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Why the "trailing" woodpecker sound?
I recently (March 26th, 2022) recorded a woodpecker in the woods around Habo Ljunga, Lomma, Skåne, Sweden and that gave me an idea. While cutting the audio, I noticed that the woodpecker's sound seems to have two moments (see waveform below): a main one (gray) and a trailing one (light blue).
Does anyone know why the sound trails off? I made several recordings and at least my subject woodpecker consistently features these two moments. If helpful, here is the original video showing the movement of the woodpecker.

It might be helpful to include more information about the species of woodpecker (if known), where it was recorded, and when.

Not sure this woodpecker is cutting. I think it is more likely signalling to it's potential mates and/or rivals.

@user1202136 I think your date is wrong, as today is April 24, 2022. At any rate, I have also heard this pattern in the US, but I don't know which species. The signaling hypothesis is interesting, as I've also heard woodpeckers tapping at a constant rate, and then stopping without trailing off.

I don't know anything about woodpecker cutting so hopefully someone more knowledgeable will answer...but could it just be that a woodpecker can't go from full speed to stopped instantly? It needs a little "slow down" time, where it stops full-force cutting and needs to oscillate a bit after to fully stop?

Comments are ephemeral and often overlooked, so in the future please [edit] your post to update it rather than tacking on comments. Please also clarify what you mean by "cutting" — several commenters seem to think you are talking about what the woodpecker is doing (usually referred to as pecking, drilling, drumming, or hammering), but I assumed it was something to do with your processing of the sound file. ——— Also, I strongly suspect that @selene is correct, but don't have time to properly research this myself.

in the UK we have two species of woodpecker that use drumming for communication.  One of these - the greater spotted woodpecker - tails off at the end of the sequence as it gradually slows and eases pressure.  The other species - lesser spotted woodpecker - stops much more abruptly, without this tailing off.  The difference between the two patterns allows you to determine which species you are listening to.
For examples of each, you can check out XenoCanto recordings here:
Greater: https://xeno-canto.org/719629
Lesser: https://xeno-canto.org/722816

Such a cool answer!

This isn't cutting, but rather part of their acoustic signaling behavior called drumming. This communication evolved from the foraging behavior of these birds. When foraging, the birds make less predictable patterns of striking their beaks against the tree when they locate insects from non-hollow trees. Over time, this evolved into an acoustic strategy by which males drum on hollow trees with predictable rhythms for territorial defense and mate advertisement. The drumming for communication is more rapid and precisely patterned compared to the drumming used during foraging. This reduction in amplitude towards the terminal part of their drumming, or the "trailing off" as you describe, has been documented for woodpeckers (see Budka et al., 2018 PLOS One) but hasn't been explicitly described. What's interesting is the duration of the "rolls" in a drumming can often be individual-specific (again, see Budka et al., 2018), suggesting that each bird might have its own set duration of how long it drums for.


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Why do eyes feel exhausted after reading on a computer screen for a long time?
Similar question before closing this one was: Question.
The answer holds true for most of the observations, but my observation differs from what is described in that question. Even if we consider that tiring eyes is due to the constant focus which creates stress in the ocular muscles, the extent to which eyes feel tired in the case of books/physical paper is lesser than that of display appliances.
Even if I keep screen brightness comfortably low, still there is a slight stress build up, which does not happen when I read a newspaper or something similar physically?
What is the exact attribute of computer displays which causes this? We have come a long way from those CRT displays and current imaging technologies offer realistic and immersive experience. Is it the refreshing frequency, which of the display which causes this stress?

Welcome lousycoder. Please take our [tour] and refer to the [help] for guidance. It's unclear to me if this will stay open as it's possibly just the wrong side of off-topic. I'd be interested in the answer anyhow. Not voting to close.

@ARogueAnt. The previously answered question has mostly answered my question. Could you please share why reading books is not tiring as watching displays even though both of them could be as near as 30-50 centimeters to the eyes.

If the nominated duplicate doesn't completely answer your question, you can [edit] and make it clear in what respect that's the case, it'll then enter the reopen review-queue.

source: Stack Exchange

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

sort: votes


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What does "DS" stand for in some articles?
I'm super ashamed of asking such a question, but there is an abbreviation that often comes in some papers that I have to read, I have no idea what it stands for and I'm just too ashamed to ask my colleagues... so here I am on the internet to try to find an answer (obviously English is not my mother tongue so it doesn't help).
Here is a figure I found in a paper. What does the "DS" stand for?

I've been trying to find out for hours now (using google and everything) but I'm really desperate. So I'm really sorry for the dumb question... but please help me, I feel so stupid. I thought that maybe it could be "day start" but I'm not sure, so any confirmation would be very welcome... Thanks in advance and I'm really really sorry for the completely uninteresting question.

Can you add a link to the paper? Sometimes the context helps to explain it.

Sorry, here is the link: https://doi.org/10.1038/emboj.2009.170
It actually appears in many papers and it's always related to time in hours...

I never heard this abbreviation, so it may be connected to this field of research. The article mentions "dry siliques", basically dry seeds (if I understand this correctly) which can be abbreviated DS and would be the starting point of the experiment. Does this make sense?

Not really, because it also appears in articles where no siliques are involved... maybe "dry seeds", but why using such an abbreviation on an axis that is indicating time?
But thank you for your answer, I'm glad I'm not the only one not knowing what it could be... even if we're still not sure of what it means, at least it makes me feel a little bit better about myself :)

At least it helped a bit :-)

Can you link to some other papers where you see this?

It may be an uninteresting question, but the emperor — or the authors of the paper —  are the ones that should be ashamed of their nakedness. Not you.

@canadianer: This one is another example, but the topic is closely related so it probably won't help: https://www.pnas.org/doi/full/10.1073/pnas.1012896107 ... I guess Chris was right when suggesting "dry siliques" or "dry seeds"... And also thanks David for making me feel even better about myself :) My shame is gone!

This paper says it is “dry seeds”.

Thank you so much canadianer! :) I'm happy :)

It could also stand for "Dormant Seed". I agree with David; it's the responsibility of the authors to define their terms.

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


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How can SNP arrays be used to detect deletions within a gene?
I am reading a journal paper where the researchers are studying the effect of disease-causing mutations in the IL1RAPL1 gene. In the first figure of this paper, they show pedigrees of families where they have family members with the disease-causing mutations.

For the BMC family, they found using a SNP array that a deletion of ~200 kb between intron 5 and 6 of the IL1RAPL1 gene results in an in-frame deletion of exon 6.
I am having trouble interpreting the graph in Figure D, which is the results of the SNP array analysis. Aren't SNP arrays used for detecting single nucleotide polymorphisms? I am confused because in this paper they are using a SNP array to detect a gene deletion.
Any insights are appreciated.

In the materials and methods of the paper, you will observe the following statement regarding the CNV (deletion) analysis:

CNV analysis was performed using CNV-WebStore (38).

That citation points to this paper, a software package designed to infer CNVs such as deletions from array data.
Recall that SNP arrays are essentially asking "how much DNA from the sample is sticking to each of N probes against specific sequences". The SNP is inferred by comparing how much DNA sticks to one allele vs the other allele on the array. If a specific sequence assayed by the array is simply missing, then you will observe a corresponding decrease in signal.
This is signified by panel D of the figure that you include, where signal in the pink region is dramatically lower.

The OP has asked many questions that could have been similarly answered by doing a little work — I think you are encouraging them to ask low quality questions by rewarding their lack of effort.

@tyersome perhaps a different aesthetic preference. OP has linked to a source, clearly stated their confusion, and pointed to specific items that confused them. They didn't know that "CNV" could mean "deletion", which I interpret as simple unfamiliarity with subject domain. They could probably get the answer with a ton of effort, but same could be said for many questions. I'm not a fan of question "quality" evaluation, but I'd still say it's upper 50% at least. I worry more about stifling curiosity than about encouraging low quality questions. Maybe I'm wrong; feel free to downvote.

It is possible that I'm being too strict based on the OPs failure to respond to past suggestions for improvements and frequent posting of questions that show no evidence of prior research. ——— As for downvoting, I only do that for answers that are actually bad (e.g. contain significant factual errors) and usually only if the poster fails to respond constructively to suggestions.


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Spectroscopic methods for quantifying peptides/proteins with or without Tryptophan or Tyrosine content
I have several peptides (20-50 amino acids long)  which I want to quantify the solubility/concentration in a solvent at certain temperature and pH.
These peptides may or may not contain Tryptophan or Tyrosine (aromatic residues) in them.
What's the preferred quantification method for it?
I came to UV-Vis method (e.g. NanoDrop) and Fluorescence method (e.g. Qubit).
Do those methods strictly require the presence of Tryptophan or Tyrosine?

I can’t write a full answer right now, but absorbance at 280 nm requires aromatic amino acids (tryptophan, tyrosine, phenylalanine) and/or cystine. If these residues are not present, you could potentially label your peptides with some fluorophore. Alternatively, the peptide bond itself absorbs at 214 nm. You can also look into assays like BCA.

@canadianer does fluoresence method also require aromatic residues?

If you’re just looking at intrinsic fluorescence of the peptide, then yes. If you are able to specifically label the peptide with some fluorophore, then no.

I suspect, but don’t know for sure, that the Qubit assay you linked to won’t work well for unstructured peptides. Thermo also sells a Qubit BR assay that apparently reacts with amino groups and therefore should work with peptides. You should ask them directly to be sure.

The A280 value is mainly due to Trp content but if the sequence is known, you can calculate the extinction coefficient very accurately. In addition, you can fully recover the sample after an A280 measurement, whereas fluorescent/colorimeteric methods require some sample loss. I give the key refs below, but this old answer (mine) may be of interest?

