valves was used and controlled through a central digital panel (MKS, München, Germany) for sub-percent precision. Similarly, humidified argon was generated by bubbling the gas through double-distilled water before being mixed with dry argon. For the treatment of microorganisms, the respective strains were seeded at 1 × 104 microorganisms per well in 100 µL of each broth. Evaporation of liquid through gas plasma exposure was accounted for by adding a predetermined amount of sterile double-distilled water. Microorganisms were counted by taking 20 µL and adding paraformaldehyde before measuring via flow cytometry as described in Section 2.3. To control the growth of unspecific bacteria contamination, 100 µL of broth without bacteria was treated. In some experiments, H2O2 was added instead of gas plasma exposure. The rest of the experimental workflow and analysis remained the same.
## 2.3. Flow Cytometry
Following gas plasma exposure, the microorganisms in the microwell plates were kept at room temperature in the dark for 16 h. In some conditions, 2 µL of catalase solution (Sigma-Aldrich, Taufkirchen, Germany) was added (final concentration: 20 µg/mL) either before or after gas plasma exposure of samples. Then, to each well, fixative was added ($4\%$ paraformaldehyde; Sigma-Aldrich) and incubated for 10 min in the dark. Then, to each well, 4′,6-diamidino-2-phenylindole (DAPI, final concentration 10 µM; BioLegend, Amsterdam, The Netherlands) was added, and the microorganisms were incubated for 15 min in the dark. All microorganisms contain ample amounts of DNA to which DAPI binds and becomes fluorescent. This way, microorganisms can be conveniently detected using flow cytometry. Next, the microplates were added to an autosampler of a CytoFLEX S flow cytometer (Beckman-Coulter, Krefeld, Germany) trigger through the forward scatter (488 nm laser diode) and collection of DAPI fluorescence via λex 405 nm and λem 450 ± 45 nm. After mixing by the autosampler, 100µL of cell suspension was acquired from each well. The resulting.fcs (3.1 standard) data files were analyzed using *Kaluza analysis* software 2.1.3 (Beckman-Coulter).
## 2.4. Antimicrobial Efficacy Using Agar Plates
Sixteen hours following gas plasma exposure, the resulting microorganism samples were spread onto CASO agar plates at different dilutions. The plates were incubated at 30 °C overnight. After 24 h, colony formation was quantified by manual counting, whereas the threshold of countability was set to 1000 per plate. For measuring the inhibition zone, bacteria were plated on agar plates, and the middle was treated with plasma. The plates were incubated at 30 °C overnight, and the area was measured after 24 h by inhibition zone image analysis.
## 2.5. ROS Analysis
Phosphate-buffered saline (PBS; Pan-Biotech, Aidenbach, Germany) was exposed to gas plasma for different treatment times. A gradient of humidified feed gas was applied to a set of samples. Subsequently, hydrogen peroxide (H2O2) was quantified using the Amplex Ultra Red Assay Kit (Thermo Fisher Scientific, Dreieich, Germany) as previously described [23]. In addition, nitrite (NO2−) concentrations were assessed using Griess reagent (Thermo Fisher Scientific) as recently outlined [26].
## 2.6. Statistical Analysis
Statistical analysis was performed using prism 9.5.0 (GraphPad Software, San Diego, CA, USA) based on one-way analysis of variances as indicated in the figure legends. Data are shown as mean + S.E. if not described differently, and the number of experiments is given in the legends. The alpha error was set as follows: α = 0.05 (*), α = 0.01 (**), and α = 0.001 (***).
## 3.1. Comparison of Plasma Jet Feed Gas Admixtures for Abolishing Microbial Growth
This study sought to investigate the antimicrobial efficacy of the atmospheric pressure argon plasma jet kINPen operated at different feed gas conditions to identify those potentially increasing the current capacity targeting microorganisms. To this end, a diverse set of microorganisms was exposed to gas plasma in vitro, and microbial growth was analyzed 16 h later (Figure 1b). While these different strains and organisms gave different patterns in size and nucleic acid content, all could be quantified confidently (Figure 1c). Hence, toxicity to microorganisms inflected by gas plasma treatment or positive control ($10\%$ ethanol) could be quantified properly (Figure 1d). Next, we screened 10 different microorganisms (9 bacteria, 1 yeast) for increased sensitivity to argon gas plasma exposure (treatment time per well: 5 s) admixed with either oxygen, nitrogen, or humidified argon (Figure 1e). E. coli strains were less sensitive, while the yeast (C. albicans) was resistant to the gas plasma treatment. By contrast, P. strains showed a particular sensitivity, which was partially also the case for S. strains. Concerning the gas plasma treatment regimens, a reduction of absolute cell numbers was observed for all regimens investigated, while admixtures were more potent than dry argon gas alone. This was also reflected in the cumulative microbial reduction scores for each feed gas regimen across all ten strains investigated (Figure 1f), which was the highest for humidified argon gas plasma treatment.
## 3.2. Comparison of Plasma Jet Feed Gas Admixtures for Inhibition Zones and Abolishing CFU
To confirm the results retrieved by flow cytometry of microorganisms grown in suspension, we plated the gas-plasma-treated E. coli samples on agar plates. We investigated the number of colony-forming units (CFU) per sample and at different dilutions (Figure 2a). Macroscopically, the efficacy of humidified argon-gas-plasma-treated samples in reducing CFUs (Figure 2b, right image) was apparent to be superior to that of dry argon-gas-plasma-treated microorganisms (Figure 2b, center image) and untreated controls (Figure 2b, left image). Quantitative CFU assessment strengthened this notion, concluding a superior ability of humidified argon gas plasma to decelerate microbial colony formation (Figure 2c). To further confirm the superiority of humidified over dry argon gas plasma treatment of microorganisms, S. aureus was plated on agar plates, and the centers of the plates were exposed to gas plasma for 30 s or 60 s (Figure 3a). The plates were incubated overnight and photographed (Figure 3b), followed by quantifying inhibition zones (Figure 3c). Expectedly, 30 s gas plasmas treatment created smaller inhibition zones compared to 60 s. Interestingly, and similar to the previous experiments in this study, humidified argon gas plasma was significantly superior regarding inhibition zones when compared to dry conditions. It should be noted, however, that $20\%$ argon feed gas humidity was similar or slightly less effective compared to $10\%$ humidity, as already observed in the microorganism suspension gas plasma experiments (Figure 1f). Strikingly, a significantly increased inhibition zone was also observed in drug-resistant S. aureus (MRSA) (Figure 3d).
## 3.3. ROS and RNS Analysis
The major mode of action in gas plasma is ROS generation. Identifying alterations in ROS generation signatures can reveal what types of ROS potentially contribute to the effects observed. To this end, we used different feed gas humidity percentages and exposure of liquid to better understand ROS dynamics. Macroscopically, it could be observed that already $1\%$ humidity in the argon feed gas led to a shorter kINPen plasma effluent (Figure 4a). Increasing humidity to $5\%$ increased this effect, while the length between $10\%$ and $20\%$ humidity was unchanged, indicating a limit of this shortening effect. Subsequently, H2O2 was quantified in PBS exposed to 5 s or 15 s of dry or humidified argon gas plasma. As expected from previous reports, there was an increased H2O2 generation with highly humid argon plasma kINPen treatments (Figure 4b). However, three novel observations were made. First, it was interesting to note that the H2O2 production rates did not change at humidity percentages up to $1\%$, despite an apparent visual change of the plasma jet plume at that percentage (Figure 4a). Second, it has not been described that adding feed gas humidity elevates H2O2 generation rates more than 9-fold. Third, we found that during humidity concentrations of up to $1\%$, nitrogen species such as NO2− were elevated (Figure 4c). Their concentrations declined at $5\%$ or higher, being close to the detection range at $20\%$ humidity. As we could not detect any enhanced antimicrobial activity of feed gas humidity up to $1\%$ (data not shown), while marked elevation was observed at $10\%$ and $20\%$, where H2O2 levels were also found to be highest, we investigated its role in the effects observed. As proof of principle, we tested a dilution series of H2O2 for its antimicrobial activity in E. coli, and the expected decline was found (Figure 4d). Next, we did the reverse experiment by using catalase, a potent scavenger of H2O2 [27], which was added either before or immediately after gas plasma exposure of four different microorganism strains. The summarized data indicate that catalase added prior to gas plasma treatment of microorganisms in liquid suspensions (not on agar plates) completely and significantly abrogated antimicrobial gas plasma effects (Figure 4e). Interestingly, catalase addition after gas plasma exposure only partially rescued the demise of microorganisms. These data strongly suggested that H2O2 plays a decisive role in the enhanced antimicrobial activity of humidified argon plasma jet treatments.
## 4. Discussion
Our study aimed at identifying feed gas compositions that enhanced the antimicrobial activity of the clinically employed atmospheric pressure argon plasma jet kINPen. Here, we report highly humidified argon gas feed into the plasma jet to meet this aim. We found elevated antimicrobial activity across several assays.
