text:
Why don't all my cell membranes "smush" when I fall?
I've read the question about cell membranes breaking apart, which is close to what I'm asking, though I'm trying to probe a bit deeper.
I understand that there are hydrophobic forces keeping the cell membrane together, and I'm roughly picturing the strength of something like water surface tension.  With this intuition, I tried to consider a few examples:

I've read the idea that the cytoskeleton can help give a cell structure.  But if a cell has some kinetic energy (say, red blood cells in the bloodstream) and runs into something else (say, the arterial wall), are the hydrophobic forces holding the cell membrane together strong enough to prevent the cytoskeleton from puncturing the membrane?
Similarly, there are videos of bacteria with their flagella traveling at what seem to be pretty significant speeds (relative to their size) - are hydrophobic forces truly enough to hold the cell membrane together in the face of that kinetic energy?  Are they a lot stronger than my intuition gives them credit for at the tiny scales of cells?
Hydrophobic forces also seem to require being in solution - the obvious counterexample would be our skin cells, which clearly are not fully in solution, but even if that were the case, if hydrophobic forces were the bulk of the forces, then wouldn't any two cells merge the moment they made physical contact with each other?

This train of thought leads to the titular question and thought experiment:
Dropping a glass of water will result in the water going everywhere.  If I were to jump up and then land, and hydrophobic forces are holding the cell membrane together, why doesn't my cell membrane fall apart from that application of kinetic energy?

RBCs repel endothelium because both have a resting membrane potential. When they are forced to pass through narrow passages as in the spleen, their cytoskeleton allows them to deform.
Glycocalyx prevents cells from fusing together.
Extracellular matrix has hyaluronic acid which gives resilience and deformability.
Surface cells die and leave keratin behind (used to be in their cytoplasms) which protects against abrasion and keeps the matrix inside.

The radius of an average human cell is approx $19$ micrometer. That gives it a a(n) (circular) area of $2000$ micrometer² (grossly exaggerating) = $2000 \times \left(\frac{1}{1000}\right)^2 = 0.00002$ cm²
If you fell on your buttocks on an area roughly $2$ palm spans, that would be an area of roughly $1000$ cm².
How many cells have you fallen on? $\frac{1000}{0.00002} = 50,000,000$ cells.
An average person weighs $68$ kg, that's around $680$ N. This force is distributed over $50,000,000$ cells. The force per cell (pressure) = $\frac{680}{50,000,000} = 0.0000136 \approx 10^{-5}$ Newtons. That ($10^{-5}$ Newtons) is the amount of force exerted by an object that weighs $1$ microgram. Pretty sure our cells can handle that amount of force.

One zero is omitted in 1/1000. In the final calculation it is repaired.


text:
Confusion about read counts distribution in RNA-seq
While reading old DESeq paper (Anders and Huber 2010) I came across following line.

If reads were independently sampled from a population with given,
  fixed fractions of genes, the read counts would follow a multinomial
  distribution, which can be approximated by the Poisson distribution.

I am unable to grasp this line. Why would read counts follow multinomial distribution? My guess would have been Gaussian distribution. Can anyone explain this?

Textbook example of multinomial distribution is multiple dice toss. The fair dice has following probabilities:
side 1: 16,66666666%
side 2: 16,66666666%
side 3: 16,66666666%
side 4: 16,66666666%
side 5: 16,66666666%
side 6: 16,66666666%

Lets roll a typical fair dice n = 20 times:
6 5 1 1 3 5 4 3 1 2 4 4 6 6 2 2 5 6 5 2

So this particular outcome of above multinomial variable is:
side 1: 3 rolls
side 2: 4 rolls
side 3: 2 rolls
side 4: 3 rolls
side 5: 4 rolls
side 6: 4 rolls

Multinomial distribution is not restricted to fair dice - the probabilities can be rigged. It also is not restricted to 6 sides - there can be any number of categories. Another textbook example of multinomial distribution is puling colored balls from wery (infinitely) large bag. Probabilities correspond to proportions of colored balls in the bag:
Blue: 53.283%
Green: 19.956%
Orange: 8.336%
Purple: 5.213%
Red: 4.374%
Silver: 3.920%
White: 2.751%
Yellow: 2.167%

Lets simulate n = 200 balls pulled from such a bag in R:
sample(c("B","G","O","P","R","S","W","Y"), replace = T, size = 200, prob = c(0.53283,0.19956,0.08336,0.05213,0.04374,0.03920,0.02751,0.02167))
B S O B B G G P B O B B P G B B G G G G B P G B B P B G B G B S W B B O O G B B O G G B S B O G B B B B B O O O B O B B B B B B O O G B B Y B R G B B B G P W Y G B P W B S R B W G Y B W B G O G B R B B G B B B B B B P R G P B B B G Y G S B B B G P B B B B B G B O G P B G B G P B B G B R B P R B G W B B B B O P G B B B B B B B B G B G G R W B B G G B G O B B B B B G B B B P B B B O R G B B B O B G

So this particular outcome multinomial variable is:
Blue: 102 balls
Green: 42 balls
Orange: 18 balls
Purple: 14 balls
Red: 8 balls
Silver: 5 balls
White: 7 balls
Yellow: 4 balls

In RNA-seq we are "pulling" reads (balls) out of a large set of suitable cDNA molecules fragments in a sample (bag). Each read belongs to a gene (color). We assume fixed fractions of genes in a sample:
gene 1: 0.05217%
gene 2: 0.00319%
gene 3: 0.00073%
...

But what we get from RNA-seq (n = milions of reads) are integer counts of reads:
gene 1: 492 reads
gene 2: 44 reads
gene 3: 5 reads
...

To comment on your idea of using Gausian distribution: Gausian distribution is continuous so using it we would assume we can get fractions of reads per gene which is not the case.

Much clear explanation :) I got confused with multinomial and multimodal :P

Good answer. I would like to add that for large samples binomial distribution can be approximated as Gaussian.

source: Stack Exchange

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

sort: votes


text:
How does the white blood cell ‘hunt’ the bacterium?
There's this mildly viral video which reportedly shows a white blood cell hunting a bacterium:
https://www.youtube.com/watch?v=JnlULOjUhSQ
What I don't understand is - at this scale, how does the white blood cell "know" to chase the bacterium and where to go? How does the bacterium "know" to run? Are they constantly shedding some bacterium-specific molecules that the white blood cell reacts to? Wouldn't the bacterium soon run out of molecules that way? Is there some other mechanism? What's going on here?
Note - I'm a total newbie; my own biology/chemistry knowledge is high-school level at best (and even then I graduated 16 years ago), so please try to explain it simply. :) I'm OK with looking up unknown terms on Wikipedia, but I probably won't be able to comprehend too much jargon. Thanks! :)

Sadly if you want a scientific answer, the question is too broad. We would have to delve into motility, immune and non-immune signaling, membrane biology of pathogens and commensals, the repertoire of immune cells, and the entirety of many kinds of response. For a rudimentary answer, try finding inspiration here, an article in Scientific American from 1998, and here on proteins that work as scouts.

@SPr - So... the gist that I get from these three links is that the invading cells do shed material all the time, and it's this material which leaves a "trail" for the white blood cell to follow. The invading cell in the video is probably not "running away" but rather moving randomly, and perhaps being pushed a bit (via fluid dynamics) by the following white blood cell.

@SPr - The exact details of losing the material and detecting it are, of course, complicated (and it seems there are many variations when it comes to the technical details), but that's the general principle.

Water (or viscoelastic fluids like blood) is not static; water molecules are constantly moving or vibrating. That poor little diplococcus isn't swimming away from the white blood cell; it's simply being moved by kinetic forces. The bacteria in this video are being pushed by the fluid in front of the moving phagocyte, making it appear to be 'running away'. The WBC is capable of movement and what you're seeing is chemotaxis. While it's more complicated than this, no, the bacterium won't run out of whatever it is that the WBC is responding to.

@anongoodnurse - That poor little diplococcus isn't swimming away from the white blood cell; it's simply being moved by kinetic forces. Yes, I suspected as much.

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


text:
Which DNA polymerase can use a nick as priming site?
Which DNA polymerase (commercially available) can initiate polymerization at nicks, without a standard primer?
My goal is to perform rolling circle amplification starting at a nick.

It sounds like you are looking for a DNA polymerase that can perform nick translation. NEB maintains a chart listing the properties of their polymerases, including nick translation and extension from nick.  Without additional details, it looks like Taq would work for your purpose.

Thanks for the answer. I was looking for something with strand displacement activity rather than 5’ removal. My goal is to perform rolling circle amplification starting at a nicking site.


text:
Protein folding
I've two questions
1. Is free ATP available in the cytoplasm of the cell?
2. In the protein folding funnel, prions and other misfolded proteins are located at the local minima of the graph. If ATP was freely available, it could possibly give a kick to the misfolded structure to cross the energy barrier and this should help the structure to fold along the idealistic path. But such a thing does not happen in reality. Why?

Yes
The energy released by ATP hydrolysis must be coupled, by enzymes, to some other reaction or process in order to be useful. It isn’t magic. There are ATP-dependent chaperones that assist in protein folding.

It seems ATP by itself can also solubilize misfolded proteins (http://doi.org/10.1126/science.aaf6846)

@WYSIWYG Very interesting, thanks.


text:
Janina kolkiewicz who faced Lazarus phenomenon
I've just read about Janina kolkiewicz case who faced Lazarus phenomenon and I was wondering how could her brain and organs survive these long hours without oxygen?

How far did you get looking for this answer yourself?

Your question is unclear as it assumes knowledge of a case involving a particular person. You can assume knowledge of biology, but not of this sort of thing. You must describe it and give references.