Protein volumes and hydration effects. The calculations of partial specific volumes, neutron scattering matchpoints and 280-nm absorption coefficients for proteins and glycoproteins from amino acid sequences

Calculation of protein extinction coefficients from amino acid sequence data

I think it would not be a problem if you use NanoDrop for your measurements. But there are better options if using UV-Vis is not a strict rule. Alternatively, Qubit itself doesn't have any issues since their reagents do not get interfered by aromatics.
As I understood from your description, you preferred using UV-Vis method, which uses wavelengths around 100-400 nm (UV-A 315-400 nm, UV-B 280-315 nm, UVC 100-280 nm). ThermoFischer provides two options for UV-band measurement using NanoDrop (Table 1 of NanoDrop Protein Quantification page), A280 and A205.
The usual A280 method is what you are concerned about, since its absorbance behaviour is strictly linked to tryptophan, tyrosine, and some disulfide bonds. This limits A280 only to protein samples with those residues. To avoid this issue, Anthis and Clore has developed a method of using 205 nm UV-band instead of 280 nm with promising results. You can choose the 205 nm-band method in the NanoDrop settings.
However, if I am not limited to measuring in UV-band, I would personally use Pierce 660 nm colorimetry method to measure my samples. This paper by Antharavally et. al. describes its flexibility on several substances (detergents, buffers, etc.) and its concentration which might suit your treatments. It is also available in NanoDrop settings, even with much greater sensitivity than both UV-Vis methods.
Speaking of Qubit, their BR (Broad-Range) Protein Assays are based on reagents reacting to N-terminals of proteins, not aromatic residues. There should not be a problem for any protein strands.

thanks so much. How reliable is Anthis and Clore method? Also for peptide that contain aromatic can be used?
With their tool https://spin.niddk.nih.gov/clore/ does that mean we can just skip performing measurement with Nandrop/Qubit?

Also, I only have Qubit 3.0 and Flex,  AFAIK I can't use BR. But can I use standard Protein Assays? Does it have any aromatic residue restriction?s

I need to clarify that Anthis and Clore's method of using 205 nm band is also available in the NanoDrop options.
ThermoFischer Protein Assays are quite robust on general protein strands. I don't remember their fluorophores are inhibited by aromatic residues....


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How do genetic variants of a gene moderate an association, leading to counterintuitive result?
I have run moderation analysis to study the interaction between SNP (dominant model) of a gene (A) with DNA methylation on cognition measures. For this, I have calculated the mean DNA methylation levels at 3 gene loci: Upstream of TSS (transcriptional start site), promoter, and gene body.
The protein from this gene improves cognition so we expect that increasing serum protein leads to better cognition outcomes. Prior research suggests that methylation in the gene body generally results in increased gene expression.
The results of the analysis showed that: in the carriers of genotype TT, increasing methylation rate in the gene body results in less recognition ability while in the holders of the C allele, higher methylation in the gene body is associated with improved recognition (2 different directions).
I know that different alleles can impact methylation rate but here the direction is completely opposite. How can I interpret the result?

The addition of a methyl group (groups) can activate or repress genes, do you have a reference that the expected result in this case is activation?

No, I do not have any data about the gene expression or serum protein level.

Can you refer to any data in general talking about gene body methylation's effect on gene expression? My feeling was that the effect was somewhat ambiguous and context dependent, but I'm not an expert. Especially in the absence of actual gene expression level for your gene of interest, it's hard to draw conclusions. Additionally, "the protein from this gene improves cognition..." sounds like a pretty squishy result. Cognition is a hard phenotype to measure usually. How large are the effects +/- error of the protein on cognition? What are the effect sizes / errors of alleles on cognition?

Thank you all. Why do you judge me? I am talking about the data I have obtained by analysis. They are not my personal idea! Still, I have not shown them to my supervisors. I wanted to improve my information before that meeting.

Fair enough. I apologise. We worry about presenting information to people that might harm anyone, it is a concern on many sites on the network. For example [worldbuilding.se] often gets questions about making explosives or poisons which creates concern. I'll delete those comments.


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If human CD8 T cell was injected intravenously into someone could it destroy the orexin receptors in the hypothalamus?
It seemed to have worked in mice https://www.pnas.org/doi/epdf/10.1073/pnas.1603325113
It seems like CDT worked its way into the mouse’s brain and destroyed the orexin receptors. Could this happen in humans too? Destruction of orexin receptors is what is believed to cause narcolepsy.
I want to test it in humans.

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

Welcome to Biology.SE. The answer would seem to be 'yes', which suggests that you might want to reformulate your question. Questions that ask "could this happen" or "is it possible" often aren't a good fit here since they tend to generate opinions. It might help to tell us why you care (context often helps clarify what sort of answer is useful). Please take the [tour] and consult the [help] starting with [ask] for details.

Okay thanks, I edited my question, hopefully it fares better.

Uhh, please don't test in humans?
O

Why would you want to do this? In addition to appearing to suggest something that would be extremely unethical (if not outright illegal), it sounds completely unproductive (and needlessly baroque if you do actually want to harm someone). I'm going to assume you aren't actually as monstrous as this makes you sound, but please take a step back and make sure you are expressing yourself clearly!

Uhh, please don't test in humans?
But conceptually, it should be about the same in humans.
That Bernard-Valnet PNAS paper presents evidence that these autoreactive CD8+ T-cells can trigger a narcolepsy-like phenotype in rodents, and it's widely accepted that a traumatic brain injury (TBI) can (probably pretty rarely) cause narcolepsy.
So, widespread death of orexinergic neurons probably can cause narcolepsy.
But it's not know whether that's a common cause.
An underlying cause (pathogenesis) could result in both idiopathic narcolepsy AND loss of orexinergic neurons.
In fact, Bernard-Valnet et al. say the same:

it is currently unknown whether autoantibodies precede or are the consequence of brain tissue destruction in narcolepsy

Though you might be able to give your human experimental subjects a long-term or permanent neurological disorder, it might not be the most useful model.


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Database of unique attributes of biological model systems
I am interested in deviations from standard eukaryotic biological mechanisms:

Sperm chromatin lacks nucleosomes, and are instead highly condensed by protamines. (most eukaryotic chromatin has chromatin with nucleosomes).
Camelid and cartilaginous fish antibodies are single-domain (most vertebrates have heavy chain + light chain antibodies).
Drosophila homologous chromosomes undergo transvection and are tightly paired. (Transvection is not usually observed in eukaryotes.)

These are some of the unique peculiarities I've found among model systems that deviate from "expected" biology. Is there a running database that catalogues unique attributes of different model systems? If not for trivia, I find them extremely inspiring for mechanistic studies!

I find this to be a very interesting question, but I think that it's critically important for you to be clear about 2 things: 1) what is the taxonomic level of focus? 2) for any given taxonomic level, what is the "expected" biology that is deviated from? I have edited to try to reflect this better.

No database that I've heard about. But you can add achiasmy to your list (absence of homologous recombination in some drosophilid and lepidopteran males). I've always found that intriguing and sometimes a useful exploit for genetic crossings.


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Is there a published calibration between footprint measurements to body length in moose?
I am in the early stages of designing a study involving a moose (Alces alces) population.
An often-true heuristic is that body parts of an animal monotonically increases in size. There likely exist counterexamples for certain choices of animals and body parts, but I think in the case I am interested in there is likely stochastic comonotonicity.
Assume that we see a moose's tracks (e.g. INat 112977489, INat 112971980, and INat 112971692) without the presence of the moose itself. The prints in the snow can collapse and distort footprints, but I am willing list those problems as limitations of the calculation. It is also the case that in the snow I do not necessarily get a flat print, which could lead to difficult-to-measure tracks either because it is hard to measure the depth of the toes as holes or that the toes appear shorter than they actually are. In some cases I will apply interval arithmetic to any calculations when I think the size of the track is roughly guessable. Often the front hooves are measurable, and rarely the posterolateral dewclaws. Anyway, my point is not to go through all of the problems, but just to show you that I am aware that even on the face of it this is an analysis that requires assumptions and tentativeness.
What I am looking for is a published mathematical function that I can plug measures on the footprints into and get estimates of the body length out.
$$\operatorname{Body Length} \approx f(\operatorname{Footprint Measurements})$$
Such a relation would probably be dependent on whether the moose was a juvenile, an adult female, or an adult male. But even a marginal relation might be useful. I don't care if the relationship is in a particular choice of units as long as I can convert back to metric.
Has anyone fitted (and hopefully evaluated, etc) such a model?

Related: https://biology.stackexchange.com/questions/107876/how-much-does-dry-moose-scat-weigh-and-vary-in-dry-weight

And this paper? https://www.jstor.org/stable/1937779?seq=3

@bob1 I am getting a 404 Error with the link to the thesis.

I think I found it based on details in the URL: Lundmark 2008

Correct. Lundmark is the one for that. I've deleted the comment as it turns up 404 for me too. Worked when I copied and pasted, don't know what happened in between.

Yes - I found a paper published in 1978 by Franzen et al "Alaskan moose measurements and weights and measurement-weight relationships" 1
In this paper they looked at a number of parameters and found that they were all correlated with body weight:

A total of 1329 Alaskan moose (Alces alces gigas) were measured for total length, 1340 for
chest girth, 1317 for hind foot, 618 for shoulder height, and 1219 for ear length. Five hundred and
four moose were weighed.  ...

...All body measurements were significantly correlated with weight: total length, r (correlation coefficient) = 0.94; chest girth, r = 0.90; shoulder height, r = 0.87; and hind foot, r = 0.81

There are some nice tables and plots with data over age (in months) and separated by sex, as well as combined data.
1:  Albert W. Franzmann, Robert E. LeResche, Robert A. Rausch, and John L. Oldemeyer. Alaskan moose measurements and weights and measurement–weight relationships. Canadian Journal of Zoology. 56(2): 298-306. https://doi.org/10.1139/z78-040


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Suggestion on program/algorithm to segment nuclei
I've got some images such as the one in this post, obtained from the neuroepithelium of a chick embryo in a confocal microscope, where nuclei have been fluorescently labeled. I'd like to be able to segment these nuclei, in particular to see their total area (which means I don't necessarily need them to be separated) and to count them. I tried using StarDist on Fiji, but I've obtained some very bad results, with it detecting basically no nuclei.
Does anyone have any suggestions on what I might do?
Here's a link to the original image in tif format: https://drive.google.com/file/d/1GqsUI-xnTPSKnRv_ECxJL7K785_qbq2c/view?usp=sharing
Below there's a comparison of my original image(above), with the StarDist output with low probability/score threshold and low overlap threshold (middle) and with default settings (below). Previously, default settings would output a completely black image, but it seems to have changed.

