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Is there a risk of localised die-off when plants bud too early?
I've been taking a few walks in the countryside in Scotland and England this winter (end of December 2014). Some parts of England haven't had any frosts yet, which is very unusual, and it's been generally quite warm since summer ended.
My friends and I agree that there's quite a lot of stuff putting out shoots and buds, as if it's April already. I can imagine that this means a lot of small fragile plants could get killed if a hard frost comes in the next few weeks. If so, it seems natural to expect that next summer will be marked by an absence of these plants, and, being dead, they won't put out seeds or otherwise reproduce for next year. In other words, we're expecting some species to experience localised die-off.
Is this plausible or are we just imagining it? If it's actually happening, is it something to actually be worried about? i.e. will a large portion of the seeds/shoots/buds/whatever refrain from growing even if some are being tricked by the mild winter, or will they be cold-resistant if they're coming up now, or is some other mechanism going to make it all okay? Alternatively, is this winter likely to trigger a large ecological change?
I realise this question doesn't single-out any particular species for attention, and perhaps it's too much of an open question for StackExchange's taste, but I'd very much appreciate some insight into how fragile or robust is the distribution of British plant life when the weather is abnormal, as it is right now.

If you're talking about shoots or buds coming out of individual seeds, then those plants are probably doomed. Most seeds are "designed" as one-shot delivery packages. In this case, they'll bud, be killed off by a frost at some point during the winter, and then be spent.
For a perennial plant like a tree that buds year after year, the impact of an early blooming will depend on the species. As per a Q&A from Cornell (Will Warm Winter Wither Plants?, 2007), most plants growing in a temperate climate (like that of Britain) will have experienced warm winters before and will have at least some evolutionary adaptations to help them deal with occasional aberrant weather. For example, even if you do see some fresh buds on a tree this time of year it is likely that the majority of its bud primordia (the parts of the plant that will someday become buds) have not developed. Although you won't see regrowth in the spring of most of the buds that opened early, you will see normal development of the buds that stayed dormant during the winter.
As for the question of wider ecological change, one anomalous year isn't going to make a difference because, as you say, a large portion of the seeds/shoots/buds/whatever refrain from growing even if some are being tricked by the mild winter. However, if a string of mild winters cause significant die-off year after year you would start to see changes in the ecosystem. It works the same way for many with loosing their hair...


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Can the eye distinguish between pure and composite colours and how do we measure this?
Red light plus green light makes yellow light.
Suppose I shone a pure red light, say 650nm, onto the same spot as a pure green light, say 550nm. The eye sees this two-peak spectrum as yellow.
This presumably means we are tricking the eye, since a pure yellow light source would also be perceived as yellow.
Do the cells on our retina treat composite spectra equivalently to corresponding single-peak spectra? If not, how do we quantify the gap?

I don't think it is perhaps quite right to think of light and light perception in this way, you are trying to make two continuous variables in to discrete groupings

Yes, we do perceive a composite spectrum in a way which is analogous to how we perceive the corresponding single-peak spectrum. Human beings have trichromatic vision, meaning that there are 3 types of specialized cells in our eyes for seeing color. Each one has a different color of light which produces peak stimulus, although they all perceive a range of colors:

(the axes are wavelength and normalized response)
None of the color-sensing cells has a peak color of yellow. In order to perceive something as being yellow it either has to be pure yellow or stimulate the 3 types of color sensing cells in a very similar way as pure yellow would. However, if you took very careful readings of the output signals from the color sensing cells you might see some subtle differences in the exact waveforms of the responses.

What tel explained is correct. I wanted to add that we actually see pure light in a composite way too.
Note for example that the M receptor has a peak at around 550nm, and a symmetric response curve. So, if you shine a 540nm light, the response of the M cone is the same as the response at 560nm. So, how do we know that it's a cool, bluish green and not a warm, yellowish green? By the response of the other cones. The ganglion cells in the retina combine the response of several cones to represent the wavelength of the light perceived by the photoreceptors (as well as some other attributes of the image within their receptive field).
As for "tricking" the eye, we're doing it all the time. Higher levels of visual processing will interpret colors depending on everything else perceived in the picture, such as light intensity, texture, and even cultural knowledge about colors. A mostly unbiased representation of wavelengths is only present at very early stages of visual processing.

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Is there a scientific explanation for male and female fragrance preferences?
The following is only anecdotal evidence, but in my experience it's very consistent.
When products have added fragrance (cosmetics, soap, air freshner, candles, etc), women often seem to enjoy the fragrance whereas men's reaction is normally something from indifference to outright revulsion.
I've tried googling this but the results are all about sexual attraction, which I'm not asking about.
One could speculate that this pattern is because the folks in marketing have worked out that adding fragrances will make women buy things and that as far as men are put off by fragrances, that doesn't have a net negative sales impact. But such theories don't answer the underlying question:
Why is there a difference in experience between men and women reacting to the same fragrances in the first place? Is there a "hard science" explanation for this phenomenon?

Are you sure this isn't individual or cultural, rather than biological?  I'm male, and while I don't use many products with added fragrance, I do fill my garden with fragrant plants.

I am a woman and I also find most of added fragrances revulting. Among the small set of my female friends it seems they usually try many different products before finding the one with smell they like. Our personal tastes are mostly incompatible between each other. I haven't seen my male friends spending time to try and sniff multiple products in order to select the preferable ones. I have seen some go for the first one fitting all requirements as written on bottle without even sniffing it once before buy.

The idea that males and females react differentially to various smells in the context of “hard science” alludes to the concept of sexual dimorphism in olfactory signaling, which has been investigated:

Stowers & Logan. Sexual dimorphism in olfactory signaling. Current Opinion in Neurobiology. 2010. 20,770-775.

What makes males and females behave differently? Although genetic master-regulators commonly underlie physical differences, sexually dimorphic behavior is additionally influenced by sensory input such as olfactory cues. Olfaction requires both ligands for signaling and sensory neural circuits for detection. Specialized subsets of each interact to generate gender-dimorphic behavior. It has long been accepted that males and females emit sex-specific odor compounds that function as pheromones to promote stereotypic behavior. Significant advances have now been made in purifying and isolating several of these sex-specific olfactory ligands. In contrast, the neural mechanisms that enable a gender- dimorphic response to these odors remain largely unknown. However, first progress has been made in identifying components of sexually dimorphic olfactory circuits in both Drosophila and the mouse.

You’re right that most research in humans (like this paper) on this subject includes elements relating to sexual orientation or sexual selection, but I did find one article that is more relevant to your question:

Lindqvist. Preference and Gender Associations of Perfumes Applied on Human Skin. Journal of Sensory Studies. 2012. 27,490-497.

Abstract

The perception of fragrances has been a growing field of interest, where perfumes classified as either typically feminine or typically masculine primarily have been used as stimuli. The current study explored gender associations and preferences of more “unisex” perfumes found in the middle of a gender continuum of fragrances, both when the fragrances were applied on humans, and when they were presented in glass bottles. Blindfolded participants indicated if they wanted to use the fragrances themselves, if they wanted their partner to use the perfumes, scaled gender associations (femininity and masculinity) for each perfume and tried to guess the gender of the person each perfume was applied on when not presented in a bottle. Results show that the gender of the person that the perfume was applied on did not affect the participants' preference or their gender scaling. Moreover, the preference did not differ between female and male participants, indicating that the commercial gender categorization is less important to the perfume consumers.

Practical Implications

On the commercial market, most perfumes are classified as either feminine or masculine, although the odor quality of feminine and masculine odors are overlapping and constitute a continuum rather than two separate clusters of odors. Earlier research has shown that participants tend to prefer perfumes positioned in the middle of this gender continuum. The current study investigates gender associations and preferences of perfumes from the middle of the gender continuum while these are applied on humans. When blindfolded participants evaluated their perception of the perfumes in this study, it became clear that neither the gender of the humans that the perfumes were applied on, nor the commercial gender labeling of the perfumes were important to their perception. Consequently, the commercial gender categorization does not seem to be sufficient for all perfumes. Instead, the classification of perfumes could be according to other aspects, e.g., according to odor quality.

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Why are adults so suceptible to dizziness?
I have a child and she, like pretty much all the others it seems, loves spinny rides in the park. Adults often can't stand them.
In fact, I recall going from loving to hating dizziness over the space of about 3 years, at about the beginning of puberty.
Why do adults react more badly to dizziness than children?

Do you have any data to support your assertion "adults react more badly to dizziness than children" ? Because that could be just your own experience, not a general fact per se.

@alec_djinn Well, I know this isn't exactly what you were going for, but when you think about it, if you ask most adults, they'll tell you they don't really like being dizzy.

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How quicky does dental pH change after eating?
I would like to know how quickly after eating I can expect the pH do change in my mouth, and how quickly this will cause dental damage.
Obviously any answer to this will have plenty of caveats (diet, composition of oral bacteria, etc) but I would like some numbers for some scenarios please.

Dental damage is mainly caused by the demineralization of the tooth enamel. Demineralization can happen due to a low pH caused either by acidic food/drinks like fruits or carbonated beverages or by bacteria producing acid while breaking down sugars.
Measurements (1, 2) have shown that food intake changes the pH (increasing or decreasing, depending on the food source), returning back to baseline after 15-30 min due to the buffering capacity of the saliva via bicarbonate and phosphate.
The drop in pH happens immediately after food intake. If teeth are not cleaned, the acid producing bacteria can have a longer-lasting effect on the pH for more than an hour. In these studies, participants are asked not to clean their teeth, so bacteria will populate the mouth. Removing bacteria or their food source as well helping the remineralization with fluoride toothpaste can counter the effects.

