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Location of genes encoding ribosomal proteins
I have cited two sources below: the first, a textbook, says ribosomal proteins are imported into the nucleolus (from the cytoplasm) where initial ribosome assembly occurs.
The second is a journal which asserts, in the first paragraph, that ribosomal protein mRNA is processed in the nucleoplasm, distinct from the nucleolus.
I am therefore very curious about the location of ribosomal protein genes whose transcript is the mRNA; specifically whether these are located in the nucleolar region or not.
Sources:

"Histology a text and an atlas" by Michael H. Ross and Wojciech Paulina. 6th Edition; pg. 79.

"Nuclear and Nucleolar Targeting of Human Ribosomal Protein S6" (Carola Schmidt, Edgar Lipsius, and Joachim Kruppa) ; Vol. 6,1875-1885, December 1995.

This is a previous answer to a question on this topic. It references a review of the topic with a poster that summarizes the situation. Of course all proteins in eukaryotes are translated in the cytoplasm, so any proteins that are required in the nucleus have to be reimported.

@David, I'm afraid that doesn't answer my question. I am interested in knowing whether the genes that encode the mRNA which then gets translated into ribosomal proteins are part of the nucleolar region or not.

Ok. Look at the distribution of ribosomal protein genes across different chromosomes. Massively diverse. Why would you expect the genes in the nucleolus if the mRNA has to go to the cytoplasm? It’s the rRNA transcripts that need to be in the nucleolus and the ribosomal proteins etc. to move there from the cytoplasm after synthesis.

Ok. This helps.


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What causes midcycle FSH surge in the menstrual cycle?
I have encountered contradictory attributions to the causal factor of midcycle FSH surge. Whereas some sources attribute it to the relatively high estrogen levels (1), others say it is because of increasing amounts of progesterone (2).
I am confused.
(1) http://www2.hsc.wvu.edu/som/physio/classes/pcol260/classroom/notes/reproductive.htm
(2)
https://www.ncbi.nlm.nih.gov/books/NBK279054/#!po=1.17188

The positive feedback observed pre-ovulation in the gonadotropins FSH and LH is regulated differently in different species, but the current evidence in humans suggests that the increase in estrogen past a critical threshold is the driver of the surge in LH and FSH (to a lesser extent).
This textbook chapter by Marques et al. provides a great overview of the regulation of GnRH and gonadotropin secretion, and I've summarized the relevant parts below.
Kisspeptin is a peptide secreted by hypothalamic neurons that has recently been identified as the peptide responsible for the positive and negative feedback effects of estrogen*. It stimulates GnRH-producing neurons, and has been shown to produce elevations in both LH and FSH in humans. Further, both antagonists and null mutations for Kisspeptin have been shown to block the LH and FSH preovulatory surge in animal models.
Besides ref. 2 in your post, I have not been able to find any recent references, either within the text you linked or otherwise, that state that progesterone is "responsible for the FSH surge."
*: This answered a long-standing "missing link" between estrogen and GnRH production, because although the feedback effects have been established since the 80s, the specific mechanism was unclear because GnRH-producing neurons do not produce estrogen receptors and therefore can't directly respond to ovarian estrogen during the menstrual cycle.

source: Stack Exchange

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

sort: votes


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Can Inositol triphosphate (IP3)-mediated Calcium release on its own cause membrane depolarization?
This is about smooth muscles.
I know that the Voltage-operated Ca²+ channels on the smooth muscle membrane can be opened by membrane depolarization to threshold. I also know
that this depolarization in question can be brought about by opening of receptor-operated calcium channels on the plasma membrane.(1) What I am curious to know, however, is whether the Ca²+ released into the cytoplasm (sarcoplasm) when say IP3 binds to its receptor on the Sarcoplasmic reticulum can (on its own, without any other thing happening) cause depolarization of the membrane potential to threshold and subsequently lead to opening of
the Voltage-operated Ca²+ channels on the muscle cell plasma membrane.
I am asking this because most often, the IP3-mediated Calcium release is discussed almost entirely as an accessory pathway for Calcium release, being only able to supplement an existing Calcium current.
(1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652144/#!po=4.24837

The membrane potential is not determined by ionic concentrations but by ionic permeability, so I would assume that it doesn't change.

Oh! Yes. You're right

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Can convergent evolution be used to explain similarity of genome of low and high Species e g. gorilla and human?
Example: 1) molecule Rhodopsin in halobacteria for producing energy from light. 2) molecule Rhodopsin for vision in human. These are said to be of different lineages and their high similarity are due to convergent evolution. Obviously then over long lapses of geologic and pre-geologic time, as the saying goes, things may be evolving to a best or most efficient at least in the particular case. So I'm wondering, much is made of the similarities of genomes of high  and low Species to "prove" man is descended from the lower species. But could not the acceptable concept of convergent evolution, in general, be used to explain the similarity of say the genome of an ape and that of a human?

For each of 20,000 genes arranged in the same way?

there are no higher or lower species, gorilla have several advantages over humans, like a much higher genetic diversity.

Because there are usually many different possible molecules that can perform nearly identical functions, it is possible but unlikely that two independent evolutionary lineages will end up with exactly the same molecule to perform the same function.  If molecule A1 and A2 perform the function FA in lineages 1 and 2 respectively, and molecules B1 and B2 perform the function FB in lineages 1 and 2 respectively; and if the probability that A1 is identical to A2 is PA, and the probability that B1 is identical to B2 is PB, then the probability that both lineages use the same molecules respectively to perform function FA and FB is (PA)(PB): the product of the two probabilities.
Let's say the probability PA is 0.01 and the probability PB is also 0.01.  Then the probability that the two lineages will have identical molecules respectively for each of the two functions is (PA)(PB) = 0.0001.  Go through the same exercise for just ten such functions, and the result is the product of all ten probabilities: (PA)(PB)(PC)...(PJ) = $10^{-20}$, a VERY small number.  So the likelihood of convergent evolution occurring on the molecular scale over a significant portion of the genome is negligible.
On the level of phenotype, though, convergent evolution is much more likely.  Different molecules and different development trajectories can produce phenotypic structures that perform closely similar functions and can even resemble each other closely.  Consider for example the wings of bats, birds, and insects.  The phenotypes can be similar, but at the genomic level there is very little similarity.
The conclusion to be drawn is that IF there is close genomic similarity between two lineages over more than a few genetic loci, then the lineages are closely related and diverged from a common ancestor.

The probability you calculate over prolonged lapse of time T is extremely small. But the probability that the genome resulted from evolution from an  abiotic state is probably as small.

@user56930 not it's really not, convergent evolution has to be probabilistic at the genetic level, while genome complexity is a much simpler directional selection, the latter can take advantage of reinforcement effects like muller's ratchet and normal natural selection.

@user56930 — This answer was an honest response to your question as to whether convergent evolution could explain the relationship between man and e.g. chimpanzees. Your question said nothing whatsoever about the abiogenesis, nor does this answer. It is thus quite unjustified to use the comment section of his answer, not to query it, but to introduce the topic of the probability of abiogenesis. I suggest you withdraw your comment.

You are getting confused by terms.
there is a difference between convergent evolution at the genetic level and the functional level.
Rhodopsin is a group of similar protein molecules with similar structure some of which have a similar function. It is not a single identical molecule. Humans and halobacteria do not have the same rhodopsin molecule nor rhodopsin genes.
The rhodopsin molecular structure may be similar but it is not the same AND the genetics and process of its production are drastically different. halobacteria and animals have very very different rhodopsin genes, and even in animals rhodopsins genes var a great deal, but vary in a predictable pattern which mirrors their evolutionary relationships.
This is convergent evolution at a functional level, stumbling across similar configurations that produce similar results, even if the coding for that structure is drastically different. think of the similarities between insect and hummingbird wings. These are not similar genetics but similar molecules or structures.
Convergent evolution at the genetic level is extremely rare and is mostly due to the law of large number than anything else. They are always small similarities in the middle of vast seas of difference. the equivalent of two books by two different authors happening to contain the same sentence even if the entire rest of the book is different. And even then it tends to only occur in closely related species where enough of the genetics are similar that the chances of getting the same mutation twice is statistically possible.
sources: https://pubs.acs.org/doi/abs/10.1021/bi00136a001
https://pubs.acs.org/doi/pdf/10.1021/bi00128a002
https://www.sciencedirect.com/science/article/abs/pii/037811199500458I
https://www.sciencedirect.com/science/article/abs/pii/S0966842X06002307

No.  First, the idea of "lower" and "higher" species is one of those "not even wrong" beliefs that we are burdened with for reasons better not discussed here.  An ape, or a monkey or starfish, is no better or worse suited to its environment than a human.  And we do have a good bit of evidence, such as the fossil record, connecting apes & humans independently of the genomic evidence.  (Much of which was known decades before the discovery of DNA.)
@S. McGrew's answer discusses the statistical likelihood of similar genomes coming about as a result of convergent evolution. But let's approach the question from the other direction, and look at a couple of examples of actual convergent evolution.
First, the ichthyosaurs https://en.wikipedia.org/wiki/Ichthyosaur and the cetaceans https://en.wikipedia.org/wiki/Cetacea  Shaped by the pressures of their marine environment, they look enough alike that a casual observer might have trouble deciding which group a particular species belonged to. Yet one group are reptiles, the other mammals, separated by hundreds of millions of years from their last common ancestor.  Their bodily form is similar, but their genomes are very different.
Another, and even more widely separated, example are the hummingbirds https://en.wikipedia.org/wiki/Hummingbird and the hummingbird moths https://www.fs.fed.us/wildflowers/pollinators/pollinator-of-the-month/hummingbird_moth.shtml They look enough alike that they're hard for the casual observer to distinguish, they occupy the same habitat (I see both in my summer garden), feed in much the same way - yet one's a bird, the other an insect.  Again, the similarities of appearance & behavior are the result of evolutionary pressures acting on very different genomes.
There are many other examples of convergent evolution.  In most cases, if not all, the similarities have come to be as the result of similar environmental pressures acting on genomes, NOT as the result of genomes evolving to be nearly similar.  That is, if you compared the genomes of two such convergent species, they would have no more in common than two non-convergent species from the same groups.


