In humans what is the last metabolic process to cease after death? After death which of our body's metabolic processes will continue functioning for the longest?

My answer isn't researched; it is speculative.

I interpret metabolic processes as anabolic or catabolic processes. I assert that only anaerobic processes can continue for a long time after vegetative death (the epithelia could house a counter-example of a post-mortem process, but I can't think of one), and I speculate that only catabolic processes are likely to have sufficient pools of reactants to continue after death. So we're looking for a catabolic process with a large reactant pool. Therefore I think that the action of digestive proteases will continue for the longest time, because these enzymes are very stable and could have a lot of substrate around (including, at a very slow rate, cleaving each other.) The neutralization of stomach pH would inactivate this process...I don't know how long that takes.

If something like blood clotting is considered a metabolic process, then probably that continues the longest. The binding of CO₂ by hemaglobin is probably faster than blood clotting. Again, I don't really consider those processes to be metabolic.


Why do restriction enzymes tend to have an even number of bases in their recognition site? When reading my textbook I noticed that in all examples but one from eight the recognition site was an even number of bases.

I wondered if this was just a co-incidence, so I took the data from this site for over a thousand known recognition sites and put it into a spreadsheet (XLS uploaded here).  The results are probably best summarised graphically:

Stats Test: Chi Squared Goodness of Fit.

Null Hypothesis:
There is no significant difference between the number of restriction sequences
that are an odd or even length.

|---------|----------|----------|-----|-------|----------|
|  Trait  | Observed | Expected | O-E |(O-E)^2|(O-E)^2 /E|
|---------|----------|----------|-----|-------|----------|
|  Odd    |    172   |  231.5   |-59.5|3540.25|  15.293  |
|  Even   |    291   |  231.5   | 59.5|3540.25|  15.293  |
|---------|----------|----------|-----|-------|----------|

Chi Squared Value = 30.586

P=0.05, 1 Degree of Freedom: Critical Value of 3.841

H0 rejected with 95% confidence (indeed with 99.9%+ confidence)

Can anyone explain or suggest why it is more common that restriction enzymes recognition sites have an even number of bases?

Updates

Expanded dataset to include new recognition sites from the resource that 96well linked to.
Removed all duplicate recognition sites leaving 465 distinct recognition sequences (my fault for not removing them in the first instance)
Ran stats test on the data
See Previous Version


What is so difficult about mushroom cultivation? I am just wondering why it is so cheap and easy to cultivate this type of mushroom: Agaricus bisporus, however a typical forest mushroom such as Boletus edulis  has to be harvested. What makes one mushroom species much more difficult to cultivate compared to another?

What makes some mushrooms easy to cultivate is that they grow profusely, they aren't tree symbionts, where as sponge gilled culinary musrhooms are symbionts. Cheap mushrooms can easily be controlled with temperature and or light to fruit year round with minimal labour, they have cheap and easily obtainable substrate, and that are very appreciated for cooking and transportable. Also Argaricus doesn't even need light as a signal to trigger fruiting bodies and can be grown in complete darkness, and the harvest can be with robots not even manual, https://youtu.be/iBENPHl4mBA?list=PLw1YvKXHZymsoJbFGRI_OFSWZ5Wwg_fVD, which makes them particularly cheap.

Mycorrhizal mushrooms like boletes and many forest associated mushrooms differ from Argaricus and
commonly commercially produced saprotrophic
types (such as shiitake and button mushrooms).
Saprotrophic mushrooms live and feed on dead
organic matter, whereas mycorrhizal mushrooms
grow in a close, symbiotic (mutually beneficial)
relationship with the living roots of a tree.

Field and dead wood mushrooms generally have simpler substrate that can be transported in boxes in the dark, and almost all cultivated mushrooms are of saprotrophic.

Saprotrophic nutrition /sæprəˈtrɒfɪk, -proʊ-/ or lysotrophic nutrition is a process of chemoheterotrophic extracellular digestion involved in the processing of dead or decayed organic matter. It occurs in saprotrophs or heterotrophs, and is most often associated with fungi (for example Mucor) and soil bacteria.

That's slightly different to Saprophytes are more generally plants which live on dead or decomposing matter and which can also be more accurately be called myco-heterotrophs because they actually parasitize fungi, rather than dead organic matter directly.

They say that Argaricus was first discovered in 1650 on melons! but as any theory, there were probably precedents. Any farmer that discovered sizeable populatons of fungi near horse and cow middens could have easily have experimented with placing some compost in a basement.

Morelles and truffles are such expensive mushrooms that the man who learns how to grow big truffles will be payign himself up to a 1000 dollars a kilo for his efforts, it illustrates the difficulty of micorrhizal cultivation.

If you are interested in fungi there is a fascinating ted talk about them from Paul Stamets.

and
https://en.wikipedia.org/wiki/Mycorrhiza


Changes in dna from dioxin poisoning A person sprayed with a dioxin, how long would it take for a dna change? Instant or over time? Would that person having children afterwards pass on any(if any) dna changes?

Studies on model organisms suggest effects begin quickly, within 6-8 hours of exposure. Rat studies suggest liver absorption of dioxin reaches a maximum from 8-24 hours, with Cytochrome P450 protein expression levels peaking afterwards. Another study uses a comet assay that measures DNA damage after six hours of dosing, and damage is tied to dose level.

Epigenetic changes to sperm and eggs are heritable, passed along to offspring. These result from histone deacetylation and methylation, which in turn change how DNA are packed and unpackaged for protein expression, and change expression itself.

A summary article on epigenetic dioxin (TCDD) toxicity suggests that there are specific effects on protein expression involved in embryonic development in model organisms, which result in birth defects and immune system damage.

In addition to controlled lab experiments on rats and mice, the United States of America and Monsanto conducted a massive, uncontrolled science experiment on humans, dropping dioxin in great quantities on millions of Vietnamese civilians during the Vietnam War.

Children of exposed victims suffered spinal bifida and other birth defects. US military exposed to dioxin in the course of deploying this chemical weapon also had their children suffer greater rates of similar birth defects.


Can cooking oil kill fleas? I cannot find a reliable way to kill fleas after removing them from my cats with a flea comb.  Soap and water does not do the job and they climb back out of the drain.
Will cooking oil  suffocate fleas?  If so how long of time until the flea expires?

Short answer: Mire them in a viscous liquid then leave them in there long enough for them to die, instead of immediate disposal.

Cooking oil is viscous, so yes you can viably use it to mire the fleas. You'll need to wait until they die though to dispose of them or else they'll come crawling back as you've stated. The DIY option is generally a water/dish soap mixture in a container: you'll put the fleas in and they sink to the bottom almost immediately. Just leave them in there and they'll eventually die in about 5 minutes. Some individuals suggest Dawn dish soap, much like here, where the claim is that the Dawn contains compounds which suffocate the fleas.

You can also make a flea trap for around the house, with a bowl of dish soap and water near a night light. They'll jump for the light and end up falling into the flea trap.


Digestion of milk in humans The intial step in the digestion of milk in humans is carried out by which of the following enzymes?

A) lipase.

B) trypsin.

C) rennin.

D) pepsin.

I'm confused between the C and D option. as it's not specified whether they're asking about adult humans only or humans in general (where infancy also included), which between pepsin or rennin will be the answer for this question?

I know that in infants the milk digestion is initiated by rennin and in case of adults due to its absence it's carried out by pepsin. Which is the correct option for that question?

Short answer
My best bet is D)

Background
A) seems incorrect as lipases break down fats. However, one has to realize there quite some fat in milk (up to 3.5% in untreated milk). Digestive lipases in man are secreted by the pancreas into the duodenum.

B) Might be a correct answer, as trypsin is released in the small intestine and...

  [Trypsinized] peptide products are further hydrolyzed into
  amino acids via other proteases, rendering them available for
  absorption into the blood stream. Tryptic digestion is a necessary
  [first] step in protein absorption as proteins are generally too large
  to be absorbed through the lining of the small intestine.

C) Chymosin, known also as rennin, is a proteolytic enzyme synthesized by chief cells in the stomach. Its role is thought to be in digestion is to curdle or coagulate milk in the stomach, a process important in young animals. If milk were not coagulated, it would rapidly flow through the stomach, impairing protein digestion. So this is a enzyme in the stomach and active earliest in the digestive system (answers A and B concern enzymes in the duodenum, which is later down in the digestive tract). However, in humans there is only a chymosin pseudogene present, and since the answer specifically deals with humans, answer C) is incorrect.

D) Pepsin is

  ...[] one of three principal proteases in the human digestive system, the other two being chymotrypsin and trypsin. [These] enzymes [...] break down dietary proteins into [...] amino acids, which can be readily absorbed by the small intestine. Pepsin [mainly] cleav[es] peptide bonds between hydrophobic and [..] aromatic amino acids [...The other two proteases have different targets].

  Pepsin's proenzyme, pepsinogen, is released [...] in the
  stomach [...], and upon mixing with the [...]
  gastric juice, [it is] activate[d] to [...] pepsin.

Here we have the adult equivalent of rennin, also active early in the digestive tract, namely the stomach. So D) is the enzyme present in humans (as opposed to C) and active already in the stomach (as opposed to later in the duodenum in answers A and B). So D is the answer.


What makes synapses stay "fixed"? What makes synapses not move or pre- and postsynaptic cells neither touch nor move away from each other? I mean the synaptic cleft is a gap between the pre- and postsynaptic cells that is about 20 nm wide (according to Wikipedia), so what makes it of that width? Are there some protein fibers anchored in both pre- and postsynaptic cells? Or do the glial cells keep them at that (often temporarily) fixed position? What prevents them from being displaced by the slightest movement of the body? I'm talking obviously about the chemical synapses.

Thanks in advance for the answer.

Synapses are held together by adhesion molecules, like cadherins and neuroligins/neurexins, so they aren't just loose adjacent membrane, they are securely anchored in place.

The adhesion molecules serve both a structural and regulatory role, being important for synapse formation and plasticity.

Missler, M., Südhof, T. C., & Biederer, T. (2012). Synaptic cell adhesion. Cold Spring Harbor perspectives in biology, 4(4), a005694.