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Is there a difference between drinking water straight from the tap compared to leaving it to sit?
An idle question - if a glass if filled from the tap and consumed immediately, it contains some dissolved oxygen from the physical process of moving through the pipes & tap. If left out (unrefridgerated) and then consumed later the bubbles are gone and there is presumably less dissolved gases.
I'm wondering whether this might have the effect of changing the relative levels of oxygen available to microbiota in the gut, and hence have some effect on the human host?

If you are speaking especially of the stomach, it actually makes no difference because the extremely low pH of the stomach allows very few bacterial organisms to survive. Often, Helicobacter pylori can however be present. Whether dissolved oxygen makes a difference to it is, to my knowledge, unknown. However, pure water does not stay long inside the stomach and passes almost immediately through to the intestines in most cases, so I doubt it would make that big a difference.
Now, it seems you are actually referring to the intestines in your question. Well, in fact the bacteria that inhabit the gut are almost exclusively limited to the colon and to a limited extent to the distal part of the ileum (small intestine). The stomach and almost all the length of the small intestine are sterile. Water absorption takes place in the jejunum (proximal part of the small intestine), which is a sterile region proximal to the locations colonized by bacteria. In conclusion, the oxygen content of tap water will not influence the bacterial flora simply because it does not come into contact with those bacteria.
BTW, the major difference between tap water that you leave sitting and the one that just came out of the tap is the chlorine concentration (decreases with time). Of course this will favor microorganism development, since it is precisely one of the reasons why we put chlorine in the water in the first place...

This implies that your water is treated with clorine. Which is not the case for most european countries. Yet, bacteria are usually no problem in the drinking water.

@Chris No chlorine in Europe? I didn't know that (oh the treachery of learning only by American books! ;-). Do we put something else as a replacement?

@Raoul In fact H. pylori prevalence worldwide is estimated to be 50% (and e.g. 30-40% in the UK). Most people have asymptomatic infections.

@Chris most European countries use chlorination - see http://www.lenntech.com/processes/disinfection/regulation-eu/eu-water-disinfection-regulation.htm

@AlanBoyd Yes, of course you are right. I've edited my answer to reflect this imprecision.

Thanks. I'm in Australia where chlorination also happens, so there's that. However I suppose I didn't mean stomach in my question, but rather gut where flora do flourish. I've updated my question to reflect this.


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How many mitotic divisions do haploid cells undergo before fertilization?
Background
This question is about human physiology and gametogenesis. A spermatozoid is not necessarily the direct "offspring" of a diploid cell. Stated differently, a spermatozoid cell can be the offspring cell of another haploid cell. I am saying "can be" and "is not necessarily", but the correct formulation might be "always is". A given spermatozoid might eventually be the descendent of 1000 generations of haploid cells before (going back in time) finding the diploid ancestor (the one who underwent meiosis II). I'd expect the same to be true for ovules although I'd expect that a given ovule have fewer haploid descendent before (going back in time) finding the diploid cell.
Question

How many haploid generations preceded a typical spermatozoid/ovule that could eventually fertilize an egg?
How does this answer vary with age and sex?

In its most beautiful form, the question is:

What is the distribution of the number of mitotic divisions that happened in the father/mother of a given individual?

Any answer that would offer a step toward answering these questions are welcome!

You may have a look at this post. Haploid gametes do not naturally undergo mitosis but haploid stem cell can be produced, that can give rise to an offspring.

Do you have evidence that haploid gametes naturally undergo mitosis? I was under the impression that they do not undergo mitosis naturally at all.

@March Ho I think OP meant Meiosis II ?

I don't fully understand the comments. When I say meiosis I mean meiosis II indeed (I edited the post). I supposed that after meiosis II mitosis occured to increase the number of gametes but I might be totally wrong (I think I remember that from a Bachelor course).


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Why the "trailing" woodpecker sound?
I recently (March 26th, 2022) recorded a woodpecker in the woods around Habo Ljunga, Lomma, Skåne, Sweden and that gave me an idea. While cutting the audio, I noticed that the woodpecker's sound seems to have two moments (see waveform below): a main one (gray) and a trailing one (light blue).
Does anyone know why the sound trails off? I made several recordings and at least my subject woodpecker consistently features these two moments. If helpful, here is the original video showing the movement of the woodpecker.

It might be helpful to include more information about the species of woodpecker (if known), where it was recorded, and when.

@user1202136 I think your date is wrong, as today is April 24, 2022. At any rate, I have also heard this pattern in the US, but I don't know which species. The signaling hypothesis is interesting, as I've also heard woodpeckers tapping at a constant rate, and then stopping without trailing off.

I don't know anything about woodpecker cutting so hopefully someone more knowledgeable will answer...but could it just be that a woodpecker can't go from full speed to stopped instantly? It needs a little "slow down" time, where it stops full-force cutting and needs to oscillate a bit after to fully stop?

Comments are ephemeral and often overlooked, so in the future please [edit] your post to update it rather than tacking on comments. Please also clarify what you mean by "cutting" — several commenters seem to think you are talking about what the woodpecker is doing (usually referred to as pecking, drilling, drumming, or hammering), but I assumed it was something to do with your processing of the sound file. ——— Also, I strongly suspect that @selene is correct, but don't have time to properly research this myself.

in the UK we have two species of woodpecker that use drumming for communication.  One of these - the greater spotted woodpecker - tails off at the end of the sequence as it gradually slows and eases pressure.  The other species - lesser spotted woodpecker - stops much more abruptly, without this tailing off.  The difference between the two patterns allows you to determine which species you are listening to.
For examples of each, you can check out XenoCanto recordings here:
Greater: https://xeno-canto.org/719629
Lesser: https://xeno-canto.org/722816

Such a cool answer!

This isn't cutting, but rather part of their acoustic signaling behavior called drumming. This communication evolved from the foraging behavior of these birds. When foraging, the birds make less predictable patterns of striking their beaks against the tree when they locate insects from non-hollow trees. Over time, this evolved into an acoustic strategy by which males drum on hollow trees with predictable rhythms for territorial defense and mate advertisement. The drumming for communication is more rapid and precisely patterned compared to the drumming used during foraging. This reduction in amplitude towards the terminal part of their drumming, or the "trailing off" as you describe, has been documented for woodpeckers (see Budka et al., 2018 PLOS One) but hasn't been explicitly described. What's interesting is the duration of the "rolls" in a drumming can often be individual-specific (again, see Budka et al., 2018), suggesting that each bird might have its own set duration of how long it drums for.


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Pink Grasshoppers
The area I found this grasshopper was Canyon Country, California, USA In a desert/field area.
I have been reading up on grasshoppers because I recently came into possession of a pink grasshopper (It was identified below as the common meadow hopper Chorthippus parallelus). One of the pages that I've read covers the eating of toxic plants by grasshoppers and how they change to bright colors to warn that they are toxic after eating poisons. Is this true? Could that explain the coloring of this grasshopper, or is it due to a recessive gene, or even erythrism? I'm trying to breed it, so any and all info on how to treat this little guy, history of the coloring if its genes, and the color changing toxic effect would be much appreciated.
Here's a picture.

Could you add a specific species? It's more of a shot in the dark right now.

Can you add those links: the other sites and the resource that talks about the toxicity?

These two sites say that this is a common meadow grasshopper: Chorthippus parallelus. Have you already checked them? I can't find anything about toxic plants here, though.

Looks like an immature instar? You might be interested in this, too: http://biology.stackexchange.com/questions/20702/how-can-a-pink-grasshopper-exist

This is a page I found in the beginning of my research hinting on the eating of toxins and color change.  https://animalcorner.co.uk/animals/grasshopper/

Also, that ID describes the species that is native here in every aspect, I'll update the Description.

Chortippus parallelus is a common species in Europe that is according to my grasshopper id-guide extremely variable in color. It can be green, brown, yellow and even purple. I can verify that from field experience. Pink however is much more rare, and considered to be caused by Erythrism  See https://en.m.wikipedia.org/wiki/Erythrism for explanation and several references to pink grasshoppers/katydids.

If the wikipedia is right, and the pink coloration is a dominant trait, then OP should have an easy time breeding for it, assuming he can breed grasshoppers in captivity.


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Can someone help me identify this caterpillar?
I was in Colorado Springs in mid-October when I noticed something floating in front of my face. I tried dodging it, but it landed on my sunglasses. When, I initially saw it, it was attached to a single ~1-foot long strand of (what I believe was) silk. Now, I BELIEVE it was using this silk to float on the wind (as I've seen some species do on nature documentaries), but it is possible it was dangling from something I walked under, and I just failed to notice. Considering where I was when I noticed it, I believe the former is more likely. The creature, I believe some kind of caterpillar, was a bright, almost translucent green. It is incredibly small, approximately 1/8 to 1/16 of an inch.
I tried to see if I could find the caterpillar online. Caterpillaridentification.org has a list of caterpillars found in Colorado that you can filter buy color. The one I believe it looks closest too is the "cabbage looper", but Google says those caterpillars are about an inch and a half long, considerably larger than what I saw. This makes me believe that I probably ran into a newly born caterpillar.

Cabbage loopers are indeed about 1 in long, and quite fat - you will find them in your garden commonly. May not be the larva of a butterfly that you are finding.

I think this is an early stage Oak Leaf Roller caterpillar. They are green and have a black/brown tip, as can be seen in your first photo. Fully grown are about 1" (25 mm) long.
They are known to dangle down from trees on silk threads when dislodged.


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Do identical twins have the same fingerprint?
When there is every thing same from their genes to their phenotype so then why they don't have same fingerprints?

