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Male and female seahorses: which is which
Seahorses have two sexes. One has mobile gametes, the other gives live birth. I imagine that a biologist who discovered the seahorse would initially call the first "male" and the second "female".
That is not the case: for some reason (why?), the ones with the mobile gametes are called "female", and the ones that give live birth from a pouch are called "male". I would like to know why.

I don't think the eggs transferred are mobile by themselves...

Is that what happened? They looked at the gametes that are transferred from one sex to the other under a microscope, and noticed "these are not mobile, therefore they are eggs, and the sex that emits them is female"?

I would imagine they compared the male and female ones, perhaps morphologically but more likely by chromosome spreads and determined that way. Male has the heterogenous chromosome (XY in our case, other species have other genetics), but I don't know what that might be for seahorses.

Of course its arguable that our sperm need some transfer too, but they are mobile once ejaculated.

One has mobile gametes, the other gives live birth - this is not true. In reality it is one has mobile gametes and gives live birth while the other does not have mobile gametes but does not give birth (they lay eggs instead - inside the males - inside the ones with mobile gametes)

I'm no expert at all but my first thought was: In any species the sex that produces egg cells is considered the female. Is this not the case here too?

@Ivo - Yes. That's the case here. The confusion comes from thinking that the eggs are mobile - they're not. Like any other species it is the sperm that's mobile. The eggs happen to be ejaculated/laid and the sperm is not ejaculated.

@bob1 Many species use the "ZW" sex-determination system, where the female has the heterogenous chromosome. But that really just begs the question: chromosomes are named Z and W rather than X and Y because they occur heterogenously in females, not because of any feature of the chromosomes themselves, so you need a prior definition of "female" to make that determination.

Please provide links to papers describing these different gametes, otherwise it is not possible for me (and others) to analyse the situation. 2. The general assumption in the question and comments is that the designation of gametes as male or female is made on the basis of “mobility”. However a recent(ish) question about giant sperm in Drosophila professed that the “generally accepted view” is that “size” is the determinant (the bigger is the female). I got severely squashed when I expressed surprise at this, but nobody could provide an  original reference to this idea.  And mobility?

Seahorses are fish. Most fishes use external fertilization to reproduce (there are certainly exceptions, though), so there's not really any aspect of "giving birth" to sex definitions (that's a mammalian bias perhaps): both sexes release gametes externally. One or both or neither fish may guard the fertilized eggs; if one is on guard, it's usually the male that does so, which isn't too different than the male seahorse's behavior, which is just more extreme.
Usually it's gamete size that is used to identify male versus female sex; female seahorses have larger gametes they include the yolk that will feed the developing embryo. Male gametes are also typically mobile. Both of these fit with seahorses: even though the female deposits her eggs in a male pouch, the eggs don't themselves move, any more than eggs move when a female fish simply releases gametes for external fertilization.
Wilson, A. B., Ahnesjo, I., Vincent, A. C., & Meyer, A. (2003). The dynamics of male brooding, mating patterns, and sex roles in pipefishes and seahorses (family Syngnathidae). Evolution, 57(6), 1374-1386.


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Do we know abiogenesis only happened once on earth?
Do we know that abiogenesis happened only once on earth? Do biologists know that all life originates from a common ancestor?
If so, is this considered a sign that abiogenesis is rare even in under generous conditions like a habitable zone?

No, we don't. Abiogenesis has never been observed, ever, so it must be rare. There are a lot of questions about this; searching the tag will get you plenty to chew on. :)

Does this answer your question? Is abiogenesis possible today? (Just one example of many.)

Also for abiogenesis to be noticed, it will have to evolve  completely different structures and metabolic pathways (non-carbon based or non-DNA,non-RNA based) to avoid competition for resources. Otherwise it might also be dismissed  as  a result of general evolution.

we have some evidence all extant life has the same origin due to codon mapping, but there could easily have been several competing life linages on the early earth. indeed all life extant life could come from the merging of different simple lineages.

We don't even know IF abiogenesis happened on Earth, let alone how many times. Most evidence suggests that all Extant life on the planet evolved from a universal common ancestor, but that isn't necessarily evidence that abiogenesis is rare. For one thing, if multiple branches of life arose independently, they would likely still utilize similar resources, thus competitive exclusion could take place. And what counts as rare may also be subjective. What's rare on the scale of recorded history may not be so rare on cosmic timescales.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

sort: votes


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Why do some insects which are able to fly unusually do it when they are threatened?
I have killed cockroaches and beetles several times in my house. Sometimes I miss the insects and they run fast, but they don't fly most of the time. Even when I touch a beetle it just continues its walking and don't flies. It just produces a bad smell.
Why don't these insects fly when they are threatened?

Bad smell sounds (smells) like a "stink bug"/shield beetle- they have defenses that don't necessitate flying. As for other beetles, it all depends on the type; some will, some won't.

But flying is fleeing. It's also a defense.

Yes, but if the beetle can get away with not flying (because they aren't great at it) and use a repellent, in the case of stink bugs, instead, they might use that. Cockroaches are very good at hiding and very good runners, but poor flyers. Them having their wings out means it is harder for them to hide.

Just a guess. how do they know what's a predator and what's another beetle? they specialize in hiding.  natural predators are the same sizes or a bit bigger, so they are very fast, and flying away is slower than running, i.e. for beetles, perhaps. also consider that these animals almost always live in leaves or grass or natural scenarios where running a short distance usually means invisibility under a leaf or in a chaotic wildlife substrate. Also consider that they may get disturbed fairly often by other beetles, spiders, cockroaches and flying takes a lot of energy.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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What does motor writing mean in neurology?
In Zoltan Torey's The Conscious Mind, the author discusses the emerge of language:

Adding weight to the thesis of the stage-wise evolution of language, Bickerton (1995) noted that
the linguistic history of the hominid line appears … as a two-stage process: first a stage in which there was a lexicon without syntax, then a stage in which infinitely productive mechanisms emerged to create syntax as we know it. If this conclusion is correct, it is a waste of time to look for antecedents of syntax in ancestral species, as syntax could not have come into existence until there was a sizeable vocabulary whose units could be organized into complex structures.
… There seems no feasible alternative to concluding that syntax has a specific neural substrate, laid down at some stage prior to the last fifty millennia, most probably at the time when anatomically modern humans emerged as a separate species.
Bickerton’s description is spot on, though it does not say what the “infinitely productive mechanisms” and the “specific neural substrate” for generating syntax actually were. To find these, we turn to the motor writing of the speech areas in the human infant’s neuroplastic brain, the break- through that gave it the leverage to handle its lexicon and generate syntax when, through feature-detection, it acquired qualifiers and function words.

From the beginning of the book, the author has referred to this breakthrough as "the speech areas acquiring a motor-arm, which is the language. Now he says "motor writing", but I can't get the exact meaning of "writing" here!

There's no specific meaning to this term. Probably a typo for motor wiring.


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What gene does the RAN-2 antigen correspond to?
In many papers, immunopanning is performed against RAN-2, which stand for "rat neural antigen-2" (some examples). It seems to have been first described by Bartlett and colleagues in 1981 and to be a cell surface protein of astrocytes.
Apart from a 1998 report that it is a is "a GPI-anchored form of ceruloplasmin", I can't find any information about what gene or protein Ran-2 corresponds to. Is this known?
Searching on standard websites (eg here, there or there) do not yield relevant results.


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What animal does this foot skeleton belong to?
I found an articulated foot skeleton. Sun bleached. What animal is this likely from?

Where was it found (in the world; there are people here from many different countries), what sort of environment (hill, beach, river etc.) and some sense of size will help with ID

Please see the species ID guidelines to improve your post: https://biology.stackexchange.com/tags/species-identification/info


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Predicting the optimal sample size for a nested experiment
I need to test the effects of different treatments on plants and I would like to know the optimal sample size (number of plants that I need to sample). The variable I need to measure is the average number of insects present in a single plant. In the experiment, I have 3 main treatments and, in each treatment, I have 2 sub-treatments. The information I can provide are the following:

Average number of larvae per plant: ranging between 0.03 and 0.1
Standard deviation: ranging between 0.09 and 0.28
The desired $Z$-score is 1.96
I have no idea about the minimum detectable effect size but I can guess it could be 10%

Looking online, I have found different formulas that return different results. The first formula was:
$$n_1=\frac{(\sigma_1^2+\sigma_2^2/K)(z_{1-\alpha/2}+z_{1-\beta})^2}{\Delta^2},$$
where:

$\Delta =|\mu_2-\mu_1|$ is the absolute difference between two means,
$\sigma_1$, $\sigma_2$ are variances of mean #1 and #2,
$n_1$, $n_2$ are sample sizes for group #1 and #2,
$\alpha$ is the probability of type I error (usually 0.05),
$\beta$ is the probability of type II error (usually 0.2),
$z$ is the critical $Z$ value for a given $\alpha$ or $\beta$, and
$k$ is the ratio of sample size for group #2 to group #1.

With this formula, comparing these two means (0.03 and 0.09) and using a standard deviation of 0.09, I am getting $n = 35$ for each treatment.
A different formula I found is:
$$n=\frac{2\sigma^2 Z^2}{d^2},$$
where

$n$ is the required sample size per sub-treatment group,
$\sigma^2$ is the estimated variance,
$Z$ is the $Z$ score, and
$d$ is the minimum detectable effect size.

With this formula, using a mean of 0.03 and a standard deviation of 0.09, I am getting $n > 6000$ for each treatment.
Could you suggest me a simple and efficient formula for calculating the sample size?

