text:
Why can white hairs get dark again?
I have learned (probably in high school?) that hairs turning white is caused by the part of the folicle which produces the pigment dying and being replaced by an air bubble. This sounds very irreversible.
I have long dark brown hair, and since I turned 25, I have had a few white hairs here and there. It is not unusual to find hairs which have a dark tip but are white at the root, which fits the above theory.
But I also have hairs which are the opposite: the lower ten centimeters are pure white, but at some point, there is an abrupt transition to dark brown, and the hair is dark again up to the root. This is all a natural phenomenon, I haven't used dyes or bleaches.
So what makes white hair white, if it can turn back to dark? Why would a single hair turn back?

The pigmentation of hairs is achieved by the follicular melanocytes (specialized pigment cells) at the base of the hair shaft. These cells produce the pigment which is subsequently transported into the cells which produce the hair and integrated into the hair matrix.
Besides genetic reasons, there are two major ways of losing this pigmentation. First, as a part of the normal hair cycle, the hair grows for a while until it falls out and the hair follicle regresses. In this process the cells in the hair follicle die, including those which made the hair as well as of the melanocytes. In this step of the hair cycle the hair follicle changes its morphology. When a new hair cycle starts, the pigment cells in the hair follicle are replenished from a stem cell population called melanocyte stem cells. These cells are located in the hair bulge (marked in red in the figure below). The cells then start to proliferate to multiply their number. A few of these cells stay stem cells (to be able to repopulate the pigment cells after the next hair cycle.) Others differentiate into melanocytes which subsequently migrate towards the bottom of the hair bulb (shown in green in the figure).

Over time, the number of stem cells gets lower, and at some point there are none left. This leads to a situation where the pigment cells are not replenished at the beginning of a new hair cycle and the hair stays unpigmented. As this is a continuous process, the pigmentation gets weaker before it is completely lost. As far as this process is understood to date, this depigmentation is irreversible.
There are two very interesting papers about this topic:

Melanocyte Stem Cell Maintenance and Hair Graying
Melanocyte stem cells: biology and current aspects.

The other reason for losing pigmentation (temporarily or permanent) is the generation of so called "reactive oxygen species" (Hydrogenperoxide) in the cells of the hair follicle, which then destroy the pigment. This is basically the same reaction which is used to bleach hairs, but in this instance from inside. This reaction can have numerous causes, among them are vitiligo and stress. The reason for the build-up of the hydrogenperoxides is that enzymes, which usually break them down before they can cause harm are either mutated or downregulated. If the level of these enzymes (the catalases) goes back to normal, pigmentation is also getting back to normal. This has been tested experimentally with people who suffer from the pigmentation disease vitiligo.

Oxidative Stress in Ageing of Hair
Basic evidence for epidermal H2O2/ONOO−-mediated oxidation/nitration
in segmental vitiligo is supported by repigmentation of skin and
eyelashes after reduction of epidermal H2O2 with topical
NB-UVB-activated pseudocatalase PC-KUS

Can malnutrition cause temporary greying/whitening of hair?

@CRags If you lack tyrosine and cysteine, probably yes. Though I haven't read any reports on people changing their pigmentation levels upon a famine.

When you say "This includes dying of the cells" are you saying the hairs are "dyed" or they "died?"

@CayetanoGonçalves These cells actually die, I re-phrased the part. I hope it is clearer now.

One of the best answers I've come across, I find. With some basic knowledge, and speaking of dying - intrinsic pun - I think the answer just does not refer to any dying of the hair producing cell, as this is beyond this question. I wonder about related questions on StE about the dying of hair cells. Hair grows after death.

@PeterBernhard It is a myth that hairs and nails grow after death: https://www.snopes.com/fact-check/coffin-nails/

I think so, too, basically. Just let me know in case I am up to delete the comment or its final sentence. Great answer!

Hair colour is maintained by a pigment called Melanin which also affects skin colour too. When the melanin content in your hair decreases, it turns grey and eventually white. Multiple factors affect melanin levels in your body.
1) age
2) Genetics
3) Diseases
4) Cell Stress
You can read about them in a little more detail here. I cannot specifically pinpoint if you have deficiency in a particular mineral or the reason for your hair whitening is hereditary from your question. It could be a singular reason or a combination of different problems. Some solutions to treat hair can be found in this link (and plenty more if you Google it). If that doesn't work, I would suggest you meet a certified Dermatologist specializing in hair treatment.

A search of the Internet shows many anecdotal cases of people reporting their grey or white hair returning to their normal color.  Interestingly, many of these ancedotal cases begin by stating that their hair had turned grey or white at a young age (early 20s) before returning to it's natural color.  Finding a scientific explanation does not seem as easy.
Dr. Robert Graves reported in 1847 a case of a military field officer that had contracted dysentery, fever and other diseases. Prior to his illinesses, the officer's hair had turned white. After a few years of receiving treatment for his illiness, his hair had returned to its natural color.  This is consistent with a study by Bublin and Thompson (1992) which found that various drugs can cause sudden hair color changes. (The abstract does not say whether this includes a change from white to natural color.) Schaffrali et al. 2002) noted two people that had a disease called porphyria cutanea tarda regained their hair color.  Therefore, stress from disease or drugs may cause hair color changes.
Flesch (1949) found that the fur of black rats could be turned white when fed a diet deficient in copper. Restoring copper to the diet turned the fur color back to its normal color. Arthur (1965) found that excess molybdenum in the diet of guinea pigs can inhibit copper,  causing their hair to turn white. These results suggest that diet can also play a role in color loss and gain in mammals.  Vitamin B12 deficiency may also have affect hair color.
These studies show that regaining hair pigmentation has many possible causes. Of course, I have no way of knowing whether any of these apply to you, nor am I qualified to make such judgements. But, hopefully, some of this information will help you to understand some of the possible reasons for hair color change in humans.

In the case of drug induced pigmentation changes, there are two possibilities. Either the drug kill the melanocytes which produce the pigment and they are later replenished as I explained in my answer or that the drugs interfere with the signalling pathways which regulate the pigmentation. The case of the diet lacking copper is relatively easy to explain. The most important enzyme in the pigmentation process is Tyrosinase, as it is catalyzing the first step of the synthesis of melanin. This enzyme has copper in its active center, without copper it is not functional.

@Chris Thanks for improving the information contained in my answer.


text:
What is the maximum amount of different bacteria in the drinking water in Europe?
I am looking for a statistical amounts which are allowed.
Some students say it is 0 for all bacteria, which I think is false.
I found this USA source.
I found there

Total Coliforms (including fecal coliform and E. Coli) mg/l. No more than 5.0% samples total coliform-positive (TC-positive) in a month.
Giardia lamblia: 99.9% removal/inactivation.

What is the right place to look for such information?

According to a text I'll reference later, humans face larger risk with microbial contaminants that chemical ones. This is the reason why most water quality standards and guidelines (including who) recommend (or allow) 0 counts per 100 ml for bacterial indicators.

No, your colleages are right: There should be no coliforms in drinking water in Europe following the Council Directive 80/777/EEC.
This PDF from the Northern Ireland Environment Agency (which follows the directice mentioned above) shows this a bit nicer.
It makes sense, since coliforms are a sign of mixing sewage and fresh water. Nothing you want to have happening.
This is the relevant table from the linked PDF:

source: Stack Exchange

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sort: votes


text:
How do fish tolerate pH changes in water?
I want to know how aquatic animals behave as a natural indicator of the acidity in lakes and rivers.
How do they tolerate these pH change?

By tolerate do you mean the mechanisms that fish have to mitigate the harmful effects of the pH change?

Often, in terms of a water body becoming acidified, it depends on the rate of acidification.  Fish and other aquatic species, such as invertebrates, are fairly resilient to miniscule changes, but they also have a threshold at which not a lot of them, adapted or no, can survive.
From the U.S. Environmental Protection Agency (http://www.epa.gov/acidrain/effects/surface_water.html):

Acid rain causes a cascade of effects that harm or kill individual fish, reduce fish population numbers, completely eliminate fish species from a waterbody, and decrease biodiversity.  Low pH [...] is directly toxic to fish. In addition, low pH and increased aluminum levels cause chronic stress that may not kill individual fish, but leads to lower body weight and smaller size and makes fish less able to compete for food and habitat.
Some types of plants and animals are able to tolerate acidic waters. Others, however, are acid-sensitive and will be lost as the pH declines.

Commonly, benthic invertebrates (including insects, crustacean and molluscs) are used as indicators for ecosystem health.  Invertebrates that need a high amount of calcium, such as crayfish (for their exoskeleton), are typically not found even in slightly acidified lakes.  Other invertebrates can be used as indicator species because they respond to changes in water conditions, such as pH.

A good example of this is the acid rain that occurred in Sudbury, Ontario, Canada as a result of sulfur dioxide emissions from mining activities, which were especially high in the 1970s.  This affected the lakes in the area not only from acid rain, but the runoff as well as there were no trees left.  The pH was so low that it effectively made all lakes in the area sterile. Since then, a lot of effort has been put into bringing back the native aquatic species, such as liming the lakes and restocking them with species such as Brook Trout (Salvelinus fontinalis).  More information can be found here:
http://link.springer.com/article/10.1007%2FBF00160348
Therefore, I do not know that aquatic animals necessarily behave a certain way as a natural indicator of acidity, however it is more of their presence or absence that biologists use to determine acidity and the overall ecosystem health in lakes and rivers.

Commonly, benthic invertebrates are used as indicators for ecosystem health. Invertebrates that need a high amount of calcium, such as crayfish are typically not found even in slightly acidified waters. Other invertebrates can be used for indicator species as they respond to changes in water conditions, such as pH.

This doesn't answer the question as it speaks of fish as indicator organisms not how they tolerate pH changes in water

This actually does attempt to answer the first part of the question, which is how acquatic animals behave as natural indicators of acidity. The answer here states that benthic invertebrates are not found in acidic water. Thus their absence may indicate acidity.

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text:
How does activation of adenylcyclase lead to increased cAMP and diarrhea?
I am trying find explanation for these mechanisms

Tox plasmid -> exotoxin (enterotoxin) -> activation of adenylcyclase
  -> \up cAMP enterocytes -> release of H2O, electrolytes in gut lumen -> diarrhea.