The idea of feed gas alterations in gas plasma devices to enhance or reduce a given effect in plasma medicine has been around for over a decade [28]. The three larger fields addressed with such an approach so far are wound healing [11], oncology [29], and decontamination and antimicrobial activity [17,30]. Regarding the latter and focusing on the kINPen, a previous version of this atmospheric pressure argon plasma jet (kINPen 09) operated with either dry argon or dry argon plus $1\%$ oxygen did not yield better results concerning antimicrobial activity [31]. In contrast, small oxygen admixtures (<$1\%$) have been previously reported to increase inhibition zones in argon-gas-plasma-treated S. aureus cells plated on agar plates [20]. Notwithstanding, it should be noted that due to biofilm formation and high abundance of ROS-scavenging biomolecules in tissues, the absolute antimicrobial activity (in terms of log CFU reduction) is only modest in gas-plasma-treated wounds [8,9,11] compared to ideal laboratory conditions where several log reduction of CFU are often observed [32].
It is known that the chemistry of gas plasma sources depends on the feed gas and surrounding gas. The same is true for the kINPen [21,33,34]. This includes feed gas humidification, which has been described to lead to enhanced generation of H2O2 in kINPen-treated liquids [23,35]. Such humidification leads to a change in the species composition in the kINPen effluent, including a decline of atomic oxygen, nitrogen species, ozone, and superoxide radicals and an increase of hydroxy [23,36]. Importantly, when referring to humidity, it is referenced to feed gas humidity, as the impact of environmental (ambient air/room air) humidity on the species profiles generated is negligible [36]. However, our finding that small humidity admixtures of around $0.8\%$ added to the feed gas promote the generation of reactive nitrogen species, of which NO2− is a reaction product, has not been documented before. Future studies may underline the mechanisms of these findings by performing additional analysis of the plasma jet via, e.g., optical emission spectroscopy. This information could be valuable for the field of plasma agriculture, where nitrogen fixation into liquids is one primary goal [37]. If in situ generation of H2O2 is aimed to be maximized, such as in the application of plasma-treated or plasma-condition media (also referred to as PAM or PAL) [38], high feed gas humidification rates may help achieve this goal, depending on the plasma source used.
Since H2O2 is a central molecule in redox biology and signaling [39], enhanced kINPen treatment effects on HaCaT keratinocytes were identified using humidified over dry argon gas [35]. Such a setting was also more cytotoxic in B16F10 melanoma cells in vitro, while nitrogen and oxygen admixtures were less effective compared to dry argon gas kINPen operation [23]. Therefore, our results are in line with previous findings made in eukaryotic cells with regard to humidified argon kINPen operations. However, in our current study, the additive toxicity conferred by such humidification in the eukaryotic organism C. albicans was rather modest, albeit previous findings had shown an antifungal activity of the kINPen in the agar plate model [40]. This difference might be explained by the different exposure models in our current study, foreseeing antimicrobial gas plasma treatment of cells suspended in broth rather than plated on agar. In addition, it must be noted that our results need further investigation in other types of plasma sources and, as of now, holds for the kINPen, primarily. We have recently humidified the helium feed gas of the European reference jet (also referred to as COST jet) [41], and our results did not show an enhanced H2O2 production or toxicity in eukaryotic cells exposed to this humidified feed gas compared to dry helium gas plasma conditions [42].
In summary, our results on the enhanced antimicrobial activity of humidified argon plasma appear promising for wound decontamination purposes. It must be tested in future animal and patient studies to verify its potential.
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|
---
title: A Preliminary Comparison of Plasma Tryptophan Metabolites and Medium- and Long-Chain
Fatty Acids in Adult Patients with Major Depressive Disorder and Schizophrenia
authors:
- Jun-Chang Liu
- Huan Yu
- Rui Li
- Cui-Hong Zhou
- Qing-Qing Shi
- Li Guo
- Hong He
journal: Medicina
year: 2023
pmcid: PMC9968143
doi: 10.3390/medicina59020413
license: CC BY 4.0
---
# A Preliminary Comparison of Plasma Tryptophan Metabolites and Medium- and Long-Chain Fatty Acids in Adult Patients with Major Depressive Disorder and Schizophrenia
## Abstract
Background and Objectives: Disturbance of tryptophan (Trp) and fatty acid (FA) metabolism plays a role in the pathogenesis of psychiatric disorders. However, quantitative analysis and comparison of plasma Trp metabolites and medium- and long-chain fatty acids (MCFAs and LCFAs) in adult patients with major depressive disorder (MDD) and schizophrenia (SCH) are limited. Materials and Methods: Clinical symptoms were assessed and the level of Trp metabolites and MCFAs and LCFAs for plasma samples from patients with MDD ($$n = 24$$) or SCH ($$n = 22$$) and healthy controls (HC, $$n = 23$$) were obtained and analyzed. Results: We observed changes in Trp metabolites and MCFAs and LCFAs with MDD and SCH and found that Trp and its metabolites, such as N-formyl-kynurenine (NKY), 5-hydroxyindole-3-acetic acid (5-HIAA), and indole, as well as omega-3 polyunsaturated fatty acids (N3) and the ratio of N3 to omega-6 polyunsaturated fatty acids (N3: N6), decreased in both MDD and SCH patients. Meanwhile, levels of saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) decreased in SCH patients, and there was a significant difference in the composition of MCFAs and LCFAs between MDD and SCH patients. Moreover, the top 10 differential molecules could distinguish the two groups of diseases from HC and each other with high reliability. Conclusions: This study provides a further understanding of dysfunctional Trp and FA metabolism in adult patients with SCH or MDD and might develop combinatorial classifiers to distinguish between these disorders.
## 1. Introduction
Major depressive disorder (MDD) and schizophrenia (SCH) are severe psychiatric diseases that affect a large number of people worldwide [1,2]. These two diseases’ diagnoses are still mainly defined by their clinical features. However, converging evidence suggests that these disorders have considerable overlap in symptoms and heritage patterns [3,4,5], making it sometimes difficult to distinguish between SCH and MDD. Therefore, clinical characteristics alone are of limited predictive value and biological predictors will be of enormous value [6].
Tryptophan (Trp) and its metabolites are involved in the regulation of neuronal function and immunity, and the imbalances in Trp metabolism have resulted in neurodegenerative disease [7]. A significant amount of evidence suggests that plasma Trp and its catabolites have been considered contributing factors in the etiology of MDD and SCH [8,9]. On the other hand, fatty acids (FAs) also play a role in neural membrane fluidity and receptor binding, affecting neurological functions such as synthesizing and releasing neurotransmitters, neurogenesis, and myelination [10,11,12]. The abnormal composition of FAs in the plasma, especially the changes of omega-3 (N3) polyunsaturated fatty acids (PUFAs) and omega-6 (N6) PUFAs in patients with MDD and SCH have been widely reported [13,14]. Although several Trp metabolites and FAs might be potential peripheral biomarkers for MDD and SCH [15,16,17], thus far, no studies have directly compared the plasma Trp metabolites and FA compositions between adult patients with SCH and MDD, so the development of combinational molecular biomarkers might be useful in distinguishing these two diseases.
In the present study, we performed a case-control study using liquid chromatography- or gas chromatography-mass spectrometry (LC-MS or GC-MS)-based analysis of plasma samples ($$n = 69$$) from sex- and age-matched adult individuals with MDD ($$n = 24$$), SCH ($$n = 22$$) and healthy controls (HC, $$n = 23$$). We sought to determine the differences in Trp metabolites and the composition of medium- and long-chain fatty acids (MCFAs and LCFAs) and analyze the correlation between differential profiles and clinical symptoms. Moreover, we also sought to identify discriminative combined panels that can distinguish individuals with MDD, individuals with SCH, and HCs using random forest and receiver operating characteristic (ROC) analysis.
## 2.1. Subjects and Plasma Sampling
This study was performed in accordance with the tenets of the Declaration of Helsinki. All subjects volunteered to participate in this study and provided written informed consent. MDD and SCH were diagnosed based on a Structured Clinical Interview for Diagnostic and Statistical Manual (DSM-5) of Mental *Disorders criteria* by two senior psychiatrists. The Mini-International Neuropsychiatric Interview was used to screen for preexisting psychiatric disorders. The Hamilton Anxiety Scale (HAMA), Hamilton Depression Rating Scale (HAMD), and Positive and Negative Syndrome Scale (PANSS) were independently administered by two psychiatrists who were blinded to the clinical status of the participants. The scores were positively correlated with anxiety, depression, and psychosis symptoms, respectively. The exclusion criteria were obesity, defined as a body mass index (BMI) ≥ 28.0; hypertension; a high-fat diet or vegetarian; lactation, or menstruation; alcohol abuse or dependence; illicit drug use; and presence of other mental disorders according to DSM-5 criteria. Finally, 24 patients with MDD (average age 33, 8 male and 16 female) and 22 patients with SCH (average age 31, 7 male and 15 female) were recruited from the Department of Psychiatry at Xijing, Gaoxin and Chang’an Hospital, along with 23 HCs (average age 29, 7 male and 16 female), all of whom underwent a physical examination. Blood samples were collected in anticoagulant tubes and centrifuged at 1600 rpm for 15 min between 8 AM and 10 AM from all participants under fasting conditions. The obtained plasma was stored in sterile cryopreservation tubes and stored in liquid nitrogen until further analysis.
