text:
What's the term for "Amino acid regulating the expression of components used to synthesize it"?
In the tryptophan operon wikipedia page, it says under the Attenuation title:

A similar attenuation mechanism regulates the synthesis of histidine, phenylalanine and threonine.

If my reading is correct, this means that these amino acids also regulate expression of componenets that synthesize them.

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

What's the term for "Amino acid regulating the expression of components used to synthesize it"? , maybe the lack of a question mark '?' in the question body stimulated this bot to write this.

The method of inhibition of the operation an anabolic metabolic pathway by the final product synthesized is called:

End-product Inhibition or Feedback Inhibition

Of more biochemical interest is the mechanism, which is:

Allosteric regulation

In general terms, the end product of the pathway is a negative allosteric effector of an early (often the first unique) enzyme of the pathway.
However this is quite distinct from Attenuation. Attenuation regulates the transcription of the trp operon, i.e. the synthesis of the mRNA that encodes the enzymes of the pathway. That summarized above relates to catalytic activity of the already-synthesized enzymes. Attenuation is restricted to prokaryotes†, whereas allosteric regulation is a more general phenomenon.
Although semantically the term “end-product inhibition” could also be applied to attenuation or even repression of transcription, in practice it is not. I do not believe that there is a specific term for attenuation of the transcription of a polycistronic mRNA for synthesis of an amino acid by its tRNA.
End-product inhibition is covered in all biochemistry text books. The best web example I can give that covers all the above terms is from Alberts et al., Molecular Biology of the Cell, freely available on NCBI Bookshelf. This example involves the pathway for the synthesis of CTP, rather than that of an amino acid, the enzyme inhibited being aspartate transcarbamoylase. However the principle is the same.
You can pick up a secondhand copy of an old edition of Berg et al. Biochemistry cheaply on eBay, for example. Well worth it to ready an authoritative account of basic topics in biochemistry, such as this one.
† The reason that attenuation is restricted to prokaryotes is that it depends on the coupling of transcription and translation. In eukaryotes, however, transcription occurs in the nucleus whereas translation occurs in the cytoplasm.


text:
Are probabilities of mutations symmetric?
For the premise of this quiestion let's assume that there is an allele A and an allele B. The allele A has a probability P to mutate into the allele B in the given timeframe.
Is it also true that the allele B has the probability P to mutate into the allele A?

The short answer is no, there is heterogeneity in the rate at which different nucleotides mutate into one another. This is generally a property of their differing chemistries (although I'm not an expert on this). Therefore, it doesn't really make sense to talk of alleles being $p$ or  $q$ like we do in most of population genetics, because the actual nucleotide (whether it's A, C, G or T does make a difference).
This is important in fields like phylogenetics, where people construct substitution matrices which describes the rate at which one base in a sequence changes to another nucleotide. Currently, it's possible to estimate the matrix parameters from empirically data relatively easily.
For example, in one of the earliest and most simple models, Kimura (1980) introduced a matrix which had two parameters - one for the mutation rate of transition substitutions (A/C -> G/T, more likely) and one for the rate of transversions (A/G -> T/C, less likely). Later methods got progressively more complex, which account for e.g. the different amino/keto properties of different nucleotides. Felsenstein's model (1981) accounted for the equilibrium frequency of the target nucleotide. These substitution values are also allowed to vary across time as well within a phylogenetic tree (e.g. Yang 1994).

References

Kimura, Motoo. "A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences." Journal of molecular evolution 16.2 (1980): 111-120.
Felsenstein, Joseph. "Evolutionary trees from DNA sequences: a maximum likelihood approach." Journal of molecular evolution 17.6 (1981): 368-376.
APA
Yang, Ziheng. "Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods." Journal of Molecular evolution 39.3 (1994): 306-314.

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text:
why not classify organisms based on genetic distance?
When learning about "families of animals" in mid-primary school, my son asked me if there is not a better way to classify animals than by looking at them (they were taught that animals are grouped into families based on what covers the skin (hair, feathers, nothing), number of legs, the way they breathe, etc.).
He was wondering if there would be a more quantifiable way of grouping them (this is my wording). I told him that since all animals share the same genetic coding principles, we could try to calculate how different their genetic material is, and derive a "distance". This would allow grouping animals in possibly novel ways, and maybe have some of them cluster in "families" (possibly different from the existing ones).
After having played my role of super-hero-dad, I now wonder if this makes sense? (and if so - is it used? and if so - why still using some classifications from centuries ago?)

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text:
Alcohol and athletes?
I've seen a lot of articles claiming that alcohol has a very bad impact on athletic performance. Examples include, but are by far not limited to:

http://oade.nd.edu/educate-yourself-alcohol/alcohol-and-athletes/
http://www.theguardian.com/lifeandstyle/the-running-blog/2014/apr/23/how-does-alcohol-affect-athletic-performance
https://www.acsm.org/docs/current-comments/alcoholandathleticperformance.pdf
http://www.athletestore.co.uk/wordpress/wp-content/uploads/2013/01/The_Effect_of_Alcohol_on_Athletic_Performance.7.pdf

I'm of course not in position to doubt those articles, as I'm a no expert in biology.
However. There is one thing I find odd.
Namely. These articles themselves claim that alcohol is widely consumed even by the highest ranking athletes. I mean, if alcohol has that bad effects... then it couldn't have been consumed by highest-ranking athletes, as alcohol-consuming athletes could never rich the heights of the tops of proffessional sports?
Also. AFAIK mediaval knights were not abstinents by any means, they were drinking beer and wine and mead to excess; yet they were able to bring their strength, stamina, etc, to an extreme.
This is not something I wish to argue about; rather, this is something I fail to understand.
BTW. This question is not personal; I don't do sports and I very rarely drink. And I regret the former, not the latter.

Whenever you look at any parameter in a population, you will have a spread. Let's take I.Q., for instance (and lets not quibble about how it's measured; it's irrelevant for our purposes):

This is the famous "bell shaped curve". You can see how few people are significantly above normal. Now, that line continues to include people with an I.Q. of 200+. That's not immediately obvious from the graph. It also continues the other way - people with an I.Q. so low that they cannot participate in their own testing. That's because the vast majority of people fall between 70 and 130.
The same principle applies to physical skill, bravery in battle, etc. The curve may be flattened or sharper depending on what parameter is being measured, but rest assured, paid professional athletes fall in the upper 1 percentile.
Lets go back to intelligence for a moment. Take someone like Bobby Fischer (Chess Player), I.Q.: 187
I guarantee you that even falling-down drunk, Bobby Fischer would have beaten me easily in a game of chess (and it's not because my I.Q. is average or below). It's because he was so very much, unimaginably better at chess than I am.
I guarantee you that even falling-down drunk, Albert Einstein could solve mathematical equations I can't even write. It's because he was so very much, unimaginably more intelligent than I am.
It's the same with great athletes. Even if they drink every night, a great athlete will outperform you or me on any given day.
That's why you are just dead wrong when you state "then it couldn't have been consumed by highest-ranking athletes, as alcohol-consuming athletes could never rich the heights of the tops of proffessional sports".
You are just laboring under a completely false premise. These people are so much better than people only 1 percentile below them that drinking doesn't necessitate that they fall in the ranks.

While a drunk Usain Bolt or Tiger Woods could beat me at their respective sports, the pro athletes etc are competing with others also at the extreme end of the bell curve, a gain of a small percentage does matter then.

@GriffinEvo - not if most of them are drinking, which they are. Alcohol use isn't a major factor for most top athletes.

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text:
Does the theory of evolution fail to explain people sacrificing their lives for their enemies?
Monika i Marcin Gajdowie, "Rozwój. Jak współpracować z łaską", the very beginning of the book:

Przede wszystkim jednak, niektórzy z nas są gotowi oddać życie z miłości do nieprzyjaciół, a to zaprzecza instynktowi przetrwania. Ten absurdalny krok nie daje się wytłumaczyć teorią Darwina.

My translation:

And above all, some of us are ready to forfeit their lives from their love to their enemies. This contradicts the survival instinct; such an absurd act cannot be explained with Darwin's theory.

To give some context: As is evident from later sentences from this book, what I quoted above is one of the few arguments the authors present while trying to support their claim that men "also belong to the supernatural order" (they write from a Christian POV).
This is not, however, what I'd like to focus on in this question.
Instead, my focus is: Does the theory of evolution indeed fail to explain the cases when someone sacrifices their life for their enemies?

The question is not very well worded. It's a good evolutionary psychology question. It's paralleled with human ability to commit suicide, which goes against the survival instinct. The fact that humans invent lots of deadly weapons and tortures and also go to war does not place men in the supernatural order, it's animalistic. The creation of simian deadly weapons is recent in evolution, and it's artificial, not supernatural, so it facilitates intra-species killing. Defensive suicide is very rare vs deserters, it's actually either last ditch attack or a brainwashed kamikaze/suicide bombing.

You might ask yourself some more pertinent questions, like "what did the theory of evolution attempt to explain?". Not altruism (or why people vote the way the do, which is generally selfishness) but something about how different species arose, I believe. And "does the evidence support the actual theory?". On a different level, you might ask yourself why the vast majority of biological scientists accept the theory and wouldn't waste their time arguing about it.

Possible duplicate of Why do some bad traits evolve, and good ones don't?

And above all, some of us are ready to forfeit their lives from their love to their enemies. This contradicts the survival instinct; such an absurd act cannot be explained with Darwin's theory.

There are two problems with this statement, which make your question whether evolution might actually explain such behaviour, essentially meaningless:
1) The statement assumes that certain actions (which are just assumed/proposed to occur) of individuals go against a 'survival instinct' and therefore contradict the theory of Darwin.
There are a lot of problems with that assumption:

the 'theory of Darwin' is quite far away from our modern theory of evolution
Evolution acts on a species, not on individuals. Therefore even if some individuals show a behaviour that is not favourable, evolution still works as normal (and that behaviour may or may not be selected again within a couple of generations).
Acting against a 'survival instinct' can in principle be beneficial to the survival of the species, even if detrimental to an individual (think of parents sacrificing themselves for their offspring).