Power analyses depend on 4 numbers: alpha (false-positive threshold for significance testing), power (probability to reject the null hypothesis given all the other parameters), effect size (how big is the difference between groups, relative to the variability), and sample size.
Given 3 of these numbers, you can calculate the 4th.
If you want to calculate the sample size, you need to know what effect size you are designing your experiment to detect. This isn't optional or esoteric, it's absolutely critical to the power analysis. The effect size most often used for "t-tests" and similar is the ratio of the difference in means to the standard deviation. There are alternative forms if you expect the standard deviation to be different between groups.
You also need to choose your alpha and desired power. You haven't mentioned either of these in your post. There are some typical conventions, like alpha = 0.05, and power is usually at a minimum 0.80, though many would argue it should be higher, at least 0.90.
In your first calculation, you've set the difference in means to 0.06 and the standard deviation to be 0.09, so your effect size is 0.06/0.09 = about 0.67. This is often considered a moderate to large effect size.
In your second calculation, I don't know what exactly you've done, because you haven't written out any of your numbers, but I'm guessing this is where you've used your "10%" number. 10% of what, though? An effect size is not a percentage, it's a ratio. It can't be "10%". But if you've set it to 0.1, or 0.006, or something like that, this is a much smaller effect, and your power analysis should tell you that you need a much larger sample to detect this effect. Seems like that's what you got.
I'd recommend using a tool like G*Power to calculate sample size, but right now you are very lost and not understanding what you are undertaking, so I would really recommend to step back and sit down to read extensively about what power analysis is and means. This is not just a formula to plug in, this is critical to designing your experiment. Open up a statistics text book and don't move forward until you understand.
My preferred way to do power analysis is with simulation, because simulation lets you see what a power analysis is really doing and lets you understand more about your data. To simulate a power analysis, you generate synthetic data under the assumptions you have, like means and standard deviation for your different groups, then you actually do a statistical test on these data. Use your desired alpha threshold, run many many independent simulations (1000 to 100000 times), and note how often your p-value is smaller than this threshold. That's your power. You can change the sample size and see how the resulting power changes.
While running simulations, check whether the assumptions you've made about your data make sense! For example, if your mean is 0.03 and your standard deviation is 0.09, how often do you see negative numbers in your simulation? How often do you see non-integers in your simulation? Do negative numbers or non-integers make sense for a count of insects? No? Aha! Then you are violating some assumptions of the tests you're doing, and you probably shouldn't be doing t-tests with means and standard deviations, but rather using a statistical model that deals with count data.
If this all seems too complicated, it's time to consult with a statistician.


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Largest crinoid species
On the wikipedia page of crinoids (sea lilies and feather stars), one can find the following statement in the paragraph "Morphology":

[...] and fossil species are known with 20 m (66 ft) stems, the largest recorded crinoid having a stem 40 m (130 ft) in length.

They also give some sources for this, but they also just mention the fact without specifying the fossil/species. When searching on the internet about the largest known crinoid species, one can find very often similar claims, but again without any source (probably coming from wikipedia in the end). In general, I am slightly doubting the statement about 40m of length: Statements about size of large organisms are very often exaggerated. For example, in popular science books, one can often find lengths for the giant squid (Architeuthis dux) of about 20m, while the truely largest individual every measured with scientific methods was probably "only" about 12m (see the paper here for example), which is of course still pretty impressive. In the words of S. J. Gould: "Our strong and biased predilection for focusing on extremes generates all manner of deep and stubborn errors".
Anyway, I would like to know how large/tall crinoids can get by knowing how large the largest species ever to be found was (preferably with a scientific resource supporting the claim). On my internet research, I found the species Seirocrinus subangularis (Miller, 1821) from the early Jurassic with stem lengths of about 20m, although also here the statements about size vary a lot from 15 to 25m and I am not able to find a precise, confirmed, statement.

Woah I understand your frustration. The web info on that is all confused without science references. a 40m fossil is very unlikely in one piece,  the biggest fossil ever uncovered, and if it was on a slab of rock somewhere, it would be famous among geologists and would have been in old newspapers as a local and great discovery. 1820's fossil id's are no accurate by today's standards, and if the fossil is gone, the reference is vague. I found an 18 meter claim of reference here: https://libraries.ou.edu/content/crinoid ... I am treating the wiki figure like complete nonsense.

I recommend the big guns on this... fossil forums is the biggest fossil forum full of serious, impassioned paleo academics. And Reddit is pretty specialized, too. Because this is a serious shortcoming in the web science references, and people are copying that wiki claim of 40 meters all over the web.

@bandybabboon thanks a lot! Yes, indeed, a 40m fossil is really unlikely. I will check out the fossil forum and keep this post here up to date in case I get an answer there.

Probably 40ft not 40m
Without a species name any claim like this is dubious. The wiki quote is not from a primary source but a fluff book which makes it even more questionable.
Unfortunately you are running into a issue were a lot of early paleontology work has not been digitized yet. the specimen in question is from 1906 so finding a digital copy to confirm is basically impossible. So we can only rely on the questionable sourcing to determine how accurate it is.
My best guess is this is a misquote on a real specimen.
geologypage.com has article about largest known crinoid specimens.

Taxocrinus saratogensis One of the largest fossil crinoids ever
discovered was found in the state of Indiana in the United States. The
crinoid, which belongs to the species Taxocrinus saratogensis, was
discovered in 1906 by a team of geologists led by John M. Clarke. The
specimen is estimated to be around 350 million years old and is
believed to have lived during the Devonian period. The crinoid is
incredibly large, with a stem measuring more than 40 feet in length
and a crown that measures more than 10 feet in diameter. The entire
specimen is estimated to have weighed more than 10 tons when it was
alive. This makes it one of the largest fossil crinoids ever
discovered.


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Question regarding statistical testing for fractions in low N paired samples
I am unsure about how to analyze some data of my PhD project and could use some input. I am analyzing data from a Phase I clinical trial where we have scRNAseq + Histology of paired PRE and POST biopsies. However, as the clinical trial was stopped early due to outside reasons (adverse effects in a different trial in a different condition), I am left with "only" 5 paired samples. Now, I want to compare fractions (e.g. Number of CD8+ T cells/mm2, or %of stromal coverage, or % of total population) between PRE and POST to see where the treatment induced changes. In some cases, it seems quite clear as there is a strong difference, however I don't know which statistical test to apply.
Normally I would say the Wilcoxon matched-pairs signed rank test, since I don't think I can assume normality for fractions. However, with 5 paired samples, the power is too low to reach significance threshold (lowest attainable p value with wilcoxon with N=5 is 0.0625), which in principle I don't care about since I think there is still a pretty strong message when I see the same effect in scRNAseq and histology, but I am worried that it will make submission more difficult.
I have also seen people use the paired t-test for these kinds of fractions in the literature in good journals (e.g. Cell), but I think that would be cheating (but I'm hoping to be wrong here - please tell me).
If you have other ideas, feel free to let me know. If there's some special test for low N paired samples not assuming normality that is not available in Graphpad, I am fine with R as well.
Thank you all!!

You don't have enough data for traditional statistical hypothesis testing. No statistical test will get you around this fact.
I'd recommend just reporting the raw data when there are so few numbers. Let your audience decide what they want to believe or not regarding the data.

Thank you, I guess I needed a bit of tough love so to speak. I had hoped that maybe there's some more advanced statistics that can make sense of the situation but I guess not.


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Inheritance of child behavior based on daily life experiences of the parent
Our brain is a large network of neurons connected with each other.Our daily experiences change how  our neurons are connected.Some experiences create better connections between two neurons A and B and worse connections betweens neurons A and C.When someone makes children of his own ,does the experiences in the life of the parent influence the behavior of his child for example if the parent has experienced some very traumatic situations will the child be more distant or less sociable?

Children inherit DNA from their parents, which in turn was inherited by their parents from their grandparents, and so on. Only modifications to the DNA in the germ-line cells (those producing eggs and sperm) are heritable; changes in brain cells are not heritable, because those do not involve the DNA of the eggs and sperm.
Everything else that influences a child is environmental. The nature-nurture debate involves discussion of how much genetics versus experience influences development of different traits and characteristics.
Part of the difficulty in measuring the relative contribution of genes and environment is that parents are often important contributors to the environment as well as genetics of their children. Environment starts in the womb, so some of the mother's behaviors and experiences can influence the developing fetus. After birth, a child will continue to be influenced by their environment. Their parents' presence or absence will be part of this environment.
A child will only be influenced by traumatic experiences of their parents to the degree that those experiences influence the parent's behavior around the child.

Do you feel that scientists who seem to have demonstrated generational epigenic modification are in error? E.g. mice and cherry blossoms.

@anongoodnurse You'll note the article you link has quite a bit of skepticism, too; I certainly believe epigenetic inheritance exists, but this is really just an extension of the genome beyond nucleotide sequence. The examples given like famine in the Netherlands involve exposure to a stressed maternal environment.

I agree there is uncertainty (I wouldn't say there was quite a bit), but the evidence is compelling; in vitro fertilization still produced mice who, without ever meeting their parents, were afraid of the scent. "A child will only be influenced by traumatic experiences of their parents to the degree that those experiences influence the parent's behavior around the child." this statement does not support generational epigenetic modification...

... In that respect, the child may well behave differently "if the parent has experienced some very traumatic situations..." I don't say it's highly likely, but it's not impossible.


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How should I analyze proportional community data, in respect to habitat variables?
I want to analyze how the proportions of groups of species in a biological community correlated to habitat variables. I have 6 functional groups, defined by their similar traits, and I want to know how their proportions vary dependent upon changes in habitat size, and time since the changes started to occur (e.g. ramp disturbances).
I basically want to be able to say, "Group A species contributed more to the community makeup / function as habitat decreased. Group B species decreased in proportion, but not nearly as fast as Group C, which were extirpated by the time only 20% of the habitat remained" with some kind of stats to back it up.
I also monitored the communities as they recovered from the distrubance, and would similarly like to make inferences about which groups were contributing more early on vs. late stages recovery (e.g. could species with D-group traits be better at reestablishing?)
I don't think using raw abundance is appropriate because (generally) all groups decrease in abundance as habitat decreases, but some groups actually dramatically increase in proportion of the community, and thus would contribute more to the ecosystem services etc. etc.
Does anyone know how I should analyze this data? I have thought about using Spearman correlations to answer broadly if the groups do correlate with habitat changes, but this cant really tell me if one group is increasing or decreasing at a faster rate.
Thank you for the help!

What form are your observations in? Counts? Are they somewhat sporadic (like sightings of animals) or more systematic (like counts of plants within a grid)? How are observations structured over time and space? Are you measuring multiple habitats, or a single habitat over time?

I would say they're more sporadic, but we tried to make it as systematic as possible so samples could be compared. It was a timed-search method, using kick netting in streams to catch macroinvertebrates. We got roughly 1,000 - 10,000 individuals in each sample, and about 70ish species in total. Which were grouped via traits into those 6 groups.