How predictably will RNA polymerase not transcribe repetitive sequences? I am working on an (expensive) synthetic construct, which happens to have many "repetitive" sequences within it that are integral to its function. Primarily, the two sequences that are worrying me are:

A long polyA (about 15 nucleotides).
A consecutive sequence of two nucleotides: GGGUUUGGUUGU, etc.

I've heard from many some of the transcription horrors they've been through because of similar sequences with similar nucleotides. However, some advise that transcribing it shouldn't be a problem.

How predictably can RNA polymerase transcribe these sorts of sequences in E.coli?

I don't think repetitive sequences are intrinsically problematic to an E coli. Bacteria also deal with things like polyadenylation. Basically, you have nothing to lose from trying -- E coli is one of the more robust expression platforms, and it's difficult to predict whether the sequence will fold into some tertiary structure (which can easily impede translation.)

So I think the predictability should be set at the baseline for E coli RNA polymerase error rate, which is about $10^{-5}$.


Can a tumor produce something not currently found in our own bodies? While speaking with my co-workers, the topic of tumors growing things came up.  The examples were (and backed by images) of tumors growing a tooth, hair, and sometimes even more complex objects such as an eye.

My question is, could a tumor reproduce something that isn't typically found in the human body?  Could it grow something that maybe a very distant ancestor would have had?

If you look at a cancer textbook (eg. Robert A. Weinberg's The Biology of Cancer), you'll find that by definition, a tumor arises from tissues normally found in the patient's body. There's a great deal more to it than just that simple statement, but given the context of the question, I think that answer should suffice.

In writing, "...tumors growing a tooth, hair...", I think you're talking about teratomas. These contain "normal derivatives of all three germ layers". These arise naturally from cells "...typically found in the human body..."

Cancer is a process where mutations in a single cell transform that cell into something that is by definition not "typically found in the human body." But a human cell transformed by mutation into a tumor (benign or malignant) is never (to the best of my knowledge) going to magically become a cell from another species or a very distant ancestor (ie. something that is not "typically found in the human body.").


What's the proper term for "brain waves" read from an EEG? An EEG records the electrical activity of the brain. An EEG shows voltage differences as a function of time and shows what have become known as "brain waves".

Is there a scientific/technical word/phrase for one of these measured "brain waves"?

The terminology around EEGs is variable, dependent on the context;

Brain wave is fine, but has a bit of a popular undertone;
Oscillation, as per the deleted answer,  implicitly refers to a longer-term behavior, i.e., something periodic (EEG);
Waveform is often used to describe a single event with a recognizable shape (ERP, compound action potentials, etc.);
EEG signal/recording/trace is more than fine too, it doesn't carry any implicit meaning about its nature, it does carry relevant information on the method used;
EEG is fine too, EEG means electroencephalogram, the 'gram' suffix comes from Greek, where it means “something written,” or a “drawing”, so literally it means something like "graph of the electrical brain". So simply speaking of 'the EEG' is OK as well.

This list may not be exhaustive, merely illustrative


Anesthetics, specifically inhaled anesthetics I have had a look at previous inhaled anesthetics and many of them appear to be fluorocarbons. What could be the mechanism behind fluorine's anesthetic properties? Is it the specific bonding pattern or the molecules involved?

I realize anesthetics are rather unknown I just wondered what people have as a hypothesis?

The following is one of the many elegant statements in General Anesthetic Actions on GABAA Receptors:

  It is the fervent view of the authors that general anesthesia is no different from any other pharmacological process: exogenously administered drugs interact with key sites on cellular proteins in the body which results directly in the alteration in the function of these proteins, in the present case, neuronal proteins that control how information is conveyed through the nervous system.

Isoflurane, Sevoflurane, and Desflurane, the current inhalation general anesthetics, along with Halothane and the intravenous anesthetics Propofol, Etomidate, Methohexital and Thiopental, enhance the function of GABAA receptors (GABAARs), the most abundant fast inhibitory neurotransmitter receptor in the CNS (ligand-gated chloride ion channels) by increasing the affinity of the receptor for GABA. Since these receptors are abundant in parts of the CNS that process higher-order brain functions, it stands to reason that GABAAR function is central to memory, awareness and consciousness. GABAARs are involved in mediating hypnosis, depression of spinal reflexes, and amnesia, three of the classical components of general anesthesia. Isoflurane, Sevoflurane, and Desflurane enhance the amplitude of responses to low concentrations of GABA and prolong the duration of GABA mediated synaptic inhibition.

A very good starting point for your investigations can be found by clicking on the linked article above.

Agent-selective effects of volatile anesthetics on GABAA receptor-mediated synaptic inhibition in hippocampal interneurons
The sedative component of anesthesia is mediated by GABA(A) receptors in an endogenous sleep pathway


What would be the impact of depositing limestone in the oceans (to reverse acidification) on ocean life forms and biodiversity? This question asked: What is the evidence it is feasible to reverse ocean acidification by adding large quantities of a base (bicarb soda)?

The result was:

  Danny Harvey of the University of Toronto has already looked into this. His solution is to deposit 4 Gt/yr of limestone into the oceans. To put this in perspective, global coal production in 2013 was nearly double this at 7.823 Gt and it is more than global iron ore production in 2014 of 3.22 Gt.

The respondent then posed the question: What impact would such a huge annual deposition of limestone have of ocean life forms and biodiversity?

My question is: What would be the impact of depositing limestone in the oceans (to reverse acidification) on ocean life forms and biodiversity?

To simplify, acidification of oceans is due to excess anthropogenic carbon dioxide CO2:

  H2O + CO2 → H2CO3 → H+ + HCO3-

Seawater is naturally saturated with another base, carbonate ion (CO32-) that acts like an "antacid" to neutralize the H+, forming more bicarbonate.

  CO32- + H+ → HCO3-

You want to alkalinize the ocean by dumping CaCO3. That sounds pretty good, and not only would it add more buffer (and decrease acidification) but it would also help the sea creatures which use dissolved Ca2+ and CO32- to make shells of calcium carbonate CaCO3. (The other effect of excess CO2 is the leaching of CaCO3 from shells and corals or other marine organisms:

  CaCO3 + H+ → HCO3- + Ca2+

The limestone mined today is used for gravel, in concrete, road surfacing, foundation support beneath weight-bearing structures, the boulder faces of earthen dams, Portland cement (N.B. the burning of limestone in the cement-making process liberates CO2 gas), Aglime (pulverized limestone) and quicklime (process liberates CO2 gas) which are both soil stabilizers, hydrated lime used to filter potable water supplies and to treat solid and liquid waste and in processing petroleum. These are only the major uses of limestone.

The average annual limestone production in Missouri (the largest deposit of limestone in the world) is about 89 million short tons/year. The cement industry alone is a MAJOR producer of CO2. Producing a ton of cement requires 4.7 million BTU of energy (some of which will release CO2), equivalent to about 400 pounds of coal, and generates nearly a ton of CO2.

So, in addition to the CO2 produced by the use of limestone in everyday life, you want to mine it and dump it into the sea. Unfortunately, even finely ground limestone (remember all that CO2 it takes to mine and crush it) is poorly soluble in water (pH 7.0). It does increase with acid, but still is very slow. Also, it sinks. The worst acidification of the ocean is in surface waters.

Some estimates suggest that close to 100 million tons of limestone are mined globally each year. (It's probably much more than that; see Missouri alone.) You want to mine, crush (to between 40µm - 10µm!!), and deliver an additional 4 Gt/yr of limestone, even though in the paper you cite, that amount per year would not help:

  Extraordinary additional measures (adding 4 Gt limestone/yr to the ocean for > 200 years) provides a modest additional benefit (additional to cutting CO2 emissions.)

Why? What difference would knowing the effect on biodiversity be when just procuring, processing and delivering the stuff would generate more CO2 than it could possibly buffer, and would have a minimal effect anyway?


How can I describe running a solution four times through a chromatography unit (in an instruction)? I'm translating a document from Russian:

  The mean retention time for the first four injections of RNase should be (40.8± 2) min. If the mean RT is beyond this range, adjust the gradient system (change the content of acetonitrile within the 20% - 32% range) and chromatograph the RNase solution four times.

I'm aware that we don't use chromatograph as a verb in English usually, but we do use it in Russian this way. What would be the generic English expression for this, usable in a procedure description? I know that we have the word run but this might be too colloquial for an official paper.

I would continue to use inject to describe loading samples into the liquid chromatography system and replace

  chromatograph the RNAase solution four times.

with

  inject the RNAase solution another four times.


What is the closest possible analogue to human cells? For an experiment, I need a specific number of cells. I will grow these cells in an incubator, and then measure the number of cells which have decayed due to the induced radiation. I am using a standard cell counting chamber (Hemocytometer) to count the number of cells.

The research question is to find the best armour for radiation; low-level really.

I was wondering which cell is the closest substitute to a standard human cell. People are telling me about yeast, but doesn't that grow from budding?

Any help and/or suggestion is appreciated.

What about Escherichia coli? Every undergraduate lab has easy access to plenty of E.coli culture methods and its stupid easy to culture. There are always HeLa cells as well if you really want the perfect analogue to human cells because, well, they are human cells. Other options would include:

a) HEK 293 cells (Human Embryonic Kidney 293 cells), which are nice for what you're looking at as they don't replicate out of control, but are still extremely easy to grow. However, they're generally used as hosts for gene expression and they're finicky when it comes to contamination and they don't really act like normal cells that would be hit by low level radiation (ie tissues that are closer to the skin's surface)

b) 3T3 cells which would be nice for you as they are contact inhibited cells, meaning they functionally keep growing into a layer one cell thick (a monolayer) which could be nice for you, especially if the low level rad you're testing is alpha emitting in which case you need a homogeneously thick cell layer.


How do bile salts affect lipase activity? BACKGROUND: It is well known that bile salts are needed for emulsification of fats. It is then said that this increases the surface area for activity of pancreatic lipase, implying that bile salts make pancreatic lipase more effective. But it is also said that pancreatic lipase do need a colipase to overcome the inhibitory effect from bile salts.

QUESTION: So what does bile salts actually do? Do they increase or decrease lipase activity? How does colipase overcome it?