Welcome to SE Biology. It would be useful to see your best 'bad result' from StarDist and maybe a link to a tiff version of the image.

Thanks, I've edited the post with the extra information

The "Analyze Particles" function in FIJI might work.
You will run into a few problems in any entirely automated analysis because your image isn't even brightness across the image; the corners, especially the top and bottom right are substantially dimmer than the rest of the image. You might need to play with the balance of brightness to compensate in any analysis that you do. You could also cut the image into chunks and process each separately, but you might run into the problem of counting bits of the image more than once.
For the Analyze Particles function you need to

Convert your image into binary (Process>Binary>Make Binary)

Watershed (Process>Binary>Watershed); this draws lines across narrow parts of the image, creating a "watershed" (like water running off a ridge between mountains)

Analyse particles (Analyze>Analyze Particles) - play with the conditions in the pop-up window. It'll output a table with all the results, a summary page and, if you set it, an overlay window (I've shown ellipses here, but there are a few options).

I'd recommend working out the minimum size of your nuclei (I got roughly 6 pixels) and using that as the lower bound in the size setting, and working out the circularity of the objects to help get rid of small/inaccurate counts. You should also set the overlays (from the show: drop-down in the analyze particles window) - ellipses might be your most useful and comparable to the ones in your posted analysis. It will help you set the conditions for your final analysis.
I've had a go with your fairly small TIF image and it isn't great (see images above) - partly because of the resolution of the image, which is only 1 micron per pixel. If you have a higher resolution image, it should work better with a high resolution image. I got about 300 particles with min size set to 6, but this includes all the objects shown in the overlay (step 3). You might want to further filter out the smaller results manually before statistical analysis.

+1 Good answer. I've run across this need to automate counting of things (mitochondria and nuclei and synaptic boutons...) before, so often, in so many different labs. Just use FIJI/ImageJ and play around with settings and try to find parameters which are reproducible and sensible to others ( = have someone else tune the parameters independently and see if yours are similar). Surprisingly I have never heard of a better approach than FIJI. You'll have the advantage of using something open-source. Always report the parameters you set, it's good scientific practice. Good luck!

Thank you very much!! You approach gives pretty good results at first glance. The problem here seems to be that most nuclei exhibiy a "hole" in the fluorescence, which are kept by the watershed algorithm. That said, I've thought of another (more complex) way of calculating this and will be comparing both methods! I'll be trying to obtain better images of course, but this was a first approach to the problem. Thanks again for your trouble!

@SantiagoBosch I noticed the holes in the nuclei and tried the Process>Binary>Fill Holes option, but it just combines all the nuclei that overlap in the middle of the image, and it doesn't work after watershed. You could try really increasing the brightness + contrast of the red image (Image>Adjust>Brightness+Contrast), then process to binary, but I don't know if that will work either.

@SPr I guess because IJ/FIJI have been designed for scientists by scientists working on the same problems as us, and it is free + open source, it makes it an ideal tool, and someone will have come across your application or something similar in the past and worked out a solution. You can also automate most of the processing using IJ fairly simply (as you can in photoshop etc) if you care to learn a little bit of programming in Macro or Java.

Fiji have a machine learning segmentation utility (WEKA). it's simple to train and use.

@heracho That sounds like the beginning of an answer - we welcome additional answers here so long as the answer the question, and I'd love a better solution than mine as it is definitely flawed

I'd really urge you to look into machine learning for this task.
You can probably get away with classical image analysis for an 80/20 solution on a particular image set, but it will be a lot of work getting there and it probably won't generalize very well.
In particular, I've had good success even for difficult cases (eg where nuclei touch or where only a subset of nuclei were to be counted) with U-Net based segmentation: In such cases, to count nuclei, I've trained U-Nets not really to segment but to place a dot on each nucleus.
Counting dots you get a very good approximation of nucleus count.
See here for details.
In order to get area, shape, intensity... as well, it can be useful to train an algorithm to segment an image into three classes: background, object (nucleus), and border.  This way, you'll mitigate the problem of touching regions which makes it difficult to tell apart different objects in the segmented image (see here).
Oh, and there are plenty of solutions out there, these days, for training machine learning algorithms without having to know much about how they work.
Full disclosure: I'm one of the developers of one of these solutions, VAIDR.


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A level 2022 Biology percentage increase question

In January 2022 WBI12/01 they asked:

9c. In 1963, there were only three males and 12 females of
C. hoodensis left in the wild.  These 15 tortoises were used in a
breeding programme.
ii.The wild population of C. hoodensis is now 1800 individuals.
Calculate the percentage increase in the wild population of
C. hoodensis tortoises.  Give your answer to one decimal place.

I did the calculation 1800-15
(new-original value)
Then divided the difference by 15 (the original value) times 100 and got 11900.0%
But the mark scheme says
1800-15 = 1785
(1785÷1800)x100% = 99.2%
So I don't understand why they divided by the new value 1800, not the old one 15, since this was a percentage increase calculation.

I’m voting to close this question because, in addition to being a "homework"question — see link for an explanation and expectations, it is not primarily about biology as defined in the [help]. Please take the [tour] and consult the [help] starting with [ask] for details.

15 to 1800 is a 11,900% increase (= form A)
or
12,000% of the initial 15 (= form B).
They asked you for a percent increase, so they want the answer in (A) form.
The correct working:
Take the new value 1800, divide by the original 15, and multiply by 100 to get a percentage: (1800/15)*100=12000 and thus you have a percentage answer in form (B). From this, to get form (A), subtract 100 at the end to get a percentage increase: ((1800/15)*100)-100=11900.
You have to remember to distinguish forms A and B. To illustrate, 100% of 10 is 10, and 11 is a 10% increase from 10 (form A), but it is 110% of 10 (form B).
In other words... the marking scheme is woefully wrong. It claims the correct percentage increase in the wild population is 99.2%. That means it's below 100% increase (i.e. below doubling). A 100% increase from a starting 15 tortoises means there would be 30 tortoises. Not 1800. So the mark scheme is hilariously incorrect.


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How does HIV assemble its capsid correctly?
HIV’s capsid is very unusual. The capsid is made of around 1200 identical CA proteins (p24). These CA proteins first assemble into either pentamers or hexamers, which assemble into a fullerene like polyhedron containing 12 pentamers at the vertices and about 200 hexamers filling the bulk. Compared to other viral capsid, HIV’s capsid is unusually big (with an equivalent triangulation number of T=1200/60=30) and highly asymmetric. Instead of a perfect icosahedron made of 20 equilateral triangles, the edges are of different lengths (as well as the h and k numbers https://viralzone.expasy.org/8577) in HIV’s capsids, and even two HIV can have slightly different capsids.
It should be difficult for such complex structures to be assembled correctly because the structural environment is very different among the subunits. For viruses with small and symmetrical capsids, the symmetry is guaranteed by the fixed binding angles between subunits (because the structural environment is equivalent everywhere). More complex viruses can encode multiple types of capsid proteins taking different positions. For example, the capsid of poliovirus can be modeled as a soccer ball, with each pentagon made of 5 VP1 and each hexagon made of 3 VP2 and 3 VP3. However, HIV’s capsid is solely made of CA, which means the very same CA need to adapt to the highly variable structural context. Some complex viruses like herpes viruses encode scaffold proteins to guide the capsid assembly, which is unlikely true for HIV as HIV’s capsid is self-assembled. Despite its irregularities, HIV’s capsid is perfectly sealed off, which is unlike murine leukemia virus with large gaps in its capsid (https://www.pnas.org/doi/abs/10.1073/pnas.1811580115?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed). How can the seemingly simple CA proteins assemble into such complex structures accurately?

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300640/

How capsids self-assemble isn't fully known for any virus, but it's been studied a lot and there are a number of principles we can apply. First, HIV isn't as unique as you assume. 30 is a fairly large triangularization number, but Faustovirus has T=277, and Mimivirus is estimated at over T=1000. The conical shape of lentiviruses is indeed very unusual, but if we look at how that shape is constructed, it seems less exotic. Hexagons can tile infinitely on a 2D plane or cylinder. However, if a hexagon is replaced with a pentagon, the tiling is distorted such that the plane becomes curved. The geometry works out so that replacing 12 hexagons in a lattice with pentagons will create an enclosed shell, regardless of size. If the pentagons are evenly spaced, the shell is an icosahedron. However, many bacteriophage build a cylindrical region between two half-icosahedral endcaps, with 6 pentagons at each end. This type of capsid is called "prolate", and the well-known T4 phage uses it, as well as the elongated "corndog" phages shown below:

Negative-stain transmission electron micrographs of the C. crescentus phage phiCbK and five phiCbK-like phages. All five exhibit Siphoviridae morphology and prolate heads. Scale bars are 100 nm.

The conical capsids of lentiviruses like HIV have a similar geometry to these corndog phage, except the two endcaps are asymmetric; with 7 pentons at one end and 5 at the other. If HIV was like many large icosahedral viruses and encoded different proteins for the pentons, arranging them correctly would be difficult. However, the current theory is that the overall geometry is imposed on the maturing HIV capsid, and CA protein simply changes into a pentameric arrangement where the local curvature of the immature lattice is too great for hexameric arrangement. From Unclosed HIV-1 Capsids Suggest a Curled Sheet Model of Assembly, referencing Nonequilibirum Assembly, Retroviruses, and Conical Structures:

Levandovsky and Zandi used tapered triangular prisms to represent CA units and were able to recapitulate spherical, conical, and tubular shapes.26 Tapering caused growing sheets to curve, and as the curved sheets grew, inclusion of pentamers became necessary to relieve accumulated stress. Opposing edges of the growing sheets eventually curled around toward each other and connected and then the top and bottom ends sealed. Conical shapes therefore emerged not as a result of template interactions or membrane enclosures but through simple nonequilibrium growth of elastic sheets.

