Does ChEMBL have a specific definition for what they mean with "Max phase for indication"? ChEMBL lists various properties at pages for substances. I would like to copy some of the data that resides under "Max phase for indication" over to Wikidata. For that it would be good to know the exact definition that ChEMBL uses for "Max phase for indication". Unfortunately I can't find it on their website. Is a definition available somewhere?

This refers to the phase a compound has "achieved" in a clinical trial.

Phases are typically ordered from 1 to 4
(although phases 1-3 are most talked about, as they are needed to bring a drug to market):

  Phase 1: Testing of drug on healthy volunteers for dose-ranging

  Phase 2: Initial testing of drug on patients to assess efficacy and
  safety

  Phase 3: Testing of drug on patients to assess efficacy, effectiveness
  and safety (larger test group)

  Finally, there is Phase 4 (referred to in your example), which is
  after a drug has been approved (by e.g. the FDA or the EMEA): here,
  the effects of a drug while used on the general patient population are
  monitored.

See also https://en.wikipedia.org/wiki/Phases_of_clinical_research

Your example has been approved (i.e. it can be brought to market, or might already be available), while others might still be in ongoing clinical trials. Others might have been "killed" earlier due to e.g. toxicity or side effects. Or have not even entered clinical trials (which would be the majority of compounds).

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


Why does the oxygen produced in the photosynthesis come from water and not carbon dioxide? In the photosynthesis equation:

$$\ce{6CO2 + 6H2O ->[sunlight] C6H12O6 + 6O2}$$

The only place where we have 6 molecules of $\ce{O2}$ is in $\ce{6CO2}$. Then it reacts with $\ce{6H2O}$ to form $\ce{C6H12O6}$ and $\ce{6O2}$ that apparently comes from $\ce{CO2}$. So why do we say that the $\ce{O2}$ produced by plants comes from $\ce{H2O}$ and not $\ce{CO2}$? I don't know if I'm the one who's understanding something wrong or is it the photosynthesis formula which is wrong?

You are missing some knowledge here for sure, photosynthesis is a little complicated at A level, so I will describe it in brief.

During photosynthesis electrons and protons (A hydrogen atom without the electron) are required for a process called the electron transport chain and proton motive force. This happens during the light dependent stage of photosynthesis, (there is also a second light-independent stage called the Calvin cycle, and that is where the CO$_2$ is used), I won't go into detail about what the protons and electrons do (unless you want me to) but you need to know that these come from a water molecule, the water is split using light (photolysis, literally: cutting with light) into two hydrogens and half an oxygen molecule (or an oxygen atom). The oxygen that was released in photolysis is not required for the rest of the pathway, so it diffuses out of the cell.

For why it doesn't come from carbon dioxide, you need to consider the Calvin cycle. In the Calvin cycle, carbon dioxide is converted to glucose by enzymes, using products from the light dependent stage, so 6CO$_2$ are combined over six cycles to form one molecule of glucose. So that is where the CO$_2$ is used as well.

Hope that helped! If you want me to go into any more detail please ask!


Possible to remove accumulated haze on fluorescence interference filters? I have a few different fluorescent microscopes, the two that use Mercury  lamps are older than 7 years. I notice on those that the thin film filters in the filter cubes (green, red, blue) have accumulated this haziness. Both the excitation and barrier filters seem to have this, more so on the ex filter and it's not present on the dichroic.

I've always referred to this as the filter being "burned" and my rational is that it's from the heat & intensity & low wavelengths from the Mercury lamp.  But in all honesty I don't know what it is or if it's removable and if so how? I would like to see if removing it improves my image clarity.

I know a picture would help here and I'm having trouble showing it but will keep attempting and add it to an edit for this question. However I have seen this on many microscopes if you have one with a merc arc lamp and it's getting up there in age take a look at the filters on it. Let me know if you see this too.

Its probably not from heat.  Filters are basically a glass substrate with some ionic compound deposited in thin layers.  These won't oxidize at reasonable temperatures, and furthermore since you have it on the emission filter as well, its even less likely to be from the source.

More likely its just accumulated organic material from the environment.  7 years is a long time, and microscopes are exposed to a lot of chemicals and other substances which can gradually build up on optical surfaces.

Most vendors have a recommended way of cleaning their optics, but usually it involves lens paper or lint free swabs and methanol (or sometimes acetone for more durable stains).  You must be very careful though, as you do not want to scratch the filter.

Semrock for instance has a detailed guide here:

http://www.semrock.com/cleaning-optical-filters.aspx


What is the mechanism behind "acquired" alcohol tolerance? I can understand natural variation in alcohol dehydrogenase (ADH) in a population leading to variation in rate of inebriation (after controlling for other variables -- e.g., mass, food consumption, etc.).

But what physiological (adaptive?) process leads to increased alcohol tolerance over the long term in a single individual?

The subject of alcohol tolerance is broader than it might appear. However, in most cases people refer to what is called metabolic alcohol tolerance. Based on your response to the comment made by Alexander Galkin, I assume that you also refer to metabolic alcohol tolerance.

Metabolic alcohol tolerance is the result of drinking significant amounts of alcohol over a period of time as you describe. Both the amount of alcohol and the duration that it takes to develop an increased metabolic tolerance towards alcohol differ from person to person.

When most people drink alcohol, the liver will responds by activating alcohol degrading enzymes that break down the alcohol molecules, which results in the elimination of the intoxicating effect. The activation of those enzymes occurs much faster with people who have developed metabolic alcohol tolerance and the concentration of those enzymes is generally higher. This means that those people can break down alcohol faster than you and me, that is, they can "tolerate" more alcohol in the sense that they simply get rid of it much quicker.

On a final note, being more alcohol tolerant is not exactly correct as metabolic tolerance doesn't necessarily mean that the organs affected/intoxicated (such as the brain) by alcohol aren't necessarily more tolerant. The alcohol is simply broken down much faster and can therefore have a limited impact.


RNA processing in eukaryotes Why does post-transcriptional  processing of eukaryotic mRNA involve addition of a 3' polyA tail, rather than one of polyU, -G, or -C?

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

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


About Frameshift Mutation I am coding a DNA translater, based on the homosapiens genome, & i knowing that the data provided from NCBI is surely not 100% precise (there may be some base changes / removes etc...)

, & i want to prevent/bypass those mistakes to get a 'close' list of the REAL chain of proteins produced, so i was wondering how the frameshift do not change an entire species, taking into consideration that if 1 or 2 bases are removed , => then all the dna/rna translation will be modified therefore => ALL proteins will change & even the start/stop codons will change its location

(am not a biologist, am asking why the frameshift doesnt do that & create a new species from 1 or 2 base changes??)

Genes (here defined as protein coding sequences) are not perfectly aligned the ones after the others in the genome. In fact, in humans (like in most eukaryotes), only a small fraction (of the order of the percent) of the genome directly code for proteins.

Each gene translation unit starts with specific markers. Not even talking about what will be or won't be transcribed, a translation unit starts with the start codon (AUG). Hence, a frameshift mutation will only affect the gene in which (or even, only the exon) in which the mutation happened.

For writing a software that finds coding sequences (and translate them), you will need to learn much more about genetics. You might want to have a look at an intro course on molecular genetics / central dogma / translation, transcription such as a number of the biology classes on Khan Academy for examples.


Where does the first oxaloacetate comes form in the citric acid cycle? Oxaloacetate forms together with acetyl-CoA citric acid. Now oxaloacetate is used but also re-used again in this cycle. But where does the first oxaloacetate comes from? Is that from the mother or produced by DNA or....?

There's not just one molecule of acetyl-CoA that's going through the TCA cycle. Every intermediate compound is present at a certain concentration, so there will be many oxaloacetate molecules per cell.