MY ATTEMPT: After some research , I found that bile salts above critical micelle concentration have inhibitory effect, but could not still comprehend how does the colipase makes lipase more efficient. Also if greater concentration is inhibitory then why does our body just secrete it in sufficient amounts? Isn't it be more efficient than to make a whole protein(colipase)?

Let us first clear out some basic concepts regarding lipase, colipase and bile salts. The pancreatic lipase has an optimum pH range of about pH 8.0 (Worthington). This can be understood easily by Le Chatelier's principle: as the reaction moves forward, there is reduction of pH (due to formation of fatty acids). So, a basic pH would help the reaction in moving forward. See this diagram (Worthington):

It can also be understood on the basis of lipase's optimum pH, which lies between pH 8-9. See the graph (orange line) (Chegg):

This optimum pH is brought about by bile salts. Bile salts are slightly alkaline, with pH range of about 7-8 (Britannica). This helps lipase in catalysing its reaction. Bile salts also help lipase by increasing the surface area of fat droplets. Bile molecules have a hydrophobic and hydrophilic part. The hydrophobic part is attracted towards fat while the hydrophilic part is attracted towards water. This helps stabilize fat droplets by emulsification i.e. breaking the fat droplet(s) into smaller parts. This also increases the surface area of fat droplets.

Now, the matter gets complicated when we talk about concentration. Since bile molecules contain hydrophilic and hydrophobic ends, they tend to form micelles with increasing concentration (just like soap). As long as its concentration is below critical micelle concentration, it will carry on emulsification and increase lipase activity. But when its concentration becomes more than the critical micelle concentration, it will form micelles and not carry on emulsion. This significantly reduces lipase activity by not only decreasing surface area, but also reducing pH to slightly acidic (Erlanson et al, 1973). This is where colipase helps. Colipase binds to the C-terminal, non-catalytic domain of lipase and stabilizes its active conformation and increases the hydrophobicity binding site (Verger et al, 1999). Colipase strongly binds to the ester bond of the triglyceride molecule, by which its hydrolysis by lipase becomes easy (Mansbach, 2011). Thus, colipase helps in overcoming the inhibitory effect or bile salts on lipase.


Are all body atoms really recycled several times during a life? I heard a point, that all (human) body atoms are recycled withing short period like few years. Recycled means "old" atoms are replaced by "new" ones during metabolism, leaving only structure unchanged.

But this looks contradicting with knowledge about DNA. DNA molecule looks unchanged and the fate of all it's atoms looks known.

Yes I know there are some spontaneous damages which are repaired, but most of DNA atoms remain in place. Even during cell division, 50% of atoms goes to one of the descendant cells. I.e. they don't go outisde body.

So, if the point is wrong concerning DNA atoms, then may it is wrong at all?

Rudolf Shoenheimer and David Rittenberg were key figures in introducing the isotopic tracer technique to biology.
This technique, which may be dated to the discovery of deuterium by Urey in 1933, produced a revolution in biological thought.
Much of the early work was done at the Department of Biological Chemistry at Columbia University under the chairmanship of H. T. Clark.
Up to this time it was thought that the components of tissues were relatively stable, and that ingested food was metabolized immediately to provide a source of energy.
The first experiments showed that when deuterated fatty acids were fed to mice, most of the label was initially deposited in adipose tissue.
It was concluded that adipose tissue acts a 'fuel depot' that is in a state of metabolic flux and is the direct source of fatty acids burned as a fuel (see here for refs). Fats present in food are not primarily used an an immediate energy source.
When a stable isotope of nitrogen became available (N15), it was found that proteins were also 'in a state of dynamic flux' and were being continuously regenerated and broken down.
The first experiments were done with N15-labeled tyrosine and it it worth quoting from the paper (Studies in Protein Metabolism. VII The metabolism of tyrosine by D Rittenberg Rudolf Schoenheimer &  S. Ratner)

The results indicate that in our rat the nitrogen of at least one
amino acid, tyrosine, was only partly excreted in the urine, while
almost half of it was retained in the body proteins.
Of this deposited nitrogen only a fraction was found attached to the original
carbon chain, namely to tyrosine, while the bulk was distributed over other
nitrogenous groups of the proteins

Shortly after giving a series of lectures at Harvard University in 1941, Shoenheimer took his own life.  The lectures were published posthumously as a classic book called The Dynamic State of Body Constituents.
Further information about the early  work on isotopes, their role in changing completely the way we think about metabolism, and the role of Columbia University in shepherding in this great era, may be found in the following open-access article by Eugene. P. Kennedy:
Hitler’s Gift and the Era of Biosynthesis
Another good reference on the work of Schoenheimer may be found here

So are all proteins broken down and regenerated?  I know of any one exception and that is the lens crystallins where there is virtually no turnover
throughout the life of an individual.
The crystallins in our lens are synthesized at birth and remain with us virtually unchanged for life.
There is a very nice open-access paper on this published in PLOS One:
Radiocarbon Dating of the Human Eye Lens Crystallines Reveal Proteins without Carbon Turnover throughout Life
(Lynnerup et al. 2007)


How much energy is in a human brain's electromagnetic activity? Lately there has been an increased interest on worldbuilding.se about a realistic depiction of fictional creatures who would feed off thoughts and dreams, with some answers proposing feeding off the electromagnetic emissions of the brain.

As a first guess I would think the energy in those emissions is very small. However, has there been any study to give an approximate amount? Most information a quick search provides stems from sensationalist articles which don't look too trustworthy.

The brain does use up almost 20% of the whole body's energy balance, but I would guess most of it is turned into heat.

If one could extract useful work out of the electromagnetic field generated by an average human brain with 100% efficiency, without any physical intrusion (so, the energy potentially available outside of our head), how much would it approximately be? An order of magnitude approximation would be enough.

EEGs pick up about 0.5 to 100 µV on the scalp and about and about 1-2 mV when measured on the surface of the brain, it's about 100 times lower than ECG (heart) signals.

Brain waves have been categorized into four basic groups

beta (>13 Hz),
alpha (8-13 Hz),
theta (4-8 Hz),
delta (0.5-4 Hz).

Votage times current = power. In this case, the amount of current would be/is hypothetical as it would be based on a "salt water" bridge; neurons contain Na+, K+, Ca++, and Cl- ions which are the basis of the current.

EEG measurements must be amplified simply to be seen. An amplifier has to provide a gain of 100 - 100,000 in order to move a delicate needle (and draw the EEG). So, using the amplifier gain as a indication of the amount of current, let's suppose you need as much force to move a pen back and forth as would be required to accelerate a feather one inch in one second.

A feather weighs 0.0082 grams and an inch is 2.54cm. That's about 2 newtons or 2 watts. So, since the current from the brain is amplified 100 - 10,000 times then the wattage picted up by an EEG would be between 0.2 to 20 milliwatts. Supposing that an EEG was only 1% efficient at absorbing the power, then the wattage could be on the order of 20 milliwatts and 2 watts. Altogether brain power might possibly enough to accelerate a feather one inch per second... at around 100% harvesting efficiency.


Can diploidy evolve in absence of sexual reproduction? Theoretical question

Can diploidy (or polyploidy) evolve from a haploid lineage in the absence of sexual reproduction ?
For what theoretical reason? How can such evolution take place?

Empirical evidence

Beside theoretical answers I'd like to also ask for empirical examples:

Are there any examples of diploid (or polyploid) species that reproduce exclusively asexually, and for which sexual reproduction never occurred in the evolutionary lineage of this species?

Or in other words,

Does diploidy (or polyploidy) exist in lineages that has never underwent sexual reproduction?

Is my assumption correct?

I am assuming that in eukaryotes haploidy appeared before diploidy. Is this assumption correct?

By sexual reproduction I mean that the genome of the offspring is a combination (with or without recombination/crossover) of two parent individuals. I don't mean reproduction with sexes (or with mating types). I welcome the discussion of self-fertilization if needed.

I can only offer a partial answer on the theoretical aspects. I don't know if you are familiar with the mid-90s papers by Otto et al. (Otto & Goldstein,1992, Otto & Marks, 1996), but these are definately relevant to your question. They deal with the "masking hypothesis" of diploidy, i.e. that deleterious mutations can be masked by "healthy" alleles, and the trade-offs between diploidy (ploidy level), recombination rate and purging of deleterious alleles. Otto & Goldstein (1992) shows that recombination is essential for the evolution of diploidy, and without recombination haploids will "win" over diploids.

Otto & Marks (1996) is a fairly comprehensive paper that builds on the previous one, and looks at how different mating systems interacts with recombination and purging to influence the evolution of ploidy levels. As a general results they predict a correlation between mating system and ploidy level, with sexual reproduction favoring diploidy while asexual reproduction favors haploidy. However, from what I can see after a quick re-read, there is nothing that prohibits asexually reproducing species to be diploid (and vice-versa) - see e.g. page 206 - and the paper includes a condition that must hold for diploids to invade in asexually reproducing or selfing populations. I have not followed this literature closely though, and I imagine that tracing recent papers that cite Otto & Marks (1996) can be useful to find further relevant studies.

You should also consider that ploidy levels can differ between sexes (e.g. bees), which can lead to antagonistic selection which can influence ploidy evolution (see e.g. Immler & Otto, 2014).

As for the empirical evidence part, I do not have any good examples. However, I imagine that it can be extremely difficult to prove that a lineage have only reproduced asexually (or never asexually), since these things are hard to track in fossils. Also consider that it is common to have both sexual and asexual stages, and many species can have a long asexual diploid stage followed by a shorter sexual haploid stage. From what I know, this is the norm in e.g. algae (arguably a group of fairly "basal" taxa). However, I don't know what the ancestral state of algae was (i.e. if they became diploid before having a sexual stage).

As for the ancestral state of eukaryotes, there seems to be evidence that the ancestral state was in fact facultatively sexual (Dacks & Roger, 1999), which would invalidate your assumption. However, this is only based on a couple of quick literature searches on my part, and I am in no way an expert in this area. There are probably more recent studies on this topic as well. However, it is clear that you cannot blindly assume that eukaryotic haploid is ancestral.


How can we digest lactose even though it has Beta glycosidic linkages? I have Read that we cannot digest cellulose because we do not have enzymes to digest Beta glycosidic linkages in Cellulose

Then how is it that we have an enzyme called Lactase to digest the Beta glycosidic linkages in lactose?

