SNPs are much denser than RFLPs and VNTRs therefore the DNA resolution is much greater with SNPs. VNTRs were historically used for linkage mapping while SNPs allowed for association studies (e.g. GWA studies). Therefore your question goes down to what are the differences between linkage mapping and association studies.

They are both forward genetic methods which aim to identify a genetic modification provoking a trait.

The two major differences between both approaches are 1) linkage mapping requires a pedigree but can be performed using a fairly small sample size while 2) association studies can be performed at the population level but usually require a much larger sample size.

Both approaches require markers but for different reasons. For linkage mapping, markers, such as microsatellites, are used to delimit the genomic region associated with the trait and take advantage of recombination events in the genome to pin down that region. This, of course, requires both 1) recombinant individuals in the pedigree and 2) at least one marker that is co-inherited with the trait. Linkage mapping allows to find virtually any genetic modifications, such as a genomic deletion, but only in the case of a genetic modification showing high penetrance.

For association studies, markers are the actual genomic modification themselves (usually SNPs) and are used directly in statistical tests (often a logistic or linear regression) for association with the trait. This means that either 1) the causal marker is available or 2) at least one marker is highly co-inherited with the causal mutation (i.e. in linkage disequilibrium). Association studies allows to find both low- or high-penetrance mutations, given a sufficiently big sample size. Also an association study can be conducted in the presence of a non-discrete (i.e. linear) phenotype which one cannot use in linkage mapping.

Another difference is that linkage mapping does not require any a priori knowledge of the genomic modification causing the trait while association studies do (as markers are statistically associated with the phenotype).

Usually both methods will highlight, with varying resolution based on the phenotype and markers used, the genomic region causing a trait but rarely the actual causal mutation will be found with 100% certainty.


Which hormones can cross the blood brain barrier?

Yes, both steroid and peptidic hormones can enter the brain, the obvious proof being that the brain responds to changing blood concentration of hormones.

The situation is different for steroid hormones (such as estrogen, testosterone, cortisol etc) which are small and lipophilic, and peptidic hormones (such as insulin, ghrelin, prolactin etc) which are big and hydrophilic.

The blood-brain barrier (BBB) is selectively permeable to steroid hormones: some of them (such as the gonadal steroids) can readily pass the BBB, while others (such as corticosteroids) pass only in small concentrations. This may however be modulated by hormone carrier proteins in the plasma.

See: Transport of Steroid Hormones through the Rat Blood-Brain Barrier - Pardridge et al., JCI, 1979

When speaking of peptidic hormones, the classic hypothesis is that hormones pass through the areas where the BBB is "leaky", i.e. where capillaries are fenestrated.
These include circumventricular organs such as the median eminence (where the terminals of many neuroendocrine neurons are located), or the organum vasculosum of the lamina terminalis (OVLT), important for reproduction and osmoregulation. The chorioid plexus is also often mentioned as a site for hormone entrance and/or sensing.

However, how exactly hormones enter the brain is still very unclear.
Our lab published a paper on this topic recently:
Rapid sensing of circulating ghrelin by hypothalamic appetite-modifying neurons - Schaeffer et al., PNAS, 2013


It means that these enzymes need a metal ion as a co-factor for their function. This metal ion is typically bound somewhere near or in the active center and helps stabilizing transition states.

Without these metals, these enzymes cannot function properly, that's why chelating agents are used in protein or DNA preparations to inhibit their function.

References

Information available at cut rates: structure and mechanism of
ribonucleases.
The Role of Metals in Enzyme Activity


Pattern recognition receptors (PRRs) can potentially discriminate between endogenous and exogenous DNA:

  Microbial nucleic acids can be discriminated from self nucleic acids using various parameters, such as their sequence, their tertiary structure, their molecular modifications and their localization. In addition, mislocalized DNA and RNA can be an indicator of cellular damage and infection. [1]

and

  Microbial nucleic acids are discriminated from self nucleic acids based on different parameters, such as their sequence, structure, molecular modifications and localization. On the other hand, mislocalized self nucleic acids — such as extranuclear DNA or extracellular RNA — can be recognized as DAMPs, probably because they are reliable indicators of cellular damage. [2]

Somewhat suspect is the similarity of those quotes; I only link to both reviews so as to include both in the references for further reading.

Distinguishing by sequence and structure are self-explanatory. Molecular modifications could include unmethylated CpG sites which are more common in bacterial and viral genomes and are recognized by TLR9. [3] Mislocalized DNA means any that is found outside the nucleus, which is a sign of damage or infection. Most of the well-studied nucleic-acid-recognizing PRRs are found outside the nucleus: TLRs are constrained to endosomes and the extracellular environment while RLRs are found in the cytoplasm. The as of yet identified DNA sensors like DAI also seem to localize to the cytoplasm. Extranuclear PRRs do not necessarily need to discriminate between endogenous and exogenous DNA: any that they sense is mislocalized. However, at least one dsDNA-recognizing PRR, IFI16, localizes to the nucleus as well as the cytoplasm, where it can recognize viral dsDNA. [4]

  It has been assumed that cells distinguish viral from cellular DNA due to the former's presence in the cytosol. However, … Kerur et al. (2011) propose that the DNA genome of Kaposi's sarcoma-associated herpesvirus (KSHV) is recognized inside the nucleus by the DNA sensor IFI16, leading [to] inflammasome activation. [5]

IFI16 apparently distinguishes exogenous from endogenous DNA by its length. [6]

Endogenous DNA is present in vivo as chromatin and the amount of exposed linker DNA between histones is too short to promote the cooperative binding and oligomerization that IFI16 requires for signalling (B). An older model, where IFI16 binds independently, is also shown (A), but it suggests that IFI16 should bind self-DNA and doesn't fit with experimental results.

That is just one specific example of how a PRR can distinguish self from non-self. DNA sensors actually seem to be on the cutting edge of research into the innate immune system and, as such, the complete picture has yet to be determined.

References:

Broz P, Monack DM. 2013. Newly described pattern recognition receptors team up against intracellular pathogens. Nat Rev Immunol 13(8):551-565.
Desmet CJ, Ishii KJ. 2012. Nucleic acid sensing at the interface between innate and adaptive immunity in vaccination. Nat Rev Immunol 12(7):479-491.
Yoneyama M, Fujita T. 2010. Recognition of viral nucleic acids in innate immunity. Rev Med Virol 20(1):4-22.
Kerur N, Veettil MV, Sharma-Walia N, Bottero V, Sadagopan S, Otageri P, Chandran B. 2011. IFI16 Acts as a Nuclear Pathogen Sensor to Induce the Inflammasome in Response to Kaposi Sarcoma-Associated Herpesvirus Infection. Cell Host Microbe 9(5):363-375.
Unterholzner L, Bowie AG. 2011. Innate DNA Sensing Moves to the Nucleus (comment on Kerur et al., 2011). Cell Host Microbe 9(5):351-353.
Morrone SR, Wang T, Constantoulakis LM, Hooy RM, Delannoy MJ, Sohn J. 2014. Cooperative assembly of IFI16 filaments on dsDNA provides insights into host defense strategy. PNAS 111(1):62-67.


Why can't we observe haplotypes directly?

The difficulty of reading haplotypes 'directly' lies in the difficulty of reading any long sequence of DNA, and this is for technical reasons.

Short DNA fragments are sequenced using a variety of methods. Gel electrophoresis can pull these fragments apart by length, but all the fragments have to be relatively close in size to get the accuracy needed to tell fragments that differ by one base pair apart. It's easy to separate a 16-bp segment from a 17bp segment easily, but it's much harder with a 516bp segment and a 517bp segment. Modern sequencing can sequence reads up to about 5kbp in length at a time. The 'reads' are then reassembled.

There are next-generation methods(pyrosequencing, etc) that can read a long dna molecule one base at a time, but for practical reasons sequencing an entire chromosome this way is cost and time prohibitive. As a result, there are always going to be fragments that you need to reassemble computationally, no matter how the sequencing is done.


Is forced cell growth related to apoptosis?

It is trivial to assume that forced growth will overcome apoptosis which is what you see in the immortalized cell lines and in cancer.

But the interesting thing is that there are instances in which forced growth causes apoptosis. The classic example is of the brain in which expression of SV40 t-antigen to make cells proliferative actually caused loss of tissue [1,2].

Knockdown of Aif (apoptosis inducing factor) also causes neurodegeneration and thymic hypoplasia by causing increase in oxidative damage.


Why do the ancestors of birds still exist?

Introduction to phylogeny
Short Intro to Speciation
Let's talk about speciation. Speciation is the process by which a single lineage split into two. This happens in a number of ways (allopatric vs sympatric vs parapatric, BDM model and others). I will consider a simple case of allopatric speciation below as it is the simplest one to understand (although not necessarily the process causing most speciation events).
Following the story of a lineage through its speciation events
Think of a population at time $t=0$. Let's call this species A (for Ancestor). Imagine that an ecological change brings a barrier right in the middle of the range of this population of A. Such a barrier could be originally caused by a fire, or a river that has changed direction or a mountain range "popping up". The two now isolated populations are free to diverge randomly through time. This is what we call a speciation event. Note that under this model, there is no necessary need for selection to explain speciation. Let's call the two diverging population B and C which exist at time $t=1$.
Now, imagine C goes under another speciation event and split into the populations D and E. In the same time, population B may have changed quite a bit so that we might want to call them F. Here is a diagram of the situation
  F           D ----- E     t=2
  |               |
  B ------------- C         t=1
          |
          A                 t=0

A is an ancestor of B,C,D,E and F and does not exist today. B is an ancestor of F but does not exist today. C is an ancestor to both D and E and does not exist today. Let some more time pass by and you may eventually end up with the following tree
  G ----- H       K   I ----- J t=3
      |           |       |
      F           D ----- E     t=2
      |               |
      B ------------- C         t=1
              |
              A                 t=0

At time $t=3$, only species G, H, I, K and J exist today, the other are ancestors of current species. Let's expand this tree even further.
  L ----- M   N       O       P ----- Q      t=4
      |       |       |           |
      G ----- H       K   I ----- J          t=3
          |           |       |
          F           D ----- E              t=2
          |               |
          B ------------- C                  t=1
                  |
                  A                          t=0

