How long does each of the stages in meiosis take?

If you take a look at the figure directly above the image you posted in the link you posted, you'll see a very different set of figures.

It turns out, time spent in different phases of the cell cycle depends on species, cell type, and conditions, specifically, the presence of cell cycle regulating signals like cyclins. You can also read about that in the link you posted.

Meiosis is similarly varied. For example, in a female human, oogonia start meiosis while the female is still a fetus. Meiosis is then arrested in prophase 1. Further progression in meiosis doesn't occur until puberty at the earliest. Spermatogenesis in a human male, on the other hand occurs over a 64 day period. Since oocytes sit in prophase 1 for ~ 13-50 years, they will have a very different proportion of time spent in each phase. You can read about this in Costanza Physiology, chapter 10.


Why is translation so much faster in prokaryotes than eukaryotes?

Unless the poster can cite more recent papers to support the assertion regarding a difference in rates of prokaryotic and eukaryotic protein synthesis, I would say that this is incorrect.

Lacroute and Stent (1968) reported a rate of 15 amino acids per sec for β-galactosidase in Escherichia coli, whereas Knopf and Lamfrom (1965) reported a rate of 7 amino acids per sec for globin chains in rabbit reticulocytes. This does not appear much different to me, especially as a recent study by Li et al. (2014) showed that the rate of protein synthesis varies with the complexity of the assembly (if any) into which a protein is incorporated.


Does PCR amplification affect microarray or DNA biosensor results?

Anytime you have PCR in a protocol, yes, you might mess up the quantification.  So you do as little PCR as you can, so that it stays in the linear range, preserving the different abundances of templates  (qPCR after all is the gold standard for quantifying expression), and you hope that there are minimal PCR biases between templates.


Help me understand how the thyroid secretes

That "red pulp" spaces you're referring are not blood vessels but, in fact, thyroid follicles that selectively absorb iodine from the blood for production of thyroid hormones and storage of thyroglobuline. So, they act as a reservoir of the materials used by the thyroid's epithelial cells, also called follicular cells, to produce thyroid hormones (T3 and T4).


Simple experimental design of a chemostat without pumps

Here is a link to a design in which electrolysis is used to generate gas which displaces liquid from the reservoir into the culture chamber, which in turn displaces culture into an outflow (where samples could be collected). The design does however require a pump for aeration, and I can't think of a way in which this could be avoided, although there is a reference cited in this article which apparently describes the use of gravity flow (I haven't checked it out).

Just for interest, this link is to a design which does require a peristaltic pump and a vacuum line but it looks to be achievable.


Do mitochondrial DNA have repair enzymes?

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


Is there a term for when a detrimental gene can be positively selected for because of linkage to a very fit gene?

Genetic hitchhiking / genetic draft

From wikipedia

  Genetic hitchhiking, also called genetic draft or the hitchhiking effect, is when an allele changes frequency not because it itself is under natural selection, but because it is near another gene on the same chromosome that is undergoing a selective sweep.

The term "selective sweep" is used improperly in the wikipedia definition. One should replace the last sentence by [..] but because it is near another allele on the same chromosome that is undergoing positive selection or if we want to reuse the term "sweep", once could say [..] but because it is near another allele on the same chromosome that is sweeping to high frequency

Selective sweep

From wikipedia

  A selective sweep is the reduction or elimination of variation among the nucleotides in neighboring DNA of a mutation as the result of recent and strong positive natural selection.


What characteristic(s) of inverse agonists allow for inhibitory effects?

The short answer is that an inverse agonist binds preferentially to the inactive state of the receptor, so it reduces the receptor's intrinsic, basal activity. The agonist was only raising the activity, not switching it on.

The most basic model of receptor pharmacology is that the receptor, $\ce{R}$, and the agonist, $\ce{A}$, are in a chemical equilibrium: $\ce{A}+\ce{R}\rightleftharpoons\ce{AR}$. In this model, the agonist bound receptor, $\ce{AR}$, generates the biological response. But in truth, this isn't a very accurate model since nothing's actually happened to the receptor. Why should $\ce{R}$ generate a biological response when it's bound but not when it's unbound? This model also wouldn't explain inverse agonists.

The del Castillo Katz model rectifies this problem by suggesting that there are two equilibria. The first is for agonist binding. And the second is for a conformational change in the receptor to an activated state, $\ce{R}^*$, that causes the biological response. Hence, $\ce{A}+\ce{R}\rightleftharpoons \ce{AR} \rightleftharpoons \ce{AR^*}$. This activated state is a different shape of the receptor, which allows a biological response. Depending on the receptor type, it could be an opened ion channel, a 7TM protein which destabilises the binding of a G-protein or more.

For many receptors (such as the GABAA receptor), the receptor can go into the active, $\ce{R^*}$, state without an agonist being bound. Hence we have the equilibrium $\ce{R}\rightleftharpoons \ce{R^*}$. This is called constitutive activity - the receptor generates some level of biological response by itself. So this shows us the chemical properties of inverse agonists. An inverse agonist binds with a higher affinity to the $\ce{R}$ form of the receptor than the $\ce{R^*}$ form. So the equilibrium shifts to the left and the receptor has reduced constitutive activity. So the drug reduces the biological effect by pulling it below the basal level. See the figure below: figure 3-1 from (Blumenthal and Garrison, 2011). NB: they opt for $\ce{R_i}$/$\ce{R_a}$ instead of $\ce{R}$/$\ce{R^*}$ and $\ce{L}$ for a generic ligand.

An agonist and inverse agonist definitely don't have the same structure otherwise they'd be the exact same molecule. They might have the same pharmacophore but they necessarily have some chemical difference that makes the inverse agonist prefer binding to $\ce{R^*}$ but not the agonist. To be honest, I'm not convinced that they even need the same pharmacophore. Although as far as I know in most cases, they do. It's not too difficult to imagine a situation where the conformational change from $\ce{R}$ to $\ce{R^*}$ moves residues in a binding pocket and prevents (sterically/electronically) the inverse agonist from binding as easily. I'm not so sure how the energy levels would work here so you'll have to get back to me on that or ask the chem/phys stackexchanges.

My crude figure below has a 7TM protein (Green) with a G protein (brown) attached. The receptor can undergo a conformational change to the $\ce{R^*}$ form (horizontally flipped) which causes the G protein to dissociate and cause some biological effect. The agonist (red star) can bind into the pocket but fits with a much higher affinity for the $\ce{R^*}$ form since the conformational change gives it a nice binding pocket. Since it fits better in the $\ce{R^*}$ state, the equilibrium shifts to the right so the G protein prefers to dissociate and the agonist introduces a biological effect.

On the other hand, the inverse agonist may fit better into the $\ce{R}$ binding pocket than the $\ce{R^*}$ binding pocket. Hence, it shifts the equilibrium to the $\ce{R}$ state, so the G protein prefers not dissociate and the biological effect is reduced.

Further reading: (Blumenthal, D. K. and Garrison, J. C. (2011). 'Pharmacodynamics: Molecular Mechanisms of Drug Action' in Goodman and Gilman. 12th ed. The Pharmacological Basis of Therapeutics) and ( Rang and Dale. (2015). 'How drugs act: general principles' in Pharmacology. 8th ed.)


When do plasmids replicate relative to its host cell cycle?

I've found a nice review that has many details on plasmid replication in general, and several papers about pSC101 in detail, and I'll try to extract the key information from these papers.

First of all your plasmid as an ori region that contains so called iteron:

  In many cases, the origin of replication contains directly repeated sequences, termed iterons, which are the binding sites for the plasmid-encoded Rep proteins and which have control properties. (...)iterons have been described for several replicons like P1, F, pSC101 (...).

pSC101 plasmid has three of these iterons present, along with a protein called rep that is necessary for replication. Besides these there are sequences that provide binding sites for host proteins such as DnaA and integration host factor (IHF).

Details of these can be found in this and this paper, both provides details on replication and the function of ori region in your plasmid.

As stated in this other paper, plasmid copy number is controlled by the plasmids themselves, that may vary on host type and growth conditions but:

  At steady state, the 1 number of replications per plasmid copy is exactly
  one per cell generation. This defines the steady state as shown in Figure 1. It should be stressed that while this is true for the population, it is not for individual plasmids-these are selected randomly for replication.

So not all plasmid copies are replicated once per cell cycle rather random ones are selected and they replicate to maintain the desired number.
When your plasmid has reached its target copy number it will adjust its replication frequency to maintain this number. This is achieved by negative control loops. There are many ways to do this (repressor proteins, anti-sense RNA) or in your case iterons. These sequence along with the rep protein may inhibit replication if too much plasmid is present by a phenomenon called  “steric hindrance" or “handcuffing”. This happens because the rep protein is capable to bind two iteron, simultaneously.
At low copy numbers saturation of iteron sequences by rep proteins initiate replication, but at high copy number rep proteins tend to interact with each other and plasmids pair up through rep-rep interactions therefore cannot replicate. See figure below:

So, long story short: plasmid replication in part depends on host factors but plasmids have means to control their copy number, and once target has been reached they maintain this number in a stable form. I know this answer does not provide solution to the when part of your question, but it provides an answer to the practical part of your problem namely: plasmid numbers are quite stable after the target number has been reached. I hope this helps

EDIT: I've found this article http://www.ncbi.nlm.nih.gov/pmc/articles/PMC210920/pdf/jbacter00181-0364.pdf that says:

  In all experiments, plasmids pSG21 (oriS only), F'lac (oriS oriV),pBR322,
  and pSC101 were capable of replicating at all stages of the division cycle,
  with no detectable differences in the patterns.

So bad news for you, because according to the paper above you cannot tell when your plasmid actually replicates. Yet still as the average copy number is quite stable due to reasons described above this may not pose a big problem. Keep in mind even if you have an extra plasmid for a short time that may still not cause problem, because transcription of your riporter gene, folding, etc takes time under which previously synthesized proteins might degrade.

However this paper says the F+ plasmid replication is cell-cycle specific, you may wan to give it a try.


How does the Golgi Apparatus perform its function?

