The question is probably more complicated than it seems because, if I am not wrong, the word adaptation here is understood at the group level.

Definitions of adaptation

Unfortunately, there is not such thing as a single, standard definition of adaptation. But for most cases the accurate definition the author is using is not of much importance as all of the usual definitions totally fit in the sentence without changing the meaning of the concept they want to express. In you case however, the concept of adaptation seems to be a bit more complicated (and interesting) because it refers to a group-level adaptation.

Note that most people does not really care about the exact definition they're using and this might yield to some confusion. It will probably be a bit hard to know exactly what the authors  (Dey et al.) of your article had in mind.

Definition of Group-level adaptation

I am here going to talk about how the term adaptation can be understood for a (social) group. This is important as I suspect the authors to use the term adaptation on a group phenotypic trait (emergent trait if you want).

Pareto optimality

To my experience, the concept of group-level adaptation is defined in relation to the concept of Pareto optimality which is a concept used in evolutionary game theory. Shortly speaking, in a system that is at Pareto optimality no individual can by any change of the trait under consideration increase its fitness without decreasing the fitness of another individual. In other words, a population that is at Pareto optimality has the greatest achievable population mean fitness. Therefore, it makes sense to consider a group to be (perfectly) adapted when it is at Pareto optimality.

Nash equilibrium

Depending on the underlying evolutionary game, the Pareto optimality may or may not be a Nash equilibrium. Shortly speaking, a population is at Nash equilibrium if no individual can increase its fitness by changing the trait under consideration. Therefore, group-level adaptation can only be stable if the Nash equilibrium is Pareto optimal. An example of game where the Nash equilibrium is the free-market game.

In your case

At first sight, because asynchrony is a group level trait, it seems to me that the sentence "Hatching asynchrony is thought to be adaptive [..]" means that hatching asynchrony is thought to be at Pareto optimality. In other words, it means that hatching asynchrony is thought to be the state of the system where the mean fitness of the group is maximized, that is no individual can increase its fitness without decreasing the fitness of another individual by being synchronous.


Meaning of “gene expression heterogeneity” of embryonic stem cells

Heterogeneity is a noun meaning:

the fact of consisting of parts or things that are very different from each other

In scientific use the context determines what is differing.
The context here is gene expression in individual embryonic stem cells (presumably single-cell RNASeq). Here the heterogeneity in expression would be for the genes

…(Neurod1, Klf4, Otx2, Pax6)

for which the expression is

…undetected in most cells but highly expressed in some specific subpopulations.

The conclusion is that although the embryonic stem cells may appear to be a homogeneous population (all alike) and do show similarities in many genes that they express, they must, in fact be a mixture of two (or more) types. (This makes the generally accepted assumption that the basis for distinguishing cells is the genes they express and the proteins they make.)
Thus the idea, expressed in the question, that the cells are identical is incorrect. I know little about stem cell differentiation, but I would assume the implication is that the subpopulation will differentiate on a different path to the rest of the population, or that it has already started to differentiate, or something of the sort (which I imagine is discussed in the paper).


No guarantee that my answer is the right one but my educated guess that your plant is a species of Acalypha. There are a number of species in this genus and I'm sorry I can't narrow it down further.

The shape of the leaves, the little 'pig-tail' shaped seed (or unopened flower) spike seen in the upper left corner of the first photo, the tinge of pink on some leaves and veins and even the twist or curl on the uppermost group of leaves leads me to think that.

I'm including some photos showing these points. Whether it's a plant in this genus is for you to decide. It would be helpful to know the size of the entire plant and he range of size in the leaves.

Acalypha wilkesiana

Another Acalypha wilkesiana with this one showing the 'pig-tail' flower spikes better.

The flower spikes are very evident in this Acalypha bamentacea here.

The twists and curls can be seen in this cultivar of Acalypha wilkesiana.

Source courtesy of Dave's Garden


What do rs id, allele coded 0 and allele coded 1 mean?

rs id is reference SNP cluster ID see here. It's basically a unique identifier.

This table is taken from your link:

rs              position        0       1
rs11089130      14431347        C       G
rs738829        14432618        A       G
rs915674        14433624        A       G

The allele codes are the 3rd and 4th columns. An SNP is  site where a different base is found in different versions of the same gene (different versions of genes are alleles). For a given SNP the different alleles are referred to as the 0 or the 1 allele. So in the table the first SNP, rs11089130,  has two alleles: allele 0 has a C at the SNP position (14431347) whereas  allele 1 has a G at that position. The allele code does not imply any biological significance.

I'm not sure what would happen if there were three alleles at an SNP, but presumably there would then also be an SNP coded as 2.

Edit:
Allele 0 is the residue from the reference genome. Allele 1 is the residue being studied, the SNP.


Do the phage repressors CI and Mnt exhibit crosstalk?

There are no reports for it yet. I don't think just because they show overall homology, they would exhibit crosstalk. Just see the alignment of the DNA binding domains of these proteins first ~70 residues from N-terminal. Moreover their DBDs belong to different PFAM families.

Similarly with the promoter sequences.
As reported in iGEM website:

Mnt promoter: tagatctcctatagtgagtcgtattaattt
cI promoter: gtgttgactattttacctctggcggtgata

They are quite different.
Moreover, if iGEM has a reported standard part such as a bistable system component: Mnt/cI promoter (BBa_K228003) then it would have been pretty much standardized. iGEM parts are usually reliable.


Which are the best programs to analyze circular RNA?

According to the most recent paper (https://doi.org/10.1093/bib/bbx014), CIRI2 shows a balanced performance on sensitivity and FDR.

"Computational detection methods have been widely used in studies on the biogenesis and the function of circular RNAs (circRNAs). However, all of the existing tools showed disadvantages on certain aspects of circRNA detection. Here, we propose an improved multithreading detection tool, CIRI2, which used an adapted maximum likelihood estimation based on multiple seed matching to identify back-spliced junction reads and to filter false positives derived from repetitive sequences and mapping errors. We established objective assessment criteria based on real data from RNase R-treated samples and systematically compared 10 circular detection tools, which demonstrated that CIRI2 outperformed its previous version CIRI and all other widely used tools, featured with remarkably balanced sensitivity, reliability, duration and RAM usage."


Why does applying pressure to a venipuncture site prevent haematoma?

Prevention of hematoma (as we say in the colonies) is by causing hemostasis within the vessel (here, a vein). Careful pressure during withdrawal, followed by firm pressure after withdrawal until primary hemostasis is achieved reduces the rate of hematoma formation.

Thorough mechanistic studies being absent, we can still confidently make some statements about what is likely happening, based on our knowledge of physics and hematology.

  Why is it not necessary until withdrawal?

Good venipuncture technique results in a single puncture of a vein that is no larger than the needle. With a single puncture, during the blood draw, all blood exiting the vessel enters the needle and the collection tube. This is why pressure is not necessary until withdrawal of the needle.  In fact, pressure at this point may cause the needle to damage the vessel at another site, allowing blood to exit into the tissue.

  How does pressure prevent a hematoma?

On withdrawal, external pressure to a punctured vessel that is greater than the internal pressure of that vessel will stop the flow of blood, preventing blood from entering the tissue.  At a standard venipuncture site, e.g., the antecubital vein, it takes approximately 2-10 minutes for primary hemostasis (in the absence of aspirin, or otherwise poisoned or disordered platelets). If you prevent flow out of the vessel during this period, you'll prevent formation of a hematoma. There are other mechanisms at work here that help, e.g., vasospasm, so you may still avoid a hematoma without pressure, but the rate of hematoma formation is higher when this isn't done

  Does it increase vein inner wall cell damage, releasing agents triggering faster clotting?

Possibly, but the primary mechanism is simple physics. Increase the pressure until a plug is formed, and you prevent blood from exiting the vessel into the tissues.


What is the name of the smallest self-replicating thing?

You're probably thinking of the Spiegelman Monster. It was actually discovered in 1965, but it was discovered that it became shorter over time in 1997.

It also wasn't included in that thread, and it has a strange name.

http://en.wikipedia.org/wiki/Spiegelman_Monster


What causes the complementary copy of an RNA molecule to separate?

First, I want to point out that the RNA world hypothesis is just that - an hypothesis. While it has been shown that it's possible for certain RNA molecules to make copies of itself, this is not a 'normal' function of any RNA.

Edit - to give a clearer answer to the question itself:

After replication of an RNA molecule it may form a stable structure together with its template or it may dissociate. Due to the various possibilities and complexity of RNA structures its almost impossible to predict this, since both the (exact) sequence itself and environmental conditions especially temperature are very important.

More background from the unedited answer:

Whether two complementary strands or RNA (or DNA) bind together is not something that can always be easily answered. For DNA of a given length (in a given environment / buffer) one can more or less predict the temperature at which complementary strands will separate (often called melting temperature), because DNA forms relatively stable helices.
RNA, however, often forms complicated 3-dimensional structures, often involving self-complementary and is not restricted to the typical helices seen in DNA. Trying to predict the resulting 3D structure of RNA molecules is still an ongoing field of research. Some of these structure are quite stable (e.g. in tRNA) but in other cases they can also be very dynamic and change quickly.
In the end it always depends on the RNA sequence, temperature and many other environmental factors.


Pregnancy is a biological process that has been very well studied by medicine. As a result, modern medicine helps a lot to prevent miscarriages and to prevent death of pregnant women.

While the latter clause is correct (maternal - and infant - mortality is reduced with medical care), the former is not.

Miscarriages have been a problem as far back as recorded history. The written record includes medicinal recipes to prevent miscarriages. The problem then, as now, is that it just can't be done very well.

From a 2000 Obstetrics journal article:

  Human reproduction is extraordinarily wasteful. The reasons for this have taxed all of the contributors to this book. As we move into the 21st century it is sobering to reflect on the fact that we have failed to harness the power of the evolving revolution in molecular medical biology to answer the fundamental question: why is the fate of a fertilized egg so hazardous and so unsuccessful? The following account summarizes our limited knowledge of the epidemiology of miscarriage and then moves on to consider some of the medical causes of miscarriage...

Miscarriage is difficult to study, and the causes difficult to establish, so the literature showing that any interventions help (antibiotics, bed rest, supplements, etc.) is not plentiful. Smoking seems to have a deleterious effect on pregnancy. How this relates to early populations is a matter of conjecture.

Some good studies do exist, however. One good study in the New England Journal of Medicine followed an ideal group: women who had no history of infertility, who were trying to become pregnant.