Tox plasmid is a toxin generated by the genus enterobacteriaceae.
I read this as that exotoxin Tox activates adenilciclase enzyme (protein) which increases the amount of cyclic AMP in the enterocytes, and releases water and electrocytes into gut lumen consequently resulting in diarrhea.
How does the activation of adenylcyclase lead to increased cAMP heparis and diarrhea?

The crypt cells of the gut can actively secrete electrolytes (ions) via special channel which finally leads to water secretion. This is usually tightly controlled, since uncontrolled loss of water is obviously not good for the cells.
Have a look at this schematic figure, (from this webpage):

Sodium, Potassium and Chloride ions are co-transported into the cell,
sodium and potassium are transported back out via other channels.
If the adenyl cyclase is activated (for example by bacterial toxins,
cholera does this), then cAMP is made.
cAMP aktivates Protein Kinase A (PKA) which in turn phosphorylates the the Cystic fibrosis transmembrane conductance regulator
(CFTR)(this channel is also important for cystic fibrosis) which leads
to the secretion of chloride ions from the cell. This builds up a
negative potential across the membrane (positively charged ions are
missing).
This leads to the secretion of sodium ions through the tight
junctions, resulting in the netto secretion of NaCl.
The secretion of salt builds up and osmotic gradient across the
membrane, which leads to water secretion and can also lead to hyponatraemia.

To overcome this problems, the so called "oral rehydration therapy" is used. The solution contains of an isotonic solution of sodium chloride and glucose. This is taken up by the sodium-glucose symporter (a special class of transporter, that transports two molecules in the same direction) and builds up a gradient which is directed in the opposite direction of the diarrhoea, helping to fight dehydration.

What is netto secretion of NaCl?

I think the water goes inside cells wit the transport of Cl- ions. Then, NaCl accumulates in the cells. The gradient across the membrane may increase if the water does not follow enough Cl-. This then leads to the water secretion into the cells. Right? Since there is too much water in the intracellular space, more water stays in the extracellular space which then is released as diarrhea stools. Right?

No: Cl- ions are secreted through the CFTR channel. Then sodium is "secreted" through the tight junctions to neutralize the negative charge, which is building up on the outsite. The results in the net secretion of NaCl (which is of course still ionic and not there as a salt.

@DeNovo Thanks for the correction, I have edited the answer. BTW: In such cases it is perfectly ok (and also in line with the stackexchange philosophy) if you edit an answer (or question) to correct mistakes.

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text:
Why Can Varied Species Live Together in Particular Ecosystems?
Consider the following question:

The Piney Woods of Eastern Texas is home to a wide variety of organisms ranging from the grass Longleaf Oats to coyotes. Which of the following best explains why these varied specifies can live together in this particular ecosystem?
  A.) Each species lives in a slightly different habitat B.) Each spices occupies a different niche C.) Each species functions at a different trophic level D.) A and B   E.) A, B, and C

I chose answer choice E with the reasoning that: Oats and Coyotes do not share the same habitat; they occupy a different niche -- Coyotes eat organisms, oats use photosynthesis; coyotes are at a completely different trophic level when compared to oats -- oats being primary producers. The answer choice E however is incorrect and I'd like to know why and what the correct answer should be. Is there a flaw in my logic?

The answer to the question as asked is E. If anyone (even the teacher) says otherwise, they are wrong.

Supposedly the answer is 'B'.

@ChinmayKanchi It isn't the best question in the world but E should not be correct.  Variation in habitat and trophic level are not mechanisms that explain species coexistence in a community.

Variation in habitat and trophic level form part of the niche that a species occupies.

The answer should be B "Each spices occupies a different niche" because this is the only answer that reflects a model of species coexistence.  Niche theory proposes a mechanism that allows multiple species to occupy the same space and time any yet avoid competition for limited resources.  Briefly, the model says that a species niche is the total suite of resources that it requires to survice and reproduce and that coexisting species will limit their niche overlap to avoid competition (and its requisite reduction in fitness).  Species can limit niche overlap by preferentially using a subset of resources that are not shared with potentially competing species (this is called the realized niche) or by evolving a new niche that does not overlap with the competitor (this is called character displacement).
Note that your reasoning is incomplete because the question does not specify that the organisms listed are the complete set of organisms  in the community.  For example if the community contained another species of grass, then choice "C" would be false.  Most importantly though, habitat or trophic variation are not mechanisms of coexistence, so they should not be used as general hypotheses explaining coexistence.


text:
Does biotin affect downstream experiments, such as RT-qPCR?
I have two biotins--one of which is binding my RNA with cleavable bonds, and the other with irreversible bonds. Does biotin have an effect if it keeps its bonds with RNA? If it does, why is this the case?

Having looked into this question, I came across this paper, where they mixed biotin labelled EGFR-mutant-specific oligonucleotide and isolated the target using streptavidin beads followed by real-time TaqMan PCR allowing a 40 fold increase in detection sensitivity of the mutant allele, suggesting that biotin does not effect nucleotides in PCR based experiments.
The life technologies webpage claims that Streptavidin-Coupled Dynabeads M-270 can be used in a PCR reaction as stated below although certain streptavidin-coupled beads can have an effect on the PCR reaction. Hence I do not think biotin itself would be a problem for an amplification reaction.

beads can be used directly in PCR, as they do not inhibit enzymatic reaction. Slight PCR-inhibition has been seen when 75–100 µg of Dynabeads® M-280 Streptavidin was used in 50 µL PCR reaction, and a concentration over 100 µg per 50 µL reaction seems to inhibit PCR completely. Dynabeads® M-270 Streptavidin do not show any inhibitory effect on PCR at these concentrations.

In fact you can buy kits such as this where you can generate/incorporate biotin into your RNA of interest for any purpose. The use of biotin and its incorporation into nucleotides seems prevalent in the literature and there are even kits for this purpose hence you should be on the safe side with your biotin labelled RNA experiments. I think the biggest challenge in RNA work is to keep it from degradation, which as far as I know is achieved through maintenance at -80 oC.


text:
How to relate human metabolic model reactions and cancer drug targets / reactome items?
Trying to find a way to take a cancer drug (from CancerDR, for instance) and infer the metabolic reactions that are affected by it in the Human Metabolic Model.
Essentially, I would like to know which HMM reactions are affected by a certain cancer therapy drug, especially the ones found in the Cancer Cell Line Encyclopedia.
Example:
Searching for the reactions that are associated with the HSP90 protein, which is targeted (to some extent) by the 17-AAG agent.  That way, I can trace back the relevant section of the HMM and mark it as 'affected' by that agent.
This could be a very broad or naïve question, but I am afraid I don't know enough to be able to determine that.
If someone can only provide some tip or guidance, that will be greatly appreciated as well.
Thanks very much!

What exactly do you mean with reactions in the CCLE? Can you provide a link to the relevant resource in the CCLE?

Sure.  I believe you have to create an account, but it's free: Cancer Cell Line Encyclopedia data; go to the last section, "Pharmacological profiling".