## 2.2. Detection of Tryptophan and Its Catabolites
Take out the samples and slowly dissolve at 4 °C, then take 200 μL of each sample and add 800 μL of precooled methanol acetonitrile solution (1:1, v/v), vortex for 60 s, and place at −20 °C for 1 h to precipitate the protein. Then, centrifuge at 4 °C for 20 min (14,000 rcf), take the supernatant, and freeze-dry. Separate the samples using the Agilent 1290 Infinity UHPLC system. Place the standard in the 4 °C automatic samplers. The column temperature is 50 °C, the flow rate is 400 μL/min, and the injection volume is 5 μL. The relevant liquid phase gradient is as follows: 0–2 min, $15\%$ for solution B; linear change from $15\%$ to $98\%$ in 2–9 min; 9–11 min, $98\%$ for solution B; 11–11.5 min, solution B changes linearly from $98\%$ to $15\%$; 11.5–14 min, $15\%$ for liquid B. The 5500 QTRAP mass spectrometer (AB SCIEX) is used for mass spectrometry analysis in positive ion mode. 5500 QTRAP ESI source conditions are as follows: source temperature: 550 °C; Ion Source Gas1 (Gas1): 55; Ion Source Gas2 (Gas2): 55; Curtain gas (CUR): 40; ionSapary Voltage Floating (ISVF): +4500 V. Use MRM mode to detect ion pairs to be measured and MultQuant or Analyst software for the quantitative analysis.
## 2.3. Detection of Medium and Long-Chain Fatty Acids
Thaw the sample on ice and take 150 μL of the sample in a 2 mL glass centrifuge tube. Add 1 mL of chloroform-methanol solution, ultrasound for 30 min, take the supernatant, add 2 mL of $1\%$ sulfuric acid methanol solution and put it on a water bath at 80 °C, methylate it for half an hour, add 1 mL of N-hexane for extraction, add 5 mL of pure water for washing, and suck 500 μL of the supernatant. Then, add 25 μL of methyl salicylate as the internal standard, mix and add it into the injection bottle, and then test using GC-MS. The injection volume is 1 μL and the split ratio is 10:1, split injection. The samples are collected on Agilent DB-WAX capillary column (30 m × 0.25 mm ID × 0.25 μm) gas chromatography system. Programmed temperature rise: initial temperature 50 °C; keep for 3 min, and raise the temperature to 220 °C at 10 °C/min and maintain for 5 min. The carrier gas is helium, and the carrier gas flow rate is 1.0 mL/min. One QC sample shall be set for a certain number of experimental samples at every interval in the sample queue to detect and evaluate the stability and repeatability of the system. The Agilent $\frac{7890}{5975}$C GC-MS is used for mass spectrometry analysis. The injection port temperature is 280 °C; the ion source temperature is 230 °C; the transmission line temperature is 250 °C and uses an electron impact ionization (EI) source, SIM scanning mode, and electron energy of 70 eV. Use MSD ChemStation software (MSD ChemStation, Agilent Technologies, Santa Clara, CA, USA) to extract the chromatographic peak area and retention time. Draw the calibration curve and calculate the content of MCFAs and LCFAs in the sample.
## 2.4. Statistical Analyses
Statistical analyses were performed using SPSS 19.0 software (IBM-SPSS Inc., Chicago, IL, USA) and R-4.0.5 (R Core Team, Vienna, Austria). Differences in continuous variables were assessed using the Kruskal–Wallis test (abnormal distribution) or one-way analysis of variance combined with Bonferroni correction (normal distribution). The measurement data conforming to the normal distribution is represented by mean ± SD and the measurement data nonconforming to the normal distribution is represented by M (P25, P75). Comparison of counting data was expressed in number and percentage and assessed using χ2 test. $p \leq 0.05$ indicates that the difference is statistically significant. The Spearman correlation analysis was used to assess the correlations between the clinical parameters and differential metabolites. To obtain simplified potential biomarker panels, the online software MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/, accessed on 12 October 2022) was used to conduct random forest analysis, screen biomarkers, and draw ROC curves, and the metabolite of Top10 was selected as the candidate biomarker.
## 3.1. Clinical Characteristics of the Recruited Participants
A total of 69 individuals were included in the study. No significant differences were found among the three groups in terms of age ($$p \leq 0.288$$), gender ($$p \leq 0.978$$), and BMI ($$p \leq 0.058$$). Scores of HAM-D and HAM-A in the MDD group were higher than those in the SCH and HC group (Table 1). PANSS total score (T), positive symptom score (P), negative symptom score (N), and general psychopathological symptom score (G) in the SCH group and PANSS (T), PANSS (N) and PANSS (G) in the MDD group were higher than those in the HC group. Moreover, PANSS (P) and PANSS (N) in the SCH group were also higher than those in the MDD group. There was a significant difference among the three groups in terms of marital status, and there was no significant difference in terms of smoking ($$p \leq 0.546$$).
## 3.2. Alternation of Trp and Its Catabolites in SCH and MDD
A total of 11 Trp metabolites were identified. There were significant differences in the levels of tryptophan (Try, $F = 17.10$, $p \leq 0.001$) (Figure 1A), 5-hydroxyindole-3-acetic acid (5-HIAA, $F = 5.551$, $p \leq 0.001$) (Figure 1B), N-formyl-kynurenine (NKY, $F = 3.551$, $$p \leq 0.034$$) (Figure 1C), Indole ($F = 38.36$, $p \leq 0.001$) (Figure 1D), Indole-3-carboxaldehyde (IAId, $F = 18.80$, $p \leq 0.001$) (Figure 1E), Indoleacetate (IAA, $F = 5.422$, $p \leq 0.01$) (Figure 1F), and indole-3-lactic acid (ILA, $F = 28.12$, $p \leq 0.001$) (Figure 1G) among the three groups. Intercomparison further showed that the levels of Try, 5-HIAA, NKY, Indole, IAId, and ILA decreased in both MDD and SCH groups compared with the HC group. Meanwhile, levels of IAA decreased in the MDD group compared with the HC group (Figure 1F), and levels of ILA also decreased in the MDD group compared with the SCH group (Figure 1G). Furthermore, levels of IAId, Indole, ILA, Try, 5-HIAA, NKY, and IAA were negatively correlated with the scores of HAMA, HAMD, and PANSS (T) (Figure 1H). However, there were no significant differences in the levels of L-kynurenine, picolinic acid, quinolinic acid, and 3-indoxyl sulfate among the three groups (Table 2). These results suggested that levels of plasma Trp and its catabolites in the SCH and MDD groups were largely changed, but only ILA is the differential metabolite between these two groups.
