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Does too much screen time really damage your brain?
So I was looking on the internet for articles to whether computers really damage your brain and I found that half of them say the do and the other half say the don't. Personally I don't think it does as majority of working people use computers in their day to day jobs and still have the same intelligence and cognitive ability after say, 10 or 15 years of using them.
So does anyone know wheter this sttement is true or not.
Thanks,
Ps. I'm not a biologist, I'm just a curious kid :)

"Damaging your brain" is far too vague a claim to be evaluated scientifically. If you can find a specific, notable claim, then skeptics.stackexchange.com is a good site for that question (check their Help to see what is on topic there). If you collect some background and have a specific question to ask about biology that can be asked here.

And of course it might depend on what you actually DO during that screen time.  Developing programs to solve problems in the sciences probably has different effects than say following social media.

JamesM, Rapidly moving images/cartoons/games for many hours per day modify the attention span and self control especially in children, and there is research for that area. It means that children can become confused when they don't have rapidly moving images and they are less able to focus on slow activities like reading, toys, etc. Perhaps read this, it's  a related scare article: https://time.com/5514539/screen-time-children-brain/ low self control i.e. when someone speaks to you and doesn't look calmly at you but looks around fast in all directions while thinking, can vary  with screen use.

@aliential: Interesting.  Perhaps that explains why I find rapidly moving images in video to be so annoying - I was never exposed to them in childhood :-)

Yes Garry Kasparov would not have had any chance of being a chess champion if he had cartoon network on TV as a kid. One study found that even 9 minutes of spongebob squarepants can shorten children's attention spans.


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Is there a negative correlation between the mRNA produced by the cell and the time of extraction?
I am doing some data analysis about gene expression time series. When I plot mRNA produced by P. Furiosus cells irradiated by gamma radiation against the time of extraction, it seems that there is a negative correlation between them. Is it a good result from a biological point of view ?

$\gamma$-irradiation produces single- and double-strand DNA breaks, depending on the dosage, and activates DNA damage repair pathways like p53. During this time, the cell cycle arrests and most if not all mRNA production ceases. For sub-lethal doses of $\gamma$ rays, I would expect to see newly-produced mRNA levels drop off fairly quickly with time following the initial dose, then possibly begin to ramp up again later as the damage is repaired and the cell cycle arrest checkpoints released.

Thank you for your answer MattDmo, but, in this way I still wonder how can be the demage repaired if the production of mRNA in order to produce proteins for DNA repairing is stopped ?

@Manuela cells accomplish this by pre-making the DNA repair machinery so that the proteins are already present in the cell, they just need to be turned on.

Ok, so I have a last question: it also seems that the mRNA produced is higher for the samples which are irradiated with respect to the not irradiated. I am not a biologist, but I was doing this statistical data analysis hoping to find this behavior, so that I can say that P. Furiosus, when exposed to gamma irradiation, produce more mRNA with respect to the samples not irradiated in order to repair better DNA . So this reasoning is nonsense?

@Manuela I don't think you can say much of anything without more information. You may be able to show that, on a cell by cell basis, irradiated cells seem to produce more total RNA than non-irradiated cells, but you can't say anything about why they're doing it. I strongly suggest talking to a biologist familiar with the details of your project. The vast majority of my work has been with mammalian systems, and for all I know there could be different DNA repair mechanisms in Archaea that I'm not familiar with.

All right, thank you so much @MattDMo

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How do Rab proteins ensure specificity in vesicle transport?
From this paragraph, from Molecular Biology of the Cell 6th Edition, the author makes it quite clear that Rab proteins are important for the specificity of vesicle transport and that Rab proteins are used as molecular markers that identify compartments. They also make it clear that for many membrane fusion events active Rab proteins are required on both sides of the reaction. What is not clear to me is how Rab proteins ensure specificity?
The author is not clear on how Rab proteins ensure specificity. The only way I can imagine this happening is that Rab proteins on the target membrane recognise Rab proteins or other molecular markers on the vesicle and only bind to appropriate markers, but the author does not clearly state this in the text.

Specificity in targeting is ensured because all transport vesicles display surface markers that identify them according to their origin and type of cargo, and target membranes display complementary receptors that recognize the appropriate markers.

What 'surface markers' and 'complementary receptors' is the author talking about here? Due to the position of the sentence in the paragraph below I'm inclined to think they are talking about Rab proteins and SNAREs.

To ensure an orderly flow of vesicle traffic, transport vesicles must be highly accurate in recognizing the correct target membrane with which to fuse. Because of the diversity and crowding of membrane systems in the cytoplasm, a vesicle is likely to encounter many potential target membranes before it finds the correct one. Specificity in targeting is ensured because all transport vesicles display surface markers that identify them according to their origin and type of cargo, and target membranes display complementary receptors that recognize the appropriate markers. This crucial process occurs in two steps. First, Rab proteins and Rab effectors direct the vesicle to specific spots on the correct target membrane. Second, SNARE proteins and SNARE regulators mediate the fusion of the lipid bilayers. Rab proteins play a central part in the specificity of vesicle transport. Like the coat-recruitment GTPases discussed earlier, Rab proteins are also monomeric GTPases. With over 60 known members, the Rab subfamily is the largest of the monomeric GTPase subfamilies. Each Rab protein is associated with one or more membrane-enclosed organelles of the secretory or endocytic path- ways, and each of these organelles has at least one Rab protein on its cytosolic surface. Their highly selective distribution on these membrane systems makes Rab proteins ideal molecular markers for identifying each membrane type and guiding vesicle traffic between them. Rab proteins can function on transport vesicles, on target membranes, or both.
Like the coat-recruitment GTPases, Rab proteins cycle between a membrane and the cytosol and regulate the reversible assembly of protein complexes on the membrane. In their GDP-bound state, they are inactive and bound to another protein (Rab-GDP dissociation inhibitor, or GDI) that keeps them soluble in the cytosol; in their GTP-bound state, they are active and tightly associated with the membrane of an organelle or transport vesicle. Membrane-bound Rab-GEFs activate Rab proteins on both transport vesicle and target membranes; for some membrane fusion events, activated Rab molecules are required on both sides of the reaction.

I read this article and it states that;

For its functions, active Rab5 must be localized to both endocytic vesicles and early endosomes.

In this case I can understand how Rab proteins ensure specificity in that Rab5 on the target membrane will only interact with an endocytic vesicle if it has Rab5 on its surface. But is this always the case? Will Rabs on a membrane always require certain Rabs or other molecules on the surface of a vesicle in order to tether and dock the vesicle? If not I can't see how they are providing specificity to transport.

This is a very long question. I appreciate that you have done your research on this, but not perhaps in human psychology: next to nobody will make the effort to read it. Whatever background you wish to provide, you need to start with a clear and precise statement of your problem. If you can’t do that, forget it.

My previous question was deleted for not being long enough. The question is quite simple really. How do Rab proteins ensure specificity in vesicle transport? Will the effectors of certain Rab proteins only interact with specific other Rab proteins?

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What exactly is "chromosome topology"?
I've been reading a lot about Hi-C lately, and this has been bothering me.  So far as I can tell from reading around, the topology is related to the conformation of the linear chromosome.  This seems like a fairly pointless description however, as they should all have the same topology.  A "conformation", in my understanding, is the chromosome being folded into a particular geometry.
On the other hand though, I guess if two genes were brought together to form a loop, they would also form a "hole" (the gap in the loop).  But this seems like a weak connection to make, just because two chromosome regions are paired doesn't necessarily mean they were bound and formed a loop.  It seems the "topology" would "best" be seen after a 3D reconstruction from the pairs data, showing the predicted geometry, and from there you could see how many putative loops and such there are, and thus start to determine the topological properties.
The last possibility I was thinking was that this is in reference to network topology implied by a contact matrix.  This seems the most likely to me, but also the least implied (to me, at least) in the literature I've ever read.
All of this has me wondering if I've missed something about the meaning of "topology" here, as opposed to just "conformation".  I'm wondering if there is a consensus on the precise meaning of topology in the genomics/Hi-C context.

'topology' can just mean 'shape' . "the way in which constituent parts are interrelated or arranged."   whether it is point-set topology, algebraic topology, network topology, chromosome topology. It is the study of the shape of something.

Conformation (chromosome) refers to the spatial organization of chromatin in a cell. A wide range of eukaryotic organisms fold into higher-order chromatin domains. These are affected by TADs (topologically associated domains), LADs (lamina-associated domains), NADs (nucleolus associated domains), constitutive and dynamic.

Topology isn't just about shape though, but about the properties of a shape that are conserved under continuous deformation, ie folding, which all chromosomes would share (w some special case exceptions).  As wiki states: 'The motivating insight behind topology is that some geometric problems depend not on the exact shape of the objects involved, but rather on the way they are put together.'  Linearly, all chromosome (of same type) are put together the same way.  I can see how perhaps there is a network topology interpretation of Hi-C data, but it doesn't seem like the implied interpretation

To use the coffee cup/donut example, there are many ways to deform a donut that maintain the same topology (such as into a coffee cup), and it would be confusing to call all of these different conformations "topologies".  However, you could deform the donut so that regions that aren't adjacent on the surface are adjacent in 3D space, and you could get unique "network topologies", but again, this interpretation doesn't feel like the implied one.  The one exception is if you consider loops in chromosomes, but that also seems correlated, but not great, with Hi-C data

*I shouldn't say "the one exception", I mean the primary exception/caveat

Could be relating to where genes are relative to each other. This affects their activity.

I can see how that might work, the issue is that this would, within one organism, every chromosome should generally have the same chromosomes, just with different chromsome configurations and gene up/down-regulation.  This would change with gene transposition, or gene insertion/deletion, but this topic is not brought up in the literature when talking about topology, or really Hi-C in general (and if it is, those are exceptions, not the rule).  Generally, chromosomes are thought of all as "the same" organizationally, as is shown by comparisons of chr region's characteristics between cell types

@user8243 You are hung up on a mathematical terminology. Your quote about continuous transformation refers to the mathematical term for topology, then the disambiguation goes on to mention discrete , network, electronic layout and geospatial topologies. It's not a word that came from math. Math uses that word because it means "shape" and no one says "shape theory".  I am not sure why mathematicians feel like they own the word... they don't use this with english words 'category', 'field' or 'group' probably because those are far more used in english language than "topology".