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Evolution of recurrent laryngeal nerve in a giraffe
Do natural selection and survival  of the fittest explain the divergent length of the recurrent laryngeal nerve...centimeters in the human, 15 feet in the giraffe?

Are you suggesting the length of the nerve evolves independent to the length of the neck? That's not how development works at all

I don’t understand what you’re asking. The divergence of all ancestral traits can be explained by evolution. I’m aware that the laryngeal nerve’s path under the arch of the aorta has been used as an argument against intelligent design; based on that and your comments on some of the answers, it appears to me that you’re just trying to start a discussion on intelligent design versus natural selection. For that reason, I have voted to close your question. Perhaps you could clarify why the divergence in length you mentioned is confusing to you.

I am expressing a fact. I find plausible that finch charateristics diverge on isolated islands. I don't find plausible that natural selection explains the lengthening of the r.l. nerve to 15 feet. Within the province of discussion of natural selection an appropriate scientific skepticism is  not possible. Is it because the theory of the r. l. nerve by natural selection is "not falsifiable". This criterion of science seems to have been forgotten. I am entitled to doubt it and not be thought to entertain intelligent design. There nay be some agency in the genome  which governs tandem association

You are expected to show some attempt to research questions before you ask them, what research have you done. Clarity in what exactly you are asking would also be a desired improvement.

I have research Darwinian explanation. I wrote a book about. If you would like I can send you the google drive link since I am trying to get feedback on it. I've read Popper.  And I don't find that appropriate scientific skepticism is permitted in the field of natural selection.

This has a lot to do with how development works, there is no gene that makes the nerve this long. Instead, there are genes that tell the nerve where to grow and what path to take using other tissues as landmarks. At each step of the neck getting longer letting the nerve follow this path is more beneficial than the complex evolution of pathways necessary to change how it grows. At each step the added length of the nerve is a small detriment while a large number of simultaneous mutations would be needed to change the developmental pathways. Since these mutations are extremely unlikely to occur together and produce the desired results, they are instead a major/lethal detriment.
Based on fish it is likely that in the early common ancestor the nerve took a straight path. As necks evolved the heart moved down into the body and away from the gills the nerve originally connected to. Thus, the nerve is trapped by its own developmental pathway, it runs behind the gill arches which in tetrapods have become the aorta which is essential and the Ductus arteriosus which is developmentally vital. The nerves uses these as developmental landmarks for how it develops and grow in long before the neck develops. In an embryo (which has no neck) this is still a short straight trip, but as the embryo continues developing it has to grow longer and longer as the neck forms. Keep in mind the larynx and heart develop in very different location then where they end up in the body. Elongation of nerves as the tissue elongates does not need to be programed individually there is a general process that makes it happen in all nerves so no new mutations are needed. This is plasticity at work. The right and left nerve are actually different lengths because different gill arches are lost on the right and left side of mammals.  Simply letting the nerve get longer is less detrimental than not having the nerve which are the two options. As I mentioned above rerouting the nerve is unlikely to happen due to the improbability of the co-occurrence of multiple mutations to completely reorganize developmental pathways. There is a cost (extra tissue and calories and some signal lag and even rare developmental errors in the most extreme cases), but since it controls most of the larynx not having the nerve would prevent vocalization or or even breathing properly. Given those two options it is fairly easy to see why evolution favors individuals that maintain this pattern.
Evolution is full of kluges and "good enough" solutions/compromises like this.

https://www.evolutionarymodel.com/apps/photos/photo?photoid=56959380
https://arxiv.org/pdf/1901.01560.pdf
https://web.duke.edu/anatomy/embryology/cardiovascular/cardiovascular.html
https://www.sciencedirect.com/science/article/abs/pii/S095943880500187X

This is good answer, but I think it would be even better if you could provide some more references for particular statements (e.g. tissues being used as landmarks for nerve growth, number of genes involved in guiding this nerve, the movement of the heart during evolution & development, etc.) within the text and also indicate within the text where the figures are relevant. ——— I also took the liberty of editing in way I hope improves the clarity of your argument, but since this is out of my field it would be great if you corrected any errors I inadvertently introduced!

The improbability of multiple simultaneous mutations is pretty basic I any link will just be to a textbook. but I can add some more references.

I'm not sure how to address this question so that we may arrive at a suitable answer, but I'm sure that the recurrent laryngeal nerve is an example of bad design. Evolution works from traits already possessed by the parents. Mammals evolved from fishes in our evolutionary past and fishes do not have a neck. As a result the recurrent laryngeal nerve of giraffes loops under the aortic arch instead of over the arch.
Offspring of giraffes that are born with a longer neck have more chances of surviving and passing on the trait because they have an easier time to access food sources in higher places and an easier time to watch out for predators. Simultaneously, by natural selection the nerve is gradually lengthened in tiny increments. As Richard Dawkins said in his book Outgrowing God, "evolution cannot go back to the drawing board. Evolution has no foresight.”1
References:
1: Dawkins, R. (2019). Outgrowing God: A Beginner's Guide. Random House.

The idea that varieties died out because their r.l. nerve was not long enough (for my poor brain)  passes the bar of implausibilty.

Also if I may add, there is the rare variation in which the left r.l. nerve is non-recurrent, direct from vagus n. to the innervated tissues. The tenets of natural selection would imply that this uncomplicated variation should have gained ascendancy

Welcome to Biology.SE! This is a good start, but answers are much more likely to receive a favorable response if you include supporting references (primary literature is best). Without that support, your answer is indistinguishable from opinion. In addition, your answer could be interpreted as saying that the looping is giraffe specific. ——— Please take the [tour] and then consult the help pages for additional advice on [Answer] effectively on this site and then edit your answer accordingly. Thanks!

I also think that elaborating on how mammals (Is it really only mammals?) ended up with a recurrent laryngeal nerve would improve your answer. Finally, if you have a quotation from a book a complete reference to that work is best including a page number. (I've edited your post to improve the wording a bit and added the book reference, but don't have time to figure out the page.)

I wanted to delete one final comment and it looks like others were deleted. It was not intentional. If you want to pick up where we left off or restore them I would enjoy it. Thank you for your elaborate answer and comments. Natural Selection explains. Intelligent Design does not explain in the way that scientist love.

have research Darwinian explanation. I wrote a book about. If you would like I can send you the google drive link since I am trying to get feedback on it.

Sure I'd love to have a look.


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Reason for sorbitol synthesis in human body
Sorbitol has been proved to be a major contributor to development of complications due to chronic diabetes.
It forms in retina, lens, kidneys, peripheral nerves, ovaries and seminal vesicles by the action of aldol reductase on glucose. It only forms sorbitol when glucose concentration gets high as it has high Km.
It is seen that it accumulates in retina, kidney, lens and peripheral nerves as they lack the enzyme sorbitol dehydrogenase to convert it to fructose however ovaries and seminal vesicles have it so they are saved from accumulation.
Sorbitol accumulates and the membranes being impermeable to it, it results in drawing in of water by virtue of its osmotic activity.
I wonder why is it even being formed in the first place in retina, lens, kidney and peripheral nerves when it serves no function there?
I tried searching for any possible functions it may have in these tissues but apparently it has a role only in formation of fructose for sperms in seminal fluid.


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How does transpiration help in sucking water up?
How can transpiration help in sucking water up as the amount of water that is sucked up by the evaporation of water equals to the amount of water evaporated. (Correct me if I am wrong). Then how it helps?

The benefit is not in taking up more water but in transporting the things that water contains.
Plants rely on bulk transport in water flowing though specialized tissue (xylem), somewhat analogous to blood flow in an animal. Water flows through the xylem using capillary action; when water is lost at the top, capillary action pulls water into the vacated space and the flow continues down the entire height of the plant. Water removed for other uses like photosynthesis also contributes, but transpiration is important for many plants to increase the flow rate.


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How do plants that reproduce with artificial vegetative propagation grow in nature?
How do plants that grow with artificial vegetative propagation grow in nature? Will they go extinct if humans stop intervening? e.g., Rose

Welcome to SE.biology! Your question seems to be on-topic, but it's expected that you show some evidence that you've tried to research the question before posting here. Please take a read of the help centre section on how to ask a good question and consider editing your post.

Downvoted because it could be answered by a minimal amount of research.

Rose species reproduce perfectly well in nature, by the normal means of seeds and suckering.  For instance, Rosa woodsii is found growing along streams throughout the western US: https://www.wildflower.org/plants/result.php?id_plant=rowo
The reason rose (and other plant) VARIETIES are propagated by various artificial means is primaily because they are selected for various factors, such as (in the case of roses) color, bloom size, number of petals, and (all too infrequently) scent.  But those characteristics don't breed true: just as with humans, plants grown from seed will be different from their parents.
A second reason is that these plants are often hybrids of different species, and so may not produce fertile seed. Vegetative propagation - sometimes to the extent of using tissue culture - is the only way to get more plants of the same kind.
With roses (and numerous other plants) there's also a matter of economics.  A rose hybridizer may grow hundreds or thousands of seedling roses to find one that might be a marketable new variety.  When such a variety is found, the most economical way to produce many plants for sale is to graft the plant onto a common rootstock*.
*This is why many gardeners think their hybrid tea roses eventually "revert" to a boring red color.  It's because they're grafted onto rootstock of the "Dr. Huey" variety, and the vigorous rootstock takes over if not properly pruned.