You will note that lineage I went extinct at some point between $t=3$ and $t=4$.
Naming subsets of the tree
Reptilia
I am now suggesting to give a generic name for all the lineages present in the tree we drew (which we call a phylogenetic tree by the way). Let's call them Reptilia. So all the species A,B,C,D,E,F,J,I,J,K,L,M,N,O,P and Q are Reptilia.
Birds and Mammals
Now let's consider a subset of this tree. Let's consider the subset made of the species J, P and Q only. Let's call them birds. Let's also call mammals the subset composed by the species G,L and M.
Lizards (and others)
Finally let's call lizards all reptilia that are not birds, nor mammals (in reality it would be more correct to call this group lizard_crocodile_turtles_snake_amphibians_tuatura). Of course, the right tree is much bigger! By the way, you can explore the tree of life yourself on OneZoom.org.
What is a taxon
By the way, a group of species is called a taxon (plur. taxa).
Monophyletic taxa
It might be straight forward to you that there is something fundamentally different between the groups that we called mammals, birds and reptilia to the one that we called lizards. Indeed mammals, birds and reptilia are called monophyletic as they are composed of a given ancestor and all its descendants. lizard on the other way is not monophyletic. A monophyletic taxon is also called a clade. Below is a graph representing what a monophyletic taxon is. It also uses the terms polyphyletic and paraphyletic to describe different types of non-monophyletic taxa

Concept of species
You might want to learn more about the issues behind the concept of species in the post How could humans have interbred with Neanderthals if we're a different species?
Concept of taxonomic ranks
What we decide to call a class, an order or a family is also somewhat arbitrary too. For example, we generally consider the monophyletic taxon Mammalia is a class. However, there is no non-arbitrary reason for calling Mammalia a class rather than Eutheria (eutheria = placental mammal).

Online resources
I suppose the above answered a big part of your question. You will be able to read all of what I just wrote (and much more) on any good introductory course to evolutionary biology. Consider having a quick look at Understanding Evolution by UC Berkeley for example as @MattDMo suggested in the comments.
Issues in your post
There are issues in your post that cannot be addressed in a single post (another reason for you to follow a quick intro course to evolution). Below I consider your post piece by piece mainly to point to some issues

Scientists believe

Terrible statement. By belief, we often refer to a non-justified belief, that is a belief about the world that is not justified (in science, the method of justification is called "the scientific method"). The statement, therefore, suggests that non-justified beliefs have a place in science while they don't. By being a little lose on the semantic, one could say that scientists "know" or they don't know but they don't believe without good reasons to believe.

that birds are evolved from reptiles

This is misleading (and it mislead you) because by "reptile" you think of a lineage that currently exists. Also, the expression "are evolved from" sounds very wrong. The expression "has evolved from" would be more correct.

evolution occur so that the organism can survive in the environment by developing new characters

This is wrong both in terms of the semantic (issue of causality when saying so that) and in term of the definition of evolution. You seem to confound evolution with natural selection.

According to natural selection

Natural selection is a process, not an explanation. It is like saying "according to gravity". The semantic is wrong, you should say "according to the theory of gravity" or "according to the theory of evolution" (or eventually "according to the theory of natural selection").

According to natural selection, those with favourable variations will survive and those with unfavourable die

You seem to apply that statement to population-level fitness (which would be mainly wrong) rather than to fitness variance within a population.

Why do the ancestors of birds (that is, reptiles) still exist?

The ancestors of birds don't exist anymore. I hope that was made clear from the above explanations.

Why didn't they get eliminated by natural selection?

This sentence suggests that you do not really understand what natural selection is but this is a story for another time. You can learn about natural selection on Understanding Evolution by UC Berkeley.


What class of histone deacetylase (HDAC) inhibitor is sodium valproate (VPA)?

This is explained at the WP page for HDAC. There are five classes:

hydroxamic acids (or hydroxamates), such as trichostatin A
cyclic tetrapeptides (such as trapoxin B), and the depsipeptides
benzamides
electrophilic ketones
the aliphatic acid compounds such as phenylbutyrate and valproic acid

and valproate is in the final class, aliphatic acids.


Given the shape and the number of legs. That most definitely is not an insect. An insect has exactly 6 legs. No more, no less.
That critter in your picture is some kind of millipede (“a thousand feet”; not literally a thousand, of course; https://en.m.wikipedia.org/wiki/Millipede), not to be confused with a centipede (“a hundred feet”; also not literally a hundred).
Millepedes are mostly harmless to humans. They eat things like dead plant matter or fungi. They sometimes also eat seedlings so they can be considered pests in gardens.
And given the colour, that’s possibly a rusty millipede (https://en.m.wikipedia.org/wiki/Trigoniulus_corallinus). They have a very wide distribution around the Indo-Malayan region. Although there seems to be no recorded observation of it on iNaturalist around your region (https://www.inaturalist.org/observations?place_id=9248&taxon_id=123010).


How to perform a chromosomal walk

I believe that the first publication to describe this approach was Bender et al., Science, 1983.  In that paper they explain how they "walked" along the chromosome to reach the Bithorax Complex (BX-C).

This approach requires two reagents:

a cloned DNA fragment that you have mapped to a defined genetic interval, and possibly to a cytogenetic interval as well (this is only possible if the organism in question has cytogenetic tools).
a genomic library of larger cloned DNA fragments.

Step 1. Use the DNA fragment to screen the library and isolate genomic clones.

Step 2. Purify each genomic clone and prepare enough DNA to construct a restriction map of the foreign insert (N.B., Bender et al., actually used heteroduplex mapping--an EM-based technique--as well) in each clone.

Step 3. Isolate a suitable DNA fragment, devoid of repetitive DNA, from one end of the clone that extends the farthest along the genome in the direction in which you wish to "walk".

Step 4. Congratulations, you have taken one "step." Now use the new DNA fragment as a probe and screen the genomic library again.  Each time you screen the library you will recover all of the genomic clones that hybridize, or overlap, with the fragment you are using as a probe.

Step 5. --> go back to Step 2. above.

Each time you take another "step" you are isolating cloned DNA that is taking you closer to your target (the gene of interest).  For the very first step you will not know which clone is extending in the desired direction (typically) so you need some type of complementary assay to decide which end of the overlapping clones' restriction map is the direction you want to pursue. In other words, you need to align the physical map to the genetic map. In Drosophila one can use  in situ hybridization to polytene chromosome squashes to visualize where the genomic clones are derived from in the genome, and this lets you pick the correct clone at that first step.

Periodically during the walk you will need to test the new genomic clones by in situ to find out when you are getting close to your target (or if you have even walked past your destination).

Ideally you will have some chromosomal rearrangements that alter the physical and genetic maps, and let you unambiguously determine when the chromosomal walk has reached, or entered, the locus.  Alternatively, a strong loss-of-function mutation in your target gene might be a deletion or deficiency that causes a RFLP, and isolating genomic DNA from such a mutant will let you use a Southern Blot to confirm that you have reached the gene.


What would be the difference if I use the Web server instead of dedicated server for protein modeling and docking?

There should be no difference in output.*** The big difference is likely going to be in the size of the analysis you can perform, and how fast the analysis is performed. A lot of web-servers have a job size limit to prevent one person from hogging resources unless you buy greater access. On a public web-server, your job is queued with everyone else's. If the server is in high demand, you may have to wait along time for your analysis to kick off.

***: I said there should be no difference in output and that is true if you set up your server the same as the public webserver with the same parameters used for analysis execution. This could be a good or bad thing depending on what you are trying to accomplish. Some public webservices do not give you access to all parameters, so setting up your own may give you the ability to tune your analysis to a greater degree.


Is it necessary for spiders to both wrap the prey in silk, and inject them with venom?

Nice question!

Based on some previous observations on other web spiders, I belive that these "redundant" behaviors are selected to avoid prey scapes, and are not trully redundant if we remenber that some preys are able to evade even if wraped. Some beetles can find a way out from the web, moving their strong legs with projections, eventually some silk lines are cut. Also beetles are more protected against bites then are other bugs, since many are under their natural armor.

Other possible explanation** :some bees, ants and wasps produces chemical signals when in trouble, attracting their sisters. From the spider point of view, this could be a way to get more food. But too many of these insects could possibly destroy the web, only because their are numerous. Obviously these are speculations.

Also, some wasps prey on web spiders. If the wasp eventually touches the web and entangles itself, now the wrap/bite strategy turns in defensive way, maybe with the "danger turns dinner" bonus.

 I did not search too much, but probably someone has alread tested some of these possibilities. Also, I read once that some spiders can treat distinct preys in distinct ways, even releasing some undesirable bugs from the web.

** This bee-wasp-ants-hypothesis is not based on observation, only on knowlodge about insects and spiders.


Why is the probability of fixation of an allele equal to its frequency?

Several proofs are given here (p. 9). My favorite comes from the genealogical argument:

Consider the situation where there are $2N$ alleles: $A_1$, $A_2$, $A_3$ ... $A_{2N}$.

By the genealogical argument, we may state that at $t = \infty$, all alleles at this locus will be direct descendants of one particular allele present at $t = 0$.

Allelic variants at this locus are selectively neutral, so $Pr(A_{1fix})$ $=$ $Pr(A_{2fix})$ $=$ $Pr(A_{3fix})$ $= ... =$ $Pr(A_{2Nfix})$. For any given allele present at $t = 0$, the probability of fixation is therefore $\frac{1}{2N}$.

Now define allelic variants $A$ and a as complementary, non-overlapping groups of the initial alleles, such that $n_A$ + $n_a$ $=$ $2N$. From the above, the probability of fixation of an allele within group $A$ is $n_A * \frac{1}{2N} = \frac{n_A}{2N} = p_0$.


Want to know about a creature which bite me

That is an insect, in the order Zygentoma. These are harmless, and do not bite. If you were bitten by something, it was not this?


Are transgender people born physically different from others?

The concept of transgenders has nothing to do with sexual organs at birth. Transgenders is a concept that has to do with sociology, not biology. See the wiki link.

intersex (previously called Hermaphroditism) has to do with biology. The wiki link makes a great job at defining intersex.

In short: A transgender person is born anatomically either male or female (with eventually exception of intersex who go on to become transgender) and they then identify themselves to the opposite sex (or a third sex) rather than identifying themselves to their actual anatomic sex.