Of 221 couples followed for 6 months, a total of 199 pregnancies were detected, of which 126 ended in live birth (therefore a 37% miscarriage rate). Because of the methodology, failure of blastocysts to implant could not be measured. The findings of this study were supported by others (31%), etc.: early loss increased when implantation occurred later than 10 days after ovulation. While the authors were hopeful ("There may be opportunities to increase fertility by extending the time during which implantation can occur."), they were also realistic ("Such interventions should be approached cautiously, however, because they may have unintended consequences with respect to the quality of surviving embryos.") Basically, you can't fool around too much with Mother Nature in this realm.

Has modern medicine been able to change this rate? Not really. Even with IVF, where thousands of dollars are spent trying to preserve a single pregnancy (certainly not the norm), miscarriage is common. The best way to increase the viability of IVF pregnancy is to select better oocytes, embryos, etc. In other words, maternal factors remain refractory to manipulation.

Even things obstetricians long took for gospel (for example, bedrest with pre-eclampsia) have little evidence of benefit to the fetus.

The literature is vast in this area (reproduction is an important field to study). I can write a book on how little can be manipulated on average (I will consider spending thousands of dollars on one pregnancy not average), but it wouldn't sell. What does sell are false claims, this one being as good as any claimed today:

  To prevent miscarrying or if one that is apt to miscarrie goe a journey let her take this powder morning and evening whilst shee journeys: Take of Dragons Blood the weight of a silver two-pence, a dram of red corrall powdered, the weight of 2 barly corns of Ambergrease, Besar ye weight of 3 barly corns, mix all these together and keep them close stoped in little vial glasse when you use take as much of it as lie upon a penny in a little clary water at nighte when you goe to bed, and in ye morning fasting and sleep after it to use it till you are out of danger.


According to oneZoom.org (see the node of interest here), the large ground finch and the large cactus finch share a common ancestor about 170k years ago. Looking among Darwin finches on oneZoom.org, I could not find a more recent speciation event. I could not find their references for their estimates though.

However, part of the difficulty here lies in the exact definition of species one is willing to use (see this post). While it is not reported in oneZoom.org, grant and grant (2009) reported an evidence of reproductive isolation within the G. fortis species.

  Speciation, the process by which two species form from one,
  involves the development of reproductive isolation of two divergent
  lineages. Here, we report the establishment and persistence
  of a reproductively isolated population of Darwin’s finches on the
  small Gala´pagos Island of Daphne Major in the secondary contact
  phase of speciation. In 1981, an immigrant medium ground finch
  (Geospiza fortis) arrived on the island. It was unusually large,
  especially in beak width, sang an unusual song, and carried some
  Geospiza scandens alleles. We followed the fate of this individual
  and its descendants for seven generations over a period of 28
  years. In the fourth generation, after a severe drought, the lineage
  was reduced to a single brother and sister, who bred with each
  other. From then on this lineage, inheriting unusual song, morphology,
  and a uniquely homozygous marker allele, was reproductively
  isolated, because their own descendants bred with each
  other and with no other member of the resident G. fortis population.
  These observations agree with some expectations of an
  ecological theory of speciation in that a barrier to interbreeding
  arises as a correlated effect of adaptive divergence in morphology.
  However, the important, culturally transmitted, song component
  of the barrier appears to have arisen by chance through an initial
  imperfect copying of local song by the immigrant. The study
  reveals additional stochastic elements of speciation, in which
  divergence is initiated in allopatry; immigration to a new area of
  a single male hybrid and initial breeding with a rare hybrid female.


Earwax, also called cerumen, is slightly acidic (1), with a pH of about 6,  and acidic foods or substances taste sour. The composition of earwax, upon which its taste depends, is related to its functions. Earwax aids in cleaning and lubrication of the ear canal and has an antimicrobial effect. The antimicrobial effect is in part attributed to its acidity, which might give an evolutionary reason for the sour taste.

From Wikipedia:

  Cerumen is produced in the outer third of the cartilaginous portion of
  the ear canal. It is a mixture of viscous secretions from sebaceous
  glands and less-viscous ones from modified apocrine sweat glands.[4]
  The primary components of earwax are shed layers of skin, with 60% of
  the earwax consisting of keratin, 12–20% saturated and unsaturated
  long-chain fatty acids, alcohols, squalene and 6–9% cholesterol.[5]

  (...)

  While studies conducted up until the 1960s found little evidence
  supporting antibacterial activity for cerumen,[15] more recent studies
  have found that cerumen has a bactericidal effect on some strains of
  bacteria. These antimicrobial properties are due principally to the
  presence of saturated fatty acids, lysozyme and, especially, to the
  slight acidity of cerumen.


In the paper "Phase diagram of microtubules" Fygenson, 1994. it's evident that with increasing temperature the length of the aggregates is growing. But it of course depends on other additional parameteres like concentration and I assume the type of the protein - alpha and beta-tubulin.


What step of the cloning process requires an egg cell? Have alternatives been attempted?

egg cells are not required for cloning, plants for instance can be cloned just fine without them. Oocytes are commonly used in animals becasue they already contain some of the chemical markers and enzymes to begin development in the mother's body and keep her immune system from attacking it. In more derived animals development is not solely controlled by the the embryo but also by the mother, so using an egg cell helps trigger those processes of the mother. If you used a standard stem cell likely the mother immune system would just destroy it as a foreign entity.


Given what you've said in the comments, and how much more common they are, I'm going with my first gut reaction of Lycoperdon perlatum.  The big give away for me was that you said there was a good taste.  L. Perlatum has a rich nutty flavor (my wife grows them), but Handkea excipuliformis (pestle puffballs) don't have much taste if any.  They are seriously notably bland.  H. excipuliformis can take on the flavor of what ever you cook them with, so if you cooked in a nut oil or with nuts, then you would have given the flavor that way.

Not that I support taste as a primary means of id...  In this case most of the puffballs are edible so you were in a low risk situation.  I just don't want to start a wave of fungus ID's that include taste info!


It's right to say coding sequence is part of exon sequence?

As I remember, exon sequences is the same with coding sequence, except
  for the first and last exon, which are parts of 5'UTR and 3'UTR,
  respectively, am I right?

Not necessarily. The UTRs can be composed of multiple exons and there can be an exon that spans both sides of the start codon i.e it is both a part of the 5'UTR and CDS. Similarly, an exon can span both sides of the stop codon.

A reason for why you are not able to map your repeat to any of the regions of the mRNA could be that your repeat falls in an exon that spans the start/stop codon. The repeat itself might span these sites. You need to provide additional details such as the location of the repeat, size of the repeat and which exon it maps to. Also mention which reference genome file are you using.


What is the theoretical maximum height of a herbaceous plant stem?

Update: I have edited the answer for a better structure and for providing reliable references.

Some of the factors that influence growth, while keeping in mind that every species has particular needs:

•   light, temperature
•   insufficient light leads to etiolation
•   water
•   amount of water and dry substances, page 185
•   water influences diameter
•   soil
•   wind
•   macronutrients
•   citokinin
•   genotype
•   heterosis
•   inbreeding
•   pinching the stem stops its growth and promotes lateral stems (I understand that you don't want to, but I list it here so that you can watch out accidents - involuntary pinching has the same effect)
•   root type
•   shelter near a fence or a wall

You might find some info as to what to consider in your calculations in this paper, although it's about trees.

Just for the purpose of knowledge, herbaceous vines like Ipomoea are also stems and they can grow longer than vertical ones. There may be more to add, but I'm only a Horticulture student, not a plant physiologist.

I strongly recommend to ask plant related questions on Gardening and Landscaping SE, a small community, but a very enthusiastic one. Also, hardly can someone become a good gardener without knowing at least the basics of plant biology and psysiology, so you have a major chance there of receiving answers in a few hours, not days.

Good luck with your project and I hope you'll return to tell us your conclusions. We will be happy to see you interdisciplinary approach.


Is there a term for the entire system of moving oxygen around?

Short answer
"Oxygen homeostasis" is the best I can think of.
Longer answer
Don't forget the other half of the oxygen equation: carbon dioxide is an important waste gas and failing to remove carbon dioxide is just as much a problem as failing to deliver enough oxygen.
You could refer to "oxygen homeostasis" if you wanted to just refer to keeping enough oxygen in distal tissues; as you describe, both respiratory and circulatory systems are relevant for oxygen homeostasis. However, it's hard to separate from the rest of the gas exchange system. Carbon dioxide is very important in determining the rate of respiration, for example, as well as the release of oxygen in peripheral capillaries. Therefore, even if you want to focus on just oxygen, carbon dioxide is going to come up no matter what! As is the function of the vasculature, heart, and lungs: even if these organs have roles outside of delivering oxygen, their functions apply to all gasses exchanged and everything that is transported in the circulatory system. Very little happens in these systems that will only affect oxygen delivery without affecting anything else.
The efficiency of oxygen delivery also depends on what exactly you're inhaling; I find it a bit bizarre to include "smoking" as seemingly part of ordinary biological function, but if you want to go there it's reasonable to consider the role of carbon monoxide and anything else that may interfere with oxygen binding to hemoglobin.


In this type of experiment the concentration of the mRNA will be greater than the concentration of the starting DNA.

When the DNA strands separate, the DNA and mRNA will be in competition for the complementary strand. Using really high concentrations of mRNA compared to the DNA will give it advantage to recombine with a higher frequency and give a higher ratio of the DNA-mRNA combination.

It is all a question of ratio.


What parts of the visual system could be responsible for a fixed, monocular scotoma?

Yes. You're right.

A scotoma only affecting one eye (i.e., one that is not perceived when one eye is closed) is diagnostic of a lesion upstream from the optic chiasm.

See Brust's Practice of Neural Science, Fig. 3-2. The figure demonstrates a full cut, with complete blindness in one eye, but the principle is the same for a scotoma.


If someone's arm is cut off, how does that affect blood circulation throughout their body?

If I understand your question correctly, you ask how does the body deals with released blood volume after the removal of part of blood vessels?

The simple answer is the body decreases the blood volume. Our body is able to alter blood volume significantly in response to different factors.

For example, take a look at this paper: Blood volume changes in normal pregnancy. It states that:

  A healthy woman bearing a normal sized fetus, with an average birth weight of about 3.3 kg, will increase her plasma volume by an average of about 1250 ml, a little under 50% of the average non-pregnant volume for white European women of about 2600 ml.