## 3.3. Alternation of MCFAs and LCFAs in SCH and MDD
A total of 35 medium- and long-chain fatty acids were identified in samples from each group. GC-MS analysis revealed that there were significant differences in the levels of saturated fatty acids (SFA, $F = 4.773$, $$p \leq 0.012$$), monounsaturated fatty acids (MUFA, $F = 3.736$, $$p \leq 0.029$$), omega-3 polyunsaturated fatty acids (N3, $F = 18.028$, $p \leq 0.001$), and the N3:N6 ratio ($F = 7.748$, $$p \leq 0.001$$), whereas there were no significant differences in the levels of total FAs ($F = 0.991$, $$p \leq 0.377$$), polyunsaturated fatty acids (PUFA, $F = 2.767$, $$p \leq 0.070$$), and omega-6 polyunsaturated fatty acids (N6, $F = 3.041$, $$p \leq 0.055$$) (Figure 2A–G). Meanwhile, levels of N3 and the N3/N6 ratio in both MDD and SCH groups were less than those in HC group. The SCH group also showed decreased SFA and MUFA compared with the HC group. Otherwise, levels of N3 were negatively correlated with the scores of HAMA, HAMD, PANSS (T), and PANSS (N), whereas the N3/N6 ratio was negatively correlated with the scores of PANSS (T) and PANSS (P) (Figure 2H). There were also significant differences in the levels of multiple fatty acids, including C8:0 ($F = 33.082$, $p \leq 0.001$), C10:0 ($F = 6.664$, $$p \leq 0.002$$), C12:0 ($F = 4.875$, $$p \leq 0.011$$), C13:0 ($F = 16.166$, $p \leq 0.001$), C18:0 ($F = 6.172$, $$p \leq 0.004$$) and C20:0 ($F = 5.872$, $$p \leq 0.004$$) in SFA; C14:1N5 ($F = 4.551$, $$p \leq 0.014$$), C22:1N9 ($F = 18.179$, $p \leq 0.001$) and C24:1N9 ($F = 15.481$, $p \leq 0.001$) in MUFA; C22:6N3 ($F = 11.865$, $p \leq 0.001$), C22:5N3 ($F = 4.083$, $$p \leq 0.021$$), C18:2N6 ($F = 3.354$, $$p \leq 0.041$$), C18:3N6 ($F = 14.976$, $p \leq 0.001$), C20:4N6 ($F = 3.307$, $$p \leq 0.043$$), C22:2N6 ($F = 9.249$, $p \leq 0.001$), and C20:4N6 ($F = 3.651$, $$p \leq 0.031$$) in PUFA. Intercomparison further showed that the levels of C8:0, C10:0, C12:0, C13:0, C22:1N9, C22:6N3, and C22:5N3 decreased, whereas those of C14:1N5, C24:1N9, C18:3N6, C22:4N6, and C22:2N6 increased in the MDD group compared with the HC group. Meanwhile, levels of C8:0, C10:0, C13:0, C18:0, C24:1N9, C20:5N3, C22:6N3, and C22:5N3 decreased, whereas those of C20:0, C14:1N5, C18:2N6, C18:3N6, and C20:4N6 increased in the SCH group compared with the HC group. Moreover, levels of C18:0, C24:1N9, and C22:2N6 increased, whereas C20:0 and C22:1N9 decreased in the MDD group compared with the SCH group (Table 3).
## 3.4. Characteristic Fatty Acids and Trp Catabolites in SCH and MDD
Based on random forest analysis, the top 10 differential molecules, including C22:1N9, indole, C8:0, C10:0, ILA, C18:3N6, IAId, Trp, C13:0, and NKY, were selected as potential biomarker panel, which could effectively distinguish between MDD and HC (AUC = 0.99, Figure 3A,B). Moreover, a panel containing C8:0, C24:1N9, indole, C18:3N6, NKY, C10:0, C13:0, IAId, QUIN, and C24:0 could effectively distinguish between SCH and HC (AUC = 0.996, Figure 3C,D). Notably, a panel consisting of C24:1N9, C22:1N9, C22:2N6, ILA, C18:1N9, C22:0, C16:1N7, C18:0, IAId, and C20:2N6 could effectively distinguish between MDD and SCH (AUC = 0.981, Figure 3E,F).
## 4. Discussion
In this study, we investigated the compositions of plasma Trp metabolites and MCFAs and LCFAs in adult patients with MDD and SCH. We found that Trp and its metabolites such as 5-HIAA, NKY, and indole, and total N3 and the N3:N6 ratio decreased in both the MDD and SCH groups. Intriguingly, the composition of MCFA and LCFA was different between MDD and SCH, while only ILA in tryptophan metabolites was different between these two groups. Moreover, the top 10 differential molecules, which could distinguish the two groups of diseases from HC and each other with high reliability, were screened. These results may shed light on the investigation of diagnostic molecular targets for SCH and MDD and are worth further exploration due to the limited sample size.
Trp is an essential amino acid and a biosynthetic precursor of a large number of metabolites [18]. In the gastrointestinal tract, Trp derivatives are formed in three main pathways: the kynurenine pathway (KP), the major metabolic pathway for free Trp, which leads to the formation of several metabolites with distinct biological activities in the neurotransmission and immune response such as NKY, L-kynurenine, kynurenic acid (KYNA), picolinic acid, and quinolinic acid [19]; the serotonin production pathway via Trp hydroxylase 1, which produces serotonin and could further metabolize into 5-HIAA [20]; and the microbial metabolism pathway, which directly transforms Trp into several molecules such as indole, IAA, indoxyl sulfate (IS), and IAId [21]. The rate-limiting step is the conversion of Trp to N-formyl-kynurenine (NKY) by indoleamine-2,3-dioxygenase (IDO) and tryptophan-2,3-dioxygenase (TDO). The abnormalities of the Trp metabolites, especially in KP, have been observed in MDD. For instance, plasma Trp and KYNA decreased in patients with MDD [22,23]. Correspondingly, IDO activity was elevated in MDD and positively correlated with depressive symptoms [24]. Consistent with these results, the present study found that Trp and NKY decreased in patients with MDD, indicating that Trp metabolism increased in MDD. However, we did not observe changes in QUIN and PIC in patients with MDD compared with HCs. QUIN is considered a neurotoxic metabolite that participates in the generation of ROS and stimulates synaptosomal glutamate release [25], whereas PIC is considered a neuroprotective metabolite that exhibits immunomodulatory properties [26]. Whereas several works found that peripheral QUIN increased [27] while PIC decreased in patients with MDD [28,29], a recent study comparing MDD cases versus controls found that there were no significant differences in tryptophan catabolites [9]. On the other hand, decreased Trp and elevated kynurenine/Trp ratios were also reported in patients with SCH [16]. Similarly, the present study also found that Trp and NKY decreased in patients with SCH, indicating that Trp metabolism increased in both MDD and SCH patients. Of note, the present study did not observe changes in QUIN and PIC in patients with SCH compared with HCs. Although a previous study found that peripheral QUIN was in patients with SCH [30], a systematic review inferred that there was no significant increase in QUIN and PIC, and peripheral blood levels of tryptophan catabolites were dissociated from central nervous system findings except for a modest increase in the serum IDO activity of patients with SCH [31]. Due to effect sizes varying greatly between studies assessing kynurenine pathway metabolites in MDD and SCH groups [23,32], a longitudinal trial with a large sample size might further clarify these differences.
Alternation of 5-HIAA in patients with MDD and SCH has also been reported. A previous study found that plasma 5-HIAA increased in depressed patients [33]. However, a recent systematic umbrella review indicated the hypothesis that depression is caused by lowered serotonin activity or concentrations is not convincing enough, and 5-HIAA concentrations in cerebrospinal fluid are not associated with depression [34]. Intriguingly, another work found that plasma 5-HIAA levels are negatively correlated with the depression/anxiety component in patients with SCH [35]. The present found that 5-HIAA decreased in patients with MDD and SCH and was negatively correlated with the scores of HAMA, HAMD, PANSS (N), and PANSS (T), indicating that plasma 5-HIAA might be related to emotional symptoms rather than disease types. Furthermore, indole metabolites, such as IAId, ILA, and IAA, are considered beneficial to inhibit neuronal damage and exert anti-inflammatory effects [36,37]. Importantly, lower concentrations of Trp and indoles, particularly IAld in serum, are correlated with more severe depressive symptoms [38]. In line with this study, we found that indole, IAId, and IAA decreased in both MDD and SCH patients and were negatively correlated with the scores of HAMA, HAMD, and PANSS (T), suggesting that the unbalance of indole metabolism might be a common characteristic of these two diseases.
Medium- and long-chain fatty acids (MCFAs and LCFAs) are natural compounds that mainly participate in cell metabolism. MCFAs are important food constituents that contain total carbon atom numbers from 6 to 12 [39], whereas those greater than 12 are considered long-chain fatty acids. The roles of MCFAs within gluconeogenesis and lipogenesis as well as mitochondrial function and metabolism have been uncovered currently [40,41]. Although animal studies have revealed that exogenous supplementation of MCFAs or their esters (medium-chain triglycerides, MCT) can improve depressive behavior and cognitive function [42], so far, changes in peripheral MCFAs in patients with depression and schizophrenia have been poorly investigated. In the present study, levels of caprylic acid (C8:0) decreased in both MDD and SCH patients and were negatively correlated with the scores of HAMA, HAMD, PANSS (N), and PANSS (T). Meanwhile, capric acid (C10:0) and lauric acid (C12:0) decreased in patients with MDD and were negatively correlated with the scores of HAMA or scores of HAMA and HAMD, respectively. Given the neuroprotective effects and neuroregulation of caprylic acid, capric acid, and lauric acid [43,44], their potential role in the pathogenesis of neurological disorders still needs to be further determined.