I never see a mathematician critique the idea of a 'football field'  by asking why 'Field' is used for that concept when the elements or operations or the identity elements aren't even clear. But I see mathematicians do this all the time about other areas using the word 'topology' .

no one asks about the genus of a chromosome topology just like no one asks about the order of a finite football field. Just about any chromosome topology reference that uses the word 'genus' is referring to the taxonomic level between 'family' and 'species'.

See comments in the answer below, but as an example: "field", "category" etc are very colloquially used terms.  However, something like "algebra" and "geometry" have very obvious mathematical connotations. In terms of linguistic clarity and scientific precision, using such words to mean something else, based on a "non-technical" but non-colloquial definition of a word is extremely confusing for anyone trying to figure out what it actually means.  This is especially the case when this is scientific field, it would be common sense for someone to think the mathematical definition is relevant here

It's important to emphasize also that, as I have mentioned, I am okay with fields using words as they please.  HOWEVER, as indicated by Maximilian Press's answer, and my own confusion, it is not clear that there is a consensus on what topology actually means.  Why not just shape?  Why not just say conformation?  These questions lead people to look up what topology means, which likely leads them into the lap of mathematics, which leads to serious incongruity with it's use here, and its mathematical meaning, which leads to confusion and lack of precisely explicated meaning.  This isn't elitism

As they please* so long as the definition is connected to something meaningful (as it seems to be here). The use of "topology" here isn't nonsensical (and is technically valid), just very confusing, is my point

@JimN hey hope all is well.  I think I found a satisfactory solution, I posted it, let me know what you think

I think that there are a few things going on in this question, I'm going to try to answer the ones that I think are most pertinent:

We should not expect "topology" as used in the Hi-C field to have a rigorous mathematical interpretation. Most of the people thinking about it are ultimately biologists who are interested in biological problems. As suggested in the comments, they are basically interested in the shape of DNA in the cell; e.g. which pieces of DNA are close together and which are far away. You can use this information for a lot of different purposes of course, but most people using the technique are satisfied with viewing topology as "the set of pairwise distances between all DNA chunks" (and whatever things you can infer from that set).

Your sense (from the comment) that the linear chromosome ordering is the main interesting feature of topology is (IMO) absolutely correct. However, it is not a given that every chromosome is put together the same way. This is related to the most useful application of Hi-C data that I know of, which is to either (A) scaffold genomes (put discontinuous sequences into the right order) or (B) deconvolute mixed populations of genomes into groups of sequences that belong to the same cell. The linear order of DNA is by at least an order of magnitude the dominant signal in the data, and is therefore the most trustworthy thing in there.

Network topology is sometimes implicit but generally central as a feature of algorithms using Hi-C data. I don't know that we can say that all workers in the field are thinking of this when they talk about topology, but I certainly am. Some random papers that make it fairly obvious: here, here, here.

(Full disclosure: I work for a company that sells Hi-C kits and services.)

Thank you for your reply.  My question is in part critical of (what I believe is) an unecessary and ambiguous use of the word.  Technically, "geometry" seems to be a better word, but was more frustrating was that "conformation" often seemed not only appropriate as well, but redundantly used alongside "topology".  I'm critical of this though not out of a sense of "elitism", but because it is genuinely confusing.  Anyone trying to understand the "topology" part here will be seriously confused if they end up reading about actual topology.  Your answer is helpful in clarifying its use here

This ambiguity is compounded when its use varies, from a "network" sense to a "shape" sense, that the sense of its use is rarely explicated clearly, and that the term is used so promiscuously.  HOWEVER, this is not to say that using the word "topology" is monopolized by mathematics - I do recognize when a field uses a shared term, it is possible it has different connotations (the point of this question, and you gave a good answer I think).

Still, all of these considerations together mean that the use of "topology" here is very vague and almost inexplicable in its general definition, having very idiosyncratic use going from paper-to-paper, or even year-to-year.  Not even in terms of linguistic use, but even just in terms of scientific clarity, this seems like an unfortunate flaw.

Also, I appreciate those paper links.  I see what you're saying about the uses there

accept the fact that the english word "topology" means anything referring to shape. Another dictionary definition: "1: topographic study of a particular place
specifically : the history of a region as indicated by its topography". Another dictionary: "the way the parts of something are organized or connected:"  Every field of study is entitled to use an english word as it suits their needs

As I said, "this is not to say that using the word "topology" is monopolized by mathematics - I do recognize when a field uses a shared term, it is possible it has different connotations".  What is confusing about topology is that, unlike "category", "field", "group", the word "topology" is no longer (if ever, I do not know) colloquial.  These words do not require anyone to look up a definition in a dictionary.  HOWEVER, the word "topology" does.  And in doing so, you also run into a formal mathematical field.  This seems needlessly confusing when "conformation" can and DOES DO the same job

I think I found a somewhat satisfying solution here, that explains the original use of "topologically associated domain".  I'm not sure if this was the original intent of the semantics, but it works kind of, enough to make the use of topology seem more reasonable.
Topology is, according to Wiki, "concerned with the properties of a geometric object that are preserved under continuous deformations, such as stretching, twisting, crumpling and bending, but not tearing or gluing."
In population Hi-C at least, Hi-C emphasizes/shows the high frequency contacts.  As an example, imagine these as contacts that form a loop (there are other conformations, but this is the simplest case).  The particular loop geometry can vary, but the contact that Hi-C can measure won't vary.  Think about a tied shoe - the shoe can move, the loop of a knot itself can have all sorts of various geometries (imagine squishing it, folding the loop with your hands, etc.).  Regardless, the knot will stay the same; the "string loci" that are adjacent in the knot will always be adjacent, which is an observable that relays that the topology is probably staying the same, ie a "loop" (not to get into knots and stuff, just considering strings touching each other as creating a hole, ie the loop).
Thus, the contact matrices are almost a histogram of the observables which relay topological features, at least for population Hi-C.
For single-cell Hi-C, because we don't have multiple samples, the contact matrix is not a histogram.  Regardless, you can think of it as one term in a histogram, and thus still part of this indirectly topological description.
Let me know if this is unclear.

Can you add your sources? The link to the wiki page etc.?


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Can we produce sugar using chlorophyll dissolved in ethanol?
I can't find anything about this on the net.
I read in my (high-school) textbook that if plants get sunlight, water and carbon dioxide, and the catalyst called chlorophyll, they can make sugar.
I'm just thinking... We CAN extract chlorophyll by dissolving the boiled leaf in ethanol! So can't we just bubble CO2 in and let the sun shine on it and add some water? Shouldn't that make sugar in the solution?

An interesting thought, but your textbook has presented photosynthesis in a highly simplified way. I suggest you go through https://www.khanacademy.org/science/biology/photosynthesis-in-plants (it's fairly detailed!). Then think again about why the method you described may or may not work.

The mechanism of photosynthesis proceeds via light-dependent reactions and light-independent reactions within the chloroplasts (organelles in cells which house the photosynthetic machinery, and indeed chlorophyll itself).
To produce glucose via photosynthesis, you certainly need the pigment chlorophyll - it is necessary but not sufficient by itself. For that, you need the Calvin cycle, which is part of the light-independent reaction within photosynthesis.
The light-dependent reaction requires chlorophyll and uses H2O and sunlight to produce ATP and NADPH, with oxygen as a byproduct. ATP and NADPH are necessary for the Calvin cycle to proceed, which takes atmospheric CO2 and produces glucose and other sugars. This is simplified into basic photosynthetic equation which you are familiar with.
     6 CO2     + 6 H2O  -->  C6H12O6 +  6 O2
carbon dioxide + water  -->  glucose + oxygen

Here is an illustration:

The red arrows point to the light-dependent ("light"), and light-independent ("dark") reactions.
Take a look at this slideshow, which answers all your questions with illustrations.

We CAN extract chlorophyll by dissolving the boiled leaf in ethanol! So can't we just bubble CO2 in and let the sun shine on it and add some water? Shouldn't that make sugar in the solution?

Unfortunately you destroy the chloroplast structures during the extraction you describe. These structures, and especially the membranes, are necessary for photosynthesis in its entirety to proceed.


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How does the position of hydroxyl group in a nucleotide monomer affect the dehydration synthesis of nucleotides?
In dehydration synthesis of nucleotides, the hydrogen atom from the 3' carbon on the deoxyribose sugar of one nucleotide reacts with the hydroxyl group on the phosphate group of another nucleotide to form water. As the water molecule forms, a new covalent bond comes into existence between the two nucleotides.
Hydroxyl group can be in different positions within the phosphate group, for example:

I'm wondering if different positions of the hydroxyl group have an impact on the dehydration synthesis between nucleotide monomers. For example, when the hydroxyl group is at the bottom, will the dehydration synthesis occur at all? Also, when the hydroxyl group is on the left, does the spatial structure of the sugar-phosphate backbone have a spatial shape different from when the OH group is on the top?

You need to keep in mind that simple chemical structure drawings like these do not at all reflect reality on the atomic scale. The 2D electron from the "double bond" is shared among the 3 O atoms (except the one on the right, AFAIK), as is the proton from the hydroxyl group. Everything is floating around in quantum probability clouds, not permanently fixed in one specific position in rigid bonds. The other thing to keep in mind is that a phosphate is a tetrahedron in 3D space and can rotate pretty freely, allowing the dehydration reaction to occur in any conformation.

Wherever the hydroxyl group is; the result is the same I think. The phosphate has oxygen arranged in a tetrahedron around it.
In cells the hydrogen is not attached most of the time. For example the triphosphate on ATP is a weak base with a pKa of about 6.6. Cytoplasm usually has a pH of about 7.2, so an ATP molecule is only protonated (very approximately) 15% of the time.
https://en.wikipedia.org/wiki/Polyphosphate#Acid-base_and_complexation_properties


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Approximately how long will it take to document all existing species?
I did some research and found that there is a new estimate of 8.7 million species, plus or minus 1.3 million and that about 1.2 million have been discovered already. About how long will it take to discover the remaining species?
I just did a bit more research and found that about 18,000 species are discovered each year. If this rate continues, then the remaining 7.5 million species would be discovered in about 416.667 years. If we subtract the 1.3 million to get 6.2 million and divide that by 18K, then we get 344.444 years. If we add 1.3 million to get 8.8 million and divide by 18K, then we get 488.889 years. So by my calculation, it would be anywhere from 344 years to 489 years (rounded). Is this about right? Or are there other factors that could come into play?