Also If we have evolutionarily developed Lactase ,Why didnt we develop "Cellulase " too ?

One simple  reason is physical interaction.
lactose is only composed of two sugars, while cellulose is giant network of interlocked sugars. Cellulose keeps the sugars tightly packed in three dimensions. even getting to the bonding site is difficult.
human and many other lactases are a huge molecules that would never be able to fit on to a cellulose chain, while cellulase of often a tiny molecule as enzymes go and the active site is not buried in the center. Compare the two enzymes.

lactase

two different cellulase enzymes
Note the big difference in size. Also look at cellulase in action.

Notice it has to peel up the cellulose strip by strip, while lactose is just floating free in solution. This even limits the speed of cellulose breakdown. which means organisms that breakdown cellulose have to spend a log time doing it, while humans have a relatively short and fast digestive timeframe, so even if we could we would not get much from it.
These functional limits also makes a cellulase enzyme harder to evolve, since it can't be too large or in organisms with fast digestive processes.  We often forget the physical necessities of enzyme function. there are plenty of other reasons enzymes do not function on multiple substrates, but this is why is basically impossible to for evolution to change lactase into a cellulose cleaving enzyme.


Cell identification by Body Cells How do the B-cells and T-cells recognize or distinguish a body cell from a foreign particle?

I suspect something to do with this causes Auto Immune Disorders.

Broad question. Summary:

The innate immune system processes everything. When it senses that something is dangerous it tells the adaptive immune system, that is T and B cells, that this thing I'm holding is dangerous (via coreceptors and cytokines).

T and B cells that are specific for this dangerous protein (or sometimes non-protein) are activated.

Ideally T and B cells that react to self proteins are deleted. These are from central tolerance mechanisms when the cells are developing (T and B cells are tested against self proteins; if they react they die) and in the periphery (once they're mature) by them only getting activated by the innate immune system and other mechanisms. There's also T regs which regulate the immune system by preventing any cells that react to self proteins from being activated.

Autoimmune disorders are caused by a break down of these mechanisms.


How to dialyze large amounts of precipitated enzyme solution (ammonium sulfate)? I am no biochemist, but I want to purify some liters of solution through dialysis. What I know are those dialysis tubes in glas vessels on stir plates for labs. But how is this done in industry for bigger quantities in an affordable way?
Background: The solution contains a precipitated enzyme (183 kDa) with ammonium sulfate (132 Da). I want to take away the ammonium sulfate to get back the active state of the enzyme.

Ammonium Sulfate (AS) precipitation is used to concentrate protein. After AS precipitation, you would centrifuge the sample to pellet the protein and then resuspend it in a small volume of water or buffer. You can then dialyze this small volume.

There are other methods of concentrating large volumes of protein, including chromatography and ultrafiltration.


What is the distinction between the terms detrivores, decomposers, saprotrophs and saprozoic organisms? All of them feed on dead and decaying matter (detritus). Detrivores and decomposers are distinct, as it says on Wikipedia, in the fact detrivores consume macroscopic clumps of detritus while decomposers metabolise detritus on a microscopic scale. Are detrivores and decomposers both types of saprotrophs? Also, what exactly does the term "saprozoic" mean, and how is it distinct from saprotroph and decomposer?

Detritivores consume (eat) detritus.

Saprotrophs feed on dead organic matter by the means of extracellular digestion.

Saprozoic organisms are protozoans that are saprotrophs. This actually comes from an obsolete classification of plants and animals where bacteria and fungi were grouped with plants and were therefore called saprophytes if they are saprotrophic. Protozoans were considered animals; so saprozoic.

Decomposer is a broad class including both detritivores and saprotrophs.

Scavengers also consume dead organisms. They are distinct from detritivores because the former consumes a relatively larger amount of dead matter. Often, scavengers are the first to consume dead organisms; the leftovers are processed by decomposers.

I could not find any authoritative source for these definitions. A peer-reviewed article by Getz (2010) attempts to classify organisms based on their eating habits.


Do adjacent axons in a nerve influence each other? Suppose I have a nerve fiber consisting of several axons all running in parallel to each other.  When an action potential is generated in a certain axon, this will alter the concentration of sodium and potassium ions inside the axon, and in the extracellular fluid around that axon.

The question is, will this change in ion concentration in the extracellular fluid, alter the threshold potential of an adjacent axon, which shares the same extracellular fluid?

Yes, activity in other cells can affect the surrounding electric field and thereby influence the behavior of nearby neurons. This phenomenon, known as ephatic coupling, can be important but is usually small.

For many cases, it is likely too small to be of physiological importance. Note that individual action potentials are quite transient and, especially in myelinated axons, the resulting currents are local and small. Therefore it's unlikely that a single neuron's activity will have a noticeable effect on nearby neurons.

However, in unmyelinated axon tracts and/or when a larger group of neurons is active, ephatic coupling is more likely. In particular, it seems to play a role in synchronizing cell populations during oscillations. For example, Anastassiou et al (2011) found that firing of cortical neurons could be entrained by the extracellular field and affected the intracellular membrane potential by about 0.5 mV.

Anastassiou, C.A., Perin, R., Markram, H., Koch, C., 2011. Ephaptic coupling of cortical neurons. Nature Neuroscience 14, 217–223.

Also, for reference:

Jefferys, J.G., 1995. Nonsynaptic modulation of neuronal activity in the brain: electric currents and extracellular ions. Physiol Rev 75, 689–723.

Buzsáki, G., Anastassiou, C.A., Koch, C., 2012. The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes. Nature Reviews Neuroscience 13, 407–420. (see pages 411-412)

Edit:
For your particular case, action potential propagation in one axon is very unlikely to affect the other axons in any relevant way in a tract of myelinated axons. This is especially true because the initiation of action potentials does not occur along the axon itself, but where the axon is just branching from the cell body (the axon initial segment). Threshold is important at the initiation site, but is not really relevant in the tract itself, where the axon is just conducting the signal it receives from the initiation site.


Spatiotemporal patterns in neural networks It turns out that my work in nonlinear dynamics directly maps to a close variant of the Integrate and Fire model. My model produces spatiotemporal patterns that resemble foam. I have to stress that this is  the result of an exceedingly simple model of neuronal activity.

The plot below visualizes the voltage levels of a network of neurons. Yellow is high, purple is low.

I am wondering is these patterns are relevant to the computational neuroscience community. To this end, I am looking for literature describing spatiotemporal patterns in (preferably biological) neural systems.

I am especially interested in any work that  proposes metrics that characterise such patterns since this would allow for a quantitative comparison with my results.

Forgive me is this seems trivial to you, but coming form complex systems theory I did my best and found nothing.

Unfortunately, I haven't looked at this sort of literature for a long time, but here are some thoughts with which to start.

Your question is about "spatiotemporal patterns" of neural systems. One of the first things that comes to mind is neural oscillations (e.g. alpha waves). This is essentially looking for the presence of "frequency patterns" in the neural system. This has a huge amount of literature.

Another methodology that comes to mind is the graph-theoretic approach. In essence, functional or anatomical activity is used to build a graph, which can be analyzed for patterns (i.e. special properties of the graphs of neural systems that are, say, shared across species). One paper: Complex brain networks: graph theoretical analysis of structural and functional systems by
Bullmore and Sporns.

Separately, I might think about the neural correlations literature. Essentially, this is analyzing a neural population by examining the correlation structure of its members, and looking for patterns within it (i.e. that characterize the population code of the system). Two review papers: Neural correlations, population coding, and computation by Averbeck et al
and Measuring and interpreting neural correlations by Cohen and Kohn.
For a review on population codes, see Information processing with population codes by Pouget et al.
This notion is sort of orthogonal to the notion of sparse coding in neural networks, more prevalent in sensory perception.

Sorry if this is broad, but then again I feel the question is quite broad as well. If you have more specific questions, let me know.


X-inactivation in ovaries Background

In all eutherian (mammals excluding the marsupials), the female (who is $XX$ for the pair of sexual chromosomes) inactivates one of her $X$. This is called dosage compensation. This inactivation occurs at a given time during the development when randomly one $X$ is silenced. The daughters of this cell inherit the $X$-inactivation pattern epigenetically, which results in some part of a tissue having the maternal $X$ inactivated while others having the paternal $X$ inactivated (daughters of some other cell which silenced the paternal $X$). This process yield to the famous turtoiseshell coat in female cats.

Question

In short

Assuming X-inactivation occurred in the lineage of the oogonia/oocytes, when does the X-inactivation and X-reactivation occur in the lineage of the oocytes?

A bit developed

Are the X inactivated as well in primary oocytes? If not, is the $X$ inactivated in the secondary oocytes in a primary follicle? If not, did the diploid mother cells of the secondary oocytes have one $X$-inactivated? If yes, did all diploid mother cells of oocytes have the same $X$ inactivated (inactivation occurred relatively early in the development or is there an imprinting) or did the mother cells of oocytes differ in the $X$ they have inactivated (inactivation occurred relatively late in the development)

See these two papers:

Early Loss of Xist RNA Expression and Inactive X Chromosome Associated Chromatin Modification in Developing Primordial Germ Cells
X Chromosome Reactivation Initiates in Nascent Primordial Germ Cells in Mice

Basically it happens just before the meiosis.


Molecules and human memory Has it been demonstrated that the memory of human brain is just connections between neurons, not "long" molecules such as RNA or proteins?

The idea that memories could be stored as RNA or proteins is an old one.  It got a lot of attention decades ago when James McConnell did a number of experiments where he conditioned planarian flatworms to respond to certain stimuli, ground them up, fed them to worms that hadn't gone through the conditioning.  He claimed to have observed that the worms fed conditioned worms learned to respond to the stimuli faster.  This supported the idea that memories were just RNA or proteins, and thus survived the grinding up process.  His results were not readily reproducible, and so the idea fell out of favor.

There have been a number of studies at this point that have been able to look at the firing of individual neurons and shown that there are unique patterns that respond to different stimuli, for example: http://www.ncbi.nlm.nih.gov/pubmed/10966627  So I think it is pretty well established that there are certain connections between neurons that are critical, sometimes even individual neurons.