Note that this post is closely related.


Novel bacterial strains of bacteria first isolated on the International Space Station, did the space environment lead to these genetic changes?

The authors propose that this is a distinct species based on a number of physiological and genetic tests. To quote the summary of your linked paper

In summary, the phylogenetic and genetic distinctiveness and differential phenotypic properties were sufficient to categorize these three ISS strains as members of a species distinct from other recognized Methylobacterium species. Therefore, on the basis of the data presented, strains IF7SW-B2T, IIF1SW-B5, and IIF4SW-B5 represent a novel species of the genus Methylobacterium, for which the name Methylobacterium ajmalii sp. nov. is proposed.

This indicates (emphasis mine) that they think that these isolates are distinct enough from species that we have found on Earth to make the isolates a species. This is a species that we haven't found on Earth, but unsurprisingly it is closely related to species from the same genus that have been found on Earth and on the ISS

The authors make no statements about how the species came to be there that I could see, only that it is a novel species from the ISS, which has not been found on Earth. No mechanisms for arisal are postulated, and the authors wisely did not speculate on this at all (speculation on results is frowned upon in science). One of the reasons they did not speculate on this will be that testing mechanisms whereby speciation has occurred is very difficult, especially as they would need to mimic in the lab the conditions in the ISS and show which conditions were important for the speciation. These experiments would be technically challenging and very time consuming.

It is worth noting that we don't really know the rate of species differentiation on Earth, let alone in space, partly because Earth is so covered in bacteria that proving that one evolved in the environment is difficult as it is hard to prove that you didn't just miss it last time you looked. To quote the paper I linked above:

For example, a single gram of soil can harbour up to 1010 bacterial cells and an estimated species diversity of between 4·103 to 5·104 species .

However, the ISS is one environment where it might be easier to see these sorts of events because it is relatively micro-organism free, and we have prior samples to go back and compare to. For some comparison of the numbers, I turn to the second paper you linked, which found:

Of the total bacterial and fungal isolates that grew, 133 bacterial isolates and 81 fungal isolates were identified by Sanger sequencing...   ...When the ASVs were summarized to the genus level, 121 taxa were detected, 77 of which could be assigned to known genera

and

Overall, the number of bacteria (combination of R2A and BA growth) isolated from the ISS from all 24 samples ranged from 6.7 × 103 to 7.8 × 1010 CFU/m2

So quite high numbers of cultivatable bacteria (CFU = colony forming units, a measure of how many bacteria will grow per sampling), indeed as high as those found in a gram of soil, but very low species diversity compared to the soil.
It is still difficult to prove that this is a new species evolved strictly on the ISS, but it does seem logically likely that evolution will happen on the ISS, as it does anywhere that life is present (as far as we know).


Master Catalog of all Fossils / Literal Fossil Record?

fossilworks.org and paleobiodb.org are reasonably good databases for fossil records. Paleobiodb has even got a map based view which is really convenient. Thank you.


Electron balance for biomass synthesis: is my professor right?

The terms are different.
Oxidation number is the difference in number of electrons (not pairs) from the elemental form (which for many elements exists only on paper) of an atom.
Degree of reduction is a more uncommon term that is basically the number of electrons that atoms in a molecule are donating per atoms of a given element. It is calculated formally by summing the number of electrons donated to reach a full shell (H=1, C=4, N=-3, O=-2, P=5, S=6 etc.) divided by the number of a given element, but that is more confusing than anything.
Carbon can be oxidised four times, e.g. methane > methanol > formaldehyde > formate > carbon dioxide (not biological route, just an example), while oxygen can be reduced twice: to hydrogen peroxide and then to water. As proof, most O2 dependent enzymes produce hydrogen peroxide (e.g. FADH2 enzymes). That is a cheat way to work out where those numbers come from.
I would recommend forgetting about the formal calculations of oxidation numbers —in biology oxidation numbers of carbon are generally not discussed.
I will open the brief parenthesis of the oxidation states of carbon just to point out they are not those: -1 for a bond with hydrogen, +1 with oxygen and 0 for a C-C bond. Carbon monoxide therefore has an oxidation state of +4, while a C in glucose (on average) has a -1. Molecular oxygen has two identical atoms therefore is 0. Elemental carbon has 6 electrons so hypothetically you cannot strip carbon more than +6.
Here what is important is figuring out how many times a carbon in a molecule can be oxidised, that is how many electron pairs a molecule can give away as every time that happens an NAD+ (catabolism) or NADP+ (anabolism) is reduced, which is key to the cell. A dehydratase removes a hydroxyl group leaving an alkene, but it does not carry out a redox reaction: the geometry is no longer sp3, but sp2, and the oxidation state has decrease by 1 in that carbon, yet carbon kept its electrons —the other carbon increased by 1 as it deprotonated, so no net change and NADH is not generated.
Knowing how many electron pairs are given away going from glucose to carbon dioxide is important because cells cannot make them disappear and a terminal electron acceptor is needed either in the form of respiration or fermentation. There is a further concept, that of reduction potential. Different forms of terminal electron acceptors are employed in Nature: oxygen, Fe(III), sulfate etc. and these have different "energy" levels at which they accept the electrons (reduction potential, measured in volts), which translated to different amounts of energy that can be syphoned off during the reaction.


Backbone hydrogen bonds between adjacent amino acids in a protein?

The situation you ask about was originally part of the 27 ribbon and 2.27 helix structures considered as possibilities by protein chemists (Linus Pauling?) in the 50s or 60s. The diagram below, showing the ribbon, is from the classic text (long out of print) The Structure and Action of Proteins by Dickerson and Geis.

This turns out to be very rare in proteins. To understand why, one must remind oneself of the conditions for forming hydrogen bonds in proteins. For hydrogen bonds between peptide bonds these would be:

Correct distance between hydrogen of the NH and the O of the CO (too far apart — bond weak, too close — repulsion).
Near(ish) linear angle of the NH and OC.
Lack of steric repulsion of other atoms in the structure

Calculations indicated that a 2.27 helix would be less strained than the 27 ribbon:

Playing with polyglycine in Bosco Ho’s Ramachandran Plot Explorer (Rama) indicates steric repulsion still exists in this structure (white striped connectors):

I could only find one report of this structure, and that was in the artificial peptide Ac-(∆ELeu)5-NHMe, with a model using dihedral angles Φ,Ψ approx. –60°, 30° (as in the Rama simulation) shown below:

It should be noted that this position of the Ramachandran plot is at the margins of stability, and I would expect the bonding only to occur in proteins where it was stabilized by other interactions (as in this artificial peptide) and no lower energy structure were possible.


Why do cyanide and arsenic smell like almonds and garlic, respectively?

According to CDC.gov and Toxnet, bitter almonds contain cyanide, which, gives them the characteristic odor, but this can be also due to benzaldehyde (PubChem), which is, by the way, used as almond flavor for cooking (Wikipedia).

Garlic has its odor due to allyl methyl sulfide (Wikipedia) and not due to arsenic, which is not present in garlic in significant amounts. Arsenic as such does not have garlic odor and foods high in arsenic, such as rice, chicken, fish, beer and wine (Prevention) do not smell like garlic.

However, poisoning by toxins, such as arsenic, thallium, organophosphate pesticides, selenium and tellurium (FPNotebook, PubMed) is followed by addition of the methyl group (CH3) to them by normal intestinal bacteria, which gives them the garlic-like odor.

So, the connection between the garlic odor of garlic and arsenic (or other) poisoning is in the presence of methylated substances: allyl methyl sulfide in garlic, trimethylarsine in arsenic poisoning, dimethylselenide in selenium poisoning, etc (PubMed).


Do hairs in the ear respond to things like shampoo?

You are mixing up hair cells and hair. Hair cells in the cochlea (wiki) have tiny stereocilia (subcellular organelles) that sense vibrations approaching the atomic scale. These are then translated in hyperpolarizing or depolarizing currents that drive the spiral ganglion cells of the auditory nerve. The 'hairs' on the hair cells will not readily benefit from shampoo I'm afraid. If you should want to test it, the shampoo should be intracochlearly administered in the scala media of the cochlea - so even if shampoo is beneficial it would be hard to utilize it without surgical intervention.


BLAST was devised to compare one sequence (the query sequence) with all the sequences in a database (target sequences), in particular the Genbank database(s). In 2012 Genbank contained over 3x1011 nucleotides in approx 109 sequences. So it is not feasible to do a rigorous comparison of the query sequence with each of the target sequences in the database, e.g. by the dynamic programming method, either local or global. It would just take too long. Instead BLAST uses heuristics to get the most likely best matches in a reasonable time.

The key assumptions of one of the heurists used is that any good overall match between sequences will contain some high-quality short matches, called high-scoring pairs (HSPs). (HSPs would be perfect matches of short runs of nucleotides, or high-score matches of amino acids (tripeptides) when one uses an amino acid comparison scoring matrix.) The program can make an index or library of those HSPs present in the query sequence and then just compare these (i.e. make a local alignment) in turn with target database sequences — a great time saving. So that is the basic answer to the first part of your question.

Just to quickly complete the story, an attempt is then made to use these high scoring pairs as 'seeds' to extend the alignment in either direction, and high scoring target sequences are saved and ranked.

An answer to your second question is you would do a global alignment when you were working with just a couple of sequences and had some scientific reason to believe that they were related, even though there were regions that had diverged appreciably. For example, you might be aware of key rare amino acids or nucleotide sequence motifs that should align in these regions and want to display them. Or you might want to align a protein of unknown three-dimensional structure with a related one of known structure to model it. But you wouldn't use BLAST to do the alignment, you'd probably use an implementation of the Needleman and Wunsch dynamic programming algorithm.


We use primers in PCR because we are mimicing natural processes. DNA polymerase cannot act without primers. It needs primers to start it's work. Binding of molecules happen by chance, so the more there are of your primer, the more likely it is that it would bind to any given string of complementary DNA. DNA replication occurs in the five prime to three prime direction because phosphate doesn't allow the reverse reaction.


What are the teeth of the viperfish composed of?