Whoever downvoted, would you mind explaining why?

I didn't downvote, but it's usually useful to include in the main post links to where you found those statistics.

I voted to close this question because many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise.

I voted to close your question because I think that it is not a question about biology in the terms of SE Biology as laid out in the [tour]. You may wish to review the three types of question listed there.

For one thing, the species concept is already a little fuzzy when it comes to macroeukaryotes, but it gets especially fuzzy when you get into single-celled organisms (which I'm guessing these estimates ignore). So, estimating the number of species will depend on who you are looking at and where you are looking. Secondly, the number of species in an ecosystem (or in this case on a planet) is not fixed. Evolution is a dynamic process which is always occurring. Populations divide and re-converge, and new species emerge, old species go extinct. The circle of life and all that.
But more importantly, extrapolating the rate of new discoveries out at a constant rate basically assumes that all species have an equal probability of being discovered at all times. Which we know isn't the case. Even if all of the species on earth were equally abundant and equally distributed, this discovery rate would not remain constant.
Imagine a giant lotto ball machine with a seemingly infinite number of balls in it, each with a random number on it. Your job is to sample this machine and document each unique lotto ball number. Say you're sampling one ball per minute. At first, almost every new lotto ball you pick is unique. You're discovering around 60 unique numbers every hour. But after a while, you start to see some numbers repeated, and after an extended amount of time you notice that more than half the balls you sample are already accounted for. You're now discovering less than 30 new balls per hour. The more you sample and record, the lower your rate of new discoveries becomes. Eventually, you are lucky if you can find a unique discovery in any given day of sampling. But you still have no idea whether you have sampled and documented ALL of the unique numbers in the machine.
If you plot the cumulative number of unique numbers you see vs the sampling depth, you get something like a species accumulation curve or a collector's curve. These generally form an asymptotic shape, like this example below. You can use some statistics based on the general shape of these curves to estimate the total number of unique species in a system. It requires making some assumptions about your sampling methods and also about the distribution of your different species, but, in any sufficiently complex community, you end up with this sort of diminishing return rate after extensive sampling.
.
Obviously, researchers are not necessarily sampling new species at random, nor are they sampling at a fixed rate. Technology is a big factor, and research funding in general will affect the rate at which new species can be discovered. But you also have to keep in mind that undiscovered species are not distributed evenly withing or between different ecosystems, and they do not have equal probability of discovery at all times. To return to our bingo ball metaphor, every different ecosystem is like a different bingo machine. In some of them, species might occur in roughly equal ratios, but in others they might have dramatically skewed ratios. Some might outnumber others by a ratio of a million to one or more. And as we add more and more to the cumulative list, those remaining undiscovered are likely to be the more rare and hard to find species.
Given all of the potential factors that might go into determining the rate of new species discovery, it would be difficult if not impossible to estimate when our efforts would reach complete saturation, but it will almost certainly slow down as greater and greater numbers of species are discovered.


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Puffball growing on a tree: What kind of mushroom is this?
What kind of mushroom/fungus is the one shown in the photos?
Description: Looks similar in size (~4-5 cm as I  remember) and shape to a puffball. It is not hard to the touch, unlike typical mushrooms that grow on trees. Several balls were growing individually (not in clusters) from the 2-3 m tall stump of a broken tree, at multiple locations from the bottom to the top. They were breaking through the bark from the inside.
Time and location: Saxony, Germany, in a mixed forest. Early September.

Very interesting! Do you happen to know the species of tree this stump is from? Knowing the "host" can be important for identifying fungi. The leaves in the background look like they could be from European beech, but the bark doesn't look right to me ...

@tyersome Yes, the background is beech. This tree I don't know, and I can't tell from the photo. If I get the chance to go back this week, I'll take a closer look and will try to figure it out. Maybe by then the mushroom fruiting bodies will have developed enough to give us some more hints.

Most trees are beech in this forest, but there's also plenty of oak, birch, conifers, and other things.

they look like mosaic puffball mushrooms (Lycoperdon utriforme), which do grow in Germany, but they don't grow on trees :-/ I don't know what these are

I believe these are Fomitopsis betulina (= Piptoporus betulinus), the Birch Conk (or Birch Polypore or Tinder Polypore), a common mushroom throughout the Northern hemisphere.

Fig. 1. Young Fomitopsis betulina emerging from a downed birch log. image: Eric (CC BY-SA 3.0)
The diagnostic features here are the scattered fruiting on dead wood, the off-white, crackling surface, and the shape. F. betulina is not a puffball, but a polypore like other shelf fungi that grow off the sides of dead trees. Unlike other shelf fungi, they remain fairly soft. These young specimens resemble puffballs, but will expand to expose the pores on their underside. Read about F. betulina and see images of mature mushrooms here and here.
F. betulina grows exclusively on birch, and the snag it is growing on appears to be birch based on the light color and horizontal lenticels. Birches do have similar leaves to beeches, though the surrounding trees could be different species.

Thanks for the guess! Looking at photos of F. betulina, the top and the bottom looks different (the top is brownish and round, the bottom is flat). This one was more or less symmetric. I don't recall seeing any which looked asymmetric, but then it was two years ago ... Yes, this is a lone birch stump and the surrounding trees are beeches.

@Szabolcs The mature mushrooms I linked earlier don't really look like what you found, but see the image I just added - when they're young, they don't have the pore surface on the bottom.

Looks convincing enough!


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What percentage of the brain is memory | Storage of thoughts, episodes
I was reading the article, in which it is mentioned that human brain constitutes 2.5 petabytes of memory. This made me wonder how much of the brain is associated with memory itself. If we categorize brain by functionality, such as dedicated areas for visual processing, audible processing, logic processing, memory storage etc, what percentage of the brain is utilized for memory itself?
I speculate that the brain does more memory related tasks then any other. As a matter of fact, almost all tasks for humans requires memory, so perhaps 70-80% of brain might be just to store memory. Is this correct? If not then what percentage of the brain is used for storing memories?

All of it depending on how you define memory.

@John could you please elaborate. Memory is defined as "storage" of any abstract object such as past events, thoughts, dreams ..etc

everything you brain does is memory, learning how to interpret sense organ signals, muscle movement, etc is all memory.

@John, what about reasoning, cognition, they do indeed differ from memory, althought they utilize memory but I believe the part of the brain that deals with reasoning, cognition, emotions, are not memory themselves.

They are all memory, they learn patterns.

@John its quite hard for me to reason that how is cognition and emotion are memories. Cognition is related to attention and learning endavour, which utilizes memories to keep track of the learned stuff but how come they themselves are memories?

they are learned skills, thus memories. even emotions are plastic meaning their associations can be altered by learning.

@John alright i understood your point after reading the answer below :) so overtime memory shapes the 'function' that gives rises to emotion and it changes. So this function itself is plastic in nature. I somehow wanted to separate these so-called learned functions from 'data' and determine how much is function and how much is data so a function would be the brains 'capability' to recognize, and data is the specific object itself. So function is more or less genetically motivated "someone likes blue color while someone else likes red...". I wish I could have framed my question properly.

It's difficult to say a number because memory and activity are intermixed. Activity induces long-term modifications in the brain wiring which can be considered as memory, but at the same time, those connections play functional roles.
For example, in the retina, the codification of the visual stimuli that are going to be transmitted to the brain is done by a network wiring that is somehow shaped by previous activity.
At an ontogenic level, we could think that the brain architecture in any specie is shaped by a phylogenetic memory during evolution.
Because of that, I'm tempted to respond 100%, but no rigorous answer can be done as far as I know.

This is the answer I was looking for but I still need some clarification. I am interested in the reference for the codification of the visual stimuli that are going to be transmitted to the brain is done by a network wiring that is somehow shaped by previous activity Now I really want to separate out the evolutionary part from functionality part, the functionality of our brain is indeed encoded by external stimuli over the course of the evolution but "given the current state" of the encoded brain,  is there anyway to know how much of the brain is memory and how much function?

So for an analogy we can use evalutionary algorithms to shape hidden layers of artificial neural network, once we reach a satisfactory state, we get a function that although has been shaped by evolutionary algorithm (which relies on memory), is still a function and not memory, when this function is later used to train on some data, say image recognition, we acquire weights and biases which can be considered as memory as weights and biases may differ if one has to recognize certain person or a cat.

@gfdsal There is no difference between the memory and function. Memory is held in the synaptic weights in the connections between neurons; nervous system function involves patterns of activity which in turns are governed by those same weights.

@BryanKrause makes so much sense. Is there any mathematical model or even a general model of this. I want to see how exactly "pattern of activity" simulate a function and why our NN computational models are so bad and less robust against computational model of brain.

@gfdsal Neural networks and brains optimize completely different things, because things that are "easy" for biology to do are really hard to do in simulation, and some computations are really easy to do in silico but very expensive in real brains (for example, the distance between nodes matters in brains, it doesn't matter to any appreciable degree in silico). An adult human has almost 100 billion neurons each making thousands of synapses and trained over somewhere between 18 and 100 years.

@BryanKrause Do we know what exactly are these so-called things that brains optimize? Is there any model of such object. All I learned is that these synapse aggregate in similar fashion as neural nets, you are right that distance in hardware in silicon doesnt matter but we do utilize the notion of distance (more precisely inner product /norm) in the computational model which simulates the nearness of the entities/object being learn just like in the brain...so functionality is mimicked by computational model itself.

@gfdsal This is where I would stop and give the advice I have given numerous people trying to understand relationships between biological and artifical neural networks who are coming from the artificial side...If you want to compare them meaningfully, you need to be an expert in both. So, instead of starting with neural nets and looking for comparisons in biology, you need to start from the ground up in the biology and start learning the biology for its own sake. Then you can start to compare.

@BryanKrause acknowledge. Thanks for the advice.