Interesting... I'd highly recommend collaborating with a statistician with some experience in your domain. Proportions don't seem quite right, because it's probably not meaningful to consider individuals as equivalent/exchangeable, but you probably need some sort of control for the "sample size". I thought I'd have some suggestions, but I'm afraid this will quickly get beyond the scope of a StackExchange answer.

Sound like you want to do some compositional analyses of relative abundance data. It's a common approach used in microbial community analysis based on metagenomic sequencing data, but that's because the absolute count data is an experimental artifact from the sequencing methods and not necessarily reflective of absolute abundances in the samples.

Highly recommended read: McCune, B. and Grace, J.B., 2002. Analysis of Ecological Communities. MjM Software Design: Gleneden Beach. ISBN 0-9721290-0-6. 300 pp.. You might find a lot of interest in distance-based analyses (see "bray-curtis distance" for your abundance data), ordinations, and literally a whole host of multivariate analyses. Keeping track of temporal autocorrelations will also likely play an important role in your analyses.

I don't have complete grasp of the scope of your study/questions based on what you've presented here , and -- perhaps I'll be honest -- that type of statistical consulting advice is outside the scope of this site. If you already knew what you wanted to do or could more narrowly describe your question/analysis, some of us would certainly try to help. But I think at this stage -- especially given the complexity of your system -- I, like Bryan, recommend speaking more thoroughly with a dedicated statistician to ensure you're adequately covering all your bases and making the best decision.

Also, you're essentially asking multiple questions that each would require its own analysis approach. You might find a role of ordinations, mantel tests, structural equation modeling, etc for your 1st question, while MRPPs (multi-response permutation procedures), partial mantel tests, and mixed-effects models might play roles in other parts of your analysis. I guess I'll end by saying that your post is currently too broad and underdeveloped for our site. But again, I hope some of these comments steer you in the right direction. Read McCune & Grace (2002) and talk to a statistician. Good luck!


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How to deal with sample size and replicates
I need to perform several replicates of an experiment, say I have 3 treatments and 4 replicates. After performing the calculation of the sample size, I get n = 100 samples needed. This means that for each replicate I need 100 samples or can I split the samples among my replicates (i.e., 25 samples per replicate)?
Thank you.

Usually, if you want to draw conclusions about a population, we use representative samples which are adequately sized (sample size) and reflects all the features of the population. If calculations say that the sample size should be 100, we need 100 data points to make statistical arguments about the population based on these 100 data points (sample size).
You mentioned there are 4 replicates i.e. you counted 4 separate setups and so, if you divide 100 into 4 groups, each with 25 data points, you have, statistically, only 1 replicate with 100 datapoints, not 4.
Please don't forget to bring with you a pinch of salt.
Furthermore, in statistics, a rule of thumb is more the merrier.  In short if you ever get confused in situations like this, choose 100, not 25, in a manner of speaking. Of course your supervisor will wonder why his reagents don't last as long as it used to.


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Intensity of UVA needed to damage skin and cause ageing
Using a UVA/B measuring device, I was able to determine that approximately $\pu{10 μW/cm^2}$ penetrates a window even when not in direct sunlight. For reference, the intensity of direct sunlight without any glass is approximately $\pu{6000 μW/cm^2}$ UVA (this UV component represents ~6% of all solar energy from direct sunlight that reaches the ground on a clear day) and $\pu{50 μW/cm^2}$ of UVA penetrates the double pane glass window in direct sunlight.
If a person were to sit in front of this window most of the day (about 8 hours). Assuming indirect sunlight, is this $\pu{10 μW/cm^2}$ dose hitting their face going to cause significant skin damage over time?

Welcome to the Biology Stack. Please take a [tour] and visit the [help] for more information on this stack and how we work. Please note that personal medical advice is off-topic here, which this post leans towards (as in we'd need to know your race and other personal information to make an informed answer; so that would be a clear breach of rules). Having said that, I can see a good question here, that isn't medical advice if you depersonalize it.

@bob1 You're right I hadn't taken into consideration different races would have different skin types and different susceptibility to skin damage. Though an expert in this field should be able to provide generalized thresholds for different skin types. Hopefully...

I've depersonalized it and added some specifics - like duration of exposure, without which this is unanswerable. If you disagree with the changes feel free to edit some more or revert, but be aware it might get closed for medical advice.


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Ladybug: Number of spots
I'm interested in Ladybugs. I read a lot about the number of spots of ladybugs. The number seems to be between 0 and 24, but as far as I can see, not every number in between exist. Up to now, I found ladybugs species with 0, 2, 4, 5, 7, 10, 11, 13, 14, 16, 17, 18, 19, 22 and 24 spots. Do more exist? Is there a scientifique site in the net with exactly that subject?
Thanks for your answers!
Ladybug


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Examples of mechanisms of metabolic trapping inside cells that create concentration gradient
I am looking for examples in biology in which a metabolite that can diffuse freely across a cell membrane (through passive diffusion), once inside, gets modified to a form that cannot diffuse back anymore. The metabolite, in this way, gets effectively trapped inside and this can lead to a concentration gradient inside vs. outside.
One such example is the one of glucose. Glucose can penetrate cells through facilitated diffusion. Once inside, it gets phosphorylated to G6P which cannot diffuse out anymore.
The phosphorylation is powered by ATP. At the end, thanks to this mechanism, one can have in principle [Gluc]_blood < [Gluc]_cell + [G6P]_cell.
However, I didn't find references measuring higher glucose concentration in the cytoplasm compared to the one in the blood. Do you know any?
Any additional example in which the same happens would be appreciated.

Welcome to SE Biology. Please finish reading the [Tour]. A point of clarification, are you asking for the concentration of free glucose within cells? There will be literally hundreds of papers from the 60s onwards with such values. Have you searched?

Concentration of free glucose + phosphorylated glucose inside the cell.
That value would be nice to have and to compare with the glucose concentration in the blood. I didn't find any paper measuring this value.


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Ubiquitous overexpression line of a gene expressed higher gene expression in leaf but not in seeds
I tried to make ubiquitous overexpression lines of a gene using a constitutive promoter vector in plant. I got multiple regenerated plants through tissue cultures.
At T0, T1, T2 leaves tissues, the gene was highly overexpressed with different levels (5-more than 20 fold change against background) in all the plants. However, in seed tissues, some of the lines didn't show any overexpression and other lines had only slight overexpression (1.5 fold change).
Would it be possible? Or, Does this mean the construct has some issues?


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Why is the ordinary cardiac muscle’s target value of the action potential 0mV?
Why do some excitable cells have a target of 0mV for the action potential, even with a slight overshoot?
Excitable cells such as muscles and nerves have the ability to rapidly change their membrane potential through depolarization. This mechanism is often explained by the influence of the equilibrium potential, as expressed in Nernst's equation, as illustrated in Figure 1,below. In other words, it is commonly stated that the mechanism behind the depolarization of nerve cells is as follows:

Originally, potassium ion channels are open, and the equilibrium potential for potassium is the resting membrane potential.
However, when sodium ion channels open, the influx of sodium ions brings the membrane potential closer to the equilibrium potential of sodium ions.

However, in the case of ordinary cardiac muscle, it appears that even with a momentary slight overshoot, the height of the action potential approaches around 0V. This seems to be the case in specialized cardiac muscle as well.
My question is as follows:

In the case of ordinary cardiac muscle and specialized cardiac muscle, why does the height of the action potential tend to reach around 0V, even with a momentary slight overshoot, despite being different from the equilibrium potential of any ion?"

Fig.1
https://openbooks.lib.msu.edu/neuroscience/back-matter/images-of-animations/

Fig.2
https://www.youtube.com/watch?app=desktop&v=JaL8lYPMscc

Fig.3 https://www.backoftheboxtalks.com/resources/ventricular-action-potential

Fig.4 https://www.youtube.com/watch?v=m-pzyhVmRJM

Fig. 5 Quoted from this book, written in Japanese;https://www.amazon.co.jp/dp/4784931813/
We apologize that some of the annotations in Fig. 5 are in Japanese, but we could not find a clearer figure.　Here, English translation of the Japanese annotations in the upper panel of Fig. 5;

膜電位:Membrane potential
脱分極：Depolarization
オーバーシュート:Overshooting (Overpolarization)
再分極：Repolarization

And, here　is for the Japanese annotations in the upper panel of Fig. 5;

電流量： Intensity of the current, it means the strength of Ion each current; For example"ナトリウム電流"（Blue curve) represents the Intensity of the current due to sodium ions.
↑外向き：Outward. That means the direction from the inside of the cell toward the outside,
↓内向き：Inward. Direction from outside to inside of cell.

This Fig. 5 is essentially equivalent to Fig. 3, but　Fig.5 gives the impression that "the Ca ion current seems insufficient to balance the K ion current　at Phase 2" in the two phases.

Membrane potentials are determined by the combination of all the membrane-permeable charges, not single ions.
You can use the Goldman Equation to calculate the reversal potential for any combination of ion permeabilities and concentrations.
Sodium and calcium will be the primary contributors to the action potential height, but the kinetics of all the involved voltage gated channels are relevant, too: the Goldman Equation gives you a steady state/equilibrium voltage. The actual membrane potential will move towards this voltage, at a rate depending on the membrane capacitance, but need not reach a given equilibrium potential before permeabilities change which then changes the equilibrium.
I would recommend looking at a plot of the permeabilities to different ions over time and think about these relative to the Goldman Equation. Here's an example plot:

from Sigg et al., 2009 via http://www.vhlab.umn.edu/atlas/conduction-system-tutorial/cardiac-action-potentials.shtml

♦ Thanks for your answer. I also initially attributed it to the contribution of multiple ions. But if so, I think there must be an opposing ion current antagonistic to the K ions in Phase 2. the Ca2+ ion current would be strong enough for that in phase 1, but not strong enough in phase 2 (See lower panel of Fig. 5).

@BlueVarious The site really doesn't work well if you abuse answers and comments to ask your actual question.

I don't think of it as abuse. I added this because, to put it mildly, I may not have explained the intent of my question well enough. The fact that multiple ions would actually be involved is also mentioned in Figure 3, which was quoted from the beginning and gives a bit more detail. So I am sorry that I should have emphasized that I understand such a vague level of detail.