In the present study, we further compare the concentrations of SFAs, MUFAs, and PUFAs in HC, MDD, and SCH. SFAs have been shown to influence several brain circuits and thus regulate mood [45]. SFAs could stimulate the release of pro-inflammatory cytokines and induce the apoptosis of astrocytes [46]. Whereas intake of SFAs causes impairments in the activity of the brain dopamine system and induces depressive-like behavior in rodents [47,48], the accumulation of SFAs may play a role in the pathogenesis of MDD and SCH. In contrast with the effects of SFAs, pre-clinical findings reveal that the intake of MUFAs has been suggested to improve brain function, such as the protection of the integrity of the dopamine system and facilitation of neurotransmitter signal transduction [49,50]. Importantly, a clinical study also found that a MUFA-enriched diet in humans reduces the risk of depression [51]. In the present study, although there is no significant difference between MDD and HC in the plasma total SFA and MUFA, C22:1N9 decreased and C14:1N5 and C24:1N9 increased in patients with MDD compared with HCs or patients with SCH. Meanwhile, C8:0, C10:0, C12:0, and C13:0 decreased in patients with MDD compared with HCs. On the contrary, plasma total SFA and MUFA decreased in patients with SCH compared with HCs. Notably, we found that C18:0, C16:1N7, and C20:1N9 decreased in patients with SCH compared with HCs or patients with MDD. Moreover, we also found that C8:0, C10:0, C13:0, C18:0, and C24:1N9 decreased whereas those of C20:0 and C14:1N5 increased in the SCH group compared with the HC group. Intriguingly, levels of C18:0, C24:1N9, and C22:2N6 were increased whereas C20:0 and C22:1N9 decreased in the MDD group compared with the SCH group. Therefore, the changes in plasma SFA and MUFA in patients with SCH are more than those in patients with MDD, and the abnormal composition of SFA and MUFA may be one of the peripheral mechanisms leading to depressive and psychiatric symptoms.
PUFAs play several important roles in brain function and neural diseases, such as regulation of neurotransmission, neuroinflammation, mood, and cognition [52]. Previous studies mainly focused on N3 and N6 PUFAs in samples of patients with MDD. Although previous studies provide evidence of decreased N3 PUFA and changed N6 PUFA levels in patients with MDD [53], the link between N-3/N-6 PUFA and MDD is inconsistent [54]. In confirmation with these results, we found that levels of N3 as well as DHA and DPA, and the N3:N6 ratio decreased in patients with MDD. However, there is no significant difference between HC and MDD on the levels of N6 and total PUFA, indicating that decreased plasma N3 is a feature of MDD. Altered N3 and N6 PUFAs in samples of patients with SCH have also been reported previously [55]. Recent work has indicated that long-chain N3 and N6 concentrations are associated with a lower risk of schizophrenia. By contrast, there is weak evidence that short-chain N3 and N6 are associated with an increased risk of schizophrenia [56]. The present study also found that N3, as well as EPA, DHA, and DPA and the N3:N6 ratio, decreased in patients with SCH, indicating that decreased plasma N3 is a common feature of the two diseases. Of note, a number of studies have found that N3 but not N6 decrease in patients with MDD. For example, levels of N3 were significantly lower in depressive patients and there was no significant change in N6 between patients with MDD and control subjects [53], and lower levels of total N3 and increased N6/N3 ratios were also reported in perinatal depression patients [57]. However, a recent study found that N3 is lower in depression, but it is not consistently associated with subsequent change in depressive symptoms [58]. Meanwhile, circulating PUFAs are unlikely to reflect a vulnerability marker for the recurrence of depression [59]. Another study further indicated that the N6:N3 ratio is positively associated with MDD at age 24, but there was little evidence of cross-sectional associations between PUFA measures and mental disorders at age 17 [60]. On the other hand, dietary supplementation with N3 during pregnancy or postpartum reduces depressive symptoms and N3 adjuvant treatment is a potential option for depression and anxiety symptoms of people with recent onset psychosis [61,62]. However, recent studies found that N3 have an overall significant beneficial effect on perinatal depression [63], but the evidence of N3 supplementation on sertraline continuous therapy to reduce depression or anxiety symptoms is not enough to make recommendations [64]. Moreover, other studies have also found that N3 supplementation probably has little or no effect in preventing depression or anxiety symptoms [65] and a non-clinical beneficial effect on depressive symptomology compared to placebo in adult patients with depression [66]. Furthermore, basic study has already shown that complementation of diet with arachidonic acid (AA, C20:4N6) is sufficient to alleviate both the microbiota-induced depressive-like behaviors [67]. Together, the changes of PUFA in patients with depression in different studies are not completely consistent, and the results of this study need to be further verified by a large sample size cohort study.
Additionally, we screened the combinatorial markers of Trp metabolites and FAs through random forest analysis. Among them, C8:0, C10:0, C13:0, C18:3N6, indole, NKY, and IAId were the common characteristic molecules in both MDD and SCH, indicating that these disorders have overlapping pathogenesis, which may also be one of the potential mechanisms behind the existence of similar symptoms in both MDD and SCH groups [3,4]. Moreover, the combinatorial markers which can distinguish between MDD and SCH mostly come from fatty acids, suggesting that fatty acid metabolism may play a role in distinguishing between the two diseases.
Finally, several potential limitations should be mentioned. Because Trp and fatty acids metabolism is greatly affected by individuals, such as gender, age, eating habits, and smoking [7,68], the recruited cases are relatively small and the results still need a large sample to explore further. Meanwhile, considering that antidepressant and antipsychotic drugs could affect Trp and fatty acids metabolism [69,70,71], the influence of drugs on plasma Trp metabolites and the composition of fatty acids cannot be excluded. In addition, the detection methods based on mass spectrometry require expensive equipment and may lead to discrepancies in results. Several important molecules related to psychiatric disorders in the plasma, such as 5-HT and melatonin, were not detected in the present study. Furthermore, several fatty acid contents detected in the present study were not consistent with previous work. For example, the concentrations of C14:0, C18:0, and C22:0 was inconsistent with those in other studies [72,73]. This inconsistency may be related to the participants’ eating habits, living standards, gender, and age. Of note, the influence of plasma collection methods, storage conditions, and fatty acid detection and analysis methods on the results cannot be ignored [74]. Therefore, the detection accuracy needs to be improved, and its clinical application is also limited at this stage. Nevertheless, both fatty acid and Trp metabolism are regulated by gut microbiota, and the metabolic pathway of fatty acids in central nervous system diseases and the composition characteristics of gut microbiota in depression and schizophrenia have been clarified [50,75,76]. The potential metabolic pathway of fatty acids in patients with MDD and SCH and the relationship between specific gut microbiota, fatty acid metabolism, and tryptophan metabolism also need to be further explored.
## 5. Conclusions
In summary, the present study characterized plasma Trp metabolites and the composition of MCFAs and LCFAs in adult patients with MDD and SCH. Trp and NKY as well as N3 and the N3:N6 ratio decreased in both patients with MDD and those with SCH. Furthermore, combinatorial classifiers that could discriminate MDD from HC or SCH from HC, as well as MDD from SCH, were developed. Intriguingly, UFA may play a role in distinguishing between MDD and SCH. Our findings might provide a potential strategy to combine Trp with FA metabolism for the diagnosis of MDD and SCH.
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|
---
title: Alginate Ag/AgCl Nanoparticles Composite Films for Wound Dressings with Antibiofilm
and Antimicrobial Activities
authors:
- Matteo Puccetti
- Anna Donnadio
- Maurizio Ricci
- Loredana Latterini
- Giulia Quaglia
- Donatella Pietrella
- Alessandro Di Michele
- Valeria Ambrogi
journal: Journal of Functional Biomaterials
year: 2023
pmcid: PMC9968148
doi: 10.3390/jfb14020084
license: CC BY 4.0
---
# Alginate Ag/AgCl Nanoparticles Composite Films for Wound Dressings with Antibiofilm and Antimicrobial Activities
## Abstract
Recently, silver-based nanoparticles have been proposed as components of wound dressings due to their antimicrobial activity. Unfortunately, they are cytotoxic for keratinocytes and fibroblasts, and this limits their use. Less consideration has been given to the use of AgCl nanoparticles in wound dressings. In this paper, a sustainable preparation of alginate AgCl nanoparticles composite films by simultaneous alginate gelation and AgCl nanoparticle formation in the presence of CaCl2 solution is proposed with the aim of obtaining films with antimicrobial and antibiofilm activities and low cytotoxicity. First, AgNO3 alginate films were prepared, and then, gelation and nanoparticle formation were induced by film immersion in CaCl2 solution. Films characterization revealed the presence of both AgCl and metallic silver nanoparticles, which resulted as quite homogeneously distributed, and good hydration properties. Finally, films were tested for their antimicrobial and antibiofilm activities against *Staphylococcus epidermidis* (ATCC 12228), *Staphylococcus aureus* (ATCC 29213), *Pseudomonas aeruginosa* (ATCC 15692), and the yeast Candida albicans. Composite films showed antibacterial and antibiofilm activities against the tested bacteria and resulted as less active towards Candida albicans. Film cytotoxicity was investigated towards human dermis fibroblasts (HuDe) and human skin keratinocytes (NCTC2544). Composite films showed low cytotoxicity, especially towards fibroblasts. Thus, the proposed sustainable approach allows to obtain composite films of Ag/AgCl alginate nanoparticles capable of preventing the onset of infections without showing high cytotoxicity for tissue cells.