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Can elephants trumpet when they have water in their trunks?
I am writing a fun story about elephants and want to know if elephants can trumpet or at least, make noises when they have water in their trunks, like when they are drinking water. Thanks for your help!

I think no. Because the elephant uses its trunk to make noise and if the trunk is filled with water then there is no chance the voice would come out.


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What is the definition of gene, genotype and phenotype, pre and post DNA?
i know that the definition of gene is a unit of heredity, also a sequence of nucleotides in DNA that gets copied to RNA and then proteins. Genotype is the genetic composition of an individual consisting of heritable genes. Phenotype is are observable traits that can be seen on the body of the organism. Knowing all this information, what is the difference between genes, genotype and phenotype before and after we found the existence of DNA?

As a point of order, the existence of DNA was demonstrated first by Miescher long before these terms came up (around 1870). He called it "nuclein" but he pretty fully characterized it chemically. However, it was not until the 1944 Avery-Macleod-McCarty experiment published in 1944 that DNA was shown to be the hereditary material.
Now a partial answer, relating purely to the origin of the terms (before DNA was known as the hereditary material):

here is a translation that I did of the lecture that defined "genotype" and "phenotype", by Johannsen in 1909. I don't think it was previously translated.
This definition was critiqued by another author (Woltereck in 1909), I translated that paper too. I don't think it was previously translated.
Johannsen came back with this lecture in 1911 (the first time the debate happened in English rather than German). This is now pretty much thought of as the canonical definition of that time.
I wrote a short essay discussing this back and forth with more sources.

The basic idea of the early consensus definition is that the genotype is the thing that you inherit, which consist of genes, which control your development. The physical nature of genes was speculative, though a lot of people suspected they were similar to enzymes. However, this genotypic control of development is partial and can be affected by environmental influences etc. The outcome of this developmental process involving both genotype and environment is the phenotype (morphology etc., the things that you can see with the eye, or with a microscope, or maybe a chemical measurement).
For further detail I strongly suggest that you read the papers I link to.
I will leave the question of the definitions post 1944 (or 1953, or post solution of the genetic code, or whenever) to an expert of that history.


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Could a mutation on neutral part of genome become deleterious?
I know that silent mutations are neutral because they dont affect function of the protein/gene, and a missense mutation would. But lets say both occur on a neutral portion, could one or the other become deleterious? I remember my prof stating that a mutation can become deleterious if on a neutral portion. I just dont remember what would cause this.
Thanks!

several related questions: https://biology.stackexchange.com/questions/73286/neutral-genetic-mutations-in-eukaryotic-cells/73293#73293, https://biology.stackexchange.com/questions/92575/how-do-we-formulate-the-mutational-load-for-junk-dna, https://biology.stackexchange.com/questions/8809/what-is-neutral-genetic-differentiation/92960#92960

@ManonValiquette can you better define "neutral portion"?  Are the "neutral portions" of genes the bases that correspond to the wobbly positions of codons? Is noncoding DNA considered "neutral" by your definition?

Of course. There are tons of ways this could happen. A trivial example:
CTA codon encodes leucine.
CTA --> TTA mutation will still encode leucine.
CTA --> CTT mutation also still encodes leucine.
By your definition, each of these mutations is "silent" or "neutral" independently.
However, if you combine both mutations, they lead to a TTT codon, which encodes phenylalanine aka missense mutation.
The fancy name for this kind of genetic interaction is "epistasis". THere are many other ways in which this kind of theoretically neutral mutation becomes non-neutral, but this illustrates it simply.


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What is the impact of selection on orthologous and paralogous genes? How would this impact differ in different regions of protein coding genes?
Since paralogs increase the size of the genome and provide more opportunity for the evolution of novel characteristics, would they be more prone to selection?

Exactly .
Paralogs and orthologs , both go under natural selection. But harmful mutations tend to have a less fatal effect if they happen to paralogs as there would  be a backup for the malfunctioning protein. In paralogs, if a bad mutation happens to a protein, the paralogous protein will compensate and help the organism maintain its function but in orthologs one mistake is enough to do harm because there are no other proteins to perform the function of the wild protein.

All the different members of the tubulin family of genes (and
proteins) are sufficiently similar in sequence to suggest a common
ancestral sequence. Thus all these sequences are considered to be
homologous. More specifically, sequences that presumably diverged as a
result of gene duplication (e.g., the α- and β-tubulin sequences) are
described as paralogous. Sequences that arose because of speciation
(e.g., the α-tubulin genes in different species) are described as
orthologous

Reference : Molecular Cell Biology of Lodish et al 8th edition page 325
Also see Campbell Biology 9th edition chapter 26 section 26-4

this is a good answer, but it would be helpful to include a source or citation.

@sam, thanks for the great answer! I am just wondering though how the impact of selection would differ in protein coding regions.... I know it would be more impactful in this region as opposed to non coding, but im not sure how the impact differs between protein coding regions.. or why? thanks!

@Manon Valiquette , natural selection effects the whole gene.  (Beneficial) selection in protein coding regions includes 1.Active sites / binding sites for complexes  2.Allosteric domains 3.Structural/Less important sections. In 1 , any change leads to a large scale of "FUNCTION" and  the "AFFINITY" to ligand of the protein/enzyme.  In 2 alternation of sequence leads to changes in "AFFINITY" for the ligand and more importantly "RATE OF CATALYSIS", while changes in 3 tend to have a less impact on the protein. Plus selection can also occur in non coding regions which mainly result in ---

--- "Gene expressing patterns and timing and amount of transcription" . for example a selection in promoter sequence can increase the rate of trancription of a specific gene , leading to overexpression of it which sometimes may be beneficial. I hope that I've understood your question correctly.


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what are the nodes and edges in gene regulatory networks
I am trying to find out how one can using gene expression data can infer gene regulatory network applying graph theory concepts. But I could not find a proper reference that
1)explain how one can get the adjacency matrix for a gene regulatory network?
2)if genes are nodes and edges are interactions between genes, where the gene expression values placed? and how one decide if there is an interaction between two genes?
3)what are the parameters there?
I found some literatures that describes DAGs but still the upper question are remained for me.
Any reference or help regarding these questions is highly appreciated if even it is going to be a keyword.

I think that this question is off-topic here as it does not relate to a specific problem in biology. You would do better transferring it to SE Bioinformatics to see if they will accept it.

You're asking for a short answer to an entire field of research. You won't get a comprehensive one that fits in a SE answer.
Generally, yes the genes/their products (which are often treated as the same thing in these abstracted models) are the nodes; the causal relationships between them are coded in (typically weighted, directed, bidirectional) edges. In graph theory more generally, you hold the "activity" of the nodes in a separate vector; sometimes that is taken as an input vector to your graph to produce a corresponding output vector at some time dT in the future (other times you aren't really interested in the activity at all and are working with just the graph itself).
Edge weights are determined by experiment, often many many interrelated experiments. If you experimentally increase or decrease expression of gene X, you can monitor gene Y for change to infer a "connection". However, it's more complex than that because an effect of X on Y could be mediated through a number of other nodes. Biology is rarely simple, and if you expect it to be you're going to make mistakes rather quickly.
If you have enough information about the graph and timeseries data about expression, you may be able to infer a model graph to describe the observed data. Some people have already compiled putative networks (particularly in model organisms) and you can find them by searching for their published papers describing them, or finding others who cite them.
If you want to do these things practically, I highly discourage working merely from textbook examples or broad summary reviews; to do something useful in science, you need to read primary literature. Your answers to these questions in your particular area of study will come by reading the methods sections of papers that publish on these networks.

Some references to start with:
Emmert-Streib, F., Glazko, G., & De Matos Simoes, R. (2012). Statistical inference and reverse engineering of gene regulatory networks from observational expression data. Frontiers in genetics, 3, 8.
Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., ... & Young, R. A. (2002). Transcriptional regulatory networks in Saccharomyces cerevisiae. science, 298(5594), 799-804.
Pavlopoulos, G. A., Secrier, M., Moschopoulos, C. N., Soldatos, T. G., Kossida, S., Aerts, J., ... & Bagos, P. G. (2011). Using graph theory to analyze biological networks. BioData mining, 4(1), 1-27.
Vijesh, N., Chakrabarti, S. K., & Sreekumar, J. (2013). Modeling of gene regulatory networks: A review. Journal of Biomedical Science and Engineering, 6(02), 223.


text:
Why is Heart Rate Recovery after exercise reasonably well described by a mono-exponential decay?
I have been measuring my heart rate recovery after exercise and I see that it can be fit reasonably well using a single exponential:
$HeartRate(t) = HR_{max} \times e^{-t/\tau}  + HR_{resting}$
This observation is further supported by this paper:
https://pubmed.ncbi.nlm.nih.gov/24494748/
From Wikipedia: "A quantity is subject to exponential decay if it decreases at a rate proportional to its current value"
So, the exponential decay suggests that the ability to slow down the heart depends on the heart rate itself. A faster beating heart somehow produces more of the signal to slow down the heart.
Is this the case? What is the mechanism that allows for such a feedback loop of the heart rate? Is the signal sent through the nerves as the heart muscles contract, or is the blood flow that allows a signal to travel?
Is there another way to explain the mono-exponential decay?
Here is an example from yesterday's run. I sprinted and then walked very slowly a few times. My heart recovery lifetime ($\tau$) including only the first three decays is 53 +/- 4 seconds. The last decay is after I ran up the stairs and then sat down, and its lifetime is of only 22 seconds.

Exponential decay is characteristic of a first-order reaction, and where the exponential factor arises because the integral of 1/x (dx) is ln(x). Radioactive decay is a great example. For any first-order reaction, we can calculate the half-life, once the first-order rate constant is known. This is independent of concentration ...