When the cell divides, it's split in two and the contents are also divided. So a new cell will also have many oxaloacetate molecules in it. This way the daughter cell can just keep running.

For the "first" oxaloacetate molecule we have to go back billions of years, and this would be a very complex question to answer. My guess would be that the first oxaloacetate molecule was produced by a non-TCA pathway, and the TCA cycle evolved later.


Would a clone of myself have exactly the same development (character, appearance) as me? If I'd have a clone of myself (with my DNA) and I would record the development of that person, would I be able see exactly the same development as myself (same personality, appearance)? For example that at a certain time, that clone would look how I looked like when I was 8?

No, your clone would differ from you. Actually such clones exist in humans also. Monozygotic twins are clones. They certainly look alike but they definitely differ in some respects.

Understanding why this is true require one to understand the concept of heritability from the field of quantitative genetics. You should definitely have a look at the post Why is a heritability coefficient not an index of how "genetic" something is?. The main reason why you would differ is because our phenotype (personality, appearance, etc...) also depends on the environment we experience.


Legality of doing private or scholastic virology with human pathogens? Is it ok for a student, say a graduate student in biochemistry, to do amateur virology using potential human pathogens?

For example, lets say the student gets a cold and tries to isolate the virus causing the cold. Is it ok for the student to do that in a school lab? How about a home lab?

tl;dr I think that doing this unofficially, at home, might be no big deal, but doing it in an institutionally supported lab (or any kind of institutional setting, e.g. if you wanted to publish a paper from the results) could involve lots of hassle and red tape.

I'm not a microbiologist, but ... technically I think this would fall under the category of BSL-2 - via Wikipedia:

  Biosafety level 2 is suitable for work involving agents of moderate potential hazard to personnel and the environment.[9] This includes various microbes that cause mild disease to humans, or are difficult to contract via aerosol in a lab setting.[11] Examples include Hepatitis A, B, and C viruses, human immunodeficiency virus (HIV), pathogenic Escherichia coli, Staphylococcus aureus, Salmonella, Plasmodium falciparum, and Toxoplasma gondii.

BSL-2 requires (among others) access control for labs; special safety training for all lab personnel; use of containment equipment for procedures that may cause infectious aerosols or splashes ...

It may seem a little crazy to lump a common-cold-causing rhinovirus with HIV, but BSL-1 (the mildest level of infectious agent control) is restricted to

  well-characterized agents which do not cause disease in healthy humans

(emphasis added). Note that even BSL-1 requires lab safety protocols beyond those for non-infectious agents.

A bit more internet searching on BSL classification for rhinoviruses (the typical cause of the common cold) suggests some variation: e.g.

Google search for "rhinovirus BSL" brings up a bunch of hits from the American Type Culture Collection (ATCC) for a variety of rhinovirus isolates that range from BSL-1 to BSL-2
the Public Health Agency of Canada classes rhinoviruses as BSL-2


Why is DNA polymerase added at the end of PCR reaction? PCR reaction is used to amplify DNA fragment. Each reaction requires a DNA template, buffer, dNTP mix and a unique pair of primers, one ''forward'' primer and one ''reverse'' primer. The DNA polymerase should be added last to the reaction, just before starting the PCR programme.

My question is, why is DNA polymerase added right before the PCR starts? Is it because it can begin to amplify DNA before adding the reaction to the thermocycler? How could it amplify the DNA when the DNA is not denaturated until added to the thermocycler?

True, the template is double stranded, but the primers could begin amplifying themselves, and any other stray DNA. You don't want any nonspecific amplification in the early stages that could compete with the target fragment. Also, even though Taq polymerase is a very hardy enzyme, it is standard practice to treat enzymes with special care, on ice so they don't degrade (although I have forgotten them on the bench overnight, and they survived that).


Why calf thymus DNA is widely used instead any other body part? Calf-thymus DNA is widely used as DNA sample. Such as testing anti-dsDNA antibody activity, nuclease activity etc, as well as certain books include calf-thymus-DNA in various examples (such as the book Molecular biology by Weaver (ed-5) mentions in a table on % (G+C), that %(G+C) of calf-thymus DNA is 40)

Now; my question is; why a peculiar organ like thymus is selected (and not liver or kidney etc); and not any organ from adult cows (which are more available at any meat shop)? whereas all the otherly-situations should contain the same DNA-sequence? Isn't it a bit weird?

Is it more easy to extract the DNA from a calves' thymus gland?

I've searched web, but nothing helpful I found.

I have crawled through google and many, many journal articles. What I can make of it, is:

"It is generally agreed that from mammalian cells (as, for example, calf thymus..." are capable of yielding high molecular weight DNA from cells, with very little protein present to decrease purity. [From Welsh and Vyska]

Additionally:
"Calf thymus gland is a fairly good source of replicatiue deoxynucleotidyl
transferase (deoxyribonucleic acid polymerase)" [From Yoneda and Bollum]

So we have a good DNA coming from the calf thymus. Calf thymus is also something we have in great abundance (worldwide slaughter of cattle) and I don't know of any other demand for it (don't know of anyone eating it?). So it should be effective and not too expensive, relatively.

Perhaps there is a difference between the thymuses (thymi?) of calves and adults, given the immune role of the thymus, it's possible. But I can only speculate on that.

And yes. It does seem a bit weird. But it works and everybody does it, so we seem stuck with it.

My two sources:

Richard S. WELSH / Karel VYSKA, Relationship between the Purity and Molecular Weight of Calf Thymus DNA, Hoppe-Seyler's Z. Physiol. Chem.
Bd. 362, S. 969-981, Juli 1981

M. YONEDA AND F. J. BOLLUM, Deoxynucleotide-polymerizing Enzymes of Calf Thymus Gland, THE JOURNAL OF BIOLOGICAL CHEMISTRY, Vol. 240, No. 8, August 1965


Markers for human genetic mapping For human genetic mapping several different types of markers are used:

RFLPs (Restriction Fragment Length Polymorphisms)
VNTRs (Variable Number of Tandem Repeats) such as mini- and microsatellites
SNPs (Single Nucleotide Polymorphisms)

What are the pro's and con's of using each type?

Do any of these markers have a specific functionality in human genetic mapping, or can they all be used for the same purposes?

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

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

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

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

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

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

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


Using anatomical terms for human organs and parts of plants I know how to apply anatomical directional terms (e.g., dorsal/ventral, anterior/posterior, etc.) for animals as a whole (bipeds and quadrupeds).

Recently, I've been studying plant physiology, and I came to know that the upper surface of a leaf is the ventral surface and the lower surface of the leaf is the dorsal surface. I cannot understand how these terms are applied to plants and leaves.

I've also seen anatomical directional terms being used for body organs such as the brain.

I want to know how anatomical terms are applied for parts of plants and body organs.

First, for reference, see here for a discussion about the difference in directional terms between bipeds and quadrupeds as well as a fairly complete explanation of word meanings/etymology.

The etymological meanings of the various anatomical directional terms should help explain their usage in body organs. For example:

Ventral -> "belly" side
Dorsal -> "back" side
Anterior -> "before" or "toward the front"
Posterior -> "after" or coming after (opposite to) the anterior

For body organs (or other body parts):

This SE question addresses hands and feet, while this page from Bryn Mawr College directly demonstrates the usage of anatomical positional terms of the brain:

Rostral/ Anterior --->   Head or front end
Caudal/ Posterior --->  Tail or hind end
Dorsal  --->    Back or top side
Ventral --->    Belly or bottom side

Anatomical positional terminology for brains is consistent across organisms. Here is another picture demonstrating anatomical positional terminology of this organ from Santa Monica college:

For plants, see "Plant Identification Terminology: An Illustrated Glossary" (Harris & Harris, 2001):

  Dorsal. Pertaining to the back or outward surface of an organ in relation to the axis, as in the lower surface of a leaf; abaxial. Figure 407.