2) An 'enemy' is an utterly human concept and has no meaning in the context of evolution or biology.
From a scientific standpoint something like "forfeit their lives from their love to their enemies" makes absolutely no sense.
An individual can sacrifice themselves in certain situations, this may just end their life and therefore be an evolutionary disadvantage. However, - in other situations - it might also help their offspring or other individuals of the species in survival and therefore be an evolutionary advantage. There is no way determine a priori whether such an action will always be beneficial or always negative - both options are possible depending on individual context.

Re "From a scientific standpoint something like "forfeit their lives from their love to their enemies" makes absolutely no sense."  It also doesn't make much sense linguistically, either.  You might also consider that it's seldom a straightforward case of sacrifice, but of risk.  The individual who e.g. risks his life to defend the tribe from a sabertooth may die, but he also may live, be hailed as a hero, and have lots of opportunity to spread his genes around as a result.

If you're asking if evolutionary explanations of suicide have been proposed... they have e.g.:

The altruistic suicide hypothesis posits that the presence of low reproductive potential and burdensomeness toward kin can increase the inclusive fitness payoff of self-removal. [...]
Altruistic self-destructive behavior has been found in a wide variety of organisms, ranging from unicellular organisms and parasites to social insects, and is debated in mammals. Self-destructive defensive behavior has evolved independently in a number of social insect species in response to natural enemies. Self-sacrificing behavior has mainly been found in the context of nest protection. Defensive self-sacrifice persists in social insects because of its positive impact on the fitness of the colony’s reproductive individuals. As with other forms of altruistic traits, the genes involved will pass on to subsequent generations.

One interesting paper proposed (using simulation) that

Altruism-benefiting fellow group members at a cost to oneself-and parochialism-hostility toward individuals not of one's own ethnic, racial, or other group-are common human behaviors. The intersection of the two-which we term "parochial altruism"-is puzzling from an evolutionary perspective because altruistic or parochial behavior reduces one's payoffs by comparison to what one would gain by eschewing these behaviors. But parochial altruism could have evolved if parochialism promoted intergroup hostilities and the combination of altruism and parochialism contributed to success in these conflicts. Our game-theoretic analysis and agent-based simulations show that under conditions likely to have been experienced by late Pleistocene and early Holocene humans, neither parochialism nor altruism would have been viable singly, but by promoting group conflict, they could have evolved jointly.

And I'm not sure people sacrifice themselves for their enemies often enough for that to be worthy of constructing an (evolutionary) explanation for. It might be like asking what's the evolutionary explanation for the moon being made of cheese. Even assuming that this phenotype (sacrificing for their enemies) does occur with some low but non-zero probability (that onus is on you prove it's higher), that doesn't invalidate the theory of evolution for a couple of reasons:

Selection doesn't act instantly to produce a perfectly fit population, instead fitness increases over time more like a power law, at least in microbes where it's easily quantified. Various loci may be under different levels of selection pressure, depending on the environment. Even assuming the mutation that causes the phenotype is uniformly detrimental to fitness (which might actually not be the case, depending on variations in the environment), weak selection can cause it to linger for a long time; see Huntington's disease as an example of weak selection. (And more recently it's disputed whether the mutations that cause Huntington's provide no fitness advantage whatsoever; the technical term for a tradeoff being "antagonist pleiotropy".)
Current estimates put the percentage of human genome that evolved due to chance alone to around 5%. Random occurrences of "weird" phenotypes can thus happen with some fairly low probability.

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text:
Do women tend to have longer legs and shorter torsos than men?
I've always heard that women tend to have a greater leg length to torso length ration than men, and I think that my anecdotal observations of pedestrians of both sexes tend to confirm that.
However, now I read that is not the case:

If they are the same height, she’s a lot “leggier” than he is. It looks as though women really do have long legs and short upper bodies for their height. (We’ll see later this isn’t the case.)
(...)
This observation is purely anecdotal, though. There are studies which measure the lengths of men’s and women’s legs, arms, upper bodies, and so on. These measurements show that women have shorter legs and longer torsos than men as a proportion of their heights.

So, at least, says a bicycle designer. And I suppose bicycle designers should know anatomy.
I have a cognitive dissonance here, since again, my eyes watching pedestrians tell me otherwise.
So - what is the truth?

I think men look like they have shorter legs because they tend to wear pants that are less form fitting with a lower hanging crotch area for obvious reasons. So this gives the illusion of a longer torso and shorter legs. Women also tend to wear clothes that accentuate the length of the legs to make the legs look longer, like high waisted pants, etc.

We seem to have a preference for proportionally longer legs (see comment here for a good summary around that study).  So when you are observing "pedestrians" they have probably tended to dress and comport themselves to skew your perception of their leg lengths.  Perhaps in your cultural environment females have a greater capacity and/or motivation to alter that perception than do men.
The reality is that adult female legs are on average proportionally shorter than those of men.  See, for example, this detailed 1977 U.S. Army study comparing body proportions in adults by gender.
For readability I would highly recommend this much broader survey of the subject, which contains not only clear illustrations of how proportions are measured but also an extensive survey of cross-cultural and historical variations: Leg Length, Body Proportion, and Health: A Review with a Note on Beauty.


text:
Can telomere length maintenance be an answer to increased life span of human beings?
Telomere shortening may prevent the development of cancer in human aged cells by limiting the number of cell divisions. However, shortening of telomeres impairs immune function and thus might also increase susceptibility to cancer.Hence if length of telomere is kept constant, wouldn't it lead to development of cancerous cells rather than increase of life span?

Possible duplicate of Is each generation getting older?


text:
Some kind of fly, identification

It has a really interesting shape. Is this a common fly ?
Edit: I found this in a relative's house. For area, I can say the  plateaus and mountainous parts of Turkey's mediterranean coast. I just saw a single one of them. It was alive. The size was like 1 cm. Never saw one before in my life. It peaked my interest so I decided to ask.

Welcome to Biology.SE. We will need (1) the location, (2) the type of habitat, (3) a scale (how big was that approximatively). Also, was it alive? Did you see only one of them?

It seems to be an mayfly (Ephemeroptera) and not a fly (Diptera) as it looks like it has tail cerci. If it is one, then chances are you saw multiple of them all slowly dying.

@Remi.b I edited the question for more information.

It is some sort of plume moth, Pterophoridae. I can't tell what species it is, but at least you know more about where to look! Or, hopefully, someone who knows more shows up.
There are probably better places to look, but I found this list of plume moths in Turkey on Wikipedia if you want to compare.

The funny thing is, if you google "t shaped fly" you can find images of this insect. :D

Yes, it's very handy when animals are easy to describe! Seems like a common species is even called "T-moth" in English.

It's funny, I just saw my first one ever tonight in Newfoundland, Canada. That family seems to have a wide distribution.


text:
Are the human placenta chorionic villi and villous tree the synonyms?
Are the human placental chorionic villi and the villous tree the synonyms? Or, if not, can I say that these tissues would have practically the same gene expression profile in an RNA microarray experiment?