This question is a near-duplicate of http://biology.stackexchange.com/questions/1054/what-causes-fingerprints-to-form-and-why-is-the-pattern-formed-unique

It's considered appropriate on biology.se that you present some of your reading/research with your question. Have you read anything about the formation of fingerprints? Otherwise it will be closed.

As @anongoodnurse says, previous research is required and you do not need THAT much of it ;) http://biology.stackexchange.com/questions/28352/why-do-human-eyes-glow-red-on-a-photo-and-dogs-eyes-green

I like the question a lot and the answer is also pretty awesome :) Voted to keep open. Background research = identical twins are clones (implicitly: same phenotype), why fingerprints different? Quite a legitimate question.

Identical twins have, despite the name, neither identic fingerprints nor identic genetic fingerprints.
Fingerprints: According to the papers listed below the fingerprints show higher similarities (the "structure" is the same), but they can be distinguished and are not the same.

On the similarity of identical twin fingerprints
Can identical twins be discriminated based on their fingerprints?

Genetic Fingerprint: Although identic (or monozygotic) twins share the same DNA, they are not the same and can still be distinguished with a DNA fingerprint, if enough regions are analyzed. The difference comes from small mutations (so called "single nucleotide polymorphisms", one base mutations) which occur in each of us individually. The other difference comes from epigenetic modifications of our genome (basically adding methyl groups to our DNA) which are also not the same between identic twins (there is an interesting video on this on Youtube). However, when using standard forensic kits it is usually not possible to discriminate between identical twins. Differences are detected with whole genome sequencing.
Have a look at these publications:

Identical Twins' Genes Are Not Identical
Finding the needle in the haystack: Differentiating “identical” twins
in paternity testing and forensics by ultra-deep next generation
sequencing
Epigenetic contributors to the discordance of monozygotic twins.

You might expect identical twins to have the same fingerprints as twins have virtually indistinguishable DNA. The distinguishing nature of physical characteristics of a person is due to both the inherent individual genetic diversity within the human population as well as the random processes affecting the development of the embryo. The same would then be true of clones of a person.

In the case of fingerprints, the genes determine the general characteristics of the pattern. Fingerprint formation is similar to the growth of capillaries and blood vessels in angiogenesis. The general characteristics of the fingerprint emerge as the skin on the fingertip begins to differentiate. However, the flow of amniotic fluids around the fetus and its position in the uterus changes during the differentiation process. Thus, the cells on the fingertip grow in a microenvironment that is slightly different from hand to hand and finger to finger. The finer details of the fingerprints are determined by this changing microenvironment. A small difference in microenvironment is amplified by the differentiation process of the cells. There are so many variations during the formation of fingerprints that it would be virtually impossible for two fingerprints to be alike.

Therefore, fingerprints aren't entirely a genetic characteristic. They are a part of a ‘phenotype’ which means they are determined by the interaction of an individual’s genes and the intrauterine environment.
Overall, identical twins’ fingerprints tend to be similar. Before genetic testing, the similarity of twins’ fingerprints was used to determine whether they were identical or fraternal. But there always will be subtle differences making even their fingerprints unique.
On the similarity of identical twin Fingerprints

Beautiful Answer! Very nice.


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How to calculate or know by experiment the entropy of enzymes or protein?
How do you calculate or experimentally determine the entropy of enzymes or protein?  In particular, I am interested in Boltzmann and conformational entropy, and Gibbs free energy.  Any references are welcome.

What do you mean by "entropy"? Are you referring to conformational entropy or to Gibbs free energy (ΔG) for folding etc?

both.And I'd like to know the Boltzmann's entropy

See this page: http://equilibrator.weizmann.ac.il/  and references therein.

In practice, like Energy calculations, Entropy is a relative numbers and difficult to get.  Computational chem and bio have been working on this problem with mixed success.  The summary of what I'm going to say here is that when you try to calculate the differences in entropy (or energy for that matter), the Gibbs Free Energy differences in most biological processes such as enzyme/substrate binding, protein/protein or protein/DNA interactions or protein folding etc is so small compared to the errors in these calculations that the computations are hard to believe.
Entropy is ultimately a term one would use in calculating the Gibb's free energy which will tell whether a given chemical or molecular process will occur.  So it's a valuable number to have.  Gibbs Free Energy (G) equals Enthalpy (heat) minus the temperature (T) times the change in entropy.
G = H - T$\Delta$S
The Entropic term, $\Delta$S is described in chemical systems often as a change in the combinatorial change of the system and the change in the heat capacity of the system. The first of these could broadly described as a 'mixing' term.  When more than one solvents or a solvent and a solute diffuse into each other mix completely, the number of possible states is maximized.
The heat capacity of the system is a more often the focus of entropy calculations for proteins and biological molecules.  This is because the conformations of the biological molecules, especially how free they are to move around are thought to contribute to the entropic part of G.
So attempts have been made to estimate from NMR and crystallography as well as molecular dynamics how much domains and side chains are free to move.  Unfortunately this is only an insufficient proxy for biological entropy.  A substantial if not dominant contribution to the T$\Delta$S term comes from solvent.
How is this so?  Water molecules form structures around proteins which are not static, but do involve many water molecules residing there on the average to see them in crystal structures and NMR experiments.  While the individual waters are exchanging rapidly, they are not in the same entropic state in water solution as they are when they form a hydration shell around an aromatic or charged side chain.
Attempts have been made to parametrize the solvent entropy by looking at the buried nonpolar surface in a folded protein, looking at the mobility of sidechains before and after folding/binding, but these metrics appear to be configuration dependent to the point that they can't calculate the protein entropy via these efforts, at least heretofore.
Conventionally, molecular dynamics tries to calculate this by surrounding the proteins or other molecules with water molecules and some approximation of the overall entropy is calculated on the entire system.  It turns out that small differences between the water molecular models and the simplifications in ball and stick/Hooke potential water models we make are also problematic approximations when there are hundreds or thousands of water molecules in the simulation.

Good，please continue


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What do the numbers in Photosystem I P700 and Photosystem II P680 stand for? Is it the optimum wavelenght? The maximum wavelenght?
I am a bit confused about this because my teacher and english Wikipedia say it's the wavelenght the Photosystem is most reactive to; my textbook and the german Wikipedia say that it is the maximum wavelenght the Photosystem can absorb :-/

It's the absorption maximum of the photosystem.

I'd first like to briefly mention what the P700 and P680 refers to. These are the reactions centers of the photosystems. The Photosystems are where the light is absrobed and converted to the form of electrons. The light is absorbed by the chlorophyll molecules and the energy is transferred to the reaction center which transfers that energy into an electron from a water molecule. Tha elecron is transport tmake ATP and NADPH, which is important for carbon fixation.
The numbers specify the wavelength of light that the reaction center are most reactive to, and therefore, the wavelength where they absorb the most light. That's what's meant by the maximum absorption. So everybody is right, your teacher, the textbook and Wikipedia. They just say it differently.


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Learn Bioconductor the hard way!
I came to analyzing population genetics data from the background of a theoretician and a computer biologist but not with the standard tools that a bioinformatician (or empiricist in population genetics) know of. I have a fairly good knowledge in R and in programming in general.
I am looking for a course/tutorial for learning bioconductor (and other R tools for analyzing genetic data). A course/tutorial that is short, dense and assumes the user has good knowledge in programming. I am happy with both a video or a written tutorial although I would slightly prefer a written tutorial. I typically aim at analyzing data on structured populations such as the average number of pairwise differences among population, or graphing the site frequency spectrum per population, etc..
There are a fair number of such tutorials. Can you please give me recommendations?

bioconductor is a source for packages, You can ask for tutorials to bioinformatics packages in bioconductor, those would be the vignettes. But, I don't understand what you mean by tutorials for bioconductor. Of the top of my head if you have population genetics data, then most probably you are dealing with normal distributions. There are statistical packages which are far more robust than most packages on bioconductor. This question is a bit unclear as to what you want to do and what sort of data you have.

I recommend the DESeq2 tutorial at:
http://www.bioconductor.org/help/workflows/rnaseqGene/
I think this is a good start for you because:

DESeq2 is a very popular package. You'll learn how exactly a bioinformatician works.
The workflow starts from alignments, and show you how to connect command-line tools with the R-package
It shows you how to generate MA plot, PCA plot etc. You'll appreciate how easy to do such things in R.
Testing for differential gene expression is very important
You'll learn how R does the programming. For example, in R it's a good idea to create a data set object, and do something like this:

obj <- .... # This is my R-object
obj <- fun1(obj) <- # Function 1 adds information to the object
obj <- fun2(obj) <- # Function 2 adds more information to the object

I'm not able to fix the format. Can someone help me?

I tried to fix the formatting, but the formatting looks bugged.

@bli Sorry, I tried to answer the question as best as I could, but I somehow screwed the formatting.

I mean, it doesn't seem to be your fault that the formatting is screwed: Normally, 4-space indentation works and it seems to me you did it right. Or maybe code-formatting is not expected to work after listings ?

@bli Yeah. I was trying to do code formatting, but I couldn't get it working...

It seems to be happening because of <. Don't know why. Possibly because it indicates the beginning of xml/html tags.


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What is the frequency distribution of each base in a DNA sequence?
Can we say that the frequency distribution of each base in a DNA sequence is equiprobable?

After the negative answer; i rephrase: Is there a use case in which the frequency distribution of the bases is equiprobable?

Just making an educated guess... DNA sequences are not random, thus the probability of any base being present at a particular location is not equal for all the bases.

My question was about their frequency.

? so should your question say "what is the probability distribution" or "what is the frequency distribution"? I guess I'm not following your question - can you help me out?