  Ventral. Pertaining to the front or inward surface of an organ in relation to the axis, as in the upper surface of a leaf; adaxial. Figure 1428.

Therefore, dorsal/ventral are determined relative to the axis of where the leaf connects to the stem (ie., the axil). Because of this, in my experience terms such as abaxial and adaxial would be preferred when referring to plants.


Is DNA green viewer carcinogenic? I use DNA green viewer in Lab to see DNA and RNA bands. Some peers told me it is carcinogenic and is not safe.
Is this correct? If yes, are there better choices to use in working with gel?

SYBR green is designed to be much less carcinogenic than ethidium bromide (EtBr).

All these gel dyes work by intercalating themselves into the DNA stack between the bases specifically which has a great potential for causing mutations and messing with the workings of the nucleus.  My remembrance is that the SYBR and GelGreen/Red etc dyes are large and relatively hydrophilic and can't find their way into the nucleus, greatly reducing their toxicity.  They also do not transfer energy to the DNA itself due to their structure and so also cause less DNA damage when being viewed on a transilluminator.


Why is cold water more refreshing than warm water? Obviously, the temperature of water does not affect its chemical composition. At least not in the ranges we are likely to drink it in. Yet it is clearly far more pleasant and refreshing to drink cool water than it is to drink tepid or warm water.

Is there actually any difference to the organism or is this just a matter of perception? Is cool water somehow more efficient at rehydrating a cell? In any case, surely by the time water reaches individual cells it will have warmed up to body temperature.

So, what, if any, is the difference between drinking cool and warm water in terms of its effect on the human (or other animal) body?

Extra bonus for explaining why the taste of water changes when it is cold.

Short answer: Cold is pleasant only when your are not already freezing and cold might satiate thirst better because it acts as enhancer of the "water intake flow meter".

Is cold water more tasty than warm water? No, it is actually the reverse as detailed in my footnote.

Cold is pleasant when your body is over-heating and definitely not if you live naked in the North Pole. Over-heating means sweating which means you loose water and therefore feel thirsty faster. Yet drinking cold water will not rehydrate the body more than warm water and drinking water has only a very small impact on the body temperature. So why do we like it?

A study was actually conducted on the subject and answers most of your questions. Here the reference.

The temperature of the body will indeed not change.

  cold stimuli applied to the mouth
  (internal surface of the body) do not appear to impact on body
  temperature and are not reported to cause any reflex shivering
  or skin vasoconstriction that influence body temperature.

As you pointed out, the temperature of the ingested water will not affect the overall hydration of the body as cells are rehydrated mostly via the blood  stream and the blood temperature will not be affected. Someone could argue that, at identical volumes, cold water (above 4C) contains more molecules (i.e. is denser) than warm water but this difference is likely very slim.

In this paper they also define "thirst".

  Thirst is a homeostatic mechanism that regulates blood osmolarity
  by initiating water intake when blood osmolarity increases

The problem is that it takes some time before the water reaches the blood stream, and therefore you need a feedback mechanism that tells you to stop drinking independently of the blood's osmolarity. This is where cold might play a role.

  The cold stimulus to the mouth from ingestion of water may act
  as a satiety signal to meter water intake and prevent excessive
  ingestion of water

The picture would then be the following

In essence, a cold sensation is pleasant in warm weather, both on the skin and in the mouth, and it apparently helps in reducing thirst by being some kind of an  enhancer of the "water intake flow meter".

Footnote

Reading the comments I just want to clarify some points.

The 5 basic tastes (sweet, salty, bitter, sour and umami) are very distinct from taste sensations (pungency, smoothness, cooling to name a few). The main difference is that taste and "sensation" signals use completely different paths to reach the brain - namely, the facial and glossopharyngeal nerves for the former and the trigeminal nerve for the latter.

Is the temperature affecting basic taste perceptions? The answer is yes. How this happens is quite simple if you understand the fundamental concepts of molecular taste perception. Essentially the temperature affects the response of the receptor TRPM5 which is the main player in depolarizing taste receptor cells in the papillae. To put it simply, higher temperatures provoke a greater perception for taste, and this is not only in term of perceived taste but really modifies the amplitude of the response at the molecular level. As an example this is why ice cream does not taste sweet when frozen but only after it melted in the mouth or on the tongue.


What is this insect I found in Russia? I found this in Russia. It is approximately 2cm long.

This is a wasp, (see that nice slim "wasp waist" it's got?), which means taxonomically that it is in the order Hymenoptera (which it shares with bees and ants).

Within Hymenoptera, wasps are diverse and often difficult to ID, but it's possible that this is a Braconid or Ichneumon (family Braconidae or Ichneumonidae). If you take a good closeup of its wing veins, chances are an expert (not me) could ID it.


Does ATP hydrolysis reaction have a high or low activation energy? I was recently studying about ATP and how it functions as an energy carrier to all biological processes; however, I came across a confusing and paradoxical statement from two sources:
(at 7:36)
and
(the free response question in the bottom of the page)

Basically, in the video, it says that ATP hydrolysis has a high activation energy which is why all of the ATP isn't randomly used by the cell processes.

And in the free response question, the answer is that ATP hydrolysis has a low activation energy and low free energy making it a spontaneous reaction.

A follow up question is: How then does the ATP of the cell used in a selective way to certain processes only?

Thanks for your help.

High and low are not very descriptive since they are relative. ATP hydrolysis may have a high activation energy compared to some reactions and low when compared to others.  The important point is that the activation energy is sufficiently high enough such that ATP is not rapidly hydrolysed under physiological conditions before it can do useful work. In other words ATP hydrolysis is kinetically unfavourable but thermodynamically favourable. The reaction rate is increased by enzymes (by lowering the activation energy), which couple ATP hydrolysis to other processes to do useful work.

Also, a note on reaction spontaneity: it has nothing to do with activation energy but rather depends on the change in free energy; ATP hydrolysis is spontaneous because it is exergonic.


Why ambidextrous persons are so rare? According to this article, only about 1% of all humans are ambidextrous:

  About 90 percent of people are right-handed, says Corballis. The
  remaining 10 percent are either left-handed or some degree of
  ambidextrous, though people with "true" ambidexterity—i.e., no
  dominant hand at all—only make up about 1 percent of the population.

Less dominance is observed in other animals, as indicated by this article:

  Bill Hopkins, at the Yerkes Regional Primate Research Center in
  Atlanta, USA, has made even more contentious claims in recent years,
  asserting that his captive chimpanzees exhibit a 70% right-handed
  preference for many tasks requiring manual dexterity, a rate that
  rises to almost 98% for very specific tasks, like the precise over-arm
  throwing of objects. However, for everyday food-related tasks (like
  cracking nuts or digging out honey), the rate remains closer to 50-50.

I am wondering if there is any theory that explains why ambidextrous persons are so rare. As a totally layman when it comes to biology it seems that this would require a more complex brain to wire all the complexity to both members and this would be rarely justified (virtually all tasks can be done without being fully ambidextrous).

Question: Why are ambidextrous persons so rare?

While not specifically answering why ambidextrous persons are rare, one potential explanation is that mixed-handedness and/or ambidexterity seems to be related to adverse effects. For instance, some studies have shown that mixed-handedness (which might not be exactly the same as ambidextrous, depending on how you define the terms) is related to ADHD symptoms (e.g. Rodriguez et al. 2010) and patients with schizophrenia have an overrepresentation of mixed-handedness (Green et al, 1989; Orr et al, 1999) and ambidexterity (Crow et al, 1996).