text:
Variation of nutrients in food
Recently when buying food, mainly vegetables, I started looking at the nutritional values. Now for some reason the Dutch broccoli has way less protein (~2g/100g) than the German one (~8g/100g). Because of this I started paying attention to this and this seems to be the case with a lot of raw products. The amount vary wildly and I can't seem to find an answer to why this is. I can imagine it varying a little between yields but this seems like an awful lot.
TL;DR
How can nutritional values vary for the same raw product?
-- EDIT - 2016-09-15 --
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║               name                ║    brand     ║     PoS      ║ Country ║ frozen ║ biological ║ energy ║ energie ║ protein ║ Carbohydrate ║ - sugar ║ fat ║ Monounsaturated ║ Polyunsaturated ║ Saturated ║ Dietary fiber ║ salt  ║ price per kg ║ amount ║
║                                   ║              ║              ║         ║        ║            ║ kcal   ║ kj      ║ g       ║ g            ║ g       ║ g   ║                 ║                 ║ g         ║ g             ║ g     ║ euro         ║ g      ║
╠═══════════════════════════════════╬══════════════╬══════════════╬═════════╬════════╬════════════╬════════╬═════════╬═════════╬══════════════╬═════════╬═════╬═════════════════╬═════════════════╬═══════════╬═══════════════╬═══════╬══════════════╬════════╣
║ AH Broccoliroosjes                ║ AH           ║ AH           ║ NL      ║      1 ║          0 ║ 27     ║ 115     ║ 4       ║ 0.8          ║ 0       ║ 0.3 ║ 0               ║ 0.2             ║ ?         ║ 2.5           ║ ?     ║ 2.07         ║ 450    ║
║ AH Broccoliroosjes voordeel       ║ AH           ║ AH           ║ NL      ║      1 ║          0 ║ 20     ║         ║ 2       ║ 2            ║ 2       ║ 0   ║ 0               ║ ?               ║ ?         ║ 3.5           ║ 0     ║ 1.99         ║ 1000   ║
║ AH Biologisch Broccoli            ║ AH           ║ AH           ║ NL      ║      0 ║          1 ║ 27     ║ 110     ║ 3       ║ 0.8          ║ 0.8     ║ 0.7 ║ ?               ║ ?               ║ 0.1       ║ 3             ║ 0.01  ║ 3.58         ║ 350    ║
║ Bonduelle Broccoli                ║ Bonduelle    ║ AH           ║ NL      ║      1 ║          0 ║ 26     ║ 109     ║ 2.4     ║ 2.4          ║ 1.2     ║ 0.3 ║ ?               ║ ?               ║ 0         ║ 2             ║ 0.02  ║ 5.5          ║ 300    ║
║ Bonduelle Broccoli                ║ Bonduelle    ║ Bonduelle    ║ NL      ║      1 ║          0 ║ 26     ║ 109     ║ 2       ║ 2.4          ║ 1.2     ║ 0.4 ║ ?               ║ ?               ║ 0.1       ║ 2.5           ║ 0.03  ║              ║ 300    ║
║ Bonduelle Broccoli                ║ Bonduelle    ║ Jumbo        ║ NL      ║      1 ║          0 ║ 26     ║ 109     ║ 2       ║ 2.4          ║ 1.2     ║ 0.4 ║ ?               ║ ?               ║ 0.1       ║ 2.5           ║ 0.03  ║ 5.17         ║ 300    ║
║ Jumbo Broccoli Roosjes Vriesvers  ║ Jumbo        ║ Jumbo        ║ NL      ║      1 ║          0 ║ 34     ║ 141     ║ 3.8     ║ 2.7          ║ 2.7     ║ 0.2 ║ ?               ║ ?               ║ 0.1       ║ 3             ║ 0.1   ║ 1.87         ║ 450    ║
║ Jumbo Broccoli Roosjes            ║ Jumbo        ║ Jumbo        ║ NL      ║      1 ║          0 ║ 27     ║ 114     ║ 3       ║ 2            ║ 2       ║ 0   ║ ?               ║ ?               ║ 0         ║ 3.6           ║ 0.1   ║ 1.93         ║ 750    ║
║ Jumbo Broccoliroosjes             ║ Jumbo        ║ Jumbo        ║ NL      ║      0 ║          0 ║ 27     ║ 114     ║ 2.9     ║ 0.8          ║ 0.5     ║ 0.7 ║ ?               ║ ?               ║ 0.1       ║ 3.1           ║ 0.1   ║ 6.14         ║ 350    ║
║ PLUS Broccoli                     ║ PLUS         ║ PLUS         ║ NL      ║      1 ║          0 ║ 27     ║ 113     ║ 3.9     ║ 0.8          ║ 0       ║ 0.3 ║ 0               ║ 0.2             ║ 0.1       ║ 2.7           ║ 0.012 ║ 1.99         ║ 1000   ║
║ PLUS Broccoli                     ║ PLUS         ║ PLUS         ║ NL      ║      1 ║          0 ║ 34     ║ 142     ║ 3.8     ║ 2.7          ║ 2.7     ║ 0.2 ║ 0.03            ║ 0.11            ║ 0.05      ║ 3             ║ 0.06  ║ 2.07         ║ 300    ║
║ Perfekt Broccoli                  ║ Perfekt      ║ Jan Linders  ║ NL      ║      1 ║          0 ║ 34     ║ 142     ║ 3.8     ║ 2.7          ║ 2.7     ║ 0.2 ║ 0.03            ║ 0.11            ║ 0.05      ║ 3             ║ 0.06  ║ 2.77         ║ 300    ║
╚═══════════════════════════════════╩══════════════╩══════════════╩═════════╩════════╩════════════╩════════╩═════════╩═════════╩══════════════╩═════════╩═════╩═════════════════╩═════════════════╩═══════════╩═══════════════╩═══════╩══════════════╩════════╝

Do you have a reliable source for these numbers? Looking around on wikipedia I find numbers between 2,1 (French) and 3,5 (German, raw). Still some difference, but I think this could be caused by different measurement standards, different types of broccoli or  just some error somewhere. I don't expect such a large difference, as the protein in living things is always doing something, no protein no living broccoli.

I added a table based on the data provided by the stores themselves, I will add more later on.

The protein values seem to cluster around 3 gr in your table. The variation looks comparatively small to me and is easily explained by differences in species, natural variability and variation in chemical measurement of the amounts.

@pbond I agree, haven't had the time to check out the German supplies, since I live fairly close to Belgium as well I'm planning on looking into it there too.

Protein levels can vary between species or variety because all it takes is a single gene mutation to cause the plant to produce an entirely new enzyme or some other protein.  It could just be an extra pigment molecule responsible for the increase in protein level.
Also I would assume the amount of nitrogen available in the growing environment would affect the protein content greatly, as all proteins contain this element.  If less is available they can't make as much protein as another plant with a plethora of Nitrogen at its disposal.
Hope this helps :)

I added a table based on the data provided by the stores themselves, I will add more later on.


text:
Nature of transmarginal inhibition
I've recently become aware about existence of such phenomena. From my naive point of view, I understood it as existence of two general types of neural cells, one type serve inhibitory purpose and the other one provide excitation, all of this happens through variation of concentration of different mediators in synaptic connections, right? So in this process (transmarginal inhibition), in a nutshell, provoked by overwhelming stimuli, layer of cells which inhibit inhibitory cell start to show increase of activity and hence inhibitory cells can no longer control activity of currently "excited" cells which result in "paradoxal", reversed behavior. Sorry for this clumsy explanation of how I understood this, please correct my view. If i can abstractly think about evolution of some particular part of biological system as a function which tries to arrive at "local maximum", what type of arrangement of environmental variables could introduce this kind of structure which suffer from such horrible drawback. I mean, there was some input and desired output (adaptation), in result we got construction which could be shut down be intensive external influence and permanently corrupted.

I'm having trouble following the logic of your explanation, can you rewrite, or cite a source? It doesn't look like transmarginal inhibition specifically is a common area of study in neuroscience today, it's an old term from Pavlov. And I'm wondering why you think this is adaptive - most of the references to it are talking about conditions like schizophrenia or post-traumatic stress. Just because a phenomenon is observed in nature doesn't mean it helps survival.

Hello Bryan,  thank you for response, i have a pleasure to attend a lecture related to brain structure in local university, and professor accidentally mention Pavlov and this subject in particular, i reproduce as i remember his explanation. I probably poorly state final part of question, will edit it right now.

I'm not completely convinced that this is a bad trait, because sometimes lack of response can be adaptive (e.g. "playing dead" can be an adaptive response). However, see this question and the answers.


text:
What pattern can be learned from the data of RNA seq counts and HiC matrix?
I now have some data on the RNA seq counts and related Hi-C matrix of gene segment on a chromosome. My concern is, basically, what can we do with these data so as to establish the connection between the two types of data such as the level of expression of gene segment and the interaction of the gene segment, since it seems that they are correlated. Thanks

Maybe start with some tutorials? This one looks interesting: http://www.jove.com/video/1869/hi-c-a-method-to-study-the-three-dimensional-architecture-of-genomes Also, you haven't done any background work for your question, so don't expect substantial answer

You need to be more clear than this. There are many things that you can do with the data. An experiment is performed to test some kind of hypothesis. With just the data and no underlying question you can calculate any thing. It can be even comparison of sequencing fidelities between two kinds of methods. The main point is what are you interested in finding?

This seems to me to be two independent pieces of data. mRNA seq allows one (in case of linear amplification) to quantify message RNA transcripts of genes of interest. that is, how many copies of mRNA for given gene are in the cell at the moment. It is ultimately, how active this gene is. In neurons different genes will be more active, than in epithelial cells, and vice versa. Genetic expression pattern provides identity of the cell.
Hi-C method, closely related to chromosome conformation capture answers question: what genes are physically interact in the nucleus via stabilizing proteins (e.g. enhcancers). There is more in the video, but general idea is that it allows you to see how genes positioned inside intricate chromatin. Since many genetic elements might physically interact via, for example, enhancers, 3C/Hi-C allows detection of such interactions. Or, at least, quantification of correlation between physical positions of two genes.
Now, the only direct connection between mRNA seq and Hi-C that I can draw is following logic: actively transcribed genes are located in expanded, less tense regions of chromatin. Hence, it will be hard to crosslink genes in such regions and correlation going to be low. Silent genes, if they are located closely in nucleus will be cross-linked with high probability, because chromatin is denser around non-transcribed genes.

HiC and 3C (chromosome conformation capture) do not idenify which genes are located nearby in chromosome. These techniques capture long range DNA-DNA interactions such as that between enhancers and promoters. Basically it captures stable DNA loops.

would it be fair to say that such techniques detect physical proximity in chromatin? I understand, that they are not about position along the chromosome

yes they do. In fact trans-DNA regulation has also been studied but these interactions have to be stabilized by some factor which is usually a protein

RNA-Seq lets you measure the steady-state levels of a transcript in a cell or tissue at a specific time-point (averaged over all of the cells that were harvested and lysed).


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What governs the distribution of blood vessels?
Whenever someone is sick, doctor places 2 fingers on wrist & observes the heart-beat-rate by feeling pulses of a certain artery.
To me it seems the distribution of blood vessels are pretty standard across all variations of humans (I mean identical blood vessel positioning seen across Caucasians, Africans, etc. members)
So when someone is born with extra finger or joined skull - which rule/gene/algorithm decides the distribution of network-of-blood-vessels in those special parts?
PS: I am definitely / apparently not a biology student, so pardon my ignorance

Is positioning of blood capillaries random or they too are identically positioned among all humans, although we can't see them.

Like most of human growth, the development of blood vessels (angiogenesis) is fractal or procedural in nature; for the same reason that supranumerary digits (extra fingers or toes) generally still have the shape of a finger or toe, they are likely to have similar vasculature. Capillary growth, while also fractal, is much more "random" in nature, and is driven primarily by the fact that ares of tissue which are low on blood supply stimulate the growth of capillaries towards them in a dynamic process - which is why tumours are generally able to maintain blood supply however large they get.

Damn :) all you people are just so smart... Awe inspiring knowledge, honestly.

The growth of blood vessels is called angiogenesis. This process occures during embrional development, tissue repair, and even tumor formation (in fact this is a crucial step for tumors to survive). This Nature review ("Molecular regulation of angiogenesis and lymphangiogenesis")provides great overview of the process, I'll try and briefly summarize things:
In general large arteries grow circumferential  to keep up with increased blood transfer, while capillaries branch to a more complex network in order to be able to supply blood to every cell. The circulation system starts as a

primitive
  and uniform vascular structures, known as primary capil-
  lary plexi,

that later develop into a hiearchical system of arteries, capillaries and veins. Main regulator of the morphogenesis of blood-vessels is the

vascular endothelial growth factor A (VEGFA; also known as vascular
  permeability factor (VPF)).