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Why is the blood thick in Wet Cupping / Hijama
I have just witnessed the wet cupping procedure being performed and have questions regarding the blood that is seen in the cups. I understand there are no studies that show cupping is an effective treatment for many diseases as some claim it to be but my question is regarding the blood that is released.
The procedure aims to eliminate the 'bad blood' which leaves clean blood to circulate the body, the practitioner pointed out the difference between the clean and bad blood and there was a substantial difference in how it looked and flowed. The blood was very clumped up and thick and didn't flow well at all whereas some of the blood was a lot more fluid and was able to flow easily. I was told this runny blood is clean blood and is what we want in our bodies.
My questions are what is the thick clumpy blood and why is it like that?
Is it actually bad blood?
Thank you in advance!

This is very good question indeed as I spoke to someone who said that he had it done and he could literally feel the difference in stress levels and blood pressure. I couldnt find correlation between the two so this is interesting topic to explore.

I believe the reduction in blood pressure maybe due to the removal of blood so with less blood circulating the pressure would drop but I may be wrong. I have also spoken with many people who have had the procedure done and they claim it massively helped with reducing pain such as back pain. I was really shocked at how thick the blood was, it was like a solid and many videos show this same thing and I was curious as to why the blood is that thick and how it doesn't cause the blood vessels to block.

Are you familiar with clotting?

Clotting occurs at the site of damage and this causes the blood to thicken right? If that is correct, then I do understand clotting but my question occurred because some of the cups had little to no thick clotted blood whereas others had the blood completely clotted and some cups had a mixture. Why does this occur if it is only due to blood clotting, shouldn't all cups have a similar amount of blood and shouldn't the blood all have the same viscosity also?

@James That would happen if all the cups were placed at the same time (since clotting takes some time). Did you observe any pattern—e.g. cups placed earlier had thicker blood?

We had a demonstration of blood coagulation/clotting in a biology lesson with the school nurse. She just took half a test-tube of blood sample from a class pupil and we waited a moment, and the blood became a solid lump inside the test-tube.
The process is there to protect you from leaking blood if you cut yourself, the process uses fibers and platelets and complex proteins.
https://www.youtube.com/results?search_query=blood+clotting
wiki: Coagulation
Blood letting is a very ancient practice that used all sorts of methods like annelids/leeches, which has not been proven to have any benefits. The blood in your body does not seperate into good blood and bad blood by sitting in a jar.

let's all downvote everything on the site :) that would be positive :)

Exactly, someone is fooling around by downvoting most of the questions.

What an awesome answer! Thank you! I too don't understand all of the downvotes, I showed research in my question and I believe it to be a good biological question and one which may help someone who had a similar question. 3 downvotes seems a bit excessive maybe if the downvoters explained what was wrong with the question it would help me and others avoid such mistakes in the future, helping the site the improve.


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Polymerase Chain Reaction Specifics
While going over PCR in my biology lecture this week I have come across a few questions I have about this process.
First, since PCR focuses on trying to replicate a specific targeted DNA sequence many times in a short amount of time, are the primers used in every cycle the same sequence? I understand the forward and reverse primers would not be the same but the forward primer for one strand in one cycle, would it be the same as the forward primer for a daughter strand of let's say the 8th cycle?
Second, why are primers not reusable for different cycles? I think this would be based off of the answer to my first question. If the primers are essentially the same sequence, why do new primers have to be used for every cycle?
Thank you in advance!

are the primers used in every cycle the same sequence?

Yes.  You put the whole reaction on the thermocycler, and then walk away until all the cycles are complete.
But one could do a second round of PCR with different internal primers on that first PCR product, if you wanted.

Second, why are primers not reusable for different cycles?

Are you asking why you can't put in 10 molecules of forward primer and get a million product molecules from that?
Each molecule of primer that is used as an extension template is incorporated into a whole stand of PCR product.  It's not a primer any more.

The primer is incorporated into the start of the new strand. The number of dna strands produced is limited by the number of primers.


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Is there an enzyme that functions without being associated with a complex?
I'm looking for an enzyme that does not function as part of a complex in its active state. Preferably it also is not part of a kinase or other kind of activating cascade as well though I would appreciate any and all names that are not part of a complex in its active state. Also would be better if it does not require post translational modifications. Of course, pre translational modifications/ interactions at rna or dna level are all good.
In eukaryotic genome but bonus points for human genome!
Thanks!!

Ribozymes may answer your conundrum here.

Ribozymes are made of 2 subunits though. I'm basically wondering if there is a protein with no quaternary structure and maybe even those little things I mentioned above.

This seems like a XY problem

I'm not really sure how else to phrase unfortunately. But that's a good thing to learn about! Feel free to edit or advise and I'll comply!

I can't really suggest an edit because I have no idea what problem you are trying to solve, and that's kind of the problem with XY questions. What is your goal?

Please provide context (why do you want to know this?) and evidence of your own research. Please restrict yourself to asking a question. We have our own scoring system here and it does not involve posters awarding bonus points. Nor is this necessary as you’ll find it more difficult to find proteins present in other eukaryotes and not man than those also present in man.

I don't really get what David is saying but Bryan, I'm mostly trying to figure this out just cause I can't think of any. Goal is to just name an enzyme which doesn't have a quaternary structure in active form and preferable has no cofactors attached or required and post translational modification.

Acetylcholinesterase.
Chosen because the esterase seems like a low energy reaction so it wouldn't need energetic co-factors.
https://en.wikipedia.org/wiki/Acetylcholinesterase
Not sure if I should do a new answer or not.

Yeah. The Zn is a cofactor so technically doesn't add to the quaternary structure. I'll keep the question open in case someone identifies a completely isolated enzyme.

@SarthakGarg , i have changed my answer.


text:
Where are neurotransmitters secreted?
As far as I know, neurotransmitters are proteins, so they should be secreted from the cell body of the neurons.
However, when I checked online, they say neurotransmitters are secreted in the axon terminal (pre-synaptic terminal). This is due to the incoming nerve impulse to the axon terminal, hence 'exciting' something to secrete the neurotransmitters with the help of ATP (abundant in mitochondria).
May I know what is the true location in which neurotransmitters are secreted?

It's usually helpful to include a link to where you found a particular piece of information, so other users can decide whether it is valid or not. This is better than 'checked online, they say....'.

There are proteins (in truth, small peptides) released by neurons, but these are not the most typical or canonical type so I don't know where you got that information. Wikipedia has a list. Most are amino acids or derived from amino acids. They are transported into vesicles and then released when these vesicles fuse with the plasma membrane.
Neurotransmitters have to be released in the axon terminal. That doesn't mean that neurons can't also release growth factors and such in the vicinity of their cell body, but the entire function of a neuron is to transmit a message from one place to another (after some processing that occurs based on received input). Neurotransmitters are the way that message is released for most neurons, and axons are the typical "output" structures of a neuron.


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Do most bacteria have plasmids?
Do most bacteria have plasmids?
I googled that and I found this

Yes, Plasmids naturally exist in all bacterial cells. Here

But I know some of them don't!
Is this sentence scientifically correct?

Most bacteria have plasmids. If you study a random bacterium, you will probably find plasmid(s) in it.

I am voting to close this question as it is not a question about biology (nor even one about scientific terminology) but about use of the English language. It might be appropriate on [ell.se].

Ignoring the grammatical quibble for now - how do you know that some bacteria don't have plasmids?

@MattDMo I know that from my textbook, I added a picture.

I think there might be some confusion between individual bacterial cells and "Bacteria" in general. The link you shared is either oversimplifying to the point of losing touch with the truth, or they simply used inappropriate word choice. It's unfortunate that they didn't seem to include a primary source to backup that claim.
For a more general statement like, "Most bacteria have plasmids," I would interpret that as meaning plasmids have been found in most bacterial lineages, not necessarily that most individual bacterial cells have plasmids. But I could see how that might confuse some readers and/or educational content creators.
I will share this for reference. The distribution of plasmids is typically heterogeneous within populations, and variable between populations. For any given plasmid, it's common for only a fraction of the population to carry it. Sometimes nearly 100% of a population carries has the same plasmid, but in other cases it can be 10% or less. I would wager that it depends on how mobile that plasmid is and on the selective pressures specific to the environment in which they are living.
I have personally observed this heterogeneity even in laboratory strains under antibiotic selection. I once determined that less than 20% of my E. coli cells in a culture were actually carrying the plasmid under selection (I did this quick experiment because I was not able to recover detectable amounts of the protein that I was trying to express in my strain).
The reference I linked might be a useful resource for the OP. In case that link doesn't work, here's the reference.
Holger Heuer, Zaid Abdo, Kornelia Smalla, Patchy distribution of flexible genetic elements in bacterial populations mediates robustness to environmental uncertainty, FEMS Microbiology Ecology, Volume 65, Issue 3, September 2008, Pages 361–371, https://doi.org/10.1111/j.1574-6941.2008.00539.x

When people work with E. coli in labs, they often use a strain initially without plasmids - which is very easily infected if someone else nearby is working with a strain that does have a plasmid.

So if we leave the lab, it is pretty unlikely to find a bacteria without plasmid(s) in nature, isn't it?

Uncertain, I dont know if a survey has been made.

@AmirhoseinRiazi - Plasmids are commonly found in natural bacterial populations. See the link in the answer I posted for more information.


text:
Why does increasing concentration of extracellular sodium have no effect on electrical gradient of potassium?
I learnt that the permeability of an ion across the membrane contributes to the membrane potential as much as(or even more than) its concentration and electrical gradients. And so far I've made peace with the fact that Sodium, having a very low permeability, doesn't contribute much (through its own movement) to membrane potential despite having a high electrochemical gradient directed towards the cell's interior.
Now, the confusing thing is that, if I imagine dumping some sodium ions (with their positive charge) on the cell's exterior, this would affect the electrical gradient of potassium (and in fact other ions)--because more positivity is recorded externally-- making potassium in particular less "ready" to diffuse out of the cell. The result of which would be a depression (that is a more negative value ) of the resting membrane potential.
If potassium's extracellular concentration were increased instead, a similar effect would be observed.
What exactly is wrong with this reasoning?
I'm putting this forward because my Professor mentioned only extracellular potassium ion as having an effect on membrane's resting potential.

You can't just add a bunch of positively charged ions in a bucket; they always come with a negative counterpart. If you somehow could, you would create lightning. Electricity is pretty powerful stuff.

Are you sure that adding extracellular $Na^+$ would inhibit $K^+$ migration?