A potential reason for the adverse effects seems to be that mixed-handedness and ambidexterity is related to delayed or weakened dominance of one cerebral hemisphere, which is important for language development (see e.g. Crow et al, 1996). See also this quote from Intelligence and the ‘Intelligence Quotient’ (Crow, 2001 from Encyclopedia of Genetics):

  Handedness, reflecting cerebral dominance, is a trait that is associated with quantitative variation. Whether this variation is a correlate of human cognitive ability, as would seem plausible if it underlies the specific characteristic of language, has been much debated, but it now appears that lesser degrees of lateralization (‘hemispheric indecision’) are associated with delay in the development of verbal, and also nonverbal, ability (Crow et al., 1998). Thus it appears that lateralization is associated with significant variation in the rate at which words acquire meaning, and that this variation reflects a dimension that is specific to Homo sapiens.

This is not my area of expertice thought, and others more knowledgeable about the field can maybe expand on this or explain more in detail.


Hedgehog AP Bio question Could someone please explain this AP Biology question? I know the answer is C but I do not understand why. Doesn't Smo prevent gene transcription? If you "block its activity" then wouldn't it cause gene transcription, whereas the goal of treating cancer is to prevent transcription? Please help!

I'm just going to outline the alternatives, I'll leave validating why choice C to you.

Choice A. If the new molecule acts in the same fashion as Hh, the results will be identical. If the new molecule bound to Pct but did not effect a response, that might work.

Choice D. Addition of Ci into the nucleus initiates transcription which seems to be the issue here.

Choice B. Best wrong answer! Can you inject enough stem cells to make a difference? Will the cells have some adverse effect? More importantly, the binding of messengers to receptors is a reversible process. The Hh will be able to detach from Ptc on the stem cells and eventually interact with Ptc on the native cells.

So, what effect will Hh have if the Smo in unable to respond?


Terminology question about the correct term for areas of biological research I am writing a paper about DNA sequence prediction. DNA sequence prediction is done across various areas of biology, including, for example, RSS sequence prediction (in immunology) and prediction of promoter regions in vertebrate DNA sequences.

I was just wondering how one would describe such specific areas as "RSS sequence prediction" and "promoter region prediction". To be concrete, I wanted to write something like:

  This paper describes a method of DNA sequence prediction using
  standard Bayesian modelling techniques. While there is much existing
  work on DNA sequence prediction, most of this work is in the context
  of biological research. Typically the techniques used are very
  specific to the biological subdomain under consideration. Also, these
  techniques often use use additional biological information about the
  biological sequences under consideration, besides the sequence data
  itself.

Is the term subspeciality the correct term to use here? Would biological area or biological domain/subdomain be better, or some other term?

Incidentally, if anyone knows other areas where DNA sequence prediction is used, please mention it/them. Thanks.

I think your suggestions are fine - there are a few ways you could write this.

I might use some variant of;

  The techniques used may be specific to the research question, and particular considerations may also be required depending on the accepted norms within the academic field


Glycolytic non-oxidative pathway I am currently digging in some books to understand the three major metabolic pathways involved in physical training. The most difficult one for me is the glycolytic non-oxidative pathway (also more commonly known as the anaerobic lactic pathway) and I would like some help from people versed in this field.

In this pathway, as far as I understand, glycolysis produces pyruvate. In this process, NADH and H+ ions are produced along the way.

Then, if there is still a high energy demand (i.e. glycolysis is still necessary); NADH binds with pyruvate to form lactate and free up NAD+ which is necessary to sustain the glycolysis (otherwhise, pyruvate would be consumed via an oxidative pathway i.e. oxidative glycosis or slow glycolysis). This can theoretically continue until glycogen is depleted or severely diminished as far as I understand.

The problem comes then from the H+ ions produced during the glycolysis. These ions cause acidosis of the muscles if not removed. However, they can be removed if sufficient oxygen is present to form water. And here is my main question :

Why, during high intensity exercise, would oxygen be insufficient to take care of the H+ ions produced by the glycolysis ? Is it because muscles used during high intensity are not the best ones for using/transporting oxygen? Is it also because these H+ ions cannot be transported towards neighbouring muscles able to oxidise H+ ions ?

I understand this is a difficult question and maybe there is no precise answer at the moment. If you could point me toward a good ressource that deals with this question, I would be glad. I currently base myself on McArdle book on exercise physiology.

I am going to try to walk through this problem, in a step-by-step manner in relation to exercise, starting from at rest, and ending at the point in which the body is no longer able to maintain its energy-charge.

At Rest

The body mainly utilises oxidative phosphorylation to maintain its energy-demands. In cells where great amounts of energy need to be produced very quickly, eg. cells that are actively replicating, glycolysis is the preferred mode of energy production because this pathway is able to very quickly produce large amounts of ATP, and lactate is able to quickly diffuse in to the bloodstream. Lactate will travel in the bloodstream, to the liver, to be recycled back to glucose through an anabolic process called gluconeogenesis. This recycling pathway is known as the Cori-cycle. Essentially, what is happening is, parts of the body that are in need of high amounts of energy, will "dump" their wastes to the bloodstream, to be dealt with by other organs.

Science and Skiing VI, 2015, pp 17-30. George Brooks of the University of California summarises lactate recycling quite nicely here.

Beginning Exercise

Muscle cells will begin to quickly utilise ATP-stores, and release glucose from the glycogen-stores, and release oxygen-stores from myoglobin.

As these stores begin to become depleted, the body will begin to go in to overdrive, in an attempt to restore itself to a resting-state. Thus, your heart-rate will increase, breathing will become faster, and glycolytic pathways will be activated through feed-forward mechanisms.

During Exercise

I have touched on this before, in another post that you may find interesting. I believe that if you read through this though, that you will understand why there is low levels of oxygen, and what the body does to attempt to circumvent this.

There will be very low levels of oxygen throughout the active tissues. The body will do everything it can to try to restore this, but it will ultimately fail to do so. Thus, the only real option it has is to rely on glycolysis in the tissues that are causing "problems". The rate of ATP-production is most dependent on the rate at which a cell can take glucose in to the cell.

The electron-transport-chain is only able to synthesise ATP at its maximum velocity - this maximum velocity is proportional to the concentration of oxygen. The rate of glycolysis is, however, essentially, only affected by the rate at which lactate can be removed from the cell and the rate at which glucose can be absorbed by the cell.

Of course, the muscles that are being used will only be concerned with producing energy. Therefore, all of the lactate that they produce will be dumped in to the bloodstream, where it will travel to the liver, in the previously mentioned cori cycle.

Overall, the issue is not in the muscle-cell's ability to regenerate NAD+. This is the easy part, seeing as there is no net-change in the concentration of NAD+ when glucose is converted to lactic acid. And also, things such as malate-aspartate shuttles, citrate-pyruvate shuttles, and glycerol 3-Phosphate shuttles can be used to maintain redox-balance. These are only but a few examples of how to maintain redox-balance.

You must also remember that carbohydrates are not the only class of molecules involved in these cycles; degraded proteins and fats can also be used to supply the TCA-cycle with alternative means of energy-production. Pyruvate probably would not even be able to be converted in to acetyl-CoA anyway, since pyruvate dehydrogenase requires the presence of oxygen to function.

Problems however do arise once the body is unable to deal with all of the waste that it is producing. There will reach a point, where the liver cells will be physically incapable of accepting any new lactate-molecules. And so, lactate will accumulate in the bloodstream. With an accumulation of lactate in the bloodstream, lactate will be unable to diffuse to the outside of the cell. Thus, cells will be unable to convert pyruvate in to lactate.

The reason why ATP-regeneration eventually fails to keep up with the rate of ATP-usage, is because the rate of conversion to lactate decreases. The rate of conversion to lactate decreases, because the concentration of lactate increases

I tried to make a little illustration of what I mean above, below. Hope this helps to conceptualize it.