They are not unique

The are made of enamel and dentine just like ours, Even the enamel in human teeth is translucent. Note viper fish are tiny so their teeth are likewise very small, so they can look transparent just by being translucent an small. Hydroxyapatite, the mineral enamel and dentine are made of is translucent. the difference is in the crystal structure,(teeth or often porous which leads to more scattering and less transparency similar to why dry paper is white and wet paper is translucent (also true of teeth)). Impurities or more precisely what else is present in the enamel and dentine are present has an effect as well, as teeth are not just hydroxyapatite.

Source for the composition of teeth.

source for the translucency and microstructure of teeth

Source discussing how translucency changes with mineralization in cow teeth.


Why is metabolism of ethanol catabolism? Could it be also detoxification?

These are somewhat loosely defined terms, but I would say catabolism is any metabolic process that extracts energy from a substrate. Ethanol conversion to acetate (via alcohol dehydrogenase; see this schematic) is an oxidative pathway which extracts energy in the form of NADH, so yes, it is a catabolic pathway.

I guess you can also call this process detoxification, since it removes a (mildly) toxic metabolite. Anyway, I think the "classification" of a pathway is less important than understanding the actual biochemistry.


Do prokaryotic chromosomes have centromeres?

No, prokaryotes do not have centromeres.  They do, however, generally have a somewhat analogous structure used during cell division to partition the replicated chromosomes and plasmids between the two daughter cells. The analogous place on the chromosome or plasmid is the parS element, a DNA sequence on the chromosome or plasmid which is part of the parABS system.  This system, consisting of two proteins (parA and parB) along with parS, forms a mechanism to segregate the copies of a chromosome or plasmid for the daughter cells.
parS is usually called a "centromere-like" site, but is sometimes referred to as a "plasmid centromere”, which is why the quote uses the phrase so-called “plasmid centromeres”.


Why is it thought that silicon based lifeforms never flourished on Earth?

At temperatures above -195C, "C" wins the day. "Si" based chemistry may be more versatile than carbon in some environments, for example in a frozen nitrogen atmosphere.
Silicon accounts for 43% of rocks, Carbon is less than 0.1 percent, except that carbon is similar to water for reactivity and dissolving stuff, and organic "C" compounds are a molecular sludge like flowing-dissolved-stone, room-temperature-lava: tar/margarine/oil/diesel/glucose/alcohols/acetone are sludgy, liquid, the molecules can rotate, flow, coalesce... Carbon molecules are fluid, sludgy, rotating, pivoting, kind of lego material, whereas silicone chemistry doesn't flow, it vaporises and precipitates out of any flowing state.
Carbon reacts with both the molecules of water, O and H, and almost everything else, to make millions and millions of compounds. Silicon can't bond H. It's like the difference in between lego technic and lego. Try making a robot from lego!
That gives life millions of times more chemistry building blocks compared to silicone, and permits life to interact with water. Silicon life can't really interact with water.

10/1 cosmic abundance of carbon vs silicon

A carbonaceous contrite meteorite can contain 70 extraterrestrial amino acids and other compounds including carboxylic acids, hydroxy carboxylic acids, sulphonic and phosphonic acids, aliphatic, aromatic and polar hydrocarbons, fullerenes, heterocycles, carbonyl compounds, alcohols, amines and amides.

If you put silicon in a flask with, metals, sulphur, nitrogen, water, etc, and do the same with graphite, and you mix and heat them all up, the carbon will tend to make a vast population of larger sludge molecules, tars, formadehyde, amino acids, and the silicon will tend to form rocky crystals, as found in geology.

SiO2 is sand, quartz, very unreactive, takes a lot of energy to make it, whereas CO2 is a relatively reactive solube compound.

Silane SiH4 is the equivalent of Methane CH4, but SiH4 oxidizes instantly in contact with water and oxygen and air and is totally unstable, not naturally occuring, and it's difficult to make it, it combusts and becomes elemental silicon and water.

A silicate rich meteorite will only contail a wide array of silicate minerals, which are simpler, mineralogical, unreactive substances compared to organic chemistry that can exist in a meteorite.

Carbon forms double electron bonds a lot easier than silicon because it is smaller and lighter with a small atomic radius.

Silicone carbide SiC is a very rare mineral which illistrates Silicon's fussiness in making bonds.

Silicon-hydrogen molecules react spontaneously with water and they exist more easily in suphuric acid, which kindof limits silicone to a square root of the combination possibilities available to carbon. The H reactions give it that extra connection ability, any time a carbonate molecule becomes unstable, it absorbs an H and it's stable. Silicone can't do that.

Silicon doesn’t want to let go of Oxygen, but it doesn’t want to attach to hydrogen. try burning or dissolving quartz and silicates, compared to carbonates and "C-H" compounds = organic compounds.

An AI life-form could make good use of silicon: it's unreactivity with water means that a silicon transistor brain can exist anywhere in frozen space, using metals and electricity for the animal's functions, and avoiding water. A robotic species of life would more probably be made of silicone, so if some alien life forms land on earth, they will probably be transistor and metal electric beings rather than carbon based ones.

Wikipedia page.


Scientific name for the union point of a plant stem and root

From Basconsuelo et al 2002:

"The zone of the plant axis where the arrangement of vascular systems changes from root- to stem-structure is often called “transition region”" (see also the refs they cite).

The idea behind it is that the organization of the vascular tissues is radically different in the root in comparison to the stem, such that the switch cannot occur in one point. This transition region (in general case) crosses the air-ground interface.


What is the difference between transverse section and longitudinal section?

For an animal with bilateral symmetry, a longitudinal section is parallel to the anterior-posterior axis (labelled central axis in the image below). Sections through or parallel to either the sagittal or coronal (also called frontal) plane are longitudinal. A transverse section is perpendicular to the anterior-posterior axis and is also called a cross section.

image source


Was there originally a non-ribosomal way of synthesizing proteins?

(A quick answer to a question that will be likely closed being not well focused on the physics of all this)

First: the ribosome translates mRNA into the chain of amino acids that eventually will become a protein. The ribosome is a huge complex, made of both proteins and RNA. RNA can have enzymatic activity like a protein: the ribosome is a Ribozyme.

This chicken or the egg problem has puzzled biologists, chemists and biophysicists for a while. The structure itself of the ribosome was the "smocking gun" for the model we have today: the RNA world. In few words: because RNA can act as a protein and it is so similar to DNA, probably our DNA-world (i.e. information stored on the DNA, work done by proteins, RNA between the two) emerged from a fully RNA-world, where RNA was responsible for both protein activity and information storage.
How in detail all this happened by evolution, is probably the subject of several nobel prizes to come.


What are limitations on the number of objects the eye determine at a glance?

The answer to this question is complicated, but assume it's not for the moment. The easy answer is that our eyes can detect patterns we're familiar with and "produce" an answer in the form of a number. Unfamiliar patterns do not produce this 'number'.

Take a die. We are immediately aware of the number of dots in the typical arrangement of one to six. We need expend no counting to do so. If the skittles are arranged in the familiar die pattern, we will have no problem knowing if there are 4 or 6 skittles.

Given a pair of dice, any gambler can tell you what number any two faces adds up to without counting the spots. Do it long enough, and your brain is on auto-recognize. In your example, if Sam is a gambler, and the skittles are arranged like the spots on two dice, again, no problem telling between 2-12 skittles.

If you arrange things in a comfortable pattern, this can go on into the hundreds.

The above was easily recognized by you as nine, I presume.

Someone good with pattern recognition will know that the above left is 25 dots. However, they will not know that there are 25 dots in the above right.

So, the easy answer is that the eye can grasp high numbers of things if they are presented in a familiar pattern. The normal mind, however, is not able to do so with higher numbers arranged in a random pattern. And, random is how most things present themselves. So, we need to count.


Is the CDC's reported drop today in COVID-19 cases by date of diagnosis meaningful?

The information you show is meaningless unless it is also accompanied by the number of tests performed. If the CDC tested 2 people and got two positive results, that doesn't tell us anything at all about the actual rate of infection. And, indeed, the CDC has been testing a shockingly low number of cases:

  ‡ Data during this period are incomplete because of the lag in time between when specimens are accessioned, testing is performed, and results are reported.

(image source)

The last day they give data for, 2020-03-15, includes 0 samples from the CDC and 4 samples from other public health labs. Since only 4 samples are represented in the chart, of course we see a drop in cases, but that's because they are based on only 4 tests. As more tests for those dates and subsequent dates are reported, the numbers will change.

Date Collected  CDC Labs    US Public Health Labs
3/12            75‡         2302‡
3/13            0‡          1511‡
3/14            0‡          165‡
3/15            0‡          4‡

As you can see in the table above (from the same source as the graph), the past few days have seen almost no tests are being included in this analysis either from the CDC or elsewhere, so any drop in cases is completely meaningless.


Do all cells of a plant contain chloroplasts?

Not all cells of the plant contain chloroplasts, but they all contain some form of plastid. When the plant is its development state, they contain proplastids which may turn into chloroplasts if the cells are exposed to light. Other forms of plastids may play a role in storing lipids, amylum or proteins and they form because there is a lack of light (these are present mostly in roots). Chloroplasts are not eliminated from the cell.
 Here you have a helpful wikipedia image:

This is a very general explanation though and you should look more into hormones and specific triggers for the formation of chloroplasts.
Article talking about chloroplasts biogenesis


By what mechanism do cephalopods regrow limbs?

well gastropod mollusks use Epimorphosis, so it is likely cephalopods use the same mechanisms. Basically all triploblastic organisms use this mechanism so phylogenic bracketing points towards it as well.
morphallaxis is generally restricted to very simple organisms.
Regeneration of the visual system in gastropods (Mollusca)
Oksana Tuchina  Victor Benno Meyer‐Rochow
Neural regeneration in gastropod molluscs
Author links open overlay panelStacia B.Moffett
Regeneration of the visual system in gastropods (Mollusca)
Oksana Tuchina  Victor Benno Meyer‐Rochow (alternative link)


It depends on the PPI network. Some, like DIP are exclusively experimental, depending on high-throughput robotic AP/MS, Tandem Affinity Purification, Y2H, cross-linking with formaldehyde, clever things involving half-fluorophores, etc. There are a lot of different methods, is what I'm saying. Y2H has a high false-positive rate, immunoprecipitation is expensive (antibodies cost money), others have other drawbacks.