I've answered a bunch of very similar questions here and on Psych & Neuro. They all end up being approximately duplicates but the underlying question is really just "how do membrane potentials work" and everyone has a slightly different misunderstanding. Some places to start: https://biology.stackexchange.com/questions/88730/when-is-voltage-generated-across-a-membrane/88777#88777 https://biology.stackexchange.com/questions/64762/cell-biology-resting-membrane-potentials/64773#64773

https://biology.stackexchange.com/questions/76166/ambiguity-about-the-relation-between-membrane-potential-and-concentration-gradie/76167#76167 https://biology.stackexchange.com/questions/52122/why-does-the-side-of-the-mebrane-of-a-neuron-with-a-high-concentration-of-positi/52595#52595 https://biology.stackexchange.com/questions/77919/why-does-resting-potential-not-become-continually-more-negative/77925#77925 https://biology.stackexchange.com/questions/57064/why-is-it-possible-to-calculate-the-equilibrium-potential-of-an-ion-using-the-ne/57066#57066

@BryanKrause , thanks for the links. But before I check them out, I'll like to make sure I understand your answer. Since we cannot add positive ions without accompanying negative ions, the change in membrane potential resulting from increase in potassium's extracellular concentration is NOT due to change in its electrical gradient (since just about same amount of negative ions from wherever counteracts that). But what then would be responsible? The change in its concentration gradient?

@Chemo-Mike Yes. If you add extracellular potassium, there is less of a concentration difference between in and out so the net flow of potassium ions from inside to outside is lower at any given voltage. Therefore, the voltage that takes the net to become zero (the "reversal potential for potassium") is less negative. The Nernst equation shows this for potassium considered by itself, and the Goldman equation will tell you what resting potential will be once accounting for other permeable ions.

Ok. Got that!


text:
Do sieve tube cells have any extrachromosomal circular DNA at maturity?
In order to generate a tube system of low resistance, sieve elements lose most of their cellular components such as the nucleus, cytoskeleton, ribosomes, tonoplast etc.
Mature sieve elements contain structural phloem specific proteins (P-proteins), mitochondria, ER, and sieve elements plastids.
In plants, sieve tube cells lose their nuclei at maturity (just like our RBCs), and thus lose their chromosomal DNA, but they don't lose their mitochondria.
In eukaryotic cells Wikipedia has divided extrachromosomal DNA into three parts based on where it is seen (I guess):

Mitochondrial
Chloroplast
Circular

Sieve tube cells have mitochondrial extrachromosomal DNA at maturity, but I'm not sure about the existence of extrachromosomal circular DNA in these circumstances.
Do sieve tube cells have any extrachromosomal circular DNA at maturity?

Hey, got it wrong way around! Sieve cells lose the nucleus, not the companion cells.

@PolypipeWrangler Corrected! Sorry. I hadn't slept for nearly twenty-four hours when I was writing this question.

I can't add anything because the "edit" link under my question disappeared but this question is relevant.

This ref. says that the plastids and mitochondria are still intact.
Found by searching for "sieve cell development"
Neuberger, D.S., Evert, R.F. Structure and development of sieve cells in the primary phloem ofPinus resinosa . Protoplasma 87, 27–37 (1976). https://doi.org/10.1007/BF01623956
https://link.springer.com/article/10.1007/BF01623956

I can't add anything because the "edit" link under my question disappeared but this question is relevant.

I cannot edit either.

Mods should do something about it. Do you know an alive plant cell that has no nucleus and no other DNA simultaneously?

I dont know of any, apart from developing xylem cells.

You know I've seen a false/true question: An alive plant cell may have no organelles.

Maybe these developing xylem cells are intended by the questioner I don't know.


text:
At what point during an organism’s lifespan do mutations occur?
I’m a software developer and I’m implementing something called a Genetic Algorithm. I would like some input on when during an organism’s lifespan mutations occur.
Genes mutate throughout the lifetime of an organism. When do the bulk of mutations, which would effect the offspring of an individual, occur? Do most mutations happen at conception and early adolescence, or do a significant number happen between adolescence and parenthood?

it is not so much when as to which cells, only mutations to germ line cells get passed on the the next generation and they can happen any time. https://en.wikipedia.org/wiki/Germline_mutation#:~:text=A%20germline%20mutation%2C%20or%20germinal,together%20to%20form%20a%20zygote.

@John I suppose that it varies between the sexes (in humans at least), since males only produce sperm during puberty, whereas females produce eggs effectively from birth, right?

Are you asking just from curiousity, or because you intend to make your implementation mimic life?  If the latter, my advice is not to bother: life is not the optimal way to implement GAs.

Well, in general, mutation happens after selection, and before fitness evaluation in a GA. I was curious if there was any biological basis for this. Seems like, based on MikeyC's answer, it does make sense to to do mutation before calculating fitness.

I'm assuming this question is primarily interested in heritable mutations, given the evolutionary nature of the link you shared. Only mutations in germ cells are heritable, so it will vary between males and females.
Female germ cells are formed in utero. Oogenesis in humans and is pretty much finished by 20 weeks gestational age (there's some debate about this, but it seems to be the current consensus view). So any heritable mutations would need to happen during gestational period. Note that that gestational age number probably varies quite a bit for different animals, but I think it's generally completed before gestation is completed (in mammals at least).
Males produce gametes via spermatogenesis continuously throughout life. So, for modeling purposes, you could probably use the age at which they conceive (though the sperm actually take a couple of months to mature).
One thing I'm unsure about is whether or not aging in the male affects the mutation rates in sperm, but might be something for the OP to look into.


text:
Is a "Nerve" a cell or a tissue?
Nervous tissue includes Neurons and Glial cells. Neurons have soma and other projections (neurites) namely Axon and Dendrites. Axon or dendrites of a nerve cell covered with endoneurium
is called nerve fibre, a bundle of nerve fibres covered by perineurium is called
nerve fasciculus, many nerve fasciculi covered by epineurium form the "nerve". Is the "nerve", which is present in the PNS, will be regarded as a tissue or a cell?

Welcome. As far as I can see, you've answered your own question.

I'm new to the subject, can you please elaborate, if you don't mind?

What kind of response is that?

I advise you to scour google and search for "cell versus tissue" - the thing you need to get clear for yourself is the distinction between these two terms. Then this question will be answered quite easily.

I think you are clear that nerves are not cells. Your question should be more precisely: Do nerves have the propierties to be consider a tissue?


text:
View and plane/section of neural tube
I have a question regarding the following image:

In my book, it states that this is a dorsal view which shows the formation of the neural tube. However, isn't this a caudal view of a transverse section? A dorsal and ventral view wouldn't apply to a transverse section right?

It looks like a dorsal view to me, like your book says.
It isn't a section at all, these are embryonic structures visible from the outside.
Maybe you are being misled by the orientation of the neuraxis differing among organisms? The head will develop at the anterior neuropore; the spine will develop down the middle. You are looking at what will be the back.
Here's another view from Gray's (downloaded from Wikipedia at https://en.wikipedia.org/wiki/Somite#/media/File:Gray20.png ):

Thank you for your answer. The neural folding was shown from two different perspectives. The first perspective being the original image in the post and the second one being: https://i0.wp.com/veteriankey.com/wp-content/uploads/2017/09/c16f002-1.gif?w=960
That image is a 'sagittal section'. In that case, isn't the original image the top (cranial) view of this section?

@Stallmp It doesn't make much sense to refer to a "cranial" view when there is no cranium. Certainly neither of these is a sagittal section, though. Your second image in the comment is a transverse slice; in that image, dorsal is "up". Can you provide a citation from what book this is or at least a more complete image? You've cut off all the description and explanation.

So if you look at the original post in my message, this is apparently a dorsal view as mentioned. There is also an anterior neuropore, which is the cranial neuropore, and a posterior neuropore, which is the caudal neuropore. In that case, isn't the second image a 'sagittal' view of either the cranial or caudal neuropore?

No, the second image is not a sagittal view of anything, and it is not showing a neuropore. In (B), you see the neural folds closing in, such that in (C) it has closed and formed a neural canal. So it's from someplace in the middle of the first image. See the "somites" on each image (same thing as "primitive segments" on the one I posted)?


text:
Howthe body differentiate between foreign and native protein? How does it know when to create an immune response?
How the body differentiate between a foreign and a native protein?
Suppose there is a bacteria, it has lot's protein on its membrane, with specific structures. How does our body know it's the foreign protein? How does it know, the particular configuration is native or foreign?

Welcome to SE Biology. Please finish reading  the [tour] to find out about this site, and the Help on Asking Questions. You will see that you are expected to do some research before posting, and such research would make it clear that there are whole books written on this topic, and it certainly is not possible to explain it in less than a book chapter. Unfortunately that does not make your question suitable for this list. Any brief answer here is unlikely to be as useful as professionally written and illustrated resources.

Can you please suggest me any book? I am new to biology.


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Are Oct4 and Oct3 the same protein?
Are the transcription factors Oct4 and Oct3, who are encoded by the POU5F1 gene, actually the same protein, or alternative spliced products from said gene?

The best review I can find is the one by Wang and Dai 2010, conveniently titled starting with "Concise review".
From the beginning of the abstract:

The human OCT4 gene can generate at least three transcripts (OCT4A, OCT4B, and OCT4B1) and four protein isoforms (OCT4A, OCT4B‐190, OCT4B‐265, and OCT4B‐164) by alternative splicing and alternative translation initiation

and from later on, in the introduction:

It is well established that OCT4 gene (official symbol POU5F1, also known as OCT3, OCT3/4, OTF3, and OTF4) functions as a master regulator in maintaining the properties of pluripotency and self‐renewal of ES cells

I take from this review that OCT4, OCT3, OCT3/4, whatever you want to call it, all refer to the same gene. However, this gene does have splice and translation variants. It seems that when talking about these variants, you will see them differentiated using A/B/B1. An older paper and some that cite it, Takeda et al, 1992, refers to the splice variants as OCT-3A and OCT-3B. If not noted, you can expect that the paper is considering them all together regardless of whether they call it OCT3 or OCT4.
I did find one thesis that treats Oct3 and Oct4 as separate proteins, renaming them from the A/B terminology, but they cite only the Takeda paper for this, which does not do the same. It seems more likely to me to be a mistake.