So, after the arm cutting, an organism will decrease its blood volume. Although it will take some time, blood volume altering is more probable way than new vessels generation.


How did people's liking of ceremonies evolve?

Perhaps customs (and culture as a whole) arises to some extent as a result of relationships between individuals of the same species. For example, I think a good example of a custom is how elephants bury their dead. This does not benefit the surviving elephants in any noticeable way, and is a "waste" of energy and time. If customs do arise because of a group dynamic, then there is clear evidence supporting that social behavior in higher organisms (chimpanzees, dolphins, etc.) does increase fitness.

However, this speculation is based upon the idea that customs are a natural result of social interaction. As to why these customs arise, perhaps it is because it enforces the group dynamic over the participating individuals.


Are all animal species prone to cannibalism induced prion infection?

An individual (animal or human) acquires a prion disease when they consume meat that contains prions (proteins that are mishapen enough to drastically change their functionality), which subsequently causes proteins within the individual to misfold into the same shape as the prion, resulting in a whole slew of problems.

As of right now, there is little knowledge of where prions come from/how they're formed. Also, there is little knowledge of how inter-species infections/transmissions occur. Researchers are currently investigating various combinations of inter-species transmissions, such as humans eating infected horse meat, or cats eating infected chicken meat, but still know only very little about this phenomenon.

To say which species have higher rates of prion disease when looking at a cannibalist communities within that species, I don't think we're anywhere near close to making those conclusions, and the same goes for inter-species transmissions.

All the best.


Has the acronym DNA ever been widely understood to stand for deoxyribose nucleic acid?

First off, that paper is the seminal discovery and publication of the structure of DNA, and is absolutely worth the read.  It's one of the most important pieces of scientific literature.

The short answer is no.  DNA stands for Deoxyribonucleic Acid.

The long answer is... this is really just picking at nits.1  DNA, deoxyribonucleic acid, is a type of nucleic acid, specifically a deoxyribose nucleic acid.  So, if your or your friend wants to be pedantic, you can call DNA a type of deoxyribose nucleic acid that stands for deoxyribonucleic acid.

You probably shouldn't, though, since if you really want to be pedantic, saying "deoxyribose" implies it's a sugar, which once it has formed the DNA backbone, it no longer technically is.  Watson and Crick clearly used the phrase your friend has, but suffice to say that British papers from the 1950s used language differently than most folks today.

As a side note, there are nucleic acid analogues, such as PNA and LNA, which generally use the "Whatever Nucleic Acid" construct for naming, but I suspect that's mostly because "peptide" is a broad category, and "locked" isn't actually a biological word.

Also, "it depends on the source you go by" is just a way of getting out of being wrong.

ETA: WYSIWYG correctly notes in the comments that it used to be called desoxyribonucleic acid, such as in this extremely important paper by Avery, MacLeod, and McCarty.

1: See what I did there?  Most people would say "nitpicking" but "picking at nits" is basically the same thing, even if almost nobody says it.


The difference between the two ways of glycine represntation

The first method of representation is the regular way, where all groups, including carbon and hydrogen are shown.

The second method is the "skeletal form", where every bend in the line means a carbon group, and the hydrogen atoms attached to the carbons are implied. It does seem a little tricky to visualise, but it is easier and faster when you come to larger groups.

Check this out.


Any evolutionary explanation for human blood groups?

Researchers have puzzled over the selective explanation for the ABO polymorphism at least back to the 1950s. Multiple lines of more recent evidence, including the very old age of the ABO polymorphism and (perhaps) multiple convergent evolution events, suggest that the ABO polymorphism is maintained by balancing selection (E.g. Saitou and Yamamoto 1997, Segurel et al 2012). As best as I know, is no general consensus on what is driving balancing selection, though some researchers have argued that the selective agent is Plasmodium falciparum (e.g. Cserti and Dzik 2007).


What are the highest and lowest amplitude values in ECG for humans?

The QRS complex is the part of the ECG with the largest amplitude.

I scanned a dozen ECG traces across the web, and as far as I can see, the QRS complex has amplitudes of up to 4 mV in a normal ECG:

ECG trace. 1 mm corresponds to 0.1 mV on the y-axis

Amplitudes are relative peak-to-peak measures. If you are asking about absolute values then the minimal voltage versus maximal absolute voltages depend on your baseline value, i.e., the offset in your voltage potential measurement system. Further, artifacts and background noise may add signal amplitudes on top of the ECG proper.

As an absolute minimum estimate, the graphs here posted show that -1 mV would be a safe minimal voltage.


Structure and reactions of the cofactors of oxidoreductases such as ferredoxin

Summary
Enzymes catalysing oxido-reductive reactions (oxidoreductases) do so with the aid of non-protein molecules (prosthetic groups or cofactors) at their active sites. The three main types of such prosthetic groups or cofactors are iron–sulphur clusters, derivatives of flavin (FAD and FMN) and nucleotide derivatives of nicotinamide (NAD and NADP). The groups of proteins incorporating these type of cofactors are often referred to by the general terms ferredoxins (also iron-sulphur proteins), flavoproteins, and NAD(P)-linked oxidoreductases, respectively.
Introduction
The vast majority of enzymes are proteins, linear polypeptide chains folded into specific but irregular spheroidal shapes. In addition to interacting with the reaction substrates, the amino acid side-chains of the polypeptide chains participate in the actual reactions catalysed by many enzymes, and in many cases are sufficient for the catalytic properties of enzymes. However for the catalysis of some sophisticated reactions, additional non-protein molecules are required — metal ions or organic molecules — known generally as ‘co-factors’, ‘co-enzymes’ or ‘prosthetic groups’. This is the case for the various enzymes termed oxidoreductases, which catalyse oxidation/reduction reactions, involving the transfer of electrons.
Nucleotide derivatives of nicotinamide in NAD(P)-linked oxidoreductases
The cofactors found most frequently in oxidoreductases are nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP). The pyridine ring of the cofactor is the electron acceptor, and the oxidized and reduced forms are termed NAD+ and NADH, respectively.

[Own diagram]
Proteins with bound NAD or NADP (non-covalently) are the most common type involved in oxido-reductions, and have systematic names composed of the cofactor, substrate and ‘oxidoreductase’. e.g.
Systematic Name: lactate:NAD+ oxidoreductase
Common Name: lactate dehydrogenase)
Flavin Nucleotides in Flavoproteins
The other common cofactors in oxidoreductases are flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN). The isoalloxazine ring is the electron acceptor, and the oxidized and reduced forms are termed FAD (FMN) and FADH2 (FMNH2), respectively.

[Adapted from section 14.3 of Berg et al.]
Proteins containing FAD or FMN are called flavoproteins, and are less abundant than NAD(P)-linked oxidoreductases, and a few of them actually perform non-redox reactions. Example of nomenclature:
Systemic name:  short-chain acyl-CoA:electron-transfer flavoprotein 2,3-oxidoreductase
Common name: short-chain acyl-CoA dehydrogenase
Iron–Sulphur Clusters in Ferredoxins
Whereas the above two oxidoreductases are common in intermediary metabolism, those containing iron–sulphur clusters (some of which are known as ferredoxins) tend to be involved in more specialized and ancient reactions, such as photosynthesis, tagged in the question. The diagram  shows one particular type (2Fe–2S) of iron–sulphur cluster and its covalent attachment to the ferredoxin through cysteine residues. 4Fe–4S stoichiometries are also found, as well as some others.
The electron transfer involves changes in the oxidation state — Fe(II)/Fe(III) — of the iron.

[Adapted from section 19.3.3 of Berg et al.]
The figure also provides a good illustration of the relationship between a co-factor and the protein in which it resides.
Example of nomenclature:
Systematic name: hydrogen:ferredoxin oxidoreductase
Common name: ferredoxin hydrogenase
The situation here is complicated by the fact that iron–sulphur clusters are found in other proteins besides those termed ferredoxin, including some specialized oxidoreductases involved in the electron-transport chain, and in nitrogenases. The term ferredoxin is historical rather than systematic.
Differences between these oxidoreductase cofactors
The specific roles played by these three cofactors in oxidoreductases is a topic of its own. However, it should be mentioned that an important difference is their standard reduction potentials, the biochemical background to which can be found in Section 18.2.1 of Berg et al., available online.
Ferredoxin-NADP+ reductase (FNR)
Electron transport occurs between the different cofactors in certain circumstances, one of which is photosynthesis where electrons are transferred from ferredoxin to NADP+. The enzyme catalysing this — Ferredoxin-NADP+ reductase — uses the third type of cofactor — FAD!


You can read about the differences between a binomial and poisson distribution at this other question on Math.SE.

First, since spikes are discrete events, it makes most sense to use a probability distribution that is discrete. A Poisson process is a process where an event occurs randomly with no "memory" for how long it has been since the last event. A Poisson distribution is the number of events if you integrate draws above some threshold from an infinitesimally small uniform distribution. Therefore, the Poisson distribution is the distribution you choose if occurrences of an event are only dictated by an underlying rate parameter - this turns out to be a reasonable, if ultimately false, assumption for neurons.

There is definitely no biological fact that neurons must follow a Poisson distribution - in fact, no neuron can be truly Poisson because, if nothing else, the refractory period makes it impossible. Rather, Poisson behavior is sort of the simplest behavior you would expect from neurons in a system where they are firing occasionally due to random noise - sort of a "null hypothesis." For many modeling approaches, this is close enough, and it allows the modeler to avoid making more nuanced assumptions. It turns out to be a decent assumption when you look at individual cells, but if you look at populations the activity deviates a lot from Poisson.

Note that the Poisson distribution is often only valid for spontaneous data; it is possible to use a nonstationary Poisson distribution to model responses to some external stimulus, but the results are likely to deviate more from experimentally derived data.


Why does caffeine give you so much energy, while being so low on calories?

I agree with @inf3rno: caffeine is a stimulant that acts on the brain and various other parts of the body (Snyder et al., 1981) and I wish to elaborate on its psychopharmacology. Caffeine's effects in the brain are mediated through adenosine A1 and A2 receptors (Daly et al., 1983). This results in a variety of actions (Fredholm et al., 1999). Most notably, adenosine inhibits neurotransmitter release in various brain structures including the acetylcholine release in the mesopontine projection neurons. Caffeine blocks these adenosine receptors, in turn leading to an increase in acetylcholine release in the cortex and hippocampus. This increases vigilance and information processing. Increased acetylcholine release in the prefrontal cortex may lead to increased attentional abilities. Adenosine also inhibits the effects of dopamine released by the striatium, ultimately leading to disinhibition of motor output in the brainstem. This in turn increases motor activity (Fisone et al., 1997). In all, caffeine does not exert its stimulant effects through its metabolic energy content, but due to its pharmacologic effects on adenosine receptors.