My question is, with the information shown in Figure 3 in mind, why would phase 2 have a value of 0mV? If you are saying that it is 0mV by chance when you substitute the actual condition into the Goldman equation, then that could be the answer you seek if it is true. But at least my question is not about what tug of war membrane potentials are generally determined by. Your answer answers that question perfectly, but does not provide any reason for 0mV at all. My question is specific to 0mV, as has been clearly stated from the beginning.

@BlueVarious Yes, it's 0 mV when you calculate a weighted sum of all the permeable ions using the Goldman Equation. Biology can't break physics. Nothing is special about zero in that equation. You'll note in the plot that the actual membrane potential is only briefly exactly zero, which it must be for any continuous function that goes from positive to negative.

Ok. That is answer, I needed !! Thank you.

At the risk of being called abuse again, there is a reason I did not mention the Goldman equation at first. I also looked at the Wikipedia page you referred me to and the equation presented there does not address divalent ions.

However, the transparency data you gave me is very useful. Once I have that data, I can understand it by assigning it to a form written in the form "Em=gA VA + gBVB" (which is also not written in Wikipedia).

Just for a Comment;
I know the Goldman equation (https://en.wikipedia.org/wiki/Goldman%E2%80%93Hodgkin%E2%80%93Katz_flux_equation), and I asked this question because I thought maybe this does not explain "0mV" at all or more specified explanations are required;
In fact, the Goldman-Hodgkin-Katz flux equation cannot be adapted to the divalent ion Ca2+, at least in the following formula. And the contribution of Ca2+ appears to not be negligible in this discussion.

At first, I did not quote the Fig.5,belowt  because it was written in Japanese, but I additionally quoted this figure as Fig5. Fig.5 shows the changes of each ion current over time, together with the action potentials of the myocardium and the timescale. If you read carefully, you should be able to read the same story from Fig. 3, but Fig.5 should be easier to understand.
We apologize that some of the annotations in Fig. 5 are in Japanese, but we could not find a clearer figure.　Here, English translation of the Japanese annotations in the upper panel of Fig. 5;

膜電位:Membrane potential
脱分極：Depolarization
オーバーシュート:Overshooting (Overpolarization)
再分極：Repolarization

And, here　is for the Japanese annotations in the upper panel of Fig. 5;

電流量： Intensity of the current, it means the strength of Ion each current; For example"ナトリウム電流"（Blue curve) represents the Intensity of the current due to sodium ions.
↑外向き：Outward. That means the direction from the inside of the cell toward the outside,
↓内向き：Inward. Direction from outside to inside of cell.

Fig.5. Quoted from the book, written in Japanese;https://www.amazon.co.jp/dp/4784931813/
(1) In the Fig. 5, a spike-like inward Na current occurs during phase 0 and phase 1. In other words, the Na current suddenly becomes strong and stops immediately. It should be clear that this is the true nature of the depolarization.
The reason why the Na current stops long before it reaches its own equilibrium potential is probably because the Na ion channel closes when the membrane potential reaches about 30 mV. Am I right?
(2) Then, the Ca current is generated just after the Na ions start up, and

since the equilibrium potential of the Ca ions is in the negative direction, and
since the period when the Ca current is flowing roughly coincides with the phase 1 period,

we can also see that the Ca current is probably the main cause which compensates  "phase 0 -induced overshoot" to 0 mV during the phase 1.
(3) The reason why the Ca current stops at a membrane potential near 0 mV is probably due to the property of the Ca ion channel to close at a membrane potential near that level. Perhaps. Am I right?
(4) And the biggest question is why the membrane potential is kept at 0V in phase 2, even though the K current is flowing and no current is depicted in the figure that is antagonistic to the K current, at least in phase 2? but I really don't understand this.

Perhaps there is another current, such as Cl ions, if so, it may explained from the Goldman–Hodgkin–Katz flux equation(https://en.wikipedia.org/wiki/Goldman%E2%80%93Hodgkin%E2%80%93Katz_flux_equation)
or perhaps the K current in the other direction is flowing from a different ion channel.

This Fig. 5 is essentially equivalent to Fig. 3, but Fig.5 gives us the impression that "the Ca ion current seems insufficient to balance the K ion current　at Phase 2.

https://cvphysiology.com/arrhythmias/a006


text:
Insect identification request - Is this a bed bug? Colorado, USA
I found three of these bugs in our friends house all dead. I never found an alive one… But I’ve been waking up with bites in the breakfast lunch and dinner pattern.
I want to confirm they are bedbugs before I tell them about it in fear of embarrassing them


text:
How many generations does it take for the average descendant not to be genetically related to the ancestor?
Parent 1 and 2 have children. Assume infinite, randomly-mating population size. How many generations until the median descendant by lineage of parent 1 has 0 base pairs inherited from parent 1?
I tried calculating this, but it was difficult to model variability in cross-over rates, and my computer is too slow for the Monte-Carlo I made.
Here is my guess:
from math import ceil, log2
import random
import numpy as np

haploid_genome_size_bp = 3300 * 1e6
diploid_genome_size_bp = haploid_genome_size_bp * 2
chromosome_pairs = 23

# Recomb hotspots
hotspot_length = 1500  # Taking the average length of 1-2 kb, in bp
hotspot_interval = 75000  # Taking the average interval of 50-100 kb, in bp
hotspots_per_genome = 30000  # Number of hotspots in the human genome

# Average crossover frequency per hotspot
avg_crossover_per_hotspot = 1 / 1300  # One crossover per 1300 meioses

total_hotspot_length_bp = hotspots_per_genome * hotspot_length

initial_genome_fraction = 1  # Starting with 100% of the genome from Parent 1
generations = 0  # Counter for the number of generations

# Loop to calculate the number of generations required for the descendant to have less than 1 bp from Parent 1
while initial_genome_fraction * diploid_genome_size_bp > 1:
    # Introduce variance in the average number of crossovers per chromosome, for probably needless complication
    # Using a Gaussian distribution centered around the average, with a standard deviation of 0.5
    avg_crossover_per_chromosome = np.random.normal(1.25, 0.5) #this doesn't actually affect the result

    # Total length affected by crossovers in one meiosis event bc hotspots
    total_crossover_length_bp = total_hotspot_length_bp * avg_crossover_per_hotspot * avg_crossover_per_chromosome * chromosome_pairs

    # Calculate the fraction of the genome that is affected by crossovers and recombination in each generation
    fraction_swapped_each_generation = 2 * (total_crossover_length_bp / diploid_genome_size_bp)

    # Update the fraction of the genome from Parent 1 in the descendant
    initial_genome_fraction *= 0.5 * (1 - fraction_swapped_each_generation) + 0.5 * fraction_swapped_each_generation / 2

    generations += 1

print(generations)

Result: 33 generations.
But really, information is lost sooner, since (approximately) non-SNPs won't contribute to information, non-SNPs are shared between individuals. Let's say there's 600 million SNPs, randomly distributed throughout the genome. Let's assume that parent 1 and the entire rest of the population differ at, say, 70% of SNPs (this value doesn't matter much, it's always 29 or 30).
from math import ceil, log2
import random
import numpy as np

total_snps = 600e6
haploid_genome_size_bp = 3300 * 1e6
diploid_genome_size_bp = haploid_genome_size_bp * 2
chromosome_pairs = 23

hotspot_length = 1500
hotspot_interval = 75000
hotspots_per_genome = 30000

avg_crossover_per_hotspot = 1 / 1300

total_hotspot_length_bp = hotspots_per_genome * hotspot_length

initial_snps_fraction = 0.7
generations = 0

while initial_snps_fraction * total_snps > 1:
    avg_crossover_per_chromosome = np.random.normal(1.25, 0.1)
    total_crossover_length_bp = total_hotspot_length_bp * avg_crossover_per_hotspot * avg_crossover_per_chromosome * chromosome_pairs
    fraction_swapped_each_generation = 2 * (total_crossover_length_bp / diploid_genome_size_bp)
    initial_snps_fraction *= 0.5 * (1 - fraction_swapped_each_generation) + 0.5 * fraction_swapped_each_generation / 2
    generations += 1
print(generations)

Result: 29 generations.
It is sensitive to the number of SNPs in existence. If we use 1 million SNPs, we get 15 generations.
Is this right? Can we find a more accurate estimate? My code probably has some mistakes.

My interpretation: assuming a generation time of 25 years, this means if you have an ancestor who lived more than 725 years ago, they are probably (P > 0.5) not genetically related to you in a meaningful way.

If you’re a mother, your mitochondria can go a long way.

@PaulTanenbaum I'm disregarding mtDNA and the Y chromosome, but it wouldn't make much of a difference since only a small fraction of descendants will be paternal/maternal line

Indeed. That’s why I said can.

Graham Coop performed simulations related to this question, based on actual transmission data for each chromosome in humans. He found that after 10 or 11 generations there was >50% chance that any particular ancestor contributed no genetic information to a specific descendant. Fewer than 5% of a person's 14th-generation ancestors will have contributed genetic information to them.

This blog post is part of a series. The first provides some more information about the data and assumptions feeding these simulations.

What is the relevance of the link discussing GWASs?

That was just a link to Graham Coop's blog, where the other posts can be found.

Father/Mother, DNA = D
Child, $\frac{1}{2} \times D$
Grandchild, $\frac{1}{2}\times \frac{1}{2} \times D= \left(\frac{1}{2}\right)^2 \times D$
Great grandchild, $\left(\frac{1}{2}\right)^3 \times D$
One's $n^{th}$ descendant has only $\left(\frac{1}{2}\right)^n$ of one's DNA.
Which generation and later will have only $1\%$ or less of your DNA?
$\left(\frac{1}{2}\right)^n \leq \frac{1}{100}$
$2^n \geq 100$
$n \geq 7$
That is to say, after 7 generations, one's genes are diluted to near homeopathic concentrations.
EDIT
Note that this is a(n) (over)simplfication of how heredity via DNA works. The actual processes are quite complsx.

This is illustrative of a simplified view of the problem, but it doesn't directly answer the OP question which introduces more complex phenomena like recombination. It's a bit more complex than this due to haplotypes, population structure, etc.

@MaximilianPress, I concur. Edited my answer appropriately.