Short answer:
For drugs with targets having a direct effect on reactions in the model:
Find the gene name for the target protein -> Find the Entrez Gene ID (or other gene identifier, depending on the model) -> Search the model file or database for reactions having a gene association with the gene identifier.
AND/OR:
Find the EC number for the target protein. -> Search the model file or database for reactions associated with the EC number (likely to miss many reactions or be imprecise).
EC numbers can be found in the UniProt database, while the HGNC database at http://www.genenames.org/ can be used to look up genes by name and find their Entrez Gene ID and other resources, including links to UniProt. Many other databases can also be used.
For drugs with targets having an indirect effect on reactions in the model:
Model/estimate in-direct metabolic effect yourself by using data on known regulatory effects to create new gene-reaction associations or modify the bounds on reactions affected by the drug.
Long answer:
To knock out or constrain a reaction based on data about a drug, you have to go from an entry in a drug database to an EC number or gene identifier consistent with the annotation in the model you are using. However, There is currently no standard annotation nomenclature for gene-protein-reaction (GPR) associations in metabolic models, and in general only direct GPR associations are encoded in model files.
Assuming that you have a metabolic model in SBML format (for example the RECON 2 model), reactions may have a gene association and/or be associated with an Enzyme Comission (EC) Number.1 However, several model reactions catalyzed by distinct isozymes (different enzymes catalyzing the same reaction) may be associated with the same EC number, and many reactions may not be annotated with an EC association. Therefore you might want to use the gene associations directly. Both gene associations and EC numbers are recorded in the "notes" tag for each reaction in the SBML file, and is not part of the SBML specification. (A proposal has been published for improving support for gene associations in the SBML format.2)
Using EC numbers:
Using EC numbers is the simplest, but not the most precise or possibly even usable solution. It is simpler than using gene associations, because genes may described using any of a number of identifiers depending on the database while any reaction is associated with at most one EC number. Once you know the target protein, you can look it up in the UniProt database, and find its EC number (if any) in the field "protein names". A simple example: The DrugBank entry for the cancer drug Fluorouracil (http://www.drugbank.ca/drugs/DB00544), links to the UniProt entry for one of its targets, Thymidylate synthase (http://www.uniprot.org/uniprot/P04818), where the EC number is given as 2.1.1.45. Searching the RECON 2 SBML file (or searching in BiGG at http://bigg.ucsd.edu/bigg/main.pl) for occurences of this number will show that it is associated with the "TMDS" reaction.
The IUPHAR database (http://www.iuphar-db.org/index.jsp) may also be useful.
Using Gene associations:
Genes are conceptually at least one step removed from the reactions their products catalyze, so one might argue that using EC numbers which actually correspond to reactions would be better. However, it is thinkable that a drug might affect only one of several enzymes which catalyze the same reaction and thus share an EC number. Furthermore,  annotation of reactions with EC numbers in metabolic models may be poor. Thus you may want to use gene associations to determine which reaction are affected by a drug.
Unfortunately, due to the large number of databases, a single gene may be described using many identifiers or symbols in different databases. You thus have to identify the gene coding for the product which is the target of the drug, and obtain the correct identifier for that gene which corresponds to the nomenclature used in the model.
Assuming again that you are using the RECON 2 model, it is an update of RECON1 which was made using the BiGG database3. Gene protein reaction (GPR) associations are therefore recorded using the gene names in BiGG. When ignoring the decimal and any following numbers, BiGG gene names appear to correspond to Gene IDs in the NCBI Gene database.5 A question on how to identify BiGG reactions  was also discussed at BioStar.6 However, you have the opposite problem: Finding a BiGG gene name from another gene identifier.
Using Fluorouracil as an example again, the DrugBank entry lists "Cytochrome P450 2C9" as a targeted enzyme, with the effect being inhibition. Following the link to the UniProt entry P11712 (http://www.uniprot.org/uniprot/P11712), we find that it has an EC number 1.14.13.- However, this EC number corresponds to a class of reactions (or rather, enzymes). There are also listed several additional EC number at the single reaction level, but as these may not cover or be associated with all relevant reactions, we'll use the gene association. Going back to the DrugBank entry (or just reading on the UniProt page), we find that the gene name is CYP2C9. Looking up this name at a suitable database, for example the HGNC database of human gene names at http://www.genenames.org/, we find the entry for CYP2C9 (http://www.genenames.org/cgi-bin/gene_symbol_report?hgnc_id=2623) and that its Entrez Gene ID is 1559. Searching for this gene identifier in the BiGG database, we find that four reactions are associated with this identifier (The actual association is to "1559.1"): P4502C9,P4502C92,P4502C93 and P4502C94. Note that none of these reactions have an associated EC number.
Defining your own GPR associations
Keep in mind that even in genome-scale metabolic models, a large number of reactions and processes are missing. While the term metabolism in its widest sense may be used to refer to all reactions occuring in a cell, metabolic models have so far been mostly limited to covering transport and inter-conversions of small metabolites. Processes involving signalling molecules and regulation of enzymes have been mostly or completely left out, along with critical processes such as DNA replication, DNA repair and apoptosis.  Because of the limited scope of the models, gene-protein-reaction (GPR) relations do not generally take regulatory effects into account, being limited to describing direct relations between one or more genes encoding (part of) a protein which directly catalyzes a reaction.
One could also model a very large number of indirect regulatory effects, but as current metabolic models generally do not specify these, you may have to construct them yourself. To find reactions in a metabolic model which are affected by a certain drug, you may have to "travel" several steps of interactions from the original target of the drug. You may consider using protein-protein-interaction network (PIN) data to help in this. You will have to consider the strength/importance of the interactions, something which may require a high degree of manual curation.
For example, if your drug affects HSP90, which is needed for correct folding of certain enzymes, you may consider creating a GPR stating that the gene for HSP90 (or rather, HSP90 itself) is needed for any reactions catalyzed by a specific enzyme to be active. This would be an indirect GPR, as HSP90 does not itself produce any part of the enzyme that catalyzes the reaction. As an alternative to on/off regulation through a GPR, you may consider searching for data on the ratio of correctly folded and misfolded enzymes in the presence and absence of HSP90, and apply bounds on reactions catalyzed by the affected enzyme to reflect this.

Again, I am amazed at your answers :).  Thanks so much for your help!


text:
Does Sirtuin protein family Sir2 work in low-calorie diet mostly?
I am reading about the protein family in relation to the prolongation of cell life.
It is known that

Sirtuins have been implicated in influencing a wide range of cellular
  processes like ageing, transcription, apoptosis, inflammation and
  stress resistance, as well as energy efficiency and alertness during
  low-calorie situations.

However, I am not sure if these physiologic processes are only during low-calorie situations.
Alertness is at least.
It says in the original paper only that

Our results suggest that in the hypothalamus, SIRT1 functions as a key
  mediator of the central response to low nutritional availability,
  providing insight into the role of the hypothalamus in the regulation
  of metabolism and aging in mammals.

However, it does not specify how the Sir2 works to high-calorie diet.
Therefore, I asked mostly.
When is the protein family active?
Does the Sirtuin protein family work mostly during low-calorie diet?

This is a direct citation from the Wikipedia, which also has a reference for this. Why don't you mark it as this and have a look at the citation? Its this one.

@Chris I clarified the question.

Does sirtuin 1 (SIRT1/SIR1) function to mediate the effects of a low calorie diet? Perhaps, but its really not clear.  Is the function of SIRT1 primarily to mediate low calorie response? Absolutely not.  What does that mean for SIRT2/SIR2 - its probably not more closely associated with calorie restriction signals, though it might be connected in a similar ambiguous way... but see below.
Firstly SIRT1 has also been shown to have many influences in many studies of conditions such as Alzheimers, anxiety and other neuro-functions.  SIRT1 modifies p53 - a bottleneck in cellular reproduction and a key regulator in cancer prevention, but which also an important aspect as to why it is active in calorie restriction conditions.
When reading reference like the one you have here its important to remember that correlation is not causality.  Very few genes in animals function only when specific behavior or conditions are experienced, especially signaling genes.
Examining the OMIM report (see link above) there has been a close examination of the possible role of SIRT1 in calorie restriction since the early 2000s in knockout mice.
SIRT1 would seem to play an important role in embryonic development for instance - cell growth is so important at that point and 80% of mice who are homozygous SIRT1 (-/-) knockouts die before they are born and even more die in the early natal period.  The mice who do survive have problems generating red blood cells which is another important case of cellular reproduction.
Yet the relationship of the knockout mice to calorie restriction has been debated - its been difficult to interpret the activity and the weight loss or gain of the knockout mice compared to wild type mice since the SIRT1 knockouts are smaller.  They may also have genetic traits that compensate for the absence SIRT1 in order to have survived.
More recently mice where SIRT1 expression in the brain have been produced, but the result has been anxiety or anxiousness as opposed to specific calorie restriction diet.
This reminds me of the story of leptin, in the early 90s they found that leptin deficient mice became quite fat, but despite this obvious linkage to obesity, leptin turned out to mediate a lot of other psychological factors as well - it only caused obesity when its function was blocked.  It did not turn out to be an appetite signal.
SIRT2 seems to have similar roles in calorie restriction.

Rogina et al (2002) found that under 2 life-extending conditions, Rpd3 (601241) mutants fed normal food and wildtype flies fed low calorie food, Sir2 expression was increased 2-fold.

But also has similar relationships to Alzheimers.  SIRT2 has not been followed up on as much as SIRT1.  This correlation might not be causal or should be nuanced in a similar way.


text:
Which processes are included in the process called cells eating themselves?
I am reading about atrophy and I am thinking to which processes the phrase cells eating themselves refer to.

Cells need something to survive these difficult times. To decrease
  protein synthesis to survive. If insufficient, cells start
  to eat themselves. Then, ubiquitine-proteosome pathway and autophagy
  pathway.

I am not sure if it is only apoptosis.
It can refer here to longer cascade.
I think it can at least refer to autophagy where one cell degrades its components.
Which processes does the phrase cells eating themselves include?

The processes are mentioned in the quote you provided: "ubiquitine-proteosome pathway and autophagy pathway". As far as I know, apoptosis per se is not utilized for recycling.

Please, make that an answer, since it answers the question.

So:
the processes are mentioned in the quote you provided: "ubiquitine-proteasome pathway (note: it's proteAsome) and autophagy pathway". As far as I know, apoptosis per se is not utilized for recycling.


text:
Is there a way to measure ATP usage in the brain similarly to fMRI?
Is there a way to measure ATP usage in the brain (or anywhere else) similarly to how fMRI works (measuring changes in iron resonance in oxygenated/deoxygenated blood)? Is there some sort of similar signal that can be used for ATP?

I'm pretty sure this doesn't exist. If it did, that would be awesome.
The following is 100% pure speculation with nothing to back this up at all (as a disclaimer).
Phosphorus-31 (the stable isotope) is NMR active, which means that you could theoretically use an MRI machine to visualize phosphorus. A quick google search shows scientists attempting to use phosphorus MRI for visualizing bone structure.
I don't really know much about MRI, but I do know some about small molecule NMR, which is based on the same principles. This is a pretty cool paper showing phosphorus-31 NMR used to measure ATP synthesis.
Maybe in the distant future it could be possible to use phosphorus-31 MRI to visualize ATP/ADP ratios in various tissues, including the brain. But that would be some amazing sci-fi stuff.


text:
How many centrioles/basal bodies are there in multi-ciliated cells throughout the cell cycle?
I thought there were only two centrioles per cell, that convert to the basal body at some point during the cell cycle. I also thought there's one basal body per cilium, so I'm not clear on where the other basal bodies are coming from. I'd like to know the distribution of basal bodies and centrioles throughout the cell cycle in multi-ciliated organisms/cells.

check this review out..

There is a single basal body per cilium. During cell division the centrosome has two centrioles, however, during the differentiation of citiated cells, there is an amplification of basal bodies that nucleate from the centrioles.
In multiciliated cells the basal bodies arise from two pathways- 1. de-novo / deuterosomal / acentriolar pathway and 2. centriolar pathway.
In a work carried out by Al Jord et al (2014), the interplay of these two pathways had been studied in the brain ependymal cells. The study shows that post division, when the cell begins to differentiate, the daughter centriole serves as a site for creation of deuterosomes. During this stage deuterosome independent procentrioles also nucleate (the centriolar pathway) on both mother and daughter centrioles. However, the contribution to basal bodies is predominantly from the deuterosomes.

more than 90% of the centrioles were generated via deuterosomes and
  less than 10% directly from centrosomal centriole

Following figure explains the process nicely.

I am not really sure about multiciliated unicellular organisms. My guess is that they retain old basal bodies and new ones are created by a similar mechanism. Most ciliates can also undergo sexual reproduction.

It seems that there is one basal body per cilium in multiciliated cells. Centriole duplication (as far as I understand, a basal body is just a different name for a centriole that is attached to a cilium) is tightly coupled to the cell-cycle. There is always one pair of centrioles that are at the base of the primary cilium (of which there is exactly one in most cells).
But not in multiciliated cells. These cells are differentiated and can no longer divide, and their centriole duplication process is decoupled from the cell cycle. In fact, they aren't, strictly speaking, "duplicating", since many procentriolar bodies may form around one cylinder. Indeed, each cilium has its own basal body; thus a cell with hundreds of cilia has hundreds of basal bodies.