That doesn't necessarily rule out that there are unique RNA or proteins in those specific neurons, and they are whats actually storing the memory.  I'm not a neuroscientist, but I think the biggest argument against such a storage system is simply the speed with which you can recognize something.  When you see a face you know you nearly instantly recognize the person, and have a flood of memories about that person.  If the memories were somehow stored in RNA or protein structures, I think it would take much longer to somehow "read-out" that data from the molecular structure.  The only thing that really works that fast are the action potentials in neurons.

An interesting comparison might be made to the system in our bodies that DOES have molecular-based memory, the immune system.  When you get sick with a cold you've never been sick with, your immune system doesn't immediately recognize the antigens that come from that virus.  Through the process of somatic hypermutation, your body produces B- and T-cells that have protein receptors that recognize the viruses and the cells infected by the viruses and go and kill them.  A small subset of the T and B cells that have the molecular recognition of that cold become 'memory' cells.  These memory cells that go into a quiescent phase, waiting around until the next time that cold infects you.  But that time they 'remember' it immediately, and you dont get nearly as sick, if at all, because the genes for those recognition proteins are stored in the memory cells.  The activation of immunological memory cells takes a long time as compared to remembering a face, or some other normal memory function, so such a molecular system couldn't be responsible.


How to get the file of a published phylogeny of a taxon If an article has a published phylogeny, is it common to get the newick file with branch lengths from the authors? In order to do further research with the tree.

It is standard practice for authors to publish their trees on TreeBase for other people to use. They'll usually list the link in the supplementary material of the paper. Some journals made this a requirement for authors.


How would one go about isolating a specific mRNA out of a pool of others? I'm writing an essay about DNA recombinant techniques where the question asks to outline all the steps to arrive at having a colony of bacteria expressing a  gene of interest.The question makes you start with a pool of mRNAs, which I assume is for making cDNA. However, how do you go from having thousands of different mRNAs to just one kind?

First of all you need to figure out what your goal is: an expression vector (i.e. plasmid) which will drive expression of a gene in bacteria (let's say E.coli), and your gene's coding sequence needs to be downstream of the promoter in that construct.

Your task is asking for a pretty routine lab task known as cloning (https://en.wikipedia.org/wiki/Molecular_cloning). Your mRNA pool might be the result of an RNA extraction from a tissue sample and your goal is to get bacteria that produce lots of the desired protein.

As this is homework, I will only give a broad overview and leave you to figure out the details.

Indeed one way you could approach this is actually some method to specifically extract the desired mRNA, then generating cDNA from it and pasting that into the vector. This is unlikely to give you good success rates, and in practice nobody purifies a specific mRNA unless they are interested in other molecules naturally bound to that mRNA.

Since this is a procedure with a very practical purpose without a scientific question behind it, there's a much more efficient way to achieve it.

Generate cDNA for all mRNAs in the mix ("first-strand cDNA synthesis").
Instead of removing unwanted RNAs, simply amplify the desired one using specific primers you designed and PCR. This gives you what is called the "insert".
Most likely if you ordered the expression vector online, you actually receive bacteria containing it, so you first have to culture those and extract DNA from the culture ("miniprep").
Next step is to paste the DNA into the expression vector. For this you need to digest both the vector and your insert using the same restriction enzymes ("restriction digest"). (Your insert will not have restriction sites on it, so you will need to introduce them by designing the primers for the PCR in step 2 appropriately.)
Run the restriction digest mixes on a gel (electrophoresis), identify the bands corresponding to the insert in one lane and the vector in the other, and extract them (gel extraction).
Ligate the insert and vector
Transform the finished product into competent E.coli


Is one DNA molecule same as one chromosome Is one DNA molecule = one chromosome or is one DNA molecule = all the chromosomes, ie, all the genetic material in our cells? I have googled it but  I am not getting clear answers ?

Considering the encyclopedic definition of a molecule...

  Molecules are held together by shared electron pairs, or covalent bonds.

...one DNA molecule is one DNA strand.

Put another way, one DNA molecule is a polymer of nucleotides connected by phosphodiester bonds. This means that one intact double-stranded chromosome is composed of two molecules of DNA interacting by hydrogen bonds.

In practice, however, one piece of double-stranded DNA is commonly called a DNA molecule.

All of the chromosomes in a cell constitute a single genome.

To further add to the confusion, identical chromatids may be said to compose a single chromosome, such that one replicated chromosome composed of two chromatids may comprise four DNA molecules, by the definition outlined above.

Note, the same encyclopedia lists ionic bonds as being on the same "continuum" as covalent bonds...

  Ionic and covalent bonding therefore can be regarded as constituting a continuum rather than as alternatives.

...so atoms held together in ionic interactions are also considered molecules, by this definition.


can a point mutation cause a frameshift? During translation initiation, a tRNA loaded with Methonine binds to the small ribosomal subunit. Subsequently, a mRNA molecule, recognized by the 5 cap, binds to the small subunit, and the tRNA scans the mRNA molecule for the presence of AUG which is the start codon. A point mutation could result in the the sequence AUG to be present after the ribosome binding site, but upstream of the "true" start codon.

Question 1:Will translation start at the mutated site?

Question 2: Could the mutation result in a frameshift, with a truncated protein as a consequence?

I have not found much information about this. I did find one homepage, with lecture notes from a genetics course at University of New Mexico referring to this type of mutation as a start-gain mutation.

http://www.discoveryandinnovation.com/BIOL202/notes/lecture14.html

"Start gain. A start-gain mutation is a point mutation creating a new ATG start codon upstream of the original start translation site. If the new ATG is close enough to the original one (so that it is within the processed transcript and downstream of a ribosome-binding site) and in frame, it will be used to initiate translation, adding amino acids to the amino terminus of the original protein. It is also possible for a start-gain mutation to be out of frame, which will not affect translation of the original protein. In general, start-gain mutations have a low impact on gene function."

I have not come across the term start-gain mutation before, but it sounds like what I am describing.

Question 3: If the start-gain mutation is out of frame, why will it not affect translation of the original protein?

Question 4: It is my understanding that the start codon sets the reading frame, and not the bases prior to the start codon. If the bases prior to the start codon are also "read" in triples, which position in the mRNA transcript sets the reading frame?

Thanks

I saw the OP edited it's question quite a lot.. This answer answers the questions before the edit, I will not delete this because it will maybe help other people
I'm not sure if you fully understand the terms you used so I will start with clarifying these.
Missense mutation

  a point mutation in which a single nucleotide change results in a
  codon that codes for a different amino acid (wiki)

Example

    DNA: 5' - AAC AGC CTG CGT ACG GCT CTC - 3'
         3' - TTG TCG GAC GCA TGC CGA GAG - 5'
   mRNA: 5' - AAC AGC CUG CGU ACG GCU CUC - 3'
Protein:      Asn Ser Leu Arg Thr Ala Leu

-------------------------↓↓↓↓↓↓↓--------------------------
    DNA: 5' - AAC AGC CTG CTT ACG GCT CTC - 3'
         3' - TTG TCG GAC GAA TGC CGA GAG - 5'
   mRNA: 5' - AAC AGC CUG CUU ACG GCU CUC - 3'
Protein:      Asn Ser Leu Leu Thr Ala Leu

The 4th codon which was CGT (and GCA on the other strand) is changed because of a subtitution of the G for a T. Because of this change the codon will not code for Arg anymore but instead it will code for Leu. So a missense mutation causes the sequence to be in the same frame as before however a codon is changed and subsequently an other amino acid is added to the polypeptide chain during translation (this is not always the case see wobble)

Frameshift mutation

  A frameshift mutation (also called a framing error or a reading frame
  shift) is a genetic mutation caused by indels (insertions or
  deletions) of a number of nucleotides in a DNA sequence that is not
  divisible by three. (wiki)
  Example

    DNA: 5' - AAC AGC CTG CGT ACG GCT CTC - 3'
         3' - TTG TCG GAC GCA TGC CGA GAG - 5'
   mRNA: 5' - AAC AGC CUG CGU ACG GCU CUC - 3'
Protein:      Asn Ser Leu Arg Thr Ala Leu

-------------------------↓↓↓↓↓↓↓--------------------------
    DNA: 5' - AAC AGC CTG CTT ACG CT C    TC - 3'
         3' - TTG TCG GAC GAA TGC GA G    AG - 5'
   mRNA: 5' - AAC AGC CUG CUU ACG CU C    UC - 3'
Protein:      Asn Ser Leu Leu Thr Leu ..........

In this case the nucleotide T is removed and thus causing a framehift because we need tree bases to form a codon. by removing a nucleotide we just read further till we find a third base and this will be our "new" codon. This new codon does not code for Ala anymore but will code for Leu. (I added the dots because of the fact that the stop codon will/can be shifted and the transcript can be either shorter or longer (the previous stop codon will no longer exist).

  Could a missense mutation cause a frameshift

In the case of a missense mutation the DNA sequence will be in the same frame (no nucleotide is added or removed) and in the case of a frameshift a nucleotide needs to be added or removed and therefore a missense can't cause a frameshift.

  such that a mutation results in the sequence AUG?

Both a missense and a frameshift could result in a start codon.
Example (frameshift)

mRNA 5'     AAC AUU GAC 3'
Protein:    Asp Ile Asp
    -------------------------↓↓↓↓↓↓↓--------------------------
mRNA 5'     AAC AU G  AC.... 3'
Protein:    Asp Met   ........

Example (missense)

mRNA 5'     AAC AUU GAC 3'
Protein:    Asp Ile Asp
    -------------------------↓↓↓↓↓↓↓--------------------------
mRNA 5'     AAC AUG  GAC 3'
Protein:    Asp Met  Asp

So both a frameshift mutation and a missense mutation can introduce a Met --> a start codon.

  a mutation results in the sequence AUG to be present in the transcript
  but upstream the start codon?