In this second picture, there is too much lactate for diffusion to occur.

Supporting information

Taken from Quantifying intracellular rates of glycolytic and oxidative ATP production and consumption using extracellular flux measurements; Mookerjee et al. 2017

"These maximum values of JATPglyc and JATPox define the bioenergetic capacity of the cells. As shown in Fig. 5D, the maximum individual capacities of JATPglyc and JATPox in the bioenergetic space plot intersect at (62.5, 46.5) for a theoretical maximum bioenergetic capacity of 62.5 + 46.5 = 109.0 pmol of ATP/min/μg of protein. At this maximum point, the glycolytic index (GImax capacity) would be 62.5/109 = 57.3%, making C2C12 myoblasts primarily glycolytic when running at their maximum ATP production rate. Compared with the actual value of JATP production in the presence of glucose (55.2), the bioenergetic capacity was 109/55.2 = 197% of the rate with glucose (Fig. 5D). This bioenergetic capacity of 197% of the rate with glucose (alternatively, a reserve capacity of 109.0 − 55.2 = 53.8 pmol of ATP/min/μg of protein) reveals that the C2C12 cells under our experimental assay conditions with added glucose were operating comfortably within their capacity to generate ATP and were well set up to respond to any acute increases in ATP demand by increasing either glycolytic or oxidative ATP production, or both."

In these experiments, the researchers were trying to figure out what proportion of ATP would be created by glycolytic and oxidative pathways in muscle cells (and other cell-types). Their findings, were that, indeed, the majority of ATP production in muscle cells comes from glycolysis.

During exercise, this difference in amounts of ATP production between glycolysis and oxidative phosphorylation would probably be even greater.


How common are the "common" human coronaviruses? I was listening to a virology expert on the Swedish radio yesterday. He said that there already were several corona viruses among humans that only affected children because basically all the adults were already immune. He said that he believed that SARS-CoV-2 will be added to this category in the future, which seemed logical to me. Basically SARS-CoV-2 will at some future time only affect children and give very little symptoms because all the adults will be immune.

By googling I found four viruses listed as "common corona viruses" that affects humans:

229E (alpha coronavirus)

NL63 (alpha coronavirus)

OC43 (beta coronavirus)

HKU1 (beta coronavirus)

1.Can something be said about how "common" these viruses are?

2.I mean if an adult for some reason has no immunity to one of these viruses how long will it take on average before he gets infected?

The reason I am asking is because if we know the answer to question 2 above for the four common coronaviruses one maybe can produce an educated guess for the likelihood for a person escaping the "first wave" of SARS-CoV-2 getting infected within a given time period after we have "herd immunity" against SARS-CoV-2.

The common [cold] coronaviruses are pretty common:

Four HCoVs (HCoV 229E, NL63, OC43, and HKU1) are endemic globally and account for 10% to 30% of upper respiratory tract infections in adults.

To pick a more detailed study in Ghana:

This study sought to determine whether human coronaviruses (HCoVs) are associated with upper respiratory tract infections among older children and adults in Ghana. We conducted a case control study among older children and adults in three rural areas of Ghana using asymptomatic subjects as controls. [...]
Out of 1,213 subjects recruited, 150 (12.4%) were positive for one or more viruses. Of these, single virus detections occurred in 146 subjects (12.0%) and multiple detections occurred in 4 (0.3%). Compared with control subjects, infections with HCoV-229E (OR = 5.15, 95%CI = 2.24–11.78), HCoV-OC43 (OR = 6.16, 95%CI = 1.77–21.65) and combine HCoVs (OR = 2.36, 95%CI = 1.5 = 3.72) were associated with upper respiratory tract infections. HCoVs were found to be seasonally dependent with significant detections in the harmattan season (mainly HCoV-229E) and wet season (mainly HCoV-NL63).

Occasionally there are substantial outbreaks of common cold, e.g. as observed in Japan:

we conducted a longitudinal survey
between 2010 and 2013 in Yamagata, Japan, to clarify
the epidemiology of HCoVs using RT-PCR methods
[...]. In 2011, we
found that the monthly detection frequencies of HCoVNL63 were higher than 20% in January and February
(28.5% and 25.3%, respectively), whereas those of the
other HCoVs (HCoV-229E, -OC43, -HKU1) did not exceed 20%. In light of these findings, we continued
the HCoV surveillance and, thus, captured data from
the largest outbreak of HCoV-OC43 reported in the last
6 years. During the 2014–2015 influenza season in
Yamagata, Japan, the monthly detection frequencies
were approximately 30–40%.

Those percentages are from people reporting symptoms (and then swabbed.) The graph below (from the same paper) nicely shows the seasonality.

Monthly distribution of clinical specimens (A) and HCoVs (B) detected from patients with acute respiratory
infections between January 2014 and March 2015, in Yamagata, Japan.

Question 2 is rather meaningless because immunity to common coronaviruses is short lived. See (also) this answer (esp. the 2nd table) to a related question putting the common coronaviruses immunity duration in perspective; reproducing just the table below (the relevant line for common coronavirus is the 1st below the break, i.e. 1st in the 2nd section of the table).

And I've managed to track down one of the primary studies on 229E long-term immunity (or rather lack thereof)

Although after 1 year concentrations of specific serum IgG and nasal IgA were
still significantly raised in the infected group, they were much lower than at the
maximum. [...] When challenged after 1 year all of the original uninfected group were infected and 6/9 of the infected group were reinfected. [...] In the infected group there were considerable individual differences. Some lost their antibody, particularly serum antibody, completely by 1 year, some did not.

And it's basically impossible not be exposed to a strain of the common cold coronaviruses at one point; one study on newborns found that interval to be 3.5 years, but that's probably an overestimation for adults.

all of the children had maternal anti-NL63 and anti-229E antibodies at birth that disappeared within 3 months [...] on average, HCoV-NL63 and HCoV-229E seroconversion occurs before children reach the age of 3.5 years.

The real question is whether Covid-19 will behave like the common coronaviruses or more like SARS and MERS for which it is suspected (from the detection of antibodies), but not certain that immunity lasts longer.

For the SARS and MERS coronaviruses, antibodies appear to persist for several years, but no studies have intentionally attempted to re-infect people, since these are deadly diseases.


What are reciprocal inhibitory synapses? Quoting Kandel's Principles of Neural Science, 2013,

  Amacrine cells generally receive excitatory signals from bipolar cells at glutamatergic synapses. Some amacrine cells feed back directly to the presynaptic bipolar cell at a reciprocal inhibitory synapse. Some amacrine cells are electrically coupled to others of the same
  type, forming an electrical network much like that of the horizontal cells.

(Page 593)

I tried searching for what a reciprocal inhibitory synapse is but could not find any relevant information.

It might be better understood if written with a comma as:

  reciprocal, inhibitory synapse

though the rules for this comma usage in English might discourage this because writing "inhibitory reciprocal synapse" doesn't sound quite right. I would say the author wrote it correctly even though it is not perfectly clear.

In this context, they are separate adjectives describing the synapse: inhibitory, because it suppresses firing, and reciprocal because Cell A gives input to Cell B, and Cell B also gives input to Cell A (where Cell A is the amacrine cell and Cell B is the bipolar cell).

The word reciprocal in this context is the adjective definition of the word reciprocal:

  given, felt, or done in return.

Note that it isn't the synapse itself that is reciprocal or in both directions, but that the cells have a reciprocal relationship.


What is the biochemical reason for mental fatigue? Is it known exactly why the brain needs sleep? What's dropping low / going high when we experience mental fatigue? I can see why low glucose could result in mental fatigue, are other reasons known?