The overall shape of the CA immature lattice before the conical core forms is guided by two forces that mimic the "scaffold" proteins used by other viruses. These are the outer membrane and the inner RNA payload, to which CA is stuck via the MA and NC subunits of the Gag polyprotein, respectively. This figure from Assembly and Architecture of HIV illustrates how the constraints of the membrane and RNA leave the Gag units organized in a way that allows the CA units to organize into the required shape once they are cleaved free:

Wow, mathematics is beautiful. I didn’t know that a fullerene structure is always enclosed no matter how the 12 pentons are spaced. It is now clear that the perfectly enclosed capsid of HIV is quite natural for fullerene structures, while the gaped capsid of MLV is unnatural and may need some mechanism to disrupt its continuity.

The formation of pentons is also very interesting. I once thought that CA proteins first assemble into hexamers and pentons, which then assemble into capsids. But there is a serious flaw in this model. A capsid contains 200 hexamers and only 12 pentons, which means the equilibrium should strongly favors hexamers. However, a slight fluctuation will greatly change the number of pentons. If pentons are not enough the assembly will fail. If there are too many pentons, they may compete with each other.


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Is it possible for prion-infected meat to be processed safely (such as in Soylent Green) and still provide some form of nutrition?
I watched Soylent Green again today, and it's clear that our understanding of the health effects from cannibalism have improved since filming. Since then, we have now already experienced first-hand a localized epidemic as a result of the outbreak of Mad Cow Disease in the United Kingdom. Morality aside, any such product could cause the suicide of Humans as a species, due to the systemic spread of incurable and fatal disease from the ingestion of misfolded proteins.
It's already known that these proteins cannot be destroyed through the normal cooking process, and can survive temperatures of over 600 °C. I've read that it would require, by temperature alone, up to 1,000 °C to destroy prion infectivity.

Incineration of prion-contaminated material is considered the most
effective method of disposal. Combustion at 1,000°C can destroy prion
infectivity, however, low infectivity remains after treatment at
600°C. Despite its effectiveness, incineration may not be a
practical solution, such as during a large outbreak of BSE, scrapie or
CWD requiring a mass culling. Incineration of contaminated soil,
vegetation and farm infrastructure (paddocks, fences) to eliminate CWD
or scrapie environmental infectivity is also not practical.

I am not a biologist, and I don't know anything about food preparation or nutrition. But I am curious as to whether Soylent Green as a concept would even be possible. For example, if temperatures must reach the point of incineration, then any form of nutrition and other desirable proteins would effectively be destroyed as well. The remains would become carbonized, which wouldn't leave anything of nutritional value.
I thought about asking this as a science fiction question, as it is dystopian in origin, but I'm interested in the biology of the problem, as it exists in reality. I also think that it would be somewhat inappropriate to ask this on the nutrition stack exchange, for obvious reasons.

I believe your question is: "Is there nutritional value in protein after exposure to temperatures of 1000 C?" "Prion-infected" is the motivation for the 1000C figure, but otherwise is irrelevant to the question, isn't it?

Nitpicking, but what you refer to as a pandemic of mad cow disease (properly known as variant Creutzfeld-Jacob Disease or vCJD in humans and Bovine Spongiform Encephalopathy in cows) was only an epidemic (localized to one area rather than world-wide).

No.
There are two processes that we need to consider.
First off: incineration at 1000 C (1832 F) in an oxidizing atmosphere will result in almost total destruction of the material. Carbon based material, such as protein, will likely be mostly converted into CO2 and water (ignoring the amine groups, sulphur groups). Calcium based substances (bones, teeth) will be significantly damaged and some residual material will be deposited as ash, similar to the remains you get from a cremation. There is no nutritional value in these remains other than some mineral content, certainly no energy value (i.e. food value).
Secondly. Pyrolysis. In a non-oxidising atmosphere (anaerobic, or in the absence of oxygen), you get something called pyrolysis, which results in permanent chemical changes in the substances treated that way. I had a look through the literature for pyrolysis of meat and it is commonly used to dispose of remains from meat processing plants/slaughterhouses, especially meat-and-bone meal (the stuff formerly fed to cattle, causing the spread of Bovine Spongiform Encephalopathy in the UK). A common theme is that there are several remains from pyrolysis carried out at 500 C (932 F) - a solid material, a liquid oil, an aqueous phase, and gas.
Typical output (from A. Chaala and C. Roy1)

and in summary of outputs and uses (ibid):

The process generated oil, gas, a solid residue, and an aqueous phase. The oil, which exhibits a high heating value of 34.2 MJ/kg, can be used alone or mixed with petroleum products as a fuel in boilers or gas turbines. However, the presence of nitrogenated compounds may cause some environmental problems if the oil is used alone. The complex chemical composition of the pyrolysis oil allows it to be potentially used for various applications, for example, as a softener for polymer processing and as an additive for the fabrication of well drilling mud. The gas with its calorific value of 12.9 MJ/kg and the burnable aqueous phase can be cofired to provide heat to the vacuum pyrolysis reactor. The solid residue can be used as a fertilizer, a moisturizer, an adsorbent, a filler for road bitumen, or a solid fuel in cement kilns.

Long story short: no nutritional value left after heating to the sorts of temperatures used for destroying prions.
1: A. Chaala and C. Roy Environmental Science & Technology 2003. 37 (19), 4517-4522. DOI: 10.1021/es026346m. Reprinted with permission from American Chemical Society.

Removal of prions in organic material by thermal degradation completely destroys the organic material. However, prions can also be digested by some enzymes, particularly keratinase, under relatively mild denaturing conditions. The resulting short peptides would retain their nutritive value. From Enzymatic Formulation Capable of Degrading Scrapie Prion under Mild Digestion Conditions:

An enzymatic formulation combining N22 keratinase and biosurfactant derived from Pseudomonas aeruginosa degraded PrPSc at 65°C in 10 min to undetectable level

A study of protease digestion of infected brain homogenates under milder conditions (50°C and pH 9.6 for 2 h.) showed partial digestion of prion protein PrP reduced infectivity more than proportionally. From High CJD infectivity remains after prion protein is destroyed

In contrast to PK, NAP digestion left 0.8% residual PrP after 2hr, yet decreased titer by >2.5logs; few residual protein bands remained. FU-CJD infected cells with 10x the infectivity of brain by both animal and cell culture assays were also evaluated. NAP again significantly reduced cell infectivity (>3.5 logs).

Another study looked at the penetration of protease into actual meat and bone meal (MBM), which is the ground-up scraps of butchery refuse that was banned for use as livestock feed after the BSE epidemic in the UK. This study is the most relevant to preparing potentially prion-infected tissues for consumption, but they don't actually investigate changes in infectivity. From Diffusion of Protease into Meat & Bone Meal for Solubility Improvement and Potential Inactivation of the BSE Prion:

Results showed that surrogate distributed in bone particles was more susceptible to degradation than that in soft tissue particles. Three factors controllable by unit operations in an industrial-scale process were also tested. It was found that removing the lipid content and hydrating MBM prior to incubation both significantly increased the rate of surrogate degradation. In a test of particle size, the smallest collected diameter range demonstrated the largest degradation of the prion surrogate, suggesting milling would be beneficial.

So, by grinding up everything into tiny pieces, removing the fat content, then treating with enzymes, it may be possible to reduce transmissions to levels that are acceptable in your hypothetical cannibalistic dystopia.

Good answer. However, you'd want to be pretty certain in your processing that you had gotten rid of all the PrP before consuming - undetectable in their sample doesn't mean that it would necessarily be eliminated completely, just to the limits of the assay! I'm guessing instead of Soylent Green you would have some sort of nice nutrient broth left over - Matrix style!


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Why would E. coli cultures suddenly start to slow down?
My E. coli cultures used to take 13.5 hours to reach stationary phase. I have not changed any of the parameters like temperature, shaking speed, media formulation/components or inoculation volume. However, the cultures now take 15.5 hours to reach stationary phase. What could be causing this issue? Is there any chance there is a phage/fungal contamination in the lab?

Fungal and phage contamination could both be checked by plating the culture. If you see plaques or multiple colony morphologies, you have your answer

If you resolve your question experimentally @JohnFlamour, please be sure to answer your own question here so that others can learn from your experience!

Are they sequential, you may have a mutation.

Several questions that might help diagnose the problem. How are you standardizing your inoculum? Using overnights or colony suspensions can be less consistent than back diluting from log-phase growth, leading to variable lag times. Are you starting from the same freezer stock for each experimental replicate, or just using subcultures? Subcultures can accumulate mutations. Has the maximum growth rate changed as well, or just the time to reach stationary? If it's contamination, I would expect the max growth rate to change (mutations from sub culturing could also cause this).

Have you considered the culture that you are using as inoculum is old and less active, resulting in a longer lag phase?


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Why is the sex ratio of male and female cats close to 50/50 (with males actually being more prevalent)?
According to this study from 1970, cats are about 50% male and 50% female. Furthermore, there appear to be about 100 male pedigree cats born for every 92 female cats.
I couldn't find any info about sex ratios for cats that aren't adapted to live closely with humans. My understanding is that female cats occasionally live in colonies and work together to guard each other and their kittens. Female cats who do not live in colonies still hunt for themselves and their own offspring and protect their offspring.
Male cats...impregnate female cats?
It would take very few male cats to keep the species going. It seems like male cats don't do anything else beneficial to the species besides donate cat sperm to the females who take it from there.
I am wondering why, from an evolutionary perspective, so many male cats would continue to be born.  Is this purely for genetic diversity purposes?

Don't forget that while species evolve, it is individuals that are acted on by selection. Individuals that are successful cause more of their genetic material to be present in the next generation.
Your question is addressed by Fisher's principle.
For an example, imagine you do have a scenario like you describe, where there are fewer males and more females. Let's say, 90 females and 10 males. In the next generation of 100 cats, each female is responsible for on average 100/90 ~= 1.1 offspring per female cat. However, each male cat is responsible for on average 100/10 = 10 offspring per male cat.
Now, imagine some female cats produce 50:50 males:females, and other female cats produce all females. The latter group will have 1.1 x 1.1 ~= 1.2 grandchildren; the former will have (1.1 x 1.1)/2 + (1.1 x 10)/2 = 6.1 grandchildren. In a world where males are rare, it pays to be a female that produces male children.
These are some extreme examples, but in general you'll always have a pressure towards balanced sexes as long as both sexes are required to produce a child.