This is some species of ichneumon wasp.

The ichneumon wasps are parasitoid wasps in the order Hymenoptera. They commonly parasitize other invertebrates, especially larvae and pupae of Coleoptera, Hymenoptera, and Lepidoptera.

Specifically, this appears to be Dolichomitus irritator.

 Photo credit:  Thomas wilson

Here's another specimen of the same species found in Weymouth Woods-Sandhills Nature Preserve, Southern Pines, Moore County, NC:

 Photo credit:  Dorothy Pugh

You can find additional high-quality images from Jeff Tome's Flickr page.

I could not find too many sources with good information about this specific species. Fontanelle Forests' Nature Search provided the most complete info:

Description: 7/8 inch long, not including the ovipositor.  The head and thorax are black.  The abdomen is red-orange.  The legs are yellow and orange.  The antennae are black.  The black ovipositor is at least as long as the body and head.
Ecology: Parasitoids of many woodboring insect larvae including long-horned beetles, weevils, metallic wood-boring beetles and some moths that are wasp look-alikes.
Taxonomy: In the subfamily Pimplinae, which has 180 species in 28 genera in North America.


What is the difference between a human being, a Homo sapiens, and a Neanderthal?

Homo sapiens / Homo sapiens sapiens
Human being, in the popular culture generally refers to modern humans, called either Homo sapiens or Homo sapiens sapiens. The existence of the two names will make sense when talking about the Neanderthals. In the term Homo sapiens, Homo indicates the genus and sapiens indicates the species. In the term Homo sapiens sapiens, the second sapiens refers to the subspecies.
Homo neanderthalis / Homo sapiens neanderthalis
Neanderthals (or Neandertals) is sometimes referred to as a species in the same genus (Homo) as H. sapiens and sometimes as a subspecies of H. sapiens. When considered as a different species then, they are called Homo neanderthalensis. When Neanderthals are considered as the same species as H. sapiens but different subspecies, then they are called Homo sapiens neanderthalensis and modern humans are then called Homo sapiens sapiens.
Related Post
The post How-could-humans-have-interbred-with-neanderthals-if-were-a-different-species will probably be of interest to you.


Do DNA supply houses maintain a watch list for dangerous oligos (Anthrax, Smallpox, etc.)?

I don't know how generally such things are followed, but in at least one contract gene synthesis provider's FAQ, they address this issue, and mention two such government-provided resources:

  Q: Does GENEWIZ have a procedure in place to address potential biosecurity
          concerns for gene synthesis projects?

  GENEWIZ is fully aware of all risks and benefits associated with gene synthesis research. With the knowledge that gene synthesis technologies have the ability to enable de novo reconstruction of dangerous pathogens, GENEWIZ employs rigorous quality control policies and procedures to safeguard against abuse of the genes we synthesize. GENEWIZ actively monitors the Screening Framework Guidance for Synthetic Double-Stranded DNA Providers [link], drafted by U.S. Department of Health and Human Services (HHS), as well as the Select Agents and Toxins list put forth by the U.S. Government.


What are the differences among food poisoning, gastroenetritis and diarrhoea?

First of all, diarrhea is a symptom, generally defined as passing large amount of loose stool. Diarrhea has countless causes, which include gastroenteritis and food poisoning (although not all types of gastroenteritis or food poisoning cause diarrhea).

Now the other two terms. Strictly speaking gastroenteritis refers to the inflammation of stomach/intestines, but clinically, it is most often used to refer to infection of stomach/intestines. Gastroenteritis is most often caused by viral infections e.g. rotavirus, noravirus, enterovirus, adenovirus... but can also be bacterial in origin.

As for food poisoning, is usually defined as illness (usually gastrointestinal symtoms, including nausea, vomiting and diarrhea) caused by "poisoned food". Food poisoning can be caused by the presence of a microbial toxin (which can sometimes be heat-stable ie not inactivated by boiling/cooking). Examples include S. aureus enterotoxin, B. cereus enterotoxin, shigatoxin... There can be an overlap, when ingestion of food causes an infection of the gastrointestinal system, but gastroenteritis is not necessarily foodborne.

Hope that clarifies things.

References for further info:
Food poisoning
Basics of acute viral gastroenteritis


Did you try to use Bioclipse:

  Bioclipse is mainly based on the Chemistry Development Kit (CDK), and contains a framework for managing and analyzing chemical compounds. Bioclipse supports editing in 2D, processing large collections of molecules in tables, calculation of various types of properties, and much more cheminformatics functionality. The Jmol application is integrated in Bioclipse as an editor, and provides advanced interactive 3D visualizations.


What's the difference between naive and memory B cells?

The main difference is that memory B cells start an immune reaction much more effective and faster than naive B cells. The reaction is also specific towards the antigen.

The memory B cell has a specific membrane receptor for an antigen. It produces specific antibodies only when exposed to the antigen.

References:

Tangye SG, Avery DT, Deenick EK, Hodgkin PD. Intrinsic differences in the proliferation of naive and memory human B cells as a mechanism for enhanced secondary immune responses. J. Immunol. 2003 Jan 15;170(2):686-94. PubMed PMID: 12517929.
Wikipedia contributors, "B cell," Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/w/index.php?title=B_cell&oldid=612990219 (accessed June 26, 2014).


Why don't sodium Voltage Gated Channels open during Repolarization?

Voltage-gated sodium channels have three basic states that represent different conformations of the protein: closed, open, and inactivated.
When a voltage-gated sodium channel is open at depolarized voltage, there is space for part of the channel to shift into a position that blocks the pore. When this happens, it gets stuck blocking the flow of sodium, and it requires a negative membrane potential to remove the block. We call this the "inactivated" state, and this model is called the ball and chain model of sodium channel inactivation.
The inactivation gating process is also referred to as the "h-gate", because h is the variable representing the gating in the classic Hodgkin-Huxley model.
Wikipedia currently has a useful table on the sodium channel page showing the different states that a sodium channel goes through during different phases of an action potential.


What is the disadvantage of having no anticoagulation after pulmonary embolism?

Not always, however typically it is given for at least a few months. Lack of anticoagulation therapy would greatly heighten the risk of having another PE or related cardiovascular events. At the worst side this could cause death or permanent disability, and PE related deaths are quite common. However this depends on the nature of the PE and risk factors. For example, obesity, cancer and the pill are all risk factors and if these were reduced then it is likely the person wouldn't have another PE despite not being on long term anticoagulation therapy. However, if there is an underlying cause even despite anticoagulation therapy a person may suffer a PE.

The problem with anticoagulation therapy is of course it stops your blood clotting. Thus haemorrhages are more common and also more severe. However in an individual receiving anticoagulation therapy, they typically have increased clotting so this may be balanced out by therapy.

Finally anticoagulation therapy is typically warfarin in the long term. Warfarin interacts with so many drugs including even antibiotics, it is teratogenic and quite sensitive to diet (any changes in Vitamin K will directly affect the effectivity of warfarin) thus frequent monitoring is required. This is annoying for the patient as they have to report for frequent blood tests as well as watch their diet etc.


Can organisms like Noctiluca be commercially exploited?

Well, scientists have been developing Bioluminescent Plants to use as a future road light source. Also, there is a way that Bioluminecent algae can be used as medicine.


Methods for varying insert size in E. coli clones

Yes.  In principle you will have a vastly increased ability to customize the boundaries of each protein domain with a primer and PCR based approach.  It is not obvious to me that the Gateway Cloning System is required, or necessarily the best choice for this approach, but that is likely subjective.

Are you familiar with, or aware of, the efforts of the SGC (Structural Genomics Consortium)?  My understanding (now somewhat outdated) is that they were going to design/use a semi-automated way of implementing the strategy you discuss (domain trimming) so that they could us a high-throughput approach to define crystallization conditions for their targets.  Perhaps you could adapt their method(s) to your protein of interest?


Is RFLP markers are dominant or codominant?

I suspect that you "know" the answer to your question and are just seeking confirmation.  First, let's get some terms straight.  Dominant and recessive are used in reference to phenotypes, so one needs to have a transmissible phenotype to score among the offspring of our genetic cross.  Phenotype are usually due to (or caused by) mutations.  In a diploid species, if you can only score the phenotype in offspring that are homozygous for that mutation (denoted m/m) then the phenotype is recessive to the wild-type allele of the gene.  In other words, a heterozygous offspring, (m/+) will have a wild-type phenotype.  On the other hand, if a heterozygous (m/+) offspring has a mutant phenotype then we would say that the mutation is dominant over the wild-type allele.
Your question is asking about a test cross of a +/+ individual to a homozygous mutant (m/m), however, in this case the RFLP does not typically have any mutant phenotype, it is just a convenient genetic marker for the purposes of this discussion.  All of the cross-progeny will be (m/+), and if you go to the trouble of preparing genomic DNA from those F1 cross-progeny and perform a Southern blot with a probe that detects the RFLP, then you will be able to demonstrate this.  Typically, unless the RFLP-bearing chromosome is homozygous, the probe will also detect the wild-type restriction fragment, so there will be two bands on the film, one for each allele.  Since you can detect the genetic marker in the F1 generation, the RFLP is dominant, but since you can also "score" the wild-type fragment, the two fragments are indeed co-dominant (after you do the Southern blot).


Why does snow not stick to the fur of wolves and some breeds of dogs?

I couldn't find scientific references, but regular web searches basically indicate that long fur as well as webbed toes promote formation of ice and snowballs in certain breeds.

From Hubpages:

  The snow attaches to the dog's long hair, melts from the body heat, and forms ice balls that grow larger, stretching your dog's toes apart and causing cracking, bleeding, and hair pulling.  This is painful and distressing for the dog, who may then try to remove them by licking them, which then causes even more ice to build up.

And among the solutions:

  Clip the fur between your dog's toes. [J]ust trim off the excess fluff.

A typical breed thriving in icy conditions is the Siberian husky. A comparison to to an airedale terrier breed shows the difference in fur length quite clearly, especially around the areas most suceptible to come in contact with snow (legs & chest areas):

And both breeds in the snow:


What is the best way to express two proteins in a mammalian cell?