This needed for the chemotaxis (the movement of an organism in response to a chemical stimulus. from: http://en.wikipedia.org/wiki/Chemotaxis) and differentiation of endothelial precursor cells (EPCs; angioblasts), endothelial cells (ECs) and the assembly of ECs to vascular structures (termed vasculogenesis), as shown in the figure taken from the article I linked. EPCs themselves differentiate from mesodermal cells during early embryo development and aggregate to form blood islands that later form the  vasculogenic formation of honeycomb-shaped primary capillary plexi.

Also it is important to note that :

alternative splicing of VEGFA can generate several variants of the growth factor, including the so-called b isoforms that differ in the last six C-terminal amino-acid residues and have anti-angiogenic properties. The balance between the different VEGFA isoforms can regulate blood-vessel
  growth and patterning.

Also local composition of extracellular matrix (ECM) and the interaction between ECM and cells can affect angiogenesis. For example release of matrix bound VEGF is important in the regulation of the level of available VEGF. Also:

Furthermore, the physical contact between ECs and pericytes is thought to induce a quiescent, non-sprouting phenotype.

Sprouting itself carried out by the selection of some ECs in the capillary wall to lead the growth of the new sprout. See next figure also from the linked article:

Notch receptors and Delta-like 4 (DLL4) ligands play key role in this process. In tip cell(s) DLL4 expression is induced (in response to VEGFA), while the Notch signaling in neighboring cells (activated by the DLL4) represses sprouting (by down regulating VEGFR2 - VEGF receptor 2) . This is important, because otherwise excess sprouting would lead to a dense network of capillaries and blood would just spread out too thin and would be unable to supply the organs with oxygen and nutrients.
In order to tip ECs be able to grow new capillaries they ahve to undergo some changes. Mobility is most likely gained by activated secreted or cell-surface bound proteases, to locally degrade the basal membrane. Interaction with other ECs have to be changed, without completely disrputing cell-cell junctions and the integrity of the vessel-wall. Also the apical-basal (apical side - faces the lumen of the vessel) polarity of the cells have to be reversed in order to be able to grow outwards (from the basal side of the endothelium. In order for the new capillary vessel to grow, the elongation of the new sprout has to be polarized and directional. This is achieved by spatial concentration gradient of ECM bound VEGFA isoforms along with prominent expression of VEGFR2 in the tips of sprouts.
For blood functional blood vessels to be formed the tips must cease growing and exploratory phenotype when they find their target, and string EC-EC junctions need to be formed. Also the generation of the lumen of the newly formed vessel is required.
As you can see forming of new blood vessels is a complex process that is controlled by local signals, yet it is part of a bigger process - the development of the embryo and organs that is regulated by many many genes and processes. Since our general architecture is the same it is logical that or circulatory system is similar. As for the abnormal structure of a body I think perfusion of that extra body part depends on the local environment.
The review linked at the beginning of this post has extra info on arterio-venosus differention and many other things.


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Binding modes of a protein on a planar surface graphene
Can a protein have different binding modes on a flat even surface like graphene? For a surface like Graphene oxide I can understand, since it has several oxygenated groups on its surface that makes it easier for a protein to have different binding modes, but what for a homogenous aromatic surface like graphene?

What biological significance is the binding of proteins to a substance never found in nature?

Proteins tend to denature on hydrophobic surfaces, which "changes" the binding modes in that it abolishes them completely. I found a study on BSA binding affinity when adsorbed to reduced graphene oxide (rGO), which should have very similar behavior to graphene itself.

The biochemical functionality of adsorbed BSA was investigated through the interaction with its anti-BSA antibody counterpart. BSA on GO can retain its binding sites while, in contrast, a denatured ad-layer of BSA forms on the rGO followed by further binding of active BSA molecules, depending on the concentration of the protein.


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Lipid packing defect
I have been trying to understand the phenomenon of lipid packing defect, but the resources in this subject are very limited. Well, I did find some papers, but before reading papers, I want to have some intuitive knowledge about it. Can anyone explain to me lipid packing defect in brief. Thanks

It really is your responsibility to show the research you have done before posting, give some references to this phenomenon and ask a precise question about what you do not understand. Asking someone to explain the phenomenon — whatever it is — is much too broad for the purposes of this site.

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!

It would help if you could delimit in which cellular of molecular context you would like to understand packing defect, for exemple during vesicular budding or lipid droplet biogenesis.
In the larger context of cellular membranes lipid packing defect occurs when there are transient "holes" made in the phophosolipid bilayer.
These packing defects can be caused by the chemical nature of the phospholipids present in the membrane. A phospholipid is chemically defined as an amphiphilic molecule: it contains a hydrophilic head and an hydrophobic tail.
The head size can vary a lot between the different possibles groups (serine, choline, ethanolamine, etc).
The size of the hydrophobic tail which is composed of long carbon chains can vary in length (typically 16-18 carbon atoms) and saturation. The saturation is very important because insaturated lipids (16:1, 18:1) tends to have to be kinked where the insaturation is.
Thus depending on the lipid composition of the membrane, it is possible to have micro domains (previously named lipid rafts) composed of only a specific lipid or group of lipid with a defined molecular composition. Packaging defects which called be name "holes" or imperfections in the membrane might occur at the boundaries of these microdomains because of the difference of the head size, length of the fatty acid chain, and saturation.
Many people also think that proteins can be responsible for the segregation of chemically defined lipids in the membrane and cause packaging defects for exemple proteins with an hairpin structure instead of a transmembrane domain, or proteins which interact with membranes with an amphipathic helix.
I hope this helps!


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Human bone density and Brown Bear bone density?
It is stated on this website that the density of a Grizzly bear bone is ten times our own. And since I am not into biology at all, I am confused as I don't understand the meaning of bone density here.
I know what the "bone mineral density" term means, and I know it is measured in $g/cm^2$, but there is also the "physical" density term which is the mass by volume and it's measured in $g/cm^3$.
Now, what does it mean when we say that an animal has a bone that is 10 times more dense than ours ? Does it mean that the bone weighs 10 times more for the same size (or volume) ? Or does it mean that it has 10 times the amount of minerals and so it is somehow stronger ?

The word density in the medical term bone density is used to quantify only the mineral content of the bone (bone mineral). It's not intended to describe the total mass density of the bone like we are used to from physics.
This is all on wikipedia: http://en.wikipedia.org/wiki/Bone_density
Thus, when one say that a Grizzly bear have 10 times the bone density, it implies that its bones have 10 times the mineral content compared to humans, and this is indeed seen as a proxy indicator for bone strength. However, this claim does seem unsupported and unrealistic as kmm points out.

I have to think they are using density incorrectly, and since they provide no reference, we really can't check. There is no way that bone density, in the scientific sense, can be 10 times higher in bears. It says "for a given size," which indicates to me that it must mean some kind of skeleton as percentage of body mass. Or it's just made up, with no basis in observation.

@kmm I found some data on the bears here: http://www.asbweb.org/conferences/2006/pdfs/20.pdf, now we just need the same numbers for humans to compare.

And I found a story about a man with a LRP5 mutation that is said to have had eight times the normal bone density, haven't been able to verify though.

The "ash fraction" value is the key here. Bear bone is 66% mineral. Typical human cortical bone is 65-70% mineral. So, no, bears don't have denser bones than humans.

@kmm, may I ask where you got these numbers ?
Also, do different spices have similar "physical" bone densities ? That is, in terms of mass over volume, can an animal have bones that are double or triple the density of ours ?

@kmm you forget to take bone size into consideration, the bone size of a grizzly bear is much larger than ours


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How do male seashorses give birth?
It's a commonly known 'fun fact' that male seahorses are the ones that give birth, but that does not make sense to me. As far as I am aware, the biological definition of male and female relates to their role in reproduction. During the pregnancy a male seahorse has a pouch similar to a uterus and a placenta that contains the embryos, does that not just make it female? How is it still a male seahorse?

Related, possible duplicate: https://biology.stackexchange.com/q/112927/27148

Seahorses are not mammals; only placental mammals have placentas.

https://www.sydney.edu.au/news-opinion/news/2022/09/06/new-research-discovers-the-elaborate-and-unique-way-seahorse-fat.html

If you go on Wikipedia and search for 'female', you will see that the sex defined as female is the one which produces the ovum.
Male seahorses produce sperm cells.
To answer your question in the title, if you search for 'seahorse'on Wikipedia, you will see that the females deposit the eggs in the breeding pouch of the male, who incubates them until they emerge and are released in the water.


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Is this contamination, debris?
I have been culturing SVG cell lines. This line was obtained as a live culture from another institute and was delivered by mail. After subculturing , I saw some particles, and I do not know what they are. The cells are growing well, no debris, no colour change, no foul smell. Can anybody tell me what this is?

Welcome JEME. Could you [edit] to add some details like: 1) The magnification (or at least some idea of scale), 2) Which objects are you referring to, do you mean the crinkled object in the centre of field or something else?

It is an imperfection in your plasticware.
Here's my reasoning:

I've seen similar artefacts 3-4 times in 5 years of culturing mammalian cells and it doesn't move within the media on gentle agitation, indicating that it is fixed in place.
it is extremely bright, and it is a phase contrast image. There's an object there but there is little refraction. I imagine light bouncing around inside a lump of distorted plastic.
the artefact is huge compared to the cells (again with little contrast). I'd be surprised if it was any kind of organic aggregate as suggested in a previous comment.