If we assume infinite crossing-over and 600 million SNPs, we'd still be left with 6,000,000 SNPs after only having 1% of the DNA. Interestingly, I think your model basically works similarly to mine, because (1/2)^30 * (600 million) is approximately equal to 0.5. That is, after 29-30 generations, it rounds to 0 SNPs left.

@BigMistake, If our (similar) models are even half as accurate, some things should be impossible, no? Unless ...


text:
To where exactly does the sarcoplasmic reticulum release its calcium when stimulated?
I`m reading through medical physiology (2nd ed) by Boron & Boulpaep. On page 240 when describing the mechanism behind muscle activation, they write the following:

After depolarization of the L-type Ca-channel on the T-tubule
membrane and mechanical activation of the Ca-release channel in the
SR, Ca stored in the SR rapidly leaves through the Ca-release channel.*

Now, according to the illustration, the Ca-release channel (sometimes linked to the L-type Ca-channels) leads back to the T-tubule, and since the T-tubule is just an invagination of the extracellular space I can`t really see why that would trigger muscle contraction.
If the Ca-content in the SR where instead released intracellularly I guess I can see how Ca could be linked to the troponin complex and the muscle contraction process could get started.
But do the Contents of the SR actually get released intracellularly? The text and the picture seem to indicate otherwise. I have tried searching online, but most sources just claim Ca gets released without bothering specifying where to.

I suggest using an image search (for example: muscle sarcoplasmic reticulum calcium) – many images will clearly show you that the calcium is indeed released into cytosol.


text:
Does columnar epithelium always have microvilli or cilia?
Is there any example of columnar epithelium in any part of our body that do not have cilia or microvilli?


text:
What happens to silverfish when we throw them out the window?
I'll find a silverfish from time to time in my flat. I don't mind them but usually I catch them and throw them off the balcony (second story) into the bushes and lawn below.
I was wondering, since they seem to live in the water conduits in the house, if they can survive outside or if they die/get killed instantly.
Thx for your help!

They can definitely survive outside. Remember, houses haven't existed for much of history at all, so what did they do for their ~400 million years of existence before the advent of houses?

Well, they could have lived in caves or next to rivers?

Yes, they can and do, but my point is that they can survive the outside, as you asked.

Are you sure those are silverfish? In my experience, it is quite difficult to catch them alive. I find it hard to believe that you do that regularly.

@Roland Yes, quite sure. I put a glass over them, when they are exposed somewhere and then a piece of paper below. The very young and tiny ones are harder but the adults are fine.

Silverfish prefer high humidity and warmth. Ctenolepismacalvum (Ritter, 1910) was recently found in Japan at a temperature of 20-30°C and 50-60% RH. As long as there are pieces of bark, wet grass or other organic or human-made structures that retain humidity after each raining event, the likelihood that they will survive long enough to complete their cycle is high.
They could face dessiccation if they are not able to find a damp spot in time, depending on their tolerance to it. However, it was not possible for me to find information about their dessiccation tolerance.
The Zygentoma (silverfish order) have high tolerance to low humidity and most of the species inhabit dry and hot environments (it's just a few that like humidity), which again makes me think that those silverfish propelled out the window will survive.

References
Shimada M, Watanabe H, Komine Y, Kigawa R, Sato Y. New records of Ctenolepismacalvum (Ritter,1910) (Zygentoma, Lepismatidae) from Japan. Biodivers Data J. 2022 Nov 3;10:e90799. doi: 10.3897/BDJ.10.e90799. PMID: 36761636; PMCID: PMC9836529.
Kulma M, Bubová T, Davies MP, Boiocchi F, Patoka J. Ctenolepisma longicaudatum Escherich (1905) Became a Common Pest in Europe: Case Studies from Czechia and the United Kingdom. Insects. 2021 Sep 10;12(9):810. doi: 10.3390/insects12090810. PMID: 34564251; PMCID: PMC8471186.
Querner P, Szucsich N, Landsberger B, Erlacher S, Trebicki L, Grabowski M, Brimblecombe P. Identification and Spread of the Ghost Silverfish (Ctenolepisma calvum) among Museums and Homes in Europe. Insects. 2022 Sep 19;13(9):855. doi: 10.3390/insects13090855. PMID: 36135556; PMCID: PMC9505982.


text:
What are the most common proteins inside cells, by mass?
I'm interested in the most abundant proteins inside cells by total mass of the protein (for example average for a whole human or for specific organs/tissues/cell lines).
It is quite easy to find that the largest % by mass in the human body is collagen (25 to 35% of total body protein).  Collagen is an extracellular protein; finding the same info for intracellular proteins has been surprisingly difficult.  Finding what is the second largest %, or a top 10 list, has also been difficult.
In the process of searching, I found PaxDb which lists protein abundance by "ppm", or counts divided by the total counts.  It is quite hard to convert that to % by mass - it would be necessary to know the molecular mass of every protein (for example by matching them with entries in UniProt), and then multiply count by molecular mass.  Another resource which seems to have a lot of data is PeptideAtlas, but I can't tell how to extract either counts or masses from that.
Is there a canonical list of (eg) top 10 or top 100 intracellular proteins by mass in a whole human?  How about the same by organ/tissue?

I can’t see why a scientist would prefer a mass-based, rather than a molar value, except, perhaps for which proteins are likely to correspond to spots on a 2D gel. I seem to remember that EF-Tu/EF-T1 was one of the stars (but that was in my field of interest). You could try searching the 2D gel literature for that sort of thing, however it will probably miss the very basic ribosomal proteins, which are analysed on a different gel system. But, really, the values for the “average human cell” would seem of interest only to stamp collectors. Have you no context?

Similar to David's comment, you want to make sure you're avoiding the XY problem: what is the underlying problem you're trying to solve? It's possible there is a better solution to the underlying problem than the one you've come up with.

@David I'm interested in physical properties which would be determined, in a mixture, by the predominant components by mass not count (think stuff like Trp fluorescence spectroscopy or XANES).  I'd like to pick a couple of single proteins as models for simplicity, but it makes sense to pick ones which would mostly determine the results when measuring an intact whole cell as well.

@AlexI I'm not familiar with that field, what percent by mass would the predominant component need to be for it to be considered "predominant enough"? And why would the mass of the rest of the protein matter for Trp fluorescence spectroscopy?

@BryanKrause Just using that as an example, my actual motivation is a different spectroscopic technique.  It would be "% of all Trp" of course, but as long as the fraction of that in aa sequence of different proteins is similar, "% of protein mass" is a pretty good substitute

"what percent by mass would the predominant component need to be for it to be considered "predominant enough"?" - This is mainly about selecting a good simplified model to study.  If actin filaments were >20% of the protein mass of a typical epithelial cell, those would probably make a good model.  I am guessing there are just a handful of things which together make >50% in most cell types, and those are probably either mostly structural (actin, intermediate filaments, microtubules); or related to the major cell function (myosin, hemoglobin).  It's been hard to get numbers to quantify that


text:
Is this scenario allopatric or sympatric speciation?
I stumbled over a speciation scenario but I am not able to say to which type it belongs. I guess for people more familiar with the theory it might be easy to tell.
I was reading about the fin whale (Balaenoptera physalus). This species is usually devided into two distinct populations, a northern one (ssp. physalus) and a southern one (ssp. quoyi). During winter, the fin whale is going to more tropical regions to breed, while in summer to artic/antarctic regions to hunt. Now, since the seasons are opposite on the northern and southern hemisphere of earth, these two populations in principle never met in the wild.
Now, imagine these two populations survive the next thousands of years and that two destinct species develope out of this populations. Would this process be considered allopatric, or sympatric? I would tend to say allopatric, since the two populations are separated, but on the other hand, there is no literal barriere and in principle they are able to interchange...


text:
Fungivore that feeds specifically on spores
I'm wondering if anyone has knowledge of an organism that specifically feeds on the spores of fungi. When I attempt to research this the results are flooded with numerous examples of fungivores but I've never been able to locate any information specifically on spore consumption.
Perhaps no organisms are known to feed directly on spores but I find this surprising. It seems spores would be an excellent and abundant nutrient source for a properly adapted organism.

This paper:

Smelansky, I.E., 2006. Some population characteristics of oribatid mites in steppe habitats. Acarina, 14(1), pp.123-130.

includes analysis of the gut content of some mites, recognizing several trophic guilds including "specialized
sporovores, and (specialized) sporovores ‘feeding
on surface’ ".  These two guilds are described:

specialized
sporovores feed on a very limited set of fungal
spores including only 4–5 morphological kinds of
spores in each mite species; the guts of sporovores ‘feeding on surface’ contain unusually high portion
of pollen grains and spores of epiphytic fungi.


text:
Working in heat
What does working in temperatures of 180 degree dry heat for long periods do to the body?
Such as inside of a cooking cyclone scraping product out of it while it's still at 180 degrees.

180°C or 180°F ?

180°F while in use it gets to 250°F


text:
Estimation of carbon stock value
I would like to ask, to calculate the carbon value estimation, the Allometric formula is of course used, but in some of the literature I searched, I found different allometric formulas but the same type of plant species. So I have a little confusion about which formula to use as the basis of my research. Could you please explain/help me on what I should do to solve my problem? Thank you everyone


text:
How many photosystems in a chloroplast?
I haven't been able to find any good order-of-magnitude estimates for how many photosystems (e.g. how many PSII complexes, how many PSI complexes) are in an average chloroplast (or perhaps per area of thylakoid membrane).
Textbooks always just show a small area of membrane, and I'm interested to know whether there are say hundreds of complexes or millions. Is there any published data on this?

This article states that in plants at 15-25% relative water content (RWC), the PSII density is around ~700 complexes/µm$^2$, and in hydrated plants ~1500 complexes/µm$^2$.

They also have some nice Cryo-SEM images of grana membranes and the changes in PSII complexes density depending on their RWC. Which is also an important aspect of the question, since the amount of PSI and PSII complexes will vary depending on the environmental stimuli.

