Pedigree Probability, Autosomal Recessive Trait So, I thought I understood how to calculate the probability for a pedigree, until I came across this answer in my textbook. The question is: what is the probability the offspring of IV1 x IV2 will show the recessive trait? Assume individuals outside the family are not carriers of r unless there is evidence.
White = Dominant phenotype, Black = recessive phenotype.
What I did is:
III3 = 1/1 Rr, III4 = 1/2 Rr, IV1 = (1/2*1/1*2/3=1/3)
III7=1/2 Rr, III8= 1/2 Rr, IV=(1/2*1/2*2/3=1/6)
IV1 x IV2 = 1/3*1/6*1/4 = 1/72.
The answer in the book is 2/35. Can somebody please explain where I went wrong?

Here is my attempt!

Generation III

III3 is rR
II3 is rR and therefore III4 is rR with probability $\frac{1}{2}$ and RR with probability $\frac{1}{2}$.
Just like III4, III7 and III8 are rR with probability $\frac{1}{2}$.

Generation IV

Let's start with IV1.

IV1 is rR if ...

III3 transmits the r allele (probability $\frac{1}{2}$)
III4 is rR (probability $\frac{1}{2}$) and transmits the r allele (probability $\frac{1}{2}$). The total probability is $\frac{1}{4}$.

However, we have to remove the probability that both parent transmit the r allele as we know IV1 is not rr. This probability is $\frac{1}{2} \frac{1}{4} = \frac{1}{8}$. So, in total, the probability of IV1 to be rR is $\frac{1}{2} + \frac{1}{4} - \frac{1}{8} = \frac{5}{8}$.

Now, IV2

IV2 is rR if ...

III7 is rR (probability $\frac{1}{2}$) and transmits the r allele (probability $\frac{1}{2}$) or if III8 is rR (probability $\frac{1}{2}$) and transmits the r allele (probability $\frac{1}{2}$).

However, we have to remove the probability that IV2 is rr as we know this is not the case. The total probability is therefore $\frac{1}{4} \frac{1}{4} - \frac{1}{16} = \frac{7}{16}$.

Generation V

Finally, we get to your question

  [W]hat is the probability the offspring of IV1 x IV2 will show the recessive trait?

Both parents need to be rR which happen at probability $\frac{5}{8} \frac{7}{16} = \frac{35}{128}$ and both need to transmit the $r$ allele which happen with probability $\frac{1}{4}$. Hence the probability is $\frac{35}{512}$.


Wikibooks claim that it is difficult to find two texts that agree on the definition of an animal In this entry of Wikibooks we find the claim

  It is surprisingly difficult to find two texts that agree on a precise definition of an animal.

Is this true?

[I know nothing about biology, but I find this claim perplexing.]

Definition of Animal

Animal is typically defined phylogenetically (just like any other monophyletic taxon; see here for intro to phylogeny). Any lineage part of the taxon Animalia (aka metazoa) is an animal. This is the definition given by wikipedia > Animal. You can find the animals here on the tree of eukaryotes.

Issue with the claim

  It is surprisingly difficult to find two texts that agree on a precise definition of an animal.

This claim is pretty clumsy in my opinion. It sure can be hard to find a set of phenotypic traits that would group all animals together but it does not mean it is hard to define 'animal'.

IMO, what they meant is

  It is surprisingly difficult to find a set of phenotypic traits the are shared by all animals and by none of the living organism that is are not animal.

This claim would make more sense. It is indeed true that it is hard to make such set of phenotypic traits. There are plenty of non-animals that are heterotrophic eukaryotes (such as fungi), there is at least one animal that is (at least partially) autotroph (Elysia chlorotica), not all animals have a nervous system, etc...


Can different bacteria strains of same species have different genomic sizes? Can two different strains of a single species have different genomic sizes? I am not asking about plasmid. Can they have different sizes of actual chromosome?

Yes, and one could argue that the differences between two strains of the same species are entirely due to their collections of genes (and therefore different genome sizes).

Take the plant pathogen Pseudomonas syringae, for example. There are many different strains, categorized by the plant hosts they cause disease on. This host range is determined by different collections of virulence genes in their genomes. So although they are the same species, they can be remarkably different in their genomes. See this (open access) paper by Baltrus, et al for more information.

A point to remember... "species" is a manmade concept, and there can be different definitions. Some species can have less than 90% similarity at the genome level!


Why isn't meiosis II called mitosis (as the chromosome number doesn't half)? Meiosis: a type of cell division that results in four daughter cells each with half the number of chromosomes of the parent cell, as in the production of gametes and plant spores.
Mitosis: a type of cell division that results in two daughter cells each having the same number and kind of chromosomes as the parent nucleus, typical of ordinary tissue growth.

After meosis II we have the same number of chromosomes as before. So why isn't meiosis II called mitosis instead?

Well, in my opinion, the entirety of the meiosis is a process (reproduction of sex cell) in which two levels of division occur, it's all kind of one process. Though meiosis II may seem to have many similarities with mitosis, meiosis II can only occur with sex cells, to my understanding that is the main factor which differentiates meiosis I and II from mitosis. Furthermore, regardless of the similarities, to call meiosis II the same as 'mitosis' (whilst meiosis II is still in the entirety of the meiosis process) is not only confusing but impractical. I'm sure, though, that somewhere along the line there are several detailed differences between the technicality behind the cellular division in mitosis as in meiosis II. But, don't listen solely to my answer, that's just my opinion since your question is subjective to my personal opinion...


Why does my grass luminesce when I step on it? I live in Austin Texas. My grass is in pretty bad shape but I have noticed small luminous spots on some areas after I step on them.

I'm guessing this will be seasonal so, for the record, this is during November and December that I've noticed it.  It's been quite wet and about 40F to 60F at night. I've seen it a dozen times over the last several weeks. I've attempted to collect samples and when I bring it inside to study it, there is nothing there but grass and maybe some young root systems.  I've googled and haven't seen anything like this discussed.  Does anybody have an explanation?

I can see about 5 spots after trampling a few square feet of my grass.  Using a DSLR and a time exposure, this is the best photo I've been able to get of one:

On one attempt, I pinched the glowy part, held it in my hand, confirmed it was glowing, brought it inside, and this is what I had:

Can anyone explain this?  Is this significant?  Or perhaps the right question is where should I go for a question like this?

If it were fireflies or glow-worms, you would have seen them pretty quickly with your searching and collection of grass. I would guess that this is some kind of bioluminescence caused by bacteria or Dinoflagellate.  I have seen this effect when walking on wet sand at the ocean. It is quite fascinating and fun to watch. According to wikipedia, bioluminescent bacteria and Dinoflagellate can exist in fresh water. The moisture in your yard might be enough to support their growth.

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

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

  The luminescence occurs as a brief (0.1 sec) blue flash (max 476 nm) when stimulated, usually by mechanical disturbance. Therefore, when mechanically stimulated—by boat, swimming, or waves, for example—a blue sparkling light can be seen emanating from the sea surface.[66]


In chromatin, what are the differences among states, interactions, and structures? I am new to the study of chromatin, and I am trying to understand what people mean when they write about chromatin states, chromatin interactions, and chromatin structures.

What are the difference among these?
Is there someone available to explain them to me clearly?

Are loops interactions or structures?

Chromatin state refers to the marks (i.e. methylated DNA, histone modifications, euchromatin v. heterochromatin) found at specific loci and is often referred to as open (readily bound by DNA binding proteins, like transcription factors) or closed (inaccessible to most factors).

Chromatin interactions can include the binding of transcription factors and other DNA binding proteins, but is usually used to describe local and long distance functional contacts between two or more regions of chromatin. These interactions are generated actively through protein-dependent chromatin organization and passively via polymer physics and the nuclear environment.

Chromatin structures can refer to the actual molecular shape and composition of the DNA or to the molecular modifications found at specific regions of chromatin (e.g. heterochromatin, DNA methylation). It can also refer to the ordered compaction of mitotic/meiotic chromosomes.

Chromatin loops are structures that may act in promoting regulatory interactions. Conversely, chromatin interactions may induce looping.

Cavalli and Misteli, Functional Implications of Genome Topology, Nature Structural and Molecular Biology 2013


How is mRNA directed out of the nucleus to its ultimate cytoplasmic location? In the process of translation, I learnt that following formation the mRNA must exit the nucleus through a nuclear pore and attach to a ribosome.

My question is how does mRNA navigate itself out of this pore, and find itself a ribosome to bind to?
Is this a process of diffusion or is there any other mechanism involved?

There is a complex progress involving many proteins that directs RNAs to the nuclear pore complex and ensures that they are moved into the cytoplasm. Below is part of a diagram (edited) from a Nature review article on this topic, showing the transport of mRNA. It is available from the authors online.

Another general review with an illustrative poster is by SR Carmody and SR Wente, and can be found in the Journal of Cell Science.

As far as I am aware, interaction of mRNA with cytoplasmic ribosomes occurs by diffusion. Direction of the ribosomes to specific locations, such as the endoplasmic reticulum, can occur, but is generally through recognition of features of the nascent peptide after tranlation has started. The Wikipedia article on protein targeting provides an introduction to this area.


What is difference between High quality and low quality proteins I have seen in news that some bodybuilder died of taking steroids; when I went through details I learned that  "low quality proteins" contributed to their death. I have studied about linkages in proteins but I don't understand what makes them stronger or weaker. So what is the difference between high quality proteins or low quality proteins? How does low quality protein affect muscular activity or growth?

"Low quality" vs. "high quality" protein does not refer to anything about the linkages between amino acids in proteins. Instead, these terms are used in a nutritional context to refer to whether an individual protein source is sufficient as a sole source of protein in someones' diet.

Essential amino acids are the amino acids that humans cannot synthesize; other amino acids can be synthesized from these, but they do not need to be part of the diet. Not all sources of protein have sufficient quantities of all of the essential amino acids. Low-quality protein sources are also referred to as "incomplete" and high-quality sources as "complete."

Meat products are typically "high quality" because they contain all of the essential amino acids together. Therefore, if you subsisted on various foods but only got your protein from one animal source, you would be okay.

Some plant products do not have all the essential amino acids in large concentrations. However, if you combine protein sources from different "low quality" plant sources that together cover these deficiencies, there is no disadvantage compared to a single "high quality" source.

In the digestive process, all you take out of the proteins you eat is the individual amino acids (generally): that means that only the amino acid composition matters, not the strength or quality of the bonds between amino acids. If someone tries to tell you otherwise, they are probably just trying to sell you something.