This is not the biochemistry, but the brain regions involved are described in this article about an fMRI study: http://www.sciencedaily.com/releases/2012/12/121210101630.htm

EDIT:

From what I can tell, mental fatigue is attributed to low oxygenation levels.  Here's a study that examines the effect of creatine in preventing mental fatigue: http://jtoomim.org/brain-training/watanabe2001-creatine-reduces-mentalfatigue.pdf


Mathematical Modelling of Natural Selection I'm a math undergrad looking for some papers on modelling the process of natural selection. The only paper I've been able to find is by the pre-eminent mathematician Herbert Wilf from 2010,

There's Plenty of Time for Evolution

Unfortunately, Wilf's model is extremely simplistic - he calculates the number of 'generations' required to spell out a 'word', if we allow each letter to 'mutate' with certain probability every generation, and we stop mutating a letter once it is correct (this is the 'selective' feature of the model). So to spell the word 'Evolution' by randomly placing scrabble tiles would require 5.4 trillion generations, but if we keep the correctly placed letters each generation and only allow incorrect letters to 'mutate', Wilf calculates we'd only need about 57 generations on average.

Wilf's model is a good first step towards modelling natural selection, but it's clearly only a first step. In particular, the fact that nature seems to know in advance exactly what letters it needs to keep in particular places and what it needs to throw out to construct a complex genetic 'word' is dubious at best.

As a young maths student the idea of the incredible complexity and diversity of life developing by a directed stochastic process gets me shamelessly excited :) I have been very surprised at just how little mathematical literature there seems to be on this topic, as I say, Wilf's one super-simplistic model is all I've been able to find. Can someone direct me to any other theoretical analyses of the power of natural selection?

Thanks

Mathematical and computational modeling of evolution is a huge field. To start you off with some broad strokes, there are two main approaches to evolutionary modeling with their own communities: frequency-independent and frequency-dependent models. Of course, in a real biological setting, the truth lies somewhere in between, but models are idealizations of key principles, and so the two extremes are good to study.
For frequency-independent selection, they key concept is the fitness landscape -- a way to map each genotype to a fitness. The population then lives in this landscape and agents with higher fitness reproduce better and so the population slowly movers over the lattice. Under reasonable macroevolutionary assumptions such as very rare mutations and asexual populations, the population will tend to be homogenous and can be just modeled as a single point in the fitness landscape with properly chosen selective sweeps to move the point from vertex to vertx (Gillespie, 1983; 1984).
The most popular concrete approach for frequency-independent selection is [Kauffman's NK model of rugged fitness landscapes] (Kauffman & Weinberger, 1989; Kauffman, 1993). Computer simulations tend to favor this sort of model. Wilf's model would be an NK model with K = 0, and fitness of 0 for incorrect letters and 1 for correct letters (to get the shorter walk). Related questions:

Is local equilibrium a reasonable assumption for evolutionary processes?
Structure of fitness landscapes in the NK model

The frequency-dependent selection approach is dominated by evolutionary game theory. A typical question for this field is the evolution of cooperation, and the most basic approach is to use replicator dynamics and look at evolutionary stable strategies. However, the field is in general saturated with all kinds of exciting models (both analytic and computational). A very friendly book-length intro is Nowak's Evolutionary Dynamics. For a genetle intro and connections to evolutionary psychology look at the slides in this post. A brief and sophisticated introduction aimed at mathematicians can be found in Hofbauer & Sigmund (2003). Related questions:

Sources for Algorithmic Evolutionary Game Theory
Why is 'Grudger' an evolutionary stable strategy?
How exactly are game theoretical evolutionary models described during implementation for computer simulations?
When does weak selection produce qualitatively different results from strong selection?

References
Gillespie, J.H. (1983). A simple stochastic gene substitution model. Theor. Pop. Biol. 23, 202.
Gillespie, J.H. (1984). Molecular evolution over the mutational landscape. Evolution 38, 1116.
Hofbauer, J., & Sigmund, K. (2003). Evolutionary game dynamics. Bulletin of the American Mathematical Society, 40(4), 479-519.
Kauffman, S. (1993). The origins of order: Self organization and selection in evolution. Oxford University Press, USA.
Kauffman, S. & Weinberger, E. (1989) The NK Model of rugged fitness landscapes and its application to the maturation of the immune response. Journal of Theoretical Biology, 141(2): 211-245
Nowak, M. A. (2006). Evolutionary dynamics: exploring the equations of life. Harvard University Press.


Reproduction and defecation In mammals and birds the external reproductive organs and waste removal organs see to be the same. Is this always the case with other animals such as insects etc...? Are there any good reasons for it?

The cloaca, which is the common opening of the urinary, excretory, and reproductive systems, is present in birds as well as in non-avian reptiles (and thus presumably dinosaurs), amphibians, and monotremes (e.g., duck-billed platypus). To answer your first question, yes, this condition does seem to be universal for those groups mentioned above.

To answer your second question, evolutionary history is as good a reason as I can think of. The cloacal system has worked well enough for >350 million years (in the case of amphibians).


In terms of ecology what is optimality? I am studying animal science and I have been learning about reproductive theories however i cant seem to understand the theory of optimality

Optimality theory

Optimality theory is a concept of linguistic. See wiki > Optimality theory. This is probably not what you were referring to.

What is optimality

Optimality is the condition under which something is maximized! In behavioural ecology, this something is often fitness and the condition is often measured in terms of magnitude/intensity of a behaviour.

Optimality models

In ecology, we call optimality model any model that separate the benefits and costs (in terms of some measurement, often fitness) of a given phenotype (often behaviour). By weighing benefits and costs one can figure out what is the optimal phenotype. The principle is extremely simple. Such graphs are quite standard:

In the graph, the X-axis represents the magnitude of a phenotype (often a behaviour) and the Y-axis represents the benefit and cost of this behaviour (with the same scale) often in terms of fitness.

By definition, the fitness is maximized when $B-C$ is maximized. In other words, compute B-C and look for the maximum (through derivation) and you found the optimal phenotype (often behaviour). In the above graph, the optimal phenotype is a little bit left to the position of the B label.

Optimal foraging theory

Foraging behaviour has been subject to much investigations using optimality models. We refer to this body of knowledge as Optimal foraging theory.


Why do I only breathe out of one nostril? I was just sitting with my hand next to my nose and I realized that air was only coming out of the right nostril. Why is that? I would think I would use both, it seems much more efficient. Have I always only been breathing out of my right nostril?

Apparently you're not the first person to notice this; in 1895, a German nose specialist called Richard Kayser found that we have tissue called erectile tissue in our noses (yes, it is very similar to the tissue found in a penis). This tissue swells in one nostril and shrinks in the other, creating an open airway via only one nostril. What's more, he found that this is indeed a 'nasal cycle', changing every 2.5 hours or so. Of course, the other nostril isn't completely blocked, just mostly. If you try, you can feel a very light push of air out of the blocked nostril.

This is controlled by the autonomic nervous system. You can change which nostril is closed and which is open by laying on one side to open the opposite one.

Interestingly, some researchers think that this is the reason we often switch the sides we lay on during sleep rather regularly, as it is more comfortable to sleep on the side with the blocked nostril downwards.

As to why we don't breathe through both nostrils simultaneously, I couldn't find anything that explains it.

Sources:
About 85% of People Only Breathe Out of One Nostril at a Time
Nasal cycle


What do arranging and assigning mean in sequence annotation? Please could someone explain these lines to me in a simple way

  These sequences were then arranged based on some overlapping regions present in them. This required generation of overlapping fragments for sequencing. These sequences were subsequently annotated and assigned to each chromosome

What do "arranging" and "assigning" mean in this context?