You can also exploit the existing huge body of research using text mining, even though that's really crude. (It boils down to: protein A and protein B or their pseudonyms are often mentioned in the same sentence, they must be related somehow). There are also RNASeq methods, where you just do hundreds of RNASeq experiments and two genes that correlated(or inversely correlated) are probably interacting in some way. If two proteins interact in organism A and they have closely-related homologs in organism B, the proteins probably interact in organism B too.

In short: In a lot of different ways. It would be wise to check the provenance of a link in such a network and handle it differently depending on what kind of link it is if you're working with big networks like this.

I don't know that there are any companies that do this commercially, but the Max Delbruck Center will talk to you about screening something custom. I don't know how long it would take but 2000 proteins would not take a long time, relatively speaking. The human genome has tens of thousands of proteins, so 2000 proteins would only be a few percentage points of the effort. However if they're totally novel there's probably library setup times and overhead, but I don't even have a good guess how long this would take. Depends on who you talk to, I expect.


How can predicting protein folding speed up drug discovery?

Firstly protein structures are not infinite. Most proteins adopt specific structure.
Drugs carry out their function by binding to its target protein. Structure prediction helps drug discovery process in two ways -

it allows identification of pockets in target proteins (where drugs can bind) whose structures are not yet solved using experimental methods
it allows in silico experimentation i.e. you can take a large number of molecules and simulate whether they will bind to a specific location in your target

I would suggest going through these reviews to get a better overview of the importance of fast and accurate structure determination in drug discovery :

Verinde and Hol, 1994, Structure
Montfort and Workman, 2017, Essays in Biochemistry


What is the expected number of children that need to be born for every possible point mutation to occur once?

I don't think the book's reasoning is correct.

There are about 3 billion base pairs in the human genome, but only ca 25.000 protein-coding genes. From the top of my head, I recall that each child has about 30 mutations. If that's in the total genome and if they were all point mutations and there's 4 options for the base pair, then we have $30$ mutations out of 12 billion options in each child. So that each possible point mutation has a probability of $30/12 \text{ billion} = 2.5 \times 10^{-9}$ or $1/(2.5 \times 10^{-9})$ if you like. The book's number is 23 times larger but in the same ballpark range. Lets call this probability $p$.

Now the probability of a mutation occuring in n children at least once is equal to one minus the probability of it never occuring in n children. In other words:
$$1 - (1 - p)^n =$$
$$1 - (1 - 2.5 \times 10^{-9})^n =$$
$$1 - (0.9999999975)^n$$

If we want the mutation to occur with probability 95%, we have to solve:
$1 - (0.9999999975)^n = 0.9$
This has the solution $n = 1 \times 10^9$

In other words, with 1 billion children, each point mutation has a 95% probability of having occured at least once. Mathematically this is not the same as saying that every mutation will have occured. In fact, this implies that 5% of the mutations will not have occured. But perhaps surprisingly, we only need 4-5 billion to up the chance to 99.999%. That still leaves out thirty thousand point mutations, but is sufficiently close to "everyone".

Compare this to the numbers you mentioned:
n = 17 million gives each gene a 4% chance of occuring
n = 80 million gives each gene an 18% chance of occurring.

Secondly, a mandatory rant. :-) "The Perfect Health Diet" is written by Paul and Shou-Ching Jaminet, an astrophysicist and molecular biologist respectively. This has the potential to marry the physicist's penchance for oversimplification with the biologist's lack of mathematical prowess. We see both in the passage you ask about. A shoddy calculation about an oversimplification of what mutations and evolution is about.
Both the book's dustcover use of a word like "detoxifying" and mention of how diseases spontaneously resolve if you eat right, are both strong crackpot indicators. It's the kind of thinking that killed Steve Jobs because he didn't seek medical help soon enough but tried to eat his way out of his illness.


Why should plants transform glucose into sucrose before transporting it to other parts?

Glucose, fructose and galactose are the three dietary monosaccharides. Glucose and Fructose are  simple monosaccharides found in plants. A monosaccharide is the basic unit of carbohydrate and the simplest form of sugar, glucose are aldose and Fructose are ketose.

  If the carbonyl is at position 1 (that is, n or m is zero), the molecule begins with a formyl group H(C=O)-, and is technically an aldehyde. In that case, the compound is termed an aldose. Otherwise, the molecule has a keto group, a carbonyl -(C=O)- between two carbons; then it is formally a ketone, and is termed a ketose. Ketoses of biological interest usually have the carbonyl at position 2.
  http://en.wikipedia.org/wiki/Monosaccharide

Whereas Sucrose is a disaccharide composed of glucose and fructose. A disaccharide is more complex than monosaccharide, more complex compounds like oligosaccharides and polysaccharides exists. Sucrose synthesised within the cytosol of photosynthesizing cells is then available for general distribution and is commonly trans located to other carbon-demanding centers via the phloem.

Sucrose and starch are more efficient in energy storage when compared to glucose and fructose, but starch is insoluble in water. So it can't be transported via phloem and the next choice is sucrose, being water soluble and energy efficient sucrose is chosen to be the carrier of energy from leaves to different part of the tree. Another problem exists,   glucose is highly reactive and this may result in some intermediate reactions while transporting glucose. Being a complex structure, sucrose is not as much reactive as glucose. So plants uses the sucrose as a medium to transfer energy. Inside the cells, sucrose is converted back to glucose and fructose. Energy is yielded when it is needed. So plants transfer glucose and fructose in the form of sucrose in order to:

Increase energy storage
Efficient energy transfer
Removing in between reactions

References

Carbohydrates
Sucrose & Starch Biosynthesis
Sucrose Metabolism
Sucrose and starch synthesis
Disaccharide


A peptide or protein can be purified by affinity chromatography. The principle is that the peptide has some substrate to which it will bind, retarding its progress through the column compared to the rest of the peptide population. A couple of typical examples are:

Using a His6 tag put on recombinant molecules, IIRC it binds to Ni2+ trapped in the chromatographic resin and is eluted with a chelator like EDTA.
Immunoaffinity chromatography, where you have a population of antibodies on the chromatographic resin which are specific to the protein that you want to purify (or alternatively having the immunogen bound to the resin so that you can purify the antibodies against it)

Mighty Wikipedia has a link about affinity chromatography here.


Does melanin protect humans from gamma radiation?

Since it is clear from the source in your question that melanin can absorb energy from gamma rays, yes higher concentrations of it would reduce the energy of gamma rays getting through the skin.  However this would not provide any real relative protection, the gamma rays are still going to go right through your skin and start damaging DNA.

Gamma rays are three orders of magnitude higher frequency and therefore carry much more energy than UV.  Of course there are energy transfer inefficiencies but since the fungus are not growing at even an order of magnitude faster, it's fair to say that melanin is not absorbing all of the energy in a gamma ray.

Since the gamma rays are not fully absorbed by melanin, they will still go through the skin and will still be able to do significant DNA damage.

So yes, but not enough to really matter.

Frequency Differences
http://www.davidterr.com/science-articles/electromagnetic_spectrum.html


Welcome to BioSE! As @Chris mentioned, transported atoms and molecules don't typically retain a record of their past history, so just by looking at a molecule in the cell you can't in general tell how it arrived in the cell (an exception might be proteins that have some chemical modification on them that allows them to be imported via a specific mechanism, such as the mannose-6-phosphate enzyme re-uptake system). In order to infer if a molecule typically enters a cell by a particular method, you will have to do several different types of experiments. I'll list a few off of the top of my head. Note to other SE contributors: since this is not my area of expertise, I'm not sure how feasible some of these experiments are, or how they are typically done, so please edit my answer to be more accurate!

Diffusion If you want to know if something can diffuse across a membrane, then the easiest way would be to try it in vitro. One way I can imagine doing this is to use a phospholipid bilayer to separate two compartments: one with your molecule of interest, one without. By measuring the concentration of your molecule that transfers from one compartment to the other, you can see if your molecule can diffuse across a lipid bilayer. Note that this will only tell you if diffusion is possible for your molecule. It may be that cells have ways to actively prevent your molecule from diffusing across your membranes, which you wouldn't be able to know from this assay.
Endocytosis or pinocytosis One way to assess if your molecule is taken up by endocytosis or pinocytosis would be to knock out (genetically or with an inhibitory drug) these processes in your cell and see if your molecule of interest still ends up in the cell. Depending on the context of the molecule you're interested in, you might be able to simply place cells in solution with your molecule of interest and measure the concentration of the molecule outside the cells over time. You could compare how much of your molecule is lost from solution when cells can't endocytose and compare to when they can; if your molecule stays around when cells endocytose, you have some indication that process is necessary. Note that there would have to be a lot of other controls for this experiment as well: e.g. ensuring the effect you observe is specifically caused by endocytosis being inhibited. Since endocytosis and pinocytosis form vesicle intermediates containing your particle of interest, one check to see if endocytosis might be reasonable is to see if you can see vesicles containing your molecule of interest in the cell. Of course, this requires a method for being able to visualize your molecule of interest (maybe it's fluorescent, or can be modified with a fluorescent marker? Or maybe there is a fluorescent protein that binds your molecule and can change color on binding? These things all exist, they just depend on your particular molecule and context).
Transport channels: In a similar vein, how does the uptake of your molecule change when you inhibit or remove from the cell a particular type of channel? You could measure this in a similar way as the bullet point above.
Active vs passive transport: If you wanted to see if uptake of your molecule requires active transport, you could try inhibiting ATP synthesis with a drug and see if transport of your molecule decreases over time. Note that this is in general not good for the cell (really!), so you might also have to have some more controls for this, maybe showing that transport of a molecule known to travel by passive transport is not affected on the timescale you're looking at, for example.

This list is by no means exhaustive, but I hope it gives you a sense of the type of experiments and ways of thinking you might be able to use to figure this out. Some general thoughts:

This tends to be case-by-case. While the type of experiments you might do to determine the mode of transport for different molecules are similar, the controls you will have to do to shore up your conclusions will really depend on the system involved, what type of effect a molecule has on your cells, whether your cell imports and exports this molecule, under what circumstances you might expect the cell to take up this molecule (so you have a way to trigger the cells to take up this molecule for your experiment). I don't know of a completely generic method for resolving this type of question.