This is actually is an awesome story: both how it happens and how it was discovered. This is one of those stories people get Nobel Prize, and this was Günter Blobel who was awarded this highest possible prize for his discovery, which is according to his Nobel prize certificate:

  "for the discovery that proteins have intrinsic signals that govern
  their transport and localization in the cell"

If you watch or read his Nobel prize lecture you will find answers to your question formulated much better than I can do it here. His Nobel lecture was opened with the following words which might already answer you question:

  Imagine a large factory that manufactures thousands of different items
  in millions of copies every hour, that promptly packages and ships
  each of them to waiting customers. Naturally, to avoid chaos, each
  product requires a clearly labeled address tag. Günter Blobel is being
  awarded this year's Nobel Prize in Physiology or Medicine for having
  shown that newly synthesized proteins, analogous to the products
  manufactured in the factory, contain built-in signals, or address
  tags, that direct them to their proper cellular destination.

Still, I recommend you to read (or watch) to the end, there are some interesting points on how it was discovered and what experiments were done to do it.


What is the difference between a mechanistic and a statistical predictive model?

Mechanistic model answers the how question. These models are usually biophysically detailed, and designed to be causal. Say you discovered a linear relation between blood pressure drug and heart rate. This would be a statistical model. It doesn't tell you how the two are related biophysically. One could build a detailed model that describes intermediate processes from the drug entering the system, to binding to receptors, and modulating levels of hormones, and acting as a signal to the heart rate modulation system. This model would have more parameters, and if it predicts the phenomena and generalizes well, then it might be a good approximation of the system. Moreover, it generates hypotheses and is more interpretable.

That being said, I do not think the two concepts are mutually exclusive. Some mechanistic/biophysical models can also be statistical at the same time. It's a matter of having enough data and constraints to be able to fit the model or not.


Do cockroaches lay eggs in human flesh when they "bite"?

No, cockroaches do not lay eggs into human flesh. You most likely received an infection of some sort from the bug, or it wasn't a cockroach.


Are fish and reptilian scales homologous?

No, fish scales are dermal (= formed in derma) bones like skull roof bones. Scales in reptiles are formed by epidermis and are made primarily of protein (from keratinocytes), being similar in derivation to hair, feather and nails.

On the other hand, in reptiles one must differentiate between scales and osteoderms (= scutes). Scutes are widespread among reptiles and they are similar to fish scales in that they are produced in derma and are ossified. Similar structures are found in some amphibians and in armadillo. Nevertheless, different types of osteoderms are currently considered as converges: "it is essential to recognize that osteoderms represent non-homologous structures that have been independently evolved a number of times" and have no direct homology with fish scales.


Whenever you look at any parameter in a population, you will have a spread. Let's take I.Q., for instance (and lets not quibble about how it's measured; it's irrelevant for our purposes):

This is the famous "bell shaped curve". You can see how few people are significantly above normal. Now, that line continues to include people with an I.Q. of 200+. That's not immediately obvious from the graph. It also continues the other way - people with an I.Q. so low that they cannot participate in their own testing. That's because the vast majority of people fall between 70 and 130.

The same principle applies to physical skill, bravery in battle, etc. The curve may be flattened or sharper depending on what parameter is being measured, but rest assured, paid professional athletes fall in the upper 1 percentile.

Lets go back to intelligence for a moment. Take someone like Bobby Fischer (Chess Player), I.Q.: 187

I guarantee you that even falling-down drunk, Bobby Fischer would have beaten me easily in a game of chess (and it's not because my I.Q. is average or below). It's because he was so very much, unimaginably better at chess than I am.

I guarantee you that even falling-down drunk, Albert Einstein could solve mathematical equations I can't even write. It's because he was so very much, unimaginably more intelligent than I am.

It's the same with great athletes. Even if they drink every night, a great athlete will outperform you or me on any given day.

That's why you are just dead wrong when you state "then it couldn't have been consumed by highest-ranking athletes, as alcohol-consuming athletes could never rich the heights of the tops of proffessional sports".

You are just laboring under a completely false premise. These people are so much better than people only 1 percentile below them that drinking doesn't necessitate that they fall in the ranks.


What are these tiny creatures swimming around my aquarium?

Hard to tell because of the poor picture/video quality, but almost immediately the body shape, distinct "face", size and behavior made me think of a small invertebrate animal called a rotifer (Phylum Rotifera).

 Rotifer eating protists. Photo Credit: Jacqueline Ronson, 2016
There are about 2000 species occurring worldwide within this primarily freshwater phylum, each of which is fairly simple anatomically. Their name (which means "wheel bearer") comes from the two crowns of quick-moving cilia they possess on their heads:

 Source: Gifer
These cilia attempt to push food posteriorly toward the rotifer's back-set "mouth" (which is actually a modified pharynx called a mastax:

 Photo Credit: Jean-Marie Cavanihac
Rotifers are small (always < 2 mm) and so eat small planktonic and protist prey. From UC Berkeley:

As rotifers are microscopic animals, their diet must consist of matter small enough to fit through their tiny mouths during filter feeding. Rotifers are primarily omnivorous, but some species have been known to be cannibalistic. The diet of rotifers most commonly consists of dead or decomposing organic materials, as well as unicellular algae and other phytoplankton that are primary producers in aquatic communities.

As for body shape:
Although all Rotifer species are bilateral animals, they vary quite a bit in body shape. Box-like shaped rotifers are referred to as being loricate, while more flexible worm-shaped species are considered to be illoricate.

 Photo Credit: Juan Carlos Fonseca Mata
Regarding sometimes staying "rooted at the tail" as the OP observed:
Some rotifers are found usually free-swimming, while others "glue" down their posterior "toes" to anchor themselves to some substrate or debris. Again from UC Berkeley:

The final region of the rotifer body is the foot; this foot ends in a "toe" containing a cement gland with which the rotifer may attach itself to objects in the water and sift food at its leisure.

 Source: Starr et al. 2013 (Cengage Learning)
See here for further "fun facts!"


Green feather-like formations in tap water - what is it? (with pictures)

I have had a biologist out taking some samples of the water. She examined them in a microscope, and identified the algae as blue-green algae/cyanobacteria. She could not identify the species further.

She said the reason probably was that my pipes where exposed to sunlight, and also that the pibes with hot and cold water ran too close to each other, creating a nice lukewarm temperature for the algae to thrive in.

I'm of course going to change the pipes :)


Why the length constant of passive current flow isn't depend on the membrane capacitance?

Length constants are defined in the 'steady state' regime of constant voltage; capacitance is important for time-dependent electrical functions but disappears in the steady state.

In a real neuron, where you have other time-dependent (dynamic) features like ion channel opening, time constants and length constants interact to determine how current flows in a length of neurite, as you intuit, but these passive properties by themselves are insufficient to describe that behavior: you need to also consider ion channel gating and conductances.

See also https://en.wikipedia.org/wiki/Cable_theory - note how the capacitance is always multiplied by a changing voltage dV/dt in the differential equations.


Why does mint oil feel cold on the skin?

Anything related to mint usually contains menthol. What does it do? It triggers the TRPM8 ion channels, causing your skin's cold receptor to become sensitive, and causing it to overfire.

This causes the brain (receiving cold signals from skin) to feel cold, and that's why you feel cold.

I have summarised it in a few sentences, but as with any scientific discovery, it took quite a few years to fully understand what was going on. NCBI have summarised this quite nicely over here (http://www.ncbi.nlm.nih.gov/books/NBK5238/)


Which strand of a gene specifies a protein?

If a piece of DNA were to be transcribed on both strands, at the same time, the transcription complexes would collide and inhibit each other, like steric hindrance.

If you could overcome this interference and synthesize primary transcripts from both strands, it follows that the two RNAs would hybridize to each other and form complementary RNA-RNA hybrids.  These dsRNAs are very poor substrates for translation by the ribosomes. This was the initial mechanism proposed for anti-sense RNA to down regulate gene expression.

In many, if not most, EUKARYOTIC cells, a dsRNA will trigger the siRNA/shRNA/miRNA response mediated by Dicer et al. leading to degradation of both RNA strands.

So in virtually all instances, only one strand will be transcribed, and encode a mRNA with a significant ORF.


How much percent of image does our eyes focus at any instant?

What you learned in high school isn't exactly true (or is misremembered). Human eyes get visual input across about 120 degrees of visual angle, and some herbivore mammals see near 360 degrees total between their two eyes.
However, the resolution is not constant. The fovea is an area of high-density receptors in the retina. When you look at something specific, you are directing light from that area of the visual field to the fovea. The fovea is limited to about 2 degrees of visual angle.
Additionally, your attention is often limited to a small section of the visual field. When viewing a scene, your eyes will naturally make saccades to bring various points into high acuity vision to get a good sense of the entire scene, but you are still seeing all the surrounding area, even if you aren't paying much attention to it. Importantly, you are still sensitive to surprising stimuli (especially those that are high-contrast or moving) in those areas that might cause you to redirect your attention, otherwise you would be very easy to sneak up on.


Why apes started to contemplate and become altruistic?

I think this is a difficult question all around, which is why its a little uncomfortable for some to be entertaining questions which are often seemingly metaphysical in nature.

I think also that it is true that biology and neuroscience will have a big impact on the question, its also fair to say that the jury is still out on this question.

The genetic anthropologist Svante Paabo is one of the most engaging researchers in this question.  He started out studying the difference between the human gene sequences and the chimpanzee to try to suss out the specific genes which might be be responsible for out social selves.  So from this point of view, it might be that intelligence started at most about the time of human chimp divergence, 8-25 million years ago.

Finding the specific genetic structures that convey our unique cognitive or social abilities would certainly pinpoint that time much more accurately.  There is just 1-4% difference between the chimp and human genome sequences (depending on how you calculate it), but even 1% of a 5 Gb genome is a lot of differences and no intelligent mutant chimp has been found (that they've told us about!) .

Since then, a lot of interest has focused on assembling a complete Neanderthal genome sequence.  Since Neanderthals diverged from humans about 500k years ago, and there's plenty of evidence that they were intelligent, comparing the three genomes (human chimp and neanderthal) would help pinpoint the specific genetic elements which are distinctly human.