Without oxygen, she would not have survived. Granted, she didn't need a lot in her reduced metabolic state.


text:
What is the most durable electronic pipette?
We have a routine task of pipetting substance concentration series in triplicate on cell cultures under a laminar hood. To speed up the process, we use an electronic pipette in the repetitive pipetting mode and an electronic dispenser. The pipettes are several times a day wiped with 70% ethanol for decontamination, as they are moved to and from the hood. Up to date, we used the Eppendorf ones, but they fail after roughly a year of use. The failing parts are usually piston position sensor and pipette tip sensor on electronis dispenser.
Does anybody have an experience with the durability of different brands of electronic pipettes (Socorex Acura electro, Gilson Pipetman M, MT E4, maybe, others), especially under a laminar hood in repetitive pipetting mode?
Thank you in advance!

What type of alcohol do you use? We used to wash plastic cuvettes with cheapest version of denatured alcohol. It had negative effect on properties of the plastic. Then one of our colleagues researched it and found that not the alcohol itself but the denaturing compound was the main culprit for deteriorating the plastic. Since then we switched to ethanol denatured with methanol.

We use 96% ethanol diluted to 70% with distilled water. I am not sure if the source ethanol contains any denaturating agent, but I will find out - thanks for the point @BagiM


text:
What is the current status of the taxon Crocodylus raninus?
What is the current status of the taxon Crocodylus raninus, the Borneo Crocodile? See Wikipedia Is it now a valid species, a subspecies of Crocodylus porosus (The Saltwater Crocodile) or merely a synonym of the later?
As for Colin Stevenson, "Crocodiles of the World, Reed New Holland 2019", it is not listed as a (valid) species, nor in the IUCN Crocodile Specialist Group.

I started to dig into this a little bit.  I think the answer is probably "it's very uncertain". I don't actually know if there's an official (rather than a scholarly) standard for validity;  I couldn't find anything at https://www.iczn.org/outreach/faqs/ ...


text:
What specimen of caterpillar is this?
Early this morning, I found this beautiful caterpillar specimen crawling over a leaf:

This specimen was found today morning (spring season) in Brazil at Porto Alegre City 30°01′59″S 51°13′48″W. With approximately 1 Inch long.
What kind of specimen is this?

This appears to be a "Monkey slug" caterpillar (Phobetron spp) of the family Limacodidae (or slug moths).
According to these sites (here and here), caterpillars of this type are commonly referred to in Portuguese as "Lagarta-Aranha" (or "lesma-macaco") [literally, "spider caterpillar" and "monkey slug" in English].
The most common Phobetron species I can find in Brazil is Phobetron hipparchia.

The caterpillar of this species appears to be quite variable (ranging from browns to reds in color) as is made apparent by here, here, and here

 Phobetron hipparchia  (Source: http://caterpillars.unr.edu/)

They're quite interesting as adults as well: https://www.flickriver.com/photos/140413390@N06/39589933685/


text:
What happens to glucose taken up by the liver in type 1 diabetes?
Type 1 diabetes is caused by insufficient insulin production.
Unlike in muscle and adipose tissue (GLUT4), glucose uptake by the liver is by GLUT2 and thus insulin-independent. Consequently, under very high blood glucose concentrations, glucose will move by facilitated diffusion into the liver.
However, insulin is not available to stimulate glycogenesis, or lipogenesis; glucagon will be secreted due to high blood glucose concentration, doing the opposite. What happens to this glucose? Does it simply diffuse back out (GLUT2 is bidirectional)? Presumably glucokinase produces glucose-6-phosphate, but the highly controlled points of glycolysis (e.g. PFK-1) will lack stimulation due to loss of insulin. Does a lack of glucagon (due to glucose still reaching pancreatic islet cells, also via GLUT2) have a positive effect?

It would seem to me that as GLUT2 is not insulin-dependent, the net transport of glucose by it depends only on the difference between intracellular and blood glucose concentrations. I assume the liver has a high intracellular glucose concentration in diabetes because it is performing gluconeogenesis. Your question would then boil down to why is it doing this latter as the "starvation hormone", glucagon, is not secreted from the pancreas in diabetes (something I did not know, but checks out). Would this interpretation be correct?

That's true, presumably the net flow of glucose in type 1 diabetes in the liver is still outwards, due to excessive gluconeogenesis.
I read that glucagon is still secreted by the alpha cells of the pancreas in type 1 diabetes (though the alpha cell mechanism is generally unclear; this might be due to paracrine signalling between beta and alpha cells; or some influence of the brain). In which case this would stimulate gluconeogenesis. Perhaps the lack of inhibition of gluconeogenesis (no insulin) is enough to tip regulation towards it rather than glycolysis (via F-1,6-BPase stimulation?).

Seems reasonable. I should know the details of the regulatory control of the key points in the pathways, but only taught metabolism from the standpoint of feeding and fasting. If I had time (I'm away for a long weekend) I'd check it out in detail, but it appers that others may be saving me the task.

1) Hepatic glucose intake may not be much greater in hyerglycemia than in normoglycemia:
Regulation of Hepatic Glucose Uptake and Storage In Vivo (Advances in Nutrition, 2012):

...neither hyperinsulinemia nor hyperglycemia can independently induce
  much net hepatic glucose uptake.

2) Glucose can be used for de novo lipogenesis in the liver despite the lack of insulin:
De Novo Lipogenesis and Cholesterol Synthesis in Humans with Long-Standing Type 1 Diabetes Are Comparable to Non-Diabetic Individuals (PLoS One, 2013):

Fasting total hepatic lipogenesis (3.91±0.90% vs. 5.30±1.22%;
  P = 0.41) was not significantly different between diabetic and control
  groups...


text:
Minimum amount of RNA for cDNA conversion and qPCR
I searched several protocols for reverse transcription of RNA and all suggest using RNA concentrations of 1ug. Could a lower amount result in inferior transcript representation and therefore decreased quality of the qPCR results?
We use the SensiFAST SYBR Lo-ROX kit from BIOLINE. I was thinking of using 500ng instead of the suggested 1000ng. In order to accommodate the protocol, I would use 0.5ul of RTase to maintain the 1:1 (m/v) ratio. Buffer, DNase, water, and RTmix concentrations for the reaction I would keep the same. For the final dilution of the cDNA, I would dilute 5x instead of 10x to maintain equal concentrations.
Does anyone have experience with this? Does transcript representation suffer?
Do the suggested protocol adaptations seem reasonable?
Thanks for the help in advance.

Two answers follow:

Technical experience of many: it should be no problem to have the same protocol with a twice-lower starting concentration, without making any adjustments whatsoever. The suggested 1ug is very much on the safer side of things, 2-fold fewer transcripts makes almost no difference. Maybe at 1 or 2 orders of magnitude (10 to 100s) less will you run into problems or a need to correct your reactions.
Scientific orthodoxy: the most scientific piece of advice anyone can offer you would be to try it both ways and compare your results using qRT-PCR. I'm guessing both approaches will show very similar results.


text:
Why does the structure for cellular retinol binding protein show interactions with cadmium ions?
A structure of cellular retinol binding protein (1CRB) contains two cadmium ions as ligands. Is Cd2+ a ligand of CRBP and, if so, is that interaction necessary for protein function or is the protein a transporter to remove cadmium? My other thought is that the interaction only appears as a result of the methods the scientists used to determine the structure of the protein.

Welcome to Biology.SE! We encourage you to do some research on your own and then, informed by what you have learned, ask any questions you still have (ideally with references to reliable sources). For example, your question about whether this is a cadmium transporter can be answered by looking at the entry for the structure you indicated! I also suspect that your last guess can be confirmed by looking at the linked paper. ——— Please also take the tour and then go through the help pages starting with How to Ask questions effectively on this site and edit your question accordingly. Thanks!

As far as I am aware, there is no known requirement for Cd in mammalian systems, but it is extremely toxic (Waalkes & Goering).
It would seem that cadmium is required to get crystals of RBP, and its presence is an artifact of the crystallization process (ref):

Pig holoRBP crystals were obtained at 277 K by the sitting-drop vapor- diffusion method, at a final protein concentration of approximately 8 mg ml ~ and in the presence of 8%(v/v) 2-methyl-2,4- pentanediol, 3mM cadmium acetate, 0.1 M Tris-acetate, pH = 6.8

The only mammalian Cd-binding protein I am aware of is metallothione (ref), which was originally isolated as a Cd-binding protein (ref), and allows safe transport of a highly toxic metal.
Carbonic anhydrase from the marine diatom Thalassiosira weissflogi can use Cd  as active-site metal (typically when Zn is low) and this may explain "the nutrient-like behaviour of cadmium in the ocean" [ref and ref]

Also from the paper you quote: "Cadmium ions represent an absolute requirement for the growth of orthorhombic crystals of... RBP"


text:
Help identifying a mushroom found in Raymond, WA, USA
Hello dear mycology wizards!
Could you help me figure out what's the name of this species.
I found the mushrooms in a forest near to Raymond, WA. The area was quite wet and mossy, but not a swamp. There was a creek ~50-75 feet away. The forest is mostly coniferous trees with a few birches.

Here are the photos of the mushroom of interest:

just as a preface to any responses you get: I have not known this community to be especially knowledgeable about mushrooms (i.e., I don't know of any mycology wizards here), so I would suggest you research further any answer you receive and/or seek additional insight from a known mycologist. (Not that an answer you get isn't correct, but I think fungi are notoriously tricky to ID and easily misidentified by even trained mycologists -- so do more of your own sleuthing with whatever info you glean from this community). Good luck :).

Candy cap is another possibility, which should have brittle stipes, a sweet odor, and a milky latex. However, it can be easily confused with the deadly galerina, so be careful.