Here is a paper that talks about some of these issues, and addresses some of the myths about balancing proteins. The quick summary is that problems develop if you get your sole protein from a source that is low in a particular essential amino acids over a long time period, but there is no need to ensure every meal contain all the amino acids.

It is possible for people on unusual protein diets, either because they are avoiding animal products or using incomplete protein supplements, to develop a particular amino acid deficiency. Otherwise, as long as all amino acids are supplied, there is no difference on health or muscles to consuming "low quality" vs "high quality" proteins.

References:

Young, V. R., & Pellett, P. L. (1994). Plant proteins in relation to human protein and amino acid nutrition. The American journal of clinical nutrition, 59(5), 1203S-1212S.


Half-life and production rate of ion channels There are "not millions, not a few hundred...somewhere in between (some tens of thousands)" of ion channels in a neuron.

Given the number of ion channels per neuron, knowing the  half-life of ion channels allows to calculate the production rate of ion channels, and vice versa.

I am looking for estimates of tpyical half-lifes of ion channels, somehow like this: "not years, not seconds... somewhere in between" but with better upper and lower bounds: months, weeks, .... minutes, hours.

Alternatively: estimates of production rates: "not thousands per second, not one per second ... somewhere in between".

[I know, that all numbers - number of ion channels, production rates, effective half-lifes - can change over time for a given neuron - this may have to do with long-term potentation. So I am talking about neurons in steady-state over a period in which no long-term potentation takes place. But I guess this won't change the rough estimates I asked for too much.]

The rate varies with channels and channel subunits, and you can also distinguish between membrane half-life and degradation half-life, because channels can be cycled bidirectionally between the plasma membrane and internal membranes like the ER. For many (most likely all??) channels these processes are under the control of phosphorylation and/or ubiquination.

For a rough estimate of magnitude though, the relevant time window is hours to days. I'll include a couple references below to support this time frame.

References

Bedford, F. K., Kittler, J. T., Muller, E., Thomas, P., Uren, J. M., Merlo, D., ... & Moss, S. J. (2001). GABAA receptor cell surface number and subunit stability are regulated by the ubiquitin-like protein Plic-1. Nature neuroscience, 4(9), 908-916.

Colley, B. S., Biju, K. C., Visegrady, A., Campbell, S., & Fadool, D. A. (2007). Neurotrophin B receptor kinase increases Kv subfamily member 1.3 (Kv1. 3) ion channel half-life and surface expression. Neuroscience, 144(2), 531-546.

Huh, K. H., & Wenthold, R. J. (1999). Turnover analysis of glutamate receptors identifies a rapidly degraded pool of the N-methyl-D-aspartate receptor subunit, NR1, in cultured cerebellar granule cells. Journal of Biological Chemistry, 274(1), 151-157.


How to select genes before log2 ratio on a RNASeq gene expression matrix, based on signal median I want to transform a TCGA mRNA expression matrix (in linear data format) to log2-ratios and then run a feature (gene) selection, selecting the 1000 most variant genes (genes with higher standard deviation across samples). The workflow is the following:

Select "good" genes before log2 ratio (genes each with median signal at least t in p% of samples);
On selected genes, run log2 ratio, dividing each gene by its median signal and then log2-transforming the result matrix;
Select the 1000 most variant genes along all samples.

How do I select t and p?

There is no rule for fixing t and p. It depends on the level of stringency you expect. Value of t depends on what is considered to be an active concentration; this need not be same for all genes.

This is an RNAseq data; I don't understand what is the "median" signal you are talking about. For each sample a gene would have a normalized expression value which is typically RPKM (Reads Per Kilobase per Million mapped reads). If you have replicates for each sample then take the mean not the median.

Regarding calculation of log-ratios: Always be careful with this especially in case of zeros. Instead of log ratios you may use some sort of a gain metric:

if
ratio = x/y
then
gain = (x-y)/y

You can also do a principal component analysis on the data and select first n principal components.


The smell of the shield bug (aka stink bug) Every time a shield bug flies into my room I try to kill it. Unfortunately, they leave a strong smell after crushing them. Whenever I smell their odor, I always wonder what  the chemical compound is that the bug releases. Does anyone know what the smelly chemical is? If so, please help me out. I always wanted to know what that molecule was.

Shield bugs (also known as stink bugs) are a group of insects in the superfamily Pentatomoidea. As summarized by this article from Rice University, the components of the chemical odor of these insects consist primarily of long chain alkanes, aldehydes, and esters. Esters are to be expected as they're the primary components of many odors. This article also includes other ecological info about the shield bugs' stink, as well as links to some references (including this peer reviewed journal article by Krall et all (1999)).

Another article mentions a 2006 study from Clemson University that identified 2 of the aldehydes in stink bug odor as trans-2-decenal and trans-2-octenal.


Typical cellular respiration lab with a respirometer -- why is potassium hydroxide (KOH) necessary? For context, if you are unsure what this question is in reference to, feel free to take a look at this video by Bozeman science and go forward to about the 2:00 mark. In a typical cellular respiration lab, in particular the one outlined by the College Board, a respirometer and some peas are used to measure the rate of respiration. What confuses me is why KOH (potassium hydroxide) is necessary so that the interior volume of the respirometer won't change. Why wouldn't the solid formed by 2KOH combining with CO2 (K2CO3) cause a change in volume, since it occupies space in the respirometer just like the gasses? Sorry if this seems like a silly question, I have very poor background knowledge of chemistry.

For an animation, feel free to view this link from Pearson.

Thanks!

The solid precipitate does not contribute as much to the pressure inside the vial as the gas does. Intuitively, the gaseous molecule contributes to the pressure by collisions that exert force on the vessel (which would push the water out). By contrast, the solid precipitate only contributes to the pressure insofar as it decreases the volume of the vessel, which is negligible in comparison to the loss of kinetic energy per gas molecule.

Basically, just because they both occupy space, doesn't mean they occupy the same amount of space (or rather, they don't contribute equally to the pressure in the vial). Gases tend to occupy more space than liquid or solid phase molecules of identical size, due to their kinetic energy of motion and the force of their collisions on their surroundings. The KOH reacts with the CO2 to remove it from the pool of high energy gas molecules, converting them to low energy molecules in the solid. With the lower number of molecules contributing to the pressure (ideal gas law), the pressure is lowered and the force of the water becomes greater than the force of the gas, and the water enters the respirometer.


What is the inbreeding coefficient for the female offspring of a sib-mating in a haplodiploid system? The inbreeding coefficient of a sibling mating for a diploid organism is 0.25 (each allele has a 25% of being identical by descent in the offspring).

In haplodiploid organisms, males result from unfertilized eggs, so they don't have fathers (they get half of mom's diploid genome, and that's it). Females have both a mom and a dad, and are diploid in the standard way (dads give their daughters their entire genome).

What is the inbreeding coefficient for the daughter of a sib mating?

From the same article on wikipedia:

  The inbreeding is computed as a percentage of chances for two alleles to be identical by descent.

Now let's draw a family tree for such mating and sign chances for having each allele:

You can see, that the "brother" has a 50% chance of receiving A allele and the "sister" has a 50% chance of receiving A from their mother, but the "brother" will not have the C allele that the sister certainly has. Their daughter will have the allele from her father and one of mother's alleles. Therefore, her chances of having a C allele are 50%, and for a A or a B allele each 75% (remember, she needs two copies, so we need to end up with 200%; furthermore, she may have two A alleles but not more than one C allele). Chances of her having two A or two B alleles are 56,25% $$0.75 * 0.75 = 0.5625$$

Now we have the percentage of chances for two alleles to be identical by descent, her inbreeding coefficient is 56,25%.

The son will have only one allele, 50% for C, 25% for A and 25% for B. Because he does not have two alleles, by definition there is no inbreeding possible.


Does body fat percentage effect storage of fat soluble compounds? Would a person with a higher body fat percentage store more of a fat soluble compound, or store for a longer time, than a person with a lower body fat percentage if they both consumed the same amount in the same time frame?

Does body fat percentage effect storage of fat soluble compounds?

Generally, yes.

Phenytoin, an anti-seizure drug, provides a good and well studied example.  The key issue here is that, for phenytoin, plasma half-life is proportional to the apparent volume of distribution of the drug.

(Apparent) volume of distribution is a pharmacokinetic property of a drug. It is the volume a drug would need to be dissolved in in order to achieve the concentration of the drug in plasma. For fat soluble compounds, this can be quite large, as the drug is primarily partitioned into fatty tissues, leaving a low concentration in plasma. Empirically, phenytoin's volume of distribution is higher for more obese patients, and (by the same reference), the half-life is proportionally longer.

As is often the case, though, it depends on the drug. For some lipid soluble drugs, an increased rate of metabolism by the liver in obesity compensates for the increased volume of distribution; for others, obesity doesn't have that much of an impact on volume of distribution in the first place.


Why do we like salt? A few friends of mine told me that salt provides zero nutritional value to us, and in fact can harm our bodies. Now, these guys are medical students, and being an engineering student myself, I decided not to argue with them. The rest of this question assumes that this fact is true, so if it's not, you can just go ahead and call me out now...

So here's my understanding of things: we 'like' doing things because of our instincts, which have slowly become refined over millions of years. For example, I 'like' eating foods with fat in it because my instinct compels me to do so. Fat is 'good' for my body, since it provides a lot of energy (obesity problems aside).

So are there certain things, such as eating salt, that are not in fact beneficial in any way, and we only do these things because we were trained to as children? This is the only thing I could come up with, but it's not a very satisfying explanation for a few reasons. First, I think humans have been eating salt for a long time. This would mean that most likely, it is actually our 'instinct' to eat salt. Also, salt is eaten in every culture today, which has the same implication.

So is there some better explanation?

In developed countries we usually consume enough salt (sodium to be exact) without actually adding table salt to food. Everything can become toxic when consumed in excess - even water - and when we frequently add more salt to foods, we tend to consume sodium in potentially harmful excess. That's what your friends are referring to.

However, salt (sodium) is one of the most essential substances your body needs to stay alive, for several reasons. One of the main purposes of sodium is the upkeep of blood's osmolarity (i.e. concentrations of osmotically active compounds. Higher salt concentration on one side of a permeable membrane attracts water to that side - I'm sure you've heard that before). There are numerous systems in your body to make sure the osmolarity of blood is correct. If they fail and blood becomes hypo or hypertonic, your cells will be sucked dry or pumped full of water and in either case, burst and die.