Is it? Assuming it's the large object in the centre of the view, it looks like it is above the focal plane but still close to focus, which would indicate something other than plasticware - perhaps debris from the plasticware, or something like a protein precipitate from FBS

Anything that you can add to support this or clarify what you mean?

I'm afraid not, but here's my reasoning: 1) I've seen similar artefacts 3-4 times in 5 years of culturing mammalian cells and it doesn't move within the media on gentle agitation, indicating that it is fixed in place. 2) it is extremely bright, and it is a phase contrast image. There's an object there but there is little refraction. I imagine light bouncing around inside a lump of distorted plastic. 3) the artefact is huge  compared to the cells (again with little contrast) . I'd be surprised if it was any kind of organic aggregate as suggested in a previous comment.

@user80053 There's nothing in the question to indicate 1) that it doesn't move, 2) it's a very poorly aligned phase contrast, looks like pseudo-phase by having the light source pointed a little sideways to the condensor. It is very rare to have obvious imperfections to the inside flat surfaces of the flask (and this is definitely inside based on focus), but not uncommon to have protein precipitates from FBS and/or plastic debris inside the flask from manufacture. 20+ years of cell culture tells me this...


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What are these bugs? [Image included]
Around August I started discovering these small critters throughout my apartment. They're around 0.5-1mm long, black with six legs and two stubby antennae. I keep my glasses on the floor by my bed when I sleep and every morning, they're are 5-8 of them crawling over my glasses. The same thing happens with my hat. A number of them have died on the window sill. What are they and what are the best ways of getting rid of them? (More pictures here: https://i.sstatic.net/pu6Bf.jpg)
Thanks!

I hope you have som pictures, it will be very hard otherwise!

I've attached one!

Good! Even though it's really hard to see. Looks like a beetle, at least. Strange that they are attracted to your glasses... Could you also add where you are located?

I'm guessing the glasses attraction is because of dried sweat on the bridge (my hat also has collected sweat over the years, though they favor one particular spot). I added a link to more images -- sorry they aren't high quality, the bugs are so small it's hard to get a good pic!  I'm in Chicago.

one of the picture you're linking to is a lot better than the others, maybe crop that and and add it here? anyway, i'm no expert, but some googling got me these that look kind of similar: http://puredefensepestsolutions.net/pest-solutions/pest-identifier/pantry-pests/merchant-grain-beetle/ but they (and other beetles like flour beetles) would probably prefer your kitchen. hmm...

(i keep commenting as i think of stuff) Do you have any food in your apartment? In that case I recommend that you go check that, in case they are breeding in your flour or something.

I appreciate all your comments and help! The merchant grain beetle does look like the ones I've seen. Most of my food out is dried (ie, pasta, unopened crackers). I haven't seen many bugs in the kitchen though I will be doing a thorough cleaning tonight!

It is one of the pantry pests and most likely a grain beetle. Check all dried foods in your cupboards. You cannot get rid of them until you locate the source


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Did the construction of the Panama Canal lead to a huge change in the local marine ecology?
Before the Panama Canal opened in 1914, its two ends were only 77 km apart over land, but the closest sea route was 32,000 km long (around the entirety of South America) and passed through much colder waters near Cape Horn. Therefore, I suspect that the Atlantic and Pacific marine ecosystems were more or less completely isolated from each other and contained very different species before the Canal opened. It also seems plausible that once the canal opened and a 77-km marine route opened up, these two ecosystems very quickly came into contact and may have reached a new, drastically different equilibrium. Is this correct? I could imagine the ecological effects being equivalent to the sudden creation of a 77-km bridge connecting the ecosystems of, say, the United States and Kenya.

This book answers your question pretty well. I was going to put together an answer based on it and other papers I found, but suddenly lost the will to.

Many organisms are transported across the channel by ships, as hull fouling or in ballast tanks (which bypasses the salinity barrier of Lake Gatun). The book mentions that oil tankers routinely dump tens of thousands of tons of ballast water from the Caribbean into ports in Alaska.

Water treatment is performed in onshore facilities by US and some other countries. But the open ocean and many other countries have no requirements.

The panama canal is not just a long contiguous connection between the two oceans as you might think. It operates under a system of locks of varying height because the surrounding region is actually fairly mountainous, so a ship has to enter a lock, let it fill until equilibration with the next lock whilst the boat rises, the barriers open, the boat moves into the next section and the process repeats. It is fairly unlikely much wildlife would be able to pass through this system thus not causing the vast ecological effects you might imagine. https://www.youtube.com/watch?v=hoQ7RHyG-EA this link visualises it for you :)

It doesn't seem unreasonable, to me, that at least some marine life could pass through the locks with ships.

Also, IIRC the canal and locks are fresh water, so it doesn't seem likely that most marine organisms could survive a passage.

I agree with @canadianer. It often takes surprisingly few members of an invasive species to completely change an ecosystem, since none of the original organisms have evolved to resist it from taking over. And if there have been 10 million lock cycles, then quite a few organisms could have passed through even if most cycles don't transfer any organisms.


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Can "red" cone cells actually see much red light?
In electronics, the most common color scheme is the "red-green-blue" (RGB) scheme.  This choice is often justified by claiming that the long-  (L), medium-  (M), and short- (S) type cones in the human eye are most sensitive to red, green, and blue light respectively.  But this seems clearly wrong if you look at the actual normalized frequency receptivity spectra for the three types of cone cells:

It's clear that the L-type cones are actually most sensitive to yellow-green light and are actually relatively insensitive to red light. (Presumably the brain distinguishes between yellow, orange, and red light by the rapidly decreasing ratios of M-type to L-type signal.)
My question is threefold:
(1) The L-type cones are usually called "red" cones.  Is this simply incorrect, or is there some justification for this name that I can't see from the receptivity spectra?
(2) Does the RGB color scheme give a better color range than, say, a "yellow-green-blue" scheme (which would more closely correspond to the actual cone sensitivities) simply because red is at one end of the visible spectrum, so you can more easily get a wide color range?
(3) If this is the case, do we not use a "red-green-violet" color scheme (which would give an even wider color range) simply because the human eye is so much more sensitive to blue than to violet light?

The same question can be asked about the color filter arrays in front of digital camera sensors. Though the "red" filter is usually most transmissive to light at around 595-600 nm (and thus "red" filtered pixels are most sensitive at 595-600 nm), every drawing you see of them anywhere, even in highly technical scientific papers, illustrates them with 640 nm "Red". Why are Red, Green, and Blue the primary colors of light?

This is a good question. The first  thing to note is that human colour vision is very complex and still poorly understood. If you visit the wikipedia page on RGB,  you will find that this correctly mentions that the S, M and L cones are most responsive to violet, green and yellow wavelengths respectively (which answers your first question - calling the cones red, green and blue is primarily for historical reasons, because there aren't any real wavelengths that only activate a single cone, it's hard to say what colour a cone 'is'). So why do we use red, green and blue phosphors? A practical answer can be found by looking at the CIE 1931 colour space: this was essentially an attempt to find how one could add together different amounts of a small number of wavelengths to make the result indistinguishable from any desired wavelength (read the linked page if you want more information, also have a look here). The result found was that the colour matching functions should look like the following graph (what this is showing is how much of a red, green and blue light are required to simulate a wavelength):

You can see that this is similar to the responses of the cones except for the peak in the red (which corresponds to violet looking like red-blue):

To answer the question in your title, red cells do see the most red light of any cone, but that is not where they see the most light. Here is an example set of spectra of the red, green and blue phosphors in a CRT:

To answer your question about why we use red, green and blue in the first place (rather than yellow-green-blue or red-green-violet), it's good to understand why the CIE 1931 functions are that shape in the first place. The wikipedia RGB page mentions that:

...good primaries are stimuli that maximize the difference between the responses of the cone cells of the human retina to light of different wavelengths, and that thereby make a large color triangle.

This gets at the fundamental reason, which is that it is generally believed that we do not perceive colours in terms of the activities of each cone, but in terms of the differences between those signals (as it says here), an opponent process. The following image illustrates a simplified version of how the opponent signals in colour vision processing are thought to function, so that the resulting signals are a black-white, a yellow-blue and a red-green axis:

This image shows the theorized shapes of the response curves of these opponent functions (see here for an interesting historical paper on this theory and here for more details and some predictions of the theory):

It is possibly apparent from the last graph why the CIE 1931 colour graph is the shape that it is, since we see red as a bimodal distribution with a distribution of green in between, and a large distribution of blue at short wavelengths and yellow is red + green. (Incidentally this also explains why we also perceive yellow as a primary colour - see the 4 highlighted points R, Y, G and B where one curve passes through 0). Additional information on the neurological and psychological correlates of colour vision can be found here and here and more technical theoretical details here.
The upshot of all of this is that red, green and blue are the best 3 colours to use as the basis for additive colour mixing, but not because they are what L, M and S cones are most sensitive to. Rather it is because it has been shown that these particular colours fall where there is maximal difference between the cone signals and because they can accurately represent all of the colours in our colour space as illustrated by CIE 1931 (due to being widely spaced and all perceived easily as you have mentioned in points 2 and 3 of your question). Effectively, the reasons are complicated and to do with the neurological processing of the colour signals and the differences between the signals rather than the straightforward signals themselves.

I think it is pretty interesting. What I thought what was most interesting about it was the way it explains why we see yellow as a primary colour too (where the curves cross zero).