To me that looks like Chrysomphalina chrysophylla, which is one of several fungi superficially similar to the chanterelles.
(The chanterelle in contrast has gradual increase in the diameter of the stalk rather than a sharp demarkation between the stalk and cap.)
Chrysomphalina chrysophylla is a species that has been reported in Washington:
 Source: Burke Herbarium Image Collection (for Washington state)

All the mushrooms I saw on the site had straight, not curved stocks. None of them grew on the dead wood/logs. I suspect it's a different fungi, but I really appreciate your attempt to identify it!

I'm pretty sure those are false chanterelles. True chanterelles, like Igor said, have a stalk that gradually widens from the base to where the mushroom cap starts, giving then kind of a fat look, if that makes sense. Chanterelles also aren't so garishly orange, they're more of a creamy orange-yellow, and they have more of a ruffled edge on the cap.
Be really careful because false chanterelles can make you quite sick. Hope you didn't eat any of those before finding out for sure! Good luck in your hunting

No, I did not eat any (in fact I didn't even collect them). I found them a year ago when I was shopping for land in that area... Thank you!

The specimens in OP's photographs don't look like false chanterelles (Hygrophoropsis aurantiaca) at all.


text:
Modern understanding Darwin's "correlation of variation"
In Variation under Domestication, Darwin makes several references to the concept of "correlation of variation":

I will here only allude to what may be called correlated variation. Important changes in the embryo or larva will probably entail changes in the mature animal.

And:

Some instances of correlation are quite whimsical; thus cats with blue eyes are invariably deaf.

In the chapter's ending, he also calls this "correlation of growth":

Variability is governed by many unknown laws, of which correlated growth is probably the most important.

I gather that this is Darwin's humble way of admitting that there are many unknown unknowns, at least as far as correlation is concerned.
But, since 1859 until present day, what did we find out about this quirky aspect of evolution? Are all cats with blue eyes deaf?

It seems obvious: one characteristic or change is associated with another, as with blue eyed cats being deaf.

Yes, I was more curious about the modern understanding of the topic, that is, if the theory is as sound as it was perceived back then and, if not, in what regards.

One must not confound a phenotypic variance-covariance matrix (usually called $P$) and a genetic variance-covariance matrix (usually called $G$) for a set of phenotypes. The mutational variance-covariance matrix is also a common concept (usually called $M$). There are a lot of papers on the evolution of the G-matrix (and related matrices).
In the abstract of Roff (2000), you can find the equuation
$$\Delta\bar z = GP^{-1}-S$$
, where $\Delta\bar z$ is the vector of mean responses, $G$ (often just called the G matrix) is the matrix of additive genetic variances and covariances, $P$ is the matrix of phenotypic variances and covariances and $S$ is the vector of selection differentials.
You will find much more by just googling "evolution of G-matrix"

It might be helpful to add a lay summary to this answer, since I think it's on a bit of a different level than the original question.


text:
What pigment is responsible for the formation of blue skin color in some animals?
Not long ago I read about Vervet monkey. Here's picture:

My question is what causes this blue coloration of the scrotum? I don't mean evolutionary need  (e.g. attracting females), but what pigment or other factor is responsible for this color?

I've suggested an edit to your post; in the future please upload pictures rather than including links. Links are discouraged since 1) if they break they no longer add value to this post, and 2) they can be used to link to malicious websites. Thanks!

A related question about blue food that doesn't answer your question, but you might find it interesting: Why are so few foods blue?

Blue coloration in animals is caused by structural color rather than blue pigments. In the case of vervet monkeys and other mammals studied this is due to collagen fibers in the skin being arranged with a regular spacing that results in blue wavelengths constructively interfering while other wavelengths destructively interfere1.
This "news" article in Science discusses this phenomenon and mentions Vervet monkeys.
Reference:
1: Prum, R. O., & Torres, R. (2004). Structural colouration of mammalian skin: convergent evolution of coherently scattering dermal collagen arrays. Journal of Experimental Biology, 207(12), 2157-2172.

Excellent! (+1). It's always nice to see such useful primary literature cited here on Bio.SE! Can you elaborate a tiny bit more from the paper (i.e., describe the tissue arrangement more explicitly etc.)? -- Not necessary, but I think doing so would make the answer stand better on its own (in case links died and someone can't get access to the paper).


text:
Could tumor cells have normal genomic profiles?
I have thawed primary tumor cells and performed FACS. They were EpCAM positive cells. Then, I expanded them as organoids in 3D and did another FACS analysis. Again, they were EpCAM positive. I also sent organoids to pathology for IHC. Results showed they expressed EpCAM, EGFR, and panCK. But to my surprise, the Ampli LowPass sequencing results showed they had a balanced profile like normal cells. How could that be explained? Any help (comments, papers, ...) is appreciated.
Thank you.

I think this is the paper about the Ampli LowPass sequencing technique. Although, I didn't read it thoroughly but from the abstract and result section titles, it appears that this technique is designed for detecting CNVs. Since it is low pass (i.e. low coverage), it may not detect substitutions and small indels accurately.
Your cells may have mutations but not big chromosomal rearrangements. It is not necessary for tumour cells to have such chromosomal aberrations. In fact a simple overexpression of an oncogene or a point mutation causing reduced/loss of activity of a tumor supressor (for e.g. p53) is enough for tumorigenesis.


text:
Can primary tumor cells grow in 2D culture?
Is it possible to expand primary tumor cells in 2D culture? Are they adherent cells? Do you have any experience especially with culturing non-small cell lung cancer in 2D?
Thank you.

Short answer: Yes, this is possible, it is the way most (cancer) cell lines have been generated.
Long answer: Culturing cells from tumor tissues is done in labs, especially, if you don't want to rely on the often very old cultures used in the labs. Many of these where started in the 1970s and are strange in many ways, e.g. contain many chromosomes multiple times. I have routinely isolated new cell lines from melanoma tissues (mostly metastases from different organs), but the general procedure is the same for other tumors as well.
To isolate cells from a tumor, you first wash the tumor sample to get rid of the blood. Then you cut down the tumors into small pieces using a scalpell, before adding a mix of enzymes like Collagenase, Dispase and Hyaluronidase to dissolve the tissue further in order to get a single cell solution. After the incubation with the enzymes the suspension is passed through a cell strainer to remove all remaining bigger cell aggregates and tissues residues and centrifuge the cells down. They are resuspended in an appropriate medium for the cell type and seeded to an appropriate plate/flask. For our samples this was typically either a 35mm plate (or a 6 well plate, which has the same area per well) or a T25 flask. Most cells from such isolations grow adherent, but sometimes you can observe cells, which do not adhere to the surfaces.
The procedure itself is not very complicated, but needs optimization. Depending on your tissue, the enzyme cocktail can be varied, as well as the length of incubation and the incubation time in this step. Then different plate/flask surfaces can play an important role, also the medium composition.
When we started doing this work in the lab, about 1 in 10 attempts was successfull, after optimization we went up to 6-7 of 10. What is important to take into account is, that the cells change during incubation and adapt to it. This means you need to question yourself, how good of a model they can be and need to be. If you need our detailed protocol, let me know, I can post it somewhere.


text:
What prevents mRNAs that are localized to a specific part of the cell from being translated before they reach their destination?
One of the methods of mRNA localization, for example, is random diffusion of mRNAs where the mRNA binding proteins are localized to a certain part of the cell. However, I was taught that the ribosome can translate mRNAs before they've even finished being exported from the nucleus. So what stops localized mRNAs from being translated all over the cell before they reach their designated location?
I was thinking maybe they're bound by hnRNPs that inhibit their translation, which dissociate when they're bound by localized mRNA binding proteins, but I could be wrong.
Or is it that they are translated all over the cell, but the concentration at their locale is just way higher in their locale?

Could you give a specific example of the type of localization you are referring to, please. Are you talking about mitochondrial or nuclear localization or something else? At the moment your question is too broad and imprecise.

Sorry, I guess a good example could be Calmodulin Kinase mRNA being transported to the synapse of a neuron on the cytoskeletal microfilaments. So in the case of that mRNA, how is it not transcribed at all on route to the synapse? I see that Nicolai has answered that particular example below though.

That’s an example I’m not familiar with. I must check out the reference from @Nicolai.

The answer to your general question is 'it depends':

A lot of RNA localisation to the ER and mitochondria happens co-translationally (based on the protein targeting sequences), so these mRNA actually depend on translation to be localised. However, RNA localisation to mitochondria can also happen due to targeting sequences in the mRNA 3'UTR - in these cases translational repression would be possible, but it's unlikely and I don't think anyone ever checked it in this particular case. (see i.e. this review)
the translation of many mRNAs that are actively transported along the cytoskeleton is inhibited during transport, either by specific RNA binding proteins or larger RNP (ribo-nucleo-protein) complexes (see another review).

There are also bound to be some specific mRNA that have very specific regulation mechanisms and others that are exceptions.


text:
Are (muscle) satellite cells the same as muscle stem cells?
In terms of muscle: are the terms 'satellite cell' and 'muscle stem cell' interchangeable? That is, are there muscle stem cells that are not satellite cells, or vice versa?

Well, there is some level of ambiguity here. The distinction at terminology level between "muscle satellite cells" and "muscle stem cells" is generally made by those researchers who insist/emphasize that muscle satellites are not a homogeneous population, e.g. Kuang et al., 2007

we conclude that satellite cells are a heterogeneous population composed of stem cells and committed progenitors.