I remember figuring this out in SimLife many many years go.  You can start out by setting the organism to have a skewed ratio, but over time, they evolve to go to 50:50

Thanks for writing such a concise and clear answer! It seems so obvious now


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The numbers of chromosomes during Meiosis
There is something about the numbers of chromosomes that doesn't make sense to me:
Let's take this illustration:

So a gamete has 23 chromosomes, which are haploid (have only one chromatid), is that correct?
Before meiosis it replicates, so now we have 23*2, i.e 2n as in the first left picture where it is written "Parent cell (2n)". Then I don't understand how is it formed in a tetrad. Where do the additional two come from. Also in the start we have 2n (after replication) and in the end after two divisions we have n for each gamete  of the total 4, so its total of 4n, what do I miss ?
Otherwise the first left picture is before the replication of the chromosomes, but then why are there 2n in a gamete cell, isn't it just 1n as in the end of the process ? Isn't the parent cell also a haploid with just 1n chromosomes with just one chromatid (because if it is before replication, it looks like a diploid cell).

see also: https://biology.stackexchange.com/questions/55832/what-is-the-purpose-of-two-cell-divisions-in-meiosis

I would recommend looking more closely at the image. I would suggest that it is in fact 1n. Those are two different chromosomes, not copies of the same chromosome, in the gametes.

Why do you think the parent cell is haploid?

@BryanKrause, that how it happens in humans, isn't it ? Meiosis is a cell division process, which happens from one cell to four or am I wrong ? I should be haploid isn't it ? Sex cells are haploids (gametes) in humans by definition.

@Ilya.K. Which cells in your diagram are gametes, and where do those gametes come from?

@BryanKrause, well it isn't said in the diagram itself, but meiosis is relevant only in gametes. Could it be that the parent cell isn't a gamete and the daughter cells are ?
The daughter cells are gametes for sure, the parent cell logically assuming must be too.

Getting closer :) Where do gametes come from, and what is the purpose of meiosis?

@BryanKrause that's probably the part where my knowledge is a little bit unclear. Where do they come from : I'm not sure, like they it's a differentiation thing, each cell in the body has the whole genome set (but it differentiate by the set of actual proteins generated by the appropriate rna instructions) , which means I think that each cell in the body from one hand has the whole 23 chromosomes, but in gametes as much as I understand the chromosomes are complected each from only one chromatid, and no two, because they are haploid cells and not diploid. I've probably mistake anywhere here.

@BryanKrause, the purpose is cell replication, like part of the life cycle of the cells.

@BryanKrause, are you trying to tell me that to create gametes, we need the diploid cell, which the parent cell is ? I think our lecturer didn't told us that part. Like who is the parent cell ? Cuz in the second image I've just posted, it is obviously said that from one pair of chromosomes (a pair means it is diploid and has one chromatid from male and one from female) in the parent cell we get 4 haploid gamete cells.
It's only makes sense if the parent cell is diploid. But who is it if not a gamete (and it can't be gamete) ? Like it can't be skin cell or some other tissue cell, can it ?

Yeah, I think you've just about got it. After fertilization, a typical human cell has 46 chromosomes, 2 copies of 23 chromosomes, with caveat that one of the pairs is the sex chromosomes which can be XX or XY. We call that a diploid, 2n cell, and there are 2 copies of each because one copy came from an egg gamete and the other copy came from a sperm gamete. Those 2n cells divide and divide to make all the cells of the body via mitosis. To make gametes, though, you need to make 1n cells; meiosis is how that happens.

The cells that give rise to gametes through meiosis are called germ cells; that's pretty much their job, simplifying things a bit. As far as "Like it can't be skin cell or some other tissue cell, can it ?" - as the wikipedia article describes, it depends - for animals, you're right, they're particular cells. For plants, they come from otherwise ordinary cells, a bit like making gametes from skin cells, yes, just in the right place at the right time.

@BryanKrause, thanks, that's a good point been clarified.


text:
What is evolutionary advantage of Spirogyra to be multicell?
Spirogyra is just a set of cells connected to each other; it has no leaves, roots, etc... It even doesn't have multiple layers of cells like Hydra. So what is evolutionary advantage for Spirogyra cells to connect to each other? Why not to live separately like Chlorella?
P.S. I think this question is different from this one: Why do some bad traits evolve, and good ones don't? The reason is that I don't see that connecting cells to each other is "bad trait". If anyone can argument that such connecting is obviously "bad trait", they are welcome to write it in comments or in answer.
I think it is obvious that been multicell is advantage, but the advantage primarily is ability for organism to combine cells of different types that perform some specific tasks better that 'universal' cell of single cell organism. So, there are no question what is advantage to be multicell for apple tree. But spirogyra looks like something unusual for me. It has multicellularity (in my understanding it is actually very ancient organism), but what is advantage of this trait?
We can of course imagine that multicellularity is "bad trait" here, and that organisms similar to spirogyra became just "evolution raw material" like dinosaurs became ancestors of birds. But this idea doesn't look correct for me, I think we have to dig deeper here. We see that colonies of similar cells are widespread and spirogyra is not the only such organism. We have also Volvox, and Cladophora is more complex but shares the same idea. So, such organisms are too widespread to be "evolutionary error" in my opinion.
From comments I can see 2 ideas:

It is more complex to eat such organism.
Such organisms can attach to the substrate.

These ideas may be correct. BTW what is advantage to attach to the substrate? Many even single-sell species can do that (for example, Vorticella).

Well, the hairs catch onto objects well, might be harder for predators to eat.

well to start it is harder to eat a long strand of cell than a singe cell.

Does this answer your question? Why do some bad traits evolve, and good ones don't?

@tyersome I have no idea whether it is good or bad to be multicellular, so the link may or may not be the correct answer. I thought about that last days when I shew Spirogyra in microscope to my children, so I asked may be there is obvious answer that biologists know; I am computer programmer myself.

If you have "no idea whether it is good or bad", then why did you ask what the "advantage" is? If there some subtle distinction you are trying to make can you please clarify. ——— One of the problems with this type of question is that they assume that there must currently be an advantage and ignore the huge influence of contingency of evolution. You may find this, introduction to evolutionary theory from UC Berkeley to be of interest.

@tyersome I ask because I want to investigate ;) I added more thoughts to question body to explain the details.


text:
What does this statement pertaining to fission mean?
I was reading about fission on Wikipedia when I encountered the following statement under Fission of prokaryotes section.

Like in mitosis (and unlike in meiosis), the parental identity is lost.

What does 'parental identity' mean here?
From what I understand it to be, it possibly means that the parental form is no longer present after mitosis as it is divided to form new individuals in the process, thus the 'parental identity' is lost. If I am right, isn't parental identity lost in meiosis also?

You're right, this makes no sense or at least is misleading. It seems the edit was introduced in March 2019, after another mistaken edit that suggested parental identity was preserved in binary fission.
I agree with Douglas that this phrase "parental identity" seems to have been invented in some study guide, so I wouldn't dwell on it. It does not seem to be used by scientists in science. From context, though, they seem to intend to distinguish with budding, where you can clearly identify one cell as the (larger) "parent", and the other distinctly as a "daughter" copy. You can tell which one is the parent, aka, "parent identity" is preserved. In binary fission, there is no such asymmetry, and you can't really consider either cell the "parent" of the other.
With respect to meiosis, the editor may have been thinking of genetic imprinting where the parent is marked in gametes epigenetically, but this doesn't have much to do with "parental identity" in terms of cell division. The only similarly is that people do use "parental identity" to refer to chromosomes marked by whether they came from the female or male parent. I think the author just got confused by reading that term in two places, not realizing the meaning was totally different, and trying to make sense of the two together. Wikipedia is great and I rely on it a lot as a basic reference that anyone can use, but this is one of the occasional examples where it falls short!

In fission, each daughter cell gets a full copy of the parental genome. But "parental identity" doesn't seem to be a standard term.

What does 'parental identity' mean here?

You're not alone; I don't get it either. At first, I assumed it was jargon specific to molecular biology or microbiology.
But, parental identity doesn't appear to be a standard term in biology.
A Google search returns exclusively online study guides, textbook exercise answers, and your own question :)

From what I understand it to be, it possibly means that the parental form is no longer present after mitosis as it is divided to form new individuals in the process, thus the 'parental identity' is lost.

Though I don't know what exactly was intended, I think the author meant the genetic material, not the cell body. That is, "parental identity" is said to be "preserved" if the daughter cell contains a complete copy of the parent cell's genome.

If I am right, isn't parental identity lost in meiosis also?

In both cases, the cell bodies are split -- so, yes.
But meiosis results in very different genetics.
In both fission and mitosis, each daughter cell (2 total) retains a complete copy of the parent cell's genome. But in meiosis, each daughter cell (4 total) retains only half parent cell's genome.
(This distinction is the ploidy of the cells.)


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Sickle cell anemia IS inherited in an autosomal recessive pattern, but sickle cell trait IS NOT inherited in an autosomal recessive pattern?
It's all about the alleles of the hemoglobin beta gene. Sickle cell anemia is inherited in an autosomal recessive pattern, which means that both copies of the gene in each cell have mutations.
Those who are heterozygous for the sickle cell allele produce both normal and abnormal hemoglobin so the inheritance pattern of the trait is considered to be codominant . Two different types of relationship between the same alleles. Why?
I think it is because in the sickle cell anemia the important thing is:
To determine whether the individual is 'HEALTHY' or 'SICK'. But in the sickle cell trait we go deeper and are concerned with the presence of 'NORMAL' or 'SICKLE' RBCs inside the body. Did I get it right?

• HbAHbA: Healthy (only normal RBCs can be seen)

• HbAHbS: Healthy (Both normal and sickle RBCs can be seen)

• HbSHbS: Sick (Only sickle RBCs can be seen)

As you can see here, the inheritance pattern for anemia is an autosomal recessive pattern, but for the trait the pattern is codominance. The question is: Why are there two different types of relationship between the same alleles?
Consider this question:

What is the type of relationship between the normal and mutant alleles (which causes sickle cell anemia) of the hemoglobin beta gene? Autosomal recessive pattern or codominance?