Approaching this as a knowledgeable artist and designer who also understands about trichromatic colour vision, I see that the answer above is a good one - but scientists often have an overly complex way of explaining things. I would have put it in the following terms. As the first graph above shows, most wavelengths stimulate two or three of our cones to some degree. As the scientific answer above says, the best primary colours are those that give the greatest colour separation/distinction. Therefore, it makes sense to take the first primary as RED, defined as the colour that can ONLY be seen by the red cone (the blue and green cones are insensitive at the longwave end of the visible spectrum); as seen in the second diagram, this is from 650 nm upwards. It also makes sense to take the second primary as BLUE/VIOLET, defined as the colour that can ONLY be seen by the blue/violet cone, which occurs at the shortwave end of the spectrum, around 400 nm. Finally, you need to choose GREEN, which is the colour that, by definition, is NEITHER blue/violet NOR red (neither of which contain green) - the middle colour. Note that although red has no green, green does contain red, as we perceive it with both the green (M) and red (L) cones. The above three choices give the best separation. Green is at its most distinctive at about 546 nm where the blue cone loses most of its sensitivity.
My final point is about violet. Colour theories always assert that 1) violet is the same as indigo or dark blue, and 2) purple is not violet and is not in the spectrum (a 'fact' shown in the CIE chart). My eyes tell me that both these assertions are untrue. The colour violet is, to my eyes, a bright vibrant hue that many people also refer to as 'purple' and which patently IS in the spectrum; I see it in every rainbow. It is clear to me that I, along with all the other people who see colour as I do, perceive more sensitively at the shortwave end of the spectrum than the textbooks would have us believe.
I have been doing research on this for some years, which I hope eventually to publish, but I conjecture this is a side effect of being a carrier of the gene for deuteranomaly (a type of R-G colourblindness) which applies only to women (hence the fact it tends to be women who get enthusiastic about bright violets and magentas).
So in my opinion (and according to my ongoing researches), the correct primary colours are RGV - red, green and violet.
The deuteranomaly gene has also been found, in one case, to confer perception of a fourth primary colour in the yellow-orange area of the spectrum (Study by Jordan, Deeb, Bosten and Mollon, 2010; https://doi.org/10.1167/10.8.12) so it could be that for some carriers of deuteranomaly the primary colours are actually RYGV and this is a further theme of my research. Please contact me if you want to work with me on it - rahbeckett@gmail.com.

Welcome Rachel. Please take our [tour] and refer to the [help] for guidance. Could we prevail on you to [edit] some paragraphs into your post, at present it's a bit of an unreadable wall-of-text. Anyhow, enjoy the site.

In regards to your comments about violet - the fundamental difference between violet and purple is that the former is a spectral colour, which can be elicited by monochromatic light, whereas purple usually refers to mixtures of red and blue. Thus any 'violet' displayed by a computer screen is technically a purple. The generally accepted reason for this is the slightly increased differential activation of the 'red' cones by short-wavelength light. Nevertheless you are right that perceptually they may be indistinguishable in some cases.

Also, as I mentioned in my answer, the fact that we perceive yellow as a fourth perceptual primary colour (along with red, green, and blue) is explained by the opponent process colour theory.


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Why do some white blood cells have lobed nuclei?
Several types of white blood cells (eg Neutrophils) have lobed nuclei.  Is this for a functional reason?  I have seen people refer to structural differences in the lobes as indicative of problems, but I have not been able to find why the nuclei form into lobes in the first place.  Is this known?

The Neutrophil Nucleus and Its Role in Neutrophilic Function is the most recent review article I could find, but you'll need institutional access. Basically there's still not a lot of consensus and this is an active field of research. A big reason that stands out is the need to migrate through tissues, and  the lobular nucleus may assist there.

Thanks!  I do have an academic affiliation, so I will check out the article.  Thanks for tracking it down!

@Kendall for those without access to the review, could you summarize it as an answer?

I am not sure if this is why their nuclei are the way they are, but this may be one of the coolest functions of the immune cells. Extracellular traps are associated with human and mouse neutrophil and macrophage mediated killing of larval Strongyloides stercoralis Bonne-Année et. al. Basically Neutrophils are capable of using their chromatin to set extracellular traps for large pathogens such as nematodes that are too big to phagocytose. They die as a result , but the are able to "chuck out" their DNA at the worm.


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Unmyelinated long axons in the sympathetic nervous system
I was recently looking over some textbook material (pdf) which claimed post-ganglionic fibers of the sympathetic nervous system are unmyelinated.  This was surprising to me, since I had previously thought that long distance transmission of an action potential required myelin (I can even remember being told that myelin was essential for large life forms, because the nerves otherwise could not have controlled distant body parts).
First, is the textbook correct?  Second, assuming it is true that post-ganglionic fibers are not myelinated, is there some advantage to this arrangement?  At the very least, I would think it would be far more energetic to send a signal in a unmyelinated axon.


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Reading and Understanding profile bands in DNA Fingerprinting
I have very limited knowledge when it comes to DNA fingerprinting. I know about the technique gel electrophoresis and how everything is carried out. But I don't know how to read the result or understand that. Can anyone please explain me how to read the result  [profile of bands]?
Because of my lack of knowledge, I can't solve problems like this one.
Please explain me using this one so that I can get a clear idea about DNA profiling. This seems like home-work problem but the thing is I want to understand the technique of restriction mapping by reading the result of restriction digestion on electrophoresis and my intention is to understand the topic. Please Help.

And I can't describe how I tried to solve this question because I don't have any kind of knowledge about this technique [Restriction Mapping] so my efforts are very silly to mention and I have improper way of approach to this as I don't know how to do the Restriction Mapping.
But I am given the answer which I tried to make sense by working on it but I just couldn't help it. It seems easy after seeing the Map but I don't get the relation between the profile of bands and the Map so if I am given a different problem I will fail to come up with a reasonable answer.

What I am trying to say is, by seeing this map and working on it I get to agree that this is the correct mapping for the data given but I have some doubts, like, why we keep 3Kb distance between BamHI and EcoRI sites. Working out in some another way will end up with wrong answer. How these inticacies are understood? By reading the profile of bands [data given] right? So that's what I am asking for you to explain to me. I don't know anything about it.
Thank you always.

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@MattDMo I would let this question go. As you can see from my description of how to go from the gels to a restriction maps, these types of HW are extremely difficult if you don't have a really good handle on what you are doing.

@AliceD I remember getting this pretty easily in school and then I would have a line of my classmates asking me to explain how to solve these. These are not trivial problems and they are not something that you can look up, and unless can work it out, it is very easy not to even know where to begin. I would cut the OP some slack. This is probably one of the harder Molecular Bio questions that can be asked at the undergraduate level.

@AMR, after edits this question is great. No worries. I retracted my vote and +1'd

The answer below should give you the logic behind how to work through these problems and answer the questions. I edited it to try and be as complete as possible as to how I thought through the solution and the steps you should take to determine the plasmid map from the restriction digest. These are very difficult questions, the best thing to do is to practice them, and they will become easier to solve.

How you would determine the plasmid map from just the restriction digest data
The thought process behind doing this is a bit involved.

From the question you are told that the Gene is 8kb and does not contain an EcoRI site inside of the gene

I say not inside because the ends of the gene were made with EcoRI cuts, but digesting in EcoRI will only produce the 8kb fragment of the gene

The vector is 6kb and you know that they have EcoRI sites at either end, but you are not told what other cut sites there are.
When you digest the plasmid in BamHI you get 3 fragments, meaning that your plasmid has 3 BamHI sites somewhere in it.
You know that your total plasmid size is 14kb (easiest way to know is just look and see that they tell you that there is an 8kb gene and a 6kb vector). Looking at the Double Restriction Digest, you can see that the five fragments add up to 14kb, which implies that there are only one of each fragment in the plasmid, and they are produced by 5 separate cuts.

This is an important piece of information because this tells you that you do not have 2 fragments of the same size making up different parts of the plasmid.
Remember that when you do a restriction digest on a circular piece of DNA, the number of fragment you get equals the number of cuts (restriction sites) in the plasmid. So because there were 5 fragments, you have 5 separate restriction sites
From the Double Digest data, you also know that the smallest fragment of DNA that you have is 1kb and the largest is 4kb.

Since the 4kb site is common to both the BamHI only and the the Double Digest, as since you do not have a 0.5kb or 1.5kb fragment (the remainders if the Double Digest 4kb fragment had been produced from the 4.5kb or 5.5kb fragments in the BamHI digest) in the Double Digest, you know that the 4kb fragment is the same in both the BamHI digest and the Double Digest, and is produced by 2 BamHI cuts.

You can now work on roughly placing where the 4kb fragment should be in the map.
If you try to place that 4kb fragment in the vector, then you would either generate a 2kb fragment, or something less than 2kb and a very small fragment.
Since you do not have a 2kb fragment or fragments smaller than 1kb, you know that it cannot be in the vector region. Also in order to get a 2kb fragment from the 6kb vector the 4kb fragment would have needed to be cut once with EcoRI and from the description, above, we worked out that the 4kb fragment is produced by two BamHI cuts
It could have been that the vector was 1kb + 4kb + 1kb, however from point 4 you determined that you only had one of each fragment, so you can't have two 1kb fragments.

All of that tells you that it has to be in the 8kb gene portion, though you need some more information to determine exactly where.

Remember that you do know that the 4kb fragment was produced by 2 BamHI cuts, which means that it cannot be at the very end of the gene region, as that would require it to be cut once with EcoRI
This also tells you that you have at least two BamHI cut sights in the gene.

What I would do here is draw two circles, the first having an 8kb arc and a 6kb arc, then draw second circle and make three cuts in it.

From 6 we worked out that the 4kb piece will overlap somewhere in the 8kb area, that it cannot be at an end and that there need to be 2 BamHI restriction sites within the gene.
You also have to consider the 4.5kb and 5.5kb parts from the BamHI digest. Since 4kb plus either of those two are greater than 8kb, then you know that the cut that separates 4.5kb from 5.5kb will be somewhere in the 6kb vector. This is how you know that the third BamHI site is in the vector.

Now that you have determine that the 4kb fragment is in the gene you can start to work out the other pieces.
You had 2 fragments from the BamHI digest that were 5.5kb and 4.5kb and in the double digest you have fragments that are 1.0kb, 2.5kb, 3.0kb, and 3.5kb.