If it is a mutation or set of mutations as the current thinking implies, there is a good chance that it is a combination of strong selection and accident.  Its true that cooperation is often enjoys a strong selective advantage, but it doesn't make you smart or hospitable.  When we talk in biology we don't say altruism, we say cooperation.  If such cooperation happened only because of selection, we would see such behavior in other primates.  So if we see this, I would lay odds to look for a rather complicated story...

Another interesting person to read is anthropologist Terrence Deacon, who is trying to understanding the terms with which we define intelligence.  About ten years ago there were actually experiments that showed that chimpanzee some strong candidate intelligence genes related to cognition could be put into people (who needed gene therapy because they had lost cognitive function) and restore that function.  Apologies, this is anecdotal - i saw him give a great talk, but he's moved on a bit and can't find the references.

This is important I think because the fundamental definitions of human intelligence have failed over the years, from the old chestnut of using tools, to a recognition of mortality, to awareness, animals have surprised us, particularly primates.   I wonder whether we will be able to confirm these vital factors until we get a monkey asking for the keys to the car so that they can go get some pizza.


What's the meaning of 'plasma' in 'plasma membrane'?

I thought it was a no-brainer, apparently it's more of a historical journey into the origins of Botany. But I have a hypothesis: During the debate of whether the cell or the fluid within it was the origin of life, that fluid was called 'protoplasm' - first formed, i.e. it's the origin of life. The plasma membrane, then, is simply that which surrounds the 'plasma' - the protoplasm.


Does the light color spectrum and frequency matter for photosynthesis?

It matters a lot.
Take a look at this graph:

This graph is for the "normal" plants containing chlorophyll.

There're also "abnormal" :-) ones, simple water plants and cyanobacteria, that contain various phycobilins for photosynthesis instead of the chlorophyll.

If your question is practical, I'd recommend using specialy-designed fluorescent lamps called grow light.


Are a bonsai tree and its normal version the same species?

Yes. For any species that it is possible to grow as a bonsai tree, it is also possible to grow that species as a non-bonsai tree. The process of creating a bonsai tree involves growing a tree in a severely restricted pot with a minimal amount of soil, and trimming both the roots and branches to maintain a desired shape and size. It is the small growing space and regular pruning which keeps bonsai trees small, not the genetics of the tree.

You may wish to check the list of species used in bonsai on Wikipedia to get a sense of which species make good bonsai plants.


Do Traits Have to be Adaptive in Order to Survive?

Good question. And good analysis. I have little to add! I'll simply provide my own list of thoughts to complement your ideas, which are not mutually exclusive.

  The fact that it wasn't discarded during the course of the species'
  evolution suggests it must have offered some benefit.

This statement is speculative. The key word here is suggests. i can think of several speculative scenarios, of course the list is by no means exhaustive:

Traits that are not adaptive can still exist in the organism as vestigial traits. This can be because the trait was recently useful but no more, over evolutionary time scales, and not enough time has passed for the trait to be lost.
The trait may also be floating, i.e. has not been selected against, and acts as a neutral trait. It therefore remains as a phenotype. Traits are theoretically unlikely to float for very long periods of time, as I will describe later.
Some traits can very indirectly affect other traits. In practice it is often difficult to completely describe or understand which traits are a result, or cause, of other traits.
Many traits can also be byproducts of other useful traits. With nipples it might have something to do with early exposure to hormones; developing a way to bypass male nipple formation could be difficult and costly. With psylocibin, it may be a side-effect of a particularly useful biochemistry to the fungus, perhaps metabolic, that is completely unrelated to its neuroactivity in humans. It may be that a biochemical pathway might form psychoactive intermediates or products that are difficult to remove or metabolize, and find themselves in the mushroom co-incidentally.
The trait may simply be very useful, but we don't understand why it is useful. Humans often overlook this possibility; for instance, I assume you have not considered that psylocibin may have unknown effects on non-human or even non-vertebrate life.
I am not an expert but filamentous fungi sometimes/often have very complicated sexual reproductive strategies. Psylocibin may be maintained through sexual selection, rather than natural selection. This is probably far fetched, but hey- we're speculating about our ignorance.
Lastly, but very importantly, all organisms face pressure to survive and replicate. It is expensive to maintain useless features and traits, or to produce excesses, or to overdevelop or harbor chemistry that is not doing anything. Natural selection is ever-active in limiting in which traits are maintained within a population. This I think is the most convincing argument; the principle of economy. This argument fares well in all discussions on biology; life is difficult, and the costs of survival are very important to consider, always. It is expensive to store or maintain constituent chemicals, even if they are not toxic, nor if they have no use for the survival of fungi. It is more economical, and less costly, to lose such traits; selection will favor fungi that save or spend this energy elsewhere. This is a very important point, and I think it is the most salient to understand the quote you provide.

I think it would also be a good idea to study the number of times psylocibin arose. If it occurred ('was invented') multiple times independently, it must have had some functionality for the organism, like wings, or vision. If it occurred only once, one can ask whether the majority of descendant strains has lost it, or whether they maintain the trait. That could also shed some light on whether it is maintained through positive selection. Lastly, psylocibin may be a chemical that allows to explore a very specialist niche of the ecosystem. If few descendant strains contain it, that can mean it is still selected for, though only by fungi that rely on it as a strategy. This would also mean that psilocybin-less fungi would have found no need to maintain it, and may point to the occurrence of negative selection. Hope that makes sense.

Mandatory reading for you on relaxed selection.

tl;dr yes, psylocibin may be maintained by happenstance, though likelier via positive selection, at least in specialist fungi


Why are vertebrae, specifically, so important in classification?

Short answer
The term vertebrata stems from grouping animals according to obvious gross anatomical distinguishing features as typically used in the early days of taxonomy. However, from a phylogenetic point of view, the presence of the neural crest during embryonic development, which is unique to this subset of animals in the phylum chordata, is a much more important distinguishing feature than the presence of vertebrae.

Background
Vertebrates belong to the phylum chordata, but share some characters that make them unique. Chordates, with a few exceptions, are active animals with bilaterally symmetric bodies that are longitudinally differentiated into head, trunk and tail. The most distinctive morphological features of chordates are the notochord, nerve cord, and visceral clefts and arches.

Vertebrates feature neural crest cells, which sets them apart from any other group. These cells appear early in development, and only vertebrates have them. Neural crest cells form the skull and jaw bones.

The neural crest has sometimes been called the fourth germ layer because of its importance (Fig. 1). The neural crest cells produce a variety of  cell types, including (1) the neurons and glial cells of the sensory, sympathetic, and parasympathetic nervous systems, (2) the epinephrine-producing (medulla) cells of the adrenal gland, (3) the pigment-containing cells of the epidermis, and (4) many of the skeletal and connective tissue components of the head (Gilbert, 2000).

Fig. 1. Regions of the neural crest. The cranial neural formt the bones and cartilage of the face and neck. It also produces pigment and cranial nerves. The vagal neural crest (near somites 1–7) and the sacral neural crest (posterior to somite 28) form the parasympathetic nerves of the gut. The cardiac neural crest cells arise from the neural crest by somites 1–3. Neural crest cells of the trunk (about somite 6 through the tail) make the sympathetic neurons, and a subset of these (at the level of somites 18–24) form the medulla portion of the adrenal gland. Source: Gilbert (2000)

In all, the term vertebrates is just a reflection of an apparent and obvious marker of this group of animals, namely the presence of vertebrae, but their distinguishing most important feature is the presence of the neural crest during development.

Reference
- Gilbert. Developmental Biology, 6th ed. Sunderland (MA): Sinauer Associates (2000)


Wikipedia tells us the following about the larva of the oleander hawk-moth (Daphnis Nerii):

  Just before it pupates, the oleander hawk-moth larva becomes browner in color. The pupa of this species measures around 5.5 to 7.5 centimeters in length, and is light brown with black spots and a black line down the middle

The stage your critter is in probably resembles Fig. 1. It's probably fine.

Fig. 1. Caterpillar just before pupating. source: wikipedia


Is it more likely that the very first living organisms had a linear genome?

It is hard to give an answer to this question that is not just speculation.  We can be reasonably confident that the most recent common ancestor of bacteria and archaea had circular genomes.  However, we currently have no way to get any conclusive evidence earlier than that.  3 billion year old DNA doesn't fossilize.  So it's just speculation what DNA looked like back then.

On the other hand, my understanding is that most experts think that RNA genomes predated DNA genomes.  These RNA genomes would be linear.


Why use a logarithmic scale when plotting pharmacodynamics/kinetics?

There could be several reasons for this. You mention in the comments that your plot of interest is the concentration-time profile. As you can see, plotting the logarithm of concentration vs time yields a very different plot for a drug administered intravenously.

The reason this is done is because the two plots yield different information. The slope of the log(C) vs t plot actually yields the elimination constant, Ke. The logarithmic plot can also be used to assess if the drug is distributed into one or more compartments. If the drug is distributed into two or more compartments, the initial slope would be different than the remainder (but this is not pictured here).

In terms of pharmacodynamics, its often useful to assess how a 10- or 100- fold increase in concentration affects the effect.


Like these questions :) Many of these illusions come from Prof. Akiyoshi Kitaoka, a japanese Psychologist and expert for Gestalt Psychology. On his website you'll find some more fascinating illusions and questions to ask here ;)

The illusion above is named Cafe Wall illusion and the newest model to explain those illusions is the contrast-polarity model. Short explanation from his webpage:

The paper explained it better to me:

  Kitaoka, Pinna, and Brelstaff (2004) proposed a phenomenal model to
  explain the Café Wall illusion, which stressed the importance of
  contrast polarities of a solid square and its adjacent line segment.
  When a dark/light square is accompanied by a dark/light line segment,
  the apparent tilt is the direction of contraction of  the square angle
  (Figure 18a,b). In contrast, when a dark/ light square is accompanied
  by a light /dark line segment, the apparent tilt is the direction of
  expansion of the square angle (Figure 18c,d).