## 1. Introduction
Hard-to-heal wounds heal slowly, have a high recurrence rate, and are associated with the presence of infection and copious exudate. The presence of microorganisms in wounds has been recognized as a significant cause for healing delay. Moreover, chronic wounds are often complicated by the presence of biofilms, inflammation, and/or non-viable tissue production. Non-healing wounds, as an example, are among the serious complications of type 2 diabetes in the world, associated with a high incidence of bacterial infections, impaired immunity, and other complications that can lead to limb amputation [1]. Current therapeutic approaches are, therefore, multifaceted and focused on a rapid healing as well as recurrence prevention. Advanced wound dressings, especially absorbent ones with improved performance, obtained with sustainable methods, and at the same time not based on the use of antibiotics, are an important aspect of wound care in many clinical settings.
Silver has been used in wound care for a long time [2], and it remains a popular active agent for wound treatment still today. It is available in numerous forms and has a broad spectrum of activity. Newer strategies in using silver for wound healing should be oriented towards prolonged release formulations to obtain local drug concentrations able to explain the antimicrobial activity without resulting in local tissue damage. Recently, with advancements in nanotechnology, silver metallic nanoparticles have been attracting the interest of researchers, and their use in wound healing has been proposed because of their unique antimicrobial properties [3,4,5,6,7,8]. Less attention has been paid to the use of AgCl nanoparticles in wound dressing although their antimicrobial activity is largely known [9,10,11,12,13,14,15,16], and to the best of our knowledge, this topic has not been largely investigated [17,18,19]. Alginate has long been used in a variety of biomedical applications owing to its many favorable properties including biocompatibility and low toxicity [20]. Of note, alginate can be tailored as a material with properties suitable for wound healing such as the ability to absorb excess exudates, maintaining a physiologically moist environment, and minimizing wound bacterial infections. Moreover, alginate hydrogels can incorporate silver nanoparticles to obtain wound dressings joining both the previously mentioned polymer characteristics with the silver antimicrobial effects [21,22]. Alginate films containing silver nanoparticles supported on pyrogenic silica have been described as potentially innovative wound dressings characterized by antimicrobial activity and lack of cytotoxic effects against fibroblasts and keratinocytes [6]. Some silver-based alginate wound dressings are already present in the market [23,24]. In these dressings, silver is present in ionic form, as a salt such as AgNO3 or as silver sodium hydrogen zirconium phosphate, silver sulphadiazine, or in metallic silver nanocrystals.
Alginate sodium is an anionic biopolymer obtained from brown seaweed. It is a linear water-soluble block co-polymer whose monomers are β-D-mannuronic and α-L-guluronic acids in different proportions, bound by 1,4-links. When treated with solutions of divalent cations, such as calcium ions, it undergoes fast gelation. These ions act as crosslinkers that interact between guluronic acid (G)-rich regions of adjacent chains, giving rise to the formation of a bulk “egg-box” structure [25].
Recently, an easy and ecofriendly synthetic approach for the preparation of calcium alginate/silver chloride nanocomposite has been reported [15] following the in situ synthesis of silver chloride nanoparticles in alginate dispersion. The composite was tested for antibacterial activity and proposed as a promising candidate for applications in the textile industry as well as a slow-smoke flame retardant.
In the present paper, a modified procedure is proposed to obtain wound dressings with antimicrobial activity. It consists of the immersion of previously prepared AgNO3 loaded alginate films in a CaCl2 solution, thus inducing in one step both the alginate gelation and the Ag/Cl nanoparticles formation. In comparison to the above-described method [15], the present procedure does not include the presence of ammonia, which is often used as a silver-stabilizing agent, and thus, no other reagents were used in addition to those present in the final films. Glycerin was added as a plasticizer agent. The obtained films were characterized with respect to nanoparticle nature, hydration properties, and silver release. Moreover, the antimicrobial and cytotoxic activities were evaluated and compared to those of AgNO3-loaded non-crosslinked alginate films.
## 2.1. Materials
Sodium alginate was bought from Sigma-Aldrich Chemical (Milan, Italy, cod.180947), glycerol $85\%$ from Acef (Fiorenzuola d’Adda, Italy), silver nitrate 99+% from Alfa Aesar (Karlsruhe, Germany), and calcium chloride from Sigma-Aldrich Chemical (Milan, Italy, cod. C1016). Deionized water obtained via a reverse-osmosis procedure (MilliQ system, Millipore, Rome, Italy) was used. Other reagents and solvents were from Sigma-Aldrich and were used as received.
## 2.2. Characterization
X-ray powder diffraction (XRPD) patterns were obtained with the Cu-Kα radiation on a Bruker D8 Advance diffractometer and PW3050 goniometer provided with a Lynxeye detector. The long fine-focus (LFF) ceramic tube was operated at 40 kV and 40 mA. DIFFRAC.EVA V5 software was used for the phase identification (software version 2.0 up, © 2010–2019 Bruker AXS GmbH, Karlsruhe, Germany) and was equipped with COD database.
Particle morphology, surface characteristics, and particle aggregation were examined using an FEG LEO 1525 scanning electron microscope (LEO Electron Microscopy Inc., NY) with an acceleration potential voltage of 1 keV. Samples were placed onto carbon tape-coated aluminum stubs and, before imaging, were sputter-coated with chromium by a high-resolution sputter (Quorum Technologies, East Essex, UK) at 20 mA for 20 s.
A Perkin-Elmer Lambda 800 double-beam UV–vis spectrometer was used to record the absorption spectra and was equipped with a data processor for recording and displaying spectra.
Reflectance spectra of the powder samples were recorded by a Varian (Cary 4000) spectrophotometer that was equipped with a 150 nm integrating sphere (DRA-900).
The light reflected from the sample surface in all directions was collected from the sphere and directed towards the photomultiplier. A fully reflective barium sulfate plate was used as a reference. The connected detector was a photomultiplier.
Quantitative Ag determination was performed with a Varian 700-ES series inductively coupled plasma-optical emission spectrometer (ICP-OES) with axial injection.
## 2.3. Film Preparation
Alginate film was prepared by dispersing sodium alginate ($2\%$ w/w) in water, then adding glycerin ($1\%$ w/w), and leaving the dispersion under magnetic stirring at room temperature for about 12 h until a homogeneous dispersion was obtained. Then, air bubbles were removed using the THINKY ARE-250 at 2000 rpm for 20 min. Finally, the dispersion (25 g) was poured into a 9 cm diameter Petri dish and then dried in a desiccator in the presence of P2O5 and under N2 flow for 7–8 h. The film will be later referred to as film β0. Once dried, film β0 was immersed in $1.6\%$ (w/w) CaCl2 aqueous solution in the dark for 24 h. Then, the gelled film was washed for three times with deionized water. Successively, the excess water was dabbed with a filter paper, and then, the film was maintained in the presence of magnesium nitrate (RH $53\%$) in a desiccator to give the film referred to as film β0CaCl2.
Sodium alginate composite films containing different amounts of AgNO3 (Table 1) were obtained following the procedure described above. Finally, the obtained composite films were gelled by immersion in $1.6\%$ (w/w) CaCl2 aqueous solution to give rise to cross-linked films and nanoparticles formation.
## 2.4. Swelling Test
Quadrate samples (2 mm × 2 mm) were cut from the films β0CaCl2, β1CaCl2, and β2CaCl2. They were weighed (W1) and sunk into a simulated wound fluid composed of an aqueous solution of 0.4 M sodium chloride, 0.02 M calcium chloride, and 0.08 M tris (hydroxymethyl)amino-methane without bovine serum albumin (pH 7.5) [26]. The test was performed at 37 °C.
At set times (0.5, 1, 2, 4, 6, and 24 h), the samples were taken, dabbed with filter paper, and weighed (W2). The following formula was used to measure the water uptake expressed as % of hydration:% of hydration = [(W2 − W1)/W1] × 100 [1] For the determination of dissolution degree, the films immersed for 24 h were weighed and dried at 40 °C for 24 h and maintained in a desiccator for 48 h. Finally, they were weighed again (W3). The dissolution degree (DD) was determined by the following formula:DD = [(W1 − W3)/W1] × $100\%$[2] This test was executed three times, and results were expressed as an average.
## 2.5. In Vitro Silver Release
Circular films (2 cm diameter) were immersed in 10 mL of simulated wound fluid at 37 ± 0.5 °C with stirring (80 rpm). At set times, withdrawals (1 mL) were done and immediately replenished by the neat preheated fluid (1 mL). The sample was properly diluted with conc. HNO3 and deionized water, and the silver content was measured by using an ICP-OES. The results were expressed as an average of three experiments.