... The half-life is usually expressed as ln(2)/k but in your case, it will be ln(2)*τ which I calculate to be about 36.7s. Thus after 36.7 seconds, HRmax will have decreased to half its original value (no matter what that initial value was), and after a further 36.7 seconds it will have decreased to half that value again, and so on

I think most people would take exponential decay in a circumstance like this to be the null hypothesis. That is, if you had something not exponential decay, that would be curious and interesting and worth understanding better.
Exponential decay is a pretty fundamental concept in the universe in general and biology in particular.

So, the exponential decay suggests that the ability to slow down the heart depends on the heart rate itself. A faster beating heart somehow produces more of the signal to slow down the heart.

I would not think about it quite this way, and maybe that's why you're thinking there is something profound here about "ability to slow". Rather, I would think in homeostatic terms and consider the "set point". If your "set point" for heart rate is high during exercise and low during rest, you'd expect exponential decay if the physiological signal being acted on is a difference between the current rate and the set point. When the rate is much higher than the set point, you'd generate a bigger error signal and this would result in a faster decay.
More concretely, you could think in terms of regulators of heart rate like CO2 and catecholamines, as both of these are likely to follow an exponential pattern, CO2 because transfer out of tissues into the blood and out of the blood into the lungs are both going to be faster when CO2 concentrations are higher. Catecholamines are going to decrease by exponential decay through enzymatic degradation: when there are more molecules around to react, the rate of degradation will be faster.

Thank you! The precise nature of the "error signals" in homeostasis will keep me entertained for some time. I study the kinetics and dynamics of very simple chemical systems, and it is quite easy to take simple systems out of mono-exponential behavior. Even the systems that you mention - diffusion of CO2 and enzymatic degradation will often show non-exponential behavior unless special conditions are met. The emergence of mono-exponential behavior from a complex combination of dynamics over different time and size scales is quite fascinating, even if trivial!

The answer by Bryan Krause is right on point from a system's perspective.
From a cardiology point of view, heart rate recovery (HRR) post-exercise has been a significant consideration in cardiopulmonary exercise testing (CPET) in recent years.
Put succinctly, heart rate is influenced by the sympathetic and parasympathetic nervous systems. Increased sympathetic activity increases the HR and increased parasympathetic activity decreases it.
The response of both systems to the cessation of exercise is a huge determinant of the  behavior of HR post-exercise. So, abnormal HRR can potentially reflect imbalances between the sympathetic/parasympathetic systems.
In Chronic Heart Failure, the failing cardiac muscle prompts inappropriate neurohormonal activation of both systems, which is sometimes described as "flooring the gas pedal and the brake pedal at the same time". This can be directly observed (see Figure) in the HRR patterns of CHF patients, which is blunted because both the sympathetic and parasympathetic systems exhibit more inertia to change. Note that a lower HR is also achieved.

In fact, blunted heart rate recovery in CHF patients confers very poor prognosis.
Another interesting tidbit: In heart transplant recipients, one can essentially observe the behavior of a "denervated" heart, as all nerve connection have been severed*. In pediatric heart recipients, heart rate recovery (defined as peak HR - HR post 1-minute) was extremely slow compared to normal controls:

This finding highlights the significance of neural input to achieving a "normal", exponential HR decay.
*some innervation can be observed months-years post-transplantation
References

Zweerink et al. Chronotropic Incompetence in Chronic Heart Failure: A State-of-the-Art Review. Circulation: Heart Failure. 2018 Aug;11
Singh TP. Longitudinal changes in heart rate recovery after maximal exercise in pediatric heart transplant recipients: evidence of autonomic re-innervation? J Heart Lung Transplant. 2007 Dec;26

Welcome  Anastasios. Please take our [tour] and refer to the [help] as and when for guidance. Great first post. Enjoy Biology.


text:
Illustrating Action Potential Conduction and Ion-Gated Channels

I can separately illustrate action potential and ion-gated channels along an axon.  However, I am not sure if I did the right thing on the picture below.  What I'm trying to show are the simultaneous processes of (1) the flow or propagation of action potential along the axon length, and (2) the position of ion-gated channels along the axon length.
The blue figures are for sodium. The red figures are for potassium. The arrows show the propagation of action potential.
Was I able to depict what I'm trying to show properly?  If not, how can I correct this?

For clarity - this is entirely your own diagram? Or you've modified someone else's?

@BryanKrause this is my own diagram.


text:
What is the definiton of repertoire shift in B cells?
I am new to biology and trying to understand this term.
Couldn't find a comprehensive defintion.
Thank you

Welcome to SE Biology. Please finish reading the [Tour] and the Help on asking good questions where you will read that you are required to show the research you have done before posting. In biology we deal more in explanations and usage than formal definitions, and if you search for "B cell repertoire shift" you will find many papers on this topic. Read their introductions and if you still can't understand post a sentence or two and explain what it is specifically that is causing problems.


text:
Calculation of drug efficacy- mathematical biology approach
I am participating in a mathematical biology project.
I would like to discuss the following problem:
Let A be a drug such that $x_{o}$ chemical units of it kills 12% of $y$ cells per 1 day, I would like to calculate the efficacy killing rate of the drug.
My attempt:
Duration of process: 1 day
Killing rate $r$ of cells by drug A:
$$
\begin{aligned}
&100y e^{-r t}=12y \\
&100 e^{-r}=12
\end{aligned}
$$
so
$$
r=2.12 / d a y
$$
Efficacy rate of drug A- meaning in which rate cells are killed
per 1 unit of drug A per 1 day:
$$
\begin{aligned}
p x_{o} &=2.12 / \text { day } \\
p &=\frac{2.12}{x_{o}}\left[\frac{1}{U \cdot d a y}\right]
\end{aligned}
$$
Here $U$ means the chemical units of the drug.
Is it correct biologicaly/physically to decompose the a rate of process into the product of efficacy rate  and the initial amount of drug?
Is there anything wrong in thi process? another way of calculation?


text:
What is the difference between mutation per base pair and mutation per genome?
Isn't genome size considered to be the number of base pairs present in DNA? So what is the difference between the mutation per base pair and mutation per genome? Are they similar or different?

I assume you read both terms somewhere?  Often, context supplies meaning. If you could directly quote the source of each term, you would likely get a good answer.

They are different normalizations of the same number. It's the question of whether you want to know how many mutations can be expected at a single position in a genome, or whether you want to know how many mutations occur across the entire genome.
See wikipedia, for instance:

There are several natural units of time for each of these rates, with rates being characterized either as mutations per base pair per cell division, per gene per generation, or per genome per generation.

Mutations per genome is the number of mutations per base pair times the number of base pairs in the genome (plus mutations that do not correspond to base pair substitutions, though they are usually ignored in these measurements).
E.g., $10^{-9}$ mutations per base pair in a genome of 3 billion base pairs correspond to $3$ mutations per genome.

not sure why this answer was downvoted/flagged. it's a pretty straightforward topic, not sure why a link is needed.


text:
Do animal muscles atrophy slower than humans?
Suppose I consider the silver back gorilla as an example.  I cannot imagine ever seeing one in the wild intentionally doing something akin to weightlifting like humans solely for the purpose of getting stronger (if I'm wrong about this, that would be fascinating to know as well).  However, last I checked a male silver back can easily lift several times its own body weight.  I used to workout heavily and used to hold my high school bench press record (330 lbs in the 160-171 lb weight class).  However, even then I would have struggled to do more than a few pull ups with a 170 lbs strapped to my waste.  Meanwhile, I've watched various types of monkeys and apes do handfuls of seemingly effortless pull ups at zoos as part of their play.
So do animals like gorillas have muscles that either start and stay stronger than humans or just atrophy much more slowly?  Or is it just a matter of constant use?  Or is it just a different proportion of fast vs slow twitch muscles as this study suggests?
I am skeptical of this last part because some estimates of gorilla strength suggest they can lift upwards of 10 times their body weight [e.g., https://storyteller.travel/how-strong-is-a-gorilla/].  I also recall reading a study in grad school of an orangutan pulling over 600 lbs with one arm clearly not straining according to the article (though I failed to find the reference while searching today, unfortunately).
If anyone has some useful references with quantitative data, that would be great as well.

No matter how much I excercise, my musculus maximus will be stronger than my abductor policis brevis by the virtue of being anatomically different musles. Why would you expect an animal with clearly different body proportions and anatomy to have the same strength as humans?

Well, it's more a matter of confusion.  Hafþór Júlíus Björnsson, for instance, is over 400 lbs and one of the strongest humans on the planet.  He weighs more than most apes.  Yet I would pick the apes in just about any strength contest over him and they never work out.  Plus, male humans have a larger fraction of our body mass as muscle than apes yet they are still stronger.

@honeste_vivere: You might consider that the normal activities of an ape are equivalent to a human "working out".  Likewise for that subset of humans whose normal activities include a lot of physical work.

@jamesqf - True, they are more physically active.  However, how often do mountain gorillas go out of their way to lift up more than 2000 lbs?  I am guessing almost never yet they can certainly do that without risking serious injury.  Hafþór Júlíus Björnsson has to constantly train and eat an absurd amount of food just to barely be able to lift that much weight.  His job is to get stronger and he wouldn't even be able to compete against a gorilla.

Few more points regarding anatomical differences: 1. A muscle can only exert so much force on tendon and bone until something breaks. Look at side by side comparison of gorilla and human skeleton. Look how much sturdier an wider are the bones and joins. Wide bone surface allows for wider and stronger tendon-bone binding area. 2. A short and wide muscle can have the same total mass as a long and thin muscle and be stronger since exerted force solely depends on cross-section area of the muscle. 3. Number of filaments in a muscle is already determined at birth. This limits what exercise can do.