This explains why you perceive a tilt. If you position the smaller squares now in distinct edges of the big squares, you can achieve 2- and 3-dimenional illusions. Here you see a increasing of the tilt due to more smaller squares:

Here you can see that the positioning of the smaller squares is critical to achieve the 3D effect of the orignial bulge effect in your question:

Notice that Gestalt Psychology is a non-reductionistic theory approach and investigates mainly the phenomenology and underlying Gestalt Laws of visual perception. How these Gestalt Laws developed on a deeper level is a question of neurobiological evolution similar to, "why have some species of apes color-vision and some not". The ellipses in the explaining picture above show you, that our cognitive visual machine somehow tries to group divided objects (square and line of same contrast/brightness) in one line and we see a tilt. I'm guessing here, but this is probably due to cognitive brain algorithm that saves things and objects we see and perceive mainly by countor and shapes, rather than pixel by pixel like a computer and digital camera do it, which of course don't perceive any tilt or 3D illusion in any of those trick images :)

Read the papers for more explanations and examples, not behind a paywall:

Apparent contraction of edge angles, A Kitaoks, Perception, 1998
Tilt illusions after Oyama (1960): A review. Kitaoka, A,  Japanese Psychological Research, 49, 7-19.


Why is ATP hydrolysis to ADP, rather than ADP hydrolysis to AMP, used to drive biochemical reactions?

Summary

The original question was edited — with the approval of the poster — so that in brief it now asks:

  Why is ATP hydrolysis to ADP, rather than ADP hydrolysis to AMP, the
  normal way in which cells drive reactions which alone involve positive changes in Gibbs
  Free Energy?

The scope of this is wider than that originally assumed in the answer from @user1136, but he has also contributed to this answer by his comments, which I have incorporated into my revision.

To my knowledge there is no generally-accepted provable answer to this question (as opposed to listing advantages for the system as it works today). What I shall do is present a hypothesis that could explain this situation. The fundamental idea† of this is that:

  The contemporary use of ATP rather than ADP in energy transfer
  reactions evolved from a preference for NTPs, rather than NDPs, as the
  precursors of RNA synthesis. This preference was a result of the fact
  that the conversion of NTPs to NMPs and pyrophosphate could prevent
  the reversal of this (and other) synthetic processes in a way that conversions  liberating phosphate could not.

AMP, ADP and ATP: Standard Free Energies of Hydrolysis

There is general agreement that the values for ∆G°′ (standard free energy change at 37˚C) for the hydrolysis of the terminal phosphate bond of ATP (β-γ) and ADP (α-β) are similar. (The following are from J.L. Jain, et al.:

ATP → ADP + Pi  –7.3 kcal/mol
ADP → AMP + Pi  –7.3 kcal/mol

Hence, there is no intrinsic energetic difference that might explain the preferential use of ATP over ADP as an ‘energy donor’ in biochemical processes, i.e. it is not evident why e.g.:

  Glucose + ATP → Glucose 6-phosphate + ADP

and not

  Glucose + ADP → Glucose 6-phosphate + AMP

And, as @user1136 mentions, there are examples where the energy of the hydrolysis of ADP to AMP can be used to ‘drive’ other reactions. He mentions polynucleotide phosphorylase, to which I would add  adenylate kinase, as this is not a synthetic process and is pertinent to the energy metabolism of nucleotide phosphates:

  ADP + ADP ⇄ AMP + ATP

The introduction of AMP into the discussion raises the question of the value of the ∆G°′ for the following reaction:

ATP → AMP + PPi

Many texts quote a value only slightly greater (ignoring the minus sign) than those for phosphate release (the one cited quotes –7.7 kcal/mol), but a 1995 review of the situation in the Journal of Biochemistry suggests that the difference is actually greater: –10.9 kcal/mol, as opposed to –7.8 kcal/mol for the hydrolysis of ATP to ADP and Pi.

The relevance of this is considered in the next section.

Biosynthetic processes and ATP

It seems to me that the example of polynucleotide phosphorylase is especially pertinent because it is a biosynthetic process in which the nucleotide monophosphate is actually incorporated into the product.

  [AMP]n + ADP → [AMP]n+1 + Pi

However this ADP-driven non-template dependent synthesis of polynucleotides is not model for template-dependent RNA synthesis, one reason being that it can also operate in the reverse direction as a phosphorolytic 3ʹ to 5ʹ exoribonuclease reaction:

  [AMP]n+1 + Pi → [AMP]n + ADP

Irreversibility is an important feature of template-dependent synthesis of RNA¶, and it is thought that the key to this is that fact that ATP is the substrate and is cleaved between the α and β phosphates liberating pyrophosphate rather than monophosphate.

  [NMP]n + NTP → [NMP]n+1 + PPi

The reason generally proposed to explain why this reaction is irreversible is that in the cell pyrophosphatase hydrolyses the pyrophosphate to phosphate in an exothermic reaction. However the problem in evolutionary terms is that pyrophosphatases would have to evolve before this would work. However, if the ∆G°′ for pyrophosphate release has a greater absolute value than that for phosphate release, this in itself would affect the equilibrium of the reaction in a manner favourable to synthesis, albeit at the greater effective cost of an extra ATP. The later evolution of pyrophosphatases would have served to reinforce and enhance the irreversibility.

The Hypothesis

The hypothesis is that nucleoside tri-phosphates developed early in evolution to provide a means of making nucleic acid synthesis essentially irreversible by a mechanism that generated pyrophosphate. As the example of polynucleotide phosphorylase shows, nucleoside di-phosphates do not allow this.

A priori it would seem that there is no reason why ATP rather than ADP should be preferred for coupling biochemical reactions. However, if one accepts the argument that ATP synthesis was required for nucleic acid synthesis, there would seem no reason for having a set of reactions generating ADP for other purposes. The energy of hydrolysis of ATP to ADP in such reactions would, in any case, have to be utilized, otherwise it would represent a net loss. Why go any further?

It may have been that ATP was preceded in evolution by an an earlier ‘energy donor’. However I would suggest that once a mechanism evolved for synthesizing and using ATP (and other NTPs) for synthetic purposes, it was more efficient to use this for metabolic purposes, largely displacing any previous energy donor molecule.

† Footnote 1

I have touched on this very tangentially in my answer to a quite different question about ATP. The common idea, however, is that the purine and pyrimidine rings of NTPs serve no purpose in energy transfer, but are a relic of their requirement in RNA synthesis, where the NTPs are not merely providing energy, but are incorporated into the RNA product.

¶ Footnote 2

RNA and DNA synthesis are not the only synthetic processes in which this strategy for irreversibility is adopted. The tRNA amino-acylation reaction — essential for protein synthesis is as follows:

  Amino Acid + ATP → Aminoacyl-AMP + PPi

And the first step in glycogen synthesis is the formation of UDP-glucose:

  Glucose 1-phosphate + UTP → UDP-glucose + PPi


What is the minimum number of clades necessary to partition Vertebrates while maintaining the classical groups of Birds, Mammals, and Amphibians?

Phylogenetic taxonomy of the Vertebrates (mun.ca) has the following graphic (14 clades total, minimum of 12 collapsing Amphibia):

Here, what was preivously 'Fish' (the paraphyletic group of non-tetrapod vertebrates) becomes 6 clades, and 'Reptiles' (the paraphyletic  group of non-avian Sauropsids) becomes 3.

It seems the question is equivalent to asking "what is the minimum number of clades necessary to partition Vertebrates while maintaining 'birds' as a clade?".


How do mutations with very little fitness benefit get fixed?

In the long run (over hundreds or even millions of generations), small statistical advantages are bound to accumulate.

Even if a mutation gives only a +1% average reproductive advantage, it is still above chance and therefore this mutation is more likely to spread through the population.
(If you can code, I have found it to be an interesting exercise to write scripts that simulate generations of evolution.)

It is also not necessarily true that effects of mutations have to be small. Single mutations can be deadly, they can change colors, create large morphological changes, and so on. It just happens to be the case that most mutations that have large effects are deleterious, and therefore won't generally spread for long throughout the population. But some mutations will be beneficial and therefore have improved odds of being passed on.


How T-Cell recognizes a cell infected by a virus?

All cells chew up internal proteins all the time - it's part of the normal activity of cells to recycle those proteins into amino acids to be rebuilt into other proteins. The first step is chopping up the protein into peptides by the proteasome.
When a virus infects a cell, one key thing it needs to do to replicate is to have the cell start making viral proteins. However, some of these get chewed up, too.
Some of the peptide fragments get bound to major histocompatibility complex class 1 (MHC-1) molecules. These are then transported to the cell surface. This is the cell advertising "hey, this is what I've found in the trash lately."
Sort of like antibodies, T-cells only bind certain antigens, and during development the immune system learns which antigens are self versus foreign by process of elimination: if you detect it during development, it must be yours. Everything else is fair game to attack. When a killer T-cell binds strongly to the MHC-1:peptide complex, it recognizes that this is a foreign peptide and the cell presenting it must be infected or damaged in some way, and this starts a cascade that leads to apoptosis of the infected cell.


Does any one know which species of insect is this one?

That is a male dobsonfly. I know this is a male because it has long mandibles which are used in mating. Female dobsonflies have short mandibles. larval dobsonflies are called hellgramites,and it really hurts a lot when they bite you.Look here https://en.wikipedia.org/wiki/Dobsonfly or here entnemdept.ufl.edu/creatures/misc/eastern_dobsonfly.htm


Cellulose acetate membrane filters vs. glass microfiber filters

It would also depend on the pore densities and pressure resistance.
Silica is used for gel filtration chromatography to separate proteins. This can be achieved when proteins do not have affinity to silica, and most of proteins could be analyzed with silica gel. Silica and grass are similar materials. However, glass and silica have negative charges on the surface. Under low ionic strength condition, positive charged proteins or positive charged surface of proteins may bind to glass. Cellulose acetate does not have charge but it is hydrophilic.


Cyanobacteria: Gram negative or Gram positive?

Cyanobacteria are clearly didermic (two membranes, inner and outer) bacteria, normally classified as Gram-negative bacteria. If your textbook says several times that they are Gram-positive, instead of a typo, you have a plain mistake.

However, things are not that simple.