Being able to measure abundance of your molecule is important. All of the experiments above rely on being able to measure the concentration of your molecule, either outside of the cell, or inside of the cell. This is often easiest if you can modify your molecule to be visualizable in a microscope or spectrophotometer, but however you do it, you need a good, reliable, robust assay in order to make strong conclusions with this assay.

Controls are really important. Thinking up all the different alternative possibilities and trying to come up with ways to rule them out is the heart of experimental science. Fortunately, it also happens to often be rewarding and thought-provoking! I certainly had fun thinking about this.

Best of luck!


Is breathing in deodorant fumes dangerous for my brain?

You can definitely absorb alcohols by breathing them in.  But doing do is far less efficient than drinking alcohol, so you don't have anything to worry about on that front.

To address your concern we have to answer two questions: how much alcohol is transfered per unit time and is there a local dosing effect due to proximity to the blood brain barrier.

It is probably pretty obvious that while alcohol evaporates rapidly compared to water, it still takes quite awhile. Imagine trying to inhale a glass of whiskey. You would get a serious headache but 30 minutes in you would still have an almost full glass of whiskey and no alcohol buzz. For an amusing anecdote relating how hard it is to get drunk off of inhaling even from a machine designed for it, see here

As to the second point - Fortunately, the blood brain barrier is a two way street for alcohol, which means that you can't get drunk in your brain if you don't have high levels of alcohol in your bloodstream. The two would dialyze into a reasonably balanced equilibrium.


Relationship between leaf structure and Photosynthesis rate

1) Your understanding of taxonomy is outdated by a few hundred years. Linneaus' original system was based on flower morphology, but we since realized that the most effective taxonomy takes into account many different traits. In today's times, we mainly use DNA sequencing to determine relationships between organisms.

2) The leaf structure is not necessarily only optimized for maximum photosynthesis rate. For instance, the leaves of cacti are spines: thin and pointy to minimize water loss and defend the plant. In fact in cacti the stem is the photosynthetic part of the plant, not the leaves. More generally, leaves may be thicker or thinner to cope with drought. You can check out the wikipedia page for Specific Leaf Area for more information.

Long story short: different plants grow in different environmental conditions, so the optimal leaf shape for any one plant depends on conditions like drought and shade.

3) There are many advantages that can be conferred by leaf shape. One example is how leaf shape can affect what is known as the boundary layer of the leaf. The boundary layer is thicker in larger, uniformly-shaped leaves and thinner in dissected or compound leaves. The intro on this webpage seems like a good resource

Overall, good question. You have to keep in mind that any trait is going to be the product of many different factors; no one factor can entirely determine a trait's morphology. For leaves, it's many different factors including photosynthetic rate, drought, shade tolerance, defense against predators, etc. that determine the shape of the leaf.


Can restriction enzymes (Type II) displace single-stranded binding proteins (SSB)?

This is an interesting point. In the case of typical restriction enzyme digestion, it is double stranded DNA that is being digested. So in this case the SSBs are presumably binding to the sticky ends after digestion, so there is no competition with the restriction enzyme.
If you are interested in a specific case where you are digesting ssDNA, and have decided to add in single strand binding proteins, the binding strength (rate constants) of the SSB and restriction enzyme would influence how much the enzyme can displace the binding protein.
Here's a paragraph from the NEB/T4 gene 32 page indicating many similar applications involving reverse transcriptases, polymerase etc.

"Recently, it has been shown to improve restriction enzyme digestion
(6), improve the yield and efficiency of reverse transcription (RT)
reactions during RT-PCR (7-9), enhance T4 DNA polymerase activity
(10-11), as well as increase the yield of PCR products (12)."

EDIT: Although the reference (6) cited by NEB does not have any evidence that proves the enhancement of restriction digestion with single strand binding protein 32. This chapter might be helpful? - Kowalczykowski et al., "21 single-stranded DNA binding proteins." The enzymes. Vol. 14. Academic Press, 1981. 373-444.
From their abstract, it looks like the mechanism of enhancement could be through prevention of ssDNA hairpins so that the endunuclease can access it's recognition site (I haven't read the full chapter). Another fact supporting this is that ref(6) mentions that other interacting enzymes can work alongside SSBs only when SSB's are not saturating all the DNA in the in-vitro reaction. In an in-vivo context, the chapter abstract states that intracellular SSBs are sufficiently abundant to saturate all ssDNA intermediates formed inside cells (I presume they are talking about E. coli)
Below is the supporting text from reference (6) mentioned by NEB - bolding is mine, for emphasis : Bittner, M., R. L. Burke, and B. M. Alberts. "Purification of the T4 gene 32 protein free from detectable deoxyribonuclease activities." Journal of Biological Chemistry 254.19 (1979): 9565-9572.

Nuclease Assays-The presence of both exo- and endo- deoxyribonuclease contaminants in the 32 protein fractions has been monitored carefully throughout these purification schemes. The results of exonuclease assays are presented in Table III, and the results of sensitive endonuclease assays are presented in Table IV. Note that, when such assays are designed to detect nuclease activities on single-stranded DNA, it is important to test 32 protein at subsaturating, rather than only at saturating, protein to DNA ratios. Otherwise, an activity which hydrolyzes only free (non-32 protein-com- plexed) single-stranded DNA will escape detection.


How many molecules NADH are produced in the Krebs Cycle?

This is slightly depending on which reaction you want to include into the cycle. I count four:

One when Pyruvate is converted to Acetyl-CoA,
one when Isocitrate is converted to α-Ketoglutarate,
one for the reaction of α-Ketoglutarate to Succinyl-CoA and
finally one for the reaction of Malate to Oxaloacetate.

If you see the reaction of Pyruvate as happening outside of the cycle, it's only the later three.
See this image (from here) for an overview:


How is the protease inhibited by lopinavir different in SARS-CoV-2 compared to SARS-CoV?

Is there a difference in the gene encoding for the protease?

This paper by Wu et al. annotates the SARS-CoV-2 genome and compares its divergence from other coronaviruses, which may help answer your second question.

This annotation includes 16 genes for non-structural protein ("nsp"). Supplemental materials for this paper indicate that all but two of these proteins (nsp7 and nsp13) have amino acid substitutions between SARS-CoV-2 ("2019-nCoV" in the paper) and SARS-CoV.

The gene nsp5 encodes 3CLpro (chymotrypsin-like cysteine protease), so there are differences there.

Literature suggests nsp5 and other non-structural proteins are potential targets for a number of antiviral therapies.

Another paper suggests further that lopinavir targets nsp3 products, among other proteins, in use against SARS-CoV:

  Lopinavir’s possible target is Nsp3b, Nsp3c, helicase, NRBD or E-channel with the mfScores of –158.050, –189.140, –114.018, –171.127, and –221.785, respectively.

The nsp3 gene contains a papain-like protease 2 (PL2pro) domain. Supplemental materials from the first linked paper suggest nsp3 has a different amino acid sequence between SARS-CoV and SARS-CoV-2.

It might be worth digging into the Wu et al. paper and the raw annotation data to look at what those a.a. substitutions are, to see if that might help in determining why lopinavir is not as efficient at inactivating PL2pro and reducing levels of the novel coronavirus.

It may also be worth considering the target itself. Going back to the Nature Biotechnology article:

  But Erik De Clercq, of the Rega Institute for Medical Research in Leuven, Belgium, says that in searching for or designing effective drugs against COVID-19: “We should stay away from antivirals known to be acting at targets not playing a role in the replication of coronaviruses.” Such drugs include penciclovir, which is targeted at the herpesvirus DNA polymerase, and lopinavir/ritonavir, which are targeted at the HIV protease. Instead, he would favor targeting a virus-specific protein such as the RNA-dependent RNA polymerase, noting that coronaviruses do not contain or use a reverse transcriptase.


What is the difference between drought resistant non-succulent plants and plants that cannot be allowed to dry out?

The difference may be related to how the plants fix carbon. While all plants convert CO₂ and H₂O to glucose and oxygen, there are at least three pathways that are used to do it. The C3 pathway is older and less efficient than the CAM and C4 pathways. Many drought tolerant plants use the CAM or C4 pathways because less water is needed. The C4 pathway is better than C3 in drier climates, hotter climates, and when CO₂ or nitrogen are limited. The hard part about this answer is that I'm not a botanist. Wikipedia lists some plants that use C4, CAM, and C3, but there is no comprehensive list, so I can't match up all the plants you mentioned in your question. In general, a higher percentage of monocots, especially grasses, use C4, but a wider diversity of dicots use C4. But you still can't draw conclusions about families of plants, because while corn and sorghum use C4, rice and barley use C3. Ragweed, a plant you say grows well in dry conditions, is a member of Asteraceae, which includes many plants that use C4. However, rudbeckias are also members of Asteraceae, but don't do as well in dry conditions. The C4 pathway has appeared and disappeared in several different plants, making any general claim hard to make. Here are some links that might help:

http://www.en.wikipedia.org/wiki/C4_carbon_fixation
http://www.en.wikipedia.org/wiki/C3_carbon_fixation
http://www.en.wikipedia.org/wiki/Crassulacean_acid_metabolism
http://www.brown.edu/Research/Edwards_Lab/reprints/sage_etal_2011jexb.pdf

If you know more about plants than me, that last link might be helpful, it's about the evolution of C4 pathway in plants and includes lists, but uses the formal species names I just don't recognize.


Definition of selection coefficient

A selection coefficient is a difference in fitness between two genotypes (or haplotypes). Let the two genotypes be A and B. Let's use relative fitness and say that the fitness of A is $w_A = 1$ and the fitness of B is $w_B = 1 - s$, where $s$ is the selection coefficient. As a consequence $w_A - w_B = s$.

The question of long-term fitness is unrelated to the definition of selection coefficient, as the selection coefficient is defined as a difference in fitness. A question of importance is "What measure of fitness should one use for a population where selective pressures are changing over time and/or space".

What measure of fitness should one use for a population where selective pressures are changing over time and/or space

Roughly speaking, if changes in fitness are over space, then you should use arithmetic mean fitness and if changes in fitness are over time, then you should use the geometric mean fitness but it is not quite that easy.

The real interest is whether fitnesses are correlated among generations. In other words, do individuals within a generation tend to have a more similar fitness values than the individuals of another generation? When variation in fitness is spatial than one should not expect such correlation. When variation is temporal one should expect such correlation.