Additionally, given that biological material is variable even within the same species (different tolerances might have a different effect on the amount of complexes/µm$^2$), I would expect variability in the complexes density among different species of plants too.
Regarding PSI, I found an article where mass spectrometry analysis approximates the average of PSI in the thylakoid of a Prochlorococcus MED4 ecotype to 4303/μm$^2$. However, the thylakoids of another ecotype had more densely PSI organizations of crystalline pseudo-hexagonal arrays and the average was estimated at 5583/μm$^2$. In fact, the article tested growth under different conditions (low-light, high-light, poor-nutrient) of the different ecotypes and supports the hypothesis that the second ecotype adapted to low-light conditions (by maximizing the amount of pigments in its thylakoid membrane) while the first one adapted to high-light conditions. In this case, the observed part of the membrane with cryo-EM tomography was ~6 μm$^2$and ~22 μm$^2$ of thylakoid membrane area for the first and the second ecotype.
I think the right answer is that there are many factors affecting the distribution of PSI and PSII that are still unknown and a better approximation cannot be made.

References
Charuvi, Dana & Nevo, Reinat & Shimoni, Eyal & Naveh, Leah & Zia, Ahmad & Adam, Zach & Farrant, Jill & Kirchhoff, Helmut & Reich, Ziv. (2015). Photoprotection Conferred by Changes in Photosynthetic Protein Levels and Organization during Dehydration of a Homoiochlorophyllous Resurrection Plant. Plant physiology. 167. 10.1104/pp.114.255794.
MacGregor-Chatwin C, Jackson PJ, Sener M, Chidgey JW, Hitchcock A, Qian P, Mayneord GE, Johnson MP, Luthey-Schulten Z, Dickman MJ, Scanlan DJ, Hunter CN. Membrane organization of photosystem I complexes in the most abundant phototroph on Earth. Nat Plants. 2019 Aug;5(8):879-889. doi: 10.1038/s41477-019-0475-z. Epub 2019 Jul 22. PMID: 31332310; PMCID: PMC6699766.


text:
Does the molecules in nerve cell membrane change 100% during the life of the nerve cell?
In their lifespan nerve cells do not divide and so they stay the same. They do get damaged sometimes and require some maintenance and change their axons a bit. They also require a lot of energy so they take in stuff and produce waste. This would in my opinion mean that the molecules in nerve cell membrane can change and that molecules do go in and out, but it does not imply that there is a process which changes the molecules in nerve cell membrane regularly. I have not been able to find information whether the molecules which make up the nerve cell's membrane change 100% during its life.
So does a nerve cell which can live 80 years change the molecules that make up the membrane regularly, so that in a long period of time almost every molecule in the membrane has changed? This would be an analogy about a human which replaces skin cells regularly.
In addition, I would be interested if nerve cells change replace other parts inside the membrane regularly in a molecule level.
In not long living cells, which divide I think that the molecules in the membrane have to change completely. If one cell divides into two, then the amount of membrane cannot be enough in neither of the cells so they need to take in stuff and grow the membrane. In this process even if the membrane may not be regularly replaced the dividing would cause the change eventually after a lot of dividing.

Hi Lauri, welcome :) maybe the genetic mutations accumulated over time due to environmental and physiological factors could make the 80 year old neuron express the wrong proteins for the membrane, or simply not produce them at all? A neurobiologist might appear and chip in at some point with a better idea.

@pawelekzzz Thank you! That is probably true. Changes in the neuron's gene could cause different proteins in the membrane and basically also to start the neuron to change the molecules in the membrane or stop replacing them. However, I don't see directly how this is relevant to my question. Or was your point that it could be at least theoretically possible that the molecules would change if there would be a certain genetic mutation?

I meant that at least the number of molecules related to membrane proteins that will
be regularly synthesized during the lifecycle of the neuron will be part of that percent. They will also change over time themselves (or entirely stop being expressed) after accumulating mutations that affect translational regulation.
Damage to membrane phospholipids measuring ~1 nm or less will be thermodynamically rearranged using existing phospholipids. Larger damage will be resealed through exo-endocytotic vesicle trafficking but those “lost” phospholipids will be recycled through a salvage pathway.


text:
Potential Function of Knuckle Popping?
Today I was walking past a door, when I accidentally hit my hand on the frame. All my knuckles popped instantly. I got curious and did the same thing but with my knuckles popped and this time the impact felt much more pronounced. Is the function of the popping of knuckle to retard the hand slowly, hence reducing the force when hit?

How do you propose that anyone knows whether that’s the purpose (if indeed there is a ‘purpose’, which it seems likely there isn’t)? (Genuine Q)

Is the function of the popping of knuckle to retard the hand slowly, hence reducing the force when hit?

No. The only physiological effect of popping the knuckles is to temporarily stretch the joint capsule improving range of motion slightly, which is why people often wiggle their fingers afterwards, or pop them before using their hands for something requiring a lot of dexterity (like safe-cracking in movies.) It may also cause the release of a small amount of oxytocin, which makes one feel good/less stressed/happy, accounting for its propensity to be habitual.
It doesn't seem to have a purpose. It's a phenomenon which can happen in many joints, including the neck and back. Some joints can click (e.g. the ankle) with certain movements, which is different.
It can be harmful to the joint capsule if forced.

What happens when you crack your knuckles?
For centuries, people have wondered about how knuckle popping works, and for decades people (usually older adults) tried to discourage their kids from popping/cracking their knuckles, warning them of future arthritis. However, it does not cause arthritis, and the mysterious phenomenon may have an explanation at last.
"Cracking" one's knuckles (or popping if you prefer; it depends on where you grew up) refers to the sound made when certain kinds of stretching are applied to the joints. One of my kids was addicted to it, so knowing if it could cause arthritis was important to me. In fact, there aren't any studies linking habitual knuckle popping to osteoarthritis. Knuckle-poppers are no more likely to develop osteoarthritis than non-poppers.

The [lack of] evidence for the association of knuckle cracking and osteoarthritis comes mainly from observational studies that have failed to show an association. [bracketed words mine to make statement clearer]

This has been born out by large retrospective studies and by small ones.
But what makes the noise? It's related to tribonucleation defined by Wikipedia as

a mechanism that creates small gas bubbles by the action of making and breaking contact between solid surfaces immersed in a liquid containing dissolved gas.

Knuckles, the joints between the flat part of your hand and your fingers, and those between the nearest and the middle finger bone) are solid cartilagenous surfaces surrounded by a fibrous joint capsule, and filled with a lubricating (synovial) fluid containing mostly proteins and dissolved gasses. When you pull the surfaces apart, the joint capsule stretches to the point that the dissolved gasses come out of solution and form a bubble (cavitation). The formation of that bubble produces a pop.
I don't understand why it produces a noise; a physicist might know. It has been compared to the noise that occurs when a suction cup is pulled off of a solid surface and air rushes in. Or my analogy would be clicking your tongue: placing the tongue to the roof of your mouth, creating a vacuum there, and then breaking contact produces a pop, how loud it is is proportional to the strength of the vacuum produced. It can be a soft "tsk, tsk" sound or if both surfaces are wet with saliva, a loud POP! I don't know why that causes a noise either, but it happens.
The formation of a bubble in the joint was first shown on xray in 1947. The noise produced was shown by MRI to be produced when the bubble formed by Kawchuk et al. in 2014, not when the gas was resorbed. You cannot pop your knuckle again until the gas bubble is resorbed into the synovial fluid.
On the left, no stretching action yet (normal joint); on the right, stretching applied to the joint with the formation of a bubble. Note how much more area the joint now occupies due to the stretching and gas.
[
Real-Time Visualization of Joint Cavitation

Do habitual knuckle poppers produce more sound than non-poppers? I have observed that people with that habit can crack it easier and louder than others. I also observe that they can do it more frequently than others.

@Aurelius - It's possible that habitual knuckle poppers have loosened the joint capsule a bit, so there might be a bit more synovial fluid in their joint space, thus more gas, thus a bigger bubble, thus a louder pop. (I don't know this for a fact.) I don't think they can pop their knuckles more frequently; it would take longer for the larger gas bubble to be resorbed, if my suspicion is correct.

(+1) Couple of doubts: 1. "It may also cause the release of a small amount of oxytocin, which makes one feel good/less stressed/happy, accounting for its propensity to be habitual" --> Is it actually? I always thought it is just placebo effect acting and there is no physiology involved. 2. "It doesn't seem to have a purpose" --> If that is the case, why did humans picked up the habit? Can it be considered an evolutionary habit?

@NilayGhosh re 1: "It may..." (emphasis mine). re 2: I don't know what an evolutionary habit is, so I googled "evolutionary habit" (scholar) and didn't get any hits. That piece is erroneous.  Lamarck was wrong.

I asked a follow up question on this topic: https://biology.stackexchange.com/questions/113071/is-the-habit-of-popping-knuckles-be-considered-an-evolutionary-habit


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Large grey bird at creek mouth (east of Toronto)
What species of bird is this?

Spotted at the mouth of Graham Creek at Newcastle Marina (Bond Head), Lake Ontario, Canada
September 9, 2023
The bird was roughly 18 inches tall; dark grey body; light grey head and neck; yellow beak

+1 for precise location. Sometimes questions here include vague locations (e.g. Canada) or no location at all, nor even a hint on the habitat, and location is often useful to discard a lot of species.

The second picture is very good (both for identification and the moment)

I'm highly confident that this is a cormorant. I'm less certain of the species, but based on the location I would bet that it is a double-crested cormorant (perhaps a juvenile based on the head color/feathering, though I don't know if this varies in adults based on season) as these are found in high numbers around the Great Lakes region, including Lake Ontario.
  photo by Jane Mann, from Macaulay Library
See also:
The rise of the Double-crested Cormorant on the Great Lakes:
WINNING THE WAR AGAINST CONTAMINANTS

Looking at the maps in my Sibley guide, there are occasionally vagrant Great Cormorants & Anhingas in the Great Lakes area.  But their coloration is different, even for the juveniles, and so I agree that it's far, far more likely to be a Double-Crested Cormorant

Anhinga can be ruled out by the bill; theirs is straight, without the hook at the end cormorants have.

A cormorant or possibly a shag. Far more common in saltwater surroundings, but can be at home in fresh water.

As mentioned by @BryanKrause, cormorants are super-common around Lake Ontario, e.g. this photo from Hamilton harbour https://ontariohunting.net/wp-content/uploads/2018/11/3-0_Super_Portrait.jpg (source: https://ontariohunting.net/nature-not-bullets-should-control-cormorants-mcmaster-biologist-says/ )

@BenBolker - Coming from UK, I wouldn't have a clue about that! But thanks anyhow.