Can one choose one of the options? I think this question is vague. Because if the sickle cell anemia was mentioned, the answer would be autosomal recessive pattern. But if the sickle cell trait (the presence or absence of sickle RBCs) was mentioned, the answer would be codominance. Isn't it so?
Edit
With thanks to Bryan Krause, I searched a little more and saw this in Wikipedia just now.

The sickle cell trait can be used to demonstrate the concepts of co-dominance and incomplete dominance. An individual with the sickle cell trait shows incomplete dominance when the shape of the red blood cell is considered. This is because the sickling happens only at low oxygen concentrations. With regards to the actual concentration of hemoglobin in the circulating cells, the alleles demonstrate co-dominance as both 'normal' and mutant forms co-exist in the bloodstream. Thus it is an ambiguous condition showing both incomplete dominance and co-dominance.[citation needed]

Before this, I believed that only two phenotypes can be seen in HbAHbS individuals: Normal RBC and Sickle-shaped RBC
But now I doubt it. Is there one more phenotype? A red blood cell that is not normal nor sickle-shaped but rather something in between? A red blood cell that is sickled incompletely? Is this phenotype really observed, studied or defined scientifically?

Comments are not for extended discussion; this conversation has been moved to chat.

These phenotypic dominance terms you learn in school - autosomal recessive/dominant, co-dominance, incomplete dominance... these are all just descriptive terms based on phenotype that become somewhat irrelevant and outdated once you have a better molecular understanding of what exactly goes on with different alleles of a gene. If none of them apply well, that's fine, because the real world doesn't follow these basic rules.
For sickle cell anemia, the serious form of the illness, the inheritance is more or less autosomal recessive, as you say. Those with two abnormal copies of the HBB gene have symptoms; those with one copy are generally symptom-free.
However, at a cellular level, it turns out that both normal and abnormal versions of hemoglobin exist. If we define co-dominance as "contributions of both alleles are visible in the phenotype", then at an intracellular level, the phenotype is co-dominant. That said, these terms are typically used at the organismal level. After all, patterns of dominance in Mendelian inheritance far pre-date any understanding at the molecular level of these things. It's very typical for traits considered to be recessive at an organismal level to show measurable differences at a molecular level in heterozygotes, yet these differences are compensated for (such as via feedback loops in gene expression) such that the phenotype isn't observed.
If we look carefully, though, even at the whole-organism level, sickle-cell carriers (heterozygotes) don't have exactly the same phenotype as those who are homozygous for the normal HBB allele. Heterozygotes are considered as having the sickle-cell trait. They're somewhat less sensitive to malaria, but there are also some associations with cardiovascular comorbidities and signs of sickle-cell disease in adverse conditions such as dehydration, especially at high exertion in athletes. Incomplete dominance describes a heterozygous phenotype "distinct from and often intermediate to the phenotypes of the homozygous genotypes". Note in this definition the word distinct and the qualifier often intermediate. There is no stipulation that the heterozygous phenotype needs to be precisely in between the homozygous phenotypes, or even that it has to be between them at all rather than somehow orthogonal, it merely must be distinct. This seems to me like the best description for sickle-cell inheritance overall, though it may be harder to follow in a pedigree as the heterozygous phenotype may not be obvious enough to recognize in every carrier.
If you have to pick one for a multiple choice question, incomplete dominance is the most comprehensive answer, but all three of these are potential answers if you constrain the parameters of the problem. It's far less important to be able to assign these particular labels, though, than it is to understand what actually happens with a sickle cell allele.
Some more quotes from Wikipedia:

The sickle cell trait can be used to demonstrate the concepts of co-dominance and incomplete dominance. An individual with the sickle cell trait shows incomplete dominance when the shape of the red blood cell is considered. This is because the sickling happens only at low oxygen concentrations. With regards to the actual concentration of hemoglobin in the circulating cells, the alleles demonstrate co-dominance as both 'normal' and mutant forms co-exist in the bloodstream

I disagree a bit with the next sentence in Wikipedia, though:

Thus it is an ambiguous condition showing both incomplete dominance and co-dominance

I don't think it's particularly ambiguous, it's just necessary to either define what level of analysis you're making the statement about or to recognize that none of these terms are entirely sufficient to describe the complexity that exists in biology.

Defining two different titles for this (codominance and incomplete dominance) seems ironically unnecessary to me now. But it made sense back then because as you said, "Patterns of dominance in Mendelian inheritance far pre-date any understanding at the molecular level of these things."


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Mechanism for switch of embryonic stem cells from "fast" cell cycle to "normal" cell cycle?
It is well-known that embryonic stem cells have a fast cell cycle (very roughly about 12 hours), while typically normal cells have a much longer cell cycle (very roughly about 24 hours).
Of course, it is not only the duration that is different, but there are many papers describing  differences between cell cycle regulation for normal and stem cells.
Question: What is known about "switch" mechanisms from the the fast cell cycle?
For some cancer cell lines in our research we see that certain drugs can switch from "fast" to "normal" cell cycle patterns - we also want to understand the mechanisms by that can happen.

This review (doi: 10.1534/genetics.118.301643) states that:

Cell cycle progression in the early embryo is likely driven by a single CDK (CDK-1) in association with B-type cyclins. In support of this, the alternating S and M phases of the early cleavage-type embryonic cell divisions do not require CDK-4/cyclin D or CDK-2/cyclin E kinase activity (Boxem et al. 1999; Boxem and van den Heuvel 2001)

It makes sense that the absence of a regulatory checkpoint (CDK2 and CDK4) accelerates cell cycle. It's like skipping security at the airport to get to the airplane faster.
So maybe that switch that you're looking for is connected to CDK2 and CDK4 taking control over cell cycle checkpoints.
Please note that this work was done in Caenorhabditis elegans, but it seems that cell cycle regulation is conserved in eukaryotes, since studies in mice (doi: 10.1073/pnas.1115201109) have shown that "Knockouts of Cdk2, Cdk3, Cdk4, or Cdk6 have resulted in viable mice", while cdk1 leads to embryonic arrest.
I know from my own research that myelomas dysregulate cyclins like crazy. So you might want to start there.

Welcome to Biology.SE. This looks like it might be a good answer and you've done a nice job of providing some supporting references. However, please include the complete reference information since links can break. One easy way to get that information is to search for the paper on Google Scholar and click on the ‟ symbol to get reference information. This is a good example of how to format references. ——— Also, can you please clarify what the "it" is referring to in "This confirms it, since ..."?

Thanks for the edit and the tip! Is providing the doi enough? That solves the 'link-might-break' problem, doesn't it?

You're welcome and thank you for editing — that is much clearer! Using a doi is certainly good, but my personal (possibly old fashioned) preference is for complete citations as they: 1) contain useful "meta" information that allows users to make a quick check for plausibility/reliability (e.g.s: Is this a recent publication? Was it in a journal with a good reputation?) and 2) can only be "broken" by destruction of both the internet and all the paper copies of the sources ...

Would you be so kind to give refrences to your research on: "myelomas dysregulate cyclins like crazy " ?


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mendelian inheritance calculating probabilities help
In a recent exam our teacher gave us the following questions:

Assume that D, E, F, G, H, and I are autosomal genes on different
chromosomes. From the mating (parent A) DdeeFfGGHhIi x (parent B)
DdEEFFGgHhii:
a. What is the probability that one of the offspring
will have the genotype DdEeFFGghhIi?
b. What is the probability that
one of the offspring will be heterozygous for each allele?

Is there any way of answering these questions without drawing a super large Punnett square?
Thanks in advance for helping out.

You need to understand that each locus follows a law of independent assortment. This means, each probability of combinations are multiples of the probability of each element. For example, Dd x Dd goes by

DD (1/4) : Dd (2/4) : dd (1/4)

and Ff x FF goes by

Ff (2/4) : FF (2/4)

If the case is DdFf x DdFF, it is

DDFf (2/16) : DDFF (2/16) : DdFf (4/16) : DdFF (4/16) : ddFf (2/16) : ddFF (2/16).

You can verify my countings by making a Punnett square. However, notice on the first case, the probability of DDFf is basically DD * Ff itself, 1/4 * 2/4 = 2/16. So as others.
To solve your problem, use Punnett squares (or just directly doing it with no issue) for each of the locus. Like this:

Dd x Dd -> DD : Dd : dd
ee x EE -> Ee
Ff x FF -> Ff : FF

What is the probability of having DDEeFF?

DD * Ee * FF -> 1/4 * 4/4 * 2/4 = 8/64

Try this on the question asked. Remember, solve smaller Punnett squares, and multiply for your desired genotype
Good luck!

The hint that the loci independently assort comes from being on separate chromosomes. If they were close together on the same chromosome we would strongly suspect dependence. If the on different chromosomes was absent, I would suspect that the exam wants me to assume independence but I might be temped to include Fre'chet bounds anyway.

I see, @AgnesianOperator. In the case of nonindependently assorting genes, we can opt to genetic linkage. If so, there would be usually two types of questions, First, calculating each probability with genetic distance information in centimorgans. Second, determining the genetic distances between loci from an observed distribution table.
Fre'chet's inequalities are something interesting, but I have not been updated that it is used in genetic mapping or genetic analysis. I would search for more if I missed it.

Yes, using centimorgans is fine if you know the conditional probability of recombination given centimorgans. Haldane's map is an example that might be suitable for a student exercise. I think we agree that in an empirical research setting the data distribution must be considered.

The Fre'chet bounds work for any probability distribution, so they certainly apply whenever we are considering recombination probabilities. Their main limitation is that they can be conservative; the price of assuming very little. If you can make more assumptions about the probability function, then sometimes you can put tighter bounds on the joint distribution.


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Paternity testing using gel electrophoresis
When using gel electrophoresis to determine the father of a child, each band of the child must match with either the mother or the father. So half must come from the mother and the other half from the father. However, that does not seem to be the case in the picture below, where does the band 6 come from?