No. It is not. Very simple case - see GC percentage.

The frequency of the bases in the genome isn't equal to 0.25, the frequency depends on what kind of organism you mean. However let's take a look at some of them:

bacteria, most of the time we can see a bias towards some bases, this could be a GC bias, for example if the bacteria lives in extreme conditions, because GC can vorm three hydrogen bonds compared to AT which can only form two hydrogen bonds. So it's genome is more resistent to extreme temperature, less denaturation chance because the stronger bonds. In bacteria there are also some polymerases which have a bias towards bases, I won't discuss this in depth to keep it short, but from these two points we can already conclude the genome isn't random
Homo Sapien, for example we need CpG Island near our promotor region, to regulate transcription. Further we have higher GC% in gene coding regions to reduce mutation chance, because we don't want to mutate genes wich are needed for survival. Their are also some sequence which are very specific for example TATA box and Poly-A signal, if our genome would be random, so all base would have a frequency of 0.25 these specific sequence could occur at place where we don't want them or they wouldn't occur at places where we want them. We need a promotor (with TATA box) for RNA polymerase binding, if our genome was random we have a big chance we would have genes wihtout a TATA box so no transcription of these genes will occur

There are a lot  more properties of the genome we could discuss but I think this will give you enough insight why the bases in the genome don't have a equally alike frequence of 0.25
UPDATE:
in addition to your second question: I think the chance of finding a genome which has an equally alike distribution is very small. because almost all organisms have undergo evelution, and when we have evolution there is natural selection and natural selection relies on mutations. So (almost) all genomes have udergo mutation, however this sometimes can favor an equally distibution for example if our genome is AGAA and one A mutates to an G we will have an equally alike proportion. So to summarize: maybe you can take a look at NCBI and look for a gc 50% wich means 50% AT so 25% of each base. If you find a genome wich has exact 50% gc, you have found your answer

There are two main driving factors to consider here:
First, G/C and A/T represent complementary base pairs, as G is always paired with C (and vice versa), while A is always paired with T (and vice versa).  Therefore the frequency of G is always equal to C, and the frequency of A is always equal to T.
Second, G is paired with C via 3 hydrogen bonds, while A is paired with T via 2 hydrogen bonds.  Therefore, G/C bas pairs are more thermodynamically stable than A/T base pairs, and require higher temperatures (more energy) to be pulled apart during replication and also transcription.  For that reason, organisms that have a higher body temperature tend to have a higher proportion of G/C base pairs than those which have a lower body temperature.  For example, the G/C content is higher in thermophilic bacteria than in mammals, and higher in mammals than in plants.  This fine-tuning of the G/C content enables the optimum balance between stability and the extra energy required to pull the strands apart when required for replication and transcription.


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Programs/software to graph biological data
I am curious about what sort of programs people in my field of academia are using to graph their data. I am a master student in biochemistry, and have more or less only used excel (on rare occasions I have used the statistical program R).
I know my question is very general, but I would like to hear suggestions for programs that could be useful when I want to compute numbers or make good graphical representation (in the life science fields, e.g. microbiology, biochemistry, biotechnology, biophysical chemistry).
Also, are the other programs to create good graphic illustrations? I am currently using Inkscape to produce molecular illustrations, and I think this is one of the most typical programs to use?

The vast majority of people use R. A priori it is really what you want to learn to use. However, it depends on the kind of data you have. If you have loads of data or if you have certain specific data you might want to use specific software for big data visualization or do you own thing in C++ or some other language. If you are working with mathematical modelling Mathematica might be handy. The answer also depends on what kind of manipulation you have to do on your data. Again R is pretty handy for manipulating data quantity that are standard in Biology.

I'm voting to close this question as off-topic because 1) the question is too broad and 2) the question is about data visualization and is not specific to biology.

GraphPad Prism is very widely used.

use R - it's versatile and free and data visualisation is very good in R

Thank you for there answers.  I will argue that this is specifically for biology. I mean, statistic and visualization of your data is a vital part of presenting everything you have. I can't post this question in a different stack exchange, because I'm interested to hear what programs people who study biochemistry, biotechnology and microbiology use. Therefore, I think this is highly relevant for the biology page.

The answer I am looking for is just a simple list of suggestions of program (not programing languages) which are good. Although the answer below is a very good one, it not exactly what I am looking for.

Unless the kind of analysis you do is really "standard" and readily available as a program, a bit of programming may become necessary. Some years ago, I found it practical to use python to perform analyses and generate custom graphical representation via the TikZ package of LaTeX. Now I most often use matplotlib, but this is still python programming. Inkscape is useful to adjust your final figures, but programmatically generating graphical representations allows rapid updates when data  or parameters change.

There is no standard software, programming language, or library used for computing and graphing biological data. The R language is commonly used for statistical work, but Python (in conjunction with the SciPy stack) and C++ also gets used a lot.
Before going further, I should point out you are asking two questions. One about computation and the other about presentation.
Computation:
You mentioned R. That is a programming language (with specialized software built around it). When it comes to programming language choice, the three most important factors are personal preference, available libraries, and the language already in use if you are joining a project with a pre-existing code-base. You might notice performance is not on this short list. The reason for this is that modern languages on modern hardware are efficient enough to, very often, make language choice irrelevant from a performance perspective. Most computational tasks suitable for R are also suitable for languages like Python and Julia.
R's strength is in its focus for statistical work. Whereas Python's standard library comes with many bells and whistles intended to ease the design of small to moderate sized pieces of software across many situations, R comes with many features focused specifically on easing the task of writing code for complicated statistical calculations. Due to it being so common in academia, R one language you are very likely to encounter in academic, computational work. That makes knowing it a helpful skill (whether you regularly use it or not). R, having such a strong suite of tools and large userbase, is also the basis for many third-party tools. One interesting example is Bioconductor
That being said, there are also advantages to using (or at least knowing) Python. It is one of the most common languages in programming in general. That means it has a diverse assortment of libraries designed for it by members of the community. When it comes to nonstatistical libraries, few languages have as many options. When it comes to statistical work, Python does not have as many options as R, but it does still have a lot. The SciPy stack, which includes the NumPy and Pandas libraries, is a big part of that. Another benefit that comes from Python's popularity in the programming world is that you will have an easier time finding programmers to help you on a large project if you decide to look for help outside of your field. (For example, far more computer science majors will know Python than R ...multiple times over.)
As far as the Julia language goes, it is still new. It is being developed as a competitor to R and Python, but it is not mature enough to be a serious contender just yet. However, since your question is about what people use, I would be remiss to ignore it. It may become a serious contender, but for right now, it is still trying to grow and prove its worth.
If performance becomes a serious issue, you would probably be forced to dump R, Python, or whatever very high level language you are using in favor of C or C++. Both are far more efficient than the so-called "batteries included" languages. C and C++ are system programming languages. They are often used in operating systems, databases, video games, and other large pieces of software which you would not want slowed down due to features being included which you did not explicitly program in. (C and C++ are also used in small projects, but I digress.) However, taking advantage of this efficiency requires some insight into how computers actually work. This is not a difficult task, and any good tutorial or book will cover such topics. Using C or C++ without this basic understanding will likely be counter productive, as doing so can lead to you inadvertently creating a program far slower than it needs to be, which could be an issue if performance is becoming a serious concern.
A non-performance benefit of C is the large library selection. As I mentioned above, few languages can compare to Python's library selection. C is definitely one of those few. Actually, C is essentially the lingua franca of libraries (due to its age, its dominant position, and aforementioned efficiency). This means you might find yourself needing to use some highly specialized library with no bindings to languages like Python or R. I have come across a few.
Presentation:
R is also a nice language for graphing data. It comes with a package known as ggplot2, which is responsible for this functionality. This is a common source of data visualizations. However, this does not mean you must use R if you want to create graphs that follow the norms of academia. First off, many people use other pieces of software for plotting. Secondly, there is the library for Python called matplotlib. It is fully featured and is capable imitating the visual appearance of ggplot. One of its built-in style sheets was included just for this purpose. Not surprisingly, matplotlib is the graphing library used in SciPy.
There are many other graphing/plotting libraries, and many of them are fairly language agnostic. Presentation is not often a deciding factor in what language to use for computation. However, if you found yourself needing to use a specific language for its presentation options, doing computations in one language and then feeding the results into another for presentation is not unheard of.
Software:
I include this as a third category because this is more complicated than deciding on programming language A or B or choosing a plotting utility. Non-computer scientists often confuse software with languages. You have to use software when writing a program in a given language, but all the work is done by the program you write. Large software suites, on the other hand, do work for you in many ways. They often come with some sort of quasi-programming language included, but that is only one part of a larger whole. While R comes with a number of software tools, Matlab and Mathematica are better example of this. Free, open source alternatives to these proprietary suites would be Octave and Scilab, although such open source software traditionally has not very competitive with the likes of Matlab. SciPy is a recent example of open source software closing the feature gap (which is a very good thing in terms of avoiding vendor lock).
Beyond that, it is hard to say what you would encounter or what is common. Most large software tools are proprietary. Different companies, universities, and individual projects will use different software, and you will not know what to expect until you you are recruited by a team.
This is why projects sticking to programming languages over large software is preferable in terms of ease of recruitment. Also, programming code can be published with papers a lot easier than describing how you used a piece of software (which is big if open data is important to you). That being said, it can not always be avoided. Many machines in biology require specialized software and many kinds of data are most easily manipulated with proprietary software. Do not worry about such situations. It, obviously, will not affect your current work from being presented in a standard way.
EDIT:
Sorry for the wall of text. The question was broad and this is a complicated issue. It was hard to summarize.