Or from a review  summarizing that paper:

Due to their position on the surface of the muscle fiber beneath the basement membrane and their characteristic expression of the marker Pax7, satellite cells can easily be analyzed by standard immunofluorescence technologies. [...]
Recent studies have provided more evidence that satellite cells are actually a heterogeneous population where all cells express Pax7 but only a fraction also expresses the myogenic transcription factor Myf5 (Kuang et al., 2007). In vitro lineage analysis shows that the Myf5-positive satellite cells arise from the Myf5-negative cells. Upon transplantation, only the Myf5-negative cells contribute significantly to the satellite cell compartment whereas the Myf5+ cells preferentially undergo terminal differentiation. Thus, the Pax7+ Myf5- cells are true stem cells whereas the Pax7+ Myf5+ cells are more committed progenitors.

However, one has to keep some perspective that these "committed progenitors" are just the offspring of stem cells following a fairly usual asymmetric division strategy broadly used by stem cells in other contexts

Stem cells self-renew but also give rise to daughter cells that are committed to lineage-specific differentiation. To achieve this remarkable task, they can undergo an intrinsically asymmetric cell division whereby they segregate cell fate determinants into only one of the two daughter cells.

Muscle stem cells live in a niche, and the niche mechanism of asymmetric division appears proximity/orientation based, as Kuang et al. found:

Planar divisions were observed to give rise almost exclusively (92%, n = 89 pairs) to identical daughter cells that were either both Pax7+/Myf5- or both Pax7+/Myf5+ [...]
Strikingly, we observed apical-basal oriented doublets where the sister cells assumed asymmetric cell fates (82%, n = 38 pairs). The majority of apical-basal oriented doublets contained a Pax7+/Myf5- cell against the basal surface and a Pax7+/Myf5+ cell located on the apical side against the muscle fiber [...]. In addition, we observed rare events where the basal cell expressed Pax7 and Myf5 and the apical cell had downregulated Pax7 and was presumably undergoing terminal differentiation.

Again, this is a fairly common process, observed elsewhere/before, per the review:

the stem cell is in close contact with the stem cell niche and depends on this contact for maintaining the potential to self-renew (Li and Xie, 2005). By orienting its mitotic spindle perpendicularly to the niche surface, it ensures that only one daughter cell can maintain contact with the stem cell niche and retain the ability to self-renew. In contrast to intrinsically asymmetric cell divisions, which usually follow a predefined developmental program, niche-controlled stem cell divisions offer a high degree of flexibility. Occasionally, the stem cell can divide parallel to the niche, thereby generating two stem cells to increase stem cell number or to compensate for occasional stem cell loss. For this reason, niche mechanisms are more common in adult stem cells, whereas intrinsically asymmetric divisions predominate during development.

However, in contexts when one isn't so interested in the sub-populations of satellite cells during their division process, just their overall contribution to muscle repairs, the terms "muscle satellite cells" and "muscle stem cells" are used (more) interchangeably, e.g. Snijders et al. (2015) write in their review:

Adaptation in the context of skeletal muscle is often discussed as a change in structure and function in response to an exercise stimulus. [...]
Skeletal muscle stem cells, also known as satellite cells, are now thought to play a significant role in the adaptive process.

Interestingly perhaps (from terminology standpoint), Nguyen et al. (2019) avoid using "satellite cell" altogether in their review and talk just of "muscle stem cells" vs "committed myogenic precursor".

To maintain this population, MuSCs may undergo symmetric or asymmetric division, respectively, producing either two identical daughter cells or both a single undifferentiated daughter cell and a committed myogenic precursor.

However this last approach kinda obscures (at terminology level) the anatomical location aspect/angle that gave rise to "satellite muscle cell" in the first place (see Snijders for a mini-history.)

Based on this review, satellite cells can replenish injured muscles, but among satellite cells there are satellite stem cells to maintain the pool of satellite cells.


text:
Does the cranial dura consist of the periosteum? and if not, then is there a mistake in my textbook?
My textbook (Neuroanatomy an illustrated colour text) states that:

The spinal dura and much of the cranial dura are separate from the periosteum, which forms the inner lining of the surrounding bones.

However, as far as I am aware the cranial dura has two layers, one of which is the outer periosteal layer or the periosteum, so I'm not sure why this is mentioned separate to the cranial dura.
The textbook later states that:

At certain locations, however, such as on the floor of the cranial cavity, the dura and periosteum are fused and the cranial dura is tightly adherent to the interior surface of the skull.

This would make sense if they were referring to the pericranium, but the first quote suggests that the textbook is referring to the outer periosteal layer (or the inner periosteum).
Please could you shed some light on this. Thank you.

First about the terms:

The outer side of the cranial bones is covered by a single layer of  periosteum that is specifically called pericranium.
The inner side of the cranial bones is covered by dura mater that has 2 layers:

the periosteal (or sometimes called endosteal) layer that is attached to the inner side of the bones
the meningeal layer that covers the periosteal layer and, at places, folds into the skull to make extensions

Image 1: Dura mater with its periosteal and meningeal layer (source: Idris Siddiqui, SlideShare)

Image 2: Extensions of the meningeal dura mater (falx cerebri, falx cerebelli, tentorium cerebelli) (source: Wikipedia, CC license)
The cranial dura mater has the periosteal and meningeal layer, but the spinal dura mater has only a meningeal layer, which encloses the spinal cord. Vertebra have no additional periosteal layer. The periosteal layer of the dura mater that covers the cranial bones does not extend to the spinal canal:

The periosteal or endosteal layer of dura mater is simply a layer of
  periosteum that covers the inner surface of the skull. The layer does
  not extend beyond the foramen magnum to become contiguous with the
  dura mater of the spinal cord. The spinal cord dura mater has no
  periosteal layer.
The meningeal layer of dura mater is a durable, dense fibrous membrane
  which passes through the foramen magnum and is continuous with the
  dura mater of the spinal cord. (V. Kekere, Dura mater, StatPearls)

Both quotes from the book mentioned in the question suggest that the periosteum and dura are two separate things: periosteum being a part of the bone (as elsewhere in the skeleton) and dura consisting of a single layer. The other  explanation, which I presented here, is that the periosteum on the inner side of the skull is a part of the dura (its periosteal layer) that has another layer (the meningeal layer). So, they are two ways how you can look at the structure of dura mater, and I believe, the second one is more widely accepted.


text:
Why didn't the human Cerebrum evolve to have granule cells like the Cerebellum does?
The Cerebellum is much smaller compared to the Cerebrum yet it contains more than half of the total neurons contained in the brain.
That's mainly due to the granule cells in the Cerebellum which allows it become so densely packed with neurons.
But why is the Cerebrum not like that? Why isn't it as "compressed" as the Cerebellum? Doesn't it make sense for it to be more smaller and compact?

Welcome to Biology.SE! We encourage you to do some research on your own and then, informed by what you have learned, ask any questions you still have (ideally with references to reliable sources). ——— Please also take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. Thanks!

By "cerebrum" I assume you really mean the cerebral neocortex, since the cerebrum includes other subcortical structures that themselves are quite distinct (e.g., the basal ganglia).
Simply, the neocortex and cerebellum have completely different functions. The cerebellum performs a particular class of computations that are very different from the variety of computations performed by the cerebral cortex. They have completely different laminar structures, with neocortex being a ~6-layer structure, the cerebellum has just 2-3. There are a much higher diversity of connections and cell types in neocortex compared to cerebellum.
It seems like an optimal configuration for the cerebellum is a very high cell density. More cells doesn't necessarily mean "better", because the more cells you have the less space you have for connections. There is no unused or empty space in the neocortex: if you packed in some more cells you'd have to lose something else.

Doya, K. (1999). What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?. Neural networks, 12(7-8), 961-974.

My bad, I didn't think about how important the individual connections were. Thanks for the answer!


text:
Lotka-Voltera predator prey model isocline?
In lotka voltera predator prey model, why do we get a straight isocline with variable prey/predator population for single value of corresponding predator/prey?
I understand that we get the prey isocline by the equation

N1=prey population ; n2=predator population
What I don't understand is why we are getting variable prey population on isocline for same value of predator population. Shouldn't the prey population be also constant?

PS: I picked the graph image from the internet so the symbols are different. Sorry.

Welcome to Bio.SE! What attempts to answer this question have you already taken? We ask that all question posters here attempt to search for an answer to their own question and explicitly indicate what research they've already done, what they learned, and what is still confusing or unknown to them. Our goal is not to simply be an answer site, but rather a site that promotes self-learning with some expert help along the way :). Please take a moment to edit your post with this additional detail, and it will likely be received more positively by our community. Thanks!

@theforestecologist  Sorry  for the trouble, It was my first time posting a question.

I dont understand exactly what you are asking. Are you wondering how the prey and predator populations can fluctuate with a "fixed" isocline? Or if the prey population is stable while the predator population is stable ("...getting variable prey population on isocline for same value of predator population"), which isn't the case? Can you please clarify.

@helppp thanks for the updates! You've improved your post :). However, I, too, am confused regarding exactly what you're asking about. Please use fileunderwater's comment as a guide for further improving your question. You're getting closer to an answer -- just a few more clarifications and we'll see if we can help you out!

@fileunderwater Yes I don't understand why prey or predator population fluctuates with a "fixed " isocline? If we are saying that rate of change of prey population is 0 for the isocline, then how come we are getting a line parallel to prey axis?

To me, it is still a bit unclear exactly where your confusion lies (also reading your comment to the other answer). Is it the meaning/interpretation of the isoclines that is the problem, or the dynamics with fluctuating populations of both predator and prey (except at the isocline intersection)?