Takeda, J., Seino, S., & Bell, G. I. (1992). Human Oct3 gene family: cDNA sequences, alternative splicing, gene organization, chromosomal location, and expression at low levels in adult tissues. Nucleic acids research, 20(17), 4613-4620.
Wang, X., & Dai, J. (2010). Concise review: isoforms of OCT4 contribute to the confusing diversity in stem cell biology. Stem cells, 28(5), 885-893.

Seems like they are the same. I found the below by using the search terms of "genbank oct3"
I see the names and splicing variations at:
"Atlas of Genetics and Cytogenetics in Oncology and Haematology"
http://atlasgeneticsoncology.org/Genes/GC_POU5F1.html
and also see a statement calling it oct3/4
at:
https://www.spandidos-publications.com/ijo/52/6/2069
which is "expression of Oct3/4 in human breast cancer and normal tissues"
Authors: Feng-Qi Zhao Yogi Misra Da-Biao Li Marilyn P. Wadsworth David Krag Donald Weaver Joseph Tessitore Da-Wei Li Guo Zhang Qing Tian Katie Buss
View Affiliations
Published online on: March 29, 2018     https://doi.org/10.3892/ijo.2018.4341
Pages: 2069-2078


text:
Why do we use an autoclave at 121°C (250F)? (Origin)
Let me start by saying I know why, but I am inquiring more about the origin.
My question is more related to literature that I cannot seem to find.
I've found some helpful papers and information on the origin of the using 121°C for sterilizing equipment, and killing bacteria but I wanted to ask the question anyways and see if anyone knew something more about it.
So to restate my question, I want to see data as to why 121°C and not 120°C?
Originally I though it is because the experiments might've been conducted in F and the inter-conversion from F to C yielded 121°C which is an odd number.
From what I could gather it started in the food industry with a company that made canned products and their canned products were exploding. This company approached MIT and after some research they found that at 121°C (250F) for 60 min in retort would kill the spores surviving the previous processing. (further exp. reduced the time to 10 min, for canned clams)
This is detailed in the paper which was published in 1897
https://www.jstor.org/stable/1623441?seq=1#metadata_info_tab_contents
The autoclave was invented in 1879 (18 years prior to the publication).
At the end of the publication it says:

Detailed descriptions of the organisms and of many more experiments will be given in our full paper on this subject to appear in a forthcoming number of the Technology Quarterly

I have not been able to find this specific issue of Technology Quarterly
The authors (S. C. Prescott and W. Lyman Underwood) also say:

As we have shown in our previous paper, in order to insure
sterilization in practice, it is necessary to obtain and maintain a
temperature in excess of 121°C (212F) throughout the contents of the
can. Intermittent sterilization may be employed, but is less efficient
and is not practicable upon a large or commercial scale. We have found
by experiment that sixty minutes at 121°C (250F) is sufficient time for
sterilizing corn, and it seems probable that this can be shortened
somewhat or the temperature reduced.

They are using °C, but since it's 1890's retorts (autoclaves) used in food industry might be F and the authors probably converted retort eqipment readings to °C for scientific community.
Also, this was what pioneered thermal death study and if you look at the temperature that they used for the study they are kind of sporadic. Probably because they wanted to see what temperature + time would reach the center of the can. The length of heating, or processing, and the pressure which is given vary somewhat in different factories and that might’ve been what led them to the 121°C and not 120°C.
Further research was done in this field:
In 1956 and 1958  F. H. Deindoerfer & A. E. Humhrey found that 250F (121C) is the optimal temperature to avoid damage nutrient media. They also discussed analytical methods for heat sterilization times.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1057515/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1057690/
What I've been specifically looking for is the first thermal death study with D&Z values that led to the widespread usage of 121°C. Andy why the time and psi required for sterilizing biological samples. I know and found papers on what is used to validate Autoclaves.
Geobacillus sterothermophilus (known as Bacillus sterothermophilus also) is used for validating autoclaves and that is due to it being very heat resistant, making a good biological indicator of microbial life post sterilization. The one paper I found which had some graphical data about its thermal death rate uses °C instead of F. I cannot seem find any information on the bacterial Log reduction at 120°C comparing it to 121°C. This answer might as well as be a mathematical equation leading to the that temperature, but that is only venue I haven't explored
Paper on Geobacillus sterothermophilus: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1057891/
If anyone can find that Technology Quarterly paper I mentioned at the start that'd be great.

I think your well-researched question is probably as close as you'll get to an answer here.  Still gets an upvote from me but I just doubt we have an expert in 19th century autoclaves. From a practical perspective, I doubt anyone has ever compared 120 to 121 - why would you? For one, the tolerance in the thermometer could very well include that degree of difference, especially decades ago, and the degree of sterilization is unlikely to be meaningfully different over any small difference in time or temperature.

At some point you might consider posting a different (i.e. not identical) but related question in History of Science and Mathematics SE. Have a look around and see if something can be written that fits the site.

Thank you, I'll look into that and rephrasing my question.

+1. Interesting question. Why do you write the link to the same F. H. Deindoerfer & A. E. Humhrey papers twice?

I have a strong suspicion that 250F was picked because humans like to round numbers to the nearest 5s, 10s, and consequently 50s. The conversion to centigrade leaves it at 121. If it ain't broke, don't fix it. Scientists can be lazy like that.

good catch on the duplicate link, fixed it

Quick answer:
For historical and engineering reasons, standards for sterilization with autoclaves were developed with steam pressure and time being the operational parameters.  Temperature wasn't even measured by autoclaves until decades after they were in widespread use. For human factor reasons, the most appealing combination of sufficient pressure and time was 15 pounds per square inch pressure (one rounded off Earth atmosphere) for 15 minutes.  The temperature that corresponds to 15 psi steam pressure is 121°C.
Long answer:
It's all about the history of steam technology and the numbers people find easy to use and remember.
Steam power was the basis of industrial process in the 19th century, and to use it safely required monitoring and controlling boiler pressure. Boiler explosions were not uncommon in the early days of steam power. The Bourdon pressure gauge was invented in 1849 and was a robust technology that yielded reliable and accurate measurement of steam pressure.
https://journals.sagepub.com/doi/pdf/10.1177/002029408702000803
When Chamberland invented the autoclave in 1879 from Papain's earlier pressure cooker, it relied exclusively on pressure measurement for control. Not until 1933 were autoclaves produced that monitored temperature at the drain line to confirm that air was exhausted and the steam was truly saturated.
https://www.steris.com/healthcare/knowledge-center/sterile-processing/everything-about-autoclaves
Study of steam engines was the basis for the development of thermodynamics and the kinetic molecular theory of gasses. Although steam is far from an ideal gas, there is a predictable relationship between temperature and pressure in saturated steam as well as well established properties of heat transfer. These can be found on standard engineering steam tables.
Examples: https://www.engineersedge.com/thermodynamics/steam_tables.htm
Saturated steam is very efficient in transferring heat. This is why scald injuries are so severe compared to simple burns at the same temperatures. It is also how saturated steam kills even heat resistant microorganisms in an autoclave. https://learnaboutgmp.com/good-manufacturing-practices-cgmp/saturated-steam-efficient-sterilization/
Many combinations of pressure and time will do the job, but some are more appealing to people than others.  One earth atmosphere of pressure at sea level is defined as 14.69 pounds per square inch (psi), though in reality it varies a little bit due to temperature and weather. Because of this variation and because humans using Arabic numerals, to do arithmetic and algebra like integer units in 5's, engineers often round off 1 atmosphere of pressure to 15 psi.
This amount of saturated steam pressure was well within the capacities of typical steam boilers of the late 19th century. And a nice round 15 psi of saturated steam will kill even highly resistant bacterial endospores in just 15 minutes.  This pressure/time combination yielding an obvious mnemonic for adequate sterilization: 15 psi for 15 minutes.
The temperature of that 15 psi of saturated steam? 121°C.
And that is why we use the very unusual 121°C for typical autoclaving. It's because we are really using a rounded one earth atmosphere of steam pressure for the same number of minutes as psi of pressure. And we did so without concern for direct temperature measurement for the first 50 years of autoclave use. Even today, the temperature of the autoclave is of secondary importance.

Nice answer. +1. Might I recommend taking a play out of one of our best answer writer's playbook: the summary/long answer style. See here, here, and here for examples. I write long posts like you, and I know my posts (e.g., here) began attracting more attention once I started emulating @AliceD. Not necessary, but it works well. cheers.

Thanks for the advice! I've used the short answer/long answer approach in other contexts, you're right it would be useful here.  I've also been trying to tighten up my answers more generally partly for readability, but also time writing, and less wear on my arthritic hands.

whenever you find a weird standard value in science the answer is usually we didn't use to use those units, but after standardization there was no reason the change the value when we changed units.


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Why does water flow from low to high concentration? Shouldn't it be the reverse?
So my understanding of water flow is as follows:
Basically, water moves about randomly because it has thermal energy. It will occasionally hit other water molecules and "bounce" back. As such, in areas of high pressure, water bumps into other water molecules a lot. However, if a high pressure water tank were connected to a low pressure empty tank, some water would be hit in the direction of the empty tank, but it wouldn't get hit back. Over time, more and more water is hit over until the water pressure equalizes. A vacuum doesn't suck so much as not push back, if that makes sense. So my trouble with hypotonic/hypertonic solutions is as follows. In a hypotonic situation, the solute concentration outside the cell is lower than inside the cell. A hypertonic solution is the reverse. So a hypotonic solution has fewer water molecules, so you would expect water to flow out of the cell because it's not getting hit back as much. But it flows in. The reverse is true for hypertonic solutions. Why is this? Thanks!

Why do you think a hypotonic solution has fewer water molecules?

A hypotonic solution has lower solute concentration outside the cell than inside the cell. In other words, the ratio of solute to water is higher inside the cell than outside. In order to equalize the concentrations, the solution inside the cell must be diluted, by drawing in water from outside the cell. A hypotonic solution has more water molecules per solute molecule than inside the cell, so water moves into the cell.
Your mistake is in thinking that a hypotonic solution has fewer water molecules than the cell. In a relative sense, it's the opposite - the hypotonic solution has a lower concentration than inside the cell, and therefore more water per solute than inside.


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Hormonal effects of Luteinizing hormone on endometrium
What is the effect of luteinizing hormone on the endometrium?
A general answer to this query is that it only thickens it. The same could also be said for the effect of Follicle stimulating hormone (FSH) on the endometrium as well.
Where lies the difference?