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Prevention of disease spreading in animal kingdom
It's my first question on here, so I'm not sure If my question fits the theme. Please refer me to the appropriate one, If I have made a mistake.
So a question that I wanted to ask has to do with whether or not animals potentially try to avoid spreading diseases. So I was thinking... In an event that a really deadly disease emerges in a population, it would be really dangerous for animals that live in social groups, of any size really, not to have any instinctual behaviours that try and prevent the disease to spread. Animals that live in big heads, like wildebeests would just probably leave the diseased individuals behind, apes and monkey could potentially cast out individuals from the group, etc. Ants have separate sections in their tunnels that serve as graveyards, I presume for this exact purpose.
A lot of parasitic organisms have adaptations that specifically target animals with social behaviour, so why wouldn't animals adapt against that?
Something that also came to my mind is that this could possibly evolve not as a social behaviour of a group, but sometimes that individuals in a group would do, for example self isolation. However, I do not find this likely, I possibly requires higher cognitive understanding of disease spread.
Am I way of base here? If not, could you please provide some interesting examples you are familiar with.
Please consider that I AM NOT a biologist, nor have any experience in the field. I am a computer scientist, who enjoys biology. If any of my axioms or hypothesis have don't even come close to reality, please be kind, I am not educated in this field. Thank you for reading

Humans lived in tribe systems like animals and were protected from pandemics, until very big cities and the start of globalization... yersinia pestis was one of the first to arrive by boat in constantinople in 4AD, they were walking on dead "like pressing raisins under the feet"... American indians were protected because they lived in tribe structures, from old world illnesses. Generally, animals  often live more like tribes than pan regional societies.

If only we had an anthropology stack. Not an answer, as I can't find any references to the practice for this use-case, but I've heard tell of tribal practices/customs of abandoning the elderly/frail under times of hardship - the same may have extended to various forms of sickness.

Taking the evolution angle, some anti-transmission behavior may be hardwired (not requiring human-level intellect) e.g. an infection usually means symptoms like (high) fever, malaise, fatigue, lethargy (mental + physical) which, combined, leave the infected person bedridden and the less you can move around in the environment, the lower the chances of you spreading the infection. Sick leave? Modern, scientifically justified methods of breaking the transmission chain, e.g. isolation/quarantine/immunization, are ultimately extensions of natural behavior found also in nonhuman animals (in response to infections). The "objective", if we could call it that, of bodily response when under assault from a pathogen, is to immobilize (e.g. severe case of the flu) or die (ebola hemorrhagic fever), both being variations on quarantine.

I like the question, and it's an area I've given some thought to. My answer is "yes." Yes, animals have adapted behaviors to avoid getting sick from disease. There's not much motivation for an infected individual to avoid spreading it, except perhaps to avoid spreading it to closely-related individuals. Nor is there a mechanism for the behavior to evolve, since the sick individual isn't going to have as many (any) grandbabies.
That said, GROOMING is a great example of an evolved behavior that is almost universally done between mother mammals and their babies, and between close adult individuals in some species. It could be affectionate disease-prevention.


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Is the "endo-" prefix in "endotherm" inconsistent/opposite to its use in "endothermic reaction"?
It seems to me that the "endo-" in the biology term "endotherm" is opposite to the "endo-" in the chemistry term "endothermic reaction." Is that the case?
As I understand it:

an exothermic reaction is one that releases energy into the environment
an endothermic reaction is one that draws energy from its
environment.

Given that, I would have expected that:

an exotherm "ectotherm" would be an organism that releases energy into its environment (i.e. warm-blooded)
and  that an "endotherm" is one that draws energy from its environment (i.e. cold-blooded)

As Wikipedia puts it (emphasis mine):

An endotherm is an organism that maintains its body at a metabolically favorable temperature, largely by the use of heat released by its internal bodily functions instead of relying almost purely on ambient heat.

That really does seem to better match the "exo-" prefix.
Is there a real inconsistency here, or do I just understand this incorrectly?

See the section “Distinction between endothermic and endotherm” on this wiki page: https://en.wikipedia.org/wiki/Endothermic_process

Endothermic = "inside + temp", as in their source of heat is from within.

The prefix "endo" comes from the Greek "endon" meaning "inner". "Therm" comes likewise from the Greek "therme" meaning heat.
Thus Endo = inner, Therm = heat, heat from inside!
The confusion applies in chemistry, not in that someone has it wrong, but that molecular reactions sometimes release heat - this is obviously to the outside so it must be "exo". The Greek opposite of exo is endo, so the converse reaction (absorbing heat) must be endothermic.
Note also that in the case of an endothermic reaction, the heat supplied for the reaction to work comes from within the materials of the reaction, it's just that in the process of the reaction occurring the heat is "used up" so the reaction vessel feels cold. Because the heat is coming from inside the reaction "endo" makes sense here too.
I did my basic chemistry too long ago for me to remember for endothermic reactions if environmental heat is needed for the reaction to proceed, but I suspect that at any temp above 0 K, the answer is generally no; the heat comes from breaking of intra-molecular bonds.

"Because the heat is coming from inside the reaction "endo" makes sense here too." Bingo, that makes it make sense and consistent, thanks!


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Can thymocytes end up in a lymph node instead of thymus?
Can thymocytes exiting bone marrow end up in a lymph node instead of thymus? If not why? Here is my thought: thymocyte in the bloodstream, on its way to thymus, can leak into interstitium with blood plasma and from there enters the lymphatic capillaries that drain to the nearest lymph node.


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Databases medicine and therapy - animal & human studies, technology readiness level
I am looking for some universal databases that would offer information about drugs and therapies currently in development.
The area of interest is mostly cell and gene therapy. I am looking for anything from preclinical research to clinical trials. I am also searching for data related to technology readiness level of those drugs/therapies.
Any help will be deeply appreciated.

There are plenty of clinical trials databases out there. Without more specifics on what you particularly want, we won't be able to help.

Forgive me. Here is exactly what I would like to find: cell and gene therapy technology readiness level, scientific data including all animal and human studies.

Sites like clinicaltrials.gov might be of some use. By specifics -you just want to find about all of them, because there are likely to be hundreds and all in different stages. The data is in the form of publications, which may or may not have been made public.

Try searching clinicaltrials.gov with the terms "gene therapy" and "cell therapy". If that isn't adequate, feel free to bring what you don't like here.


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Why is the codon size three, rather than four?
The genetic code consists of triplets, each of which (apart from the stop codons) yields an amino acid when the mRNA is translated.
But why did triplets evolve, rather than a longer or shorter codon size?

Does this answer your question? How did the genetic code evolve?. It and similar questions in our archive have answers that discuss this topic at length.

The reason is pretty simple: It comes from the number of amino acids used to make proteins and thus with the necessary number of possible combinations and robustness of the system.
We have 20 amino acids which are coded by the triplets plus one start and two stop codons. If any of these would only be coded by one base, we already need 23 codons. However, in such a case there would be no redundancy in this system, since any change of a base would lead to an amino acid exchange which can negatively affect a proteins function.
To calculate the number of possible amino acids use the number of bases on the RNA and the length of the codon.
If the codon has a length of 2, you have (sic 2^4=16) $4^2 = 16$ possible combinations. This is obviously not enough for what is needed. (sic 3^4=64) $4^3 = 64$, which is enough to have some redundancies in the code and not every altered base leads to an exchange of an amino acid. It therefore also adds some additional robustness to the code.
If your codon had a length of 4, there would be 4^4=256 combinations, which is way more than needed. This adds a lot of complexity to the translation. [codon length of 4] raises the number of necessary nucleotide by a third, which costs the cells a lot of energy. The extra energy expense on nucleic acid lengths is negligible compared to that of maintaining the extra tRNA synthetases and tRNAs.
The codon triplets are evolutionary well conserved, there is even a mathematical paper available which states that organisms with codons of n>3 will reduce their codon size to a triplet code by evolution.
Reference

Codon Size Reduction as the Origin of the Triplet Genetic Code

"[codon length of 4] raises the number of necessary nucleotide by a third, which costs the cells a lot of energy". The extra energy expense on nucleic acid lengths is neglectable compared to that of maintaining the extra tRNA synthetases and tRNAs. This should be at least some orders of magnitude.

(Just meant as a slight expansion to your answer, which is good overall.)

@KaPy3141 Thanks for the expansion, you're welcome. I added this.

This answer takes it for granted that the codon size is a function of the number of amino acids used for protein synthesis (20), rather than the other way around. That seems reasonable to me, but including a mention of whatever support exists for it would benefit the answer.

@timeskull It evolved this way because of 20 amino acids. I will see to phrase this more clear.

@Chris "It evolved this way because of 20 amino acids". And what makes you think that the genetic code didn't arise until all the synthesis of all 20 amino acids had developed? What if I suggested the evidence suggests it evolved at a time when there were fewer than 16 amino acids, or argued that 20 amino acids aren't needed. I would stick to the question, which I'm surprised you even answered, or having decided it wasn't homework, didn't clean up. I'll do so, but vote to close. However, if people want to discuss other aspects of the genetic code, they should formulate a question.

@David We don't know and we cannot. But seeing the universality of the code suggests that. You can of course argue that all life forms that use less amino acids didn't make it over time. There is no solution to it.


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Carbon dioxide concentration in alkaline media
I am running a batch experiment using penicillin bottles where I have bacteria growing for 21 days in a highly alkaline media (pH 10). I am measuring the CO2 and O2 content in the headspace over time, but I am specially interested in the CO2 production. Usually I can simply use the CO2 content measured with a gas-chromatographer (GC) but because of the pH of my media, the CO2 will be dissolved into my media. This I have seen in the sharp drop of pH over time as well.
I want then, to calculate the amount of CO2 that has dissolved into my media. I know I require Dalton's Law of partial pressures and Henry's constant/Law. The thing is that, I am a bit confused because as I measured the pressure inside my closed bottles, the pressure in these bottles became negative. So my calculations are returning a negative value for my concentration of gas in the solution. Furthermore, I do not know if the formulas I used (Dalton  and Henry), take into consideration the pH of my aqueous media.

What salts are present in you media? Something like calcium will precipitate with carbon dioxide and removed from your system.