## 2.6. Microorganisms
Staphylococcus aureus (ATCC 29213) and *Staphylococcus epidermidis* (ATCC 12228) as Gram-positive bacteria, *Pseudomonas aeruginosa* (ATCC 15692) as the Gram-negative microorganism, and the yeast Candida albicans (SC5314) were used as microbial strains for evaluating the antimicrobial activity of the films described in this study. Bacteria were grown in Muller Hinton agar (MHA), whereas for Candida cells in Sabouraud agar. Oone colony of each microorganism was inoculated in the appropriate culture broth medium (Muller Hinton broth MHB or Sabouraud broth) and maintained for 24 h at 37 °C. Then, after centrifugation, the recovered microorganisms were washed twice in sterile saline and counted by spectrophotometric analysis. The suspensions were then diluted in the appropriate culture medium to the concentration required in the following assays.
## 2.7. Antimicrobial Activity
To determine the antimicrobial activity, the Kirby–Bauer disk diffusion test was performed, and the Clinical Laboratory Standards directions were followed. The zone of inhibition (ZOI) was evaluated according to the method previously described [27] with some modifications. Microorganism suspensions were washed in sterile phosphate buffer, and cell concentration was measured by spectrophotometry (600 nm). Microbial cells (1 × 108 per mL) were uniformly sown on MHA or SDA plates. Film samples (6 mm diameter disks) were sterilized by UV and placed on the surface of the MHA or SDA plates. Then, disks were hydrated with 20 μL sterile water and finally incubated (37 °C, 24 h). Film β0CaCl2 was used as a negative control, whereas the positive control was constituted by disks containing gentamicin (30 µg). ZOI was calculated by measuring, with a metric ruler, the diameter of the clear zone around the disks. Data were expressed in millimeters (mm) as mean ± standard deviation (SD) of separated experiments ($$n = 3$$).
## 2.8. Antibiofilm Activity
The antibiofilm activity was performed in an in vitro model of static biofilm assay as previously described and properly modified [28]. The test was conducted in a 96-well microtiter plate. Bacteria were seeded on MHB medium with Candida albicans in Sabouraud broth and grown overnight at 37 °C. Then, the organisms are diluted in $2\%$ sucrose MHB until a concentration of 106–107 cells/mL was obtained. Using a 96-well flat-bottomed polystyrene plate, 200 µL of suspension were inoculated in the presence of alginate-based films. Gentamicin (2.5 μg/mL) and fluconazole (5 µg/mL) were used as positive controls for bacteria and Candida albicans, respectively. After incubation for 24 h at 37 °C, biofilms in each well were washed twice with sterile water (200 μL) and dried for 45 min. Staining was carried on by adding $0.4\%$ crystal violet (100 μL) to each well for 30–45 min. Biofilms were then washed with water for four times, and crystal violet was dissolved in $95\%$ ethanol (200 μL) for 45 min. Absorbance of crystal violet (570 nm) was measured on a microplate reader (Tecan). The antibiofilm activity was calculated by comparison of the absorbance values of the biofilm obtained after treatment with film versus control biofilms. The results were expressed as mean ± SD of the absorbance values of two individual experiments performed in triplicate ($$n = 6$$).
## 2.9. Cytotoxicity
To determine cytotoxicity, the cell ATP level was measured by ViaLight® Plus Kit (Lonza, Milan, Italy). This specific kit allows the bioluminescence measurement of the amount of ATP present in metabolically active cells. Human dermis fibroblasts (HuDe) and human skin keratinocytes (NCTC2544) were used to test cytotoxicity of sterilized UV light films. The cells were grown to confluence in RPMI 1640 medium supplemented with streptomycin 10 μg/mL, 10,000 units penicillin, and $10\%$ heat-inactivated fetal calf serum for 18 h.
Monolayer cells were treated with films for 24 h at 37 °C, and then, plates were allowed to cool at room temperature for 10 min. Successively, the cell lysis reagent was added to each well to extract ATP from the cells and allowed to act for 15 min. Finally, the AMR Plus (ATP Monitoring Reagent Plus) was added, and after 2 more min, the luminescence was read by a TECAN microplate luminometer. Results are expressed as relative light units (RLU).
## 3.1. Film Preparation and Characterization
Initially, sodium alginate films containing silver nitrate (film β1 and film β2) and neat sodium alginate (film β0) were prepared (Table 1, not-gelled films). The preparation of these sodium alginate films was performed by adding glycerin as a plasticizer agent. Glycerin, in fact, is reported to act as a plasticizer for improving alginate films physical properties [29,30,31]. These films were prepared according to our previous experience, which, based on macroscopic observations of flexibility and smoothness, suggested the proper alginate/glycerin ratio was $\frac{2}{1}$ [6]. Then, the obtained films β0, β1, and β2 were dipped in a CaCl2 solution able to simultaneously induce alginate gelation by the divalent cation Ca2+ and the formation of AgCl nanoparticles by the presence of chloride anions. Thus, to determine the best CaCl2 concentration able to induce the formation of homogeneous and uniformly distributed nanoparticles, sodium alginate films were immersed in different CaCl2 solutions ($0.8\%$, $1.2\%$, and 1.6 w/w). As observed in SEM micrographs (Figure S1), films prepared by dipping in a $0.8\%$ CaCl2 solution showed the presence of bulky AgCl nanoparticles. Similar results were obtained when a $1.2\%$ CaCl2 solution was used. By immersion in $1.6\%$ w/w CaCl2 solution, films containing small and fairly uniform distributed nanoparticles were obtained, as shown in Figure 1. For comparison, a micrograph of film β0CaCl2 is reported in Figure S2. It can be noted that most of the inorganic nanoparticles are less than 100 nm in size. It can be supposed that the higher concentration of chloride anions in $1.6\%$ CaCl2 solution allows a rapid and efficient AgCl nucleation limiting the crystal growth. Moreover, a higher Ca2+ concentration inducing a faster gelation of alginate [32] can reduce the diffusion of silver ions and consequent AgCl particle growth. In Table 1, the thickness of films before and after gelation is reported, and an increase of film thickness can be observed following the immersion in CaCl2 as reported by Russo et al. and Li et al. [ 32,33]. This can be due to the water absorption during crosslinking and to the stabilization of the conformation of the swollen state following gelation. In all films, the presence of silver caused a decrease in film thickness. Probably, silver-based nanoparticles induced a water absorption decrease (as proved hereafter), and thus, a minor swollen state was obtained.
The XRD patterns of films β1CaCl2 and β2CaCl2 are shown in Figure 2. It is possible to observe, beyond the crystallization of AgCl salt, the presence of metallic Ag nanoparticles. In particular, XRD patterns showed main peaks at 2θ: 27.8°, 32.2°, 46.3°, 54.70°, and 57.6°, which are characteristic of AgCl (COD number: 9011666), whereas peaks at 38.3°, 44.2°, and 65.1°, which corresponded to [111], [200], and [220] planes of face-centered cubic (fcc) crystal structure of metallic silver (COD number: 9011608), indicate the presence of Ag nanoparticles [34].
The differences in the peak intensities are due to the different amounts of silver in the final alginate films. The dimensions of AgCl nanoparticles were determined by applying the Scherrer equation to [111] and [200] and Bragg reflections at 2θ° 27.8 and 32.2 of the AgCl cubic phase, considering the correction for the instrumental line width broadening. The X-ray diffractograms were fitted by using a pseudo-Voigt profile function to obtain the FWHM related to [111] and [200] peaks. Based on this calculation, silver chloride nanoparticles obtained in β1CaCl2 and β2CaCl2 have a size of 65 and 25 nm, respectively. The dimensions of AgCl nanoparticles as from Scherrer equation were confronted with those showing the SEM images, and as can be noted, the nanoparticles sizes were larger than those estimated by XRD and distributed in a large dimensional range.
Figure 3 show the UV–vis reflectance spectra of films β1CaCl2 and β2CaCl2 together with those recorded on β0 and β0CaCl2 samples for comparison. Both spectra of the samples loaded with AgNO3 had a band centered on the 420–430 nm range, which is absent in the silver-free films (β0 and β0CaCl2); this band is due to the Ag nanoparticles surface plasmon resonance [9,35]. In both cases, the bands present an asymmetric profile likely due to the formation of an Ag-AgCl nanostructure [7].
From XRPD and UV–vis analyses, the presence of Ag/AgCl nanoparticles was proven, and thus, it can be asserted that nanoparticles can be obtained even in the absence of ammonia [15] and that the alginate gelation, with consequent reduction of alginate chain mobility, prevented agglomeration of AgCl nanoparticles.
## 3.2. Water Absorption
Water absorption capacity is an important property of a wound-dressing material. In fact, good hydration properties allow the absorption of exudates, preventing maceration and providing a moist environment [36]. As shown in Figure 4, all films exhibited good and rapid hydration, and the highest absorption percentage was reached within 2 h. The percentage of hydration was slightly higher for the control film β0CaCl2 (consisting of neat calcium alginate), and the presence of silver induced only a low decrease of hydration, with no differences between film β1CaCl2 and β2CaCl2.