Hoping you can read a code in R, the easiest is probably to read some code that make a simulation and look at the output. So here is a code that performs simulations. The key difference between simulations with spatial and temporal variation is the line that gets fitness value (runif).

set.seed(43)

temporalVariation = function(N, lowestFitness, highestFitness, nbgenerations)
{
    Ns = numeric(nbgenerations)
    Ns[1] = N
    for (generation in 2:nbgenerations)
    {
        fitnessPerIndThisGeneration = runif(1,lowestFitness, highestFitness) # All individuals have the same fitness in a specific generation
        N = N * fitnessPerIndThisGeneration
        Ns[generation] = N
    }
    return (Ns)
}

spatialVariation  = function(N, lowestFitness, highestFitness, nbgenerations)
{
    Ns = numeric(nbgenerations)
    Ns[1] = N
    for (generation in 2:nbgenerations)
    {
        FitnessOfEachIndividual = runif(N, lowestFitness, highestFitness) # Individuals differ in fitness within a generation
        N = sum(FitnessOfEachIndividual)
        Ns[generation] = N
    }
    return (Ns)
}

N = 1000
lowestFitness = 0.95
highestFitness = 1.08
nbgenerations = 200

spatialNs = spatialVariation(N, lowestFitness, highestFitness, nbgenerations)
temporalNs = temporalVariation(N, lowestFitness, highestFitness, nbgenerations)

plot(y= spatialNs, x=1:nbgenerations, col='blue', xlab = 'generation', ylab = 'N')
points(y= temporalNs, x=1:nbgenerations, col='red')

In blue is the simulation with spatial variation. In red is the simulation with temporal variation. You will note that the geometric mean is always equal or lower than the arithmetic mean.

Whether the arithmetic or geometric mean fitness matters most will affect the reproductive system that will be most successful. In this regard, you should read Ripa et al. 2009 about bet-hedging


That appears to a "bag worm", which is as you surmised a caterpillar.

This suggest that it is from the family Psychidae, but I won't even try to guess at the species.  However, if you see any adults you may be able to identify them using this website.

An example image of an North American species:


why do some cells in the body prefer necrosis to apoptosis as a means of cell death?

There is actually no preference for apoptosis or necrosis in cells of the human body - both types can occur in all cells and they have different triggers. The main differences can be seen in this figure (from here):

Apoptosis (also called programmed cell death) has three different triggers (intrinsic, extrinsic and Perforin/Granzyme pathways), see the image below for details (from reference 1):

All three activate different components and caspases in the beginning but finally all activate Caspase 3, which finally activates endonucleases (which degrade the chromosomal DNA), Proteases (which degrade the proteins in the nucleus and the cytoskeleton) which leads to the degradation of the cell. In the end apoptotic bodies are formed from the cell. Additionally the mitochondria break down and release cytochrome c and ATP. Their release from the cell attracts macrophages which take up and eliminate the apoptotic bodies and in turn release cytokines which suppress an inflammatory response.

Apoptosis goes on in a ordered way and does not trigger any further reactions in neighbouring cells (except these receive the same signal). See also reference 1 and 2 for more details.

Necrosis is triggered by external stimuli of the cell as injury of tissues or toxins from infections. Necrotic cells swell, while there internal structures are in a state of unregulated degradation. Finally the membrane will burst and set free cytochrome c and phosphatidylserines from the membranes which cause inflammation in the affected tissue. The necrotic cells are not removed by macrophages which allows the released interior of the cell to spread further and cause problems.  See reference 2 and 3 for more details.

Necrosis is usually not as a beneficial process, but there are also publications which see
the process as a specific form of cell death (see reference 4).

References:

Apoptosis: A Review of Programmed Cell Death
Apoptosis vs. Necrosis
Cell death by necrosis: towards a molecular definition
Review Necrosis: a specific form of programmed cell death?


What to call a trait that has current utility but unclear evolutionary origin?

As you point out, people have sampled other terms like "aptation" but these terms are not commonly used.

In order to not imply anything about the evolutionary history, since it is unknown, I think it makes most sense to refer to these simply as traits or phenotypes (or genotype for that matter, depending on the approach you are taking). If you wish to emphasize that these traits are beneficial to the organism, it is sufficient to call them beneficial traits or use other adjectives like useful, positive, etc.


At the command line:

wget ftp://ftp.ensembl.org/pub/release-84/gtf/gasterosteus_aculeatus/Gasterosteus_aculeatus.BROADS1.84.gtf.gz
gunzip Gasterosteus_aculeatus.BROADS1.84.gtf.gz

Then in R:

library(GenomicFeatures)
txdb = makeTxDbFromGFF("Gasterosteus_aculeatus.BROADS1.84.gtf")
hist(log10(width(unique(exons(txdb))))) # exons
hist(log10(width(unique(unlist(intronsByTranscript(txdb)))))) # introns

Note that some of the annotated exons (and the introns between them) are incredibly unlikely to be correct. For example, there are 1 base long exons and introns. I don't think anyone actually believes those are correct, but the distribution is probably otherwise approximately correct.

Edit: For what it's worth, there are no negative sized exons in the GTF file. My guess is that the overlapping exons are from different transcripts (or genes on opposite strands).

Edit2: If you want to get your introns from a "union gene model", then use something like reduce(exonsBy(txdb, by='gene')) and then lapply gaps() to that. The results will be correct and the process will probably take less time than what you've been trying.


How early can we know the sex of a human being now?

Before the zygote, there is no individual for which sex can be defined! However, it is possible to know the sex of the future zygote if you know the gametes that are going to fuse.

In humans, just like in all placental mammals (which excl. kangaroos and platypus), sex is defined by sexual chromosomes, where males are XY while females are XX. A mother can therefore only pass on an X (and have no influence on the sex of the offspring) while a father can pass on either an X or a Y which will determine the sex of the offspring. Knowing the paternal gamete (the spermatozoid), one can infer what the sex of the future offspring will be. Of course, in one ejaculate, there are about as many X-bearing gametes than Y-bearing gametes.

Technically speaking, could typically make a karyotype to infer whether chromosome X or Y is being transmitted.


Actually, no. There are also recombination prone regions of the Y chromosome that recombine and exchange material with X chromosomes, and these are called pseudoautosomal regions (PARs).

Y chromosomes can be used similarly to mitochondrial DNA to build up profiles of ancestry, but the sequences used for this purpose lie outside PARs, in the non-recombining region.

What about seqeuences outside PARs, do they show genetic variation?

As pointed out in the comments, PARs comprise only 5% of the Y chromosome, but even in the non-recombining regions of the Y chromosome studies in well-characterised populations have found that the mutation rate can approximate autosomal mutation rates in some regions of the chromosome, and exceed them in others.

What processes, other than recombination, drive mutations?

There are loads of different mechanisms by which mutations in general can be generated, including exposure to UV, free radicals, tobacco smoke, aristolochic acid, and perhaps most importantly spontaenous deamination of methylcytosines, which is an age related mutational process, proofreading errors inherent to DNA polymerases. Also, it is well known that in sperm, with age the mutation rate goes up throughout the genome. While UV is unlikely to be a prominent mutagen as was pointed out to me in the comments insofar sperm are concerned, factors like smoking still play a role.

An illuminating read about mutational processes and the mutational footprints they leave in genomes, as understood from studying cancer genomes, is here.


Human brain is superior than till-date computers, yet why we perform poor than computer?

Three reasons:

Most of the storage capacity of the brain is used to store implicit knowledge. For example how to move your body, how to automatically recognise objects or how to hear and parse your language. These things may seem easy to you, but they require a lot of learning. Just look at how clumsy five year olds still are, they have been training how to use their body for five years straight and still skin their knees all the time.

Humans are actually able to retain huge amounts of information, both in their short term memory and in their long term memory. We know this because there are savants and hyperthymesia. It is likely that these abilities are actively suppressed in neurotypical people.

Because it is just not evolutionary adaptive to remember every detail. Intelligence depends on weeding out unnecessary information. If normal people learn huge amounts of information they often rely on memory abilities that are evolutionary adaptive, like the ability to remember a path from landmark to landmark.


What is the present tense verb form of apoptosis?

According to Google Scholar, there were ~40000 hits for "apoptose" and ~120k hits for "undergo apoptosis" in published literature, both of which had significant numbers of high-impact articles.

Therefore, it is clear that both expressions are sufficiently used in literature for either to be used.

Personally, I would say "undergo apoptosis" being both shorter than your original phrase and not risking coining new word forms.


This seems to be one of rare actual photos of lymph online (suggested in the comment above):

Image: Lymph (source: IJCRI - Case Reports Journal)

This particular lymph (or "lymph fluid" or "lymphatic fluid") was aspirated from a "lymphocele", which is an abnormal collection of lymph in the body (appearing outside of the normal lymphatic system).

While a lymphocele is not normal, the lymph in it, such as in this photo, looks quite normal: it is a clear (translucent) and yellowish liquid.

  The lymphatic (lim-FAT-ik) system is a network of tubes that collects
  lymph (LIMF). This clear, pale yellow fluid drains out of blood
  vessels all over the body. (KidsHealth.org)

The froth is from proteins as they normally appear in the lymph.

The image of lymph in Wikipedia is not a clear lymph, but obviously a chyle (a milky fluid containing the lymph and chylomicrons due to thoracic duct injury).


What causes light to be brighter in the corner of the eyes?

Your retina has two kinds of light-sensing nerves: cones and rods. Cones are responsible for color vision, i.e. hue, while your rods handle differences in the value, as in how bright it is.

Humans have adapted to have cones mostly in the center of the eye (which corresponds to what you're looking directly at), where the most distinguishing color information is needed. It's not often that you'd use your peripheral vision to identify the actual color of something, and this explains why you're seeing a difference between pink and red. The intensity of the color is correct, but you aren't able to identify the hue because of a lack of cone nerves.

So yes, this is normal. A fun trick (and also totally helpful if you have a messy room) is to look a foot or so above the floor when you're walking in the dark. It allows you to see what you're walking on better, since you need intensity receptors more than color receptors.