Perhaps the actual father is not included in the tested group?

Can you confirm or deny that "1" is actually the child's father? An explicity description of what is shown on the gel would be helpful here. Can you think of any explanations other than genetics for unexpected bands on gels?

This is a very bad question for a scientific site because it contains no explanation of what is being subject to electrophoresis,  not even whether it is DNA, and certainly not how it has been treated. When this question was posted originally this information should have been demanded of the poster. Certainly the question is unanswerable from the information given. It should be closed.


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Is 50Hz noticably worse for eyes than 60Hz on a 4K monitor?
I was told in ux.stackexchange that this question is better suited for biology.stackexchange, so, here we go ;).
I have a 50Hz 4k monitor (28 inch and using 1920x1080 scaling - so, the text is super smooth and pixels are non visible from my 90 cm distance as I sit) but I can't set it higher to something like 60Hz.
Does this equals to some problems long term or the 10Hz difference is not something I should be worried at all?

Welcome. Why would any refresh rate be harmful to your eyes?

@AliceD people have different views on this topic. A lot of people say higher refresh rate is easy on eyes. That indirectly says 60Hz is less good for your eyes. See this https://superuser.com/questions/302415/is-60hz-refresh-rate-as-bad-as-i-believe-it-is The discussion in comments is not clear.

Also, the more I read that higher refresh rate like 120Hz is easy on eyes, why we still have 60Hz monitors? They would potentially be straining eyes more for maybe half of the customers?

Yes, flickering can cause eye fatigue and headaches, but 50Hz vs 60Hz would only be relevant if your 4K screen was built in the old CRT technology, which certainly not the case.
Todays screens do not flicker at the refresh rate frequency, instead you should check the backlight flicker, which is, sadly, not always disclosed  by the manufacturer.
Read more at: https://www.rtings.com/monitor/tests/motion/image-flicker


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Does your body type affect the rate at which you age
Out of the 3 body types: ectomorph, endomorph and mesomorph, does one age quicker/slower than the others or does it not matter so much?
There are many factors that affect the rate of ageing, but I'm just wondering if body type plays a role.
I've read that humans age slower due to a slower metabolism, so does that mean that ectomorphs have, on average, live longer or is there something about endomorphs that means they live longer?

Welcome Pencilcase. We are expected to show the results of our own investigations into a subject here, you can [edit] to tell us what your searches found and where the sticking points are. You should also take our [tour] and refer to the [help] for guidance as to the ways of any site you post on. Enjoy the Stackexchange network.

The term endo/meso/ectomorph just describe shape, vaguely. These are not strict nor scientific definitions. Your question would be better posed by asking whether BMI, body muscle percentage, fat percentage, height or weight affect aging. I would also advise you to define what you mean by 'aging', which itself is poorly understandable. Do you mean life expectancy? Do you mean actual well-being (what kind?), or the incidence of specific aging diseases?

Hello, thanks for answering!
I'm not a biologist but I think by ectomorph I mean people with a high metabolism and a lower percentage body fat and by endomorph I mean someone who puts on weight easier and has a slower metabolism (so generally a higher fat percentage.)
I heard that the reason why humans age slower is due to a slower metabolism and I want to know if that means ectomorphs live longer than endomorphs or if there's something else at play.
And by ageing, I mean how quickly it takes for damage to accumulate (eg: does one experience more inflammation or take longer to repair)

@Pencilcase I have never heard words like 'ectomorph', 'endomorph' and 'mesomorph' used in a scientific sense. Even whether such things as 'body types' exist is doubtful.


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Why isn't the Ramachandran plot symmetric?
Since only relative position of groups along a bond is considered while calculating torsional strain and considering "+" and "-" means clockwise and anti clock wise rotation, shouldn't any set of $\phi$ and $\psi$ angle say (x, y) satisfying the energy consideration have correspondingly (-x,-y) since they are relatively the same configuration? But only the Ramachandran plot for glycine shows this symmetry, see below, why doesn't this show for all the proteins?

Not what you are looking for per se, but note that the Ramachandran plot is a field over a subset of $\mathbb{R}^2$. Such a field will have a parity decomposition which relates to reflection invariance (symmetry) and reflection equivariance (i.e. odd "symmetry").

Welcome to SE Biology. However . I can't understand your question as it stands, and I've published papers with Ramachandran plots in them. To explain something like this you absolutely need a diagram and you need to explain exactly what Ramachandran plot you are referring to. (And please do not give links to common terms from Wikipedia — we don't need to know what glycine is, but a plot of glycine in some context showing symmetry would help.)

Wikipedia has a Rama plot of glycine. Is that representative of the symmetry you mentioned?

@AgnesianOperator yes

but only the Ramachandran plot for glycine shows this symmetry

With the exception of glycine, all the common amino acids exhibit chirality at the carbon atom adjacent to the carboxyl group.

Except for glycine, the amino acids exist as chiral molecules in two forms, the L- and D-enantiomers. Although the two enantiomers exhibit identical physical and chemical properties, living organisms use only amino acids of L-chirality.

Jeong, Y., Kim, H.W., Ku, J. et al. Breakdown of chiral recognition of amino acids in reduced dimensions. Sci Rep 10, 16166 (2020).

+1 I thought of this but wasn't confident. In principle if we switched the left-right handedness of each chiral center, would we expect to see the reflection of the original Rama plot on the Rama plot of the reflected molecule?

That sounds correct to me.

It's awkward answering your own question, but I think I have now realized where my misconception arose from.
If we look at the 3 dimensional structure of a protein

and consider the third alpha carbon to visualize. Let us take phi and psi as (x, y) and (-x, -y), then the groups associated with nitrogen and carbonyl carbon attached to alpha carbon are relatively in same configuration for both (x, y) and (-x, -y) but here we are missing to consider the relative configuration of groups attached to carbonyl carbon and nitrogen with respect to the group attached to the alpha carbon, since if a clockwise rotation of psi brings the oxygen attached to the nitrogen closer to hydrogen, then the anticlockwise rotation will bring the oxygen closer to the side group, thus clockwise rotation and anticlockwise rotation of phi or psi is not symmetric when considering it with respect to the alpha carbon. Since the alpha carbon of glycine has another hydrogen attached to it instead of a side chain both clockwise and anticlockwise rotation become equivalent leading to a symmetric graph.
If we say that (x, y) is stable for an L- amino acid chain then (-x, -y) will be stable for D- amino acid chain (we can imagine this as R and H on alpha carbon switching places for L and D amino acids, thus the once stable counter clockwise orientation for L- amino acids will now have to be clockwise for D-amino acids for it to be stable again)

It's awkward answering your own question - actually it's encouraged! If you find an answer to your own question otherwise, please include it as an answer.


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Why is the process of releasing gametes in females different from that of males?
In context of humans, males produce sperms, store them (for few weeks? then regeneration?) and ejaculate them "on demand" but females can not do that. Females have an almost fixed pattern of production and release of ova leading to menstruation most of the times (menarche to menopause).
I know release of ovum is accompanied by some additional "preparations" for possible conception.
Why could nature/evolution have not "designed" the reproductive system in females similar to that of males eliminating the need for menstruation?

Production and release of ova during pregnancy could have been regulated (like milk in mammary glands) by hormones to prevent multiple pregnancies.

I guess it has something to do with the time taken to "prepare" the body for possible conception and, production time and survival time limits of ova and sperms.

Each individual optimizes the probability of offspring carrying their genes. Anatomical and behavioral optimization between sexes contribute to distinct strategies used between different sex.

I guess it has something to do with the time taken to "prepare" the body for possible conception and, production time and survival time limits of ova & sperms.

True. This is the hypothesis of any mating cost.
We need to understand two concepts. First, every investment has a cost (of offspring being dead). Second, every individual wants its genes to survive and propagate.
Consider a case of a mammal mating. We currently understand that the embryo will stay inside the womb for longer times inside the female. That means, what are the best chances a female can raise an offspring?

make numerous ovums that has equal chance, or
sacrifice numerous ovum contents, but one to form a single stable ovum?

The latter option would be better, while the former option allows the mammal to rear as much as possible, if the offspring die before birth say 50%, that will cost a whole lot of survival opportunity for the female. The latter is much clearer, we can get an almost good guarantee the offspring will at least be born alive.
Now, comes to a unique part. Since females can only have extraordinarily little amounts of ovums, would accepting weak sperms do the math above? Of course not. That's why some female mammals observe sexual selection, either by copulatory structures or behaviors that could indicate weak and strong males.
However, the need of females to preserve their genes hinders the males' effort to preserve their own. How is that? By selecting males, there would be less chance to fertilize the ovum. Remember, males need topreserve their genes. Which option will give the best chances, considering the females' investment above?

just one sperm, just one mating
copious amount of sperm, multiple mating

Even a single sperm would not be guaranteed entry to the ovum, why should consider the former? The latter would be better. Since females will always raise their offspring, mating multiply and with much more sperm content will increase the chances of the females' offspring will be the males'.
This is just a surface of the evolutionary basics that drive the mating behavior. In fact, both contribution and behavior will drive each other, resulting in complex behaviors such as Lek mating, or even paternal care.
I suggest you to read books about evolution and animal behavior such as Futuyma and Dugatkin. If you want to understand quickly, read Unit III of Futuyma. But try to read it from A to Z, both are great introductory books on the logic and hypothesis of evolution and behavior. After reading those books, you can read more research papers about mating cases you find intriguing. (If you want the quickest takeaway, see the TL; DR)
Good luck!


text:
Image sensitivity of eyes and peripheral vision
I have bad eyes and need glasses. However I have noticed when it is dark, I am able to see contrasting colours a lot better in the corner of my eyes, than in the center, e.g a mark on my wall I can't see if I look directly at it, but I can see it at the corner of my eyes.
I have also noticed that the light in my kettle appeared to flash on and off in the corner of my eyes, but when I look directly at it, it doesn't blink at all.
Slow motion imagery on my phone shows the light IS indeed blinking.
So what specifically about human eyes allow for these effects? If it was simply blurry then I would just account that to lack of focus of light. But surely the refresh rate of my eyes (to see flashing) is constant?