You can use a bidirectional promoter. The problem that you mentioned about proteins not expressed in same level happens because of competition for polymerase. But there are well optimized parts and also commercially available vectors that work fine.

You can clone genes in a serial order. It won't be a problem. Just leave a 100bp linker after the polyA signal of previous gene. If your cassette becomes too huge, then insertion becomes slightly difficult. That's why people use IRES or TA-peptides, etc.

Retroviral based insertions work quite decently, but you can't control copy number variation between different cells.

You can use two different promoters. The dynamics will depend on the promoter strength and concentration of inducer.


You are right, The main function of the epiglottis is to seal off the windpipe during eating, so that food is not accidentally inhaled.(quote from here).

It's a flat shield of cartilage, which is obviously an efficient valve, It's a valve between the trachea and the esophagus.

It lets lions to eat a pound of meat without choking on their prey. It lets humans drink tea without coughing on their buddies.

Information stating that it's "possible" to eat without an epiglottis doesn't imply that it's "efficient and safe", and contradicts medical interventions where they use a piece of ear cartilage to build a new epiglottis.

Survival didn't encourage the "possibility to eat"... it has made animals very robust and efficient at it. Herbivores can spend most of their day eating, and are often attacked while they are eating and drinking. Carnivores also have reasons for efficient swallowing, big carnivores can eat many pounds of meat very fast while fending off competition from hyenas and other predators.

Sleep apnea patients have their epiglottis modified to give room to breathe at night, and they risk choking and aspiration for a while, although they can adapt because they keep some of the cartilage, so they still have a valve.

Different animals have different breathing habits, with some being obligate nose breathers, including human babies of under 6 months and up to 6 years. That's because the epiglottis either contacts the trachea or it leaves space there.


Layman definition of genetic polymorphism?

Polymorphic sites

Consider the following sequence of DNA

ATTTGC

Now consider that in a population of 5 haploid individuals (in reality populations are larger of course) you have the 5 following sequences

ATTTGC
ATTTGC
ATCTGT
ATTTGC
ATCTGC

Looking at those sequences you can identify two sites (site 3 and site 6) for which the nucleotides vary throughout the population. For example, at site 3, 3 individuals have a T while 2 individuals have a C. Sites 3 and site 6 are said to be polymorphic sites (a.k.a. segregating sites).

Statistics of genetic variance related to polymorphic sites

Note that there are all sorts of ways to describe the genetic diversity in this population. You could calculate the total number of segregating sites or the average number of pairwise difference between any two sequence. Or the average expected (and not observed) heterozygosity (which is sometime refer to as genetic diversity). One could calculate the frequency distribution of the number of individuals carrying a given variant (called the site-frequency spectrum).

Other polymorphism

Note that I emphasized on polymorphic sites for the moment but there are a whole bunch of different reasons that two genomes may differ. Two sequences may differ in their length as well (insertions and deletions of nucleotides). Genomes may differ in the number of copy of a given sequence (copy number variation). Genomes may differ in the number of copy of very very long sequences or in the order of those sequences (synteny). Genomes may differ in their number of chromosomes or in their ploidy level.

About the citation

  In this area,there are six different chemotypes that are the expression of a genetically controlled polymorphism inT.vulgaris(24)

It is hard to say anything without the link to the article.

There are six different chemotypes (found in the population). Not all individuals have all chemotypes (eventually each individual has one or two chemotypes). Having one or another chemotype depend on your DNA sequence.

Assuming that the difference is due to polymorphic sites (which is impossible to say for sure without reading the paper), there is therefore one (or several) polymorphic sites that explain the variance in chemotypes in the population.


How are colors outside the standard RGB color scheme perceived?

This question is both biology and physics I think (I guess it's biophysics! :) so I feel it's worth answering here.

First, we must recognize the difference between wavelength, which is just a physical property of light, and color, which is by definition a human visual perception. The color "red", for example, is a particular visual sensation humans have when encountering light of certain wavelengths. A color cannot be described by a single wavelength number, because the light we see in nature is never monochromatic; it's a complex mix of photons of all sorts of wavelengths.

As John's answer also pointed out, the human eye has three types of cone cells which responds to wavelenghts differently, determined by their absorption spectra (see picture below; R represents the rod cells, which I ignore here). Human color perception can be described as a mix of signals from the L (long wavelength, red), M (medium wavelength, green) and S (short wavelength, blue) cone cells. Mathematically, this is a linear combination $l \cdot f_L + m \cdot f_M + s \cdot f_S$ of the three spectra $f_L$, $f_M$ and $f_S$. The coordinates $(l,m,s)$ generate the LMS color space, which by definition contains all colors humans can perceive.

Now for your question: what colors are outside the RGB scheme?

This depends on precisely what you mean by "the RGB scheme" and "color". The picture you posted is actually not an RGB scheme but a two-parameter color model known as CIE 1931, which is roughly the same as the LMS color space, minus a light intensity parameter. If by "color" you mean the human visual perception, then by definition there are no colors outside the LMS space.

On the other hand, there are many kinds of light that humans cannot perceive correctly: you can imagine from the figure above that there any many cases where two different wavelength mixtures give the same response. For example, a mix of "red" and "green" light may result in the same $(l,m,s)$ values as "yellow" light, even though this is physically different. And of course, some wavelengths our eyes don't register at all, but we usually don't consider such wavelengths as "colors".

Finally, if by "RGB model" you mean the types of light that RGB devices like your computer screen can produce, then the answer is that there are many colors outside RGB. This because RGB devices use light sources for R, G and B with different wavelength profiles than those of the cone cells. Therefore, a typical RGB device generates only some subset of the LSM space. For example, in the figure below, the triangle represents the colors generated by mixing three monochromatic R, G and B light sources in the CIE RGB space, one of many possible RGB spaces.


Difference between modules in KEGG Module

M00115 is a pathway module (NAD biosynthesis) whereas M00542 is a signature module (EHEC/EPEC pathogenicity signature).

From the KEGG page on modules:

  pathway modules – representing tight functional units in KEGG
  metabolic pathway maps, such as M00002 (Glycolysis, core module
  involving three-carbon compounds)
  signature modules – as markers of phenotypes, such as M00363 (EHEC
  pathogenicity signature, Shiga toxin)


Why are fibroblast used so commonly in cell biology?

From the comments by Shigeta and WYSIWYG :-

1.They are easy to get and they can be preserved and used over time.

2.They can be differentiated easily.

3.Due to historic reasons - someone getting lucky and finding a protocol for these cells.


Why is there disagreement on the number of surfaces of the human heart?

Heart surfaces are not clearly anatomically defined but arbitrary determined in the context of the heart orientation, that is the relation of the heart to other organs. Different sources mention 3 or 5 heart surfaces and there seems to be no "official" agreement about this.

Most sources (Dartmouth College, Gray's Anatomy for Students 2004...) agree about at least 3 surfaces:

Anterior (or sternocostal)
Inferior (or diaphragmatic)
Left pulmonary

Many sources (TeachMeAnatomy, KenHub...) mention additional 2 surfaces:

Posterior (or base)
Right pulmonary

The reasons for disagreement:

The heart base may not be considered a distinct surface (as in the picture).
The right pulmonary and anterior (sternocostal) surface are often considered one surface.

Picture: Heart surfaces (source: Echo Class 101)


Effect of respiration on Arterial pressure

Alan's pointing picture is this

I found this picture better

but not sure if it is exactly the level respiration to the arterial pressure.


This looks like the Satyr Comma or Polygonia satyrus.

Characteristic of this species is a dark border near the tops of wings, fading near the bottom. They are common across the Western United States and Southern Canada.

For more information on this species, try this link and this link.

To differentiate between moths and butterflies you can look at the anntenae. Butterflies often have a bulb at the end whereas moth antennae are feathery or saw-edged.


Are cytotoxic (killer) T-cells always present or are they only produced during a cell mediated immune response?

Naive T cells are regularly matured in the thymus where they're released into the blood. A majority are CD4+, but many are also CD8+. As a caveat, many are TCRαß+, and few are TCRyδ+ (outside the scope here but fun to look up and read).  From there, they home to the lymph node where they hang in the T cell zone until blood trafficking signals coax them into the blood. T cells regularly navigate the body in response to signals from different cells such as blood vessel endothelium, lymphaptic vessel endothelium, epithelial cells, and so forth (1).

The basic process behind an adaptive immune response is that antigen-presenting cells get ahold of foreign antigens and head back to the lymphoid organs like lymph nodes. By the time they get there, they've matured into "licensed" professional antigen-presenting cells. They interact with both CD4+ or helper T cells, and CD8+ or cytotoxic T cells. It's more complex than that, but the point of the helper T cell is to produce "help" signals. These include IL-2, and other cytokines which not only assist the CD8+ T cells in their activation, but also determine a lineage they'll take based on other factors.

So they're both there, in the lymph node at the time the antigen-presenting cell, such as a dendritic cell, arrives to activate the lymphocytes in that region. Take home point: the naive lymphocytes are there until they are activated, in which you would be correct in your last line. But they do actually do things other than sit there, other take home point. They aren't simply anergic and waiting.


The way neuroscientists currently think about storage in the brain, it doesn't make any sense to think about "duplicate" data but rather about the "robustness" of a given memory to interference or confusion, which increases with consolidation and reconsolidation of memories or can degrade over time.

Repeated exposure can contribute to the robustness of a memory, but so can other factors such as the emotional content of a memory (which, depending on the emotional state, can increase or decrease memory robustness, and this can also vary with the "jist" versus "detail" of a memory).

Note that there are also very different types of memory, so that repetition is very important for motor plans and "muscle memory" whereas episodic memory can get lost in the repetition of daily recurrent events, such as parking your car or eating lunch: you might remember where you parked or ate today, but if you have a routine this can blur into all one memory, where you have a notion of eating at a particular restaurant many times, but you would struggle to remember specifically eating there on December 14th, 2011, unless there was some other special event on that day.

In your example of reading a book, there would likely be two types of memory: 1) memory for the episodic event of reading the book, which would be a separate memory because it is a separate event, though it could be confused with other similar episodic events. 2) Semantic memory for the content of the book: this would be a single memory, reinforced with subsequent readings of the book, and supplemented with all your other semantic experience with the content of a book: discussing the characters of a fiction book with your friends, learning about molecular genetics from a textbook and from a lecture course, etc.