A gene is only transcribed if this gene is preceeded by the appropriate sequences:

The start codon will be present in the first exon so the only way to put a start codon before the "old" start codon while remaining all other sequences(UTR,promtor, enhancers etc.) in tact is to "create" one just behind the 5' UTR and before the "old"  start codon in the first exon. This can be done by just inserting AUG in there, HOWEVER we are talking about point mutations:

  A point mutation, or single base modification, is a type of mutation
  that causes a single nucleotide base substitution, insertion, or
  deletion of the genetic material, DNA or RNA

The start codon we are talking about is positioned AFTER the 5' UTR (as said above):

By inspecting the "general" 5'UTR sequence we can see that there are already "start codons" (not really start codons because they are not translated") present before the start codon. We could probably add one using a frameshift or a missense mutation as described above and in your edited question:

  If the new ATG is close enough to the original one (so that it is
  within the processed transcript and downstream of a ribosome-binding
  site) and in frame, it will be used to initiate translation, adding
  amino acids to the amino terminus of the original protein

As far as I can reason is the only way to create a start codon BEFORE the old one is to change the UTR. As stated in your queation this can only "work" if the UTR parts which have an important function are not affected. Further to get this working the 5'UTR should contain a (not "important" )sequence which can be mutated tot form an AUG (see my explanation above)


Why do humpback whales sing songs? Scientists have documented that it seems to only be male humpback whales who sing structured songs, but do we know what purpose their songs play?

There are four hypotheses with varying levels of supporting evidence for why humpback whales sing.

Yes, only males have been shown to sing. It used to be thought that the songs only occurred on breeding grounds and therefore served a reproductive purpose. However, songs have since been recorded on migration routes and feeding grounds, though not as prolifically.

The hypotheses are:

"Mate Attraction" whereby males sing and females approach them to mate. No evidence has ever shown a female humpback whale approach a singing male. Rather, a group of males will swim after a female, vying for position, until she is receptive to mating. Then the closest whale (the primary escort) will be best poised for success. In my opinion, this is the least plausible hypothesis.
"Lekking" whereby a group of males sing to stimulate the females to begin estrus and advertise their body size and health for female mate choice. https://en.wikipedia.org/wiki/Lek_mating This may allow for female selection of choosing a mate later while being pursued as part of competitive group. I am unaware of which articles support this hypothesis and provide evidence. Birds and land mammals are much easier to observe in a lekking behavior than any underwater animal is.
"Territory establishment" whereby males sing to mark their territorial bubble of water. If a male has a larger territory, then it is more likely a female will pass through that larger territory so that the male can respond by pursing her. This could be supported by proving that male humpback whales respect each other's territories and space themselves consistently across their watery world. Refer to http://dx.doi.org/10.1121/1.4962217
"Orientation by echolocation" has recently been put forward by Edward Mercado that song reflects on a broad scale around the whale's environment to provide feedback for navigating the general area. Many researchers argue the plausibility of such low frequencies echoing effectively.

New studies into cultural transmission of parts of songs across ocean basins may suggest the song is not just for reproduction but to fulfill wider communication needs or generate a form of social creativity. See work by Ellen Garland.


Cortico-cortical connections I wonder what the principal ways of (direct) cortico-cortical connections are.

I came up with the following possibilities:

vertical: a cortical neuron connects to another one in roughly the same cortical column, but in another layer
horizontal: a cortical neuron connects to another nearby one, preferably in the same or neighboring layer
"intragyric": a cortical neuron connects to another one in the same gyrus (see here)
interhemispheric: a cortical neuron connects to another one in the same (or neighboring) area of the opposite hemisphere

Are all of these relevant? And/or are there relevant but completely different ways of cortico-cortical connections, e.g. "intergyric"?

Addendum: Maybe too late I found a concise summary in the Wikipedia articles on white matter and association fibers (the latter term I wasn't aware of when I asked my question), which doesn't contradict and complements Bryan's answer:

intracortical (Bryan: "intracolumnar" vs. "horizontal")
short association fibers ("also called arcuate or U-fibers [...]  connect together adjacent gyri")
long association fibers which "connect the more widely separated gyri and are grouped into bundles" (often called fasciculi, but probably not exclusively)
commissural fibers (Bryan: "callosal projections")

There definitely seems to be no reserved name for something like "intragyric" fibers (see second addendum here).

Your question "are all of these relevant" doesn't make much sense to me, but I am going to assume you are talking about it in terms of terminology and answer that way.

The "vertical" connections you describe are usually referred to in the context of cortical "columns" and are therefore referred to as "intracolumnar." Within a column, intralaminar connections by far dominate the total number of synapses, but connections between layers are also important (note that my answer Cortical projections from layers 2/3 back to 4? covers some of this as well, though that question is much more specific).

Horizontal connections refer to connections between cortical columns of the same cortical area (e.g., from V1 to V1 with a different orientation selectivity). These are often stronger between the same layers, but simply saying "horizontal" does not specify that you mean intralaminar horizontal connections.

"Intragyric" is not a word that is used - I think you made it up. Gyri aren't really specialized functional units, and although there may be some brain areas that are localized within a gyrus many span either several gyri or share a gyrus with other areas (for example, "Heschl's gyrus" isn't even just one gyrus). Therefore, you can't really generalize "gyric" connections as being in a particular class, you would have to refer to the specific areas that are connected to understand the nature of those projections.

Interhemispheric connections are fairly ubiquitous in neocortex, and they make up several white matter tracts that connect the hemispheres, most prominently the corpus callosum. As such, those connections are also often referred to as "callosal" projections.

Other terminologies that are used are "top-down" versus "bottom-up" according to the position of areas in the cortical hierarchy. "Lower" areas are considered to be those with primary sensory and motor functions, whereas higher areas are associative/executive areas. The canonical reference for these projections is Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral cortex (New York, NY: 1991), 1(1), 1-47. The key feature of top-down versus bottom-up projections is a difference in the interlaminar pattern of connectivity between different cortical areas. It can be hard to really parse the precise hierarchical of some of the higher-order cortical areas, and the patterns of top-down and bottom-up are fairly mixed for areas at similar levels of the hierarchy, however.


What is this insect (Germany)? It was hovering and in between it was very fast and hard to photograph. I'm not even sure if it is an insect? Photographed in Germany.

It's hard to tell from your photo, but you should check whether Macroglossum stellatarum (German: Taubenschwänzchen/ English: hummingbird hawk-moth) looks similar to what you've seen.

This moth is living in Germany (and other regions) and due to it's way of flying (hovering and audible humming) it's sometimes confused with a hummingbird.


Is there some genetic variance underlying music appreciation? Is there any research done on the genetic variance for Music appreciation?

If not, why is there no genetic variance for this trait?

In 2013,
Dr. Liisa Ukkola-Vuoti, University of Helsinki, Finland, done a detailed GWCNV(Genome-Wide Copy Number Variation) Analysis of certain group of people for musical creativity and aptitude.

Genome-Wide Copy Number Variation Analysis in Extended Families and Unrelated Individuals Characterized for Musical Aptitude and Creativity in Music

They did a Genome Wide Copy Number Variations (CNVs) in five extended
pedigrees and in 172 unrelated subjects characterized for musical
aptitude and creative functions in music
Muscial Aptitude is taken as Sum of Scores of Auditory structuring ability, Seashores test for pitch and for time. Along with data on creativity in music was surveyed using a web-based questionnaire.
Several CNVRs containing genes that affect neurodevelopment, learning
and memory were detected.
A deletion at 5q31.1 covering the protocadherin-α gene cluster (Pcdha 1-9) was found co-segregating with low music test scores (COMB) in both sample sets. Pcdha is involved in neural migration, differentiation and synaptogenesis.
Creativity in music was found to co-segregate with a duplication covering glucose mutarotase gene (GALM) at 2p22. GALM has influence on serotonin
release and membrane trafficking of the human serotonin transporter.
Genes related to serotonergic systems have been shown to associate not only with psychiatric disorders but also with creativity and music perception.
Both, Pcdha and GALM, are related to the serotonergic systems influencing cognitive and motor functions, important for music perception and practice.
A 1.3 Mb duplication was identified in a subject with low COMB scores in the region previously linked with absolute pitch (AP) at 8q24.
No differences in the CNV burden was detected among the high/low music test scores or creative/non-creative groups.

  In summary, CNVs and genes found in this study are related to
  cognitive functions. Our result suggests new candidate genes for music
  perception related traits and supports the previous results from AP
  study.

Source:

[1] Genome-Wide Copy Number Variation Analysis in Extended Families and Unrelated Individuals Characterized for Musical Aptitude and Creativity in Music

[2] Musical Aptitude Is Associated with AVPR1A-Haplotypes


How did multicellular life evolve? I can imagine several specialized unicellular beings collaborating. But how does life get from that point to a unique pluricelular being that reproduces into another pluricelular being?

The key is specialization: e.g. some cells specializing in getting food, others in producing something sticky to keep them together. Which cell does what is usually determined by chemical signals: depending on their specialization they produce particular chemical compounds. So if a non-specialized cell notes that one compound is rather low because the specialized type of cell producing it is in low supply then it specializes that way.

While initially all cells are capable of reproduction, at some point there also will be cells specialized for reproduction, whereas the others lose the ability to reproduce to better concentrate on their specialized duty. Hence the other cells do not have an independent existence anymore but exist only as part of the larger organism. When such an organism is then to be considered a separate pluricellular entity is a matter of definition: if it is an entity independent of the original (e.g. capable of moving away)? if sexual reproduction happens?

Wikipedia also has some things to say.


Designing genes with DNAWorks: Maximum nonzero score? I'm designing a gene in DNAWorks, and I'm unable to find a set of conditions that gives an "overall score" of zero (which is what I normally insist on). People that have used DNAWorks: what's the highest nonzero score you've been able to successfully assemble?

You might want to read Gibson's paper on the step-wise assembly of the mouse mitochondrial genome (1):

He started with 60b long oligos with 20b overlap, as he assembled 5 of those 60-mers into a backbone, obtaining 384b fragments. On the next step, he joined 5 of those 384mers, obtaining 1.2kb constructs. You can do the same, but on the second step use 2x 384mers to get you ~600bp gene. Gibson didn't use DNAWorks to chop up the sequence. He just started from base 1, so that his fragments were F1 [1:60], F2[41:100], F3[81:140], etc.

I think that 15b homology is pretty low (Gibson used 20b for assembling the 60mers in the first step, and 40bp homology for the next assemblies). 60b oligo length is standard.

You can also try one step assembly with all of your oligos (via PCA) as you planned, but I think that the two step assembly might be more efficient.