Both FSH and LH are indirectly involved in endometrial thickening:

GnRH regulates release of the gonadotropins- luteinizing hormone (LH) and follicle-stimulating hormone (FSH) from specialized cells (gonadotropes) in the anterior pituitary gland
LH and FSH promote ovulation and stimulate secretion of the sex hormones estradiol (and estrogen) and progesterone from the ovaries.
As estradiol levels increase, the intact basal layer regenerates the endometrium to its maximum thickness late in the ovarian follicular phase (proliferative phase of the endometrial cycle).     ...{1}

Again, wikipedia{2} says the same:

...In both cases, the endometrium initially proliferates under the influence of estrogen.

The difference between the hormones, of course lies in their other functions. You can see this for more on that. To clarify again, the endometrium does not thicken 'differently' under the influence of each.
{1}-https://www.msdmanuals.com/professional/gynecology-and-obstetrics/female-reproductive-endocrinology/female-reproductive-endocrinology?query=lh
{2}-https://en.wikipedia.org/wiki/Endometrium#Cycle

extending @Bipasha: (cant comment yet)

As the endometrium gets to the to the mid-cycle (ovulation), the LH surges, and the become more dominant in the "luteinising phase" of the ovary. In this phase, in response to the LH, the ovary secrete progesterone that "stables" the endometrium in the "secretory phase".
When the LH drops, the progesterone drops and the endometrium sheds. In clinical perspective it's called "progesterone withdrawal" and the principal used for fertility evaluation.
When the regular and timely mensuration occurs, its serves as an indirect indication that the endometrium "saw" estrogen (or other derivative as esterdiol) and later, progresteron.
In other words, in the right physiological fertile context, LH is indirectly stabilise the endometrium.


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What's the role of SNP (Single Nucleotide Polymorphism) in a disease when there is no gene associated to that SNP
I am quite new to the field of GWAS (genome-wide association studies), and I'm combining GWAS results and single cell analysis on type-1 diabetes (T1D), to see the role of cell specificity on the disease.
However, I don't understand one aspect about GWAS results. The GWAS results lists all the significant SNPs (low p-value) from a certain study on a particular disease. After that, those SNPs are mapped to genes using either positional mapping (using windows), eQTL mapping, or even both.
However, some SNPs do not map to any genes using both positional and eQTL mapping procedure. Some removed SNPs even have a lower p-value than those which are mapped to genes.
Here is my question: since all the listed SNPs are supposed to be significant (tiny p-value), how can those SNPs which are highly correlated to the disease also show no association towards any gene. How do these SNPs give rise to the disease?
I would like to thank you in advance. Sorry if I'm using wrong jargon or anything, and please let me know, if you want any further clarification.

SNPs do not signify anything about the functionality of a particular piece of DNA. You can think of a SNP as just a sign that says "hey, something in my neighborhood might be interesting!!" In this respect many GWAS SNPs are so-called "tag SNPs", that have been selected specifically to give the minimal number of SNPs that can be linked to all of the genome (e.g. every 1 centimorgan there is a SNP, or whatever).
So: SNPs do not say anything about biology, or about genes. The only thing that they signify is linkage to something that is possibly interesting.
Your issue seems to be that you are coming up with GWAS SNPs that do not show apparent linkage or statistical associations (e.g. eQTLs) to anything that you think should be interesting.
There are a lot of ways in which this could be the case:

There actually is a gene in that part of the sequence, and we just haven't annotated it properly.

The reference genome is wrong in that SNP's location, or is missing an interesting piece of sequence (i.e. a gene) that exists in your population.

That SNP has a population structure signal (i.e. it is more common in one population than another) that is associated with your trait of interest, which you have not properly corrected for.

That SNP is spuriously linked (for whatever reason) to a more distant part of the genome.

That SNP was mis-mapped and is actually in the wrong part of the genome somehow.

There is technical interference due to high similarity to some other part of the genome, which your procedure has not corrected for.

Sometimes frequentist p-values are not actually informative and a thing that looks interesting according to p-values is simply not interesting.

Though there are no genes, there is a long-range enhancer in the region of the SNP that affects a distant gene.

Though there are no genes, there is repetitive DNA linked to the SNP that leads to a complicated regulatory feedback that affects something about your character of interest.

Something about microRNAs?

Your SNP doesn't have any genes nearby, but it is linked to a TAD boundary that affects overall chromatin architecture.

There is a long non-coding RNA there.

Your eQTL significance threshold is too stringent.

Your eQTL association analysis missed an important isoform or transcript.

... and many other hypotheses! Many of these are very hand-wavey or unlikely, but sometimes biology is just weird.
However, in general I would default to an explanation in which there is some kind of technical or statistical artifact. Even when nothing is obviously wrong, there is usually some kind of technical problem in genomic datasets.

This is a great answer.

Are you sure about your artifact proposal? I seem to remember a recent paper in Nature by the ENCODE consortium that is consistent with the poster’s observations. You might check, or I will if you don’t have full access.

@David if you are referring to the estimated functionality proportion, yes that is ENCODE. subsequently a lot of evolutionary biologists got very angry about that and discredited a lot of it, but my explanations (8, 9, 10, 11, 12) are all basically ENCODE-adjacent- it's def true that there's a lot of stuff in the genome that ain't a gene that is still biologically notable. However, I would argue that artifacts (explanations 1,2,3,4,5,6,13,14) are still more likely. Of course, it can be an artifact and still be interesting!

OK. I found the papers and they weren't quite what I remembered.


text:
Adaptive radiation vs divergent evolution
What is the difference between divergent evolution and adaptive radiation? People have Said different things
Divergent evolution is when species from a common ancestor evolve differences by adapting to different environmental conditions
Adaptive radiation - species evolve differences due to the different environments
Are they essentially the same thing also I’m confused with the terminology niche
Could someone please tell me the similarities and differences between the two

Welcome to SE.biology & thanks for your question. It's helpful for people trying to answer your question if you include links to sources for the statements made, rather than saying 'People have said different things'.

They are similar, but distinct, concepts.
In divergent evolution, selective pressure causes differences within a single species to accumulate, eventually leading to speciation. Speciation can be caused by a variety of factors, such as geographical, reproductive, behavioral, or temporal isolation, etc.
In adaptive radiation, typically several niches are present in an ecosystem, leading to several species evolving from a single common ancestor. A niche is essentially an opportunity for a species in an ecosystem to evolve, to where there is little to no competition. Darwin's finches tend to be the prime example for adaptive radiation. Since there was little competition when the finches first arrived at the Galapagos islands, they speciated into multiple distinct species to specialize in consumption of seeds, fruits, insects, etc. Eventually, each species evolved to have distinct traits, such as in their behaviour and reproduction, making mating between species close to nill.

There is not a hard, clear distinction between the two.  In divergent evolution, accumulation of differences as a result of selective pressures amounts to adaptation to different "niches" defined by behavior, environmental role, etc.  The two terms are useful and have different meanings as you've describe, but their meanings overlap.

I agree, their meanings do overlap. However by distinct I meant the terms are generally not interchangeable; as I understand adaptive radiation is only used for several speciation events occurring from a single ancestor. But yes, I believe this would still be considered divergent evolution.


text:
Who discovered DNase?
I was recently studying genetics in which  DNase had a crucial role in proving DNA to be the genetic material and I tried to find who discovered DNase (like the discoverer of DNA) but in vain.
Who found the DNA-digesting DNase ?

You imply (if I’m not mistaken) that you know who discovered DNA. I wonder whether you might be confusing who discovered DNA, who showed it was the genetic material, and who elucidated its structure. If you’re interested in the history of science it might be useful to clarify that while we are about it.

@David Thanks It clarifies my doubt If you don't mind I have a question that is , In Martha Chase Experiment, It has been proposed that Since Radioactive Nitrogen is Transferred The DNA act as a genetic material but Why can't the transferred material be RNA as It also has same amount Of Nitrogen as of DNA ?

A principle of this site is that questions should be asked as separate questions, not as add-ons in comments. There are a few questions on the Hershey-Chase experiment on this site, and also a Wikipedia entry. However the short answer is that the bacteriophages studied consisted of DNA and protein, and the experiment was to distinguish between the two. You need to look at old experiments in their historical context.

There are, of course, many different deoxyribonucleases (DNase), but the question has other implicit problems. It assumes that there was a single event that resulted in the realization of the existence of a new enzymatic activity. As the Introduction to this paper by M. McCarty on the purification of one such enzyme in the Journal of General Physiology in 1946, science wasn’t (and still often isn’t) quite like that:

The enzyme which breaks down highly polymerized desoxyribonucleic (sic) acid
has been known for many years under various names. In 1903, Araki (3)
reported that crude preparations of trypsin and erepsin brought about
liquefaction of gels of a thymonucleate prepared according to the
method of Neumann (4) Although Araki interpreted the effect as being
proteolytic in nature, his experiments represent the first observations
on the enzymatic breakdown of this type of nucleic acid. Two years
later Sachs (5) demonstrated that liquefaction of the nucleate gel by
pancreatic extracts is caused by an enzyme distinct from trypsin, and
further presented evidence indicating that trypsin rapidly inactivates
the nuclease. De la Blanchardière (6) confirmed the findings of Sachs,
and made several unsuccessful attempts to separate the nuclease from
the inactivating tryptic enzymes. This writer also devised a more
quantitative method of measuring the nuclease activity by following the
fall in viscosity of a dilute solution of thymonucleate during
digestion with the enzyme.

Araki, T., Z. physiol. Chem.,1903,38, 84.

Sachs, F., Z. physiol. Chem.,1905,46, 337.

De la Blanchardière, P., Z. physiol. Chem., 1913, 87, 291

[desoxyribonucleic acid and thymonucleate are older terms for DNA and its ionized form]
Many scientists have subsequent been involved in identifying different types of DNase and their roles in DNA metabolism, and anyone wishing to know about a particular DNase would need to research the literature.


text:
What causes the sound of climaxing bees?
I just saw the funniest video of bumblebees(?) having sex. (mirror) As they were getting it on, there seemed to be an almost audible 'moaning' coming from the pair. From what I presume it was a sexual climax we heard!
Bees have neither vocal chords nor lungs, so I wonder: what is that sound?