Source: NCERT class 12 (This text in in reference to the method developed by Frederick Sanger)

Word "arranged" means simply alignment of sequence based on overlapping regions in two sequences. For example:

Seq1: AGTGTCCGTCGTAAGTCA

Seq2:GTCGTAAGTCATCGAGATACC

leading to:

Seq12: AGTGTCCGTCGTAAGTCATCGAGATACC

Maybe he used the word "arrange" as overlapping determines the direction of resultant sequence (for which word alignment is sufficient)

Assignment: Is simply dividing the genome's sequence down as per chromosomes of the species. Like for example, if it's human genome sequence and first chromosome is 2,50,000bp long (just assumption - I don't remember exact figure), then first 2,50,000 nucleotides in the sequence will be "assigned" to chromosome 1. From 2,50,001 onwards to chromosome 2 and so on..


What does the "cov" mean in a velvet assembler generated contig name? A exmaple of a contig name generated by velvet assembler:

NODE_127_length_39203_cov_244.873016

What does cov_244.873016 mean?

It sounds like coverage. Does it mean reads coverage or other statistical description of the contig?

It means k-mer coverage. From the velvet manual:

  4.2.1 The contigs.fa file

  This fasta file contains the sequences of the contigs longer than 2 k
  , where k is the word-length used in velveth.  If you have specified a
  min_contig_length threshold, then the contigs shorter than that value are omitted. Note  that  the  length  and  coverage  information
  provided  in  the  header  of each contig should therefore be
  understood in k-mers and in k-mer coverage (cf. 5.2 ) respectively.
  E.g.  for a 500bp contig and a k-mer length of 21, the length in the
  header will be 480.


What was the breakthrough behind the “sudden” feasibility of mRNA vaccines in 2020? Several sources describe the initial failures in the realization of a successful mRNA vaccine. E.g., this 2017 article from Stat describes the following problem faced by Moderna while working on one of their mRNA vaccines:

The safe dose was too weak, and repeat injections of a dose strong enough to be effective had troubling effects on the liver in animal studies.

Another Stat article describes a similar challenge:

In animal studies, the ideal dose of their leading mRNA therapy was triggering dangerous immune reactions — the kind for which Karikó had improvised a major workaround under some conditions — but a lower dose had proved too weak to show any benefits.

The work by Karikó was conducted before Moderna and BioNTech were founded, so it does not seem to be the breakthrough that led to feasible mRNA vaccines. I am also aware that one of these companies, Moderna, is secretive about its technology.
However, I would like to learn, at least at a high level, the reason mRNA vaccines are a viable option against COVID-19, while earlier attempts to develop them against other diseases, such as Crigler–Najjar syndrome, were unfruitful.

I am aware of Why weren't mRNA vaccines clinically tried earlier?, which was closed for being opinion-based. However, my question is specific to the biological mechanism behind the breakthrough that enabled feasible mRNA vaccines, so is objective and within the scope of this site.

Answering my own question after reading the 2018 Nature review article “mRNA vaccines — a new era
in vaccinology”
The resources and motivation engendered by the COVID-19 pandemic are a major factor in the development of the first mRNA vaccines approved by national governments. However, before the COVID-19 pandemic, there were recent advances in mRNA vaccine pharmacology, which made everything possible.
Introduction
The Nature review points out that it was not a single breakthrough, but a lot of research that was conducted during the last couple of years.
Demonstrations of protective immune responses by mRNA vaccines against various infective pathogens were published in recent years. In the first one, published in 2012, direct injection of non-replicating mRNA vaccines was shown to be immunogenic against various influenza virus antigens in multiple animal models1. Since then, several studies on animals, and in some cases, healthy human volunteers, have managed to induce protective immunity against rabies2,3, HIV-14,5,6, Zika7,8,9, H10N8 and H7N9 influenza10, and other viruses.
The authors of the review, which was written before the COVID-19 pandemic, believed that “mRNA vaccines have the potential to solve many of the challenges in vaccine development”. Therefore, had the pandemic not happened, it is likely that we still would have seen effective mRNA vaccines being developed, albeit at a slower pace.
Recent technological advancement has largely overcome the main challenges in the development of mRNA vaccines.
The Challenges
1. Instability
Protein expression after the vaccine is administered might be insufficient if, for instance, the half-life of the vaccine is too low, or if in vivo mRNA translation is insufficient11,12.
2. Inefficient in vivo delivery
mRNA vaccine delivery is tricky. For instance, mRNA can aggregate with serum proteins and undergoes rapid extracellular degradation by RNases. Therefore, formulating mRNAs into carrier molecules is often necessary, and delivery formulations need to take into account factors such as the biodistribution of the vaccine after delivery, mRNA uptake, and protein translation rate13,14.
3. Safety
The complexity of modulating the immunogenicity of the mRNA used in vaccines can potentially lead to unwanted stimulatory effects on the immune response15,16,17.
The Recent Advances
1. Optimization of mRNA translation and stability
Sequence optimization techniques such as replacing rare codons with more frequently used synonymous codons18, as well as enrichment of G:C content16, have been examined for increasing in vivo protein expression.
2. Progress in mRNA vaccine delivery
There are numerous delivery methods for mRNA vaccines that have been examined in the literature. In recent years, the limitations of some of these, such as using physical methods (e.g., electroporation) to penetrate the cell membrane, were demonstrated19. On the other hand, progress was made toward the increased efficacy and reduced toxicity of other delivery methods such as cationic lipid and polymer-based delivery13,16,20,21.
3. Modulation of immunogenicity
Recent studies have demonstrated that the immunostimulatory profile of mRNA can be controlled more precisely using a variety of techniques. These include chromatographic purification to remove double-stranded RNA contaminants, the introduction of naturally-occurring modified nucleosides to prevent the activation of unwanted innate immune sensors, and complexing the mRNA with various carrier molecules (this includes novel approaches to adjuvants that take advantage of the intrinsic immunogenicity of mRNA)15,17,22,33.
Apart from the advances in techniques such as purification and the introduction of nucleosides, there was also an improvement in the understanding of when these techniques should be used, based on factors such as the mRNA platform used, RNA sequence optimization, and the extent of mRNA purification under consideration16,24.
References