I think your issue is mainly with the interpretation of the isoclines.
If you assume this standard predator-prey model:
$$\frac{dN_1}{dt} = rN_1-pN_1N_2$$
$$\frac{dN_2}{dt} = apN_1N_2-mN_2$$
you get the isoclines:
$$ N_2 = \frac{r}{p} $$
$$ N_1 = \frac{m}{ap}$$
with the first isocline referring to prey and the second to predators. These isoclines mean that the population growth rate of prey and predators (respectively) will be zero exactly at these isoclines (as well as at the point N1=N2=0). Since the isoclines, for this partuicular model, are fixed values and not functions of N1 and/or N2 they will be strait lines. Also, in a sense, you should view the isoclines as the borderline case where population growth rate shifts between a positive and a negative value (ie a growing or a decreasing population). The isoclines are not giving you the population size of the prey at a certain predator population size (which you seem to be implying with "...why we are getting variable prey population on isocline for same value of predator population"), but the locations in the plane where the population growth rate (for either prey or predators) is zero.
A graphical view of only the prey isocline (with some color coding) can be:

This means that the prey population (blue) is growing (arrows to the right) below the blue prey isocline, so there if a "flow" to the right there, while it is declining at predator population sizes above the isocline (arrows to the left). So basically, for all predator population sizes (N2) below isocline the prey population will grow, and for all N2 above the isocline the prey population will decline. In reality the rate of increase/decrease differs depending on how far from the isocline you are (so arrows should be of different lenghts), but to simplify the issue and to show the general principle I'm just showing the direction of flow here.
The same picture for the predator population is:

Here the predator population (orange) is declining to the left of the orange predator isocline (arrows down) because there is too little prey to sustain the population, and increasing to the right of the isocline (arrows up).
If you combine these you get this, with the black arrows showing the overall direction of the combined population trajectories:

I hope this clarifies the issue a bit. Otherwise, please comment and hightlight what parts you find unclear.
Also, the dynamics of this Lotka-Volterra model also means that populations that start exactly at the intersection of the isoclines (i.e. both N1 and N2 will lie at that point) will stay there, since that is an (unstable) equilibrium point. Populations that are started anywhere else in this plane (except for cases where N1 and/or N2 is zero), will follow an oscillating population trajectory, that will not change if there isn't any external pertubations (environmental changes, input/output through immigration/emmigration etc). Therefore, the combined trajectories of N1 and N2 will form an ellipse in the plane, until they are perturbed (by something outside the current model), when they will then settle at a new ellipsis. For examples of the ellipses, see this phase-plane graph from Wikipedia, with initial values as points:

However, also note that changing the model, i.e. to include a logistic component to the prey population, will completely change the population dynamics.

I am going to try and cover the math with a few more words, to show that your intuition is in fact, correct (which with math, is not always given).
In the differential equation you wrote $$ \frac{d N_1}{dt} = r_1 N_1 - p_1 N_1N_2 \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;     (1) $$
the numbers $r_1$ and $p_1$ are simply constants that give a strength of coupling, between the change of a variable (the left-hand side) and how this change is computed (the right hand side).
Would you set $p_1=0$, then the resulting solution of (1) would be an unhindered exponential growth. If we go and increase $p_1$ to $p_1>0$, then we increase the "efficiency of conversion from $N_1N_2$ into negative $N_1$", or more simply put "the predators become more efficient at hunting".
Hence, intuitively, as the predators become more efficient, by increasing $p_1$, the prey population cannot grow exponentially grow to infinity any more. It must now level off (as the solution of (1) will show you, if you keep $N_2$ constant, see also the logistic function "In ecology: modeling population growth").
And the stable value towards which it is leveling off, is given by the requirement $\frac{d N_1}{dt} =0$, which leads us to the isocline $0=r_1-p_1N_2$.
Now, coming back to your question, it is important to notice that by requiring $\frac{d N_1}{dt} =0$, we have already set $N_1=const.$, we just have no means yet to compute this value.
 So the prey population is in fact constant! And the predator population that can live off this unknown value is given by the ratio of prey multiplication vs. hunting efficiency, which is the isocline.
As a last comment, it is strange that an equation for $N_1$ turns out to give us the most  information about $N_2$, but that's how it often is with coupled differential equations.

Okay, that does clear up a few things.  But shouldn't a fixed predator population of N2=r1/p1 correspond to a fixed value of prey population, so instead of a line we get a point ?

@helppp Could you post the link where you've got the image from? Then I could check with their variable namings. The way I see it the line means exactly that: For one particular N2, there is one constant N1. However, now if we change N2 to some other number N2', then N1 has also to change, in a correspondingly linear fashion, along the isocline.

here you go: http://nre509.wikidot.com/lecture-15-nov-4

Why are you bringing the logistic function into this? The prey model in the Q is not based on the logistic, and the levelling off in the logistic model has nothing to do with the isocline in this Q.

@fileunderwater: Because when keeping $N_2$ constant, this is a logistic DEQ. It helps develop what you expect from a solution. The first term is an enxponential growth, the second one an exponential decline. If the logistic level-off is actually reached, depends on the ratio of the coefficients.


text:
Why do cats sleep in a curled up position?
I've noticed that cats will usually sleep curled up like ball, heads down and titled, with tails near their face. Is there any specific reason that cats would have a tendency to sleep this way?

Cats are not the only animal that does this.  Dogs do, as do most small mammals I've seen.  FTM, except for lacking a tail, so do I.  There are a lot of possible reasons: it conserves heat, protects one's belly from attack, is just more comfortable...

Welcome to Biology.SE! We encourage you to do some research on your own and then, informed by what you have learned, ask any questions you still have (ideally with references to reliable sources). ——— Please also take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site and edit your question accordingly. Thanks!


text:
How many atoms has the smallest known bacterium?
Background thoughts before this question: is it feasible to simulate a complete bacterium, atom by atom, in a computer simulation? On modern systems, either in an  upcoming exascale computer?
In current research they've simulated an organella with 100M atoms but I don't know on which infrastructure.
On Quora, there is an estimation of E.coli to have about 9x1010 atoms. With 4m base pairs it is though still quite big and possibly would produce too high computational workload in a simulation.
See also:
https://scicomp.stackexchange.com/questions/33941/is-a-complete-bacteria-simulation-with-an-exascale-supercomputer-possible
If they have simulated an organella with 100M atoms atom by atom, possibly you could already completely simulate some viruses, but they are not independent organisms.
So there has been an atom by atom simulation of the polio virus capsid in 2014 on the K computer with 10 petaflops. To include enough water molecules to fill and surround the capsid, Okazaki and colleagues needed to model the dynamics of nearly 6.5 million atoms, which they did for a simulated 200 ns.
Question - which order of magnitude would a small bacterium count on atoms? What about the smallest known bacterium Nasuia deltocephalinicola with its 112K base pairs? How many atoms has it got?

Do you perhaps mean pathogens? I imagine you can classify pathogens by dozens of criteria, but number of atoms strikes me as little more use than the day of the week in which they were discovered. Molecular science is past the descriptive phase today. It is concerned with mechanism.

There are literally hundreds of "well known pathogens". Their molecular weight is known, but their pathogenesis is much more important.

Please edit your post to clarify why you want this information — it isn't clear to me how this could possibly be useful.  If you are just trying to get a sense of scale then you may find this website helpful.

@tyersome I try to understand the physical complexity

I'm not sure number of atoms really helps with that — for example, a diamond has many more atoms than a virus, but to me it seems clear that a virus is much more complicated ... You might find the wikipedia article on complexity helpful for organizing your thinking on this subject.

changed question to narrow down and be more specific, with more background information.

I am sorry to sound harsh but this question is absurd. It does not matter how many "atoms" an organism has. You cannot model the organism by the number of atoms it contains. Two proteins may have exactly same number of atoms but their functions may be worlds apart.

@WYSIWYG it's just about order of magnitude. For sure you need a more complex model than just a set of atoms. I'm just trying to understand the computational gap between the already successful organella atom level simulation with 100M atoms and a complete small organism.

A droplet of radius 1µm will have ~1.7×10⁷ molecules of water (three times more atoms). This is an easy calculation. A typical protein molecule may have ~10³ atoms. Molecular dynamics simulation of a crystalline virus particle may tell nothing about it's infection dynamics. Typically, these models are used for studying molecular structure changes. It can be used to study how viral proteins bind to receptors but not the entire infection cycle. The scale of those processes are different.

It is akin to modelling motion of large objects using quantum-mechanical models.

I really wonder why it's not known how many atoms does a bacteria species can have, roughly. Or why it should not be asked on a Q&A site. I think, now the question is not too broad and quite specific.

@J.Doe It can be calculated. It is not explicitly reported because nobody thinks that it would be useful. Your question is not broad but the purpose of it is not clear. It certainly is not very useful. Moreover, a cell can change its structure in response to the environment and can drastically alter the number of molecules it contains. The importance of the number of atoms in the context of the paper that you linked is because of the technique they use. MD involves calculation of intra/intermolecular interactions. It makes sense for molecules/supramolecular complexes, not organisms in general.

I agree wholeheartedly with @WYSIWYG, I feel a layperson can misinterpret the notion of complexity far too readily. It's actually a very deep topic of discussion even for specialists. I have provided an answer for the sake of closing this question. As you can see, a bacterium is made of a great big number of atoms. Alright, so is a perfect crystal (a simple configuration), or a perfectly disordered gas (also a simple configuration). In biology, all simplicity is obfuscated by emergence and by chemistry (not physics). Knowing about atom number is a most useless and uninsightful bit of info.

Let's take the example of the model bacterium E. coli, for which one can find the numbers for a wet cell of a dry mass of 0.28pg. If you have a feeling for how much smaller the smallest known bacterium is compared to E. coli, you can ballpark things.

The number of carbon atoms in a single E. coli cell is approx. 7x10^9 carbon atoms.
The ratio of elements in E. coli is C : H(1.77) : O(0.49) : N(0.24) .