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Is there already discovered non-carbon form of life?
I have heard of some rumors going around about a living organism based on non-carbon. Is Has research been done with real form of life based on non-carbon? Or carbon-based life is only type of life what humans know of?
Carbon chauvinism

See http://www.thewestheimerinstitute.org/pubs/Is%20there%20a%20common%20chemical%20model%20for%20life%20in%20the%20universe%3F.pdf

See http://biology.stackexchange.com/questions/3652/what-elements-are-a-possible-basis-for-life

I think the question can be phrased better than "rumors going around" - I don't think "rumor mill" is quite in line with this site's vision. Can you be more specific about who is the source of these claims, and what exactly they said? Otherwise, the question is unanswerable.

In a word, no.  There are some good chemical reasons to expect all life to be carbon-based.
Of course, it is no longer a silly fantasy to imagine an artificial intelligence that might qualify as life.  (Still FAAAARRRR in the future, though, if ever.)

Thank you. Is there any proof of unpossibility of existence the non-carbon life, e.g. phosphorus-based or boron-based? Or this is hypothesis, similar to those where talked "The Earth based on 3 elephants, 3 elephants based on turtle, etc..."

@perpetuity You have asked a very concrete question about findings so far, but your comment is about possible future findings. I think you should ask that as a separate question.

Carbon is much more abundant than silicon or phosphorus, while being more reactive at room temp and forms gases and liquids at cooler temperatures than silicon compounds. A silicon based organism would probably only be possible on a really hot planet where the silicates are more reactive and more flexible, but still unlikely. I don't know what solvents would be acceptable at those temperatures and the silicon equivalent to CO2 is SiO2, which is solid, not a gas, so probably shouldn't expect an oxygen based metabolism.


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Why are many fruits sour?
Many fruits (like apples, berries, citrus fruits etc.) contain high levels of organic acids, especially malic acid and citric acid. Are there any evolutionary functions of those acids in ripe fruits? In unripe fruits the sour taste may protect fruits from being eaten prematurely by herbivores, but why are those acids still present in ripe fruits? Are they there for increasing osmotic pressure so plants can make bigger fruits in a cheap way by just inserting more water in them? Or do organic acids perhaps play a role in pathogen protection? Or are they just a by-product of some other biochemical mechanism in fruit development?

Most apples are not very sour, same with berries. Citrus fruits (especially lemons) are an interesting case. Moreover, these fruits also contain peels which have aromatic oils. I am not sure if animals find the peels tasty. One direction to look at is how the citrus seeds are dispersed. I am trying to look for articles on this.

One possibility is that the organisms responsible for dispersing citrus fruit do not taste the extreme sourness, like how birds can't taste capsacin produced by peppers. That's just a guess, though

Fruits are sour for the same reason our skin has an acidic pH. To defend bacteria and other microbes that cannot grow on a fairly acidic environment. That's why even coca-cola and other drinks are highly acidic to inhibit bacterial growth. All the same strategy.

Here's a modelling paper for malic acid accumulation in fruits, just for extra reading! (malic acid is what they put into sour candies to make them sour along w/ citric acid, generally) http://jxb.oxfordjournals.org/content/57/6/1471.full

You mean malic acid, not maleic acid?

Short answer
Great question! I have done some research on the topic and found so much interesting information. It still seems like a topic that i being researched on, but so far, the research shows that malate is created by a CAM and C4 like pathway while citrate is created from TCA cycle.  Their functions are that they are important biomolecules in metabolism, in particular respiration.
Background
Malic acid and citric acid are the two main organic acids that are accumulated in the fruits and cause the sour taste. Citrus fruits contain more citric acid and other fruits like apples and pears contain malic acid. I will provide a detailed analysis for both cases.
In an article by Deshpande & Ramakrishnan they mention two hypotheses about the accumulation of the citric acid in fruits. One was that the organic acids are not formed in the fruit, but transported to the fruit, in which the fruit acts like a storage organ. The other hypothesis is that the carbohydrates in the fruit is converted to the organic acid. In their research. they tried to isolate some enzymes from the Garcinia fruit to support the second hypothesis. They say:
This [reciprocal relation between acid and sugar content] would indicate the transformation of sugar to citric acid in the fruit tissue itself due to the presence of the requisite enzyme systems.
They suggest that the TCA cycle is how the citric acid is being accumulated and stored.
The article in the comments by Lobit et al. also supports a similar hypothesis of the accumulation of malic acid. The authors tell us that the malic acid is most likely produced in the fruit itself because the pH of the xylem and phloem (the transporting organs of plants) have a pH of close to 7 or higher. It seems that the malic acid is stored in the vacuoles of the mesocarp cells and that the amount of malic acid in the fruit depends on the transport of the malic acid to the vacuoles in the mesocarp cells.
Pathways
The actual pathways for the creation of citric acid and malic acid are very complex. Here is a picture of the different pathways in the cytosol of the mesocarp cells thst create these organic acids (picture taken from Etienne et al.)
The first pathway described is the PEP pathway, which is really a modified CAM or C4 pathway (which are teo ways to deal with photorespiratin, and are adaptations to hot, dry environments). The PEP is converted to oxaloacetate by PEPC, which also takes in CO2, then that oxaloacetate is converted to malate by NAD-MDH. PEPC is regulated by malate concentration and cystolic pH, showing that the activity of PEPC is to indirectly increase the malate concentrations, not just to create more oxaloacetate.Let me note that I still don't fully understand why C4 and CAM-like pathways are present in Fruits from C3 plants.
The major pathway for citrate synthesis is the TCA cycle. Both are also involved in metabolism. TCA cycle (the citric acid cycle) is an important cycle and the second pathway in aerobic respiration. This pathway occurs in the mitochondria. Malate reacts with acetyl-CoA to make citrate and the CoA is released. The citrate then goes on to be repeatedly oxidized and ends up back to oxaloacetate. Now, for metabolic reasons, for example, if the amount of ATP created is top much at the end of aerobic respiration, the citrate could be transported out of the mitochondria, leading to citrate accumulation.
Control of acid accumulation
The control of the organic acid accumulation is different for both malic acid and citric acid. Malic acid accumulation in the vacuoles is controlled by vacuolar storage and vacuolar transport (Etienne et al). This hypothesis was really the subject of the article in the comments. Their article was about modeling the malic acid based on this hypothesis and compare it to actual biochemical analysis of fruits. Their results supported the hypothesis.
The accumulation of citric acid is more dependent on metabolism, therefore respiration. This is since the vacuolar transport is slower for citrate than malate, and so whatever limits thr speed of malate vauolar transport affects citrate. But citrate concentration in thr cytosol would be the only other main factor affecting the vacuolar transport. A model by Wu et al. was created based on this hypothesis and compared to the actual citrate concentrations, and once again, this hypothesis also supported.
Functions of these organic acids
Suprisingly, the only functions of malate and citric acid cycle is mainly for respiration(mainly TCA cycle), and other metabolic processes. Malate does affect the texture, ripening, and starch metabolism and more of fruits, as described in this article. But, malate and citrate are important for all respiring organisms, including us.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4536381/ Some of the acids are for controlling plant pathogens. But probably not all of them.

@inf3rno true, but those talk about benzoic acid and quinoic acid, which aren't the main organic acids causing the sour taste...It is mainly malic and citric acid

It's not true that the only function of citrate, malate and the TCA cycle is respiration. (Strictly speaking, the TCA cycle does not do respiration at all; that would be the respiratory chain.) The TCA cycle is involved in a number of metabolic conversions, including amino acid and fatty acid synthesis. Citrate is the precursor of fatty acids, and malate is important in the malate-aspartate shuttle that helps control cellular redox state.

Also, it would be good to clarify that sour taste is not caused by citrate or malate, but by free protons (pH). The taste receptor detecting H+ was discovered 2006, see http://www.nature.com/news/2006/060823/full/news060821-9.html

This does not really answer the question. You are just saying how acid accumulates and not why acid accumulates, which is what the question is about. Please revise your answer to add more information on this aspect or the answer may be removed.

I like that the left hand image (labeled "mitochondrion") actually looks like a piece of fruit :)


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What is the origin of prions?
We know something about the origin of the first cell. But what do we know about prions? How did they originate?

Well, it's not like we know the origin of cells.

@Bird - I agree with Eli... what do you mean by "we know the origin of the first cell"?

The computational study by Ehsani et al., 2011, argues that an ancestor metal-ion transporter gene ZIP served as the initial template for the prion founder gene, where the same author produced a 2012 paper that said this was probably a product of a spliced LIV-1 ZIP transcript that became reverse transcribed and inserted into the host genome. Thus, evidence in part points to a retrogene origin for prions (mediated by a retrovirus, especially since the gene is integrated into the host w/ no introns). They go on to state that two genomic rearrangements spanning hundreds of millions of years serve as the basis for the prion founder gene: A cysteine flanked core element inserted into the ZIP ectodomain, and then the insertion of a spliced, C-truncated ZIP transcript.
I don't think the evolutionary origin of prions are very well understood, yet, but I will try to find more recent data on the subject.


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Exporting RNA in extracellular vesicles (exosomes)?
I'm interested in how much is know about the process by which RNA is secreted from cells into extracellular vesicles.
Where is a good place to start reading about this?
How much is known about this pathway?
Can the pathway be engineered?

Perhaps you should start by searching google scholar for some good review articles (Nature Reviews and Annual Reviews are quite elaborate). A broad question like this is not suitable for the stackexchange format. If you can narrow down your question you can prevent it from being put on hold.

How can I make it more specific? Should I specify an organism?