Look up the renin-angiotensin-aldosterone system for example: when the kidney filters blood, it reabsorbs or lets through water depending on the current blood osmolarity; leading to higher or lower amount of higher or lower concentrated urine. You drink lots, your blood is diluted, it becomes less tonic, kidney registers that and lets water through more, you urinate more. There are many more elements involved there, including blood pressure, nerve signals stimulating thirst or hunger of different kinds, some hormones etc.

As you can see, there's a reason why the basic infusion given in hospitals to replace lost blood quickly isn't just water but normal saline.

Delayed update to pick up some side aspects of your description: 1) There are of course things that humans do which have absolutely no value to them whatsoever. Anything that plays into the feel-good-reward-circuit in our brain can become such an unhelpful habit. Take smoking and drug consumption as examples. 2) About evolutionary relevance: Being a key player in maintaining body function, evolution selected for instictively liking salt. Simultaneously, most people will not like food that is extremely salty - a protective mechanism against excess.


Why can't certain nucleoside analogs be used to label bacterial RNA? A 2020 publication in Nucleic Acids Research 1 includes the following passage:

A variety of nucleoside analogs have been developed for metabolic RNA labeling in various eukaryotic cells (9–16). Among them, 4-thiouridine (4SU) and 5-ethynyluridine (EU) are two most widely used noncanonical nucleosides that can be conjugated via thiol coupling chemistry and click chemistry, respectively (9,10). Although the metabolic RNA labeling technique has been instrumental for studying RNA dynamics in eukaryotes, it is not applicable to bacteria.

The authors give no citations or further explanations for the bolded claim.  Indeed, I have found at least one publication that contradicts this statement,2 showing 4SU labeling in E. coli:

We have defined conditions allowing the substitution of 13 +/- 2% of the uridine residues in bulk RNA by 4-thiouridine.

One explanation is that 4SU is a natural RNA modification in bacteria, as Rogers et al. 3 states that most bacterial tRNAs contain 4SU. So, while bacterial RNA can be labeled with exogenous 4SU, naturally occurring 4SU confounds analysis. Concerning EU, Blenkiron et al. 4 used this analog to label nascent RNAs from uropathogenic E. coli in order to track the fate of bacterial RNAs in membrane vesicles:

We then looked at whether we could track uptake of MV RNA cargo into treated host cells by labelling UPEC nascent RNA in the bacteria before it was packaged with MVs. This was achieved by adding an excess of a modified uracil, 5EU (5-ethynyl uridine), which was incorporated into the newly synthesised and MV associated RNA.

Additionally, the text of this research grant award abstract 5 suggests that EU is suitable for labeling both E. coli and B. subtilis:

We have been investigating whether bacteria can incorporate the “clickable” RNA analog 5-ethynyl uridine (EU) for subsequent attachment of fluorescent label (Alexa Fluor) for microscopic detection or a chemical tag (desthiobiotin) for streptavidin-mediated RNA capture. The results for both aspects so far are a qualified “yes”. Both Escherichia coli and Bacillus subtilis grown with EU can subsequently be detected by fluorescence microscopy, but E. coli becomes considerably more brightly labeled.

I can find no research stating EU / 5EU naturally occurs in bacterial RNA.
My question, in short: What aspects of bacterial metabolism or RNA composition justify the claim that 4SU and EU are "not applicable" for bacterial RNA labeling?

Edit, 1 March 2021 -- I'm adding a bounty to garner more attention. From further reading, I suspect the answer to be one of 3 possibilities.

Per David's comment, the bacterial cell wall may be impermeable to certain formulations of nucleoside analogs or the reagents subsequently used in thiol coupling / click chemistry.
Certain nucleoside analogs are toxic in bacteria to an extent not seen in eukaryotic cells, perhaps by a mechanism that causes the elongating RNA polymerase to stall.
4SU and EU labeling are applicable to bacteria, and the claims of the authors are unsubstantiated.

References

Meng L, Guo Y, Tang Q, Huang R, Xie Y, Chen X. Metabolic RNA labeling for probing RNA dynamics in bacteria. Nucleic Acids Res. 2020 Dec 16;48(22):12566-12576.
Favre A, Bezerra R, Hajnsdorf E, Lemaigre Dubreuil Y, Expert-Bezançon A. Substitution of uridine in vivo by the intrinsic photoactivable probe 4-thiouridine in Escherichia coli RNA. Its use for E. coli ribosome structural analysis. Eur J Biochem. 1986 Nov 3;160(3):441-9.
Rogers KC, Crescenzo AT, Söll D. Aminoacylation of transfer RNAs with 2-thiouridine derivatives in the wobble position of the anticodon. Biochimie. 1995;77(1-2):66-74.
Blenkiron C, Simonov D, Muthukaruppan A, Tsai P, Dauros P, Green S, Hong J, Print CG, Swift S, Phillips AR. Uropathogenic Escherichia coli Releases Extracellular Vesicles That Are Associated with RNA. PLoS One. 2016 Aug 8;11(8):e0160440.
Click-chemistry labeling of RNA: A new tool for microbial ecology?

Meng et al. actually give their explanation in the first paragraph of their results section. The main reasons for their claim are that they did not detect any labeling with 4SU or EU and that both analogs suppress bacterial growth. Also they raise the issue with the naturally occurring 4SU in tRNAs.

Aiming to develop nucleoside analogs compatible with bacterial RNA labeling, we first set out to evaluate the two nucleoside analogs widely used in eukaryotic cells. E. coli cells were incubated with 4SU or EU at varied concentrations for 2 h, which resulted in no detectable labeling even at high concentrations (Supplementary Figure S1A, B). Moreover, severe suppression of bacterial growth was observed with both 4SU and EU (Supplementary Figure S1C, D), which was in agreement with previous observations that 4SU impaired cellular metabolism in E. coli (31). Cell viability was significantly impaired with 4SU at concentrations higher than 100 μM, while EU did not induce significant decrease in cell viability (Supplementary Figure S1E, F). In addition, tRNAs of bacteria contain endogenous 4SU generated via thiolation of uracil (32), which may interfere with metabolic labeling if exogenous 4SU would be used. Of note, although EU does not incorporate into DNA in mammalian cells (10), significant labeling of DNA was observed in EU-treated E. coli, presumably due to metabolic conversion of EU to EdUTP (Supplementary Figure S1G). Together, these results demonstrate that 4SU and EU are not applicable for bacteria.

This explanation is not necessarily incompatible with the results in the other references mostly because the strains and the test approaches are different.
In Favre et al. they use a different strain of E. coli,"an Escherichia coli
pyrD strain" that is optimized for 4SU incorporation :
In Material and Methods :

pyrD used to control the level of 4-thiouridine incorporation

and in Results :

a) growth of E. coli AB1157 sfiA pyrD in the presence of 4-thiouridine
Preliminary studies showed that the level of s4U incorporation into the rRNA of strains MRE 600 or K12 AB1157 grown in a standard glucose medium in the presence of 4-thiouridine remained at the detection limit. We therefore use AB1157 pyrD mutant deficient in the pyrimidine biosynthesis pathway. To our growth medium we systematically add 40 μg/ml uridine because it is  the minimal concentration required to supplement growth fully. The growth of the pyrD mutant was first examined at different temperatures and different exogeneous s4U concentrations from 40 μg/ml upwards in the conditions defined in Material and Methods, In Fig. 1 we report  the growth curves obtained for two s4U/U ratios,1 and 2.5, and four temperatures: 25°C, 28°C, 30°C, 35°C. When the ratio is 1 there is practically no growth inhibition. With  a ratio of 2.5 the  growth  inhibition becomes strongly dependent on temperature. The culture does not grow at all at 20°C, the  growth is linear between 25°C and 30°C and for temperatures above 30°C it escapes inhibition, becoming exponential. As will be described below significant s4U incorporation occurs in  conditions where growth is linear.

In Favre et al. as seen at the end of the paragraph above as well as in another publication (Bezerra and Favre, 1990) from the same lab shows that incorporation of 4SU depends on several factors.
Concerning the work of Blenkiron et al., it is harder to explain but they also use a different strain so that may impact the incorporation and they do not use the same approaches compared to Meng et al. to detect it. Confocal microscopy for Blenkiron et al. vs Dot blot and In-gel fluorescence for Meng et al..
Finally as far as the grant abstract is concerned, it's hard to conclude because the information is scarce but as Meng et al. they also observed an effect (although milder) of 5EU on bacterial growth and again, they used a different approach to observe the labeling based on fluorescence microscopy as Blenkiron et al..

References :

Meng L, Guo Y, Tang Q, Huang R, Xie Y, Chen X. Metabolic RNA labeling for probing RNA dynamics in bacteria. Nucleic Acids Res. 2020 Dec 16;48(22):12566-12576.
Favre A, Bezerra R, Hajnsdorf E, Lemaigre Dubreuil Y, Expert-Bezançon A. Substitution of uridine in vivo by the intrinsic photoactivable probe 4-thiouridine in Escherichia coli RNA. Its use for E. coli ribosome structural analysis. Eur J Biochem. 1986 Nov 3;160(3):441-9.
Blenkiron C, Simonov D, Muthukaruppan A, Tsai P, Dauros P, Green S, Hong J, Print CG, Swift S, Phillips AR. Uropathogenic Escherichia coli Releases Extracellular Vesicles That Are Associated with RNA. PLoS One. 2016 Aug 8;11(8):e0160440.
Bezerra R, Favre A. In vivo incorporation of the intrinsic photolabel 4-thiouridine into Escherichia coli RNAs. Biochemical and biophysical research communications. 1990 Jan 15;166(1):29-37.


Are lymphocyte sizes clustered in two groups? Tortora writes in Principles of Anatomy and Physiology:

  Lymphocytes may be as small as 6–9 μm in diameter or as large as 10–14 μm in diameter.

Those ranges are quite close to each others. Should the above be taken to mean that lymphocytes sizes are clustered in two groups, or is it just a way of saying that lymphocytes are 6-14 μm?

Unlike erythrocytes that have a very rigid shape and almost cannot change their size (hence the size distribution is indicative and can be used for diagnostic purposes in medicine), lymphocytes can change their size in a wider range, this is why you see the numbers 6-9 and 10-15 μm.