Ishikawa 2011 is a review that examines the structure of primary and motile cilia, and ciliogenesis. It does not spell out how the basal body gets there.
Anderson 1971 describes the formation of new cilia in monkey oviduct. They first remove the ovaries of these monkeys to prevent cells from differentiating (this apparently requires estrogen), then administer estrogen and look at EM images of the cells over the following 6 days. They describe at length the processes of basal body formation.
Dirksen 1991 is another review focusing specifically on basal body formation during ciliogenesis. From their introduction:

In order for the 200-300 cilia to form that the fully differentiated cell will need, production of that many centrioles is required first.
  The cell, after the last division, has usually retained a pair of
  centrioles. To what extent these mature centrioles are involved in the
  earlier stages of centriole formation, in which centriole precursor
  structures of varying sizes and shapes are generated and proceed to
  undergo transformational changes of great complexity, is largely
  unknown..

Sorokin 1968 is apparently a classic text which goes over EM images of ciliogenesis at various stages, and proposes a series of events describing what is happening. This is probably what you want, re: where are the other basal bodies coming from.
Bettencourt-Dias 2007 reviews the research on the formation of new basal bodies. This is another publication that answers your question very directly:

Many ciliated cells, such as those in vertebrate respiratory and
  reproductive tracts, can have 200–300 cilia per cell. This requires
  the generation of multiple centrioles during ciliogenesis. Here,
  centrioles are generated by two pathways, a centriolar and an
  acentriolar mechanism. In the first one, a parent centriole usually
  produces one daughter at a time; however, in certain cases several
  centrioles have been observed to develop simultaneously around one
  parent centriole, with the daughter centrioles being released into the
  cytoplasm to mature. The acentriolar pathway is the major pathway for
  basal body production. In this pathway, fibrous granules 124 that are
  70–100 nm in diameter first appear in the cytoplasm and subse quently
  move to the apical cytoplasm. Deuterosomes appear within the area.
  (...) Multiple procentrioles can grow out from deuterosomes, and
  mature daughter centrioles travel towards the apical region where they
  form ciliary basal bodies.

What about multi-ciliated protists?

@har-wradim I have no idea. The above is for mammals.


text:
about the direct intervention of a child's gender
Can we determine the gender of a child now,I mean,not randomly?
There are equal amount of sperms with X chromosome and Y chromosome.
Can these two kinds of sperms be distinguished easily?
If yes,we can choose the kind of sperm to meet the ovum,then the gender of the child can be determined.

Sperms can and are sorted using flow cytometry to attempt to separate sub-populations carrying X or Y chromosomes. The technique isn't perfect but it is undergoing "clinical trials" in the USA.

Gender selection as an invitro fertilization method has been in limited use in the US for decades. i just found this link: http://chooseagender.com/Methods-Of-Gender-Selection.aspx

"Sex" is the right word when talking about biology.  "Gender" is about the cultural signifiers and differences that a culture puts on people depending on their sex.
There are transexual people and transgender people and intersexed people...so it's a little rude to them to act like biological sex is a binary thing, or that is it totally the same as gender.

yes, sex selection also helps. It is illegal in China and India,but not in most of the countries especially in western countries. It should be a basic human right for parents?


text:
Why do genetic drift generates negative linkage disequilibrium?
The very first sentence of the abstract of this article is:

"In finite populations subject to selection, genetic drift generates negative linkage disequilibrium, on average, even if selection acts independently (i.e., multiplicatively) upon all loci."

Question
Why does genetic drift generate negative linkage disequilibrium?

Im still a bit confused about this.. I understand that low variance should mean that negative equilbria are less affected by selection, and therefor favoured by drift, but I don't understand what causes the low variance to begin with..

@user2810298 I believe negative disequilibria means "associations between deleterious and beneficial alleles" Keightley & Otto, Interference...; whereas I believe positive disequilibria means those between deleterious and deleterious (or, beneficial and beneficial). I think if one has a deleterious allele and a beneficial allele, their fitness effects are canceled out, hence causing low variance.

@Vibius Is there a precise sense in which fitness effects can `cancel out'?

Genetic drift is the change of allele frequencies in a population due to random sampling during reproduction. This can cause some allele combinations to become more or less common than would be expected without drift, thus creating a disequilibrium. However, it's the combination of genetic drift AND selection that generates negative (instead of positive) disequilibria. From the discussion of the article you linked to:

Selection eliminates positive disequilibria more efficiently than it eliminates negative disequilibria, because negative disequilibrium reduces the genetic variance upon which selection acts. Consequently, the average disequilibrium over loci ... becomes negative over time.

Drift can cause negative or positive disequilibria, not just negative, by changing allele frequencies through random sampling error. Since selection acts on variance and negative equilibria correlate with low variance, they are not affected by selection as much as positive disequilibria. Thus genetic drift favours a negative linkage disequilibrium only in the presence of selection. Does that make it clearer? Perhaps I'm not understanding what you're asking (wouldn't be the first time today).


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Fisher's Fundamental Theorem of Natural Selection
Ronald Fisher discovered what he, with humility, called the Fundamental Theorem of Natural Selection. This theorem says (in its modern terminology):

The rate of increase in the mean fitness of any organism at any time ascribable to natural selection acting through changes in gene frequencies is exactly equal to its genetic variance in fitness at that time.

As I understand it, it sounds alike the standard equation that we learn in the first class of Introduction to evolutionary biology
$$R = S \cdot \frac{V_G}{V_p}$$
In words: the response to selection equals the selection differential times the genetic variance of the trait under consideration divided by the total phenotypic variance of the trait under consideration
But how can we prove/demonstrate that Fisher's fundamental theorem of natural selection holds true?
I don't ask for empirical evidences that support this claim but for a theoretical/mathematical proof/demonstration of this claim.

Can the term "selection differential" be used in contexts other than breeding?  Like to say that some traits have a "selection differential" that is higher than other traits in some time-steps and lower than other traits in other time-steps.  For example, if an individual is better than a second individual at capturing prey, while the second individual is better than the first at evading predators, the first individual has more of an advantage when prey are scarce and the second individual has more of an advantage when predators have proliferated.

The following answer is not complete and only give some intuitive grasp on Fisher's fundamental theorem of Natural Selection. A better devlopment can be found in Ewen's book
Let's first define what is the Additive Genetic Variance
Consider a quantitative character that is determined entirely by a locus $A$ which two alleles are $A_1$ and $A_2$. the measurement $m$ of this quantitative character for an individual is given by their genotypes so that the genotypes $A_1A_1$, $A_1A_2$ and $A_2A_2$ have measurements $m_{11}$, $m_{12}$ and $m_{22}$ respectively. Suppose that random mating obtains with respect to this character and that the frequencies of $A_1A_1$, $A_1A_2$ and $A_2A_2$ are $x^2$, $2x(1-x)$ and $(1-x)^2$, respectively. Then, the mean value $\bar m$ of this measurement is
$$\bar m = x^2m_{11} + 2x(1-x)m_{12} + (1-x)^2m_{22}$$
and the variance in the measurement is
$$\sigma ^2 = x^2(m_{11} - \bar m) + 2x(1-x) (m_{12} - \bar m) + (1-x)^2 (m_{22} - \bar m)$$
The covariance between the fathers and the sons (assuming no change in allele frequency) is
$$x(1-x)\left(xm_{11} + (1-2x)m_{12} - (1-x)m_{22}\right)^2$$
The correlation between the fathers and the sons is found by dividing the covariance by the variance (since the variance of fathers equal the variance of sons) is
$$\frac{x(1-x)\left(xm_{11} + (1-2x)m_{12} - (1-x)m_{22}\right)^2}{\sigma ^2}$$
which can be decomposed into dominance and additive variance
$$\sigma _A ^2 = 2x(1-x) (xm_{11} + (1-2x)m_{12} - (1-x)m_{22})^2$$
$$\sigma _D ^2 = x^2(1-x)^2 (2xm_{12} - m_{11} - m_{22})^2$$
Replacing the measurement by the fitness, you get the additive genetic variance in fitness.
$$\sigma _A ^2 = 2x(1-x) (xw_{11} + (1-2x)w_{12} - (1-x)w_{22})^2$$
$$\sigma _D ^2 = x^2(1-x)^2 (2xw_{12} - w_{11} - w_{22})^2$$

Now, the mean fitness in the population is given by (as already said)
$$\bar w = x^2w_{11} + 2x(1-x)w_{12} + (1-x)^2w_{22}$$
Using Wright-Fisher equation, the change in mean fitness is
$$\Delta \bar w = 2x(1-x) (xw_{11} + (1-2x)w_{12} - (1-x)w_{22})^2 \cdot (w_{11}x^2 + (w_{12} + \frac{w_{11} + w_{22}}{2})x(1-x) + w_{22}(1-x)^2)\bar w ^{-2}$$
which can be approximated
$$\Delta \bar w ≈ 2x(1-x) (xw_{11} + (1-2x)w_{12} - (1-x)w_{22})^2 = \sigma _A ^2$$

Reference

I don't think that you need to look further than the Price equation, which is basically a proof of a generalized version of Fisher's fundamental theorem. Price had a series of papers in the 70's that derived and applied the Price equation (e.g. Price, 1970; Price, 1972a), but most relevant for your question in probably Price (1972b).
A nice summary of Price's legacy can be found in Frank (1995).

There's a Frank paper from JEB (2007?) on it too which is good - we have an ongoing discussion group of the price equation here at the moment. (Any good suggestions of papers with quantitative genetic applications of price equation?)

Good to know. I've seen this one as well, but haven't read it: Frank. 2012. Natural selection. IV. The Price equation

That's the one, why did I think it was 2007?? I only read it last week!