No, specifying an organism would not help much. If your question was about specific points about the process of exosome formation then you can be directed to suitable paper. However, one can only suggest you to read a review on exosomal RNA. Your question about how much is known is also subjective. The third question: again, one can engineer anything but it may or may not be useful/productive. First, you are asking multiple questions and your questions are, moreover, too broad.

I just want to know if its possible for cells to be (genetically) engineered to produce a signal every time an mRNA is transcribed and have that signal exported into the extracellular environment.


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What's the purpose of Cdk activity having more than one method of becoming inactive?
Cdk becomes partially active once its bound to cyclin and then gets phosphorylated and fully active once a Cdk-activating kinase (CAK) phosphorylates the partially active Cdk. This fully activated Cdk complex can be inactivated through a Wee1 kinase which phosphorylated the Cdk at a different site or through the binding of a Cdk Inhibitor protein (CKI).
Why would the cell need more than one way to inactivated this complex? Are there two methods in case one of them should "fail?" (i.e. the kinase not phosphorylate the Cdk complex in the proper spot) or is there some alternative reason?


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Is my terminology for proteins correct?
Statement: Protein X consists of 20 amino acids.
Question 1: Is it necessary to write "Functional" Protein X or is it already implied, that it is functional?
Question 2: Referring to question #1 - Does "Active," "Functional", "Native", "Mature," and "Stable" all serve as the same as synonym?
Question 3: How would I refer to the 16th, 17th, 18th, 19th amino acids?
Option 1: AA-16 through AA 19
Option 2: (Subscript) A16A17A18A19
Option 3: The 16th through 19th amino acids ...

1) I don't think so. I would not assume functionality.
2) People may diverge a bit on the semantics, but here's what I would say (my background is more cell bio and structural bio than biochem or genetics).

Active - Has enzymatic or signalling activity (or some other functional capability). Often proteins have multiple activities, or different active sites, so activity should be with respect to a specific function.
Functional - I interpret this to mean has all of its native activities intact. (I don't take this to mean anything structurally). One could also use this as a synonym for active, especially for a specific functionality.
Native - I take this to mean the protein has not been altered from its form found in nature. This implies it is functional.
Mature - My natural feeling for this is that it means the protein is structurally mature, i.e. it has been folded properly, transported to the correct cellular compartment, post-translational modifications completed, etc... For a non-functional mutant protein, I would hesitate to call it mature though, even if it were not semantically incorrect.
Stable - I interpret this entirely structurally. i.e whether the protein has folded to an energetic minimum or their natural structural state (incl. proteins with disordered domains). People might say, though, that stable means it has a natural lifetime, i.e. the cellular environment or the enzymes present are not destroying it at an abnormal rate.

I'm not quite sure what (3) is asking; if you edit, maybe I can comment.


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Has any scientist elaborated on the "selfish neuron" hypothesis?
Daniel Dennett references a talk by Sebastian Seung, where the latter speaks about "selfish neurons". I've been trying to learn more about this hypothesis, but cannot seem to find anyone who has elaborated on this line of thinking. Could someone point me to some resources, or this an idea whose time has not yet come?

I would argue that the "selfish neurons" idea is a lot less interesting in terms of biological implications than the similarly-named "selfish gene" hypothesis.
It's basically proposing a bottom-up understanding of neuronal circuits where the developmental design feature is that neurons are individually optimizing their input-output relationships in some way. There isn't really any biological controversy about this suggestion.
Dennett (and probably others) goes a little crazy with it and turns it into a discussion of the agency of individual neurons, etc, but from a biological perspective I would argue that this is a pretty boring type of agency, at least in so far as using this definition pretty much all cells in a biological organism would be argued to have agency, because they are on some level "making decisions," but that's all biology is: organic systems of machines that respond in some way to their environment, and which are subject to selection pressures by which the systems of machines that reproduce best come to predominate.
Where this argument is useful, and Dennett uses this approach as well, is in contrasting biological systems with silicon computers. However, all of today's machine learning algorithms are really based on "selfish" nodes according to Dennett's description.
In summary, the selfish neuron hypothesis is just a philosophical approach to what we already know about biological neurons. It's meant as a way especially for people from a more algorithmic/computational background to think about how biological neural networks differ from algorithms structured from logical first principles. It doesn't make strong hypotheses for biology beyond what is already understood and agreed upon. I think this is probably why you don't see much more study about it.

Comments are not for extended discussion; this conversation has been moved to chat.


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Is there redundancy in the auditory system like there is in the visual system?
In the early visual system, there is a great deal of overlap between retinal ganglion cells, which results in redundancy of the signals that neurons carry to higher visual processing areas in the brain.
Is there a similar type of redundancy in the early auditory system?

There is certainly redundancy in the auditory system, well demonstrated by Gal Chechik et all
It is also clear that there is pronounced intersensory redundacy, involving auditory systems here
Another article discusses clear auditory redundancy in adults when participating in a task to discriminate between two sounds as quickly as possible
...the auditory system maintains and tolerates functionally independently represented redundant and contradictory predictions.
In terms of redundancy in development, it seems there have  been shown links in mice discussed by Dr Thomas Braun
Hope this helps!


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Has anybody used Evrogen's DSN-normalization protocol for cDNA normalization?
I found the link to a commercial product by Evrogen to normalise cDNA samples for gene discovery projects here:
http://www.evrogen.com/technologies/normalization.shtml
The most up-to-date reference seems to be this Curr Protoc Mol Biol. paper by Bogdanova et al.:
http://www.ncbi.nlm.nih.gov/pubmed/20373503
They claim their method is compatible with nextgen sequencing platforms:

cDNA normalization using duplex-specific nuclease (DSN) is a highly
  efficient approach that can be applied for normalization of
  full-length-enriched cDNA (Zhulidov et al., 2004; Zhulidov et al.,
  2005). The resulting cDNA contains equalized abundance of different
  transcripts and can be used for construction of cDNA libraries and for
  direct sequencing, including high-throughput sequencing on the next
  generation sequencing platforms (Roche/454, ABI/SOLiD or
  Illumina/Solexa).

Has anybody successfully used it for next-gen gene discovery projects?

This seems to be more like a poll than a question.

Can I turn it into a poll in this website?

No, I meant more that poll-type questions can be closed as "not constructive".  You should probably reword it a bit to prevent this.


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Variance in Fst in the infinite island model
The most famous result in the study of structured populations come from Sewall Wright. He showed that in an island model, where each subpopulation is of size $N$ and the migration rate is $m$, then the pairwise $F_{ST}$ is
$$F_{ST} = \frac{1}{4Nm+1}$$
This equation gives the expected $F_{ST}$. Because populations are finite in size ($N$), genetic drift yield this value to vary.
What is the variance in $F_{ST}$ in the infinite island model?

References
evolution in mendelian population is the original paper who derived this result from Sewall Wright.
Indirect measures of gene flow and migration: FST≠$\frac{1}{4Nm+1}$ is an influential paper in the field.
GENE FLOW IN NATURAL POPULATIONS is a famous review as well.

Could you post a reference or two in which that equation is derived?

@tel See my edit. Note also that I reduced the Fst formula making the standard assumption that $m>>\mu$ (, where  $\mu$ is the mutation rate) just to make things easier. Thank you

Say @Remi.b, if I had two populations, and for each population I knew the genotypes of each individual (e.g. Aa, AA, aa, etc.) but for multiple loci (e.g. AABb) do you know of any simple ways of calculating the gene flow between these two populations? I used some R packages in the past but they were a bit fiddly. If you can recommend me a R/Python package and/or the breakdown of the maths I would be much obliged.

@hello_there_andy Is it good to hear from you again. You should make a new post for your question. I don't quite know the answer right now.

From Lewontin and Krakauer 1973, the ratio
$$\frac{F_{ST}(d-1)}{\bar F_{ST}}$$
approximatively follows $\chi^2$ distribution of degree $k=d-1$. Here $d$ is the number of demes (number of islands), $F_{ST}$ is the random variable of the $\chi^2$ distribution and $\bar F_{ST}$ is the average $F_{ST}$ that is $\bar F_{ST} = \frac{\sum F_{ST}}{n}$, where $n$ is the number of $F_{ST}$ values.
The variance of a $\chi^2$ distribution is $2k$, therefore
$$var\left(\frac{F_{ST}(d-1)}{\bar F_{ST}}\right) = 2d-2$$
Taking $\frac{d-1}{\bar F_{ST}}$ out of the ratio, the variance of $F_{ST}$ becomes
$$var(F_{ST})=\left(\frac{d-1}{\bar F_{ST}}\right)^2(2d-2)$$
, which simplifies into
$$var(F_{ST}) = \frac{2(d-1)^3}{\bar F_{ST}^2}$$

The above expression is probably the most interesting result but one could go further and express the variance independently from the mean (by replacing $\bar F_{ST}$ by Slatkin 1991 expectation for $\bar F_{ST}$ in a finite island. It yields to
$$var(F_{ST}) = \frac{2(d-1)^3}{\left(\frac{1}{1+4Nm(\frac{d}{d-1})^2}\right)^2}$$
, which again "simplifies" into
$$var(F_{ST}) = \frac{2 \left(4 d^2 m N+d^2-2 d+1\right)^2}{d-1}$$


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How to selectively download 3 fields from every record in UniProtKB?
I want to download a comprehensive table of protein names from uniprot.org.
More precisely, I want to generate a tab-delimited table consisting of the id (accession), entry name, and protein names "columns" from the UniProtKB database.
I want to get these three columns/fields for all 80M records in UniProtKB, and I don't want to specify all those Uniprot IDs through, e.g., a bazillion URL-encoded queries.  Also, I need to do this from a host that I can access only through a text interface, which basically rules out browser-based solutions.
I just spent a couple of hours going back-and-forth over the Uniprot site's docs, and I can find nothing useful.  The Perl example given there1 shows how to download full records, but downloading every full record from UniProtKB would be too slow and onerous to be considered2.
Does anyone know how to modify the Perl example (or any other way) to download only the three desired columns from UniProtKB?