And they indeed cluster into several different groups: so-called "large granular lymphocytes", also known as NK-cells or "natural killers" (usually >10μm) and "small granular lymphocytes", constituted by a large family of T- and B-lymphocites(usually <10μm). But this clustering is not really distinct, for as I said above, both NK and T/B-cells can shrink (if the osmolarity of the external medium grows due to acidosis, inflammation etc.) and swell (on binding many IgE/IgG complexes, on certain cell factor released etc.). Besides, there are also some intermediate size cells, called NKT-cells, that also flatten the distribution.

So, what you can definitely say is that the typical size distribution of lymphocytes has two peaks: around 8 and 12 μm respectively.


Is there a hormone combination that makes humans grumpy? Imagine a typical situation that is likely to give rise to a bad temper within an individual: a person is awoken very early in the morning by a sound of a lawn being mowed next door.

Unlike expected awakening by an alarm clock, such unexpected awakening by a lawn mower is likely to leave the person in a bad temper, feeling grumpy or sulky.

I'm interested if there's a specific hormone or process that makes a person experience the feeling of grumpiness? Is it related to adrenaline and fight or flight instinct?

In other words, can experience of grumpiness be induced under laboratory conditions by using some combination of hormones/drugs?

This is a hard question to respond to.

Many things might make someone grumpy.  There are also individual temperaments, making grumpy hard to quantify - a Grumpy to one person might barely be a blip on another individual's scale.  Hormones like cortisol reflect stress, and can make people in general irritable, but I doubt any one combination of hormones would always cause grumpiness.

But I thought I'd venture an answer since I did see this paper today:  "Low glucose relates to greater aggression in married couples" doi: 10.1073/pnas.1400619111

Being hungry will do this for lots of people, so maybe a bit of an answer for you. There are lots of different kinds of signals that mediate hunger though, so still a tough call.

Update: here's an additional article that specifically talks about parts of the brain involved in aggression and grumpiness as response to a drop in glucose.


What is this bee/wasp nest? Perhaps this is a tropical wasp. Can you identify it? Is it artificial?

This is likely a honeycomb created by some species of honey bee.

A beekeeper (Jessie Brown) from New Mexico shared to her blog the following photos of a "free form" bee hive some of her bees created:

 Photo credit: Nina Dubois

In that instance (as well as the one mentioned here and pictured below), the beekeeper moved some "burr comb" to a new location and the bees used that moved remnant piece to build a mound-like comb.

 Photo credit: Phillip Cairns


Homogeneous and complex nuclei In the Wikipedia article on nuclei one reads:

  "The neurons in one nucleus usually have roughly similar connections
  and functions."

I read this as "a nucleus usually is roughly homogenous", i.e. contains a small number of neuron types, distributed roughly equally and with a roughly homogenous connectivity pattern.

But it is also stated:

  "A nucleus may itself have a complex internal structure, with multiple
  types of neurons arranged in clumps (subnuclei) or layers."

What I would like to know:

Is my reading correct?
Are there really more nuclei of the more simple (homogeneous) type than of the more complex type?
Which are prototypical examples of both of the types (more simple and more complex)?
Which are the greatest nuclei of "the" simple type (with respect to volume or number of neurons, taking "simple" with a grain of salt)?

I think you are reading too much into that statement. The proper reading of that statement is to add on the implied "..compared to other nuclei." That is, what defines a nucleus, in most cases, is some shared similarity in connectivity. That does not mean homogeneity.

I also think your reading of the second statement is incorrect; it does not suggest that there are "simple and complex" nuclei as two distinct categories, rather it is indicating that "complexity" varies, and gives a couple examples; essentially, it is exactly saying that you should not assume homogeneity.

I don't think it makes much sense to think in terms of "number" of nuclei, and anyways, nuclei can be somewhat arbitrary. For example, take the auditory thalamus: the medial geniculate nucleus (MGN). The MGN is typically divided into three parts: the dorsal, ventral, and medial divisions. Someone chose to call them all the medial geniculate nucleus, based on gross appearance, but with more functional understanding we can classify each part separately. Should this be one nucleus or three? It really doesn't matter, it's just semantics and terminology to get people talking about the same structure. In one context, it makes sense to talk about the whole MGN, in other cases it makes sense to differentiate between MGv, MGm, and MGd. You could call them subnuclei, or nuclei, or whatever you want. Most people choose to just be consistent with the terminology used in their field for historical reasons because it doesn't matter.
I don't really think it makes sense to think of in terms of prototypes; nuclei are different from each other.
Again, you'd have to first define simple and complex. I don't think there is meaningful dichotomous distinction.


Could potatoes that have been refrigerated for 142 days still sprout? I know that potatoes can still sprout even after being refrigerated, but could you refrigerate them for 142 days still use them as seeds to grow more plants after that?

As for the temperature of the fridge, look at this.
 Considering that, what would be likely?

What about frozen or hermetic potatoes?

If anyone's wondering why I'm asking such a strange question, here's why.

Yes, it is very common to do this on farms. I have grown potatoes that I stored loosely in my basement (~5 degree temperature during the winter when they would be stored) for about 6 months at a time every year for the past 20 years.


Book recommendations: biological data analysis/error I'm working as an undergrad in a tissue culture lab, and I have the most experience with statistics out of everyone in the lab. However, most of the knowledge I have in statistics is from my math courses which are mainly theoretical.

Does anyone have good recommendations for books on biological experimental design, data analysis, and statistical error? I'd prefer that they be specific to biology, but if there are some good general books with applications that works for me as well. I just want to get a feel for any specific knowledge I will need.

There are many books that teach statistics and R together. I would personally not recommend these books. Learn the fundamentals and just google what command already exist in R to perform the analysis you need to do.

I would recommend Experimental Design and Data Analysis for Biologists by Quinn and Keough. It is general, applied and pleasant to read.

As you already have good basis in statistics, you won't need an intro textbook but for other users (and because I personally work with one of the authors) I would like to mention The Analysis of Biological Data by Schluter and Whitlock.


Are there any animals that get smaller as a normal part of their life cycle? It seems that at any given moment in a creatures life, it either grows bigger or has stopped growing.

The only exceptions I know of are extreme events like insects undergoing metamorphosis or evolutionarily irrelevant effects like humans shrinking a bit at old ages due to their spine getting compressed (I consider it irrelevant because for most of human history, people old enough for this effect to be significant enough were either dead or long done with reproduction).

Are there any animals that are known to "grow smaller" over some period of their lives as a purposeful part of their biological functions?

In holometabolous insects it is quite common for the final larval stage to be heavier than the adult stage. For instance, Goliathus beetles, which are among the largest insects on earth, the adult stage often weighs about half of the final larval stage (which weigh 80-100 grams).

The same situation can be seen in the Hercules beetles, which this picture of both larvae and adult of Dynastes tityus clearly shows:

.
(picture from http://harrellhouse.com/in-the-museum-eastern-hercules-beetles/)


How can a drink contain 1.8 kcal energy while 0 g fat/carbs/protein? How is it possible that the Red Bull Zero contains 0 gramms of fat, carbs and protein, but it still has 1.8 kcal of "energy".
I always thought that the human body can gain energy only from 3 kinds of nutrients: fat, carbs and protein. Is there a 4th kind? Or they just display an energy value that's not accessible to the body?

The list of ingredients on the can mentions "Zuckerkulör," which is caramel colour, which can have 2 kcal/g, according to one producer.

Next, there is "Citronensäure," which is citric acid, which can, as other organic acids, have 2-3 kcal/g, according to this source.

There is also taurine, which is an amino acid-like compound, so it could, like proteins, have 4 kcal/g, but is, according to Taurine Metabolism in Man (Journal of Nutrition), poorly metabolized and probably has less than 0.2 kcal/g.

It is sometimes allowed, at least by U.S. Food and Drug Administration, to round the amounts of macronutrients (carbs, proteins, fats) smaller than 0.5 g per serving to zero, which is what they obviously did in this case, but they decided to keep the summary of calorie values of all ingredients exact.

It is usually said that only 3 types of nutrients contain energy: carbohydrates, proteins and fats.

Digestible carbohydrates (sugars and starch) provide 4 kcal/g. Undigestible, but fermentable, carbohydrates, such as soluble dietary fiber, sugar alcohols or polyols (maltitol, mannitol, sorbitol, xylitol, isomalt) and organic acids (citric, acetic acid, etc.), can provide 2 kcal/g of energy in average. On the other hand, some carbohydrates (such as "Sucralose" from the ingredient list) are neither digestible nor fermentable, so they do not provide any calories.

The "fourth" nutrient that can provide energy (7 kcal/g) is alcohol (ethanol), but is not considered a nutrient by some authors.

According to Food Label Accuracy of Common Snack Foods
 article (Obesity, 2014), the calories on the food labels should represent usable calories (metabolizable energy):

  Of note, it is important to distinguish that food label calories
  actually represent metabolizable energy, which is total caloric
  content minus calories that are presumably not absorbed by the body
  and excreted as waste.


Can anyone identify this plant from Bangladesh? I have taken the picture from an agriculture university in Bangladesh.

The genus is Lantana, of Verbenaceae. That particular one could perhaps be L. camara. There's a number of papers that exist which study L. camara in Bangladesh, just some examples:

http://link.springer.com/article/10.1007%2Fs11676-007-0060-6

http://www.banglajol.info/index.php/BJB/article/view/1513


what is this centipede like creature? They are very big. About the size of my hand in length and I've seen two now. My cat brought one in from the Texas border region.

dark bands between segments and long tails match:

Distribution matches:


Which variables are controlled in the mammalian womb to ensure a healthy environment? Recently, researchers have had some success with artificial wombs. Which aspects of the womb are difficult to replicate through technology?

It seems you are referring to this recent advance:

http://www.sciencemag.org/news/2017/04/fluid-filled-biobag-allows-premature-lambs-develop-outside-womb
https://www.nature.com/articles/ncomms15112

Involving putting premature lambs (delivered via caesarean) in bags of nutritive fluid and connecting the umbilical cord to an apparatus to oxygenate the blood.

Your question asks which variables are controlled in a mammalian womb, which I think is a misleading way to look at what a womb does and thus what the difficulties are with reproducing it. Namely, it makes it sound like the womb is a container whose purpose is to keep environmental variables (temperature, pressure, etc) at a good value for the development of a fetus. The problem is the womb doesn't just contain the fetus, it feeds it via the placenta. And the placenta is a structure built by fetus during embryogenesis, that connects to the lining of the uterus and enmeshes itself with it so that there is a huge surface of contact between the blood vessels of the mother and the blood vessels of the placenta, so oxygen and nutrients can pass through the mother's blood vessels to the placenta's and from there to the fetus via the umbilical cord. This allows the fetus to get all the nutrients and oxygen it needs to develop.