Here's a paper with an historical bibliography of mathematical analyses in the introduction.
As you can see when you demand a mathematical treatment of something as poorly understood as the genetic inheritance of traits, the word proof is to be used in a qualified way.  In this case a multilocus fitness with variation in the population with no linkage between the alleles.  Its probably a case that shows up frequently enough, but how many alleles are we talking about?  With large numbers of alleles which are scrambled randomly at each generation (zero linkage) I would imagine that the number of individuals that contain a lot of diversity.
Most GWAS studies show lots of less probable variants may contribute to many genetic traits (like height, diabetes, etc).  So this is quite a reasonable number of the cases.
The fundamental theorem is true for any number of variants involved though, so hopefully this helps.

There's an interesting treatment of this theorem in the Journal of Mathematical Biology (late 2017), which supposedly accounts for ongoing mutations in the population (not accounted for in Fisher's original).
https://link.springer.com/article/10.1007/s00285-017-1190-x
They show how their modifications produce the same results as Fisher's original when ongoing mutations are assumed to be non-existent.  They also show some results of simulations based on different ongoing mutational distributions.  They discuss which distribution is most reasonable based on observation.
Although this is a mathematical treatment, I think the trustworthiness of the theorem would ultimately be tied to empirical evidence, as I hinted at above.


text:
How many chemical species are on average in a typical plant and animal cell?
I want to know what sort of range there is on the number of different chemical species in a typical plant and animal cell. Failing that, some specific examples (with sources please).
Thanks

What is a chemical for you?

anything that can diffuse in the cell

well there are about 6000 distinct proteins in a yeast cell. So I would guess in the hundreds of thousands. https://www.sciencealert.com/simple-cell-has-42-million-protein-molecules-life-universe-everything

There is no average plant cell.  However this article describes a whole plant flux balance model with 333 metabolites. This won't describe a lot of the molecules plants make.
I seem to remember a natural product analysis of garlic that had scores of sulphur containing compounds that give its distinctive smell for instance.  This model would be a simplified plant which has no special characteristics like that, which probably doesn't exist.  Its probably not less than half the number of compounds that some plants produce or use.


text:
Maintaining purebred pedigrees and how to lessen chance of getting disease?
Many breeds of dogs are known for a high incidence of genetic disorders. German shepherd and Saint Bernard dogs are predisposed to developing a crippling condition called hip dysplasia.
Q: What advice would you give to dog breeders who want to maintain their dogs' purebred pedigrees, but also want their dogs to be as healthy as possible?

Interesting question. I assume that "natural"/"ancient" dog breeds like huskies have fewer problems with inbreeding, but still maintain their traits; but I don't know that that's true, or why it would be the case.

choose mates from as far away in the breed by pedigree as possible.  I don't think there is anything that can stop the inbreeding problem for breeds like bulldogs who are so far along and come from a small progenitor group.  Ultimately you have to allow genes to come in from the greater pool.

heard about the same problem being faced in the breeding of white tigers in India. http://en.wikipedia.org/wiki/White_tiger

Outbreed your dog every couple of generations with a bloodline that is slightly different or at the very least a similar looking breed.

Many races of dogs are relatively new with most of them appearing (were bred) in the last few hundred years. These variations are caused by small mutations in certain genes and this is also the problem. To keep a race pure, it has to be interbred to maintain the special set of mutations. And this makes the dogs vulnerable to collect more damaging mutations, especially when the number of animals used for breeding are too small. This is the same problem, that animal conservation projects face in zoos.
A good example for that is the Dalmatian dog. Its characteristic spotted pattern is caused by genes, that can also cause sensineural deafness. To avoid this, deaf dogs are excluded from the breeding and a backcross project was started.


text:
Does neuroeconomics study the brain or study economics?
I'm trying to understand what neuroeconomics is. There are two possibilities for what it might mean. (1) The study of cognitive processes in the brain by applying basic principles of economic theory like concepts of utility, decision making, etc. (2) The study of how a human behaves in an economic setting, somewhat like game theory and so on, which is more economics than brain science.
Which one is it?

Neuroeconomics is the study of the neural basis of economic behavior.

You should consider asking this question on the cognitive sciences stackexchange, which specializes in neuroscience and related fields.

As @Kyle beautifully summed-up,

Neuroeconomics is the study of the neural basis of economic behavior.

The terms applies to studies concerning the appeal of new logos for marketing purposes to the understanding of the neural correlate of subjective value. The term neuroeconomics has been subject to some debate which made it sometimes unclear. In particular, the term is ambiguous with regards to its applications.
Are the theories that are built upon these studies used for marketing purposes (some would say "to optimize brain washing you in the necessity of buying a 7 blade razor") or for the sake of knowing how the brain may be better understood and to the therapeutical applications of these new theories.
My answer would therefore be this:

the brain is a complex system for which science often used analogies to make progress. It has been compared as steam machines in the 1800s, electricity in the 1900s, or to computers in the this century.
The complex interactions present in an economic system -as studied by game theory for instance- present a powerful analogy to understand the brain.
Of course, it thus impacts our knowledge on economics as these are often based on our knowledge of decision making. Thus, your two options are (1) and (2) are interconnected.

My initial reaction is that (1) is preposterous, because there is no economics of the brain, as it is not made up of rational actors who trade or manage resources as individuals. Therefore it must be (2).
Also, I happen to know from experience that there is much said and written about (2) and less about (1).
Here is some evidence supporting this:

Duke University's Center for Neuroeconomic Studies states that they apply "the techniques of cognitive and systems neuroscience – along with computational modeling – to understand economic decision making and related behavior".
The IISDM at NYU (who have a program in neuroeconomics) says their goal is to "better understand the mechanisms, predict the impacts, and shape the policies that will define the study of decision-making tomorrow (...) by developing novel research infrastructures to support the propagation of neurobiological insights about the human animal into the policy domain"..
The Society for Neuroeconomics says their mission is to "foster research on the foundations of economic behavior by promoting collaboration and discussion among scholars from the psychological, economic, and neural sciences".
The most highly cited result on Google Scholar for "neuroeconomics" is titled "Neuroeconomics: How Neuroscience
Can Inform Economics". The third hit's abstract says "Economics, psychology, and neuroscience are [aiming to provide] a single, general theory of human behavior. This is the emerging field of neuroeconomics (...) The goal of this discipline is thus to understand the processes that connect sensation and action by revealing the neurobiological mechanisms by which decisions are made."

So I would conclude from this that neuroeconomics is the study of human decision making, by application of neuroscience.
Granted, at this point I feel compelled to admit that perhaps I was too quick in my initial reaction: Is it really possible to isolate the study of the human brain from the study of human decision making? There is just so much overlap that even a "pure" neuroscientist will inevitably generate research which bears much relevance to economics. And with economics, the only way to "escape" neuroscience is to assume that all actors are perfectly rational, which is almost certainly at least a little bit untrue (although a staple of classical economics). It's probably a bit of loop, and I'd favor NYU's emphasis on it being interdisciplinary field rather than "field X applied to field Y". That said, indeed, most neuroeconomics studies appear to be interested in solving economics problems, and not neuroscience problems.


text:
What is splice junction pairs?
Splicing is a modification of pre mRNA when all introns are removed and exons are joined.
What is a splice junction pair? It is two exons which connected together?

Splice junctions are the exon-intron junctions, at which splicing takes place.
Splice junction pairs are the pairs of such junction (to cut an intron you need to splice in two junctions).
So, you are almost there, since two exons will be joined in correspondence of two subsequent splice junctions.
You might find these slides useful (slide B-6)

EDIT:
As Adam pointed out the slides are no longer available. I have no idea on where they are gone, but I suggest referring to the following wikipedia pages for an introduction:
RNA splicing
Exon junctions
Alternative Splicing

The slides are no longer there (Page Not Found, 404)

Added some very basic new references (wikipedia). I don't know where the original slides went!


text:
Is there any format for official Physiological/Medicine answers?
Assume you have an exam which has 5 extensive questions and 60 minutes.
You do not have time to cover most if you write everything in essay format.
If you start to write essays, you do not really have time to cover all mechanisms and so on.
I just heard that one student did the exam with by list format, for instance

sitting -> venous return down & skeletal muscles not working correctly -> trombus.

and then describing relevant mechanisms similarly and combining the their roles shortly.
Another morphology of H. pylori

Curved (spiral shape), Gram-negative, 2-4 micrometer long, coccoid forms in older cultures,

Is there any official standard or unofficial accepted way how to answer questions in Physiology/Medicine?

Given the highly variable nature of such processes and systems, it's unlikely that a common standard is feasible or sensible. In medical questions, a bottom-up order like in your example usually makes sense, starting with the most specific known cause and deriving from there until you arrive at the symptoms. Treatments can branch off or into the order at the point where they apply logically.
If your exam instructions ask for flow text, your question is alreay unnecessary - but if you believe you have the choice, use a note format that is appropriate by common sense. You are essentially creating a diagram, and like any diagram you have to ensure that it is self-contained and comprehensive.
You can shorten the amount of time it takes to write sentences by reducing the literary quality. Of course a well-written text is more pleasing to read and mark, but the main emphasis in your grading will usually be content, meaning that you can afford to form sentences of repetitive structures or lacking logical connection if it is difficult to figure out quickly whether there is one or how to express it etc.

I usually answer in a extensive and descriptive way, and I try to put as much information as possible. If it's a process I usually add a little diagram. If there are lot of attributes to add sometimes I do lists, but usually teachers don't like them an it's easier to find errors or lacks in lists.
There is no standard answer model at least in my University.

I completely agree with figures about the anatomical structures. They help a lot and help you to think what to answer.


text:
water stress expression markers in arabidopsis thaliana
So far I found papers that show studies using RNA arrays on whom they categorized water stress gene markers in root. Water stresses were reproduced by different protocols (manitol...) but always on several week old plants. Does anyone know any study carried on young (6 days more or less) arabidopsis thaliana plants?


text:
What is lack in sense of smell called?
People who lack the sense of hearing, vision and speaking are called Deaf, Blind and Mute.
But what is the person called if he/she lacks the sense of smell? Is there any case like that?