According to Hoiczyk and Hansel (2000), this traditional classification of the prokaryotic envelope doesn't work well with cyanobacteria, whose cells show a combination of the features of Gram-positive and Gram-negative bacteria:

  The multilayered peptidoglycan of gram-positive bacteria, with a thickness ranging from 20 to 40 nm, usually forms a physical barrier for the dye. In gram-negative bacteria, however, with their relatively thin sacculus of 2 to 6 nm, the stain can easily be washed out. Together with other characteristics, such as the occurrence of accessory cell wall polymers or the presence of an outer membrane, the peptidoglycan architecture largely determines the different properties of the two cell wall types in terms of mechanical stability, permeability, and resistance toward chemical substances. Although this classification is generally useful, it oversimplifies the concept of bacterial cell walls. It also ignores, for example, that the largest and perhaps most diverse group of bacteria, the cyanobacteria, possess cell envelopes with a combination of these features. (emphasis mine)

Here is an image (ibid.) comparing a Gram-negative cyanobacteria with Escherichia coli:

Electron microscopical comparison of the gram-negative cell envelopes of the cyanobacterium P. uncinatum (A) and E. coli (B). Both bacteria were identically processed using cryosubstitution procedures. Note the combination of gram-positive and gram-negative features present in the cyanobacterial cell wall, like the thick peptidoglycan layer and the outer membrane, respectively.

Hoiczyk and Hansel (2000) add that...

  ... Despite their overall gram-negative structure, the peptidoglycan layer found in cyanobacteria is considerably thicker than that of most gram-negative bacteria. (emphasis mine)

In conclusion, cyanobacteria are Gram-negative bacteria. However, their envelope show some features os Gram-positive bacteria. Besides that, there is variation withing the group.

Source:

Hoiczyk, E. and Hansel, A. (2000). Cyanobacterial Cell Walls: News from an Unusual Prokaryotic Envelope. Journal of Bacteriology, 182(5), pp.1191-1199.


As others have mentioned poly-A seems to be favoured because of higher concentrations of ATP with respect to other NTPs, due to its ubiquitous role. There is no real proof for this like most "why" questions. However, the ubiquitous presence of ATP is itself an evidence for a random selection of ATP and a subsequent expansion of its role. There is no thermodynamic explanation for this. The selection is likely to have been random.

Polyuridylation is also known to happen in eukaryotic cells (reviewed by Munoz-Tello et al., 2015) and one of the well known cases is that of the let-7 pre-miRNA (Heo et al., 2008). Polyuridylation marks this pre-miRNA for degradation.


Why does protein kinase C activated by different means have different effects?

You probably remember correctly — at least in part. The part that is missing is that protein kinase C isn't just one enzyme, but perhaps a dozen different isoforms that fall into three different classes, differing, among other things in their requirements for activation (e.g. whether they require calcium ions as well as diacylglycerol). It would be theoretically possible for protein kinase C activated by one pathway to have different effects from that activated by another if the different isoforms involved had different properties. This has indeed been suggested, although it has been difficult to establish experimentally.

The following two reviews that deal with this are about 20 years old, but may allow easier general access (and are easier to read):

Dekker, L.V. and Parker, P.J. (1994) Trends in Biochemical Sciences vol 19 pp 73–77.

Jaken, S. (1996) Current Opinion in Cell Biology, vol 8, pp 168–173.

The following quotation from the summary of a more recent and more extensive review article (Steinberg, S.F. [2008] Physiol. Review. vol. 88 pp. 1341–1378) may be pertinent:

  "There is growing evidence that individual PKC isoforms subserve unique (and in some cases opposing) functions in cells, at least in part as a result of isoform-specific subcellular compartmentalization patterns, protein-protein interactions, and post-translational modifications that influence catalytic function."

One other feature of protein kinase C is relevant to this question. Most other protein kinases (which tend not to have multiple isoforms) have a more or less restricted substrate specificity determined by residues of a particular type at particular positions with respect to the phosphorylation target residue (Ser, Thr or Tyr). This limits the proteins the kinases act on to specific targets. In contrast, protein kinase C can phosphorylate target residues in a wide variety of contexts. The current model (above) allows specificity of protein kinase C for target proteins to be obtained in a different way — by the specific proteins that each activated isoform binds to, i.e. by protein–protein interaction rather than target-site context.


Co-transformation of plasmids from the same incompatibility group

It turns out that there doesn't seem to be a specific mechanism to prevent multiple incompatible plasmids from coexisting.  Velappan et al put in more than one incompatible plasmid with different selection genes in them and put the bacteria on a single antibiotic and periodically checked for the second vector (by testing for  second antibiotic resistance).  It apparently took weeks for the second vector to disappear - many generations.

Higher copy number plasmids did better, with longer times to lose the second plasmid.  They seem to conclude that its just the natural rate of loss of plasmids that will cause the bacteria to lose the second plasmid without selection.  I imagine with two antibiotics in the culture it would take some months and you could potentially store the bacteria at -80C indefinitely.  Still in most experiments its going to be an additional headache where compatible origins of replication seem to have a more typical half life for retaining the plasmids.

They also state that the frequency of double transformations is more frequent than is usually appreciated, which seems to imply that you will get some colonies from a typical high efficiency transformation from plasmid preps.  However, they introduced the multiple plasmids by phagemid infection rather than transformation in this study.


The answer is logical if you understand the reasoning behind Hardy-Weinberg. I recommend that you to have a look at the post Solving Hardy Weinberg problems and try to answer the question yourself. Once you've done that, you can hover over the yellow zone below for the answer to compare against what you've understood.

The answer:

   If the assumptions of Hardy-Weinberg are respected (see Assumptions of Hardy-Weinberg rule), incl. random mating, then a population is back to Hardy-Weinberg equilibrium at the beginning of any single generation. H-W equilibrium is directly caused by the random sampling of gametes. This random sampling is happening at every single generation and therefore a single generation is enough to get back to H-W equilibrium.


What is the acceleration profile of the greyhound?

I'm going to try to break this up a bit to address your sub-questions. Most of it is summarized from Williams et al 2008--and almost all of the work I'm referencing comes from the Royal Veterinary College Structure and Motion Lab.

Acceleration Profiles:

So, I can't find an acceleration curve over time for these, but we do know about the potential acceleration range for greyhounds and cheetahs. Greyhounds can reach a max speed of about 17 m/s (Usherwood and Wilson 2005), cheetahs can reach up to 29 m/s (Hudson et al. 2010). Cheetah stride-averaged accelerations have been measured up to 120 W/kg --they can speed up by 3 m/s over a single stride, and slow down by up to 4 m/s (Wilson et al. 2013). Racing greyhounds have achieved 60 W/kg (Williams et al. 2009).  Maximum acceleration decreases with increasing speed

How Land Animals Can Be Fast

Augmentation or hypertrophy of proximal musculature. More than a fifth of a greyhound's limb muscle mass is associated with the proximal portion of the hindlimb (Williams et al. 2008). Muscle power (work/time, important for acceleration) is roughly proportional to muscle volume, so bigger muscles are better in this case.  In cheeetahs, a similarly large muscle mass is devoted to hip extensors (though different specific muscles; Hudson et al 2010). Big muscles = high power and high force production.  In addition, sprinting mammals tend to have longer muscle moment arms than non-sprinters--so they can produce greater torques for a given force.
Longer muscle fascicles. This may also be an adaptation for power output. Greyhounds have longer fascicle lengths in their hamstrings than your average domestic dog (Williams et al 2008), and human sprint athletes also have longer fascicle lengths than endurance runners (Abe et al. 2000).
Long limbs and flexible spines: Longer limbs w/ spinal flexion = greater stride length--and cheetahs have particular elongated hind limbs. A long hind limb also lets cheetahs maintain foot contact with the ground for longer, so lower peak forces are required.

These aren't nearly all of the things involved, but I suppose this is a start.

References:

Abe, T., K. Kumagai and W.F. Brechue. 2000. Fascicle length of leg muscles is greater in sprinters than distance runners. Med. Sci. Sports. Exerc. 32: 1125-1129.
Hudson, P. E. et al. 2010. Functional anatomy of the cheetah (Acinonyx jubatus) hindlimb. J. Anat. 218: 363–374.
Usherwood, J. R. and A. M. Wilson. 2005. No force limit on greyhound sprint speed. Nature. 438, 753-754.
Williams, S.B. et al., 2008. Functional anatomy and muscle moment arms of the pelvic limb of an elite sprinting athlete: the racing greyhound (Canis familiaris). J. Anat. 213:  361–372.
Williams, S. B. et al. 2009. Pitch then power: limitations to acceleration in quadrupeds. Biol. Lett. 5: 610-613.
Wilson, A. M. et al. 2013. Locomotion dynamics of hunting in wild cheetahs. Nature. 498: 185-189.


Can Anyone Identify This strange cockroach looking bug

That is a mole cricket. Family Gryllotalpidae. They generally live underground, but as you noticed, they can fly. https://en.wikipedia.org/wiki/Mole_cricket


Species identification - what kind of worm is this?

This is almost certainly not a millipede as it has no antennae and moves by compressing its body. My money is on insect larva, possibly a drain fly (which would make sense if you regularly see them in the bathroom).

It would be interesting if you could put one in a jar and see what it develops into.


How many honeybees are there, and how has the number changed across time?

1 billion hives
(at 10,000-50,000 bees/hive this is 10-50 trillion bees)

Managed: 100 million hives

Based on country-level data from FAO, supplemented  for a few countries with Apiservices, in 2011 there were about 80 million managed hives. Because FAO lacks any data for some countries, and other countries under-report (for instance US figures don't include hives kept for pollination service and hives kept by small-scale operators) a reasonable round estimate of managed hives in the world is 100 million. (This implies a 128% correction to the FAO numbers). (Aizen and Harder 2009 give context on FAO figures).

Wild/Feral: 900 million hives

Wild/feral hives of Apis mellifera are difficult to count via direct observation. Jaffe et al 2010 use a genetic sampling method, and also report a reasonably strong correlation between the total number of hives (managed and wild) per square kilometer and the mean annual temperature of the area.
I used the best fit line from their data to estimate the "hive-carrying-capacity" by country using (the admittedly very general) land area and mean annual temperature. Then I subtracted the number of managed hives from the carrying capacity to estimate wild hives.