More simply, if you multiply the ratios by 4, you get the ratios of approximately 4 carbons, 7 hydrogen, and 2 oxygen atoms for each nitrogen atom.
Taken together, there are approximately the following number of atoms in an E. coli cell:
C: 7 x 10^9
H: 1.23 x 10^10
O: 3.5 x 10^9
N: 1.75 x 10^9
That is around 2.4 x 10^10 individual atoms. As you may have noticed, these numbers do not have any bearing on the complexity of the system whatsoever. They also do not provide any insight into the intrinsic biological plasticity and dynamics of the system.

but how many atoms does the supposedly much smaller Nasuia deltocephalinicola have? most references I can find refer to its genome size.

@J.Doe as I mentioned before, the composition and size of a bacteria will not remain constant. The paper in the question talks about a supramolecular complex, not a cell. If you assume that composition of all bacteria is more or less the same then you can simply calculate the values for your bacterium by scaling the volume accordingly.

@WYSIWYG so what is the size of the Nasuia deltocephalinicola compared to E.coli?

@J.Doe that's a separate question and is also something that you can Google easily.


text:
It there any experimental approach to determine the electronic structure of a given aminoacid inside a protein?
It there any experimental method to determine the electronic structure of a given amino acid inside a protein?

I mean the electronic configuration of all orbitals in a given amino acid, but something like you describe: "Within the active site of an enzyme, is a tyrosine -OH protonated or not," could help

The two most often used methods used to determine protein structures are X-Ray crystallography and NMR (nuclear magnetic resonance spectroscopy). Both of these allow some deductions of electron configuration, but don't actually measure it directly (and as far as I know there is no method available that can do that, but physicists might know more about that).
X-Ray crystallography essentially detects the electron density of a protein crystal. Usually this density is 'only' used to calculate the structure of the protein, but using good controls and smart math might allow one to also detect charges or specific electron configurations (I haven't checked if anyone ever tried something like this). One general caveat of protein crystallography is that the protein structure/configuration in a crystal may not actually correspond 100% to the state of the protein in its normal environment.
NMR measures the chemical shifts and coupling (quantum) spin of atom nuclei (usually H, N & sometimes C), which is more or less directly depend on its electronic micro-environment. Since structural biology usually doesn't care about things like orbitals, protein NMR data is then used to determine the distance of specific nuclei, which allows derivation of a protein structure.
Since NMR data directly measures atomic properties of single nuclei, I think it is probably the closest to what you are looking for, but asking actual NMR experts will be necessary to figure out whether determining specific orbital configurations could be possible (and even then it would likely be a multi-year interdisciplinary research project).
Another approach, that was mentioned in the comments on the question, would be determining charges on specific amino acids, which could be done using biochemical or spectroscopy assays, if one is only looking at one (or a few) specific amino acids in a protein. These assays need to specifically designed for your protein and amino acid of interest - I can't give specific sources here, but reading up on how people (started to) figure out the chemical mechanisms of enzymes might give you some insights on possible experiments.


text:
How do tumor cells 'gravitate' towards each other?
In a popular article it is mentioned that in centrifugal experiments with cancer cells that

When subjected to microgravity-conditions, the cancer cells were unable to sense each other and therefore had a very hard time coming together.

which is because

[...] the process through which cancer grows and spreads would seem to indicate that there is a means through which the cells are able to sense each other and gravitate together to form a tumor.

I would now be interested in the role of such fundamental forces in cell-signaling.
How does gravity interact with cell-signaling and lead to the 'gravitation' of tumor cells towards one another?
To my knowledge, cell signaling is a bunch of processes that involve the propagation of electrical signals by chemical means, so I am rather surprised that gravity would play any role in this.

That article looks like incoherent gibberish, to be honest. Very little in it makes any kind of sense. The statement that "the only way cancer cells could sense each other is through mechanical forces" is nonsense. You can't get microgravity with a centrifuge - all you can do is put the cells in higher "gravity" and then reduce the "gravity" back to 1. And so on. Undoubtedly the actual scientist knows these things, but the person who wrote the article clearly didn't understand what they were being told. Trying to figure out the reality is probably a waste of time, until Chou publishes.

@iayork: Yes, I was very confued upon reading it as well. The fact that the article on Universetoday is essentially a copypaste of the UTS article, and also misspells Chou's name is not very indicative of quality science journalism. However I was just curious if in the biology world there is some indication that this might be a real effect and what its provenance should be.

It actually looks like the original article was in fact written by Chou, and is still just as confusing. Statements like "By disabled, I mean they either die or float off because they can no longer hold on" sound a bit like https://xkcd.com/1217/ to me, and comes with no citation, nor does any of Chou's previously published work have any relevance to this. It kind of sounds like they shook up some cells growing in a dish and they fell off the dish.

Microgravity can affect the mechanical forces of the cell and alter gene expression; there are some reports on this. However, the statements made in the popsci article are ridiculous.

@WYSIWYG: I'm happy to upvote any credible source that goes beyond "Gravity affects pathways somehow". I'm interested in the microphysics, you could say.

@AtmosphericPrisonEscape I don't have time to write a full answer, at the moment. But have a look at this article https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007526/

@WYSIWYG Interesting article. So it seems that they essentially point to macroscopic shear stresses, blood pressure drops etc. to be responsible to deform cells and then cause all sorts of trouble. Wouldn't this cell degradation then also show up in a petri-dish under full $\vec g$, but with enough space for cells to expand, instead of squished together? It seems the cells rely on the effects of accumulated weight to keep their shape, so I'm surprised that a cells in a small petri dish show those effects...

It is reported that 99 genes are significantly upregulated in presence of normal gravity, whereas in absence of gravitational force no gene expression is seen in case of T cell activation. Research article attached concluded  that gravity is important for regulating various essential T-cell activation signalling pathways, which play key role in cell proliferation and apoptosis.
Transcription factors like NF-kB, CREB, ELK, AP-1, and STAT are responsible for tumor cell development. And NF-kB and CREB showed gravity-mediated gene expression. As, the PKA
signaling pathway regulates expression of these transcription factor, so it means that gravitational force moderates PKA signalling. And PKA signalling also mediates tumorigenesis. So, by regulating various cell signalling pathways, gravity controls the tumor cells.
Gravity also modulates the activity of Epidermal growth factor, which are implicated in tumor progression. (Via: https://www.ncbi.nlm.nih.gov/pubmed/7757250)

Thank you for this, but your answer doesn't answer my question. You say 'So, by regulating various cell signalling pathways, gravity controls the tumor cells.' and I asked 'How are cell signaling pathways regulated by gravity?'

The article (summary?) you've linked gives a hint at the end: "The physical mechanisms by which the T cells respond to gravity remain an intriguing enigma [...]". However the article is from 2005, so maybe there is some more recent insight? Or are we simply not there yet...

As gravity controls the expression of various Transcription factors, which are responsible for proliferation and death of cells by regulating signalling pathways. So this effects progression of tumor cells.

@TwinkleSheen You're repeating the same thing. "Controlling transcription factors" is not a mechanism for gravity to have an influence, it's just a synonym for "regulating cell signalling".


text:
Functional unit
What is meant by functional unit of a system?
Like when we say that the neuron is the basic unit of neural system, do we mean that all those things that are performed by neural system can be performed by an isolated  neuron?
If yes, how? And if not, then why do we call it as functional unit of neural system?
Like we say hepatic lobule functional unit of the liver is not hepatocytes, because we say that liver has complex functions, and single hepatocytes cannot perform it. So the functional unit of liver is the hepatic lobule.
Basically I am asking can a single  neuron perform the most complex functions of neural system: like memory storage, control and coordination (to a smaller extent) regulation of  a cell.
How can a single neuron control or regulate another cell, because wouldn't it need other neurons for processing of stimulus?
Can an isolated neuron process any stimulus and make other cell to respond in some way? If not so why we call it the functional unit of neural system?

In biology, functional unit of a system refers to the smallest structural element that is capable of performing the tasks typical for that system (MP Hlastala, Physiology of Respiration).
In the nervous system, a neuron is usually considered a functional unit, because it is capable of performing the basic task of this system, that is transmitting signals. But to perform more complex tasks, more neurons need to be organized into structures, which are usually not called functional units but, for example, pathways (visual pathway, somatosensory pathway) or centers (respiratory center, cardiovascular center, etc.).
Functional unit smaller than a cell
In the muscle cells, the proteins myosin and actin form myofilaments, which are organized into sarcomeres, which are considered functional units of the skeletal muscles, because the main muscle function (contraction) occurs on the level of a sarcomere.
Functional unit as a single cell
A single fat cell (adipocyte) is a functional unit of the adipose tissue, because it can perform its main task, that is to store fat.
Functional unit as a structural element
A structural element can consist of various cells, ducts, small blood vessels, etc.:

A nephron in the kidneys
A hepatic acinus in the liver (not a hepatic lobule)
A pulmonary acinus in the lungs (a respiratory bronchiole and its alveolar ducts and alveolar sacs, not a pulmonary lobule)
An acinus in the exocrine and Langerhan's islets in the endocrine part of the pancreas (Access Medicine)
A lymhoid lobule in the lymph nodes
An osteon in bones

"Functional unit" doesn't have a very specific meaning. It's mostly a term used to help biology students imagine organs as collections of parts.
The entities named functional units in a textbook don't typically perform every single function of a whole organ. A cardiomyocyte, for example, is a functional unit of the heart. It can perform really important heart-related functions like spontaneous rhythmic contraction. However, it can't pump any blood.
Similarly, neurons do important nervous system functions by themselves, like firing action potentials, and ultimately things like memory occur due to changes within individual neurons. They can't, however, do anything useful to the whole organism alone.