This condition is called 'anosmia', see these two links: Wikipedia and from the british National Health Service. They include a definition and reasons for anosmia.

the person would be called 'anosmic'. See https://en.wiktionary.org/wiki/anosmic


text:
Cambrian explosion and evolutionary arms race
I've seen many times mentioned in textbooks and popular articles that a reason of the Cambrian explosion is an 'evolutionary arms race' between predators and prey. But this isn't really a sufficient reason, since that happens all the time, but evolution seems to happen only at brief intervals separated with long intervals of stasis, which is described extensively in the Punctuated equilibrium hypothesis.
So, my question is, what made the evolutionary arms race of the Cambrian possible?

Lots of things happened during the Cambrian explosion, and I do not think that anyone believes that it was only due to predator-prey arms races. The wikipedia page has a summary of hypotheses, and as you can see the arms race theory is just one of many. It is also likely that there is no single cause, but several interacting factors.

I think it is really wrong to assume that evolution occurs only in punctuated way. Evolution is a continuous process.


text:
Correlating beta-lactamase expression to absorbance

When penicillin-resistant bacteria are grown in liquid culture media,
  β-lactamase is secreted into the medium. The supernatant of such a medium can be assayed for β-lactamase activity. Culture supernatants
  different organisms , which are suspected to be penicillin-resistant,
  were obtained and were assayed for β-lactamase activity. The corresponding absorbance value were measured at a certain wavelength.

Let us assume that supernatant from organism 1's culture had absorbance value X and 2 had absorbance value Y.
My question : If X>Y, does that mean that more β-lactamase was being produced by organism 1 ?

How does this beta-lactamase assay work? If it works in a way that more secreted enzyme metabolizes more substrate resulting in more absorbance, than yes.

@chris It's been treated with an inhibitor of B-lactamase.

The supernatant is treated with a b-lactamase inhibitor? And what happens then? Or does the inhibitor change its color due to the inhibition?

@chris Yes the color becomes yellow. What would happen to the absorbance then ?

Ok, then more b-lactamase means more inhibitor binding and this results in more color development leading to a higher absorption. So higher absorption means more b-lactamase in the supernatant.

Hi @Chris You have answered my question in the comments. Do you want to write an answer ?

I can do that later today.

In the β-lactamase test, an inhibitor of β-lactamase is added to a sample of the culture medium. The inhibitor binds to the enzyme and changes its color, which is in direct correlation to the concentration of the β-lactamase. More β-lactamase means more inhibitor binding and this results in more color development leading to a higher absorption. So higher absorption means more β-lactamase in the supernatant.


text:
Correlating Ki values of pesticides to bacterial growth

Four pesticides P1 to P4 are reversible inhibitors of an enzyme E that
  is essential for the growth of a bacterium B. Their Ki values are
  given in the table below. Each of these four pesticides is used in
  four geographically different regions R1 to R4. The residual
  concentrations of these four pesticides in the respective regions are
  also shown in the table below:

Which pesticides will be able to inhibit bacteria ?

My question : I know that Ki shows the binding affinity. So, how is that related to residual concentration ? How can I deduce whether it will kill the bacteria or not ?
Unrelated question : Is it acceptable to use the word pesticide here ?!

Ki is the equilibration dissociation constant. The smaller this constant is, the stronger (more specific) is the binding between the inhibitor and the enzyme.
If the residual concentration is now higher than the Ki, for each molecule from the inhibitor which dissociates from the enzyme a new will bind (simply because of the concentration). If the concentration is lower (or much lower), this will not be sufficient to inhibit the enzyme. This assumes that the relation between enzyme, inhibitor and substrate are linear (and we are not getting some kind of saturation here).
Under the conditions mentioned above, P1 and P4 will inhibit the enzyme. For P2 and P3 the concentration is to low.


text:
Chaos theory and population cycles of odd periodicity
I have just begun to read about Chaos theory and have come across the statement that "Period three implies chaos."
My question: Does any odd period imply chaos or only 3? If so, how can populations of cicadas that cycle every 17 years exist?

Can you give a bit more background? What period 3?

@chris Period 3 means a cycle of 3 years.

Ahh, now. Lifecycles based in the number 3 overlap with several others - 6, 9, 12, yearly, and so on. If the lifecycle is only 17 years, then a parasite needs to have exactly the same lifecycle (its a primer number so there are no other fractions) to meet its host.

@Chris Ummm..I have read that before and I am not trying to ask the reason why 17 year cycle are beneficial, i am asking how can they EXIST in the first place ?

@Chris It will become clearer to you what exactly am asking after reading this

Oh. I will have a look into your resource a bit later and then see what I think about it.

its said that cicadas always have prime number of years in their hibernation cycles to prevent synching up with any predator population booms. http://www.newyorker.com/online/blogs/elements/2013/05/why-cicadas-love-prime-numbers.html

Ok, I am out. The answer from Filedunderwater is what you need.

The chaotic behaviour you are referring to (at least the one described in your link in the comments) is a property of the discrete version of the logistic equation, where you get chaotic dynamics at growth rates above ~3.55 (see the logistic map). The behaviour of this equation has been described in a classic paper by Robert May (1976). As you increase growth rate (a in your link) from one you go from a stable attractor (approached directly or by dampened occilations) to cycling behaviour (between 2 to 4 to 8 states as growth rate increase) to chaotic dynamics, which is shown in this bifurcation diagram.

And to be clear, nothing of this has anything to do with period/cycle length per se (in the sense of species interactions or lagging feedback loops), but is a property of the model and the population growth rate. The statement about period 3 implying chaos probably refers to a brief window around r ~3.83 ($1+\sqrt{8})$ where you get cycling between three values, and at higher values then this you only find chaotic behaviour (which you get at lower values as well though).
Addition:
I now realize that the statement "Period three implies chaos" comes from the theoretical paper with the same name (Li & Yorke, 1975). This paper proves that all one-dimensional models (not only the equation above) that has a period 3 cycle will also show chaotic behaviour. This proof is a special case of the Sharkovsky's theorem, which is older but was unknown to Li & Yorke at the time.
There is also a question at MathSE that deals with the same problem, and some of the answers there link to useful resourses:
https://math.stackexchange.com/questions/2901/period-of-3-implies-chaos


text:
why can't we digest cellulose
I have a very tricky question....all the veg and fruit
cells contain cell wall and it is made of cellulose when we eat how our body digest though we
don't have the enzymes to breakdown 1-4 beta glucose sugar?

We don't digest cellulose; it just passes through us unchanged.

Related: https://biology.stackexchange.com/q/59205/24354

Humans, unlike cows for ex. don't have the necessary bacteria in their intestines that make the enzymes(cellulases) necessary to breakdown the 1-4 beta glucose bonds. So we cannot break down cellulose into its constituent glucose molecules as we do with starch. Therefore this is secreted as unbroken down chains of glucose called fiber.

tnx sir for your reply...but it didn't satisfy me i asked so how we can eat fruits and vegs they all got celloluse in thier cell wall

That's why I tried to explain that those parts of vegetables we can't digest are called fiber.

so then why in many biscuits and chocalate companies ads they say it fibers and etc if we can't digest it then why they promote it?


text:
To understand clearly extraintestinal diseases
Extradistestinal disease seems to prefer to "bowel" diseases, I think this is about diseases outside gastrointestinal tract so stomach.
Consider diseases ulcerative colitis and Crohn's disease (enteritis) as examples.
Colitis affects to colon, outside of small intestine, I think extraintestinal therefore.
Crohn's disease (enteritis) however affects to the small intestine so I would think intestinal disease (but this clause is wrong) - it should be at least have extraintestinal manifestations.
What is the exact definition of the word extra in intestinal diseases?

Certain intestinal diseases have symptoms that appear concurrently in other systems of the body, but the bowel diseases themselves are not extraintestinal.

Extraintestinal manifestations of inflammatory bowel disease are prevalent in both ulcerative colitis and Crohn's disease. The most common manifestations involve the musculoskeletal and dermatologic systems. Other manifestations involve the hepatopan-creatobiliary system (eg, primary sclerosing cholangitis) as well as the ocular, renal, and pulmonary systems1.

One of the key differences between extraintestinal manifestations and comorbid conditions (though seemingly not a necessity, the article cites primary sclerosing cholangitis as an counterexample) is that the extraintestinal effects will subside once the disease of the bowel is treated.
1 Levine, J.S., Burakoff, R. (2011). Extraintestinal Manifestations of Inflammatory Bowel Disease. Gastroenterol Hepatol (NY), 7(4), 235–241.

Does there exist any extraintestinal disease with some type of diarrhea?

@Masi In that case, the manifestation wouldn't be extraintestinal, it would be directly related to the intestine.


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How to determine the actual flux in the human metabolic model of a cell line?
The problem to be solved is to determine what the flux values are for the different reactions in the human metabolic model.
As far as I understand, a good way to do that would be to use gene expression data to calculate a flux, but I am not sure that is a good idea or if it is even possible.  I am not very sure of what is the correct process to do this.
Thanks for any help or suggestions!

A metabolic flux is the rate at which a metabolite gets converted into another metabolite by an enzyme. Metabolites aren't coded for by genes, so gene expression data doesn't help determine metabolic flux, unless there is some feedback that will cause the concentrations of the various enzymes involved to change via gene expression. But that occurs on a timescale which is much slower than typical metabolic flux.

I am no expert on the field, but quantifying gene expression isn't a simple problem, although it is a possibility.
A solution I know to be used is using radioactive markers. See for example this review and particularly "The cell-cell lactate shuttle" section, which might give some insights.
This can include radioactive tracers (such as [14C]lactate), non-radioactive tracers (with [13C] or [2H]), "net exchange measurements" (I don't really know what this means here, perhaps the kind of exchange calculations they present here), and muscle biopsies (it is then possible to measure the metabolite concentration by enzymatic reaction or spectrophotometry for example).