The "Biobag" these researchers created for these lambs is designed for fetuses who are advanced enough in their development that the main problem they have with surviving outside the womb is that their lungs are immature; the main purpose of this contraption is to allow oxygenation via their umbilical cord while keeping their lungs filled with fluid. And it also seems like they're being fed via that fluid, which suggests they're mature enough to get nutrition via their digestive system.

The paper gives quite a few details of the challenges involved in even that comparatively low level of uterine service. Infection, setting up the cannulas and oxygenating system so that the blood flow is just right and doesn't overtax the fetal heart, making sure there is no clotting, haemorrhage or brain damage...

I imagine the main challenge of making an actual artificial womb that's usable from implantation on would be emulating implantation itself, with artificial endometrial lining that a placenta could naturally develop in and intermingle its blood vessels with and somehow accurately reproducing the flow of blood that's necessary to feed the placenta. If we assume an artificial womb for a fetus that already has an umbilical cord, so we basically need to emulate the placenta's job not the uterus', but can be used earlier than Partrige et al's Biobag, then I imagine all the concerns they had about cannula size and getting the blood flow just right would be a million times harder with tinier, less-mature umbilical cords and fetuses. Not to mention if they need to put nutrients in the blood and not just oxygen.


Detecting nuclear DNA in suspension of mitochondria Is there a way to detect nuclear DNA in a suspension of mitochondria extracted from leukocytes? I need to make sure there is no nuclear DNA in the suspension before extracting mtDNA from the mitochondria.

Centrifuge the suspension in Cesium Chloride solution at a particular g value which causes the mitochondria to settle to the bottom of the centrifuge tube but leaves nuclear DNA forming a layer near the top of the centrifuge tube. This is since the nuclear DNA is less dense than the mitochondria. Using a needle syringe, extract a small part of the centrifuged suspension from the very bottom of the centrifuge tube. This extract is most likely to contain no nuclear DNA. Hope this helps :).


How are the gene sequences of individual sperm and egg cells "randomized"? What I mean by "randomized" is, in the place where an egg cell or sperm cell is made, what is the mechanism by which each one is not made identically? Though I am a layman, I'm pretty sure that if the sperm cell that was right next to "me" had made it to the egg instead of the one that did, the resultant human would have a different genomic sequence and different features.

Meiosis is the type of cell division responsible for the diversification of genetic material among egg and sperm cells. The diversity comes primarily from crossing over (Prophase I) and the cell divisions (Telophase I & II) later on in the process.

  Meiosis begins with one diploid cell containing two copies of each
  chromosome—one from the organism's mother and one from its father—and
  produces four haploid cells containing one copy of each chromosome.
  Each of the resulting chromosomes in the gamete cells is a unique
  mixture of maternal and paternal DNA, ensuring that offspring are
  genetically distinct from either parent. This gives rise to genetic
  diversity in sexually reproducing populations, which provides the
  variation of physical and behavioural attributes (phenotypes) upon
  which natural selection acts.

Further detail of the precise phases can be found in the Wikipeida article.

[picture from wikipedia]


Effects of beer on muscle recovery after exercise I noticed it several times that when I drink beer (even one bottle) after some heavy workout, the next day my muscles are more stiff than other times, and not the same way... Is it because that lactate and NADH levels are raised both due to the anaerobic training and alcohol metabolism?

There are a few studies around related to this. One particular study(1) suggests that:

Neural drive is decreased following eccentric exercise leading to a reduction in muscle force. Alcohol may further reduce the already depressed neural drive.
Alcohol also has been shown to affect the innate immune system by altering the activity of a number of inflammatory proteins. A lot of these play "important roles in the damage and repair processes occurring after eccentric exercise". Alterations in these proteins may affect muscle recovery post-exercise.(2).

The second point is maybe what's relevant to the question at hand? They say more research is required though.

Edit (expanded discussion per comment below). The study itself was carried out using 8 (+/-1) standard drinks immediately following a workout. The article(1) itself doesn't hypothesise the point made earlier regarding inflammatory proteins, it rather points to earlier research(2), to suggest this may be the case.

Whether a dose-dependant relationship exists, or the magnitude of it with regards to the alteration in inflammatory proteins is not discussed (except in the context of chronic versus acute alcohol use). Just that the possible effect on inflammatory proteins exists which may affect muscle recovery post-exercise.

Barnes, et al. Acute alcohol consumption aggravates the decline in muscle performance following strenuous eccentric exercise. Journal of Science and Medicine in Sport. 2010. 1:189-93.

Edit
2. Szabo. Consequences of alcohol consumption on host defence. Alcohol Alcohol. 1999. 1999:830–841.


Do mitochondrial DNA have repair enzymes? Mitochondria are considered endosymbionts originated from a prokaryote. So, do they have a DNA repair mechanism ?

Yes, mtDNA can be repaired by enzymes coded by nuclear genes.
http://www.ncbi.nlm.nih.gov/pubmed/22992591


Variant VCF: AD vs DP? In my VCF file from GATK, I have the following definitions for AD and DP.

AD - Allelic depths for the ref and alt alleles in the order listed
DP - Approximate read depth (reads with MQ=255 or with bad mates are filtered

I don't understand the definitions, can anybody explain in a less technical way?

From what I can read, AD gives the number of reads spanning the reference and variant allele. But what does DP mean? This doesn't look like the total number of reads spanning a variant, so what is this? How does this different to AD?

DP is the total number of read bases spanning a particular position. If you add up the different AD, you should get a number close to DP, the difference being merely in how the reads are filtered in either set of numbers.


Why is Chromosome 1 called Chromosome 1? Chromosome 1 is the designation for the largest human chromosome. Humans have two copies of chromosome 1, as they do with all of the autosomes, which are the non-sex chromosomes. Chromosome 1 spans about 249 million nucleotide base pairs, which are the basic units of information for DNA. It represents about 8% of the total DNA in human cells.

Why is Chromosome 1 called Chromosome 1? Is being the largest human chromosome the only reason?

Chromosomes were first known about from karyograms (that's the word for chromosome pictures like these) sort of like this one (1)(2):

The scientists looking at these chromosomes didn't know much about them at first. They were discovered before anything was understood about genes, but by 1922 it was thought they were the carriers of genes. Without much understanding of the chromosomes, and certainly no understanding of what they carried, scientists needed an easy way to order and compare them. They chose a straight forward option - size - and paired them up and then lined them up biggest to smallest. Because the sex chromosomes didn't fit into this scheme of matching pairs they were left to the end.

Hence Chromosome 1 is Chromosome 1 because it is the largest autosomal chromosome.

Notes:

The actual first karyogram was of a plant, this one is of a human male.
The image above is public domain, obtained from Wikipedia, and originally made by the National Human Genome Research Institute.


Why is peripheral vision not bleached by daylight? In daylight, rods are known to be bleached: we have to wait some time after going into darkness before scotopic vision becomes effective. But, as I understand, peripheral vision is also mostly due to rods, since away from the fovea, cone density rapidly declines.

But I wonder then: if rods normally saturate in bright light, why does peripheral vision still work in daylight?

Short answer
In photopic lighting, peripheral vision is mediated by cones.

Background
The rods are indeed saturated at daylight, and even at twilight (source: Nature). However, the cones are active and although their density in the periphery is low, they are still present (Fig. 1). Hence, peripheral vision in photopic lighting conditions is mediated by cones. Because of their low density in the periphery, however, visual acuity is low (Kolb, 2012).

Fig. 1. Rod & cone densities in the retina. (Kolb, 2012)

Reference
- Kolb, Photoreceptors, In: Webvision: The Organization of the Retina and Visual System. Utah University


How are neurons / synapses "biased"? I'm trying to see if I understand this correctly. I've read the question Can the human brain be reduced to a binary system? and one of the answers explains:

  While action potentials are usually binary, you should note that
  synaptic communication between neurons is generally not binary. Most
  synapses work by neurotransmittors, and this is a chemically mediated
  graded response that, for example, act on voltage-gated ion channels.

Looking into the graded response article on Wikipedia:

  Postsynaptic potentials are changes in the membrane potential of the
  postsynaptic terminal of a chemical synapse. Postsynaptic potentials
  are graded potentials, and should not be confused with action
  potentials although their function is to initiate or inhibit action
  potentials

Ok, so from what I understand, involving what I learned in this video about action potential, and those two quotes, there can be a "bias" in the synapse process of neurons that make them more or less likely to reach the threshold for action potential when they receive neurotransmitters as the result of the activity from axons connected to their dendrites. Basically, I have the idea that somehow, the synapse area between neural connections becomes trained based on past interactions on whether or not to fire "easily" or be "reluctant" to fire or else fires more powerfully or weakly contributing more or less toward action potential of neurons on the receiving end.

Edit: On second thought, I also recall learning about a mechanism enforcing recharge time between firing, so the neurons are throttled if they fire too rapidly, a mechanism which, (iirc) if defected can cause epilepsy. Really not sure about that, but it would sort of be the opposite of "training" it seems to me.

So I have a few questions surrounding this subject:

Are some "actions" or "transmissions" (for lack of the correct terminology, when the neuron fires) more powerful than others, contributing more dramatically to action potentials of neurons receiving neurotransmitters when it fires?
Or if I'm on the wrong track with that question, how does the bias occur / form over time? Is a bias based on short term or long term series of interactions? How many past interactions are significant in the current state of the bias at any given time?
Is there bias at all?

The term that most scientists use to describe a synapse's "bias" is synaptic strength. The strengths of synapses depend on their "history".  The change of synaptic strength is called synaptic plasticity. This topic is closely related to memory formation and is a very broad question to answer (groups of wikipedia/scholarpedia pages and tons of reviews, not single publications).

Generally, the strength of a synapse, i.e. the size of the effect of a presynaptic stimulus on the postsynaptic neuron depends on presynaptic and postsynaptic factors. To name just a few:

the number of vesicles released from the terminal,
the expression levels of the neurotransmitter reuptake and/or breakdown enzymes,
the expression level, location and posttranslational modifications of postsynaptic receptors and
uncountable other factors.

Although there have been decades research and a nobel prize (to Eric Kandel) on the topic, there is still a lot to find out.

For a start, you might want to look up
Synaptic plasticity and/or
Spike-timing dependent plasticity (long term potentiation and long term depression).