A functional unit can be taken as that part of a system that sort of imitates the function of the whole system. The work done by a group of "functional units" eventually gives us the function of the whole system as one.

Hi @seera-deborah! It would be helpful if you can expand on what exactly neurons do and they appear as if they imitate the function of the whole system.

Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers in the help center.


text:
question about stem cells
I was reading this paper:
https://www.ncbi.nlm.nih.gov/pubmed/26119455
and became confused after this sentence:
"The  ICM-derived mouse embryonic  stem  (ES)  cells and epiblast-derived
human  embryonic  stem  cells have  the  full  potential  to
differentiate  to  ectoderm, mesoderm,  endoderm, and trophoblast."
As far as I know, the trophoblast is originated from morula cells that are totipotent, and ICM cells are pluripotent...
Moreover, are ESCs derived from the ICM of the blastocyst? Because if yes, does it mean that they can also become primitive endoderm and give rise to some extraembryonic tissues? Because as I know only epiblast (primitive ectoderm) gives rise to 3 germ layers... does it mean that ESC are derived from epiblast only or not?
Thanks


text:
Exactly what kind of spider is this in Louisville, KY?
I took this photo many years ago, but I guess the year doesn't really matter. It was here in Louisville KY, on the outside of a window, on a web it built. It was a couple hours after sunset in the summer. It was about the size of a silver dollar.

Some people said it's a Garden Orb at first, while recently others say it's a Wood spider. Either way, I'm not entirely sure.
What species of spider was this?

It is an Orb Weaver (Neoscona crucifera). It is found from Maine to Florida in the east, to Minnesota in the Midwest, to Arizona in the southwest, and in Mexico.

Females are about 9.5–19 millimeters (0.37–0.75 in) long, while males are somewhat smaller. The upper surface of the abdomen is brown and hairy. The legs display alternating light and dark brown bands. The undersurface of the abdomen is black, with two white spots.
This species is relatively variable in color and sometimes pattern, but is most commonly seen sporting a rusty-red or golden orange color. The orb-shaped web is very large and is often constructed on buildings and other man-made structures, especially near outdoor lights. This species is most conspicuous in late summer and early fall.

For many years, this kind of orb spider would build a very large web every night just outside the back door (near a light.) While fascinating to watch, if was a lot less fascinating to forget it was there in the morning and walk face first into it. But I prefer to live and let live, so... :)


text:
RNA product storage in isopropyl alcohol
I have an issue. I isolated RNA from cortex a few days ago. For isolation of RNA i used this procedure:
I homogenizised my sample (mouse cortex) with Trizol. Then to the sample add chloroform, shooke and centrifugate it. After this part i took away the aquatic phase with RNA from mixture and add it to the eppendorf tube with beforehead prepared isopropyl alcohol with glykogen. Again i shook and centrifugate it. In this part i removed isopropyl and let only RNA pelet. Afterwards i did same thing with 75% ethanole. Last but not least i dissolved the pellet with DEPC, checked its concentration on nanodrop.
From nanodrop i saw that one of the sample had been contaminate with guanidine isothiocyanete. So i just desided to repeat steps od my isolation from isopropyl alcohol. To increase precipitation of RNA and increase chance od decontamination i decided to let RNA in isopropyl alcohol precipitate in -80 °C freezer for a night. Unfortunately i fail to remember it untill now.
My question is: Will it affect any integrity of my RNA sample?

It would generally not be an issue to leave RNA in alcohol but you should clarify your question. What do you mean by "let it clean"? Why are you doing it after the extraction and quantification? What was the concentration of alcohol?

WYSIWYG i try at least write down the steps i did. Today i was at lab but i forgot check the concentration. But i usually use all chemicals in proportion  to volume of trizol. So the isopropyl alkohol is from bought storage bottle.


text:
PCR markers for C57B6
Do you know any primers that can be used to genotype mice and check if they are still C57B6? I'm concerned about genetic drift in my colony. I bought a breeding pair 3 years ago and expanded. I wanna make sure my animals still retain genetic markers of c57b6. Thanks

Why not buy more mice? Breeders have schedules to make them as homogeneous as possible. Spontaneous mutations that are maintained in your colony won't show an association with any sort of markers.

Welcome to Biology.SE! The only way to check for genetic drift would be to sequence the entire genome of your mice — in all likelihood any pair of primers would give you the same result even if you had a significant accumulation of point mutations. As @BryanKrause says, buying more mice is much more practical. ——— You may also benefit from taking the [tour] and then going through the help pages starting with [Ask] questions effectively on this site. Thanks!

Jackson Labs offers a service for this for what looks like a reasonable price. I have no experience with the service other than general good feelings about Jackson.

We have a unique selection of mouse single nucleotide polymorphism (SNPs) panels useful for a diverse set of mouse research applications.
Applications of SNP scanning services

Development of congenic mouse lines
Confirmation of C57BL/6 substrain background

[...]
Available custom designed SNP panels specifically tailored for your needs
The right panel for your needs - $179/sample
[...]
C57BL/6 substrain characterization panel distinguishes between C57BL/6J (B6J) and C57BL/6N (B6N) or C57BL/6NTac (B6NTac) genetic backgrounds

--GENOME SCANNING SERVICE
Edit to include some points raised in comments:

"These panels [i.e. the ones Jackson labs offers, noted above] seem to be intended for comparing between known strains, like when you make a transgenic strain and are in the process of backcrossing. It would not be as useful for monitoring drift, or for comparing an unknown C57BL-derived line to a standard one." – Bryan Krause
Any mouse colony will diverge from other colonies, especially if there are relatively few founders.

The identification of two CNVs in the small portion of the genome screened demonstrates that individual mice of highly inbred strains are not isogenic and suggests other CNVs may be segregating within C57BL/6J as well as other carefully maintained inbred strains.

--Genomic copy number and expression variation within the C57BL/6J inbred mouse strain

At the very least, intermittent back-crossing to a mouse from a different source is recommended.

With time, isolation and a little spontaneous genetic drift, a founder pair can produce a new substrain in as little as three generations (something to bear in mind if you're breeding mice in-house without “refreshing” the gene pool with an intermittent backcross to a bona fide C57BL/6J ... Clearly, substrains of C57BL/6 (and other inbred strains) are not all the same.

--All (C57BL/6) Mice are not Created Equal

Simply buying new mice as needed, from the same (reliable and standard) source each time, gives you a better chance of consistency, since a large breeder is less likely to see on-going founder effects.

If you have a solid reason for keeping your own colony, talking to the experts at Jackson Labs would be a good starting point; presumably monitoring strain consistency is something they think about as an ongoing issue, and they can give better advice than we can.


text:
Adult Bugs in Low Humidity House Heated With Wood?
I have a home heated with wood. The humidity is currently around 30% but I'm guessing these bugs have reproduced when the humidity was higher. They really have a hard time when I see them in the basement.
I do have some wood that was a little punky. They seem to come out as soon as I start a fire in the stove, probably due to the heat?

Approx 3cm long
Located in the eastern townships of Quebec, Canada. Any suggestion on what this is and how to treat them?

Welcome to Biology.SE! Please edit your post to add an estimate for the size of this insect as that can be a helpful clue for identifications. ——— You may also want to take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. Thanks!

@tyersome Thanks. I modified the question with the length of the insect. I'm starting to think this may be a Sirex Woodwasp?

Great, thanks for updating — looks like you got a good answer as well!

The pictures are not entirely clear, but I’m relatively certain that it is a wood wasp of the genus Xiphydria (family Xiphydriidae). Traits that point to this is e.g. 2 pair of wings (i.e. a wasp and not a fly), narrow slender antenna, elongated body, the shape of the head sitting on a relatively long “neck”, often with light/white markings on the top and or the back of the head (which can be seen on picture 2) and often white markings along the side of the abdomen (which your insect has) The second picture also shows the relatively robust ovipositor (used to inject eggs into wood).
They also lay eggs into dead wood (usually deciduous wood) and are not uncommon to find in houses, hatched from fire wood.
The species is very hard to determine though, but X. mellipes could be one bet. This species also seem to be found in Canada, see zoology.ubc.ca/entomology. It is also similar to Xiphydria camelus which is common here in Sweden, but I’m sure if it is also found in Canada.

(Xiphydria mellipes from wikimedia commons
Pictures of some species can be seen at bugguide.net).
These insects are not dangerous to find inside, and they only attack dead wood in standing or fallen trees, not construction wood. They are not uncommon to find indoors (along with longhorn beetles and other wood insects) if you bring in mixed fire wood, especially if the wood wasn’t processed and dried quickly after felling. An interesting feature of these insects is that many (all?) inoculate the wood with particular fungi spores, and the fungi later function as the food for the larvae.

Excellent. Thank you, I think you're right with that picture; it really looks like it. White stripes on its head and abdomen. How dangerous is this to my house and what could I do to treat it? I've been searching every log in the pile but it's quite difficult. Do they rather punky wood?

It’s not dangerous at all. The adults have hatched from wood taken inside. They will try to escape outside or die inside the building. They only attack moist dead wood or strongly weakened trees. It is common to get these inside (along with eg long horn beetles) when you bring wood indoors.

You should be able to find round exit holes in one of the logs. From wat I know, all wood wasps have round holes. The other option is that they hid under loose bark but that is less likely, especially if you find several of them.

Thanks a lot! Very appreciated.