Summary: Try one of the extensions of FBA which take gene regulation into account, but be aware of the limitations. See below for references.
Long answer:
There are two approaches to estimating internal metabolic fluxes: The (primarily) experimental and the (primarily) computational. I say primarily, because even for the experimental approach, a large amount of computation need to be done, and for the computational approach, experimental studies must be consulted in order to set realistic model parameters.
Experimental determination of internal metabolic fluxes has been centered around 13C-metabolic flux analysis (13C-MFA) performed through carbon-labelling experiments, as mentioned above. 13C-MFA is complicated and expensive, so there is a relative lack of experimental data, and most experiments cover only a few fluxes when compared to the number of possible reactions, typically several thousand in genome-scale metabolic models. In 13C-MFA, most experiments estimate the fluxes in a much smaller model (for example the central carbon metabolism), avoiding or ignoring other possible reactions, and the set of fluxes that are estimated varies between experiments.
Models which are used in computational approaches to flux analysis are typically larger than the models used in 13C-MFA experiments, and thus it is usually not possible to determine all the fluxes from experimental data alone. Thus, an approach called constraint-based modelling (COBRA) is mainly used. The basic assumption of most current flux analysis methods, both experimental and computational, is that metabolite concentrations are at steady state. Mathematically, this can be described by the equation
$S\overrightarrow v  = 0$
where $S$ is a stoichiometric matrix relating the metabolites and all possible reactions (basically a compact description of the metabolic model), and $\overrightarrow v$ is the flux vector containing all the flux values. In addition to the steady state requirement, constraints are typically applied to the uptake and excretion rates of various metabolites, limiting them to biologically realistic values. Other requirements, such as requirements for ATP maintenance consumption can also be applied.
Because there are typically many possible flux patterns that obey the above constraints, a principle is needed for selecting a biologically realistic solution from the solution space of feasible flux patterns. Assuming that cells optimize their metabolic patterns in some way, different objective functions are used that attempt to capture the metabolic behaviour for cells. Once an objective function is chosen, the set of possible solutions can be searched for the flux pattern that gives the highest objective value as a function of the flux vector. Given that the objective is linear (simply a weighed sum of fluxes), an optimal solution can be found rapidly. In general, many different optimal solutions may exist for a given objective function. The method of applying an objective function to a constrained metabolic model at steady state is called Flux Balance Analysis (FBA).
The most basic and a popular objective is maximization of biomass production. While useful for determining maximal growth rates, this objective is unlikely to be realistic when applied to human cells. FBA and related methods is generally well-suited to determining performance limits for single endpoints such as growth rate or production of a single metabolite, but not capable of precisely determining all internal metabolic fluxes. The point that many optimal solutions may exist for a single objective function is important in this regard.
As 13C-MFA and FBA are based on the same concept of metabolite balancing, they can be viewed as different ends of the same spectrum, from purely experimental to purely computational, with 13C-MFA constrained FBA (where 13C-MFA results is used to constrain the possible fluxes in a model before optimizing an objective function, or minimizing the difference between the experimental fluxes and the FBA solution, subject to additional constraints) in the middle.
For an introduction to Flux Balance Analysis, see  Orth, Thiele & Palsson: "What is flux balance analysis?" Nature Biotechnology 28 245-48 2010.
For performing Flux Balance Analysis, several software packages are available. One of the most used is the COBRA Toolbox for Matlab. A version for Python called CobraPy is also under development. Both are available at http://opencobra.sourceforge.net/openCOBRA/Welcome.html
Note that most gene-expression data only shows relative changes in expression between two conditions. Most methods are thus based on comparing two different conditions. More recently, RNA-sequencing (RNAseq) may also be used to obtain more direct measures of gene expression levels. Many extensions and variations on FBA have been published which take into account gene expression. Some of these are regulatory FBA (rFBA, Covert & Palsson: Journal of Biological Chemistry, 2002 277, 28058-28064), Metabolic Adjustment by Differential Expression (MADE, Jensen & Papin: Bioinformatics. 2011 Feb 15;27(4):541-7 ) and iMAT (Schlomi et al:  Bioinformatics (2010) 26 (24): 3140-3142.). For a more recent method, gx-FBA (gene expression-FBA), see *Navid & Almaas, BMC Systems Biology 2012, 6:150).
You may also want to read this article which deals with construction tissue-specific metabolic models: Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Mol Syst Biol. 2010 Sep 7;6:401. doi: 10.1038/msb.2010.56.
The problem with using FBA and related methods to estimate internal fluxes is that validation of the results is difficult because of the mentioned lack of experimental data. I wrote a project report on the topic during the last year of my Master's, which includes a basic description of 13C-MFA. It can be read at http://www.slideshare.net/jarlemag/rapport-31295058

This is a wonderfully complete answer.  Thank you very much!  I am actually on the path of using FBA to achieve this.  In our project, we have several cancer cell lines from the CCLE that we are trying to simulate through FBA.  However, we would like to "customize" the Human Metabolic Model to the characteristics of each cell line in order to get a better baseline for analysis.  The CCLE provides some gene expression data, so we'll definitely look into that.  Again, thank you!  If you have any other suggestions, I would gladly hear them :). +1.

Glad to be of help. It's a bit difficult to give suggestions without knowing more specifically what you want to do, but feel free to ask if you have any more questions. May I ask what software you will be using for the analysis?

Absolutely.  So far, I have chosen COBRAPy to run FBA (don't have access to MATLAB and I'm experienced with Python).  Perhaps the greatest aid I could get from you would be your opinion.  I have asked this about using the HMM, as well as this on where to get good HMM data.  In essence, I am trying to gauge what I need to do to predict the outcome of gene knockouts by cancer therapy drugs.

That's cool. I'm in the same situation, also using CobraPy. I like it better than the MATLAB Toolbox, but unfortunately it doesn't have as many modules available. I've been working on implementing some methods only published as MATLAB code (or not at all) for use with CobraPy, but they're not quite ready yet. I'll see what I can do for your other questions, although I haven't worked on any applications of FBA to human metabolism.

You cannot use gene expression to estimate fluxes. The reasons are as follows. Gene expression determines mRNA levels which in turn determine enzyme levels. However the relationship between gene expression and enzyme level is not linear. Your biggest problem however is the fluxes are system dependent properties and are not dependent on any single enzyme. A flux is in principle a function of all the kinetic properties of every enzyme in the pathway. The only way to get the fluxes is either by direct measurement or using FBA or kinetic models.


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Why do we dream while sleeping?
Is there any specific reason behind why we dream? Why do we sometimes get weird and unusual dreams? Sometimes we can't even recall what we dreamt of. Why does this happen?

There're so many theories...personally, I think dreaming is the brain trying to defragment, going over the past memories and getting rid of the connections that are not deemed as important. And this process of memory consolidation is seen as a dream. This explains why we often dream about the things that has happened during the day.

This question might be a better fit on CognitiveScience.SE

@Remi.b Considering many other animal species dream, most animal species sleep, and considering there must be an evolutionary reason for both, I think it fits perfectly here. Also, sometimes the same question in two different communities will get different, thus interesting, answers.

Disclaimer: the shortest answer still remains we don't know...yet.
Talking from the evolutionary perspective, I have found as many as 8 theories about the purpose of dreaming, some of which even contradict each other(!). But I'll describe them one at a time.

One obvious theory is that we dream about something we dream of. So, dream is basically a way of wish-fulfillment; what we are dying to achieve, we get that in our dreams. Though it has been made quite scientific by Freud et al, it still doesn't look much scientific, at least from evolutionary perspective.
Another idea, made popular mainly by Hobson et al, is that dreams are purely because of accidental firing of neurons. In what they call activation-synthesis theory, they claim that during sleeping, neurons in areas of brain, including brain stem, limbic system, secondary visual cortex, etc. fire accidentally. When the brain tries to interpret those signals, the result comes out as dreams.
Another theory, proposed by Zhang et al, is that dreams are our brain's way of converting short-term moemory into long-term memory. This quite explains why some people reommend a power nap after learning something new, it helps the brain in storing the knowledge as long-term memory. Also, recent studies have concluded that it is better to remain awake for hours after a traumatic experience rather than sleeping right off, if you want to forget that experience faster.
Another theory, popularly called reverse learning theory, basically says that we dream to forget things. Dreaming is a way for our brain to prevent information overload so that memorizing new things becomes easier. Seems the opposite of Zhang et al and most likely answers why Sometimes we can't even recall what we dreamt of.
Yet another theory, seemingly more sound from evolutionary viewpoint, says that dreams are just like the playing-dead response of our body. When we dream, the neurotransmitters related to movement are shut down, resulting in what seems like a dead body. So, our body preferred to retain this mechanism because it could've helped in a way like the freeze response did.
A theory, proposed by Revonusuo et al, says that dreams are to make people ready for real-life situations. According to it, people who often dream about being chased by a tiger will learn how to overcome that situation and eventually will be able to survive such case. Seemingly answers your question Why do we sometimes get weird and unusual dreams?
Barrett et al, based on Revonusuo's theory, proposed that dreams are a way for solving problems for humans, partly because dreaming mind makes connections faster than awake one. Though this explains how Kekulé predicted benzene's structure, it doesn't look very much scientific.
A yet another one, by Coutts et al, says dreams are a way for "natural selection" of best possible method to solve a problem, including emotional situations, and is called Oneiric Darwinism. A much similar idea by Hartmann et al is called contemporary theory of dreaming.

I will not discuss the mechanism of dreaming, not only because it will make the answer too long or because others have delved into that point in their answers, but because it will answer the How? part rather than the Why? part, and also because that part would be better suited for cogsci.SE.

7 is also seen in the movie Lorenzo's Oil (1992), supposedly a true story. There's also the hypothesis of communication between the unconscious and the conscious mind, since both know things differently. But probably most of these theories are right, each in a different circumstance. Only 5 makes no sense to me: if it alone were true, wouldn't it be better not to dream at all?

@rodrigo yeah 7th one seems most backed-up with case studies, like the Kekulé one I mentioned. Of course, they all might be true until any of them is proved wrong ;) I don't know about 5th one, but they should be having some back-up studies...I'll read the paper soon ;)

Recent scientific research suggests that dopaminergic pathways are responsible for dreaming. According to this theory if something affects your dopamine system, it will also affect dreaming. My personal takeaway from this is that your dreaming can be viewed as an indicator of how your dopaminergic system works. Significant deviations from the baseline dream content may be a reaction to drugs, especially psychiatric drugs or changes in diet. These changes rarely persist for many days, as the brain compensates for the new thing.