While I understand what you are asking, I think you are asking three questions at once. Can you plase clarify what is the main question being asked? Peripheral vision, the cases you experience, or the refresh rate of your eye?
Also, I wish there would be clearer grammar and statement. I am having a tough time understanding your third sentence.

Does your kettle use LED by any chance? If so, those certainly blink on AC power, basically lots of on-off as the waveform passes through. Why the eye see it as steady is something for you to research.

I would say the main question is about what causes the effect in my kettle, and the specific relation as to why I can only notice it when looking at it through the corner of my eye.

Yes the kettle is an LED, i know WHY it blinks. But  not as to why the difference in my perception of it varies with the location on my eye.

I think we can agree that the faraway star we see mostly twinkles, or pulses when seen by our naked eye. Since you stated that the kettle LED is also blinking, both are the same cases.
You are experiencing what is called averted vision. Our eyes have 2 different cells that can sense light: cones and rods. Cones are adept in seeing colors and mostly concentrated on an angle centre to the eye (the fovea). The rods, however, are contrast sensing and more concentrated around the the periphery of the fovea.
Cones are simply great in distinguishing color, while the rods are great in detecting brightness. This affects what you are seeing in dim or dark locations: since there is not enough brightness to be sensed by your fovea, the cones can't distinguish really good. The rods around the fovea, however, are doing just fine. This is the reason you can see details while "tailing" using your eye. In fact, amateur (and ancient) astronomers observe faint stars by using their peripheral vision.

stars twinkle because of the atmospheric turbulence which gives the same effect as a haze mirage on a hot road.


text:
Where does the silica found on grass and other plants come from?
Grass has tiny silica "teeth" on it called phytoliths:

I have trouble understanding how can a plant possibly extract silica from soil and form anything out of it. Silicon dioxide is used for chemistry glassware and can survive nearly anything.
I found that what the plants use is actually monosilicic acid in the form of $Si(OH)_4$, but I have not been able to find how that comes to be in the soil in the first place. Clearly, silicon dioxide does not hydrate in water readily the way potassium oxide does, for example, otherwise glassware would not be a thing.
And even if I knew how does the hydrated form of the oxide form, I still do not understand how do the plants manage to dehydrate it in order to prevent it from being water soluble.
Can someone explain the whole chain from $SiO_2$ through $Si(OH)_4$ back to $SiO_2$ that can be seen in the picture above?

Does this help? https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2435.12704 Keyword to parse the paper: "dissolved Si (DSI),"

Silica $\neq$ silicon dioxide! So the chain is: silicon dioxide $\left(SiO_2\right)$ to orthosilicic/monosilicic acid $\left(Si(OH)_4\right)$, which can then polymerize to form silica particles, see image below.
The first step in the chain occurs via reaction with a basic solution (e.g. aqueous sodium hydroxide, $NaOH$). The resulting $Si(OH)_4$ is water-soluble, and thus can be taken up by organisms. Enzymes such as silicatein can then catalyzes the reaction to form silicate particles. These particles can then be deposited in specific parts of the organism. See Otzen's 2012 review in Scientifica for more information.

Could you clarify the difference between silica and silicon dioxide please? It seems that it's crucial part of the problem.


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Why does the sympathetic nervous system constrict in heart failure?
As I learn about heart failure in medical school, we are consistently taught that one of the compensatory responses to heart failure (and the accompanying reduction in cardiac output) is for the sympathetic nervous system (SNS) to activate. While this has myriad effects, one that is described in most cardiac pathophysiology textbooks (eg, Lilly) is that the activation of the SNS causes peripheral vasoconstriction, raising the systemic vascular resistance (SVR).
However, I don't understand why the body would do this.  The underlying problem in HF is a reduction in cardiac output (either due to diastolic or systolic failure). Raising SVR (using the cardiac equivalent of Ohm's Law: Pressure = CO x SVR) would either a) cause cardiac output to drop, holding pressure constant or b) force the heart to generate more pressure to generate to maintain a constant CO. Both seem like poor responses to a failing heart. So why does the body do this?
Put otherwise, if I had independent control over every hemodynamic parameter in the body and I was confronted by a failing heart, my solution would be to increase HR and contractility (which the SNS does), but to vasodilate the systemic arterioles to lower resistance and thus (by Ohm;s Law once again) reduce the pressure the heart would need to generate in order to drive the same amount of flow as prior to the heart failure. Why is this a bad idea?
I think there are some preliminary questions that might help clear up my confusion. They are probably very basic, but I think they will help clear up the confusion I face.
A. Why is blood pressure (specifically mean arterial pressure, measured at the aorta) important to maintain? The goal of the heart is to maintain tissue perfusion, which seems to me to be function of the volume of blood which gets to a certain organ.
B. Does the body regulate blood pressure or cardiac output? If both, which takes priority?
I think if I understand these two questions, I might be able to better understand why the body reacts the way it does to heart failure.

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.

This is basic physiology. The human body doesn't "think" or know/reason; it reacts to stimuli. If the CO is low, it basically reacts the same way in an attempt to normalize BP regardless of the cause (e.g. hemorrhage vs. CHF). This is also why ACE-inhibitors are used in CHF, because the body doesn't "know" why BP is lower than normal.

Perhaps it's related to the physiological results of drowning, which also causes cardiac arrest, which appear to be of the same type. In that case, you can research the reasons for the physiology of conservation of oxygen in response to drowning, which is an ancient nervous pathway that exists in nearly all terrestrial vertebrates. Perhaps there is some research to do on the specifics of that.

Best try a medical forum, this is generalist so a lot of genetics/ecology/microbiology folk here.

@LifeInTheTrees - Nit-picky, but there are also a lot of medical people here, including physicians and people who teach medical students (I've been both). This kind of question is very basic and will likely not be answered by a medical professional. A medical forum might be better, but a medical student forum might be best.


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Shape of the first leaves of a plant
I am quite unfamiliar with everything that is in the slightest related to biology,
so I am very sorry if this question does not meet your standards and is too basic.
Lately I am quite enjoying growing some plants from seed and watching them grow.
Doing this I noticed that, at least for apples and tomatoes, the first 'pair of leaves' looks quite like different from the leaves following. Especially for the apple,
the first two leaves look like from a completely different plant.
So just out of curiosity, is this a general phenomenon and how can it be explained, i.e.
why do these plants do it?
Thank you in advance for any reference/ hint/ answer!

They are referred to as cotyledons (seed-leaves).
Apples as specified in the question are dicotyledons, they have two seed-leaves. Some other plants are monocotyledonous, i.e. just have a single seed leaf, thus:

User: Pengo, via Wikipedia CC BY-SA 3.0 2022.
The cotyledons are a part of the embryonic plant and whilst inside the seed capsule store energy in the form of starch (e.g. in oats and barley) and or fats/oils (e.g. in nuts). They are a distinct form from the mature leaves which grow as the plant matures.
They are also present in the seed prior to fertilisation, as distinct from true leaves which develop later after germination.


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This looks like it was somebody’s home - but who?
Found this near the edge of a forest in upstate New York. It looks like the remnant of a cocoon of some kind. I would appreciate any help in identifying its original maker / occupant.
I hope my fingers give a reasonable indication of scale - estimating about 30 mm across.

looks like a tiny loofah!

That looks similar to the dried fruit of Echinocystis lobata (wild cucumber), which grows throughout New York. The fruit is about the right size (~3 cm) and shape, whereas the best alternative I can come up with is smaller and differently shaped (Sicyos angulatus (burr cucumber)).
I'm confident that this is something in the cucumber family, but there could be other related plants. If you had images of dried vines/leaves associated with your specimens it might help confirm this or suggest alternatives.

Source: iNaturalist (© Robert D Stevenson).

Source: Dylewski, Ł., Maćkowiak, Ł., & Myczko, Ł. (2018). Physical defence of the wild cucumber Echinocystis lobata in an invasive range changing seed removal by rodents. Plant Ecology, 219(7), 863-873.

We do have some vines growing in the area where I found this. Thanks for the quick and thorough reply!

@Floris: You're welcome — if you can get pictures of the whole plants later this year (especially with details of the flowers, fresh  fruits, leaves, and stems) it would be helpful to edit them into your question.

good recommendation- if I see these things growing (rather than the skeleton on the ground) I will surely do that.


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Are animal whiskers a useful monitoring tool?
I have come across studies that have used stable isotope values from seal/sea lion whiskers to infer foraging ecology. However, I am also aware that whiskers can fall off and then grow back. Is there a way to determine the age of a specific whisker, to verify the timeline stable isotope samples represent? E.g. if a sample is taken every x mm that correlates to the foraging ecology y years ago.

theforestecologist might have a great answer for this. For me, one wait is to feed harmless radioisotope carbons during a specific observation time. If you can regress one way to another the rate of whisker growth, then I would be probably feasible

Whiskers have very similar science to other hair follicles. You need to specifiy the types of whiskers, rat, seal or tiger whiskers?

I expect that vibrissae growth rate would depend on the species, the type of vibrissae, time of year, etc. One paper that comes to mind is Zhao & Schell 2004, which estimated growth patterns of harbor seals (Phoca vitulina) using labeled tracers:
https://www.int-res.com/abstracts/meps/v281/p267-273/. I am sure there are other papers that have studied pinniped vibrissae growth rates. I recommend a more specific search using Google Scholar.


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Apparant inconsistency in DNA topology theory in formation of origin of replication
I'm studying an introductory course in genetics and came across something I don't fully understand. I obviously used Google to find where I'm thinking wrong, but I still can't understand it.
To catalyse strand separation, a negative supercoil is introduced due to the binding of DnaA-proteins, so the strands aren't being broken to form the supercoil. This means that the linking number must stay the same. Due to the negative supercoil the Writhe is decreased by 1, and thus the Twist must increase by 1 (because Lk stays the same).
A higher twist means that the DNA strand is overwound. Meanwhile my Textbook says this negative supercoiling implies underwounding.
Where am I wrong in my thinking?

Does this answer your question? https://biology.stackexchange.com/questions/54059/why-is-compensatory-negative-supercoiling-generated-in-a-positively-supercoiling/