References:

http://regentsprep.org/Regents/physics/phys09/ceyes/sensing.htm

http://hyperphysics.phy-astr.gsu.edu/hbase/vision/rodcone.html


This is an old question but it seems relevant to answer now given current state of art. See also this related thread on biostars.
There are now many tools that perform this function, which is somewhat routine. A partial list:

quickmerge
metassembler (older)
MAC
RagTag (successor of RagOO)
CAMSA

I don't know which is best. Quickmerge is the one that I remember seeing the most. I believe that it is more common with eukaryotic genomes than microbial, as microbial genomes are now often getting closed with long reads.
In general we should expect that the regions that are agreed-upon by the assemblers will be fairly trustworthy, e.g. "improved" potentially. Artifacts are more likely to be found by using this kind of comparison as well.
The strategies used in each case will depend upon which tool you use. I haven't used them enough to say for sure.


Is this necrotizing skin infection caused by Staphylococcus aureus?

No. It is caused by A-group streptococci. Source Murray and empirical evidence.


Will a completely removed cat whisker grow back?

The short answer is that yes, they will grow back. Cats do regularly shed their whiskers and grow them back in time (reference). The thing is that if damage has been done to the root of the whisker, it may grow back in an irregular manner (reference). Wish for the best and by now I think the whisker should be back just fine.


Why don't chilli peppers taste as hot in space?

TL;DR

All food taste bland in space, not only chilli.

The claim in that tweet ("Chili peppers don’t taste as hot in space as they do on Earth") is not exactly correct because, the way it's worded, it gives the impression that only chilli peppers have a different taste. In fact, astronauts/cosmonauts use more chili and other spices than they regularly do on Earth, for a reason: they say that food in space (microgravity) taste bland. All food, not only chili.

Since the beginning of space flight, astronauts report that food taste different in microgravity. According to the Scientific American article When It Comes to Living in Space, It's a Matter of Taste (Romanoff and Romanoff, 2017):

  Many said that flavors are dulled and they crave fare that is spicier and considerably more tart than they would prefer on Earth.

So, due to the food tasting so bland, astronauts in fact use more chili and other spices than they normally do on Earth:

  It's possible that hot sauce and salsa could be key ingredients to the success of a manned mission to Mars. The kicked-up condiments already came close to causing a mutiny on the International Space Station (ISS) in 2002 when astronaut Peggy Whitson threatened to bar entry to the crew of the visiting shuttle Atlantis unless they came bearing a promised resupply of the spicy stuff. Only when shuttle commander Jeff Ashby announced that he had the goods did Whitson say, "Okay, we'll let you in then." Whitson was joking, but the need for astronauts to be able to  spice up their food while in orbit is no laughing matter.

However, it's still unknown why food taste bland in microgravity. Also, there is no consensus about that fact, to start with:

  There's little scientific data to back up astronauts' claims that taste changes in space, despite a number of studies since the 1970s on the effect of microgravity on the sense of taste and smell. In essence [...] study participants were split on the matter.

For those that report a change in the taste, some hypothesis were proposed:

  One of the most prominent physiological changes associated with spaceflight has to do with fluid shifting from the lower to the upper parts of the body because of weightlessness. This facial and upper-body swelling also creates significant nasal congestion, and because odor is essential to the sense of taste, a decrease in the perception of flavors would occur.

And also:

  The shuttle has a "sterile" smell, which when combined with other odors, such as the scent of their rinse-free shampoo, can be somewhat distracting.

However, there is little scientific evidence supporting this fluid-shifting hypothesis. According to Vickers et al. (2001), reproducing that fluid-shift in a simulated microgravity, where people had a head-down bed rest, has no effect on the threshold sensitivity of tastants. The same lack of changes in the taste and smell sensitivity under simulated microgravity was found by Olabi et al. (2002).

Despite that, this fluid-shifting hypothesis is supported by NASA (Nasa.gov, 2017) in an educational resource for kids:

  From the early 1960s, astronauts found that their taste buds did not seem to be as effective when they were in space. Why does this happen in space? This is because fluids in the body get affected by the reduced gravity conditions (also called fluid shift). On Earth, gravity acts on the fluid in our bodies and pulls it into our legs. In space, this fluid is distributed equally in the body. This change can be seen in the first few days of arriving in space when astronauts have a puffy face as fluid blocks the nasal passages. The puffy face feels like a heavy cold and this can cause taste to be affected in the short term by reducing their ability to smell.

The same source says:

  When food seems to lose its flavor, astronauts usually ask for condiments, such as hot sauces, to give food some intensity of taste. A variety of condiments are available for the crewmembers to add  to their food such as honey, and sauces like soy sauce, BBQ, and taco. (emphasis mine)

Conclusion

For reasons yet unknown, it seems that all food (not only chilli peppers) taste bland in microgravity. To cope with that, astronauts rely on chili and other hot spices.

Sources:

Romanoff, J. and Romanoff, J. (2017). When It Comes to Living in Space, It's a Matter of Taste. [online] Scientific American. Available at: https://www.scientificamerican.com/article/taste-changes-in-space/ [Accessed 26 Dec. 2017].
Nasa.gov. (2017) [online] Available at: https://www.nasa.gov/sites/default/files/files/Taste-in-space-TLA-FINAL.pdf [Accessed 26 Dec. 2017].
VICKERS, Z., RICE, B., ROSE, M. and LANE, H. (2001). SIMULATED MICROGRAVITY [BED REST] HAS LITTLE INFLUENCE ON TASTE, ODOR OR TRIGEMINAL SENSITIVITY. Journal of Sensory Studies, 16(1), pp.23-32.
Olabi, A., Lawless, H., Hunter, J., Levitsky, D. and Halpern, B. (2002). The Effect of Microgravity and Space Flight on the Chemical Senses. Journal of Food Science, 67(2), pp.468-478.


Would oxygen levels be stable without photosynthesis?

The answer to your question is in the first graph of the Wikipedia article you linked to: Great Oxygenation Event. In that graph, where time is measures in billions of years, you see that O2, as it was produced, was absorbed in oceans, seabed rock, land surfaces, and finally, about .85 billion years ago, O2 sinks filled and the gas accumulated in the atmosphere.[1] The spike you speak of was probably due to

  the evolution of the large vascular land plants that brought about increased O2 production and increased O2 levels due to the enhanced global burial of microbially resistant, lignin-rich organic matter during the Permo–Carboniferous (Berner 2004).

More simply put, there hadn't been equilibrium established yet between the amount of oxygen being produced, the stabilization of the ocean layers and the 'burial of excess carbon' in the deepest ocean layers. Most of the O2 on earth was produced many millions of years ago; it is a myth that the O2 we breathe today is the same O2 made by, say, ocean phytoplankton yesterday.

Nadene Unger states in the NYT article that

  [I]t is a myth that photosynthesis controls the amount of oxygen in the atmosphere. Even if all photosynthesis on the planet were shut down, the atmosphere’s oxygen content would change by less than 1 percent.

This is because there are tremendous oxygen sinks that store oxygen gas, such as the surface layers of the ocean. As O2 is used, the ocean would give up free O2. Because of these sinks, some estimate that

  if photosynthesis were to cease, atmospheric oxygen would be depleted in 5000 years due to respiration, weathering, and combustion.[2]

while others state that

  If photosynthesis were for some reason to stop, oxidation of the entire organic carbon reservoir would consume less than 1% of O2 presently in the atmosphere and there would be no further O2 loss (since there would be no organic carbon left to be oxidized). Conversely, if respiration and decay were to stop, conversion of all atmospheric CO2 to O2 by photosynthesis would increase O2 levels by only 0.2%.[3]

It is very hard to get a comprehensive answer of what would happen exactly. Do we assume all vegetation/phytoplankton suddenly disappears, or does it die (thus increasing to the carbon drain on O2)? Do we assume quick quick death of animals based on lack of vegetation/plankton, etc. as food, or would it be slower? As I said, a comprehensive answer is difficult to find. In any case, the atmospheric O2 would not fluctuate wildly in any immediate fashion.

[1] The oxygenation of the atmosphere and oceans Heinrich D Holland, Phil. Trans. R. Soc., 29 June 2006
[2] The Global Oxygen Cycle
[3] Introduction to Atmospheric Chemistry


Protein purification: Linear elutions or stepwise elution, using imidazole or pH gradient?

Linear is better typically. The flow rate combined with fraction size and length of time gives you better resolution for which proteins are coming off the column at what point.

Once you've narrowed down the imidazole concentration at which your protein comes off the column, you can in future just stick to concentrations around that area, though it's still advisable to use gradients either side of that concentration as your preps are never likely to be completely consistent.

How do you know you're losing 80% of your protein before achieving purity? If your protein isn't separating from other contaminants during IMAC, you can try switching to an IMAC optimised strain (I use NEB BL21(DE3) NiCo21's).

Usually you'll have to do some downstream purification in any event. Gel filtration is common. You could also consider a different column chemistry such as anion exchange.

EDIT

Typically I wouldn't expect that you would need to mess with pH very much when performing IMAC. I certainly have never had to. You are likely to need physiological pH to ensure native folding of your protein.

You can however use other additives if your protein is recalcitrant. For example, I often add 1mM DTT and 2M urea to my samples and then heat them slightly as my protein binds things easily and is extremely stable. GE Provide a whole booklet of supported additives for their columns, you may have the same thing for yours too.


Choosing the best assay for my experiment?

Necrotic cells could be trypan blue positive. WST-1 Assay could reflect cell number by measuring mitochondrial dehydrogenase, therefore, you could not know how many cells die in dishes. When you define apoptosis in your experiment as caspase dependent cell death, measuring caspase activity is the best.

PS

Trypan Blue Staining actually is a method to see membrane integrity.


The answer lies in hemoglobin, which is responsible for the transportation of oxygen throughout our bodies. It is the protein found in red blood cells, and thus it has a reddish hue to it. When an organism has lightly pigmented skin, the oxygenated hemoglobin causes the pinkish hue that you are describing.


What is the meaning of a selection regime in this context?

I'm an evolutionary biologist. When someone says "selection regime" they simply mean the general conditions (environmental, ecological, etc.) that could have produced a particular evolutionary outcome. For instance, in the example that you mention, they seem to imply that they are interested in knowing if these condtions (i.e. the "selection regime") in the branch that lead to the evolution of humans were somehow different than these of other primates. So, it is a hypothesis, in this case. Unless they state elsewhere in the paper what exactly is this "selection regime", they are simply referring to this idea.