LTP is also a good example to answer all three of your questions (if I understood them correctly).

third question: yes.
second question: LTP (and other mechanisms).
first question: Different frequencies of spike trains are more or less effective at triggering LTP, making them more or less powerful to the change in synaptic strength, affecting the response of future input to the same synapse.


Is it possible to print humans? According to this news, scientists can use stem cells to print objects. So say theoretically, is there any possibility to print human beings?

The easiest answer to this question is NO. We will not be able to print humans any time soon, if ever. Despite the potential of the technology, it will likely still make more sense to use stem cells to fight genetic diseases, create limited cellular masses such as hearts and other organs, and to do reconstructive surgeries such as skeletal repairs.

The reasons vary but will include:

The human being is not just a single series of cells, we are a complex melange of integrated systems connected together in a predetermined manner by our genetic code.
The standard 3D printing process might be most effective for producing a single type of cells or a simple organ whose structure is simple and whose configuration could be managed with computer aided design to produce the cells needed at the time of the organ's creation. Even an organ such as a liver will need connective tissues, for blood to be provided for the organ and those cells would need to be integrated as well.
Brain tissue would be the most difficult part of this process. Even having the tissue matrix derived from stem cells would not give us the understanding of how to create an actual brain from a printing process, which uses a layering method to deliver the material into a 3D structure.

It is certain that some things we may do in the future may be done by printing output that resembles cellular matter, i.e. bone repair and restructuring.

In the case of fixed materials such as bone, a 3D model could be taken and then replicated on a printer. The replicated material is then integrated into an area of the body and allowed to either grow in place or artificially stimulated to grow to replace the damaged area.
I use bones as an example since they have very limited purposes and once replicated artificially, would be relatively easy to put in place. This would certainly transform the dental industry, perhaps hip replacement surgeries.
If the technology could be applied internally to damaged tissues, perhaps spinal injuries could be repaired and with proper rehabilitation, a person who may have lost mobility due to an injury could have nervous tissue regrown and learn to walk again.

The potential for specific cellular development is outstanding but the method for growing complete humans has had millions of years evolution and not likely to be surpassed by Humanity in the next thirty to one hundred years unless we come to a far greater understanding of the human genome and the genetic/cellular relationships between systems in the human body as a collective whole.


How to measure quality and quantity of DNA? I would like to mesure DNA. I quantify the concentration with Qubit fluorometer, but I would like to know also quality of DNA. I try BioAnalyzer (Agilent),but without success. Bioanalyzer measure DNA samples from 100 to 7 000 bp (12 000 bp). Problem is that my DNA is not sheared, I would like to quantify whole mouse DNA. Have you any idea? Thanks!

You can run your DNA sample on agarose gel to see, whether you have significant degradation.

If you are interested in contamination, you can make a standard photometric analysis to assess the 260/280 and 260/230 ratios and absorbance at 320 nm on NanoDrop or even something similar to Eppendorf's BioPhotometer.

In case RNA may be an obstacle for some down-stream procedures, with Qubit you can also measure separately DNA and RNA concentrations and then decide if you have too much RNA and it's worth treating your sample with RNase.


Understanding food composition data from USDA for Vitamin A When researching the nutritional value of carrots the Vitamin A comes in two  measurements as RAE and UI:

https://ndb.nal.usda.gov/ndb/foods/show/11124?n1=%7BQv%3D1%7D&fgcd=&man=&lfacet=&count=&max=25&sort=default&qlookup=Carrots%2C+raw&offset=&format=Abridged&new=&measureby=&ds=&Qv=1&qt=&qp=&qa=&qn=&q=&ing=

After reading the following article
https://ods.od.nih.gov/factsheets/VitaminA-HealthProfessional/

I understand that IU can be transferred to RAE, but I wonder if in case of USDA does two records represent the same value or they are supposed to be combined? :shy:

If you had previous experience working with this database I will be more then glad to hear you opinion about that :)

The corrected answer: It seems that the both rows from your table show the same thing: the sum amount of all vitamin A-related substances, but in different units; the 1st row in RAE and the 2nd row in IU.

As I said before, according to ods.nih.gov, 1 IU retinol = 0.3 mcg RAE, but this conversation is true only for retinol (the true, "pre-formed" vitamin A), which is found only in animal foods.

The main vitamin A-like substance in plant foods, such as carrots, is beta-carotene and the conversion rate is: 1 IU beta-carotene = 0.05 mcg RAE, so the 20-fold difference between 835 mcg RAE and 16,706 IU now makes sense.

Why to complicate this?

Large amounts of vitamin A (retinol) can be toxic. The upper tolerable level (the amount that should cause no side effects and is not nearly toxic) for retinol for adults is 3,000 mcg RAE. For example, 100 g of chicken liver contains 4,296 RAE of retinol. (You can also see that for the liver, 4296 RAE/14378 IU = 0.3, so this explains again that the two rows are the same thing.)

You can see that the same IU of vitamin A in animal foods is translated into much more RAE than in plant foods. This is also why high IU of vitamin A in animal foods can be (potentially) much more toxic that the same IU of plant foods.


Hodgin-Huxley model for a single neuron I am viewing (through edX ) an introduction course to computational neuroscience. In the second lecture, the Hodgin-Huxley model is considered. I am going over some of the questions and have encountered a problem with one of them (a picture of the exercise is attached below). I have a strong background in mathematics, but my background in biology is yet very poor. I am having a hard time connecting the biology to the math. Can anyone help with this question:

Thank you!!

Since you didn't get the right answer to #6, let's review the basis for this model.

The basis of the model is precisely the statement in #6: an individual channel has a defined conductance when it is conducting, and if all of them are conducting then the total conductance is the single-channel conductance times the number of channels (conductances in parallel add).

Confusion comes from the fact that, in the terminology used here, an "open" channel is not necessarily conducting. The probability that a single channel is conducting is the product $r^{n_1}s^{n_2}$.

$r^{n_1}$ describes the "activation" process, while $s^{n_2}$ describes the "inactivation" process. These are two separate processes, with the activation process now known to be driven by voltage-dependent changes in the configuration of transmembrane domains of the channel protein, while the inactivation process is a charged part of the protein inside the cell that more slowly moves to block the channel when the cell is depolarized. See this summary by Clay Armstrong, who contributed much to our understanding of these processes.

So in the terminology here, a channel can be "open" (in terms of the $r$ process) but still "inactivated" (through the $s$ process) and thus be non-conducting. It can also be "closed" (in terms of the $r$ process) and "inactivated", in which case it is also non-conducting.

The way this is modeled is that $s=1$ means no inactivation, while $s=0$ means fully inactivated. So that covers question 3. This is in contrast to the activation process, in which $r=1$ is full activation.

Question 4 might be a bit misleading as there may be a hidden assumption that you are starting from being at potential $u_0$ for a long-enough time and then increasing $u$ suddenly (which is how action potentials normally are generated). In that case your understanding of differential equations should make it clear that $\tau_r$ and $\tau_s$ are the time constants for the responses of the $r$ and $s$ processes to a change in $u$. The process with a shorter time constant responds more quickly, so activation precedes inactivation (on the average). The different powers associated with the $r$ and $s$ processes ($n_1,n_2$) might confuse things a bit, but try running this model and you should be convinced.

This might seem convoluted at first, but Hodgkin and Huxley worked out this model based solely on their electophysiological studies (with help from Bernard Katz). It's amazing how this model's postulates of multiple single channels and separate activation and inactivation processes have been so well verified at the molecular level over the past decades.


Difference between viral and native RNA I am a data scientist with really next to no training in microbiology.  I hope you'll all forgive my ignorance to entertain these questions.  The attention COVID-19 has gotten recently got me thinking:  What is the fundamental difference between viral RNA and the RNA native to a particular cell?

What I mean is, we are often told in school that viruses hijack the cell's protein manufacturing facilities to express their own genetic material.  The cell produces so much of the viral protein that it eventually lyses (for example).  But what is it that makes the cell produce so much of the viral proteins?  How does the cell not produce too many proteins from the cell's own DNA?

I suspect the answer comes down to the lack of gene regulation for the viral RNA.  But is every gene that is native to the cell really subject to some sort of regulation?  If so, is the real danger of viruses that they lack any kind of regulation?  Then that seems to be a fairly easy thing to detect- at least theoretically.  In other words, a cell, or a scientist could label a sequence of RNA as dangerous simply because it is unregulated, regardless of whether it came from a virus.

A second question is, we are told that the viral proteins self-assemble and encapsulate copies of the viral RNA just by chance.  Doesn't this seem unlikely?  Are the virus's components really so ubiquitous in the cell that the virus will self-assemble including all its necessary components a significant portion of the time?  I suspect for this to happen, the virus's RNA would need to be copied many times so that it would be plentifully available.  Then it comes back to the same question as above.  Is viral RNA unique in that it gets copied indefinitely?

There is no fundamental difference between viral RNA and and native cellular RNA other than the sequence of RNA bases in them.  The sequence differences are not biochemically apparent in the RNA, only in the protein products produced from the RNAs.

Regulation of native RNA is done in a huge variety of ways (nothing in the cell is designed; everything is ad hoc, so any random happenstance can become established).  Native regulation is essential, otherwise runaway production will happen leading to cell death or to cancer.

Much, if not most, of the native regulation is done by regulating transcription of DNA into RNA. Once the RNA is in the cytosol, little further regulation is done, so viral RNA in the cytosol has the run of the cellular protein factory.  But at least some viruses have acquired further advantages which help their RNA out-compete the native mRNAs for use of the protein machinery (see, e.g., Hijacking the translation apparatus by RNA viruses)

So it is not really an easy thing to "label a sequence of RNA as dangerous simply because it is unregulated" as the wide range of normal RNAs in the cytosol does not provide a basis for determining if any are "unregulated" and the cell cannot be protected in that manner.

Self-assembly is widespread in normal cellular functions as well as in viral production.  The molecules involved have long-honed attractive points for their mate molecules, and in the jiggling molecular soup of the cell the molecules can soon bump into each other and join up.  Thanks to the virus's uncontrolled production, new viral particles have plenty of component molecules available for this assembly.


Specifics of decussation Beginner question here:

The definition of decussation I see is the crossing through the midline of a bunch of neurons.  But I was wondering if there was a little more to it than this, because I'm given the impression in readings that this is a somewhat difficult task to perform developmentally, like the body might have to take extra effort to regulate the crossing so that the neurons do not interfere.  So when nerves from both eyes cross, for example, do they pass AROUND each other or do the bundles of nerves all weave through each other?