1 You need to click on the phrase "Perl example" to see the code.
2 I downloaded a small test sample of 1000 full records, I found that the size of the information I actually want from those records is only 0.2% of the total.  IOW, downloading the full records would take up ~500x as long as downloading only the desired information.

I have never worked with perl and I'm unsure of its commands but by the sound of it you need to specify the columns using regular expressions in the download command lines (e.g. in the R language you use commands such as grep or regexpr). Hope this hint helps!

did Biomart work ?

@WYSIWYG: Thanks for the suggestion, but I had used Biomart before and found it difficult to work with, so I basically ruled it out as an option for this.  I was looking for answers based directly on an API published by Uniprot.org.

BioMart is connected to UniProt (it is basically an ENSEMBL resource to connect with all EBI/EMBL databases).. If you install biomart then you can easily pass commands to download specific data. It is quite convenient; they have improvised it as well; so you can have a look at it again.

Use BioMart. It retrieves UniProt information and you can select the features that you want. These files wont be that huge. So  you can download it in your PC and SFTP to wherever you are doing your analysis. A better way is to install BioMart in your workstation. See the BioMart documentation.


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"Gold standard" for CNV detection methods?
Is there a generally accepted "gold standard" for testing the performance of CNV detection methods?  I'm interested both in learning about existing datasets that may serve as gold standards for CNV detection, as well in methods for producing such datasets in the first place.
(In case it matters, I'm primarily interested in the evaluation of CNV detection methods in laboratory mice.)
Thanks!


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Why does the definition of a "gene" require it to have a product?
In a textbook, I found the following (emphasis in the original):

At this point, we can provide a molecular definition of a gene as a sequence of DNA that specifies production of a functional product, be it a polypeptide or a functional RNA molecule.

The concept of a gene predates our knowledge of DNA by several decades.  My understanding of the original meaning of the term "gene" is that it was thought as whatever it was that conferred a heritable trait to individuals, and that could mutate and (in the case sexual species) segregate independently (of other such "genes").
Therefore, I don't see why, for example, a distant enhancer (which does not code for product) would be considered a gene.  After all, it is inherited, and could conceivably exist in various forms ("alleles") in the population.  These various forms could have different effects on the phenotype, and thus be grist for selection, just like any other gene.
Are there example of such "non-product" genes?  If so, how common are they?

TL;DR - It's just a scientific convention. Whether it is good, broad enough etc is another question.
The question is a bit like asking why in mathematics, the set of natural numbers does not contain negative numbers. The reason is simply because it was defined like that as it was considered a useful working definition.
As you noted the definition of a gene has radically changed, from being defined by the oberved phenotype, to a molecular definition agnostic to functional consequences.
Maybe your interpretation of the old definition of a gene (as an inheritable, modifiable piece of genetic information) is correct, but modern nomenclatures tend to focus on what one may call defining "minimal functional categories". You could define a gene as a group of all the sequences that lead to a given phenotype, sure, but for a complex phenotype like "being tall", you would have to include a huge part of the genome in your definition of the gene (growth factors, transcription factors, cellular metabolism, all of it!!). Pretty much anything could be a gene of some kind given a certain context. And if everything is a gene, well, then the definition is too broad and not really useful.
That is why a bottom-up definition is more useful: define the gene as small units that may or may not infuence certain phenotypes, and then define the phenotype as the result of all the genes involved.
Many things that can be inherited and that exist in various forms are the product of distant pieces of DNA, some coding for proteins, others for regulatory RNAs, so the scientific community decided to define the gene as the "minimal functional unit" of genetic information. That does not mean that each gene is unaffected by other factors (just like for example a "cell" is a functional unit but must be considered as a part of a broader context to understand how it works), so genes may interfere with each other, overlap etc.
It's also important to emphasize that the gene is not only the protein/RNA coding sequence, but also includes promoter regions, untranslated ends and many other regulatory elements that can also have inheritable phenotypic consequences. So pretty much anything functional is part a gene; enhancers are a special case, and a recent challenge to this contemporary definition of a gene, because they challenge the previously accepted notion that genes are structurally continuous and therefore spatially well-defined.

What happens when an enhancer or promoter affects multiple protein-coding sequences?  Is it considered part of all those genes?

What language is TL:DR?  The language of this site is English.


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How can I control or anticipate the time that a caterpillar spends in its chrysalis?
My young daughter caught a caterpillar (pararge aegeria, to my non-expert eye) and we put it in a breathable jar with leaves, kept indoors in England. (Current climate is around 14-19 degrees Celcius at home, I have no specialist equipment to control the environment.)
In the last few days it has entered its pupil stage in a very dark brown chrysalis. I would like my daughter to be present at its emergence, if possible.
Is there anything I can do to either control the time that it emerges, or anticipate the time that it emerges?


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What is the evolutionary reason behind the fragility of teeth?
Almost all organs in the human body have a rather large threshold within which the organ or tissue is capable of repairing itself using materials supplied by the body, whether it's made from organic tissue or structural proteins. Wounds and minor damage to the skin or flesh for example heal by themselves, skin, nails and body hair can grow back if damaged or removed, even most bones can be repaired autonomously by a biological body. Cutting off a significant chunk from the human flesh or removing over 90% of a hair or a nail would cause no permanent injury, and the body is capable of repairing the damage over time with ease. The vast majority of the human body (not counting critical organs such as the heart or the brain) can be "grown back" to an extent by itself, because such parts have a rather large damage threshold.
On the contrary, teeth do not. There is a certain threshold in which tooth enamel can be supplied and "repaired" by the body to an minimal degree, but past that point virtually any damage caused to teeth are permanently irreparable by natural means. Which is quite strange, given how fragile a set of human teeth is, be it chemical or physical damage. Especially if you take more "artificial" causes into account. A moderately heavy object aimed towards a human mouth, for example, can easily render ten to fifteen teeth permanently damaged past the point of recovery within a heartbeat, also causing the said person's digestive process to be heavily impaired.
Another strange fact worth noting, is that the human body is capable of producing two separate set of teeth due to biological growth and size differences, but not more than that. Wouldn't it be beneficial for a biological body to be able to supply new teeth in the place of ones that have been damaged or removed? One could argue that such an action would be too complex and impossible, similarly to growing back an entire limb or a spare heart, but given the material that makes up teeth and its fragile nature, it would be safe to assume that it is biologically possible, especially given the fact that the human body DOES produce two separate set of teeth over its lifespan.
However, even stranger still, is that the only element capable of damaging or deteriorating  teeth by natural means, is the consumed food itself, and the acidic bacteria found within. Several types of edible food consumable by human means are capable of damaging the enamel to critical levels within relatively short periods of time, even non-artificial ones. What happened before the invention of the toothbrush and various dental cleaning methods? Why haven't humans evolved in the past tens of thousands of years to the point where repairing or regrowing teeth by natural means is feasible? Simply put, why don't teeth grow back contrary to hair, nails or skin?
What is the biological and evolutionary reason behind teeth being so fragile and indisposable?

Regarding the replacement of teeth, sharks do this continuously.

I think your premise is wrong - teeth are not fragile and enamel is supposed to be the hardest part of the human body. Also, strictly speaking, humans do not produce two sets of teeth independently. Both sets are produced at the same time (with a very cool looking result): The mouth of a child is a terrifying thing to behold

@RoryM most non-mammals replace teeth continuously mammals are the weird group out with only limited numbers.

I don't recall where I read this, but I believe human teeth cannot be replaced because we require a fairly high-precision bite. Compare this with a shark's mouth where they just need a bunch of teeth in the same general area, making it practical to regrow them at will.

The evolutionary biologist in me would argue that, on average, teeth are exactly as strong as they need to be. In other words, the fitness cost of producing and maintaining teeth is balanced with the the fitness benefits of having teeth.
To address your questions from an evolutionary lens:
Why haven't humans evolved in the past tens of thousands of years to the point where repairing or regrowing teeth by natural means is feasible? Simply put, why don't teeth grow back contrary to hair, nails or skin?
The short answer is that we have evolved the ability to regrow teeth. That's why you lost your baby teeth and a new set grew in their place. And why most folks have wisdom teeth that grow in later in life.
Essentially, we only need enough functional teeth to get us to the point of reproduction. After that, the effects of selection for stronger, more, better teeth wanes.
You may find this review article1 helpful wherein the authors explore the evolution of teeth, and specifically health issues related to teeth from an evolutionary perspective.

[1] Koussoulakou et al. (2009) A curriculum vitae of teeth: evolution, generation, regeneration. Int J Biol Sci; 5(3): 266-243.

you do realize endless teeth is the norm mammals have lost that ability. We have not evolved the ability to grow new teeth, we grow a set number of teeth.

Human teeth and animal teeth are not fragile. It is meant to last a life time, barring physical injury. If anything makes it fragile it is ourselves. The main two causes of tooth loss is dental decay and gum disease. Both are cause by the soft tenacious bacteria filled biofilm called 'Plaque". If there is no plaque then there is no dental caries(cavities) and no periodontal disease(gum disease).
Wild animals don't have both and eskimos did not have these diseases till they were exposed to modern civilization. Raw fibrous food have a terrific cleaning effect and effectively removes plaque. And even if there is plaque, since there is no refined carbohydrates there is no decay.
If you want to prevent dental decay remove plaque completely, by brushing ,flossing and sealing all the pits and fissures where plaque can lodge. Follow this and one can eat all the sugary things without worrying about their teeth if not anything else.