Although this formula probably overestimates large, cold countries and underestimates Africa (the formula gives 211 million feral hives in Africa when literature suggests closer to 300 million), in general, it seems to give not unreasonable estimates in comparison to the literature. Globally, this formula gives an estimate of 984 million wild hives. Given that land area included desert and other unsuitable habitat, it seemed reasonable to round down, and I took 900 million as my estimate.

Historical Populations

1961-2011
FAO statistics date to 1961. I plotted their numbers, with the 128% correction for each year. I assumed that during this time the number of wild bees has remained virtually unchanged, at 900 million, because it was defined by mean temperature and land area, which have not changed.*

1650-1961
This period represents the globalization of Apis mellifera. Before 1600, there were no European honey bees beyond their native range (Western Eurasia and Africa). However, once established in new areas (the usually cited first beehive in the USA in 1622), Apis mellifera rapidly spread in both managed and feral populations, in North America (17th c), South America (18th c), Australia (19th c) and East Asia (20th c) (Crane 1999)
.

I used carrying capacity of native range countries (just about 35% of the carrying capacity of the globe, or 350 million hives) as a before-1650 estimate,  and then assumed a geometric increase of about 2% per decade in available land area (ALA), as Apis mellifera bees and beekeeping made their way around the globe.

To estimate the number of managed bees during this period, I assumed a human:hive ratio of 35:1**, and modelled hives based on historical estimates of human population, multiplied by the ALA for the decade. The 1650 estimate was 5 million managed hives.

*Although diseases, pests, and pesticides have been reported to affect feral populations, I didn't find any solid information on this. For instance, feral populations of Apis mellifera mellifera and A. m ligustica have been widely reported to be in decline in the USA, but at the same time, feral populations of Africanized honeybees (Apis mellifera hybrids) have been rapidly spreading. Even with 90% losses in the USA, Canada, Japan, and Europe (areas affected by varroa) my estimates would only be decreased about 10%. However, it's also possible that land-use change has greatly affected feral bee populations (Moritz et al 2007).

**This wasn't a totally wild guess. I first calculated the human:hive ratio for 1961-2011. This ratio was increasing - there were 71 people / hive in 2011, and 47 in 1961. Initially, I assumed the rate of change in the ratio to be constant, but this led to unrealistically large estimates for historically managed hives. However, the rate was clearly increasing (just, perhaps in a nonlinear way I didn't want to estimate), so I decided instead to compromise on a number less than 47 and greater than 4. I decided on 35, as it produced what seemed like a realistic estimate of 5 million hives in 1650, compared to around 20 million today for Eurasia and North Africa (excluding sub-saharan Africa where wild-harvest remains important and likely was even more so in the past).

 Aizen MA, Harder LD. 2009. The Global Stock of Domesticated Honey Bees Is Growing Slower Than Agricultural Demand for Pollination. Current Biology 19: 4–4.
 Crane E. 1999. The World History of Beekeeping and Honey Hunting. Taylor & Francis. (Chapter 12).
 Jaffé RR, Dietemann VV, Allsopp MHM, Costa CC, Crewe RMR, Dall'olio RR, Rúa PPDL, El-Niweiri MAAM, Fries II, Kezic NN, et al.. 2010. Estimating the density of honeybee colonies across their natural range to fill the gap in pollinator decline censuses. Conservation Biology 24: 583–593.
Moritz R, Kraus FB, Kryger P, Crewe RM. 2007. The size of wild honeybee populations (Apis mellifera) and its implications for the conservation of honeybees. Journal of Insect Conservation


Can proteins/peptides pass through the intestine?

Entire proteins can be transported across the epithelial cells of the digestive system.https://en.wikipedia.org/wiki/Transcytosis

This is common in neonatal infants aiding in immunity passed via proteins in mother's milk. It is much less common as you age. http://www.vivo.colostate.edu/hbooks/pathphys/digestion/smallgut/absorb_aacids.html

The process is termed "transcytosis" if you wish to search for whether this occurs for a particular substance. One such goup of proteins entering the body in this manner are prions. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5004172/


Absolutely yes, is the short answer.

All genes are encoded in a  5-prime $\rightarrow$ 3-prime manner on each of the 2 DNA strands of the double helix.

Here's an example of a stretch of the genome from a bacteria that I work on in my PhD:

Each of the blue boxes is a separate gene. You can see they're able to be encoded on both strands, and run in opposite directions.

Consequently, whether a base pair is AT or TA changes the overall sequence, and would affect any gene which happens to span that base pair.

When reading the DNA during transcription, the strand that the gene resides on is called the Template (sometimes "Sense") strand.

The strand is separated by RNA polymerase enzymes, and it then uses the opposite strand of the DNA, known as the "anti-sense" strand, to create a copy of the gene sequence, but in RNA instead of DNA (and Thmidine bases are substituted for Uracil, as in the diagram).

Thus, the polymerase creates a mirror image of a mirror image, restoring the sequence of the original strand, but in it's RNA representation.

Flipping the bases round in the helix would change the sequence in the DNA molecule, and this would be propagated by the enzymes etc. which rely on it for transcription and replication.


How late in a human pregnancy can a zygote split?

Identical twins

Twinning occurring at the two cell stage or afterwards, up to and including the 16 cell stage, which translates to days 1 to 3 after fertilization, results in diamniotic, dichorionic twins.

Twinning at the 32 cell stage (day 4), up to  and including day 6 results in diamniotic, monochorionic twins. The majority of identical twins split at this stage.

Twinning from day 7 up to day 10 results in monoamniotic, monochorionic twins. This is rare and only accounts for about one percent of identical twins.

diamniotic: twins have separate amniotic sacs
monoamniotic : twins share one amniotic sac
dichorionic: twins have separate placentas
monochorionic: twins share the same placenta

Conjoined twins

This is where things get a bit fuzzy. While some sources say that conjoined twins occur when the twinning event takes place after day 10, others say conjoined twins are created when

  the twinning event occurs at about the primitive streak stage of development, at about 13–14 days after fertilisation in the human

It is very likely that because of the rarity of conjoined twins (one in 200,000 live births) there isn't enough data available on the very early embryogenesis.

Sources and further reading:

The embryology of conjoined twins

Twinning

Conjoined twins


What is the surface area to volume (SA:V) ratio of a red blood cell?

I googled "surface area of a red blood cell" and this paper was the first result.  It should answer your first question. Though it was unclear to me what the surface area unit of measure was, which may require a bit further reading.  There's also this article, which goes a lot more into the math of calculating these two things.

As for your second question about how much it changes, intuitively I would guess very little and it probably does not significantly change exchange rates.  I couldn't find any research on the topic.  The hard part is defining all the shapes they may get squeezed into, then either calculating or measuring SA:V. Possible?  Surely, a well written computer model could do it at some point.  But worth the time/money?  Probably not.


I am guessing on this one, and there may be some good research on it, but I do know that there can be combinations of genes acting on different behaviors, such that if you have a certain combination of 5 genes, you are a nurturing parent (which would be selected for), but when you accumulate more of these tangentially related genes past some threshold, you end up with non-selected behavior. For example, for homosexuality, which has been shown to be genetically heritable, it may be that 5 genes in a suite make you super attractive to women (thus these genes stick around), while 10 genes combine to make you gay. (Note, I am NOT equating homosexuality with pedophilia in ANY sense. Homosexuality if a healthy normal trait for humans. I am just saying that this is a theory about how suites of genes can be individually selected for while some combination of them is non-selective. Similarly, heterozygous sickle-cell genotype produces resistance to malaria, which is adaptive enough to keep the gene around, which is non-adaptive in the homozygous condition.)
In answer to the other parts of your question, humans are absolutely subject to natural selection. Darwin was dead-on correct about virtually everything he said, to the point where it is frustrating for evolutionary biologists today to work in his shadow, because he pretty much got it all right in 1859. "Theory" is the strongest conclusion that science can ever come to, and people have been trying to tear down Darwin's theory for 160 years without being able to put a single dent in it.


What evolutionary explanations are there for death?

Death is not only for humans. All 'complicated enough' organisms die (with a notable exception of Hydra, though you may argue when it comes to the complexity). It is is easier to create a new organism from scratch than to repair both internal factors (free radicals, metabolic by-products, ...) and external (physical damage, exposure to toxins, ...).
Underlying causes of death actually can be evolutionary beneficial. For example, shortening of telomeres offers protection against cancer (on a cellular level), but also bounds lifespan.
So actually they may be evolutionary competition (within the same species) of young and old. Mutations helping young but harming older may be preferred to the opposite ones.


Can conventional PCR amplify DNA from different organisms from a specimen in a single step?

If you had a 100% BLAST hit for 3 species from a single amplicon sequence then it only means that region of DNA is conserved in the three species so you have at least one of those species present not necessarily all three.

If you had three different amplicon sequences and each one matched one species to a total of three, then you have all three species present.


Do we have fundamental conflict in biology?

Peto's Paradox is a great one. This addresses the disconnect in cancer incidence with cell number in an organism. It goes something like this:

Assume current oncogenesis theory to be correct in that mutation acquisition is the rate limiting step in creating a cancer, such that you need ~5 specific mutations in a single cell for that cell to be fully transformed into a cancerous cell. This then being the case, it is so rare that any cell can acquire all necessary mutations that in humans we don't see cancer incidence appreciably increase until the 5th decade of life.

Now, let's assume man has an average weight of 50kg and a blue whale has an average weight of 130000kg, with roughly equivalent lifespans. Assuming average cell weights are the same in both organisms, there are 2500X more cells in a blue whale than a human.

If linear mutation rate is the rate limiting step in cancer then increasing cell numbers is akin to increasing the number of times you flip a coin to try and get heads, which means there is a 2500X greater chance of getting all ~5 necessary mutations in a single blue whale cell than in a single human cell. If human cancer incidence starts to spike at 50 years, this means blue whale cancer incidence should spike after 7 days and blue whales should largely be eliminated by cancers within the first month of life.

Hopefully makes you question a bit what is causing cancer.
Make sense?


Source of information on the evolution of aging/senescence

I don't know about just one source that fits everything you've asked, so here's a custom bibliography to get you started instead.

General Sources

I first learned about biogerontology from the excellent series of introductory essays at João Pedro de Magalhães' website, senescence.info; I definitely recommend starting here.