Let me know if you need more help.

1. Gibson et al, 2009. Chemical synthesis of the mouse mitochondrial genome


What do different fermentation products have in common? I met with the following question in my masters course:

  What do different fermentation products have in common?

Thinking about this, I have difficulty in identifying the similarities between lactic acid and alcohol fermentation.

Although there is  no net oxidation or reduction in glycolysis, a constant supply of  NAD+ is (paradoxically) required in order for glycolysis to continue. Otherwise, the glyceraldyde-3-phosphate dehydrogenase reaction (GAPdh) could not generate 1,3-diphosphoglycerate.

So how is the NADH generated in the GAPdh reaction converted back to NAD+? Both alcohol and lactic acid fermentation regenerate NAD+ by reduction of the carbon skeleton that was oxidized in the GAPdh reaction, albeit at different 'points' in the glycolytic reaction sequence.

In alcohol fermentation, alcohol dehydrogenase acts as aldehyde reductase, reducing acetaldehyde to ethanol and NAD+.  In lactic acid fermentation, lactate dehydrogenase acts as a pyruvate reductase, reducing pyruvate to lactate and NAD+.

In both alcohol and lactic acid fermentation, there is no net oxidation or redution: glycolyis is the splitting of glucose.

Finally, we may note that the electron acceptor in both cases is 'internal'  Neither process requires an external electron acceptor such as oxygen.  The electrons removed from the carbon skeleton in the GAPdh reaction (generating NADH) are added back to the same carbon skeleton (but with different molecular arrangement) in both the ADH and LDH reactions.


Datasets of aligned nucleotide sequences Where can I find some datasets of aligned nucleotide sequences? And what should I assume about the accuracy of the alignments there?

(I would like to use such datasets for training the alignment model I am working on. In particular, to help me get an estimate on some parameters such as the frequency of single nt INDEL at some locations.)

You can find 46-way multiz alignment from UCSC genome browser, it is down on comparative genomics part and labelled as "cons 46-way", which is a genome alignment of 46 vertebrate species. You can use data on their genome browser on the site, or get download information here.

If you are interested in pair-wise alignments, I don't know of any pair-wise alignment database, but in fact you don't need one. You can search for nucleotide sequences from NCBI nucleotide database and align them using BLAST on their website. BLAST is maybe the most common tool for pair-wise alignments and also for database alignment searches, where a single query sequence is searched for matches throughout a database of sequences. If you want to do a large number of alignments, you can download BLAST to your computer to do them faster.


Is it possible to genetically alter human beings to see parts of the infrared? Most electron transitions take place in the infrared region,The ability to see this part of the electromagnetic spectrum without reliance on sophisticated technology would have tremendous advantages. Is it possible to manipulate human genes to see this part of the spectrum?

Our heads are warm, so the receptors that react to infrared radiation would be set off constantly by ambient radiation, not just radiation that comes in through the eye.  Note that the animals that do see infrared are cold blooded.

So it would be a massive genetic engineering project to get working infrared vision, to either make human heads be room temperature, or to thermally insulate eyeballs from the surrounding tissue.


Can we use cancer cells to generate blood vessels? Is there any possibility to use cancer cells, which generate blood vessels, to generate our blood vessels when we are wounded or when we have varicose veins in our legs?

Thanks for your answer in advance.

Using cancer cells in this manner would be far too dangerous, as there is nothing to prevent the cells from implanting and forming new tumors. Fortunately, we already know a great deal about angiogenesis, which is the process by which new blood vessels are formed or grown out of existing ones. If you want more details on how the process works, the article I linked to goes into a good amount of detail regarding the key players and how they interact.

It would be much easier (and safer) to use our knowledge of the cytokines and growth factors responsible for blood vessel formation to develop biological therapies that could potentially be used to treat varicose veins. However, current therapies can be quite successful, and there may not be a large enough market to justify the quite large expense required to develop angiogenesis-based therapies.

Unless a patient has some sort of genetic or other issue, angiogenesis is already involved in wound healing. As new tissue grows back, capillaries and perhaps slightly larger blood vessels expand out from the nearest sufficient vein/artery pair to vascularize the new cells. There may be issues with patients who are taking angiogenesis inhibitors as part of a therapy plan for cancer, for example, in which case compromises would have to be made if necessary.


Expression of red and green fluorescences in the same tissue In this article (https://jcs.biologists.org/content/122/14/2351), especially in Figures 1 and 2, they show the expression of GFP and red fluorescence in the same tissue, and I feel like that red fluorescence is present where GFP is expressed (though weaker than where GFP is absent), but I wonder why it's not yellow? Usually, when these two are expressed in the same cells (in this case, GFP is in cytoplasm and red indicates a membrane protein), the yellow color is observed, not like this. In this article, I feel like I see some red below green if that makes sense...

If anybody knows what this means, please give me some advice!
Thank you.

These images are not typically taken using color cameras. They are taken using grayscale cameras, using filters that allow the excitation wavelengths to hit the sample and the emission wavelengths to go to the camera.

For visualization, these black and white images are often put into the red or green channel in a digital image (TVs and computer monitors make color by mixing different amounts of red, green, and blue light: RGB). If you have red and green together that shows up yellow to a human eye, but that doesn't mean any yellow light is involved: it's just perception.

If you don't see yellow in these images it's because the red and green emission were not in the same place.


Does the human ear adapt to noise levels? I have noticed lately that if I go to sleep, when I have my radio running, it is on lowest volume, I still consider it kind of loud.
In the morning, when being on the edge of waking up, I hear the birds, and the tennis balls already being batted on the court nearby, but I do not hear my radio. If I wait a few more minutes, I start to hear the radio, with no changes in the sound levels outside.

I know that the human eye adapts to the light levels (aperture, what cells used), but is there something similar for sound sensitivity?
Note, the radio is on that occasion running all night long, with always the same sound level.

In  this instance, I would say your attention has been adjusted, not your ear's ability to perceive sound. Our ears don't have a control setting or a means of adjusting incoming sound levels (though I'm certain when an ambulance with loud siren drives by, we all wish we did).

What you are experiencing is a prioritization of the sound by your brain in relationship to other sounds.

You put the sound on before you go to sleep. Your brain accepts that incoming sound as non-vital, non-threatening sound. (Radio, meant to soothe, supposed to be there, relegate this sound to innocuous)
Come dawn, new and novel sounds appear. For our brains, the new and novel could indicate a threat, so your brain prioritizes that sound over the known and considered innocuous sound (your radio) which it has heard all night. Birds, tennis balls on courts are distinctive enough your brain would prioritize them even though you know in your conscious mind neither is an actual threat.
As you waken, your brain then reminds you there is still another sound in your environment which is not threatening and yet still prevalent (your radio) prompting you to decide if you want to do anything with the non-threatening sound.

Yes, this is an oversimplification of a very complex process of sound prioritization but most modern science bears this out. As a curiosity, our minds are predisposed to seek out information which may be vital to us, hence the reason conversations held by other people who are on the phone are so distracting because our brains dislike hearing things which may be necessary to our survival but only hearing half of the conversation.

EDIT:

As I was reminded there are some involuntary control elements built into the ear via:

the tensor tympani muscle whose role is to dampen sounds (mainly internal ones such as chewing)
and the stapedius muscle which dampens the ability of the stapes vibration and protects the inner ear from high noise levels, primarily the volume of your own voice.

You can thank the stapedius muscle for making your voice sound so strange to you when you hear it on a recording. You have never truly heard your voice until you hear an external recording and playback of it!


Should I consider [H+] as substrate in MCT transport equation? I'm trying to model the transport of lactate in cells (in both direction via Monocarboxylate transporters):

[Lactate]intra + [H+] <----> [Lactate]extra + [H+]

I found some data on kinetics of Lactate itself (Km and Vmax) but I don't find anything on [H+].

My initial thought was to consider [H+] as a substrate, and model the transport as a sequential ordered Bi-Bi reversible reaction (from this paper: Poole & Halestrap (1993). Transport of lactate and other monocarboxylates across mammalian plasma membranes. doi:10.1152/ajpcell.1993.264.4.c761)

But it require a lot of parameters (Ki, Km, Vmax) for each substrate involved (especially H+).

So my question is: Should I consider [H+] as a substrate or just as an external parameter that impact the direction of the flux ?

Thanks everyone

(first question on Stackexchange)

To include or exclude the H+ basically depends on the scope of your model. The H+ can be used as external parameters if you assume that both sides of the membrane are well buffered and the pH will not change. If you want to simulate a condition during which the pH changes, like for example strong exercise in muscle or ischemia, then you would need separate H+ for each side of the membrane.


Does the minimum spanning tree tell us anything useful about evolutionary ancestry? Question migrated from bioinformatics stackexchange due to lack of interest.

I'm new to bioinformatics and have been reading through a bioinformatics book, and it seems calculating a phylogenetic tree is quite a complicated process.

I'm wondering if generating the minimum spanning tree (MST) from a similarity matrix would provide a decent approximation to the actual phylogenetic tree, i.e. provide some information on the evolutionary ancestry of a collection of organisms?  My thinking is that animals diverging from ancient ancestors will always be farther away than animals that diverged recently, so the MST will at least show me what animals are genetically related and which are genetically distant.

I realize this is not quite the same thing as a phylogenetic tree, but it seems to give me some of the same information provided by a phylogenetic tree, namely which animals are closely genetically related and which are distant relatives.

For reference, I'm measuring similarity based on the normalized compression distance (NCD) metric.  The metric is defined in "Clustering by Compression" by Cilibrasi and Vitanyi.

Here is an example MST using the dataset from the referenced paper.  Some parts make sense from my rudimentary knowledge of biology, like the clustering of primates.  Other parts are new to me, and I'm not sure if the relationships are just an accidental feature of the metric, MST, or if real.  For instance, cows are more related to whales instead of horses according to the MST, cats and dogs appear to have evolved from seals or visa versa, and pigs are related to a wide variety of animals: ranging from bats to rabbits to whales.