"If there is no plaque then there is no dental caries". I can agree with that, as there must be a method of decay, but is bacteria really the cause? Can a tooth be "healthy" enough to resist the actions of bacteria (which I would think would be present in everyone's mouth, yet some people's teeth don't decay even with no brushing ie eskimos)? An analogy would be that dead animals decay because they're dead. If they decayed because of bacteria, then live animals would decay as well (unless they cleaned the bacteria off 3 times a day, which they don't). I question the accepted cause of caries.

The sequence is like this: Plaque harbours and protects the acid producing (acidogenic) micro organisms. Acid producing microorganisms metabolise refined carbohydrates to pretty strong acid. This acid easily decalcifies the enamel which is 96% minerals. However the quantity of the acid priduced is minute and its action lasts for 20 minutes to 40 minutes and tapers off. The role of the plaque is to harbour these Microbes in high concentrations close to the enamel or tooth structure and to prevent dilution of

the acid by saliva. The effect of acid in enamel is like acid on marble. Enamel gets damaged even by mild acids like carbonated drinks. These are well established facts readily available in standard text books in Dentistry. In short no plaque no caries.

@RamManoharM I've heard the claim before that indigenous people had no cavities nor gum disease until after European contact. Do you have a reference that evidences this?

human teeth are rather fragile compared to the teeth of other animals, and the material itself is rather weak compared to other hard biomaterials

Because teeth first evolved to be disposable not permanent... then mammals lost the ability to replace them.
There are two questions here, one about regrowth of teeth the other about tooth composition.
Tooth regrowth
The norm for vertebrates is to keep growing new teeth forever, mammals have lost this ability, the current reasoning is that the ancestor of all living mammals were all small nocturnal short lived insectivores. Because of this we are stuck with a bunch of otherwise counterproductive adaptations, limited numbers of teeth is one of them. insectivores benefit greatly from tightly fitted complex teeth which you can't do with endlessly growing teeth (you can dinosaurs found a way but it is not easy) The current understanding is that mammals used (mutated) the genes that let us regenerate growth centers for teeth into genes that control the shape of teeth which is why mammal teeth are so much more complex than any other group of organisms. Since they were short lived this limited number of teeth would not be a hindrance. Because these genes are now used for something else the only way to get them back would be to recreate them from scratch. (two great books on the subject non mammalian teeth and the (evolution of teeth) Mammals don't really grow multiple sets of teeth they grow one set of teeth over an extended time frame, some mammals like elephants only grow a few at a time but still run out eventually. Note there are one group of mammals that does keep regrowing teeth, cetaceans have re-evolved polydont by giving up the differentiated heterodont complex teeth of other mammals, they have lost the genes entirely. So for mammals the choices are extremely simple endless teeth or a set number of different complex teeth.
Why teeth are made of what they are
Tooth enamel and dentin did not originally evolve for eating things, they developed from the external armor of thelodont fish. The inorganic salts teeth are made from were originally a way of storing calcium, then were used in armor, then were used for their electrical properties, only after all this did they start to get used for processing food. Basically early fish used what they already had available, not a material specifically evolved for shear strength, so now we as their descendants are stuck with it. Evolution involves a lot of jerry rigged solutions, teeth happen to be a good example. Snails for instance have "teeth" (radula) made of a much harder material than vertebrates have, it is actually among the strongest natural materials ever found.
Why human teeth are particularly weak
Now humans have fairly weak teeth because we have much less enamel than our relatives (chimps, early hominids, ect) this is believed to be due to to invention of tools and cooking by our ancestors, cooking, among other things, softens foods. Teeth cost a lot in terms of energy and calcium to produce so if they do not need thick heavy enamel to they will naturally evolve to be weaker so those resources can be used elsewhere. On top of that our jaw is much smaller so there would have been considerable pressure ot make teeth smaller as well. For most of human history our teeth were good enough, only now with advances in medicine and sugar rich foods are we regularly exceeding the operational lifetime of our teeth.
To sum it up mammals are using a disposable structure in a permanent capacity.

Human teeth are strongly attached to a socket, which is not true for many other animals. Our teeth are designed to last our lifetime (specifically up until the point we pass on our genes). Most people's teeth last until they are in their 50s, when the majority of people have passed their genes on.
As for food attacking our teeth, this would be fruit juice, sugar etc. These were not the diet of people years ago, in fact refining sugar is more of a recent discovery. And since that time we have been plagued with bad teeth. I think it was queen Victoria that was first introduced to refined sugar and suffered deleterious consequences quite rapidly.

Adding to your answer; for most of our evolutionary history we lived shorter lives and reproduced at an earlier age. Therefore, our teeth have probably served us fine, and there haven't been strong selection for even more durable teeth. I can also imagine a trade off with other parts of the body for the minerals needed to build teeth, especially in a sometimes poor hunter/gatherer diet.

Sugar is water soluble, so it doesn't stick to teeth. The real enemy is starch found in grains.


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Is it possible for a person to become "reinfected" with the same strain of a virus?
If a person contracts a virus, viral conjunctivitis for example, is it possible for the individual to become "reinfected" with the exact same strain of the virus once the person has it treated and the symptoms have gone away? I am a nursing student and am fascinated with virology, but my basic microbiology class did not go very in-depth on the subject.

I think norovirus might be a example. Although patients develop immunity after recovery, the immunity wanes quickly. So a person can contract norovirus for multiple times. I don't know whether it's because of viral mutations.

The nature of infectious agents is that they transmit between organisms. This means that they have reservoirs outside a single host, and hence of course encountering the exact same strain twice is possible if this strain leaves the body and at a later stage is carried back to it. This could typically happen for example with influenza or common cold viruses, spreading from one child to other children at school and later being carried back to the original child through them.
The reason why the child will not develop another illness when being exposed to the same virus again is the adaptive immune response: After the first infection, immune cells specific to a pathogen will proliferate and differentiate both into effector cells to destroy the pathogen, and into memory cells. These can mount a much stronger immune response much faster when they come in contact with the same (or a structurally very similar) pathogen, meaning that a secondary exposure usually does not result in a proper infection and illness. Of course, this mechanism doesn't work properly for anyone with a compromised immune system.
In most cases where a viral disease develops repeatedly, this is due to evasion mechanisms. For example in some viruses, those antigens which tend to be targeted by immune systems have high mutation rates. In this case the "same" virus is actually a mutated strain which causes the same illness, but "looks" different to the immune system, and so the memory cells don't respond. Again, influenza is a great example. The reason why we get flu again winter after winter, is because this virus tends to mutate over the year with relatively low infection prevalence. Then during the winter, when the conditions are favourable for flu infections, typically only a small number of strains cause epidemics - because we were maybe immune to last year's influenza, but this year's has mutated antigens which our immune systems do not recognise yet.

Much better! I'm removing my down vote and deleting the comments you've addressed. I'll upvote if you add some references :) I know it's a pain for answers you pull from your general knowledge, but it's how we keep things honest here!

Exactly that - the Q is asked at best around first-year undergrad level, so I wanted to keep it simple. WP links should suffice for a reader here. Your answer complements this very well with more depth and detail, you're clearly more familiar with this field than me :)

@DeNovo: Actually could you repost the comment regarding winter prevalence of influenza? I had no idea about that (I'm guessing this is more recent than my degree), and thought it was an interesting detail to add on this topic.

i don't remember exactly what I said, but it was probably something about the immune system not being "weaker" in the winter and seasonality being a function of a virus, not the immune system. Influenza has a winter peak because it is more stable in dry cold conditions. Other viral infections (e.g., enteroviruses, arboviruses) have a summer peak.

As discussed in @Armatus's answer, the adaptive immune response can protect against or severely limit the progression of re-infection.
Viruses have a number of ways to escape the adaptive immune response (see Murray Medical Microbiology Ch. 48). They can interfere directly with the immune system (e.g., preventing interferon action or suppressing antigen presentation), they can hide from some parts of the immune system (e.g., by spreading directly from cell to cell, or maintaining a long intracellular latent period). Some viruses are empirically less immunogenic, resulting in waning immunity. A given viral species can have a very large amount of antigenic variability, and/or a high mutation rate for important antigenic sites. Some of these escape mechanisms help maintain an initial infection and some reduce the effectiveness of a memory response on re-infection.
Viral conjunctivitis is caused by one of several serotypes of adenovirus. Generally, infection is believed to produce protective immunity against the same strain (Ch. 52, Murray Medical Microbiology), but there are many different serotypes and, perhaps more importantly key antigens are highly variable. Adenovirus uses a few other strategies to escape the adaptive immune response. The virus can enter a latent intracellular phase (avoiding the humoral response) and block a number of important effectors of cell mediated immunity with small interfering RNAs (avoiding the cell mediated response). Despite this, infection does result in seroconversion, and empirically, protection against reinfection by the same strain (Murray Ch 52 again).

Viruses that mutate quickly (particularly notorious are respiratory viruses such as the flu and common cold) quickly produce new "strains" within the same virus family. While most people should be familiar with the terms "influenza A" and "influenza B", those are merely blanket terms for a large family of viruses with thousands of strains (by surface structure). Immunity against a given strain is no guarantee of immunity to a different strain.
In the general case, reinfection with an exact same strain previously recovered from is possible if the immune system "forgets" the pathogen (which happens with some infections, hence the need for periodic booster shots) or if the person becomes immunodeficient.