A short book written by two experts, for Scientific American Publishers, is Finch and Ricklefs' Aging: A Natural History. "The" book on the Evolutionary Theory of Aging is Michael Rose's Evolutionary Biology of Aging. "The" book on comparative biogerontology is Finch's Longevity, Senescence, and the Genome. A "pop" account of recent research (esp. to do with caloric restriction and long-lived mutants, which have people excited right now, and the search for longevity drugs) is David Stipp's The Youth Pill. A constantly-updated-with-new-editions-reference is The Handbook of the Biology of Aging. In 2008 (just missing the 2009 rapamycin excitement), Cold Spring Harbor Press published a collection on Molecular Biology of Aging. The Gerontological Society of America has an e-textbook out, that I think is going to be updated on the regular, called Molecular and Cellular Biology of Aging.

The Definition and Measurement of Aging

Usually, people define senescence as an increase in "mortality" with age. Mortality roughly means vulnerability; the older you are, the easier it is to die. Mortality is measured/estimated demographically, in terms of (hypothetical or actual) cohort survivorship. There are two quantities usually used: one for discrete-time, and one for continuous-time. Where $N_x$ the number of survivors still alive in a cohort at age $x$,

$q_x = \frac{{N_x}-{N_{x+1}}}{N_x}$ discrete-time; The Age-Specific Probability of Death.

$\mu_x = -\frac{N^{'}_{x}}{N_x}$ instantaneous; The Force of Mortality.

The first one is the fraction, of those alive at age $x$, who will die before age $x+1$. This estimates the probability that an individual aged $x$ will die before age $x+1$. This is intuitive: to age means that an 80-year-old is less likely to make it to 81, than a 20-year-old is to make it to 21. Notice that $q_x$ is bounded between 0 and 1.

The second one is the instantaneous rate of death, normalized against cohort size at that instant (whereas the first was the number of deaths in an interval, normalized against cohort size at the beginning of the interval). It is the instantaneous, age-specific, per-capita death rate. It can be visualized as the slope of the survivorship curve, divided by its height, times -1 to make it positive. It is not a probability. It has a dimension of rate ("per-second", "per-hour", etc) and it has no upper bound.

This way of defining senescence is described in Nature Scitable's Aging and its Demographic Measurement (although the authors give an erroneous definition of the force of mortality). It is discussed and justified intuitively, and at length, in Peter Medawar's The Definition and Measurement of Senescence.

Sometimes, you might want to count a decline in fecundity as aging, too, even if mortality wasn't changing. Or, you might want to define senescence in terms of various kinds of physiological performance. This is really a matter of taste, I suppose, or of what kinds of question you're trying to answer. Ageing or Senescence is just the part of getting older which, on top of having more birthdays, is somehow or other "bad" for you.

But the most common criterion is that $q_x$ or $\mu_x$ grows with age.

Mainstream Evolutionary Theory of Aging:

The mainstream idea is that aging evolves because of the declining force of natural selection with age. Natural selection "cares less" about things that happen late in life, than about things that happen early in life.

Mutation Accumulation (MA): the theory proposed in Peter Medawar's An Unsolved Problem of Biology. (Theory that aging is due to genes that are silent or neutral in early life, and deleterious in late life.)
Antagonistic Pleiotropy (AP): the theory proposed in George C. Williams' Pleiotropy, Natural Selection, and the Evolution of Senescence. (Theory that aging is due to genes that are beneficial in early life, and deleterious late in life.)
Disposable Soma: Proposed by Thomas Kirkwood and Robin Holliday; sometimes considered a version of AP. (Theory that aging is due to a tradeoff, in turn possibly due to allocation of limited resources, between reproduction and maintenance; selection favours less than perfect maintenance. Can be considered a version of AP where the "early beneficial effect" is increased maintenance, and the "late deleterious effect" is decreased survival.)

Summarized in Nature Scitable's The Evolution of Aging. Note that both MA and AP could be partly true; both kinds of genes could exist.

Both MA and AP are commonly cited as predicting that higher extrinsic mortality should lead to the evolution of earlier / faster senescence; but things may be more complicated than this.

The Declining Force of Natural Selection: Hamilton's Formalization

Medawar's and Williams' insights were verbal. William Hamilton did the math, and showed that certain formal indicators of the strength of selection on a genetic effect, necessarily declined with the age at which that effect occurs. These indicators were I think: 1) the partial derivative of $r$ (the intrinsic rate of increase / malthusian parameter, which he took to be fitness) with respect to the force of mortality at age $x$; and 2) the partial derivative of $r$ with respect to fecundity at age $x$. (The first starts declining at the age of first reproduction; the second starts declining immediately.)

In passing, this also demonstrated that a remark R. A. Fisher had previously made, and which Medawar had accepted, was fallacious. Fisher and Medawar had assumed that the strength of natural selection was proportional to age-specific reproductive value; but since reproductive value can increase with age, and Hamilton's indicators can't, reproductive value can't be measuring the sensitivity of $r$.

Hamilton's paper: The Moulding of Senescence by Natural Selection.
Charlesworth summarizes Hamilton's results and puts them in context in Fisher, Medawar, Hamilton and the Evolution of Aging.
Charlesworth's book Evolution in Age-Structured Populations is supposed to be quite important and to have furthered and refined stuff in this area.
Apparently things might be a bit more complicated than this? Baudisch has claimed that although Hamilton's indicators must decrease with age, other indicators, which aren't obviously unreasonable, can increase.

Gompertz, Weibull, and Gompertz-Makeham

The Gompertz equation is intended to describe how the Force of Mortality $\mu_x$ grows with age. The Gompertz equation was come up with empirically, not for any theoretical reason; it just seemed to Benjamin Gompertz to fit the data quite well, for a good stretch of adult lifespan. The same goes for the Weibull equation, as far as I know, and for the Gompertz-Makeham equation.

Gompertz is an exponential growth equation: $\mu_x = \mu_0 \cdot e^{Gx}$ (where $G$ is a parameter). It looks like a straight line when graphed on a semilog plot.
Weibull is a power growth equation: $\mu_x = A \cdot x^B$ (where $A$ and $B$ are parameters). It looks like a straight line when graphed on a log-log plot.
Gompertz-Makeham adds a constant to the Gompertz equation: $\mu_x = \mu_0 \cdot e^{Gx}+C$. This ruins the elegance of the semilog-graphing, alas; it doesn't look like a straight line.

Apparently some people have tried to show how eg. Gompertz can evolve in MA models, but the generality of this is questionable (see Box 2 in this Trends in Ecology and Evolution paper). Gavrilov and Gavrilova (proponents of the "reliability theory of aging", have said something about Gompertz and Weibull being special: ("Both the Gompertz and the Weibull failure laws have their fundamental explanation rooted in reliability theory... and are the only two theoretically possible limiting extreme value distributions for systems whose life spans are determined by the first failed component... In other words, as the system becomes more and more complex (contains more vital components, each being critical for survival), its life span distribution may asymptotically approach one of the only two theoretically possible limiting distributions—either Gompertz or Weibull (depending on the early kinetics of failure of system components).") I don't know what that means.

Gompertz is the most commonly cited / used equation, I think. It's supposed to be more accurate than Weibull. Gompertz-Makeham I guess is more accurate, but of course it would be - it has an extra adjustible parameter, which, if it isn't helping, you can just set to zero!

Sometimes these equations are erroneously presented in terms of $q_x$ instead of $\mu_x$. This is erroneous historically, but also because $q_x$ has an upper bound of 1 and couldn't possibly obey any of the equations, at least not indefinitely.

Sometimes people find it more intuitive to describe Gompertz' exponential growth in terms of how long it takes $\mu_x$ to double; in humans, this "Mortality Rate Doubling Time" is about eight years.

Note that the equation does not accurately describe early life; mortality often starts high in infants, before falling to its minimum, and then starting to grow again. Thus $\mu_0$ isn't the actual mortality rate at age 0, but the backwards-extrapolated mortality rate you would have had at age 0, if you were perfectly Gompertzian (or whatever).

It also may not describe very late life. A hot topic right now is "late-life mortality deceleration", where the exponential growth seems to slow down such that Gompertz overpredicts mortality in the very old; whether this is so, and why, is debated.

Reliability Theory and the Reliability Theory of Aging

"Reliability Theory" itself is just a mathematical framework for describing survival / failure rates and stuff. (Engineers use it to quantify stuff like, the rate at which parts have their first breakage, or whatever.) Some of the quantities it describes are basically the same as some analogous quantities in demography / life histories, if "first failure" is taken to mean death. For example, the "Survival Function" $S(t)$ is the probability, at time $0$, that failure will not yet have occurred by time $t$; this is obviously analogous to the probability $l_x$ that a newborn will still be alive at age $x$.

Systems can be made of parts; if you know the survival/reliability patterns of the parts, and how they go together, you can tell something about the survival/reliability of the whole system. To illustrate, compare two kinds of reliability structure:

A "series reliability structure" is one where, if any part fails, the system fails. An example would be a block held up by a chain; if any link breaks the block falls.
A "parallel reliability structure" is one where, if all parts fail, the system fails. An example would be a block held up by a number of individual rings, attached separately; only when the last ring breaks, does the block fall.

"The Reliability Theory of Aging and Longevity" is a specific theory proposed by Leonid Gavrilov and Natalia Gavrilova, intended to explain patterns of organismal failure ("death") in terms of component failure, and how the components are put together. If I recall, they propose that aging organisms are made up of redundant blocks of non-aging components; supposedly, this can explain near-Gompertzian aging over most of adult life, as well as apparent late-life mortality deceleration.

Group Selection

Heresy! Most evolutionary biologists / gerontologists, I assume, are happy with the mainstream theory and don't take the group selection theory seriously. Iunno, try Mitteldorf? Here's a paper and he also wrote a pop book with Dorion Sagan. On group selection in general as an explanation for altruism, I think David Sloan Wilson's the guy trying the hardest to defend it (or "a new version of it").

Molecular Mechanisms

Iunno, try The Hallmarks of Aging? The trouble is we really don't know what mechanisms cause aging. There's some good ideas, but finding evidence is haaaaard. One problem is that, if you want to know why some species live longer than others, and you're looking for physiological correlations, body size is a huge confound (elephants and whales live longer than mice and dogs), and so might be phylogeny.