Note also that talking about the "data capacity" of a human brain compared to a computer is a bit silly, because data isn't stored in the nervous system in bits, and a "fair" accounting of human memory needs to consider the vastly multidimensional interactions that are easily coded in a nervous system but not at all easily in a binary system. Note that other papers have come up with estimates that diverge greatly from the numbers you cite, for example Wang et al 2003 which gives a value of 108432 bits based on the number of synaptic connections. That number is truly inconceivable to our conscious experience even if it is within the capability of our brain. Clearly there are other limiting factors not involved in a simple binary system, for example confusion with similar memories, and there are types of memory that computers excel at (such as the pixel values of an image) whereas human memory deals in abstractions and hierarchical representations.

References

LaBar, K. S., & Cabeza, R. (2006). Cognitive neuroscience of emotional memory. Nature Reviews Neuroscience, 7(1), 54-64.

Walker, M. P., Brakefield, T., Hobson, J. A., & Stickgold, R. (2003). Dissociable stages of human memory consolidation and reconsolidation. Nature, 425(6958), 616-620.

Wang, Y., Liu, D., & Wang, Y. (2003). Discovering the capacity of human memory. Brain and Mind, 4(2), 189-198.


Research from the early molecular genetics era that supported protein as the primary carrier of genetic information?

It’s difficult to be convincing with a negative answer, but I venture that the answer to your question is that the idea that protein was the genetic material was not supported by any experiments, but was a supposition based on the conventional wisdom that proteins were more complex and therefore more suited to the job.

I suggest that you should be thinking earlier than bacteriophage and Hershey and Chase. Bacteriophages only came into genetic research after the war, and the Hershey/Chase experiment (1952) was only a rigorous confirmation of the conclusion of Avery et al. in 1944 (mentioned in this Scitable article). The system that Avery et al. used (bacterial transformation) went back to Griffiths in 1928 and must have been the first that allowed any sort of experimentation in this area. And I think it was more a question of working out what was happening than devising an experiment to distinguish between protein and DNA as the genetic material.

To my mind this illustrates something about how science progresses. It is often dependent on advances in technology and changes in the conceptual framework in which scientists work. (Sometimes — e.g. Mitchell’s Hypothesis — it needs the experimental results to change that conceptual framework.) Coming back to the Hershey/Chase experiment, this was performed when the balance of scientific thought had already changed to DNA as the genetic material.

Footnote: It’s earlier than you think

I generated the Google ngram below to put the term you use, ‘molecular genetics’ into historical perspective.

This shows that the term ‘molecular genetics’ was hardly in use at the time of the Hershey–Chase experiment and Watson and Crick’s postulate of the structure of DNA in the early 1950s. I think that this reflects the fact that the concept was not current. The more popular term, ‘molecular biology’ gained currency on the basis of the structural work on DNA and proteins, and the name of the journal in which much of the work was published (Journal of Molecular Biology). The question is assuming a state of science that did not actually exist before the 1950s.


Book recommendation on selective breeding?

I will Suggest:

Selective Breeding in Aquaculture: An Introduction

Authors: Trygve Gjedrem, Matthew Baranski

ISBN: 978-90-481-2772-6 (Print) 978-90-481-2773-3 (Online)

http://image.slidesharecdn.com/selectivebreedinginaquaculture-anintroductionreviews-methodsandtechnologiesinfishbiologyandfisheries-140725230642-phpapp01/95/selective-breeding-in-aquaculture-an-introduction-reviews-methods-and-technologies-in-fish-biology-and-fisheries-10-1-638.jpg?cb=1406347865


Adjustment = a small alteration or movement made to achieve a desired fit, appearance, or result; the process of adapting or becoming used to a new situation (Google Dictionary).

Adjustment is a very general term; it doesn't mean anything specific in biology or other sciences and it can cover all the terms you've mentioned: adaptation, acclimatization and even learning.

If you check in Thesaurus.com, you can see that synonyms for adjustment include acclimation, acclimatization, modification and improvement, and that one of the synonyms for adaptation is adjustment.


Does conjugation support gene selection?

Interesting Question (glad the "group selection" post got you thinking!)

Me and two friends thought about your question during our Biology BSc at ICL (in fact we also thought about an even more puzzling phenomenon called "bacterial transformation" which is like conjugation, but they incorporate genes from dead bacteria!!) our first year course convener recognized our answers as "most likely candidates" so here they are:

1. Stress-induced Experimentation Hypothesis

The likelihood of conjugation/transformation occurring may change for a bacterial population as a whole depending on how stressed it is (or perhaps how unfamiliar the environment is?). Stress signals could cause the population to be more "risky" and take up the DNA from surrounding living/dead bacteria and incorporate it with its own genome: "the hell, we're out of options.. lets transform into something that resembles the indigenous species of this strange ecosystem!". Indeed Bacteria have memory (see: chemotaxis) this means that perhaps they can be able to tell whether they have been receiving more stress now as opposed to before, meaning they can "trial and error" with various genes that have been imported within their plasmids! — "Let's try this gene, oh wait... I'm dying, hmm let's kill off this plasmid and take some more genes!".

In reply to this my course convener said:

  "ah yes, a switch from asexual to sexual reproduction occurs in
  many organisms under stress. The genes that cause the
  sex/transformation to occur may gain a net benefit from recombination
  with genes taken from other organisms/the environment."

2. Diversity Plagarism Hypothesis

If we look at the entire population of conjugating bacteria as a single competitive unit itself (e.g. like a tissue is a coordinated group of specialized cells) that can compete with other populations of bacteria who cannot conjugate the conjugating population will "win". This is because a conjugating population will always have much higher phenotypical diversity as it can mix traits between the individuals. This means a conjugating population is much more efficient at undergoing natural selection for beneficial traits or trait combinations.

Think of natural selection (coupled with mutation) as an inventor... something that helps you invent much "fitter bacteria" is the ability to pull things apart from this bacterium and that bacterium and glue them together, this is essentially what conjugation/transformation does!! it allows you to pull bits from this bacterium and stick it to bits from that bacterium to get a "super-bacterium". It's like open source technology (free to share) as opposed to patented technology!! Conjugation is immediately a good thing because it means you can "steal" cool technology from living/dead bacteria and incorporate it into your population's gene pool!

Hope this was helpful!


Recessive alleles at Hardy-Weinberg equilibrium

Let's go through the possible answers. Which of the following could be predicted? Not (1), because we don't know whether selection favors or disfavors the recessive alleles. Not (2) for the same reason. Not (4) by definition. Not (5) because recessive alleles don't magically become dominant.

This leaves us with (3), which also seems correct: not only do we know that frequencies don't change under the Hardy-Weinberg assumptions, but also an equilibrium is by definition a state at which frequencies remain the same.

An aside: this question fairly clearly recalls G. Udny Yule's confusion about the fate of recessive alleles, which lead Punnett to enlist G. H. Hardy's help in deriving Hardy-Weinberg equilibrium. Yule expected recessive alleles to decline in frequency by virtue of their recessiveness; Hardy showed otherwise.


How are cell death like apoptosis and entropy related?

Unless you have a closed system, don't bother with the second law. These sound like some poetic descriptions but they won't tell you much about biology.

  It is argued that cell senescence is due to the accumulation of defects and wastes, but cell death could have a more active implication of carrying away the debt caused by utilizing information.

The first part of sentence which I italicized here is sufficient to understand the biology: cells age and die off because they accumulate defects. Organisms, whether single-celled or multi-celled, ultimately get around this by making lots of copies of themselves and expecting some to fail.

The second part of that sentence says "could" and is poetry to describe the first half, as well as the sentence that follows. It doesn't add any more science, unless you care about the existence of "entropic altruism" in the universe, which sounds to me like a religious rather than scientific approach. It's just stating that cell death (and perhaps, to an extension, death of multicellular organisms) can be useful to organisms/species rather than merely destructive. There is nothing wrong with finding beauty in physics and mathematics, but beauty in itself says nothing about how things work or how things should be.

In the context of a multicellular organism, cells kill themselves to not kill/harm the whole organism (e.g., to not develop into cancer, or as a planned event during development). The biological reason they do this is because multicellular organisms that have evolved genetic mechanisms to identify potentially harmful cells and have those cells die are more likely to reproduce and produce more multicellular organisms like themselves. If you want to interpret this as "entropic altruism" because cell death increases entropy, that's fine, but no thermodynamic argument is needed or even all that helpful in explaining the biology.

Note also that the book you cite doesn't seem to be in common use; it has no reviews on Amazon or Google books, and a previous book by the same author only has 1 review. I don't have anything against the author and they could be an excellent statistical physicist, but language like this makes me think they are not a biologist.


How many gigabases of DNA are there on earth?

If you simply take one order of insects, Coleoptera, there are just under 400,000 described species with estimates from 850,000 to 4,000,000 species total in just this order.  The number of primates is under 1,000.  If your assumption of say 10MB for all other primates would be accurate, just adding in the low end estimate of 850,000 at 10MB per 1000 we are quickly at 8,500GB which seems to be a factorial out of the GB range.

So, we have a broad estimate of non-bacterial of plants, animals etc. at say 8,700,000.

Jason Gans found in a 1 gram of soil survey approximatly 1,000,000 bacterial species.

SO the total accounting for species number is totally impossible to estimate for anything at this time, let alone the genome.

Even for something as "common" as a giraffe, there are up to 9 sub-species with genome differences within each subspecies.

So, once we get them all decribed, we can then work on the genome sequence for each and get you some answers!


Storing Taqman plates with polymerase in fridge before running

Not sure if this question is still valid, but it was marked as unanswered and frequently viewed, so here's a go :)

These days most polymerases (certainly for Real Time PCR) are so-called Hot Start enzymes (ask your manufacturer, because they save you a whole lot of trouble!). They are modified with a protein that prevents them from working until activated at 95 deg. Celsius. Be aware though that not all hot start enzymes require the same activation time at 95 deg. Celsius, and some enzymes lose activity when activated for 15 min. at 95*C instead of 2 min.

In my experience storing plates at 4 degrees (or room temperature) is not a problem at all, and most manufacturers advertise that the PCR mixes (including primers, probes and DNA) are stable at room temperature for 24 hours. You do however need to protect the mixtures from (sun)light because the probe might be damaged when exposed for longer times.

Personally, I would not recommend storing real-time PCR plates in the freezer, because condensate will most-likely form when you thaw your plates. This can influence the PCR, as real-time PCR uses light for the analysis of your samples.