I think that is a soldier fly.
https://animals.howstuffworks.com/insects/will-black-soldier-fly-maggots-save-humanity.htm

The adults do not eat or sting, only mate, lay eggs and die.  The maggots are very large and awesome devourers of rotten fruit.  They alternate with worms in my worm bin depending on season.
I have no idea what they are doing in your house!

thanks for the well-written answer, but (-1) because this doesn't appear to be the correct insect. for example, look at the difference in shape of antenna, color of legs, wing characteristics, ecology (soldier flies don't burrow in wood to my knowledge), etc.


text:
Do species ever move into new territory and then die out because of the local diseases?
We usually hear that an invasive species has brought with it a disease which it itself shrugs off easily, but which then decimates the local population which has never encountered it before. It's a very common story. But it doesn't make sense to me. Surely it should be far more common for the reverse to happen? Surely a newly arriving species has to face not just one or two new things in the new environment, from one or two new individuals, but an entire environment coming at it from every direction with hundreds of viruses, bacteria and competitors it has never come across before. So how come the story is always that the invading species kills off the locals, when you would expect the invading species to have hundreds of totally new threats and strange foods to handle, would be unable to cope, and would die out?

So how come the story is always that the invading species kills off
  the locals, when you would expect the invading species to have
  hundreds of totally new threats and strange foods to handle, would be
  unable to cope, and would die out?

There is a problem of observation bias for these two scenarios.  In the first scenario a few members of an invasive species enter a new range, transmit a novel disease to the pre-existing species, which suffers a massive (easily observable) die off. In the second scenario, a few members of an invasive species enter a new range, catch a local disease, and die in short order (unobserved and unnoticed).
In other words, a few individual deaths from any cause will generally go unnoticed. Thousands or millions of deaths of deaths from a novel disease are more likely to attract attention.

That's a good answer, thanks.

Charles is correct.  You might want to look up 'failure to thrive', and 'introduction failed' when humans tried to introduce new species (the existing environment ate them up), and it didn't work out.
We tend to record successes, and bury failures.


text:
Are there organisms that "branch more" near the leaf?
(I'm a computer scientist)
Tree branching is a fractal patterns in nature. I know stems typically branch in two at each level (self-similarity). I guess there are plants or other organisms that branch in 3 at each level (still self-similar).
But are there organisms where the stem first branches in 2, then at the next level branches in 3 or more? And maybe at the next (maybe the last) level branches even more, say in 7? It doesn't need to be the stem of a plant, it could be any part of any organism (fungi,...), e.g. the "flower part" of a plant, or a micro-organism.
I'm looking for places where just the branching factor changes, but otherwise little else. What I'm not looking for "branch by 2, branch by 2, branch by 2, and then the very final step is one level of fascicle where branching is 5". I would be fine it's "branch by 2, branch by 3, then fascicle where branching is >3".
I'm trying to find if there is something in nature (e.g. organism, geological, or physical structure) that follows this pattern found in a computer science algorithm, RecSplit, which I co-authored.
Like the following: it first branches in 3, and then branches in 8. The actual numbers don't matter to me, it might as well be branch in 2, then in 3, then in 5, or so.

Welcome to Biology Stackexchange! Could you directly link a picture of the branching you describe? I think i found it in the linked paper, but it'd be easier if you can directly link it. Additionally your questions title starts with tree's but the question focuses more on all plants - and I don't think tree's will show the pattern you are looking for so this might mislead people a bit (other plants or maybe fungi might?, not really my area of expertise).

Thanks a lot! I added a picture, and changed the title... I'm not sure what labels would be best. Feel free to edit my question!

https://en.wikipedia.org/wiki/Fascicle_(botany)

Thanks @John for the link! Do you consider this an answer to the question, or is it just the correct term for my awkward / clumsy description "flower part of a plant"?

@ThomasMueller I don't know enough about plant development to turn it into a full answer, but I know what you were asking existed so I want to leave the link.

I think I understand what you mean, but I'm afraid the fascicle is only one level of branching... Sure you could say the plan is branching before that, say branching factor 2, and then the fascicle branching factor is 5... but I'm looking for two levels of branching of the same type, and one is wider...

Can you add some information about why you are interested in such an example? Branching in most plants completely is different from what is seem in your example or in phylogenetic trees. In vascular plants branching is typically from lateral buds rather than splitting of the growing tip so your question as currently formulated doesn't apply to most plants. In most plants these lateral buds are associated with the axils of leaves and thus the branching pattern primarily depends on the phyllotaxis. ...

However, not all lateral buds grow out to form branches, so the observed branches will be a subset of those potential branches. Finally, while some plants produce leaves (and buds for branches) in whorls (all initiated at the same time and position along a stem) many produce leaves (buds) one at a time. Depending on your goal for this, I think your question may need to be rewritten to do one of the following: 1) focus on the minority of plants that show dichotomous, trichotomous, or polytomous branching, 2) allow for branching in whorls, or 3) deal with leaves/buds rather than actual branches.

Note that there may also be fungal hyphae that show "chotomous" branching. However, while I know little about that subject it seems that lateral branching is also the predominant form in that kingdom.

It looks like Penicillin might be what I'm looking for: G in https://www.researchgate.net/figure/Conidiophore-branching-patterns-observed-in-Penicillium-A-Conidiophores-with-solitary_fig2_266395536 -

@tyersome Thanks a lot! If you want to write an answer (link in my comment) I can give credit to you. (I will still create a bounty tomorrow, maybe there are better examples.)

If you're satisfied by "any organism", how about humans?  The single bone of your upper arm/leg branches into two bones in the lower limb, then into five finger/toe bones.

I can't say that your question is very clear to me, but perhaps something of interest to you would be a common type of inflorescence called an umbel. specifically, a compound umbel with associated umbellets.
Compound Umbel:

 Source: Educational Technology Clearinghouse
Some examples can be found here
Again, since your post is not clear to me, I'll also include images of other complex inflorescences:

 Source: texaswildbuds.com   [the compound cyme might be of interest to you]

Thanks a lot! Yes, this is interesting, however it looks like the number of branches are the same on each level (8 for Compound Umbel). I'm looking for something that branches lesscloser to the root (e.g. branch by 2), and branches more near the "top". Chervil does look OK to me.

One case seems to be Chervil.
Another case Penicillin, specially figure G.

Technically Penicillin is a fungus not a plant - though I'm not sure if OP cares about the distinction for his question.

I'm the OP :-) Organism is fine. Actually, a geological structure or even physical would be fine as well - anything in nature.


text:
Reference Request: Human visual system takes in $10^7$ bits/sec at the periphery and compresses it down to 50 bits/sec deep inside
In Sparse Components of Images and Optimal Atomic Decompositions by Donoho, 1998, the author claims that

The human visual system is thought to do a tremendous job in achieving sparse representation of image data, taking $10^7$ bits/sec at the periphery of the visual pathway and winnowing it down to about 50 bits/sec deep inside.

Can somebody please point me to the source of that claim, as it is not mentioned in the paper, at least to my knowledge.

Good to ask for such a reference, because these sorts of claims are usually based on some truly silly assumptions when taken too literally.

How about this:
https://www.springerprofessional.de/data-compression-and-data-selection-in-human-vision/3218014
The original link in the Abstract referenced (https://link.springer.com/content/pdf/10.1007%2F978-3-642-04954-5_7.pdf) above isn't available anymore, but I found a repository:
https://webdav.tuebingen.mpg.de/u/zli/prints/ZhaopingNReview2006.pdf
I don't think the review is peer reviewed, but maybe you find a reference in there (it's not my field, so I guess you know more on where to look ;-)
She's now in Germany:
https://www.researchgate.net/profile/Li_Zhaoping
If you don't find anything, maybe you can ask her on researchgate directly.


text:
What is the technical term for when a clade on a phylogenetic tree does not have an extended branch? (see image)

As we see with ZCA2, ECA2 & XCA2 these branches are compressed and do not extend as TCA does. Is there a technical term for this and what usually causes it?

Welcome to Biology.SE! We encourage you to do some research on your own and then, informed by what you have learned, ask any questions you still have (ideally with references to reliable sources). For example, have you looked at the autogenerated "Related" posts associated with your question? This post seems like it could be relevant. ——— Please also take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. Thanks!

The phenomenon where you have different "evolutionary clocks" of selection is called heterotachy. The branches are therefore heterotachic or simply long branches —long branch attraction is a problem with Bayesian inference for which many arguments have been had, so there is a lot of literature on it.


text:
Cellulase Sample Digestion Protocol?
Is there an effective way to use cellulase(s) and/or lignase(s) to remove unwanted plant debris from a sample?
I'm working with a series of fresh water grab samples for environmental assessment. The objective is to separate out the benthic invertebrates as a proxy for biodiversity and habitat health. We use 500 micron mesh to remove the bulk of the sediments but this leaves several liters of fine plant material in a variety of stages of decomposition. While searching through yet another petridish of rotting sphagnum I wondered if there might not be a better way to do this?
Is there an effective protocol for decomposing the plant matter using some mixture of cellulases and lignases? Or am I barking up the wrong tree?

Welcome to Biology.SE! No experience with this but I would guess that cellulase treatment would be far too slow and I wouldn't have thought there was much lignin in sphagnum. Are these samples of living organisms or have they been fixed in some way? If live, could you use a variation of the technique I've seen where leaf litter is heated in funnels? Maybe you could try using noxious chemicals or heat to drive the invertebrates from the sphagnum slurry?

Thanks tyresome. The samples aren't entirely sphagnum and have a healthy amount of grasses, leaves, etc. Pretty much a stew of anything that fell into or grew in the river. The critters have been preserved in ethanol and are hopefully dead.

You could try experimenting with enzymes on some samples you've already analyzed — if you find something that works publish it and post your answer here!  The only alternative I can think of is if you could find a stain that was selective for invertebrates (I was thinking about chitin, but then realized your samples must be riddled with fungi). Good luck!