Thanks in advance.

The optic nerve fibers cross inside the optic chiasm sharing the same shell:

The crossing fibers go ones between others, like on this classical picture -


What happens to the food you accidentally aspire? I'm well aware of the health effects of aspirating solid food and liquids, but I'm interested in the reaction of the body on the biological level to the strange body on our lungs.

After I almost aspirated corn, I started to wander: what does the body do when food got on our lungs?

Will it be eventually absorbed? Destroyed by our white cells? Or just lie there forever until it fully decomposes?

The body has mechanisms to prevent food to get into the lungs, so the body is aware that eventually some food will get into the lungs. As a result, it makes sense to believe that our body would have a mechanism to deal with such issue if all other mechanisms fail ( coughing and etc.,) yet I couldn't find anything on Google.

People can drown because of aspired food. If they don't then it can cause diseases, for example pneumonia. In extreme cases a tree can grow in the lungs. There are other aspiration/inhalation related diseases like silicosis or asbestos lung cancer. So it depends on the composition of the object (or liquid or powder) and other factors whether it causes a disease or not. I did not find anything about what exactly happens with these objects in the lungs. Probably the lung tries to get rid of them mechanically, if there is no success in that, then they cause a local inflammation, which can lead to diseases if it becomes chronic and/or the object contains pathogens.

  Common presenting symptoms (information available in 36 cases)
  included dyspnea (14), fever (9), and cough (6). A history of
  recurrent pneumonia was present in 9.

2007 - Pulmonary Disease due to Aspiration of Food and Other Particulate Matter: A Clinicopathologic Study of 59 Cases Diagnosed on Biopsy or Resection Specimens

  The annual overall inpatient cost associated with pediatric bronchial
  foreign-body aspiration is approximately $12.8 million. Combined, the
  rate of death or anoxic brain injury associated with pediatric foreign
  body is approximately 4%.

2014 - The national cost burden of bronchial foreign body aspiration in children

  Gastric aspiration is a high-risk condition for lung injury.
  Consequences range from subclinical pneumonitis to respiratory
  failure, with fibrosis development in some patients. Little is known
  about how the lung repairs aspiration-induced injury.

2015 -Resolution of Lung Injury after a Single Event of Aspiration : A Model of Bilateral Instillation of Whole Gastric Fluid

  Aspiration is a common but underrecognized clinicopathologic entity,
  with varied radiographic manifestations. Aspiration represents a
  spectrum of diseases, including diffuse aspiration bronchiolitis,
  aspiration pneumonitis, airway obstruction by foreign body, exogenous
  lipoid pneumonia, interstitial fibrosis, and aspiration pneumonia with
  or without lung abscess formation. Many patients who aspirate do not
  present with disease, suggesting that pathophysiology is related to a
  variety of factors, including decreased levels of consciousness,
  dysphagia, impaired mucociliary clearance, composition of aspirate,
  and impaired host defenses.

2014 - Aspiration-Related Lung Diseases
2012 - Aspiration and Infection in the Elderly
2015 - Pediatric foreign body aspiration: A nidus for Aspergillus colonization
2012 - All that wheezes is not asthma: a 6-year-old with foreign body aspiration and no suggestive history


What are typical values for bone mass in humans? I wonder what are typical bone mass values for adult males and females? And do they change significantly with workout and diet?

I wonder what are typical bone mass values for adult males and females?

This seems hard to find. The only value I could find is on Bionumbers at it says that vertebrates compact bones have a mean density of 2 mg/cm$^3$ [1]. However in medical practice two scores are used to indicate the ratio between tested bone density and ideal bone density [2, 3] and absolute values are uncommon.

  And do they change significantly with workout and diet?

Bone mass is mainly influenced by genetic factors. Only up to 25 % may be influenced by environmental factors such as diet and exercise [4].

Among the medical conditions that influence bone mass, osteoporosis is the most frequent especially in women. Other conditions are: hyperparathyroidism, glucocorticoid therapy, other bone abnormalities and fractures [2].

References:

Brian Cotterell, Fracture and Life, Imperial College Press, 2010 p.77 bottom paragraph via http://bionumbers.hms.harvard.edu//bionumber.aspx?id=108642&ver=2
Bone density. (2014, September 15). In Wikipedia, The Free Encyclopedia. Retrieved 17:08, September 29, 2014, from http://en.wikipedia.org/w/index.php?title=Bone_density&oldid=625737182
http://www.niams.nih.gov/Health_Info/Bone/Bone_Health/bone_mass_measure.asp
http://www.niams.nih.gov/Health_Info/Bone/Osteoporosis/bone_mass.asp


Insect identification request - Is this a bed bug? I live in Spain and today I found several of these in my son's jacket. I am afraid they are bed bugs nymphs because last year we had a bedbug epidemic in some neighborhood houses.

The insect in the photo is about 1mm and has green spots in his body. Maybe they are just aphids that have been brought from the park.

I got curious and after some image search I got two candidates:

Plagiognathus repetitus

Mullein Bug


Why can a gene lack of a binding site be expressed in skin cells? In order for a specific gene to be expressed in the mammal’s cells, all of the gene’s binding sites must be bound by transcriptional activators. The mammal’s skin cells contain activators that bind to sites B, D, and E, while the mammal’s liver cells contain activators that bind to sites A, C, and E. (From Khan academy)

Why can both Gene 2 and Gene 4 be expressed in skin cells? I think Gene 4 can't since it doesn't have site E.

You understand this wrong: All present enhancers of a gene must be bound by a enhancing factor, not all factors of a certain cell types have to be bound. So when skin cells contain activators for B, D and E they can activate gene 2 and 4 of your example, but not gene 3 since the activators for A and C are missing.
So when you have a gene containing any combination of B, D and E, its activation in skin cells is possible according to this model. The same is true for any combination of A, C and E for liver cells. The special case would be a gene having E as the only enhancer as this could be activated in both, liver and skin cells.


Is differential equation modelling in molecular genetics useful? I graduated last year with a degree in Applied Mathematics and just this month I started a PhD in molecular genetics. I was accepted into a program specifically for individuals with a quantitative background, though the differences between my program and the general graduate program seems fairly minimal.

The department is fantastic and I'm enjoying learning the experimentation, but I haven't had the opportunity yet to use my actual skills.

The more talks I attend, the more I realize that much of the "computational" side of molecular genetics seems to be split between machine learning, bioinformatics and statistics or some combination of the three. In my undergrad I studied topics such as differential equations (partial and ordinary, extensively), dynamical systems, vector calculus (though I never took any fluids courses, I was more of a systems guy), computational mathematics, control theory and some computer science (about 5 courses).

I've talked to a few of the faculty so far and when I mention the possibility of differential equation modeling, they don't seem comfortable giving me guidance. In addition, I read a review paper today that seems to suggest this kind of modeling is fairly uncommon.

So, my questions are these: Are differential equation models useful to geneticists and biologists? Why are they not done more often? How difficult would it be to create my own project that involves differential equation modeling coupled with experimental parameter finding and model verification?

Nobody seems to be able to give me an answer, so I hope the Stack Exchange community has some insight.

Thanks in advance!

Are differential equation models useful to geneticists and biologists?

Well yeah, of course they are. Look up Alan Turing and "The chemical basis of morphogenesis", or look up "differential equations and gene regulatory networks" But folks have to specialize, and not every department studies every aspect of a field. You may just have ended up in a department where nobody is studying an aspect of genetics that can be well modeled by differential equations. At lot of molecular genetics is still figuring out the coarse grained phenomenology of the genome, like "How does a cell figure out which copy of the X chromosome gets condensed into a Barr body?" A lot of these problems involve picking out subtle signals from noisy data, thus the interest in statistics and machine learning.

If diff. eqns. are the passion of your life, you might have to look 'next door', to departments studying biochemistry and population genetics, both of which do huge amounts of modeling using differential equations. There are also applications of differential equations to molecular genetic methods like QPCR and next generation sequencing, but you'll either have to sell your mentor on the topic, or move to a different department.

On the other hand, if it's just a matter of diff. eq. being your undergrad emphasis, you may want to find a biological problem that interests you, branch out beyond diff. eq., and use your general mathematical maturity to pick up the relevant mathematical tools: say statistics, optimization, or dynamic programming.


Can acid-fast M. tubercolosis obstruct alveoli? I am not sure which word is the best here for colonisation of alveoli by acid fast-mycobacteria. I found this question, and I am getting confused by the term obstruction of alveoli because I tend to relate it to COPD which is not a case here:

Which of the following is the predominant pathogenic mechanism of tuberculosis?

a) cell-mediated hypersensitivity
b) obstruction of alveoli by large number of acid-fast mycobacteria

I think the right answer is "obstruction of alveoli by large number of acid-fast mycobacteria", but I am not sure if you can say that acid-fast mycobacteria obstruct alveoli.

Are acid-fast mycobacteria "obstructing" alveoli or just colonizing?

Mycobacteria are on the order of 2µm in length and 0.2µm in diameter.  Alveoli are on the order of 200µm in diameter.  Obstruction is possible, but M. tuberculosis grows rather slowly.  Too slowly, in fact, to avoid being engulfed by alveolar macrophages.

Furthermore, obstruction does not sufficiently explain the predominant symptoms of tuberculosis:  bloody sputum and the tubercles themselves.


Molting in arthropods Do all the arthropods molt ? Which ones do not molt ? Why don't they need to molt ?

I tried googling this - but did not get satisfactory answers.

in my opinion all arthropods molt. In fact arthropods are a part of clade called ecdysozoa, the members of which undergo ecdysis (molting).

Molting is necessary because arthropods have an exoskeleton which has to be removed if the organism has to grow.


Population Growth Rate Question? A population of 600 birds faced a problem of biological magnification resulting in a large number of deaths reducing their population to 350. But 230 births also took place and 21 birds immigrated into the population while 13 birds migrated out. How many deaths took place in the population? What is the growth rate of this small population?

So I guess we need to use the
PGR = (BIRTHS + IMMIGRATION) - (DEATH + EMIGRATION) / INITIAL POPULATION x 100%

So.. I keep getting -2% as my answer, but apparently the correct answer is -41.7%

Thanks!

As you have phrased it, the question can be understood in two ways.