After drying (24 h at 40 °C), the films were weighed to assess the weight loss. In all cases, the weight-loss percentage was very low (15.8 ± $2\%$ for film β0CaCl2, 18.2 ± $1.7\%$ film β1CaCl2, and 17.1 ± $2.3\%$ film β2CaCl2), indicating that all films after 24 h of immersion in simulated wound fluid almost completely maintained their integrity and that the presence of silver did not affect the film dissolution.
## 3.3. Antimicrobial Activity
Films antimicrobial activity was assessed by the Kirby–Bauer test. Film β0CaCl2 showed no antimicrobial activity, whereas un-gelled films β1 and β2 showed antimicrobial activity against all tested microorganisms (Figure 5). Unfortunately, it was not possible to measure the inhibition halos because these films in contact with agar medium dissolved, and the halo edges were enlarged. Films β1CaCl2 and β2CaCl2 showed antimicrobial activity against bacteria *Pseudomonas aeruginosa* and *Staphylococcus aureus* with the inhibition halos reported in Table 2, whereas in the case of Staphylococcus epidermidis, they showed antimicrobial activity in the contact areas of films with microorganisms. They showed low activity towards the yeast Candida albicans.
The antimicrobial mechanism of Ag/AgCl nanoparticles remains still unclear, and even if it is supposed that they exert their action with a mechanism similar to silver ions, some differences can be considered [37,38]. It has been hypothesized that nanoparticles can anchor to the bacterial cell and can be internalized. Moreover, they release silver ions, which bind molecules essential for microorganism survival, such as proteins, lipids, and DNA. In addition, Ag/AgCl nanoparticles promote the generation of reactive oxygen species, which are considered to be the main products leading to bacterial apoptosis [15,19].
## 3.4. Antibiofilm Activity
Since many bacteria grow in the form of biofilms, especially in chronic wounds, the antibiofilm activity of the prepared films against P. aeruginosa, S. aureus, S. epidermidis, and C. albicans was evaluated. Biofilms were grown in static conditions in the presence of composite films. The biofilm formation was evaluated by measuring the mass of the biofilm using crystal violet staining. For the un-gelled films, it was not possible to determine the growth of the biofilm, as they rapidly solved in the culture medium.
As shown in Figure 6, all films caused a reduction of mass biofilm against all tested bacteria, showing good antibiofilm activity against Gram-negative and Gram-positive bacteria. Instead, the films showed no effect on the formation of the Candida albicans yeast biofilm.
The mechanism of antimicrobial action of silver nanoparticles is ascribed to many factors and is not yet completely understood. It is reported that the activity of silver nanoparticles with size under 10 nm is mainly due to the nanoparticles itself. In fact, small silver nanoparticles can act by adhering to the surface of bacteria, altering its permeability, and can penetrate inside the cell with consequence damage to different targets. For nanoparticles with larger size, the main mechanism is due to silver ions release [39]. From the above-reported characterization, nanoparticles size resulted higher than 10 nm; thus, with the aim of evaluating silver ion release from films, an in vitro release test was performed on film β2CaCl2, which was chosen as a model. Silver release was carried out in simulated wound fluid up to 72 h. The test could not be performed for un-gelled films, as they dissolved in the fluid. The silver release profile showed an initial burst effect, and then, a gradual and prolonged silver release was observed, and a plateau was reached after 50 h (Figure 7). The release profile can be affected by the fluid composition, which contains chloride anions, and in fact, the plateau was observed when the condition of saturation was reached (AgCl solubility 1.9 mg/L) [40]. Silver ions release is the consequence of many steps: first, in the presence of water, gradual alginate hydration occurs, and the water penetration induces silver ions solubilization from surface of metallic silver/AgCl nanoparticles, and successively, ions diffuse across the hydrated hydrogel and are released. In the case of silver metallic nanoparticles, silver release is preceded by its oxidation. Moreover, AgCl, due to its very low solubility, ensures a slow release of silver ions [12,13,18].
In order to investigate the relationship between swelling and silver release, regression analysis of silver release for 24 h and water absorption data were applied. A correlation with $R = 0.93$ (Figure S3) was obtained, meaning that the silver release is correlated to the water adsorption, but other factors also come into play. Among the main models used to describe a drug-release profile, the one that best describes the release of silver from film β2CaCl2, was the Korsmeyer–Peppas model [41]. It is described by the following equation: Qt/Q0 = ktn, where *Qt is* the drug amount released at the time t, Q0 is the drug amount at the beginning, and n is the diffusional release exponent. A correlation coefficient of 0.98 was obtained for $$n = 0$.1$, elaborating the release data in the time range of 1–48 h (Figure S3).
## 3.5. Cytotoxicity Evaluation
The evaluation of the film cytotoxicity was performed by testing the viability of two human dermal fibroblast (HuDe) and keratinocyte (NCTC2544) cell lines for 24 h. Results are reported in Figure 8. The un-gelled films were toxic in both cell lines. Unlike this, film β1CaCl2 and film β2CaCl2 were always significantly less toxic than the corresponding films containing silver nitrate. In particular, film β1CaCl2 and film β2CaCl2 showed very low cytotoxicity towards fibroblasts. The low cytotoxicity of films is a remarkable result, as the use of silver nanoparticles is limited by the narrow window between silver ions and silver nanoparticles as concerns cytotoxicity against different kinds of eukaryotic cells and bacteria [42]. Cytotoxicity mechanisms of silver nanoparticles both against eukaryotic cells and bacteria or fungi is due to many factors, and among them is silver ions release, which depends on many parameters such as size and shape of nanoparticles. Moreover, the ions present in the surrounding environment can also affect the ion release. Other mechanisms of cytotoxicity are the generation of ROS and free radicals [43]. It can be hypothesized that un-gelled films, which rapidly solve in presence of water, induce a toxic silver concentration, whereas alginate gelation decreases the polymer solubility and thus stabilizes the films, preventing the rapid achievement of high silver concentrations. As concerns the use of silver or AgCl nanoparticles as antimicrobial agents in wound dressings, no clear conclusions can be drawn. Tran et al. [ 16] observed that composites containing AgCl nanoparticles showed to possess less antimicrobial activity than composites containing Ag0 nanoparticles but resulted as more cytotoxic against fibroblasts and keratinocytes. In other papers [10,11,12,14], Ag/AgCl nanoparticles are described, and Kubasceva [11] observed that hybrid (AgCl/Ag)nanoparticle/diatomite composites with a dominant content of AgCl nanoparticles showed higher antimicrobial activity, but no cytotoxicity studies were performed. Boccalon et al. [ 14] reported that the susceptibility of the bacterial strains toward Ag nanoparticles is lower than that of Ag/AgCl. Vosmanska et al. [ 44] prepared AgCl nanoparticles on cellulose dressing, which revealed the same antimicrobial activity against both *Staphylococcus epidermidis* and Escherichia coli, but in this paper also, no cytotoxic activity was investigated. Finally, Zhou et al. [ 19] obtained Ag/AgCl nanoparticles coated on graphene with high antimicrobial activity and attributed the good antimicrobial performance to the oxidative radical generation by the Ag/AgCl-graphene. The main problem in drawing clear conclusions on the different effects of Ag0, AgCl, and Ag/AgCl nanoparticles is due to the differences of the papers as concerns the nanoparticles’ nature, their size and shape, the way of reporting antimicrobial and cytotoxic results (for example, MIC or zone of inhibition for antimicrobial activity), and the used bacteria strains, as just previously referred [9].
## 4. Conclusions
Alginate films containing Ag/AgCl nanoparticles were obtained according to a sustainable procedure that does not involve the use of organic solvent and additional reagents, such as capping agents, as alginate itself performs this function. The immersion of previously prepared AgNO3 alginate films in a CaCl2 solution induces in one step both the alginate gelation and the AgCl nanoparticles formation. Films containing AgCl nanoparticles uniformly distributed were obtained. Moreover, the presence of metallic Ag was detected as well, due to the reducing action of alginate. The composite films showed good water absorption capacity, good antimicrobial and antibiofilm activities towards the tested microorganisms, and low toxicity for keratinocytes and fibroblasts. Un-gelled alginate films containing silver nitrate, which were prepared for comparison, showed higher cytotoxicity against both tested human cells. The lower cytotoxicity could be due to the prolonged silver ion release from Ag/AgCl nanocomposites films, which prevents the achievement of cytotoxic silver concentrations in the surrounding environment.
Based on these results, the proposed procedure represents a sustainable and successful approach for obtaining alginate Ag/AgCl nanoparticles composite films able to prevent microbial colonization and biofilm formation with reduced cytotoxicity for the tissue cells.
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