@honeste_vivere: I dare say he wouldn't be able to compete against my horse, either.  I think we may be looking at two different things here.  I'm looking at the difference between a sedentary human (or other animal) and a trained one.  You seem to be more interested in species differences, no?  In that case, look at sled dogs.

@jamesqf - Yes, I am curious if there is something different beyond just a different fraction of fast and slow twitch muscles between humans and, say, great apes.  Suppose you could teach a gorilla to intentionally strength train.  I think the difference would be even more stark.  Is it really just skeletal and muscular differences that make up that much of a difference though?

Animal muscle does atrophy and gain depending on use.
First, animal muscle does atrophy if the animal is too sessile. However in nature it is hard to be sessile. Consider how physically fit hunter-gatherer humans are in terms of their cardiovascular systems. If you are constantly active you don't need to "exercise" to build muscle - you are getting loads of physical activity. Walking 10km a day or more is normal for most humans without advanced technology. We used to see atrophy in animals a lot more, but with animal welfare laws we usually don't keep animals in tiny cages that prevent them from moving anymore.
Some animals are less lazy than humans: many animals will also instinctively stay active even when provided with the conditions to be sessile, but when forced to not be active we do indeed see muscle atrophy. This is especially true of less intelligent species, because the conditions to be sessile are too rare to waste "instinct space" on, but humans who have a much more broader range of behaviors with far more learning behaviors, so we can become very sessile. The downside of intelligence is that you can use it in self-destructive ways.
Just like humans, animals can also build extra muscle by doing the same thing over and over again: a draft horse will build different muscles than a race horse just because it is using them differently.
Many animals also have physiology that makes atrophy harder. Hibernating bears are known to have special adaptations to prevent atrophy because hibernation is defined as long periods of inactivity. But we only only see this in animals that have something like hibernation or have drastically different muscular systems.
So why is a gorilla so much stronger?
Well to start, wild male gorillas mass between 130 to 260 kg. Note that gorillas in captivity often become overweight weighing even more. They have short legs so we don't realize how much bigger than us they are. For scale, Andre the giant (a human far outside the normal range) masses about as much as a large but normal range male gorilla. But there are several other factors.
Humans’ muscles are weaker than other primates’ in significant ways. We have traded strength for much better endurance and fine control of muscles - we do indeed have a significant difference in muscle composition and possibly muscle fiber recruitment, although it is hard to test the latter - you can't tell a gorilla to contract one muscle as hard as they can. As a gain however humans have amazing endurance for any animal and far finer motor control than any other primate. An active human can have better endurance than almost any other terrestrial organism, humans can walk a horse to death, that is a human walking side by side with a horse can keep going long past the point the horse has died from exhaustion.
Gorillas are only stronger in some aspects, a gorilla upper body is certainly stronger, gorilla have large arms and a deep chest drastically increasing the muscle mass of the arms compared to a humans. But the best human could probably beat the best gorilla at kicking power, gorilla legs are comparatively small. To use Andre the giant again, Andre has a lot more muscle mass in his legs than a gorilla and the gorilla has a lot more in the arms, humans have long well-muscled legs. Like all things, genetics can set you up with better musculature, and you will keep it as long as it gets some use.


text:
Is Signal Transduction Unidirectional from the Stimuli to the Final Receptor?
I wonder if signal transduction in biological systems including visual, olfactory, tactile or any other biological system, is unidirectional. Suppose that $X_i$ is the $ith$ cell in the signal transduction pathway and $X_{i+1}$ is the next cell down the pathway. To be more clear let me rephrase my question. Suppose that,
$X_i \rightarrow X_{i+1}$
means that the signal is sent from $X_i$ to $X_{i+1}$ and,
$X_i \rightleftharpoons X_{i+1}$
means that the signal is being sent both from $X_i$ to $X_{i+1}$ and vice versa but the signal amplitude in the $X_i$ to $X_{i+1}$ direction is larger so on average we can say that effectively the signal is being transmitted from $X_i$ to $X_{i+1}$. Which one of these cases is true for biological systems? Or can both occur depending on the system?
The question might not be a very good one because I don't have any background in biology. I would appreciate any answer or guidance. Thanks in advance.

Welcome to Biology.SE. This is not simply an answer site, but instead a site that promotes self-learning with some expert help. Consequently, questions that show little or no prior research effort are off-topic on this site. Please [edit] your question and tell us where you've looked for answers, what you do know about the topic, and where exactly you still have questions. Please also try to focus your question (this is very broad) as this can involve chemical (e.g. hormones) and electrical signals. Please take the [tour] and consult the [help] starting with [ask] for details.

No.
I'll just use one example, the retina, for a proof by contradiction.
In the retina, the principle "forward"/unidirectional pathway would be from photoceptor cells (rods/cones) to bipolar cells (BC) to retinal ganglion cells (RGCs/GCs). RGCs are the projection neurons whose axons make up the optic nerve from eye to the rest of the brain.
However, there are other cell types in the retina as well that convey information horizontally and in reciprocal/feedback directions. Here are some examples depicted in a review paper:
(image from Demb & Singer 2015)

In (a), on the left, you see connectivity between a bipolar cell (BC) and an amacrine cell (AC), a type of interneuron in the retina. The AC is excited by the BC but also inhibits the BC; this is not unidirectional. In the middle, you see a horizontal connection between two BCs through an AC. On the right, you see another horizontal connection among BCs, in this case BCs of different types, through an AC.
Horizontal and feedback connectivity patterns are ubiquitous in the mammalian nervous system; you'll find them everywhere you look, so it's not reasonable to expect signal transduction to be unidirectional.
I'll add that it is not straightforward to determine the "strength" of signals in the nervous system, especially when inhibition is involved. For only excitatory connections, you might measure the excitatory potential (voltage change) at the cell body as a measure of "strength", but this is complicated because this strength depends on lots of other things: you can have nonlinear interactions in dendrites such that multiple signals sum linearly, sublinearly, or supralinearly; the rate of presynaptic activation matters, so even a "strong" synapse may not be particularly influential if the presynaptic neuron rarely fires, etc.
For inhibition, it's even more complicated, because many inhibitory potentials involve shunting and may not affect the membrane potential at the soma at all unless they are paired with an excitatory input. It's possible to have an inhibitory input so strong that a cell can effectively never fire, and yet the effect of that inhibitory input alone has no detectable influence on the cell's voltage, it merely provides a shunt that fixes the membrane potential at that voltage.
Demb, J. B., & Singer, J. H. (2015). Functional circuitry of the retina. Annual review of vision science, 1, 263-289.


text:
What does Guyton mean by "the ratio must be grater than one" when it comes to the safety factor to start an action potential?
AllorNothing Principle. Once an action potential has been elicited at any point on the membrane of a normal fiber, the depolarization process travels over the entire membrane if conditions are right, but it does not travel at all if conditions are not right. This principle is called the all-or-nothing principle, and it applies to all normal excit- able tissues.
Occasionally, the action potential reaches a point on the membrane at which it does not generate sufficient voltage to stimulate the next area of the mem- brane. When this situation occurs, the spread of depolar- ization stops. Therefore, for continued propagation of an impulse to occur, the ratio of action potential to threshold for excitation must at all times be greater than 1. This “greater than 1” requirement is called the safety factor for propagation."
What he means with "1" is he talking about milivolts? What are the values of the ratio he mentions.
Source of Info: Guyton & Hall Medical Physiology textbook

Welcome to Biology StackExchange! Ratio of two identical quantities has no units because both quantities have the same units, which then cancel each other. For example: if the action potential is $60;\rm mV$ above the resting potential, and the threshold potential is $15;\rm mV$ above the resting potential, then their ratio is $60;\rm mV/15;\rm mV = 4$.

Thank you very much!

The two quantities of concern are "threshold" and "peak voltage" (both relative to resting potential).
If the ratio "peak voltage"/"threshold" is less than one, then that means peak voltage is less than threshold, which by definition of threshold means an action potential will not propagate.
If the ratio is exactly = 1 then the peak voltage exactly equals threshold. This is a precarious situation: any little randomness in the system would mean the action potential could fail to propagate. That's why they're calling the ratio a "safety factor": if the ratio is, say, "2", then the depolarization is twice what you need to propagate and you could say this is quite safe. If it's 1.01 then there's a little margin built in but it's still likely you could see a failure to propagate.
For an analogy most people encounter in daily life now, let's think of the charge on your cell phone battery in the numerator and the charge you use in a day in the denominator. If the ratio "charge available"/"charge used" is less than one, your cell phone won't make it through the whole day without dying. If the ratio is 2/1 then most days you'll end the day with around 50% left; you could say you have a safety factor of 2 and if you use more than expected some days you'll still be okay.

Thank you very much! super clear!


text:
Is life in the open ocean homogenously spread?
Obviously around land masses or in shallow water where reefs and coral may grow, life is diverse and numerous. But how spread out is sea life in the open ocean (for example, half-way between Hawaii and California) where there is no land mass or shallow depths for hundreds or thousands of miles?
Does life exist in clusters with large swaths of oceanic desert in between or is it relatively homogenously spread?

You need to consider ocean currents. In a nutrient-rich current, density of life will be (much) higher than outside of it.

Are you purely interested in distribution across the horizontal plain? If you consider depth in your equation, around 90% of marine life is concentrated in the upper palagic zones, as sunlight can't penetrate much deeper than around 600 meters.

This is sort of a partial answer, but here is a map using chloryphyl density to map the global distribution of marine life. As you would expect, most is clustered around costal regions, but you can also see some pretty distinct zones in open ocean, with more primary production apparently in the northern and southern latitudes. Not sure how much this map projection distorts apparent distances, but it should help give you an idea.