If you want to save yourself some pipetting, but can't prepare plates in advance, you can prepare a primer-and-probe mix, which you can freeze in batches. In our lab, we keep a stock of primer-and-probe mix for every assay. Maybe this also works when you already add water and PCR mastermix, but I have never tried. I wonder how other people do this, so please leave a reply.

Hope this might help some people.


DNA quantification in a high school bio lab

Within some linear range, the intensity of stained DNA bands in a gel is directly proportional to their mass. By making a standard curve from bands of known mass, the mass of unknown bands can be estimated. This process is called densitometry. I wrote briefly about its use in quantifying protein bands after SDS-PAGE in this answer, but I'll go into more detail on how this is done using the following ethidium bromide stained gel:

On the right is a molecular weight marker (BstEII digest of λ DNA) with bands of known mass. On the left are two bands of unknown mass (actually a double-cut plasmid).

I use a free program called ImageJ to estimate band intensities. They have a tutorial on measuring band intensity here. You can also get ImageJ packaged with Java (and bunch of other stuff) in the software Fiji.

Open the image in ImageJ and use the Rectangle tool to draw a box around the marker, then select Analyze > Gels > Select First Lane (or shortcut Ctrl+1). Next, drag the box over to surround the other lane and select Analyze > Gels > Select Next Lane (Ctrl+2). Now select Analyze > Gels > Plot Lanes (Ctrl+3) to plot image intensity as a function of position on the gel:

The area under each peak (minus the background noise) represents the some total of intensity for each band. To measure this area, use the line (Straight) tool to draw bounds on the base of each peak:

I've done it somewhat haphazardly here, but you get the idea. Now, using the wand tool, click inside each peak and ImageJ will tabulate the integrated intensity of each. Shown below are the intensities of the marker bands (with the top band being Band 1) as well as their masses (which are known):

          Mass (ng)    Intensity
Band 1    45           5319.891
Band 2    28           3816.234
Band 3    24           3256.406
Band 4    16           2298.749
Band 5    15           2074.749
Band 6    8            1084.991

Take this data into Excel (or similar) and plot intensity as a function of mass. Band 1 looks like it is outside the linear range and is underestimating the mass. This was actually expected since, if you look closely at the band in the gel image, there are red pixels indicating that it is oversaturated. Ignore this band and perform a linear regression on the rest.

The regression gives the equation $I = 134.74M + 53.988$ with $R^2 = 0.9975$. Rearranging for mass, we have $M = \frac{I - 53.988}{134.74}$. Get the intensity of the unknown bands as described above and calculate their mass with the preceding equation:

          Mass (ng)    Intensity
Band 1    27           3736.991
Band 2    15           2125.284


Why aren't circadian rhythms exactly 24 hours long?

Biological/organic systems are notorious for imprecision, making a perfect 24-hour cycle practically impossible - nevermind the fact that "hours" are a purely artificial concept that humans invented to help make sense of time.

The simplest "close-enough" way to measure days that doesn't require an implanted clock microchip or heavy computing power is to detect extreme changes in light or temperature associated with transition between day and night.

An extra argument against hard-locking to a 24-hour cycle: Adaptability and migration. If every life form is locked to a strict 24-hour cycle with fixed time slots for sunset and sunrise, this limits migratory adaptation since different regions have different sunset/sunrise and day lengths at different times of the year. Timing a wake-up and sunrise and sleep at sunset (or the reverse among nocturnal species) generally works across most of the planet no matter the season (the only exception being the niche case of a solstice at the poles, for example http://www.slate.com/blogs/bad_astronomy/2016/06/22/why_does_the_sun_never_set_at_the_north_pole_in_the_summer.html )

There's also some evidence that days on Earth are getting longer ( see
https://www.space.com/40802-earth-days-longer-moon-movement.html )


The first two sentences of the Wikipedia Ribosome article say:

  The ribosome... serves as the site of biological protein synthesis (translation). Ribosomes link amino acids together in the order specified by messenger RNA (mRNA) molecules.

Slightly later, in the Overview section it says:

  Ribosomes can bind to a messenger RNA chain and use its sequence for determining the correct sequence of amino acids for generating a given protein. Amino acids are selected, collected, and carried to the ribosome by transfer RNA (tRNA) molecules, which enter one part of the ribosome and bind to the messenger RNA chain. It is during this binding that the correct translation of nucleic acid sequence to amino acid sequence occurs.

And it then tells us "The attached amino acids are then linked together by another part of the ribosome."

So, the function of the ribosome is to make sure each codon of the mRNA is matched up with the correct tRNA, and then to catalyze the linkage of the associated amino acid to the growing chain of the protein being built.


There are two ways of classification of Prokaryotes(on the basis of mode of nutrition) that you will generally come across:
Way 1

Way 2

The First classification is very much based on a complete segregation between respiration and photosynthesis. In the first classification, anything that needs another animal to get food is a 'Heterotroph'. (Here, chemotroph and chemoautotroph are the same things)

But Generally the 2nd Classification is preferred, because prokaryotes have some very unique nutritional habits that cannot be explained on the basis of 'Eating/Not Eating'

In a way synthesis is the creation of a carbon compound by use of some energy.
So we need to classify based on energy and carbon source. Here organic carbon source means it is a 'hetero'troph and inorganic means it is an 'auto'troph. Similarly if Light energy is the direct energy required, it is a 'Photo'troph and if a chemical compound is required it is a 'Chemo'troph

By the First Classification, there are no 'Chemotrophic/Chemoautotrophic eukaryotes' meaning no eukaryote can produce food from inorganic material using chemical energy.

But by the 2nd Classification, essentially all eukaryotes that do not photosynthesize, instead use organic compounds as a food source, all animals, fungi etc. are 'Chemoheterotrophs'*However no Eukaryote is a 'Chemoautotroph'


Although we think of parasites as harmful and tend not to consider them for conservation, they do peform valuable functions including population regulation and the development of immune systems. More philosophically, under the 'intrinsic value' argument sometimes used for conservation, every species should be considered to have an intrinsic right to existence, regardless of its ecosystem function, harmful effects on other species or appeal to humans.

Conveniently, this article has just been published on this very subject. :)


For H3K9me1:

H3: name of the histone
K9: amino acid and position (K = lysine, position 9) of modification
me1: modification (me = methylation, ac = Acetylation), and number of modifications

So H3K9me1 means that the 9th residue (lysine) of histone H3 was monomethylated. Similarly H3K9Ac means that same residue was acetylated.

Wikipedia gives a decent explanation of the nomenclature of histone modifications, and there is also a more detailed table in Nature Structural & Molecular Biology.


When giving blood, what is the specific Iron measurement they take?

Most likely they were measuring the hemoglobin concentration, in units of g/dL (i.e. 101 kg/m3). Assuming by your username you are male, the reference range for [Hb] is approximately 13.8 to 18.0 g/dL (sources vary somewhat), which roughly matches the "19" you were told was the upper bound.

Wikipedia also notes that [Hb] "is typically tested before or after blood donation", making it likely that that was what they measured.

Calling it "iron" isn't strictly correct. The human Hb tetramer's molecular weight is about 65 kDa, yet it contains only 4 iron atoms, so the actual concentration of iron in your blood is actually much less.

Useful resource: Wikipedia's list of reference ranges for blood tests has a very detailed chart of commonly cited reference ranges for many substances, with citations.


Determining limiting nutrients from a graph

The control graph shows the baseline against which we can compare the other graphs. It is the graph without any changes, and hence is the graph in which one of the nutrient is limiting.

In the graph for +P, there is no rise in biomass and the graph resembles the control. This shows that Phosphorous is not the first(initial) limiting nutrient, as its addition did not affect the biomass production.

The +N graph shows a significant rise in biomass, indicating that N was indeed the initial limiting nutrient. On its addition, the biomass production increased.

The +N and +P graph shows a higher biomass than +N and the control. This indicates, that while  N was established to be the first(initial) limiting reagent, addition of Phosphorous also significantly improves the biomass yield, and hence P must also have become a limiting nutrient once N was added and its limiting effect removed. That is the reason why +N+P graph is higher than just +N graph. If phosphorous would not have been limiting even on addition of N, then the +N+P graph would have resembled +N graph.


Gibbs free energy and entropy in enzyme catalysis

As @canadianer hinted, the answer is enthalpy.

ΔG = ΔH - TΔS

For binding to be a spontaneous process ΔG must be negative. If the binding of a ligand to a protein decreases system entropy then ΔS is negative and the entropy term -TΔS is positive. However ligand binding involves the formation of various protein-ligand interactions (hydrogen bonds, ionic interactions, van der Waals interactions) all of which make a negative contribution to the change in enthalpy, so ΔH is negative. If |ΔH| > |TΔS| then ΔG will be negative.

This simplified account ignores the parallel changes taking place due to the ligand 'dissociating' from the solvent.


Alignment of sequenced fragments in Next Generation sequencing (sequence assembly)

Assembly and alignment are generally used to refer to two different algorithms that work in two different ways.

Alignment takes your sequence fragments, and compares them to a reference genome, and tells you where that read aligns and how closely it aligns.  For a while, popular aligners used Burrows-Wheeler transform algorithms to make special indexed versions of the genome, this made alignment to the index far faster.

Assembly is when you have no reference, and use the overlap of the reads to build large contigs.  For a while De Brujin graphs were a popular algorithm for that.


I've answered a related question, which was wondering why older people get more cancer from accumulated DNA damage and yet their children aren't immediately susceptible to it, here:
https://medicalsciences.stackexchange.com/questions/19915/why-do-age-related-dna-transcription-errors-not-manifest-in-children-as-readily/
Quoting from my answer there:

...a parent does not pass on all their mutations in all their cells, they pass on just one, which need not have any deleterious mutations at all, even if the parent has cancer themselves in some other part of the body.

If that one cell is defective in some way, it is less likely to be involved in creation of a successful pregnancy, and may lead to miscarriage. Therefore, the probabilistic process of reproduction tends to result in offspring from selection of healthier gametes.

There are in fact mutations that accumulate in gametes, but if any of those mutations are very serious, they are unlikely to support development of an entire new organism, and they are also relatively few. The burden of age on the genome is spread over all the cells in a body, and worst in types of cells that divide the most, when errors are most likely to occur.


How to predict the effect of a non coding SNP variant on the expressed protein?