Since you have already determine that that 4kb piece is the same for both digests, then at this point you can tell yourself that the 1.0kb and 3.5kb fragments made up the 4.5kb fragments and the 2.5kb and 3.0kb fragments made up the 5.5kb fragment.

Since you know that there has to be two EcoRI cuts that make the 6kb fragment, you are going to need two fragments that add up to 6kb.

The only way to get this with the four fragments that you have from the double digest is with the 2.5kb piece and the 3.5 kb piece.
So you have now determined the exact position of one of the BamHI cut sites. It is in the Vector, 2.5kb from one of the EcoRI sites and 3.5kb from the other EcoRI sites.

Now that you determined where one of the sites is, you know that the 2.5kb fragment was paired with the 3.0kb fragment, so this tells you that there is a BamHI site 3kb away from the EcoRI site in the Gene.
From there you can connect the 4.0kb piece to the end of the 3.0kb piece because you know that the 3.5kb piece has to be attached to the 1kb piece and cannot be attached to the 3kb piece.
All that is left is to close the circle. You know that you have 1.0kb more of the gene that needs to be place and this will connect the 7.0kb that you determine of the gene in step 11 to the 3.5kb fragment in the vector. You have that 1.0kb fragment, and that is the one.

So that is how you determine how to construct the plasmid map from the restriction digests.
What the distances between the cut sites tell you
The cut sites are determined by the sequence of the DNA that the Restriction Enzyme recognizes.

EcoRI recognizes GAATTC
BamHI recognizes GGATCC

You will notice that these are palindromic sequences, so 5'-GAATTC-3' is 3'-CTTAAG-5' on the complimentary strand.
All that the distances are telling you is that in the areas in between the cut sites, the sequences GAATTC and GGATCC do not appear. If they did, then the Restriction Endonuclease would recognize that position and cut the DNA, and you would have an additional cut site at that location.
Assuming that you were given the plasmid map, this should be the answer.
The answer should be C. The 1kb and 3kb fragments are the DNA fragments from the gene that are generated from the EcoRI / BamHI digest. So one end of the fragment was produced with EcoRI and the other end of the fragment was produced with BamHI
The 4kb fragment is the result of BamHI restriction alone. So both ends of the fragment were produced by BamHI so it cannot be the answer to a fragment produced by EcoRI / BamHI restriction.
If they are saying that they also want answer A as well, then their question is very poorly worded, in my opinion.

The short answer:
After the Eco digest, you have two pieces, (which means a single cut) one 6 kb which is all vector, one 8 kb, which is all gene.  Then you digest those with another enzyme, but the pieces that came from the vector should add up to 6, and the pieces that came from the gene should add up to 8.  The 2.5 and 3.5 long pieces must be the cut up vector, the rest must be the cut up gene.  There is no other way to group pieces of those lengths into 6 kb and 8 kb parent fragments.
To find the order of them all:
Basically, you have the 5 smaller fragments, and you want to put them in the right linear order, like this:
enzyme - DNA of some size - enzyme - DNA of some size - enzyme ...etc.
We know that there is 6 kb Eco RI fragment, and THEN we cut with Bam, so there have to be Bam fragments that add up to 6, and the rest will add up to 8.  In this set that HAS to be the 3.5 and 2.5 which are part of the 6kb fragment that you get when cutting with Eco alone.  So we know part of the sequence :
Eco - 2.5 kb - Bam - 3.5 kb - Eco - ??? Bam ??? Bam ??? Eco
Since there are only two, order doesn't matter.
Now, if the 4.0 kb fragment was adjacent to the 3.5 kb fragment, the result of cutting that with Bam alone would be 7 kb.  There is no fragment that size, so that's not right.  Same with the 3.0 kb fragment.  So, it must be the 1.0 kb fragment, because that would yield the 4.5 kb fragment that we do see.
Eco - 2.5 kb - Bam - 3.5 - Eco - 1.0 - Bam ??? Bam ??? Eco
Again, if the 4.0 were adjacent to the 2.5 kb fragment, the Bam alone digest would have a 6.5 kb fragment, which it doesn't.  So the 4.0 fragment must be in the middle, with the 3.0 fragment adjacent to the 2.5 fragment, which yields the 5.5 kb digestion Bam alone digestion product that we observe.
Eco - 2.5 kb - Bam - 3.5 kb - Eco - 1.0 kb - Bam - 4.0 kb - Bam - 3.0 kb - Eco

You cannot assume the 2.5 and 3.5kb fragments make up the 6kb fragment right away. You have to get to it by a process of elimination that rules out the 4kb and 2 X 1kb fragments from being a possibility.

We know the whole vector is 14 kb.  We know the 5 fragments visible add up to 14.  Therefore, there is only one fragment of each size.

Your answer makes the point without explaining how you get there. You can't make the assumption without ruling out the 4kb and 1kb two times first. You did that as a matter of course, because you are familiar with how to do it. Someone who doesn't understand needs that explained to them. You also don't mention that there are 5 fragments that add up to 14kb in the initial part of your answer and you can't assume that the OP will have picked up on that or understand the significance.

The other answer already existed when I wrote mine, and it lays out why each band must represent only a single fragment of that size.


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How many possible human genotypes are there that produce distinct phenotypes?
This and this Quora question ask how many unique human genotypes are possible. The answers take the combinatorial approach of raising the 4 possible base pairs to a power which is some appreciable fraction of the 3 billion base pairs in the human genome, to get absurdly large numbers like $10^\text{many millions}$. But as many of the answers point out, this is a gigantic overestimate, because the vast majority of those gene sequences wouldn't produce anything remotely resembling a human, and even among the tiny fraction that do, there are enormous numbers of sequences that produce phenotypically identical humans (after all, most mutations don't produce any detectable effect). (When I say that two genomes "produce indistinguishable phenotypes," I am holding the environment fixed and only considering the genome's contribution to the phenotype.)
It seems to me that in order to avoid counting non-human genomes or double-counting phenotypically equivalent genomes, the better approach is use genes rather than base pairs as the combinatorial building blocks. The human genome has at most 20,000 protein-coding genes, and apparently most genes have two alleles, although some have only one and others have more than two. (I'm defining an allele as an equivalence class of phenotypically indistinguishable DNA sequences that form a single viable gene. For the purpose of this calculation, we can mentally group together the two chromosomes' versions of the same gene, and increase our allele count to include any interactions between the two chromosomes' sequences.) [Edit: according to the answer below (which I find much more trustworthy than this Quora link), this is a huge underestimate for the typical number of alleles per gene, with a better estimate being ~300. Needless to say, this dramatically changes the final answer.] This would produce a maximum of $2^{20000} \approx 10^{6020}$ possible phenotypically distinguishable genomes. While this is obviously still an astronomically high number, it's an infinitesimally tiny fraction of the estimates produced in the Quora answers.
Is my reasoning correct?

When you're looking for specific estimates in biology (such as e.g. the number of coding sequences in the human genome), I recommend starting with the website bionumbers rather than Quora or wikipedia.

Is my reasoning correct?

I can see at least five major problems in your reasoning.
Do most genes have two alleles?
The claim that most genes have two alleles is wrong. Actually, the entire top answer in the linked quora post is wrong. The person answering confounds simplified cases used to teach intro genetics class with what nature really looks like.
As about one every 100 nucleotides is a SNP (bionumbers) and given that a gene is on average about 30k sites (bionumbers), the average number of alleles is probably closer to 300 although that would be counting synonymous mutations which is a bit unfair. About 20% of substitutions are synonymous (bionumbers), which would lead to an estimate of 240 alleles per gene on average. Even if you consider that 90% of these mutations have no effect on the phenotype (which is maybe an overestimation, bionumbers), you're left with 24 alleles per gene. Of course, this is a very vague estimate but it is, I think, much better than 2.
Non-coding sequences
Also, the majority of phenotypic distinction is caused by non-coding (non - gene) sequences such as regulatory sequences. You cannot ignore them in the calculation.
According to this pie chart (not sure if we can trust this chart though), 5% of the genome is made of regulatory sequences (against 1.5% of the genome that is coding).
One genotype ≠ one phenotype
If you have in mind that one genotype = one phenotype, then it would be very wrong too. There is environmental variance, epigenetic variance and other sources of variance (e.g. developmental noise) that underly phenotypic variance (see this post to understand the sources of phenotypic variance in populations).
indels and CNV
You are only considering substitutions. There are plenty of indels and ohter CNV too.
The existence of this variation does not only complicate the question, it actually renders the question a bit undefined because if you allow the genome to take any size, then number of possibilities is necessarily infinite.
Diploidy
Your calculations assume individuals are haploids. But humans are diplontic.
Gene are not atomic
Genes are not units that cannot be split. Recombination do happen in genes and it would be wrong to take the number of variants at genes (or at any other type of sequences) as basis for your calculation
Attempt at a calculation
So, ignoring many of the problems, here is my attempt at a calculation.
There are about $1.5 \cdot 10^7$ SNPs in the human genome (bionumbers). Based on this pie chart (not sure if we can trust this chart though), I will assume that about 6.5% of them are in coding or regulatory regions and I will assume (based on that paper) that 90% of them have no fitness effect and by extension I will assume it also mean no phenotypic effect (although the actually percentage should been increased). This will result in $1.5 \cdot 10^7 \cdot 0.065 \cdot 0.1 = 97500$  SNPs of interest. It results into $2^{97500} ≈ 10^{32500}$ possible haplotypes of interest. The number of possible genotypes of interest is therefore $\left(10^{32500}\right)^2 = 10^{65000}$. I also assumed absence of epistatic interactions otherwise the number would become so fantastically closer to infinity!
Interest in the calculation
I fail to find much interest in making such calculation because it entirely depends upon the model we want to consider. There is no offense against the OP's question here (and in fact the OP shows that he understands the importance of the considered model), I just want to make sure readers understand that these calculations are based on a very arbitrary model and one cannot make any sense of the given result without understanding the model.
The calculations from the Quora post that OP linked assumes that every SNP could be polymorphic. As long as the intention behind the calculation is not clearly stated, this is a perfectly reasonable model. Here, in my attempt, I assume that the number of SNPs is fixed, but any combination of it is possible. This can or cannot be a fine assumptions. Also, the estimates of the number of SNPs are of course, estimates of the number of SNPs that are at a frequency that is not too low to be detected! So, if we were, for some reason, to consider all the SNPs (by assuming some drift-mutation equilibrium), then the result would differ quite a bit. But again, it all depends upon the specific model one wants to consider.