Here's where I found this map.
And here's one of the links they references, which looks to have some more resources to explore.


text:
What is the current scientific consensus regarding the relationship between Eukaryotes and Archaea?
In the traditional 3-domain system, the domains Bacteria, Archaea, and Eukaryota are all distinct from one another, with the latter 2 usually being sister-groups in a clade.
However recent evidence has come to light showing that Eukaryotes might have arose within Archaea, rather than being the sister group to it. More specifically, Eukaryotes might have evolved from the Asgard archaean superphylum.
What is the current consensus towards this issue? Do most evolutionary scientists today still consider Eukaryotes to be the sister group to Archea? Or is it thought that eukaryotes are archaeans?

What makes you think that there is a consensus on any controversy in science, and what makes you think that knowing which view is dominant has any importance per se. As scientists, we on this list are only interested in the strengths and weaknesses of arguments. Please present your questions in these terms.

For a recent provocative article on this subject, see Isolation of an archaeon at the prokaryote-eukaryote interface, and see also The mysterious microbes that gave rise to complex life (both articles published in Nature in 2021)


text:
What is the current state of research on the relationship between sponges, ctenophores, and other animals?
I've been reading about the basal taxonomy of animals recently, and it seems as though there is some controversy surrounding the classification of sponges, ctenophores (comb jellies), and all other animals. One proposal has it that sponges form a monophyletic group, sister to all other animals. Another proposal is that sponges are polyphyletic, with the rest of the animals descended from some group of sponges or another. A third proposal is that in fact ctenophores are the sister group to the rest of the animals.
What does the current state of research on this topic look like? What are the arguments for and against each view? Is there a general consensus?


text:
Sequence structure of antibodies
It is said that

"When a virus or a pathogen enters the body, the immune-response produces Y-shaped proteins called antibodies to bind to the pathogen or virus".
"Also it is possible to extract antibodies from the blood."
Since antibodies are proteins, is it possible to sequence their structure ?
If the answer to point-3 is Yes, then can't coronavirus antibodies be sequenced, more antibodies be produced from this sequence on a large scale, and then these are administered to the infected people ?

I would like to know any challenges to the above mechanism like "difficulty in figuring out the correct antibody or so" ? Thanks!

Looks like you have re-invented monoclonal antibodies. https://en.wikipedia.org/wiki/Monoclonal_antibody

@PolypipeWrangler Yeah, in a way. But this is not done via sequencing of the protein but isolating and identifying the right plasma cell.

Thank you all for the information!

@Chris does this mean that the above mechanism has not been "exactly" applied till date ? I am asking this since you said "not done via sequencing of the protein but isolating and identifying the right plasma cell".

@harrypotter having the protein sequence doesn't help you making the functional protein. Having the relevant plasma cell does.

Giving a simple answer is difficult as the field of humoral immunology is quite extensive. Here is an abbreviated overview.
Our body produces myriads of different antibodies during an immune response, not just one. It is impractical to isolate and sequence one antibody protein as their sequence differs in very subtle ways. N-terminal sequencing like Edman degradation is not practical as it covers only a few dozen residues at most. Perhaps proteolytic digest of an antibody and peptide sequencing is possible, but again this requires a large amount of a pure antibody. Protein sequencing is not practical.
Instead, people sequence the DNA corresponding to a given antibody instead of sequencing the antibody protein itself. As a given B cell expresses one antibody in large amounts, Milstein and Kohler (Nobel laureates) devised a technique to fuse B cells with tumor cells, creating hybridomas. Each hybridoma thus produces a single antibody. Such hybridomas may be cultured – monocultured in fact - in the lab to large amounts, leading to the production of a uniform, single antibody, termed monoclonal antibody. The corresponding DNA sequence of such monoclonal antibody may be readily sequenced.
I would think it feasible to create a library of individual hybridoma monocultures using a patient’s B cells, and then select the hybridoma producing the best monoclonal antibody from the library, and sequence that DNA. Epitope binning [https://en.wikipedia.org/wiki/Epitope_binning] is one example of a technique to identify the best antibody. The successful hybridoma may then be culture to large scale to produce lots of that exact antibody.
Administering such purified antibodies to a patient is not straightforward as this foreign protein will be itself recognized by the patient's immune system and cleared. There are techniques to reduce the immunogenicity of a given antibody, but that will be a lengthy discussion in itself.

Welcome to Biology.SE! This looks like it may be a good answer, but answers are much more likely to receive a favorable response if you include supporting references (primary literature is best, but for this textbooks may be acceptable). Without that support, your answer is indistinguishable from opinion. This is a good example of how to format references. ——— You may also want to take the [tour] and then consult the [help] pages for additional advice on [Answer] effectively on this site. Thank you!

Thanks for the answer. It was useful!

It is possible to sequence these antibodies.
It is likely that these antibodies are already produced, but injecting antibodies into people does not build immunity. At best, it can temporarily mitigate the spread of the virus. It does not build immunity because it would not teach your body to make its own antibodies, which is the purpose of a vaccine.

Thanks @JMorrissette, if I give sequenced antibodies over a period of time, is it possible that these antibodies bind to all the existing virus proteins. Partly we will have destroyed cells but partly the uninfected cells can be saved. Isn't it true ?


text:
Why does sequencing virus proteins take time?
According to the below paper, the coronavirus spike protein sequence was available to scientists by end of february 2020 - the begin of march 2020 timeline. I had this question that why does sequencing of a virus protein take so much time (I am a software engineer, currently studying molecular biology to better understand the pandemic, hence I am seriously unaware!) ? The reason of asking is because, in case of another epidemic, we might need to spend again a lot of time to sequence the protein. This might be a real concern!
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7151553/#:~:text=At%20the%20time%20of%20the,remain%20identical%20or%20almost%20so.

Note that the protein sequence is inferred from a DNA sequencing experiment, not sequenced separately.

@MaximilianPress Yes, that is an important point, and one that I neglected to state explicitly in my answer.  Thank you for clarifying in yours -- Protein sequences are inferred from the DNA sequence using gene/ORF calling software.

You really can’t expect us to read through this paper to discover what exactly is the time period between what events you feel is “so much time”. Sequencing the genome of a virus in itself can be done very quickly. I suspect that you may be confusing stalking  the deer with cooking the venison. If you don’t know where the meat got to before it got to the supermarket, perhaps you need to do some reading. Biology perhaps?

Sequencing a viral genome requires isolation of the virus, propagation in cell culture, extraction of nucleic acids, and preparation of a sequencing library.  Once sequences are obtained, a genome can be assembled de novo using (untargeted) shotgun reads, and gaps in the genome can be spanned with (targeted) Sanger sequencing.  This process can take weeks to months depending on the availability of resources and the growth characteristics of the virus.
For details on how the 2019-nCoV genome was sequenced, see Zhu et al., published January 2020:
A Novel Coronavirus from Patients with Pneumonia in China, 2019

Thanks @acvill, that answers my question. So, "the availability of resources and the growth characteristics of the virus" are the reasons. Thanks again!!!

Note that mine is a very general answer and is indeed pessimistic about processing times.  Your question would be much improved if you walked us through your logic in deducing what you describe as "so much time", per David's comment.

Sequencing DNA (which is what was done for the COVID virus, post reverse transcription as it is an RNA virus) does not take very long. A NextSeq instrument can provide results in <24 hours. Protein sequences are inferred from the DNA sequence using gene/ORF calling software.
SOme of this is suggested by @acvill, though I think that they are pessimistic about time estimates. Viral genomes are pretty easy to assemble (matter of hours). In principle you can dispense with the isolation step too, though that makes the analysis more complex.
It is all the medical and bioinformatic stuff around the sequencing, e.g. isolation and analysis and ethical paperwork (necessary!), which takes time.

Thanks @Maximilian Press, that was very informative! "A NextSeq instrument can provide results in <24 hours" was useful information to know. Thanks again!!!


text:
Are neurons capable of buffering a signal to sync up with other data?
The brain is the most complex thing that mankind discovered thus far in the universe. Super computers aren't able yet to outperform the human brain (running only on ~25 watt or so) on the domain of general intelligence.
With a computer it is fairly straightforward to capture an image stream and split it into 2 streams. So in a videoclip depth data could be contained by alternating the images from 2 streams from two different angles.
What if an organism would loose sight in 1 eye. And the other eye would be fed with data that contains actually 2 image streams, with these alternating angled images, at an always exact framerate. Would the organism (the brain basically) be able to comprehend the data and experience depth? For that it would kind of need to buffer every other image and put them through simultaneously, mimicking the feed from two eyes basically.
Would this be possible? Is there any research done on a topic similar to the example above? Where data is buffered by a neural network to be send in combination with other data?

For this answer, I'll use a very broad definition of "buffer" as a mechanism to integrate information at different delays. I have no interest in getting into specific computer science definitions of what a buffer is and I don't think it makes any sense to use them in biology.

Parallel processing and predictive coding
The brain is a massively parallel system, so of course there are different "streams" of information flowing at all times. Certainly the brain as a whole does some level of buffering, though the mechanisms available to individual neurons are unlikely to do what you suggest. The "buffering" in individual neurons has a lot more to do with learning and memory, for example in spike-timing-dependent plasticity which incorporates a physical record of past inputs in a learning rule.
One model of cognitive function is predictive coding, in which the brain holds a model of the world at different hierarchical scales and updates this model with new information. This model is effectively a buffer against which new incoming information is compared to draw attention to discrepancies that require further attention (such as the sudden appearance of a predator).
Audiovisual integration
One simple example of buffering is in audiovisual integration: the brain's processing of visual information is much slower than auditory information, and yet the perception of, say, a human speaker's voice vs. lips or the sound and sight of a bouncing ball are perceived in synchrony (see for example Recanzone 2009; note this has absolutely nothing to do with speed of sound vs speed of light).
It's important to understand that the visual system doesn't process visual information anything like a computer. There are no frames in biological vision. That said, humans can deal with a lot of unnatural sensory input, and they also use a lot of other visual cues besides stereo vision, the so-called "monocular cues".
Motion parallax and wiggle stereoscopy
One of these monocular cues is motion parallax (binocular vision can also utilize parallax without motion). Wiggle stereoscopy simulates motion parallax, as if your head were oscillating back and forth, to create an illusion of 3D, and seems much like what you are proposing. It doesn't matter whether you view the image with one eye or two.