A) Generate exon & transcript counts for your samples, library size + quantile normalize the data.
B) Group samples into variant/wild-type categories
C) Use wilcoxon's rank sum test to see if there are differences in exon inclusion or overall expression. Remember that 3'UTR variants can also imply differential degradation by miRNA. Tools like TargetScan can help you with miR-analysis.


Can heritability be deduced from a correlation coefficient?

No. But a strong correlation may nevertheless be an indicator for heritability (it makes it more likely).

The reason is, that the correlation in the phenotype (birth weight) is not only due a correlation in the genotype but also a correlation in the environment of the child and its mother (culture, economical situation, genes, etc of their respective mothers).

If you were able to remove the association of the environments and of the genotypes and the environments by an intervention (eg. shuffling the zygotes (ideally of parents who were shuffled as zygotes as well)) then the correlation coefficient of the phenotype between one of two parents and the child would be half the heritability. $corr=\frac{1}{2} H^2$

Phenotype ($P$), Genotype ($G$), Environment ($E$)

$P_{parent}=G_{parent}+E_{parent}$

$P_{child}=G_{child}+E_{child}$

$
\begin{eqnarray*}
corr(P_{parent},P_{child}) &=& \frac{COV(P_{parent},P_{child})}{\sqrt{VAR(P_{parent})}\cdot \sqrt{VAR(P_{child})}} \\
&=& \frac{COV(P_{parent},P_{child})}{ VAR(P)}\\
&=& \frac{COV(G_{par}+E_{par},G_{chi}+E_{chi})}{ VAR(P)}\\
&=& \frac{COV(G_{p},G_{c})+ COV(G_{p},E_{c})+ COV(E_{p},G_{c})+ COV(E_{p},E_{c})}{VAR(P)}\\
&=& \frac{\frac{1}{2}VAR(G)+ COV(G_{p},E_{c})+ COV(E_{p},G_{c})+ COV(E_{p},E_{c})}{VAR(P)}\\
&\overset{(1)}{=}& \frac{\frac{1}{2}VAR(G)}{VAR(P)}\\
&\overset{(2)}{=}&\frac{1}{2}H^2
\end{eqnarray*}
$

$(1): \,\,\,$if you managed to get $COV(G_{p},E_{c}), COV(E_{p},G_{c}),COV(E_{p},E_{c}) = 0 $

$(2): \,\,\,H^2=\frac{VAR(G)}{VAR(P)}$ - the definition  of heritability


How do cells figure out the big-picture shape?

Hands are complicated and the genetic machinery behind their shape doubly so.

It's easier to figure out worm segments first, and then work up from there. An egg has head/tail information encoded in it even before fertilization: see here

You can imagine the first or second cell division would give a 'head' cell with higher concentration of head polarity transcription factors. These transcription factors switch on other regulatory genes, and the complexity works upwards from there. For more information about how worms and other segmented animals work out what goes where see Hox genes. The sad truth is that most of how this is done is unknown or not well understood.


Easy derivation of Kimura's approximation for the probability of fixation of a mutation

Presumably you've solved this, but, in case not, it's because the PDE is a Kolmogorov backward equation, so the first and second order coefficients are the mean and variance of the underlying stochastic process being modeled.

In detail, consider a stochastic differential equation (which has a solution given by an Ito diffusion process):
$$ dp_t = \mu(p_t,t) dt + \sigma(p_t,t) dW_t $$
then the following system holds (under some conditions):
$$ -\frac{\partial}{\partial t} u(p,t) = \mu(p,t)\frac{\partial}{\partial p}u(p,t) + \frac{1}{2}\sigma^2(p,t)\frac{\partial^2}{\partial p^2} u(p,t) $$
where $u$ is the density of $p$ at $t$.

Note that the drift (infinitesimal mean) $M=\mu(p,t)$ and diffusion coefficient (infinitesimal variance) $V=\sigma^2(p,t)$ are as in the paper (except for the negative sign, which I assume is ignorable since he mostly seems to care only about the case when $\partial_t u\approx 0$ anyway).
Indeed, they are equivalently written:
\begin{align}
\mu(p,t) &= \lim_{\delta t\rightarrow 0}\frac{1}{\delta t} \mathbb{E}\left[ p_{t + \delta t} - p_t \mid p_t=p \right] =: M \\
\sigma^2(p,t) &= \lim_{\delta t\rightarrow 0}\frac{1}{\delta t} \mathbb{E}\left[ (p_{t + \delta t} - p_t)^2 \mid p_t=p \right] =: V  \\
\end{align}
as Kimura writes.

Note that a useful approximation of the transition density is given by:
$$ \mathbb{P}[p_{t+\delta t} \mid p_t] \approx
\mathcal{N}(p_{t+\delta t}\mid p_t + \mu(p_t,t)\,\delta t, \sigma^2(p_t,t) \,\delta t) \tag{TD} $$

Ok, so everything above is just basic stochastic processes theory. Thus, if we have a stochastic model for the population dynamics, we can derive values for $M$ and $V$ from it (by computing its moments), and those will carry over to the backward Kolmogorov equation, upon which Kimura's work rests.

Here is where my ignorance of population dynamics shows. However, since Kimura mentions Fisher and Wright, I looked up the Wright-Fisher model.
It seems like Kimura is using the diffusion process approximation of the Wright-Fisher model.
This appears to be a well-studied and storied model that I cannot fully describe here; instead, I found the work by Tataru et al, Statistical Inference in the Wright–Fisher Model Using Allele Frequency Data to be an excellent description of it, though I do not pretend to understand much of it.

What's important, however, is that the change in genes (transition density) can be described by a binomial distribution. This can be approximated by a normal distribution:
$$ \mathbb{P}[p_{t+\delta t} \mid p_t] \approx \mathcal{N}(p_{t+\delta t}\mid p_t + a(p_t) \delta t,\, p_t (1-p_t) \delta t ) $$
using the standard approximation to the binomial.
This then gives us a forward Kolomogorov equation (not backward) written:
$$
\frac{\partial}{\partial t} u
=
- \frac{\partial}{\partial p}\left[a(p_t) u(p_t) \right]
+
\frac{1}{2}\frac{\partial^2}{\partial p^2} \left[ p_t(1-p_t)u(p_t) \right]
$$
This basically implies that $V=p(1-p)$.

( I noticed that another way to prove this is to notice that the Wright-Fisher approximate diffusion (without any selections, etc... so $a\equiv 0$) has an infinitesimal generator given by: $ \mathfrak{G} f(p) = p(1-p)\partial_{tt} f(p) / 2 $. This immediately implies $V=p(1-p)$. But may be less straightforward to understand. )

Confusingly, however, the paper has changed timescales (variables), so that $\delta t \leftarrow \Delta t / (2N)$, and then set $\delta t$ to $1$ (probably so that they would not have to write $2N$ everywhere).
If we undo this transform, we get
$$ \mathbb{P}[p_{t+\delta t} \mid p_t] \approx \mathcal{N}(p_{t+\delta t}\mid p_t + a(p_t) \delta t,\, p_t (1-p_t) \delta t/(2N) ) $$
If you compare this to our approximate transition density above (equation (TD)), you will see that this implies: $$ \sigma^2 = V = p(1-p)/[2N] $$
as desired.

Now, what is the infinitesimal mean, i.e. $a$ or $M$? Clearly this depends on the selection model, since it controls how the "environment" deterministically affects the process. Kimura describes this as a "constant selection advantage" with coefficient $s$.
The Tataru paper notes that the diffusion approximation to Wright-Fisher under genetic drift, mutation, and selection is given by:
$$
a(p) = -\nu p + \xi(1-p) + 2N\tau p(1-p)[h-(1-2h)p]
$$
If we (1) ignore mutation by setting $\nu=\xi=0$, (2) remove allelic dominance effects by setting $h=1/2$, and (3) define $s:= N\tau$, we get:
$$
a(p) = s p(1-p) =: M
$$
which of course we see by noting $M=a(p)$ matches $\mu$ in the equation (TD) above. (Note that the $2N$ transform also occurred here, but it was hidden inside $s$).

Thus, we have derived where Kimura's $M$ and $V$ come from, albeit probably not in the simplest possible manner.

All that remains is to derive the (steady-state) equation for $u$. I guess I'll do it for completeness.

Ignoring the steady-state subscripts, we get:
\begin{align}
G(x) &= \exp\left( -\int \frac{2M}{V} dx \right)
     = \exp\left( -\int 4sN dx \right)
     = \exp\left( -4sNx\right) \\[0.15cm]
u(p) &= \frac{\displaystyle \int_0^p G(x) dx}{\displaystyle \int_0^1 G(x) dx}
     = \frac{\displaystyle \frac{1}{4Ns}\left[ \exp\left( -4sNx\right) \right]_0^p}{\displaystyle \frac{1}{4Ns}\left[ \exp\left( -4sNx\right)
\right]_0^1}
     = \frac{\displaystyle -\left[ \exp\left( -4sNp\right) - 1 \right]}{\displaystyle -\left[ \exp\left( -4sN\right) -1
\right]} \\
&= \frac{1 - \exp(-4Nsp)}{1 - \exp(-4Ns)}
\end{align}
as required.

Apologies for any errors. (I am neither a population dynamics modeler nor a mathematician, so please point out any problems).


Physical activity in fasted state: Glucose for brain vs muscles

In general it is the reciprical action of the hormones of the fed and fasted state — insulin and glucagon — that are responsible for this, together with the differences in hormone-sensitivity of the glucose transporters in muscle and brain. See the accepted answer to this question: During starvation, does the human body do anything to prioritize which organs receive nutrients?.


What type of spider is this that just decided to stop my plans of sleeping

It is a male Steatoda, probably S. grossa (picture below).  These spiders are often called False Widows, since the females are generally a large purply black and look similar to their cousins the Black Widows. Steatodas are pretty harmless, though, although a couple of species (in the UK/Europe) are known to sometimes produce bite effects like a mild Widow bite.  Not at all dangerous, but a little disquieting if you're the one that gets bitten.  Presuming that you're in North America, though, you're fine.  Steatodas are Theridiid ("cobweb") spiders common in and around houses, and the harmless males are often encountered when they wander around looking for love as adults.

Bug guide has a good section on S. grossa, including lots of images of male spiders like this one.

https://bugguide.net/node/view/6932

Information on Steatoda envenomation is broadly available, but not in great detail.  The Wiki entry appended below covers the ground as well as any of them.

https://en.wikipedia.org/wiki/Steatoda