As the pair is mating on a newspaper, I'm almost certain we're hearing transduced vibrations from the bees made audible through the paper and not the bees themselves. (Nonetheless, what a beautifully humorous anthropomorphism! Moaning bees certainly give vivid color to the birds and the bees!)
I have multiple theories:

The ejaculation of sperm by the drone is known to be 'explosive', even rupturing the endophallus and making a 'popping' sound. I wouldn't call the sound in the video 'popping' by any means, though.
(Un)controlled movements of legs or wings by either of the pair. This seems very likely considering the subjective frequency of the sound, but that's just speculation on my part.
Perhaps it's the queen piping? I'm really grasping with this one. I don't even know if that species' queens pipe or even have the ability to pipe.

Any excited entomologists wanna fill me in?

Okay, perhaps the sound issue isn't resolved yet. this video shows a rather similar species also demonstrating that sound!

Firstly, those aren't bumblebee faces ... those are big fly eyes. Those are Bumblebee Hover Flies (Volucella bombylans):

The noise in the first part of the video is identical to a fly flying around your head and the noise at the end sounds like what a fly would sound like when you press it against a surface like a wall or screen (or a newspaper, apparently)

I thought those compound eyes were rather 'fly-like', I just couldn't put my finger on it. Thanks for the species identification! As for the sound, I had someone remark the sound was similar to a fly on its back flapping its wings.


text:
Do birds have pharynx like mammals?
I saw this in Wikipedia:

Birds do have a larynx, but unlike in mammals, it does not vocalize.

And this pdf in Google.
It claims that birds do have a pharnyx.
Do birds have a structure called pharnyx? (Mention the ref. please)

Pharynx and larynx are not the same.

@kmm I said that they are?

Yes, birds do have a pharynx.

Birds can breathe through the mouth or the nostrils (nares). Air entering these openings (during inspiration) passes through the pharynx & then into the trachea (or windpipe). {1}

The larynx can't produce sound -- it's only there for breathing and eating. Instead, birds' sounds are produced at the bottom of the trachea, just above where the trachea branches into the lungs. This juncture, made of cartilage, is the syrinx.

The syrinx is the vocal organ of birds. Located at the base of a bird's trachea, it produces sounds without the vocal folds of mammals. The sound is produced by vibrations of some or all of the membrana tympaniformis (the walls of the syrinx) and the pessulus, caused by air flowing through the syrinx. This sets up a self-oscillating system that modulates the airflow creating the sound.   {2}

Since birds have both a syrinx and a larynx, it's unclear exactly when the syrinx took over sound production duty for the larynx.
{1}-http://people.eku.edu/ritchisong/birdrespiration.html#:~:text=Birds%20can%20breathe%20through%20the,as%20long%20as%20the%20neck.
{2}-https://en.wikipedia.org/wiki/Syrinx_(bird_anatomy)


text:
Why do I get cytosine to guanine/adenine transitions in bisulphite treated sequences?
I got my sequencing results (bisulphite treated and non treated sequences of same species Allium cepa) and now I have to do analysis in Cymate online tool. I prepared all sequences as it is written in original Cymate paper (master sequence and clones - aligned in ClustalW, blunt ended).
My problem is that I got gaps in results (image is attached, it is from Cymate Result) on positions 27, 50, 58 etc.

When I looked back at my original alignment FASTA file and compared those positions, I noticed that those gaps are from C to A, or C to G transitions (and obviously Cymate outputs only C to C, and C to T cases).
Does anyone know why do I get those C to A, or C to G, are those some mismatches, should I manually remove it from alignment, or did I made some other mistake?
Any advice from you would be very useful for me!
My FASTA file alignment, which I uploaded to Cymate, is here (if anyone wants to check). First sequence is master sequence (non-treated, orifinal sequence) and the rest are clones (bisulphite treated sequences).

Consensus_cepa__(289_bp)
GAAAGCCAACCACCACATCCGCCATCCCTCACAGTATGCCAACGAGCAGCTGAATGACTCCGAACAACGCAAAGCATGACGCCCAAACCGACGAACACCCAACCGAAAGGCCACAAGCGCAACGTGCATTCCAAAACCCCATGAACCACCGAATCCTGCAATGCACACCACGCTCGACGCCATTCGCTACAGACCACATCGACACGAGCGCCAAGCCATCCATCACCCGAAGCCATCCACCCACTCACAAACATACCACGAAGCACAGCAAATATGAAGACAAACCCTC
MV_A_SP6_izrezani_s_primerima__(295_bp)
AAAAATCAATCTCCACATCCGCCATCACTCACAGTATATTTAC-AGTAGATAAATAA-TTAAAATAACGCAAAACATAACGCCCAAACAGACGTACTCTCAACCTAATAACCTCGAACGCAACTTACATTCAAAAACTCGATAATTCACGAAATTCTGCAATTCACACCAAA--TATTGCATTTCGCTACGTTCTTCATCGACACGAAAACCAAAATATCCATTGCCAAAAATCATTCAGACGCTCACTGAAATAACACAAAACACATCAAA-ATAATAACAAACTTTC
MV_B_SP6_izrezani_s_primerima__(295_bp)
AAAAATCAATCTCCACATCCGCCATCACTCACAGTATATTTAC-AGTAGATAAATAA-TTAAAATGACGCAAAACATAACGCCCAAACAGACGTACTCTCAACCTAATGACCTTGAACGCAACTTACATTCAAAAACTCGATGATTCACGGAATTCTGCAATTCACACCAAA--TATCACATTTCGCTACGTTCTTCATCAACACGAAAACCAAAATATCCATTACCAGAAATCATTCAGACGCTCACTGAAATAACACAAAACACATCAAA-ATAATAACAAACTTTC
MV_C_SP6_izrezani_s_primerima__(291_bp)
AAAAATCAATCTCCACATCCGCCATCACTCACAGTATATTTAC-AGTAAATAAATAA-TTAAAATAACGCAAAACATGACACCCAAACAGACATACTCTCAACCTAATAACCTCGAACGCAACTTACATTCAAAAACTCGATAATTCACGGAATTCTGCAATTCACACCAAA--TATCGCATTTCGCTACGTTCTTCATCGACACGAGAACCAAAATATCCATTGCCAGAAATCATTCAGACGCTCACTGAAATAACACAAAACACATCAAA-ATAATAACAAACTTTC

Welcome to SE.biology. This is a nice question, but I think you might get a better answer in https://bioinformatics.stackexchange.com/

how did you generate these sequences? are they e.g. sanger sequences or did you go through a complex workflow (not familiar with cymate)? what proportion of bases carry this error?

Also, your cymate data is not linked.

I quickly aligned your sequences, and as far as I can tell, the answer is that your "consensus" sequence is a poor match for the 3 other sequences:
CLUSTAL format alignment by MAFFT L-INS-i (v7.310)

Consensus_cepa_ gaaagccaaccaccacatccgccatccctcacagtatgccaacgagcagctgaatgactc
MV_A_SP6_izreza aaaaatcaatctccacatccgccatcactcacagtatatttac-agtagataaataa-tt
MV_C_SP6_izreza aaaaatcaatctccacatccgccatcactcacagtatatttac-agtaaataaataa-tt
MV_B_SP6_izreza aaaaatcaatctccacatccgccatcactcacagtatatttac-agtagataaataa-tt
                .***..***.* ************** **********... ** **.*. *.***.* *.

Consensus_cepa_ cgaacaacgcaaagcatgacgcccaaaccgacgaacacccaaccgaaaggccacaagcgc
MV_A_SP6_izreza aaaataacgcaaaacataacgcccaaacagacgtactctcaacctaataacctcgaacgc
MV_C_SP6_izreza aaaataacgcaaaacatgacacccaaacagacatactctcaacctaataacctcgaacgc
MV_B_SP6_izreza aaaatgacgcaaaacataacgcccaaacagacgtactctcaacctaatgaccttgaacgc
                 .**..*******.***.**.******* ***. ** *.***** ** ..** ..*.***

Consensus_cepa_ aacgtgcattccaaaaccccatgaaccaccgaatcctgcaatgcacaccacgctcgacgc
MV_A_SP6_izreza aacttacattcaaaaactcgataattcacgaaattctgcaattcacaccaaatattgcat
MV_C_SP6_izreza aacttacattcaaaaactcgataattcacggaattctgcaattcacaccaaatatcgcat
MV_B_SP6_izreza aacttacattcaaaaactcgatgattcacggaattctgcaattcacaccaaatatcacat
                *** *.***** *****.* **.* .*** .***.******* ******* .. . .*..

Consensus_cepa_ cattcgctacagaccacatcgacacgagcgccaagccatccatcacccgaagccatccac
MV_A_SP6_izreza --ttcgctacgttcttcatcgacacgaaaaccaaaatatccattgccaaaaatcattcag
MV_C_SP6_izreza --ttcgctacgttcttcatcgacacgagaaccaaaatatccattgccagaaatcattcag
MV_B_SP6_izreza --ttcgctacgttcttcatcaacacgaaaaccaaaatatccattaccagaaatcattcag
                  ********.  *. ****.******. .****. .******..** .**..***.**

Consensus_cepa_ ccactcacaaacataccacgaagcacagcaaatatgaagacaaaccctc
MV_A_SP6_izreza acgctcactgaaataacacaaaacacatcaaa-ataataacaaactttc
MV_C_SP6_izreza acgctcactgaaataacacaaaacacatcaaa-ataataacaaactttc
MV_B_SP6_izreza acgctcactgaaataacacaaaacacatcaaa-ataataacaaactttc
                 *.***** .* *** ***.**.**** **** **.* .******..**

I would suggest trying to come up with a different, more appropriate consensus/reference sequence. This one does not appear to be appropriate.
Granted, I have no idea how you came up with this consensus sequence (it certainly is not a consensus of the other sequences you show), and possibly there is something else going on that I am not understanding.
This does not seem to have anything to do with the bisulfite conversion, as the data also include changes that cannot be attributable to bisulfite, gaps, etc.
Knowing more about the whole workflow would help.
UPDATE
Also, while I'm not familiar with the workflow, could such gaps not be related to methylation on the opposite strand? E.g. CGTA-->TACG.
Is there a particular methylation context that you are looking at? CpGs only?
In some cases there is support for weird variants (e.g. consensus is not an outgroup).
If it's sanger data, it's always a good idea to directly inspect traces.