Recanzone, G. H. (2009). Interactions of auditory and visual stimuli in space and time. Hearing research, 258(1-2), 89-99.


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Flexor/extensor group in lower arm and limb bud rotation
Have the flexor and extensor groups in the lower arm have rotated laterally 90° towards the humerus epicondyles independently of the rest of the lower arm? The pre-axial and post-axial veins are still in aligned with their segments in the upper arm, so I assume that the muscle mass that forms the flexor group was initially located on the anterior side aligned with the flexors in the upper arm. The other option is the entire lower arm rotating relative to the upper arm but it seems less likely.


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Why don't weak detergents lyse the nuclear membrane?
A low concentration of a non-ionic detergent lyses the cell membrane, but leaves the nuclear membrane intact. Both are phospholipid bilayers, so why is only the cell membrane lysed?
Under these conditions, are the membranes of other organelles lysed?

Great question. It seems only zwitterionic detergents are talked about when lysing organelle membranes. I don't see why lots of 'weak' detergent wouldn't get the job done if the only goal was to lyse the organelle membranes.

First, an important fact   about non ionic detergents- {1}They have a hydrophilic head group that is uncharged and are preferred for their ability to break lipid-lipid and lipid-protein interactions. They have limited ability to break protein-protein interactions and are often referred to as non-denaturing detergents and are used to isolate biologically active membrane proteins.
Generally, moderate concentrations of mild (i.e., nonionic) detergents compromise the integrity of cell membranes, thereby facilitating lysis of cells and extraction of soluble protein, often in native form.
An example would be Triton X-100. {2} Non-denaturing detergents such as Triton X-100 have rigid and bulky nonpolar heads that do not penetrate into water-soluble proteins; consequently, they generally do not disrupt native interactions and structures of water-soluble proteins and do not have cooperative binding properties. The main effect of non-denaturing detergents is to associate with hydrophobic parts of membrane proteins, thereby conferring miscibility to them.
The following article is about the same protein insolubility that I have written above, but in the nuclear membrane of chicken RBC’s. {3}

Protein has been selectively extracted from isolated chicken erythrocyte nuclear envelope by (1) dilute MgCl2/Triton X-100 followed by (2) concentrated MgCl2/Triton X-100 solutions. Certain proteins appear to be selectively dissolved in the first solvent and may occur in the nuclear envelope primarily as lipoproteins. Among the proteins insoluble in the low MgCl2/Triton X-100 wash, as well as in 500 mM MgCl2 without Triton previously used in the preparation of the envelope fraction, the quantitatively major polypeptides dissolve in a combination of high MgCl2 and Triton X-100. Further, much of this dissolved protein precipitates when the MgCl2 concentration is lowered by dialysis. The insolubility of these proteins appears to result from a combination of ionic and hydrophobic interactions and may explain the resistance of nuclei to various manipulative procedures including nonionic detergent washes.

The conclusion is that the protein insolubility of these detergents is what makes the nucleus resistant. You know that the phospholipid bi-layer is common for both- the cell membrane and the nuclear membrane. But underlying the inner nuclear membrane is the nuclear lamina, a fibrous meshwork that provides structural support to the nucleus. The nuclear lamina is composed of one or more related proteins called lamins.
Coming to your last question, using the example of Triton X-100 and leukocyte cells, a paper says: {4}

Leukocyte membranes except the nuclear envelope were solubilized in a buffer that contained 1% Triton X-100.

Which means that all membranes- including mitochondrial, dissolve in the detergent because they do not have an additional protein layer in them, like the nucleus does.
1-http://www.genotech.com/protein-research/detergent-accessories.html
2-https://www.thermofisher.com/in/en/home/life-science/protein-biology/protein-biology-learning-center/protein-biology-resource-library/pierce-protein-methods/detergents-cell-lysis-protein-extraction.html
3-https://pubmed.ncbi.nlm.nih.gov/999948/
4-https://link.springer.com/article/10.1007/BF00554425


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Can we compare the effectiveness of an inhibitor by checking how much they change Km and Vmax during a reaction?
While comparing two inhibitors, can we check how they alter the Km and Vmax of the reaction and then decide which inhibitor is more potent.
I tried explaining in this way:
While I think the answer should be "no", I am not entirely sure.
I got these statements from Wikibooks :

Competitive inhibitors can only bind to E and not to ES. They increase Km by interfering with the binding of the substrate, but they do not affect Vmax because the inhibitor does not change the catalysis in ES because it cannot bind to ES.
Uncompetitive inhibitors can only bind to the ES complex. Therefore, these inhibitors decrease Km because of increased binding efficiency and decrease Vmax because they interfere with substrate binding and hamper catalysis in the ES complex
Mixed inhibitors can bind to either E or ES complex, but have a preference for one or the other. This can either increase or decrease Km, respectively. Both cause a decrease in Vmax.
Non-competitive inhibitors have identical affinities for E and ES. They do not change Km, but decreases Vmax.

From this it is shown that the inhibitors do affect Vmax and Km. But I can't figure out a way to compare them. Any help?

Why do you think the answer "should be 'no'"? You can certainly compare two inhibitors of the same "class", that is: either compare two competitive or two uncompetitive inhibitors. If competitive inhibitor A increases $K_{\rm M}$ by $10%$ and competitive inhibitor B by $50%$, then – obviously – inhibitor B is more potent than A.

The kinetics of enzyme inhibitors is a basic aspect of biochemistry that is treated in almost every textbook on the subject and can be found in numerous resources for students — PowerPoint slides, lecture notes and the like. Just search for "Enzyme Inhibitors Lecture Notes" or the like. Then decide what it is you want to compare. One competitive inhibitor with another? One non-competitive inhibitor with another?  Or something else? Clearly you cannot compare different types of inhibitor. You need to clarify your problem before you can answer it.


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How correlated is the chirality of different molecules?
In astrobiology, a proposed way of testing whether life found on another world is alien or originates from Earth is to determine the chirality of its molecules. This is of course only useful when the biochemistry is similar enough that one may suspect contamination.
But this test has a weakness. While different chirality can confirm alien origin, similar chirality does not exclude alien origin.
To mend this, a plausible idea is to cross check the chirality of a wide range of compounds. A false positive suggesting Earth origin would then have an exponentially smaller chance to match every single compound tested.
...or so I hope.
The issue is that I fear various chiral compounds do not have statistically independent default chirality. For instance, common biochemical pathways may produce one compound from another, leading the chirality of the first molecule to directly determine the chirality of the second.
I'm looking for a high level perspective: Does the chirality of a single compound more or less determine the chirality of all other compounds in an entire biochemistry, or are there a great number of compounds that have an arbitrary default chirality compared to others?

If the chirality is not conserved along the biochemical pathways, then the test outlined in the first paragraph is not valid. Although, concievably one could design other tests, comparing various compounds and chains.

Hypothetically if an alien species were found , and if they contained similar biochemical polymers (DNA with A,T,C,G , Protein with 20 Amino acids etc) then we MAY be able to conclude that they share an origin with us. (Just similar chirality does not necessitates the theory of same origin)

Does the chirality of a single compound more or less determine the chirality of all other compounds in an entire biochemistry?

Yes. As Chiral molecules are almost always produced/purified from chiral medium (containing other chiral molecules and/or chiral physical attributes e.g. polarized light).
Therefore (Assuming that the reaction is enantioselective and you want pure chemical with a specific stereochemistry) the configuration of the chiral center of a new molecule does depend on the reagent chirality. Still this relation is not constant and differs from one reaction to another. For instance textbook SN2 reaction leads to inversion of configuration while Williamson ether synthesis reaction maintains the chirality.
A non-racemic mixture of a chiral compound is resulted from previous non-racemic mixture and so on. therefore the stereochemistry of the first non-racemic mixture determined the S/R , L/R ,(-/+) chirality of the entire life per se whose identity may never be fully understood.

Biologic reactions preserve chirality whereas non-biologic reactions generally do not (although there are examples of rxns where chirality is preserved )
I think this strategy would work for comparing  biomolecules with multiple chiral centers. For example, from an IUPAC perspective, D-glucose is (2R,3S,4R,5R)-2,3,4,5,6-Pentahydroxyhexanal and simply among aldoses  & ketals , finding a single biomolecule (not just carbohydrates,) with multiple chiral centers where a single carbon involves a different chiralty than one used by life on earth, would highly suggest that non-earth originated life was responsible.


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Architecture of lamellae in trabeculae in spongy bone
It is easy to find the architecture of lamellae in osteons in compact bone, they're layers of collagen fibers and each layer alternates in the angle the fibers are oriented. Is the lamellae in trabeculae similar, and the main difference that there isn't a central blood vessel to supply the bone cells with nutrients, since that is done trough the marrow instead?


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How to identify the subspecies/breed of a bee
I have been a beekeeper for a number of years and originally obtained my first colonies from a guy in my neighbourhood. However, when I sell bees to someone else, they typically ask what species of the European/Western honeybee (Apis mellifera) I have/they're buying. Technically, they're after the subspecies or breed (like Italian, Carniolan, Buckfast, ...), but I don't know what to tell them. I just call them local (or locally-adapted) bees.
Is there a way that one can find out the subspecies/breed I currently have? Perhaps through DNA analysis/sequencing or some other kind of scientific analysis? Regardless, is such subspecies identification available/accessible to the hobby beekeeper (should read as being relatively inexpensive)?
Images like the following are circulated to estimate one's breed:

However, traits are hardly a definitive assessment of a breed, especially if you consider how close some of the breeds are listed above. For example, what's the difference in a trait ranked 5 and 6, say.