Thank you for the thorough answer. I completely agree that the question is ill-defined and any numerical answer is pretty much meaningless. My motivation for asking the question was simply to verify that a naive calculation based solely on the number of base pairs in the genome is even more meaningless and arbitrary, and gives enormous overestimates compared to any possible even vaguely reasonable model.

i actually would also agree with @Remi.b the number of phenotypes would include all the possible physical behaviors, appearances and other properties of a living thing.  since most phenotypes are the result of combinations of genotypes in unpredictable and nonlinear ways, with continuous (as opposed to 0/1) sorts of behaviors - the number of possible phenotypes are incalculable.

@tparker "My motivation for asking the question was simply to verify that a naive calculation based solely on the number of base pairs in the genome is even more meaningless and arbitrary" One additional thing to think about here is the actual number of people, somewhere around 10^10 or 10^11 depending on how many generations you want to consider. In that context, the distinction between 10^65000 and 10^6000 is not really all that important, either, from a sampling perspective. The distinction is going to be more important if you think about more numerous organisms with smaller genomes.


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How many times have the cells in a human body divided?
Every single cell in a multicellular organism can in principle trace its "ancestry" back to the zygote through a continuous chain of cell divisions. How many divisions have occurred in a typical cell in an adult human body since the zygote was fertilized?
Obviously the answer depends on the organism's age and on the type of cell (as different types of cells divide at different rates). To be concrete, what is the average number of cell generations from the zygote across all the cells in, say, a typical 25-year-old human?
(Or any other age, if that's more convenient to estimate. I'd also be curious about the approximate minimum and maximum number of divisions, and which types of cells they occur in. If it's too difficult to estimate these statistics over the whole organism, I'd be interested to know if there are any specific types of specialized cells for which it's possible to estimate the "generation number".)
To be clear, I'm not asking about the maximum number of times that a cell can divide. I'm asking about the average number of times it has divided at a given point in time.

As a starting point for further exploration, Fig. 1 of this paper shows an association between different cancer types and the lifetime total divisions for the stem cell subtypes from which those cancers are derived.  The authors give their derivations of the replication rates for each subtype in the supplement (PDF download).

What type of cell?  For instance, AFAIK red blood cells don't divide at all, they are produced by other cells in the bone marrow.  I would expect the same is true of other kinds of cells, such as sperm cells.

What research have you done on the subject? this is something you could google.

E[MAX(X(t))] of the sampling distribution is the not the same as the largest value in the support for X(t)'s distribution function. It is a sensible to similarly wonder about the maximum number of times it has divided at a given time point $t$.

The supplemental material of the paper that Dirigible references in a comment to my question gives a rough estimate of these values. If I understand their simple model correctly, then we can estimate the average number of times that the stem cells in various types of tissues have divided over an 80-year lifespan from Table S.1 by finding the row corresponding to a cancer of that tissue, and then calculating $\log_2(s) + d$, where $s$ and $d$ are given in the table. (For specialized cells, I guess you'd add 1 more to capture the final cell division that produces the specialized cell?)
I haven't done the math out, but glancing over the table, it looks like the generation number varies widely between tissues, from a low of about 27 for some brain cells to a high of almost 6000 for cells in the colon and rectum.

Please [edit] your post to include the actual citation of the paper. It's not clear what paper you are referencing. Thanks

@theforestecologist - The paper is Variation in cancer risk among tissues can be explained by the number of stem cell divisions. The supplementary material is found by clicking on the link near the end of the article.

The supplementary material says epidermal stem cells divide about every $48$ days, typical stem cells divide about every $5$ days, oral mucosa stem cells divide every $14$ to $20$ days, etc. Some cells seldom divide. Carcinoma cells tend to divide much more frequently than average cells.


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Any latest edition or successor of "Invertebrate zoology" by Ruppert & Barnes 2003?
I have the 6th edition of the textbook "Invertebrate Zoology" by Ruppert and Barnes from 1993. I know there is a 7th edition from 2003, but is there and will there ever be a 8th edition? Assuming they should come every 10 years, shouldn't there have been one in 2013? So if Ruppert & Barnes retired, is there any more recent successor or alternative?

BTW Barnes is listed as 1 of the authors for the 2003 edition as well.

Thanks! I would still like to know whether there is a more recent alternative.

Found it! I created my own answer.

A worthy successor to this book series is "Invertebrates" by Richard C. Brusca et al. The latest edition being from 2016, so exactly what I was looking for.
https://www.amazon.com/gp/product/1605353752/ref=pe_353720_261047730_em_sp_C_1p_1_ti

I studied invertebrate zoology using Barne's book, and I was reluctant to buy a book different from the classic one. I checked comments on the Brusca's book, and I was surprised that all of them are good ones (5 stars). It seems it's a better alternative to Barnes' book (7th edition 2003), as the last edition (3rd) was published in 2016 and includes the recent taxonomical reviews (e.g. new phyla, merged ones, etc.). I'm considering buying this; the price is quite reasonable compared to the other one.


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Why was it initially thought that Mendel's findings were contradictory to Darwin's natural selection?
When I read about the modern evolutionary synthesis, the text said that it showed both ideas to be compatible, once thought to be contradictory. Would it be because Mendel described an element of "randomness" in character transmission, as opposed to the mechanism of natural selection originally described by Darwin, or is it something else? I do not yet have a big knowledge on evolution, so pardon any mistakes.

Welcome to Biology.SE. Can you please link to the article you are referring and indicate where it says that " both ideas to be compatible, once thought to be contradictory"?

Thank you. Sorry, I guess article was a poor choice of words, I've changed it now. It was a college text I've read in portuguese, in case you understand: http://aprender.ead.unb.br/pluginfile.php/23405/mod_resource/content/2/A_Sintese_Moderna_Ridley.pdf

It's thought that Mendel's communications were anti-Darwinist, and some argue that his original paper was written specifically as a refutation of Darwin's descent with modification. Mendel believed species were created by God and not Darwinian evolution. Because of this, when he found a law defining constant probabilities of heredity, he saw it as more of an argument for the consitency of genetic information and thus species. To him this was in contrast to the ability of heritable traits to vary slightly in progeny, leading to selective advantages. Source I paraphrased: http://jhered.oxfordjournals.org/content/87/3/205.full.pdf


text:
Formulation of Biomass reaction for metabolic model
What are some good review articles that could help me develop basic knowledge regarding biomass equation formulation?
I read this paper titled biomass objective function, but it only gives a general idea, and I'd like to learn more about the specifics of the process.

Please have a look at the tag wiki for reference-request. Your question should have all the details outlined in there. There is a book called Metabolic Engineering by Stephanopaulos et al.. That should give you some basic knowledge.

What precisely do you want to know? Are you interested in biomass composition for a particular cell type / experiment, or in the math involved? The paper you cite provides a good starting point for biotechnology applications I think. But for most organisms, there is little experimental data available on biomass composition.


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How much tissue is required to do RNA-seq analysis on a single organism?
How much tissue would be required to do RNA-seq analysis on a single organism?
More specifically, if a person wanted an RNA-seq analysis of expression for a single organ, how much tissue would they need to donate?

Depends on a lot of parameters? Can you add some more details?

Our DNA core wants 1.5 ug of RNA.  I find that I can obtain that amount from a standard Trizol prep from about 1 mg of Arabidopsis floral tissue.  I usually double or triple what I harvest to account for random variation in yield.

Any sources to add? +1 for this contribution and welcome 2 Bio

ThermoFisher has literally everything in tabular format. As a side note I'd also peg an A260/A280 > 1.8 as equally important as yield for best results.

http://healthcare.utah.edu/huntsmancancerinstitute/research/shared-resources/center-managed/high-throughput-genomics-site/services/illumina-sequencing/rna-sequencing.php

The Illumina TruSeq RNA Sample Prep Kit v2 with oligo(dT) selection
  recommends an input of 100 to 1000 ng of total RNA in a volume of 30
  ul for library construction.
The Epicentre TotalScript RNA-Seq Kit (Epicentre cat# TSRNA1296) is
  designed for an input of 1-5 ng of total RNA in a volume of 12 ul to a
  RNA sequencing library.

Whether you will get a complete picture of a whole organ from such a small slice is an entirely different question.  The brain has different regions, with different gene expression.


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What kind of (cinnamon?) tree is this?
This tree was found in the rainforest on subtropical Japanese islands. At first I thought that it was a camphor tree, which are indeed common in Japan. However, the leaves are slightly different and elongated, and the fruit  has a sharp tip and is much larger than that of camphor trees. The bark is very aromatic and smells like good cinnamon, perhaps a bit peppery. Any ideas?

It has 250 species!

This is the Japanese cinnamon, Cinnamomum tenuifolium, or "Yabu Nikkei" in Japanese. It smells like cinnamon and is found from the middle of Honshu (Fukushima prefecture and southward) throughout Shikoku, Kyushu, Okinawa, and into China. It is the native and more commonly found cinnamon species in Japan that grows wild in forests. The other species is Cinnamomum sieboldi, which was introduced to Japan in the early 18th century from its native Indochina via China. C. tenuifolium is distinguishable from C. sieboldi by its much more symmetrical arrangement of leaves, as depicted in your photograph.
This page also details the differences and similarities to other related species in Japan, however it is only in Japanese:
Camphor/Cinnamon species in Japan.