A dopaminergic pathway runs from the ventral tegmental area, ascends
  through the lateral hypothalamus, various basal forebrain areas
  (nucleus basalis, stria terminalis, shell of nucleus accumbens) and
  terminates in the amygdala, anterior cingulate gyrus and frontal
  cortex. Damage to the dopaminergic pathway results in a loss of
  dreaming. Furthermore, chemical stimulation of the pathway (with
  L-DOPA for example) increases the frequency and vividness of dreams
  without affecting REM sleep.[10] It is interesting to note that the
  mesolimbic and mesocortical pathways are considered the seeking areas
  or the motivational command centers of the brain.

And

The evidence of the involvement of mesolimbic and mesocortical
  dopaminergic pathways suggests that dreaming occurs when a
  motivational component is activated.

Well i will like to contribute a fact which might seem a little bit out of context.
R P Feynman, the famous physicist, in his semi-autobiographical book mentioned his experiments with his consciousness and also 'dreams'. He reported that he was actually able to alter his dreams, with a little bit of practice, while he was experiencing them. Well after reading that i was quite fascinated with the possibilities and tried it myself to a fair amount of success.
Moreover although the exact mechanism or motivation of sleep hasn't been understood it is generally accepted that 'dreams' always occur in the REM stage of sleeping. In light of the 'Restorative theory of sleep',which basically says that sleep happens to make up for all we lose during daytime, i can say that dreams are actually a byproduct of the fact that maintenance of brain cells occurs by a different pathway than normal body maintenance. So all in all saying that the 'Waking up' part of our body isn't perfect and almost everytime one part of brain 'Wakes up' before the other and contributes to the bizarre yet frequent phenomena of 'Dreams'.

A couple comments: about 75% of dreaming occurs in REM, but REM is not a requirement for dreaming. The term for conscious control of dreaming is "lucid dreaming", and potentially "dream incubation" for intentionally dreaming about a certain thing

This is a difficult question to answer because we are only aware of basic mechanisms that go on in the brain during dreaming. One theory that is prevalent during sleep is that we may be replaying the day's events in order to extract and store the important information encountered. So if you block sleep after learning you can interfere with it. The function of dreaming itself is more speculative but one idea is that all that replaying back of sensory information along with normal conscious processes creates vivid imagery that is strange and new.As you know during REM the brain is very active so it can "perceive" as if it were awake. This answer is mostly directed at how we dream but hopefully you've gleamed some additional insight from it.


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Is there a homeostatic setpoint for number of hours of sleep required by a human?
I've heard this TED.com talk about dieting and it mentions that there's a very definitive setpoint within the human brain about how much a human should weight. The speaker mentions that after as much as 7 years, the body returns to that homeostatic weight setpoing.
I'm interested if there's something similar for sleep - is there a homeostatic setpoint that says that a human should sleep X hours out of 24?
In this example by homeostatic I mean:
If the sleep setpoint is at 9 hours, the human can sleep for 8 hours for some time, but when the artificial sleep restriction is removed, the human would return to 9 hours of sleep naturally.


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Does playing music during sleep actually suppress rather than rouse the brain?
I've long been interested in the effect of music/sound on dreaming, and even built 2 apps that play music during REM period. Now I'm looking at this article about FMRI studies of a sleeping brain, and I see that it mentions:

During wakefulness, acoustic stimulation elicits activation of the
  auditory cortex (red). Similar stimulation during light NREM sleep
  stage 2 evokes transient downregulation of widespread cortical areas
  (blue), supposedly a sleep protective mechanism.

and

Acoustic stimulation in REM (rapid eye movement) sleep revealed a
  different brain activation pattern during phasic and tonic REM
  periods, with strongest suppression of cortical reactivity during
  phasic REM sleep periods.

Can I interpret information on that site to suggest that auditory stimulation during sleep actually makes the brain less active? Can one assume that playing audio during REM would disrupt dreaming due to transient downregulation?

This is a very interesting but difficult to answer question. That is because scientists are still debating about the various stages of consciousness. As it stands, there is evidence that people can learn even though they are asleep indicating that it is likely that sensory channels are open and information is being processed even when asleep. That likely means the brain is behaving as if it were awake at certain times during sleep. In this article they interpret the lack of blood flow seen by fMRI as less active which is mostly correct. Playing audio during REM is a tricky question because as you know dreaming does not require sensory input so that channel(hearing) may be free to receive information although your guess may also be true if if the music was loud enough to interfere with other cognitive processes.


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Healing rate of cut while suffering from a cold
I recently cut my finger fairly deeply with a box cutter and had to have it stitched. During the healing process I contracted a strong cold/mild flu (a sore throat and runny nose with a high fever, aches and shivering). I doubt the two have anything to do with one another apart from happening to occur at the same time.
But they did occur at the same time. So I'm wondering: what is my body going to do?
If I recall my junior high biology, a cut is healed by platelets and [other stuff I can't recall], whereas a virus is fought with antibodies. Presumably in both cases it's a bit more complicated than just that. I'm also not sure if there is any crossover - are antibodies, for example, needed to protect the open wound from bacterial infection? Regardless, my question is:
Since the resources in the human body are finite, would having to fight off the cold have a detrimental effect on the healing of the cut?
If certain resources are needed for both tasks, would the body divide its resources or give one precedence over the other?
I'm guessing this is not something that is easy to measure, since it would be difficult to conduct a control experiment given the insane amount of variables. But presumably there is a consensus in the biological community on whether there would be an effect, even if it is not possible to determine the degree of said effect.
I should mention in closing that I am not remotely worried about any of this; it just piqued my curiosity.

First of all: No, there is no connection between these two incidents, correlation does not imply a causation. Cold and flu viruses affect the respiratory system and the infection route goes via it. A cut is a local wound, which does not affect the respiratory tract.
Then: Recovering from an infection is a task for the immune system (its both, the innate and the adaptive immune system, the last involves the antibodies), which is not doing much for wound healing. The wound attracts neutrophils and macrophages which are attracted by factors released by the wound and they react to bacterial infections (when they occur). See this Wikipedia article.
The ressources of a normally healthy person are quite big. This is demonstrated by the fact that many secondary infections only occur in a opportunistic fashion (for example viruses like Herpes or certain fungi) when the body is weakened by other infections. So there is a limit, but this will certainly not be reached with a severe cold.


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GO terms for non-model organisms
I have a list of differentially expressed genes from an RNA-Seq experiment in Xenopus laevis that I'm looking to functionally annotate with GO-terms. As X.laevis is not listed in DAVID it seems I have 2 options:

BLAST my DE genes against a database with GO terms (human/mouse) to look for orthologs
Use a program that assigns GO from BLAST results, such as Blast2GO

I've been trying with Blast2GO recently, but find if very slow and generally lacking - does anyone have any experience doing GO in Xenopus or other non-model organisms?

interesting question, but no experience doing this from me. Have you tried BioStars.org?

I've done a functional annotation of a non-model, and used Blast2Go with fine results.
Specifically, I took all of my proteins and queried again the NCBI non redundant (nr) protein database using mpiBLAST, then I analyzed this output using Blast2GO (B2G4PIPE) and a local B2G Database.

blast2go is on the verge of getting commercialized (as they have started selling PRO versions) and my previous experience was not so good with it.
I used IntrProScan to associate GO terms with the transcripts, it ran long but it reported all the possible sequence features.
To use these custom annotation was tricky for visualization, but thanks to BiNGO, I was able to do it flawlessly. For future use I have documented it here, http://infoplatter.blogspot.in/2014/04/gene-ontology-go-enrichment-analysis-in.html
Good luck!!

Updating this thread to include EnTAP, (Eukaryotic Non-model Transcriptome Annotation Pipeline) which wraps protein domain assignment, orthologous gene family assessment, Gene Ontology term assignment, and KEGG pathway annotation into a single tool. I have used it for annotating sequences from divergent groups of non-model species.
See the paper in Molecular Ecology Resources.


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Pseudosexual reproduction
Research projects with artificial life generally use creatures that are haploid. The offspring randomly inherit some genes from one parent, and some genes from the other parent.
Q1: Are there any biological species which reproduce similarly? I.e., they're haploid, but the offspring aren't clones. Perhaps hermaphroditic species like slugs or some plants?
Q2: Is there a name for this type of reproduction? If not, I guess I'll call it "pseudosexual" since it's a simplified form of true sexual reproduction.

RE Q1 - perhaps N. crassa is something along those lines. (http://en.wikipedia.org/wiki/Neurospora_crassa)

Yes, that looks like a good example.

Generally, all diploid species pass through a haploid phase in their life. This is called the alternation of generations and the cycle may be presented like this:

Commonly we see organisms that spend most of their life in the diploid phase, with greatly reduced haploid phase (e.g. humans "live" in haploid state only as gametes). However, this is not the only way possible. There are organisms, which spend similar amount of time in each phase, which change ploidy depending on the conditions of the environment and, of course, organisms which spend most of their lives as haploids, with only a short diploid stage.
As a rule, lower plants, fungi and protozoa may exibit this behaviour. Some examples:

Saccharomyces cerevisiae (yes, baker's yeast) will undergo meiosis and form haploid spores in unfavourable conditions, which then can grow as haploid colonies until they encounter a colony of opposite "sex"
Mosses commonly grow larger gametophytes (haploid) than sporophytes (diploid)
Some brown algae grow sporophytes and gametophytes that are indistinguishable form each other
Ferns often grow large sporophytes and small, but self-sufficient gametophytes.

Next question should be "why only lower plants and fungi?" And the shortest answer is that a diploid organism is usually more robust, it can survive more potentially lethal mutations than a haploid.

I don't know any example of haploid, but (pseudo)sexually reproducing artificial life (and hardly any at all existed 4 years ago when the question was posted!). So I assume you meant in-silico life. Then, yes, usually as you described.
There is no regular mechanism of inheriting some genes from one parent, some from the other, when parents are haploid. Such mechanism in diploid parent is meiosis, which is not, of course, possible in haploids.
Rather irregular processes that involves 2 haploid nuclei (identical or not) similar to what you describe are known in some basal eukaryotes (excavates) and in fungi lacking regular sexual cycle. In different contexts these cycles are called pseudo-, as you suggested, or para-sexual cycles.