It's just a TSB media adjusted with CAPS buffer. No precipitation was observed.


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Qpcr Copy number formula
I recently started to get involved with quantitative PCR. I have some data and I want to calculate the copy number of them. In the output Excel file, I have the following cells (I am running Quandstudio v.1.5.2).
Well| Well Position|Omit|Sample Name|Target Name|Task Reporter|Quencher|CT|Ct Mean|Ct SD|Quantity|Quantity|Mean|Quantity|SD|Y-Intercept|R(superscript 2)|Slope|Efficiency

I found the following formulas
copy number = 10^(ct - intercept)/(slope)
copy number = 2^-ΔΔCt

I have two questions.
a) Are these formulas accurate?
b) Is there any other suggested formula that I can apply to my data?
If there is any helpful article that has calculation formulas, it is more than welcome!

Welcome to the Biology Stack, this site values questions that show some attempt to research the answer for them selves. So - what can you tell us about the two formulae - What situations would you apply them in? Why are they different?

The second formula (2^-ΔΔCt) you are presenting does not calculate a number of copies of your target. It is instead used in relative quantitation, where you want to know the relative expression of your gene of interest normalized to a reference gene, and compare it between samples of different treatments.
From your question, it seems that you want to perform absolute quantitation instead, more precisely, you want to know about the exact number of copies of your target in different samples.
For this, you need to run your samples alongside a standard curve consisting of several dilutions of a known quantity of your target. You have to know the number of copies of the target which are present in each dilution step by following the method described here: https://toptipbio.com/dna-copy-number-qpcr/
After running your plate and provided the efficiency of your primers is ~ 100 % and is similar between your standard curve and samples (which you should have tested before), you now know the relationship between number of copies of the target and Ct value. The Ct value you have in each sample can thus be extrapolated to a number of copies.
Edit (because I did not go all the way) :
Then you can plot the Ct values against the log of the concentration of your standard. You extract the formula of this curve, and you replace x by the Ct value of your sample in order to know y = concentration of target in your sample.
Otherwise I found this here : sciencedirect.com/science/article/pii/S0301472X02008068
"Most real-time PCR instruments have software that can automatically compute the amount of template of an unknown sample from a standard curve. However, it can be done manually by putting the observed Ct value for an unknown sample into the formula: (observed Ct − y intercept)/slope." intercept and slope being the ones of the calibration curve.

Thank you very much for the prompt, analytical, and clear answer. You reply without being ironic, trying to evaluate my skills, or asking me testing questions. I think,  I understand the logic and the connection between the curve and the copy numbers. And regarding the first formula? Can this be used for direct copy number calculation? I am asking cause I want to understand how to connect the rest of the excel columns with copy numbers and ct?

I have never seen the first formula before. I do not know what type of samples you have run, what it is your columns contain. But what I know for sure is that you need to have a calibration curve in order to know the relationship between Ct and number of copies.

... I just found here : https://www.sciencedirect.com/science/article/pii/S0301472X02008068
"Most real-time PCR instruments have software that can automatically compute the amount of template of an unknown sample from a standard curve. However, it can be done manually by putting the observed Ct value for an unknown sample into the formula: (observed Ct − y intercept)/slope." intercept and slope being the ones of the calibration curve.

Thank you once again for the reply as well as for the paper!!!!! Now I can practice myself on qPCR data!!!


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light hitting the center of the retinal receptive field
In my teachers slides, it says "light hitting the center of the retinal receptive field can either increase or decrease the number of impulses fired"
Is this "or" because it depends on whether the light hits a photoreceptor connected to an on or an off bipolar cell? So does that mean when light hits a certain place, it hits only one photoreceptor? How are these two types of bipolar cells arranged? I thought that if some light hits the center, there is an equal number of on and off bipolar cells.

Your teacher's slides should include which cell in the retina they are talking about. If they don't, the slides are very incomplete.

They do not. But what do you mean? What cell are you thinking of and why would that make a difference? Thanks!

Because there's no such thing as a "retinal receptive field". The retina doesn't have a receptive field any more than a school has a kidney. There are neurons in the retina, though; those have receptive fields. But there are a lot of different kinds of neurons in the retina. The statement would not be true if, for example, you applied it to a rod or cone photoreceptor cell.


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Do hair cells in the ear also vibrate at frequencies outside our hearing spectrum?
(The question has its origin because I asked myself in how far frequencies outside our perception can harm our hearing.)
First of all, the energy of a mechanical wave (in this case, the sound wave, which stimulates periodic movements of a gas) is proportional to both amplitude and frequency. Often, I read that it is written that energy depends only on amplitude, but when I have two waves with the same amplitude, and one has a higher frequency than the other, it apparently carries more energy. It has a shorter wavelength and moves the molecules much faster over the same distance. Since $E = F * s$, a wave with a higher frequency must carry a greater force (and therefore energy) to overcome the inertia of the molecules more quickly.
I'm not entirely familiar with how the ear works, but I do know that it has three sections. Waves enter through the outer ear, continue to vibrate the eardrum with their frequency, the middle ear amplifies this, and then somehow it goes into the inner ear, where there's a fluid-filled cochlea with hair cells. Certain frequencies can only reach specific spots due to the cochlea's geometric structure, allowing differentiation of pitch. Specific hair cells vibrate more strongly for certain frequencies, opening ion channels and sending signals to the brain, or something like that.
However, what I'm wondering now is whether it's really about the geometric structure or the fact that the hairs are of different lengths, thus having different natural frequencies, and frequencies that match their natural frequencies simply stimulate the right hairs through resonance? If that's the case, one can consider it similar to a forced oscillation, for example, when ultrasound reaches the hairs, we're far from the resonance case, so the hairs vibrate at ultrasound frequencies, but the displacement is extremely small, is that the reason they don't transmit signals?
How can I understand this? And if ultrasound stimulates the hairs to tiny vibrations, where does the rest of the ultrasound wave energy go? Do the hairs heat up, or do they simply reflect it (since in non resonance case the energy transfere between an exciter and oscillator isn't really good... try to excite a spring with a weight attached to it with a significantly faster frequency than its natural frequency from above, and you'll see that even when you wiggle it with high amplitude, the oscillator hardly moves from its position but only twitches faintly at your specified frequency, so same frequency but lower amplitude means the energy almost stays in the exciter itself)?
TLTR: Are vibrations in the ear stimulated at frequencies beyond our perception, and what is the reason we don't perceive them even when we increase the amplitude (decibels)? (And I'm referring to vibrations that don't originate through bone conduction, I've also read about this possibility.)

Hyperphysics has a good overview of human hearing from a physics perspective you may want to check out. It should clear up some misunderstanding you have.
First, the idea that hair cells in the cochlea are like strings that vibrate at their resonance frequencies is interesting and I understand how you would think that is what happens, but it is wrong. Each individual hair cell has 50-150 stereocilia linked together. When longest ones move, they pull on the second-to-longest ones, which pull on the third-to-longest ones, and so on until they all move. This collective movement is what triggers the nerves to fire and signal that a sound was heard. (source)
This leaves the question of what causes the longest sterocilia to move. The base of the hair cells are imbedded in the basilar membrane while the sterocilia are connected to the tectorial membrane. Both membranes are between fluid filled canals. This image shows the arrangement very well:

The basilar membrane had different physical properties along its length. For this reason, when a sound causes vibrations in the canals the basilar membrane only moves relative to the tectorial membrane at certain spots. The relative movement of these membranes causes the sterocilia to bend, which cause the hair cell to trigger the nerves.
Now that all of that is out of the way, we can finally answer the question: why does turning up the amplitude of ultrasonic sounds (i.e. sounds with frequencies above human hearing range) not trigger hair cells eventually? To quote a 47 page report on how humans detect ultrasonic sounds: "The impedance-matching function of the middle ear, necessary to transmit sounds from the outer to the inner ear, is known to be unable to handle ultrasonic frequencies (Pumphrey, 1950)." Literally all that stuff I just talked about is irrelevant. Ultrasounds are unable to be transmitted by the middle ear no matter how large the amplitude is. The only way ultrasounds could ever trigger the nerves is if they bypass the middle ear, such as by vibrating the bones of the skull.
That report's source does not elaborate on why the middle ear is unable to do this, but I found this paper that focuses on the middle ear as a physical system. From figure 3, we see that ultrasounds, which are above 20kHz, have extremely little gain from the middle ear, meaning they are barely transmitted at all:

Sidenote:
"Often, I read that it is written that energy depends only on amplitude" This is only true for electromagnetic waves. In mechanical waves, the energy is proportional to the square of the amplitude and the square of the frequency.

The "vibrating string" metaphor would apply to the basilar membrane rather than the individual hairs.


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Please help identify this tiny bug
Starting about 2 months ago I began seeing these tiny, light brown bugs in one bathroom. I did find them outside the bathroom but in close proximity to it (on a childs wooden toy and in our picture frames on the wall). I haven't seen them elsewhere. Most of the time I'd find them dead and they die very easily. I'd find small patches of them, usually under something or behind something with less light.  Otherwise I find them just moving a long the sink and find them in the corner of the tub. I have seen them on the wall and floor too. They can move fast but most of the time are still or slow moving. I haven't experienced any bites nor my family. The amount I see has lessened since I first noticed them.
I did get a pest control company out a month ago and they said it looked like field mites. Said they were harmless, attracted to moisture with a short life span and they'd be gone in a few weeks on their own. They haven't gone away though and when I research mites I find nothing that looks like it. It's too small for my phone to focus on so I took one to work and got a picture under the microscope. It's about 1 mm in length. Also, I do have a cat that goes outside.
Geographic location = Central Virginia, USA

Lovely picture.
This is quite likely to be one of the organisms known colloquially as "Booklice". In fact this is probably one of the genus Liposcelis, which is a genus of small wingless insects within the booklouse family Psocodea. They are common pests of stored items, including books, stored cereals, dusty areas etc, as they will eat almost anything of plant or animal origin.
I think I have the right genus here because of the enlarged top joint on the 3rd pair of legs, and prominent abdomen. Compare your image with the image below from wikipedia:

(Image copyright: MAF Plant Health & Environment Laboratory, CC BY 3.0 AU https://creativecommons.org/licenses/by/3.0/au/deed.en, via Wikimedia Commons)