The population size at t+1 is 350, after births, deaths and migration have taken place.
The population size is 350 after deaths, but you also have to take births and migration into account to calculate population size at t+1

For alternative 1 the growth rate is:

$pgr = \frac{(230+21)-(488+13)}{600} = -0.417$,

with $\Delta N=-250 \Rightarrow -250 = 230+21-deaths-13$

For alternative 2 the growth rate is:

$pgr = \frac{(230+21)-(250+13)}{600} = -0.02$


How can I make sure my UV-purificator kills bacteria? I'm going to show a UV-purificator for water on science fair. How can I easily check if purificator kills most of the bacteria? I need a quick and possibly easy method.

Not having the equipment needed to actually count bacteria, you can use things you know bacteria does to find out how much they were affected.

My approach would be thus:

Select a model bacteria. There are a few candidates, but probably the most readily available is lactobacilli, which can be found in yogurt and (loosely translating terms of art) is a Gram-stainable fermentor-sometimes-breather.
Infect the water with a known quantity of bacteria and a food source (lactobacilli eat lactose - ie from milk) and equally divide it into a control and experimental group...
You'll need to find an alternative way to estimate the bacterial content in the volume of water used compared to a control colony. Since lactobacilli produce lactic acid, you could use the pH value of the water (either with an indicator or a meter) to detect bacterial metabolism, compare that to the control's pH value.
Record the UV exposure time from the experimental group, and isolate the control group from any potential UV light source, such as the sun.

Even if you find that, for example, your particular strain of lactobacilli is not sensitive to your UV light source, that's a perfectly scientific result! How did you obtain it? The source likely knows what kind of bacteria it is. Perhaps the UV light merely interferes with bacterial metabolism, and doesn't kill it. Unanswered questions are wonderful, you may have provided a place for further research to take place. You could then use the two groups to infect a food source (ie milk) and compare post-exposure growth, depending on how much time is available.


Basic Modelling in Quantitative Genetics I am pretty bad in thinking quantitative genetics models. I am trying to get some basic understanding of modelling the evolution of a quantitative trait. I am therefore asking for help to analyze a very simple model. I welcome any explanation of some other classic model of the evolution of quantitative traits.

Scenario

Consider a haploid population of constant size $N$. The fitness of the individuals is determined exclusively by a single quantitative trait $z$. $l$ loci codes for this trait. The genetic value at each locus adds up to give the quantitative trait $z$. The mutation rate at each locus is $\mu$. A mutation changes the genetic value at any given locus by $+ \Delta z$ with probability $\frac{1}{2}$ and by $- \Delta z$ with probability $\frac{1}{2}$. If you prefer to consider the effects of a mutation to be drawn from a normal distribution with mean $=0$ and variance $= \sigma^2$, please feel free to do so. The fitness $w(z)$ of an individual is given as a gaussian function of its quantitative trait $z$

$$w(z)=\exp\bigl(-Vz^2\bigr),$$

where $V$ is the strength of selection. The optimal phenotype is $0$, that is $w(0)=1$. The larger is $V$, the more severe it is to be at a given distance to the optimal phenotype. If you want to assume that the fitness $w(z)$ is some other function of the trait $z$, such as the even more simple $w(z)=z$, please feel free to do so. For simplicity, we assume no environmental variance on the quantitative trait.

Questions

What is the equilibrium mean fitness $\bar w$ of the population?

What is the equilibrium genetic variance (=phenotypic variance) for fitness $w$ and for phenotype $z$?

Trait z is represented by k genes: z1....zk (I am using k instead of l because the former is visually differentiable from 1 ).
For simplicity let's assume that there is only one mutable site in a gene. So a mutation can impart a change of $\pm \Delta z$. Starting from initial state of z at zero, the system will proceed to equilibrium where the rate of forward mutation would be same as that of backward mutation; since the rates are same the deterministic steady state of z should be zero.

A mutation event can also be considered a binomially distributed RV. After n events, the mean number of forward mutations would be 0.5×n.   Mean fitness = mean forward mutation — mean backward mutations = 0

You can also model the mutation events as a simple random walk. The mean of that is 0 and the variance is n. But what about large n; I am not sure. You should read about random walks or ask in CrossValidated. With $t\to \infty$, you would get a lot of variants but variants would be filtered out by selection (as the optimum is at 0). I think selection can be incorporated in the random walk with death rate being proportional to the distance from 0. But again I do not have much experience with such hybrid models.

I tried a simulation with n=10000000 (using Monte Carlo); different colours denote different runs (or in another words different loci). Y-axis denotes the value of z.


What is the life cycle of a wart? There doesn't seem to be a lot of information available on research done on warts.  What is the life cycle of a wart?  How does it spread? -- specifically how does it recruit cells to spread it?  What is the life cycle of a PV-infected dermal cell?

This article has some good information. It's certainly more than I want to know about warts.

  Isolated warts may remain unaltered for
  months or years, or a large number of new lesions
  may develop rapidly in a short period of time. The
  development of warts is not predictable.
  Approximately 65% of warts disappear spontaneously
  within two years. The patient’s age and number of
  lesions do not seem to affect the prognosis.

There are many different types of warts and of HPV. Since warts cause a type of dysplasia their life cycle can be very variable and unpredictable.


What is the conversion between r and FST? From Schonman (2013):

...allele A can only invade under Hamilton’s condition  R=$F_{ST}$ > C/B.

From Harpending (2002):

The best general definition of the coefficient of relation $R_{XY}$ between individuals X and Y is (Bulmer, 1994) $R_{XY}$ = $F_{XY}$/$F_{XX}$, where $F_{XY}$ is the kinship between X and Y and $F_{XX}$ is the kinship of X with himself [..]
[..] $F_{ST}$ is just the coefficient of kinship between members of the same deme [..]
[..] $F_{Self} = \frac{(1 + F_{ST})}{2}$  [..]

This means, unless I am mistaken, that if I take Harpending's equation and substitute $F_{ST}$ for $F_{XY}$ and substitute 1/2(1+$F_{ST}$) for $F_{XX}$, I can calculate within-deme relatedness: 2*$F_{ST}$/(1+$F_{ST}$).
Yet Schonman says R=$F_{ST}$?
What am I doing wrong here?

I am very unsure but here are my thoughts...

We can work out from

$$R_{XY} = F_{XY}/F_{XX}$$

I do not really understand the concept of coefficient of kinship and the concept of coefficient of kinship with oneself but you say

  According to the paper, kinship with himself is 0.5 in a sexual population

So, let's assume

$$R_{XY} = 2F_{XY}$$

Let's assume that the individual Y is drawn from anywhere in the total population. Again, I don't really understand the concept of coefficient of kinship but let's assume that $F_{XY}$ is the same as the probability of identity by descent between these two individuals, then in Nei (1973) terms, $F_{XY} = J_T = 1 - H_T$. Hence, $R_{XY} = 2\left(1 - H_T\right)$ or $H_T = 1-\frac{R_{XY}}{2}$

Given that

$$F_{ST} = 1 - \frac{H_S}{H_T}$$

it results that

$$H_T = \frac{H_S}{1-F_{ST}}$$

and therefore,

$$1-\frac{R_{XY}}{2} = \frac{H_S}{1-F_{ST}}$$

solving into

$$R_{XY} = \frac{ 1 - \frac{H_S}{1-F_{ST}}  }{2} = \frac{1-F_{ST} - H_T}{2(1-F_{ST})}$$

I would recommend you making some more reading on the coefficient of kinship to ensure that my interpretation here is correct.


What causes Pseudomonas fragi to smell sweet? I am working with Pseudomonas fragi and I could not help but notice that it smells sweet, which probably explains its species name 'fragi' from 'fragum', strawberry in Latin.

Does anybody know what causes this bacterium to smell sweet? It must be some volatile compound that they release in the air? Why would they do that? Do other bacteria release odorant molecules? If so, why?

The strawberry-like odour that you perceived is mainly attributed to three ethyl esters, namely the ethyl esters of butyric, hexanoic and 3-methylbutanoic acid.

There are other odour-active volatiles produced by Pseudomonas fragi, about 26, which are said to add to the richness and complexity of the odour of the three aforementioned main compounds.

Source:

Analysis of odor-active volatiles from Pseudomonas fragi grown in milk - Cormier et al. 1991

The study by Cormier et al. should be a good starting point for further reading as it references a variety of scientists who have worked on this.


How to learn DNA Origami Can you tell me is there any good softwares and tutorials which can be used to learn DNA Origami. I am new to this and want to learn from basics.

Advance thanks for your help

edited: INSILICO

Try this.

  cadnano simplifies and enhances the process of designing three-dimensional DNA origami nanostructures. Through its user-friendly 2D and 3D interfaces it accelerates the creation of arbitrary designs. The embedded rules within cadnano paired with the finite element analysis performed by cando, provide relative certainty of the stability of the structures.


Fetal development, gastrulation and embryonic disc I am completely confused by the images circulating on the internet of human gastrulation.

First, lets see how it happens in deuterostomes. This image depicts the process:

(image is from Wikipedia)

From here we can conclude that blastula becomes gastrula when some of the ectoderm beecomes endoderm, the place where it goes inside becomes anus and then mesoderm is formed.

Ectoderm here is the outermost level and gastrula already has anus.

However, in this image of human gastrulatuion we see completely different things:

(image source)

The mesoderm here is the outermost layer, ectoderm is inside and the gut cavity is formed by the separation of a part of the yolk sac. There is no anus and the posterior end of the gut is blind. Also other similar images suggest that a twins may be separated already after the mesoderm was formed (thus uniplacental twins).

The lack of agreement between the images disturbs me.

Just to point out some of the differences in the depicted processes:

In first image mesoderm forms after gastrulation, on the second it forms far before gastrulation
In the first image anus forms in the process of gastrulation, in the second image anus remains blind
In the first image ectoderm is the outermost layer, while in the second picture mesodem is the outermost level that encloses all, including ectoderm.

Human embryogenesis is much more complicated than the more general and simplified picture given in your 1st figure.
For details, please study http://en.wikipedia.org/wiki/Human_embryogenesis

To point out the most distinctive features which might have led to your confusion:

Before gastrulation, the blastocyst cavity is formed.
Only the inner cell mass undergoes gastrulation.
Mesoderm forms quiet late and spreads, thereby also forming the chorion as well as the amnion.
The embryo itself is formed from a subset of all embryogenetic cells. This is shown in your 2nd figure, part C and D. Yet, tissues are still going to spread such that the final ectoderm as well as mouth and anus will be formed.