Is amphibians being descended from fish reflected in the animalia taxonomy?

Fish are a paraphyletic group: that is, any clade containing all fish also contains the tetrapods, which are not fish. For this reason, groups such as the class Pisces seen in older reference works are no longer used in formal classifications.

You got something completely wrong. In evolution one can not say that one taxonomical group evolved from the other. We say that two taxonomical groups have common distant relative. With that said all vertebrates have common distant relatives. Important is to know when did the branching in speciation happened.
Proto-amphibians evolved in Devonian by further speciation from relative that was sarcopterygiian (fish). It was a fish with some properties of amphibians (lungs and bones in appendages).


Why does higher venous volume increase atrial pressure?

Imagine the circulatory system is an amusement park ride.  The ride is the left ventricle and the arterial system.  After riding, people go around and get back in line to go again.  The line and the building housing it are the venous system.  Maybe the lungs are some sort of staging area where you get ready to get on the ride.

The right atrium is the end of the venous system.  Venous pressures are right atrial pressure.

When all is well the line is moderate and people wait a short time before riding again.  But now 100 more people arrive.  If the park workers can speed up the ride or loading rate to accommodate the extra riders then great.  But if the ride cannot go any faster then the line backs up.  If you imagine that it is raining out, all the people in line bunch into the building housing it.  Venous pressure increases.  It will stay increased unless the number of riders (blood volume) decreases or the heart improves its output to accommodate the load.

Congestive heart failure is a useful example.  The ride speed (cardiac output) cannot increase because the heart is weak.   If riders increase (blood volume) it backs up into the waiting line or venous system.  This increase in volume occurs if someone with CHF eats a salty meal – water follows salt and blood volume increases, which backs up in the venous system because the heart cannot increase its output to accommodate the increased volume.  These sick folks are said to be volume overloaded.  You can see increased venous pressure as the signs of CHF – for example dilated external jugular veins.

Among many adaptations to deal with increased venous pressure is atrial natriuretic peptide.  When increased venous pressure stretches the right atrium this peptide hormone is secreted which is a cue to the kidney to dump sodium, and with it fluid volume.


Consequence of Plants as Incomplete Protein Source

With a few exceptions among some bacteria, all species on the planet make protein from the same 21 amino acids, and the relative abundances of amino acids is very similar in proteins from plants, animals, fungi and even prokaryotes. See for example this article (available as PDF here). So protein from pretty much any food provides the same amino acids.

The idea that plant proteins are "incomplete" and lack some amino acids seems to be a myth: see for example this correspondence in the American Heart Association's journal Circulation. Plants generally contain less protein than meats per weight, but there is nothing wrong with the protein they contain. Most people in the world obtain the majority of their protein from plants. There are probably some specific parts of some plants that are not nutritionally optimal --- if you for example lived exclusively on peanuts for a year, you might experience some problems ... But any commonsense, varied plant diet will provide all amino acids. A detailed report (and some mythbusting) is here.

Regarding essential amino acids, as mentioned in comments this is a species-specific concept. Humans and most animals can synthesize about half of the 21 amino acids, while the remaining are essential. There are some species differences --- arginine is essential for cats, for example, but not for adult humans. In contrast, plants can synthesize all amino acids. But their protein composition is similar in the end.


How long can human tissue last without blood?

As EMT (Emergency Medical Technician) instructors will tell you now, when wearing a tourniquet, you have about four hours to get the injury to a vascular surgeon and get it cared for appropriately. The rule therefore is four hours. However, the common thread I see in most sources is that about an hour and a half is the longest you want to go without blood flow to a limb.

As far as what happened to you, it sounds more like the limb simply fell asleep. When a limb falls asleep, it is getting the nerve pinched off for a time as well as loosing some blood flow. However, this is not a complete loss and so your arm is able to survive because it is still receiving enough oxygen and other nutrients to sustain its existence (as well as having toxins and CO2 pumped away from it).

I had a very difficult time finding any concrete, scientific information on this subject overall.

So, if you would like more information about this, please visit the following links. The first is a WikiPedia link on Limb Infarctions (or an embolism in a limb). The second is from Mental Floss on Why Limbs Fall Asleep. The third is a somewhat random article on someone's personal experience on Sleeping on their arm.

So, in summary: although I could find no solid evidence on how long a limb can live without its blood supply, it appears to be about 2-4 hours (some sources say 5-8); however, I would like to add that your case appears to be a severe case of an asleep limb, you were/are likely in no danger. Also, if your arm indeed did have circulation completely cut off, it would have turned pale, then blue and later a livid red and purple as the blood began to pool; you then would begin to experience the effects of the limb dying i.e. necrosis, gangrene.


I'm not quite sure what you mean by

  regardless of x and y being out of balance.

Surely it would make more sense to assume you gain 0 weight if x and y are balanced? The prime reason why people get obese is probably because x and y are not balanced for them (there are other reasons though, as well as reasons why people can have it imbalanced and still not gain weight).

Even if you consume exactly as many calories as you expend in a day, you may gain weight depending on how (ratio of protein/fats/carbohydrates) and especially when you consume the calories. The body may for example store consumed amounts as fat after eating and then use carbohydrate storage from liver and muscle when starving, so long term you would still gain weight.
Adipose (fatty) tissue requires energy too. If you consume in the same manner after as before cutting a large amount of it away, you may just regain it until x=y again.
Also consider: if people ate just half an apple a day more than the exact amount of energy they need, they should gain more than a kilo on average every year. But they don't, and you can hardly assume that people manage on average to consume the exact amount their body needs.

The reason for that is probably leptin. It is a hormone produced by adipocytes (fat cells) and essentially indirectly reduces food uptake and increases expenditure, among others by decreasing your appetite. This has been regarded as a sort of "adipostat"; your leptin system creates a genetically determined level of body fat that you will tend to obtain. Dieting or cutting away fat will cause a drift to return to the previous weight because of a lower level of leptin (due to reduced fat cells). Of course it's not as simple as that though, so it's also possible that you will actually long-term reduce weight through those methods. E.g. exercise seems likely to be an exception somehow.


What is known about major events of pre-LUCA evolution?

There is an awful lot of literature and debate about what happened before LUCA consequently here are some key words to read more about, first on Wikipedia, then on review papers and then on the many papers...

According to the Oparin-Haldane hypothesis life formed from an abiotic primoridal soup.
These abiotic building blocks were formed by lightning, meteorites, UV or other processes (see Miller–Urey experiment and the Murchison meteorite)
Not all metabolites we know today existed and many that do not have a use today existed (non-proteogenic amino acids on Wikipedia is an article/list on the topic).
The genetic code is a frozen accident (Crick), but many believe it went in waves and was rather promiscuous (e.g. 3rd position pairs came later) and may have included ornithine and norleucine, which were "usurped".
Ignoring the temperature/location aspect, from a chemical point of view, life arises from a hypercycle process and requires gradients.
DNA did not form as is. The ribose may have been glycol and the nucleobase glycine: many metabolites in nucleotide metabolism are able to base pair.
The RNA world came first, then DNA with chromosomes came later. This has an odd effect in that early enzymes had to be highly multifunctional.
To have evolution, you need compartmentalisation.
Tar is gloop that forms easily abiotically. Tarrification is a threat to early life, but could have helped with compartmentalisation.
Montmorillonite clay can act as a scaffold for DNA polymerisation.
Ribozymes are RNA enzymes. The most core cellular processes is still RNA operated: the ribosome and tRNAs.
Many cofactors are primordial and are attached to riboses, e.g. NADH, FADH and arguably cobalamins.
Proteins came later, but still today the catalytic power of protein comes from their cofactors or from a single amino acid (e.g. cysteine as a nucleophile).
Once you have potentially RNA-encoded proto-enzymes you can start building more of the useful compounds that were available in the primordial soup but were depleted. Most pathways will therefore form by retrograde pathway evolution.
Enzyme activities can only be evolved if there is a pre-existing activity to select. Luckily accidental activities happen, called promiscuous activities (this term a century ago had no sexual meaning and used mean "being muddled").
Modern enzyme are highly specific and evolved to work at a high turnover (fast) and work at physiological substrate concentrations. But still have promiscuous activities because the substrate chemistry is similar. If the enzyme has never see a given compound the enzyme will not be evolved to not act on it and maybe the activity has no detrimental effect (neutral). When an enzyme evolves into a new activity an intermediate form is seem with higher promiscuity. These are often argued to be primordial-like.
Many pathways have a common origin, for example the Krebs cycle and the branched chain amino acid pathways and actually experiments in E. coli have found that the enzymes can rescue "deficiency" (auxotrophies) in the other pathway albeit slowly. Therefore, as enzymes could act on different similar substrates a set of overlapping pathways arose (patchwork hypothesis).
LUCA is the last common ancestor. It was likely thermophilic and lived in thermal vents as seen in every documentary. If life started there is debated.
Early enzyme were like very unstable, very very slow and may have often broken good metabolites in a futile manner. Given the problem of segregating with a chromosome and the need for high promiscuity, they had to be multifunctional. Not to mention that similar-ish amino acids were used interchangeably —isoleucine and valine say are hard to tell apart to modern tRNA synthases, go figure for the early ones.
Enzymes generally fall under a few families, which share a common ancestor. Rossmann fold enzymes for example bind NADH. TIM barrels are a ubiquitous fold.

So to answer your question, between the RNA world and LUCA, enzymes were slow and were selected upon to remake the more complex metabolites in the soup and then the simpler ones and thanks to their poor selectivity a patchwork of pathways arose. Once simple core pathways started and all metabolites could be made, more complex compounds that cannot arise abiotically such as the amino acids tryptophan and arginine were made. The enzymes became more selective and stuff like straight chain hydrophobic amino acids were selected against and the genetic code was fixed. Then you can make stuff like chromosomes and everything happens fast and efficiently.

Caveat. Early life was messy, really not efficient (it had no competition) and happened a long time ago. As time machines are physically impossible, all this is conjecture (sensu Popper), but the words theory and hypothesis are used happily in the field of origin of life.