Note, the 'randgen' nodes are randomly generated DNA sequences that I added to the dataset as a sanity check.  As expected, they are off on a branch by themselves instead of mixed into the population of real animal DNA sequences.  The reason why they are clustered is because I repeat each DNA sequence 40 times to amplify the signal, and repeated short random subsequences become compressible.  The random DNA sequences are probably clustered because they tend to share random subsequences, while the mammal DNA sequences are orderly and have fewer random subsequences.

Here is the repo to reproduce the tree.
https://github.com/yters/ncd

Your graphic is omitting nodes of the tree, branching points, which are essential for trees and phylogeny.

When you read the data file, you should count the brackets ((( ))) because they signify where the tree has nodes, common ancestors.

You should generate simple phylogeny trees, prior to doing complex data mining for similarity. The names are in latin? there are genetic distance numbers? What format and data are you using? You have given the common animal names. you may have to use a database of common-and-latin-names to be ables to search "tiger"... that database will return "panthera tigris tigris"... And then you can start crawling up and down the tree branches to search for animals related to tigris tigris, by counting brackets and marking species close to that name.

To prevent the tree exploding to 5000 animals, you can
1/define a search depth. Depth 5, Five, will not go further than five brackets: (((((panthera_tigris_tigris)(lion)(cheetah)))))
2/represent a random fraction of the species (1/100 gives 50 animals from a 5000 tree)
3/use statistics measures to select certain animals based on data mining.

If you want to travel from whales to monkeys, you will have most of the mammalian family, and you will be able to count nodes and brackets by the dozens.

Not that parsing 5000 species has a big computational load that can take 1 hour to read through once, let alone 40 times!

Whichever statistics you are using to measure similarity, number of brackets / genetic distance numbers, you should have once represented trees as branches, nodes and leaves, because that is what tree data is meant to represent.

I'd recommend that you draw a tree using nodes and random animal selection, like 1% chance the animal is drawn in the final tree. When your tree has branches and is drawing OK, change the 1% selection line for the complex MST / MCD selection.


What is the reason for cats not liking water? I have two cats myself, a Siberian and a Maine Coon, neither of which like water. In fact, they detest it - like most cats. I was wondering what the reason for this was and if any of you have any interesting theories as to why this is the case.

Thanks in advance!

First, some cats do like water. But it seems true (from personal observation and most people's opinion) that most cats don't.

The question has already been asked many times online. Just Google your question!

I doubt one will find peer-reviewed papers on the question but below is a summary of what seem to be the most often mentioned possible reasons I could find. Of course, these bullet points are very hypothetical and I don't know of any research presenting evidence for or against these hypotheses.

Their fur is not really adapted for the water and will very quickly become waterlogged and heavy making it uncomfortable.
Cats are generally speaking quite skittish
Cats may not like the odour of chemicals we put in the water.
Cats love to groom themselves. It is an aweful lot of work to do the grooming after a bath.

Note also that domestic cats are descendent from cats living in very arid areas. The most closely related species with cats are the African Wildcat living in Northern Africa, the Near East and around the periphery of the Arabian Peninsula.

Source

My non-peer reviewed sources are

http://www.petful.com/behaviors/why-do-cats-hate-water/
http://www.animalplanet.com/pets/healthy-pets/do-cats-really-hate-water/
http://www.petguide.com/blog/cat/why-do-cats-hate-water/


How does CO2 gets diffused into the red blood cells? Carbon dioxide diffuses out of the tissues and into the blood, where it is dissolved in the plasma. While some of the carbon dioxide remains dissolved in the plasma, most carbon dioxide diffuses into our red blood cells. In the red blood cell, some carbon dioxide binds to hemoglobin, forming what we call carbaminohemoglobin.

Do any other gases also diffuse into the red blood cells, if no why does only CO2 gets into the RBCs ?

The red cell membrane is highly permeable to gases because the molecules of gases are small, uncharged, and soluble in lipids, such as those of a bilayer.The effect of 4,4′-diisothiocyanato-stilbene-2,2′-disulfonate on CO2 permeability of the red blood cell membrane Remember red blood cells are  cells like any other cells only that they have hemoglobin and no nucleus. Because they have an ordinary cell membrane, it follows that the laws of diffusion which apply in gases and other cells will also apply with gases and RBCs. Oxygen is the major gas which gets into RBCs, so is carbon monoxide and others


Are the y-axis values informative when performing biolayer interferometry? I am currently reading  an this article by Alexandra C. Walls et. al.
I would like to ask a question about a graph that is being used in the article and I wanted to know if my analysis was correct.

I was wondering if for the Binding Response versus Time graphs of SARS-CoV-2 (panel A), and SARS-CoV-1 (panel B), can we infer that SARS-CoV-2 was more adept at binding to the human ACE2 because the y-axis has larger numbers than for SARS-CoV-1? If not, why not?

From the linked article:

We found that hACE2 bound to SARS-CoV-2 SB and SARS-CoV SB with respective equilibrium dissociation constants of 1.2 nM (Figure 2A) and 5.0 nM (Figure 2B).

An equilibrium dissociation constant (commonly called Kd) represents the propensity of a complex to dissociate into its constituent pieces.  A smaller value represents a smaller propensity to break apart, i.e. a stronger interaction.
So, yes, considering only the data presented, domain B from the SARS-CoV-2 spike protein shows a slightly higher affinity for hACE2 than the equivalent domain from SARS-CoV.  Note, however, that the authors are careful with their wording, and state in multiple places that the relative affinities of the homologous domains are comparable.

The SARS-CoV-2 SB engages human ACE2 (hACE2) with comparable affinity to SARS-CoV SB from viral isolates associated with the 2002–2003 epidemic (i.e., binding with high affinity to hACE2).

What's more telling are the binding constants (kon and koff) given in Table 1:

$$\begin{array}{c|c|c|}
\text{} & \text{SARS-CoV-2 S}^{B} & \text{SARS-CoV S}^{B} \\ \hline
\text{K}_{D} \text{ (nM)} & 1.2 ± 0.1 & 5.0 ± 0.1 \\ \hline
\text{k}_{on} \text{ (M}^{-1} \text{s}^{-1}\text{)} & 1.4 × 10^5  (2.3 ± 1.4 × 10^5) & 1.4 × 10^5  (1.7 ± 0.7 × 10^5) \\ \hline
\text{k}_{off} \text{(s}^{-1}\text{)} & 1.6 × 10^{−4}  (1.7 ± 0.8 × 10^{−4}) & 7.1 × 10^{−4} (8.7 ± 5.1 × 10^{−4}) \\ \hline
\end{array}$$
Values reported represent the global fit to the data shown in Figures 2A and 2B and the averages obtained from five (SARS-CoV-2) or four (SARS-CoV) replicates carried out with different protein preparations are shown in parentheses.

Note that Kd is the reciprocal of the association constant, Ka, which is equal to the ratio of the binding constants.
$K_{a} = \frac{k_{on}}{k_{off}}$, $K_{d} = \frac{k_{off}}{k_{on}}$
Since the values given for kon derived from the global fit are the same for SARS-CoV-2 and SARS-CoV, the observed difference in Kd is due to the different values of koff.  So, at equilibrium, SARS-CoV-2 SB and SARS-CoV SB will associate with hACE2 at the same rate, though SARS-CoV SB dissociates faster.


Insect identification, UK, 07-19 Can anyone identify this insect found in the North East of the United Kingdom, July 2019. About 3-4cm long.

Could this be a wood wasp?

Thanks.

It is definitely a Siricidae and looks like a Urocerus gigas (sometimes called Greater horntail), which is also found in the UK.

In the Nordic countries this is one of the more common species of sawflies, and I suspect the same is true for the UK. The picture below and some info on their biology can be found at species.nbnatlas.org:


How do I measure genetic distance? I'm not sure how to measure genetic distance. There seems to be many different equations out there, and all the ones I found are rather old.

In my specific problem I want to see if the twist in collagen differs if the species are different. (I have a program to predict collagen twist according to amino acid sequence)

I therefore want an objective numerical value to base my comparaison on. "Nei's standard genetic distance" seems good, but it is very old so I was wondering if there was a modern alternative. Is there an R package or something like that to calculate it automatically?

There are a few answers here, it is a little unclear which is closest to what you want.

[edited to be more complete and direct]

1) Nei's distance is mostly for comparing populations of the same species, so it should be fine if that is what you are doing. I am guessing that based on your post, you are more interested in cross-species comparisons. Of course, the logic is the same, it's just the math is different. For among-population divergence, Fst (fixation index) is also commonly used. But if you are using a sequence alignment or some such data to compute genetic distances, there are lots and lots of metrics. Some of them are very simple- for instance you could use Hamming distance and just count the number of residue differences between each sequence.

As for computing these metrics, there is a webserver called GenePop online that will compute Fst for you if you plug in a dataset. I don't know of R packages that compute these things, I would guess just by looking at wikipedia that coding functions to do this would be relatively trivial (if you are comfortable with r).

2) If you are truly looking among species, a somewhat more appropriate approach might be to model your species in a phylogeny, rather than to use distance methods (though the two are attempting to solve sort of the same problem). There are lots of easy-to-use online programs for this, for instance: FastML. You can just copy-and-paste a seq alignment in there. After you have the tree in for instance newick format, there are good tools for visualizing trees both online at iTOL, and through R with APE.

APE also has good utilities for modeling phylogenetic processes, so you could in principle directly model changes in protein folds through evolutionary time (assuming you have a meaningful summary of protein folding, either continuous or discrete).

I don't have enough reputation to link to more of the resources I mentioned, sorry.


What is the biological basis for tiredness after eating? I can sometimes feel quite drowsy after some "meals" (e.g. a cold cut & cheese sandwich with juice on the side) and less drowsy (or maybe less often) after others (such as a salad).

This drowsiness sometimes affects my work at the office, so I wanted to ask these questions:

What biological factors lead to the body getting tired after eating?
Are there any strategies that can be used to minimize this effect?

High carbohydrate meals will undoubtedly increase the relative levels of insulin, increase the shuttling of glucose from the blood to the cells, and leave you fatigued in wake of that. See reactive hypoglycemia. Reducing carbohydrate consumption should, to some level, reduce this effect. Caffeine should just as likely increase blood glucose levels by increasing glycogenolysis through PKA activation.

As Chris Stronks pointed out, eating can cause low blood pressure via redistribution of blood.