I am not sure about apiculture, but in academic research it is typical that people use microsatellite markers for identifying subspecies of bees. Microsatellite are repetitive regions of the genome that are useful in at identifying different species/subspecies, as well as for generating pedigrees and paternity analysis. Different species/subspecies have different numbers of repeats in a particular microsatellites, and these differing number of repeats are heritable. People use microsatellites because they are cheap, easy to run and reliable for identifying species/subspecies. Because there can be many different alleles (or different numbers of repeats) at a given microsatellite locus, so you only need relatively few microsatellites in total to identify individuals.
An example can be found in this paper. They used 7 microsatellite loci and could reliably identify between different African and European sub-species. It is worth a read of the intro:

Recent population genetic surveys in human (Bow- COCK et al.
1994;DIRIENZO et al. 1994) and other mammals (GOTTELLE et al. 1994;
TAEOR et al. 1994) and in bumble bees (A. ESTOUP,M. SOLIGNAJC. ,M.
CORNUET and A. SCHOLL unpublished results) have shown that
microsatellites are highly efficient at differentiating
populations or groups of populations. In this paper, we investigate their
usefulness for honey bee population studies by adressing the
following specific questions: Are the three evolutionary branches
inferred from morphometry and mtDNA confirmed by microsatellite
data? Are microsatellites useful for differentiating sub-species and
populations within subspecies? How does the pattern of variability of
these markers vary between branches/subspecies/populations and which
factors may be invoked to explain it? Is it possible to assign a given
colony to its population of origin from microsatellite data and how do
the individuals from this colony cluster within the population?

References:
Estoup A, Garnery L, Solignac M, Cornuet JM. Microsatellite variation in honey bee (Apis mellifera L.) populations: hierarchical genetic structure and test of the infinite allele and stepwise mutation models. Genetics. 1995 Jun;140(2):679-95. PMID: 7498746; PMCID: PMC1206644.

Are you using the first word in your post, "typically", in an indirect generalized way or from a perspective of insider knowledge/awareness of apiculture? I ask because the paper you quote only cites a single additional study of unpublished results, which doesn't support the interpretation of "typically" to mean widespread as I think is implied from your post's wording. I don't know one way or the other, but I think it'd be good to clarify your wording and possibly explicitly indicate your knowledge of the subject so that future readers know how to frame your response. thanks.

I slightly misunderstood the post and didn't notice it was talking about bee keepers in particular - I said 'typically' since microsats are (most likely - I don't have direct evidence) used in research to identify different Hymenoptera species/subspecies. I've got a reasonable amount of experience in population genetics of Hymenoptera, so that's what I'm going off. That paper is old, so the citations are out of data, but having a look here shows it is still common. Will amend the post to make it clear.

Thanks! I had a hunch that was the case. Again, I personally don't know one way or the other, and I just wanted to make sure your post was clear to others. Thanks for the update!

@user438383: You mention "cheap [and] easy to run." Can you elaborate? I'm a beekeeper without any lab access, but I'm interested in this as a side-project. Are there tools available to the laymen to perform identify these microsatellite markers?

@Werner - good question - ill edit in the answer to my post soon.

@user438383: Any update you can provide?


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Is this Quercus coccifera?
This specie grows in a dry hilly area in the south of France close to Marseille. I made the picture today. It is quite dominant and grow close to the soil maybe about 50cm.

Yes. That is definitely a Kermes Oak / quercus Coccifera.
It should start blooming in a week or two, in case you're still in the area by then I recommend checking it out.
It is thriving in that area specifically because it's a dry area, otherwise they tend to be pushed out by Holm Oaks / Quercus ilex.
The combination of the area (see below), habitat (dry hills) and picture (especially the acorn cupule) are pretty conclusive and support your original assumption.

also the inferior side of the leaf is usually hairy for ilex not for coccifera

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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Melanistic Snow Leopards?
Are there any confirmed cases of melanism in snow leopards? I am aware that melanism is much more common in Jaguars and Leopards, both often called black panthers, but I cannot seem to find any info on melanism in snow leopards.

I'm not aware of any confirmed cases of melanism in snow leopards either.
There are some relevant studies on the evolution of melanism on Felidae. Melanism seems to occur only in two extant species of the genus Panthera (Panthera onca and Panthera pardus). There is a direct correlation between melanistic colorations and enviroment (especially humidity):

Moist forests (especially in Southeast Asia) presented very high
  frequencies of melanistic leopards (e.g., 39 of 71 individuals [55%]
  in Southeast Asia), and more than 80% of the black animals in our
  database, a fivefold increase relative to the expected number based on
  the overall number of records. Furthermore, we found no confirmed
  melanistic leopards in the Middle East, Arabian Peninsula, Central
  China, and Russian Far East, nor any mention in the literature as to
  the presence of melanism in these regions, indicating that this
  polymorphism is really absent from these areas. Overall, there was a
  significant reduction in the frequency of melanism in some biomes that
  consist of open habitats or temperate forests. There thus is a clear
  pattern in which melanism tends to increase in tropical/subtropical
  moist forests and decrease in open/dry or temperate habitats

References:

https://www.sciencedirect.com/science/article/pii/S0960982203001283
https://www.intechopen.com/books/big-cats/ecology-and-evolution-of-melanism-in-big-cats-case-study-with-black-leopards-and-jaguars


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Are these spinach leaves?
I often buy baby spinach from the store, and sometimes, in a few bags of spinach I also find these leaves:

They have a different shape than the spinach leaves, they are a lighter green, and they taste differently. The bag doesn't say that "it may contain traces of" other plants, so are these some part of the spinach plant? Or are they something different? Why do they often come together with the spinach leaves? I haven't found any other kind of leaves (besides spinach) in the bags except those in the picture.

Those are the cotyledons (seed leaves) of spinach.
For comparison, here's a picture of what spinach sprouts look like:

Source: https://wimastergardener.org/article/spinach-spinacia-oleracea/


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Action potential: why called "depolarization" when polarity is reversed, not removed?
During an action potential, the voltage shifts from the resting potential of -70 mV, to +30  mV, to then fall return back to the resting potential again of -70 mV. This reverse of the polarity, what is the reason it came to be called "depolarization", as in, removed polarity?

While the cell is polarized (in the positive direction) at the height of the action potential, it has been depolarized from its resting, negatively charged state, meaning the original polarity has been lost or reversed. In my mind, the slight (30mV max) positive polarization for that brief period of time is kind of an "overshoot" of neutral charge, just like during recovery the potential exceeds -70mV for a period of time before coming back to the resting state.


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how many times can a spitting cobra spit its venom?
exactly how many times can a spitting cobra spit its venom at a predator
it has a small venom sac, so I presume it can only spit once or twice only

I presume it can only spit once or twice only An unwise presumption.

These cobras exhibited distinct control of venom flow with spits averaging 1.7% of the volume of the venom gland, thus enabling the cobras to rapidly expel over 40 consecutive spits ... There was no significant difference in the amount of venom spat between the first few spits and the 20th spit, however there was a significant (Student's t-test with unequal variance, p=0.017) decrease in the amount of venom spat between the 20th and 40th spits.

--Protein variation in the venom spat by the red spitting cobra, Naja pallida (Reptilia: Serpentes)

so it can spray up to 40 times


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Tools for modelling and visualizing growth of cells
I am looking for a program/GUI app/package that would help me do simulations for cell growth. I have a microscopic mathematical model, and the scenario is basically the following: I start with a rod-shaped cell characterized my its center and direction angle, it grows until it reaches a certain length, it divides into two identical cells whose angles change randomly and the process continues.
Is there any program or package that I can use for such a situation? I have found several on GitHub, but they were mostly for very complicated biological processes. I use Python/Julia/Matlab and can code, but I was wondering whether there are any tools for such simpler scenarios.

Welcome to Biology.SE! Please take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. In particular, this question seems like it might be a better fit for [Bioinformatics.SE]. Thanks!

Hello, mathematical modeler here.  Some context about your model would be helpful.  It seems like a PDE model, for which, generally, people write their own code.  There are some packages that would help - such as finite difference (or other) numerical approximations for the gradient and Laplacian, but without details it is hard to know where to direct you


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Examples of alkali metal and halogens covalently bonded in biological molecules?
Divalent and monovalent ions are often non-covalently bonded in biological molecules, they are primary building blocks of the machinery of biology. Iodine, the halogon in period 5, is covalently bonded in thyroxide. What are other examples of covalently bonded monovalent ions, alkali metals and halogens? Are there molecules that covalently bond Flourine, Chlorine, Sodium and Potassium?

Sodium and potassium are not going to be covalently bound in biological molecules. For fluorine: https://www.tcichemicals.com/en/ap/support-download/chemistry-clip/159-07_ChemistryChat.html, an example for chlorine: https://en.wikipedia.org/wiki/Epibatidine

Thanks, very good answer. The Wiki page on Epibatidine mentions an "extremely high affinity". Gilbert Ling did some work between 1950 and to his death last year, and mentions Robert W. Taft, that may relate to why Epibatidine has "extremely high affinity". It seems that halogens like chlorine polarize the molecule. I'm assuming thyroxine has similar properties since iodine is also a halogen, also, the large effort required by organisms to synthesize thyroxine suggests it should pay off for some reason, so I'm looking a bit for information about that.

Try searching for "bioinorganic chemistry".

A "covalent bond" affords close-to or full homopolarity of both bonding partners. Metals are genuinely low in electronegativity as in contrast to organic bonding partners like C,O,N, ... Thus there never can be colvalent bonds between such metal (cations) and organic moieties.