Petsch, B. et al. Protective efficacy of in vitro synthesized, specific mRNA vaccines against influenza A virus infection. Nat. Biotechnol. 30, 1210–1216 (2012).
Schnee, M. et al. An mRNA vaccine encoding rabies virus glycoprotein induces protection against lethal infection in mice and correlates of protection in adult and newborn pigs. PLoS Negl. Trop. Dis. 10, e0004746 (2016).
Alberer, M. et al. Safety and immunogenicity of a mRNA rabies vaccine in healthy adults: an open-label, non-randomised, prospective, first‑in‑human phase 1 clinical trial. Lancet 390, 1511–1520 (2017).
Pollard, C. et al. Type I IFN counteracts the induction of antigen-specific immune responses by lipid-based delivery of mRNA vaccines. Mol. Ther. 21, 251–259 (2013).
Zhao, M., Li, M., Zhang, Z., Gong, T. & Sun, X. Induction of HIV‑1 gag specific immune responses by cationic micelles mediated delivery of gag mRNA. Drug Deliv. 23, 2596–2607 (2016).
Li, M. et al. Enhanced intranasal delivery of mRNA vaccine by overcoming the nasal epithelial barrier via intra- and paracellular pathways. J. Control. Release 228, 9–19 (2016).
Pardi, N. et al. Zika virus protection by a single low-dose nucleoside-modified mRNA vaccination. Nature 543, 248–251 (2017).
Richner, J. M. et al. Modified mRNA Vaccines protect against Zika virus infection. Cell 168, 1114–1125.e10 (2017).
Richner, J. M. et al. Vaccine mediated protection against Zika virus-induced congenital disease. Cell 170, 273–283.e12 (2017).
Bahl, K. et al. Preclinical and clinical demonstration of immunogenicity by mRNA vaccines against H10N8 and H7N9 influenza viruses. Mol. Ther. 25, 1316–1327 (2017).
Weissman, D. mRNA transcript therapy. Expert Rev. Vaccines 14, 265–281 (2015).
Sahin, U., Kariko, K. & Tureci, O. mRNA-based therapeutics — developing a new class of drugs. Nat. Rev. Drug Discov. 13, 759–780 (2014).
Kauffman, K. J., Webber, M. J. & Anderson, D. G. Materials for non-viral intracellular delivery of messenger RNA therapeutics. J. Control. Release 240, 227–234 (2016).
Guan, S. & Rosenecker, J. Nanotechnologies in delivery of mRNA therapeutics using nonviral vector-based delivery systems. Gene Ther. 24, 133–143
(2017).
Kariko, K. et al. Incorporation of pseudouridine into mRNA yields superior nonimmunogenic vector with increased translational capacity and biological stability. Mol. Ther. 16, 1833–1840 (2008).
Thess, A. et al. Sequence-engineered mRNA without chemical nucleoside modifications enables an effective protein therapy in large animals. Mol. Ther. 23, 1456–1464 (2015).
Kariko, K., Muramatsu, H., Ludwig, J. & Weissman, D. Generating the optimal mRNA for therapy: HPLC purification eliminates immune activation and improves translation of nucleoside-modified, protein-encoding mRNA. Nucleic Acids
Res. 39, e142 (2011).
Gustafsson, C., Govindarajan, S. & Minshull, J. Codon bias and heterologous protein expression. Trends Biotechnol. 22, 346–353 (2004).
Johansson, D. X., Ljungberg, K., Kakoulidou, M. & Liljestrom, P. Intradermal electroporation of naked replicon RNA elicits strong immune responses. PLoS ONE 7, e29732 (2012).
Schlake, T., Thess, A., Fotin-Mleczek, M. & Kallen, K. J. Developing mRNA-vaccine technologies. RNA Biol. 9, 1319–1330 (2012).
Reichmuth, A. M., Oberli, M. A., Jeklenec, A., Langer, R. & Blankschtein, D. mRNA vaccine delivery using lipid nanoparticles. Ther. Deliv. 7, 319–334 (2016).
Fotin-Mleczek, M. et al. Messenger RNA-based vaccines with dual activity induce balanced TLR‑7 dependent adaptive immune responses and provide antitumor activity. J. Immunother. 34, 1–15 (2011).
Rettig, L. et al. Particle size and activation threshold: a new dimension of danger signaling. Blood 115, 4533–4541 (2010).
Kauffman, K. J. et al. Efficacy and immunogenicity of unmodified and pseudouridine-modified mRNA delivered systemically with lipid nanoparticles in vivo. Biomaterials 109, 78–87 (2016).


Why do grapes not pea shrink when placed in strong sugar solution? I tried an experiment. First, I placed grapes in pure water(hypotonic solution). The grapes burst because of endosmosis. Then, I placed new set of grapes in strong sugar solution(fully saturated) but they did not shrink. And then when I placed it in strong salt solution(fully saturated), they did shrink a little. Why does this occur?

How is this possible?

Well, without the details of your experiment to cross-check with the sugar and H2O content of your average grape, I'd say the saturated solution probably approximated the natural molarity of sugar in the grape. At least to the point it didn't make any advese effects noticeably on your time scale.

That seems the most apparent solution to me. I suppose it's also possible (though I don't know the mechanics behind it) that hypertonic solution might have acted as a preservative - similar to jam. It's not just water which will attempt to reach an equilibrium, but all compounds that can pass through the membrane - perhaps sucrose/fructose/glucose can do so, maintaining the structural integrity of the grape.

Both are guesses until you reveal more information, though.


What is positive and negative supercoiling? Is the following correct?

Positive supercoiling  = the coiling of DNA helix (B-DNA) on itself during intesified coiling of the two DNA stands in right handed direction

negative supercoiling  = the coiling of DNA helix(B-DNA) upon itself during uncoiling of the two DNA strands performed in left handed direction?

I'm a little confused.

According to this powerpoint from the SIU School of Medicine:

Right handed supercoiling = negative supercoiling (underwinding)
Left handed supercoiling = positive supercoiling

And from this Boston University webpage:

If DNA is in the form of a circular molecule, or if the ends are rigidly held so that it forms a loop, then overtwisting or undertwisting leads to the supercoiled state. Supercoiling occurs when the molecule relieves the helical stress by twisting around itself. Overtwisting leads to postive supercoiling, while undertwisting leads to negative supercoiling.

And finally from wikibooks:

Positive and Negative Supercoilings

Positive supercoiling is the right-handed, double helical form of DNA. It is twisted tightly in a right handed direction until the helix creates knot.

Negative supercoiling is the left-handed, double helical form of DNA.

Although the helix is underwound and has low twisting stress, negative supercoil's knot has high twisting stress. Prokaryotes and Eukaryotes usually have negative supercoiled DNA. Negative supercoiling is naturally prevalent because negative supercoiling prepares the molecule for processes that require separation of the DNA strands. For example, negative supercoiling would be advantageous in replication because it is easier to unwind whereas positive supercoiling is more condensed and would make separation difficult.
Topoisomerases unwind helix to do DNA transcription and DNA replication. After the proteins have been made,the DNA template supercoils by the force to make chromatin. RNA polymerase also influence DNA strand to have two different supercoiled directions. The region RNA polymerase has passed forms negative supercoil while the region RNA polymerase that have not passed forms positive supercoil. By these processes, supercoils are generated.

In the following image from web-books:

 (a) Positive supercoils (the front segment of a DNA molecule cross over the back segment from left to right). (b) Negative supercoils.
This video, titled "super coil (positive and negative) formation of DNA" should help you visualize this.


mRNA Sequencing Basepair from Polyadenylation Site? I was wondering how many basepairs are usually sequenced with mRNA/cDNA illumina methods from upstream of the polyedenlation site?
Thanks.

50-75 bp could be achieved.

Refrencing TruSeq® RNA Sample Preparation v2 Guide. My lab used random primers and read lengths were an average of 75 bp in length for an RNA seq project. But controlling distance from polyA wasn't considered in out project.

Using oglio(dT) primers you could try and control a specific length from the polyA tail.Two basic variations use either random primers or oligo(dT) primers for this reaction. Oligo(dT) primers are highly 3’ biased and mostly
suitable for mRNA abundance (expression) analysis. Random primers also result in some bias, which can be reduced by fragmentation of the input RNA.

Source: RNA Sequencing Methods Collection - Illumina, Page 8.

Different lengths can also be achieved for different needs.
Gene expression / RNA Profiling – Quantifying the coding transcriptome typically requires a short single read (often 50–75 bp) to minimize reading across splice junctions while counting all RNAs in the pool.

Transcriptome Analysis – Novel transcriptome assembly and annotation projects tend to benefit from longer, paired-end reads (such as 2 x 75 bp) to enable more complete coverage of the transcripts and identification of novel variants or splice sites. Paired-end reads are required to get information from both 5’ and 3’ ends of RNA species with Stranded RNA-Seq library preparation kits.

Small RNA Analysis – Due to the short length of small RNA, a single read (usually a 50 bp read) usually covers the entire sequence. A read length of 50 bp sequences most small RNAs, plus enough of the adapter to be accurately identified and trimmed during data analysis.

Source: Illumina (Considerations for RNA-Seq read length and coverage)


What percentage of human body's cells are contained in blood? What percentage of human body's cells are contained in blood vs. the rest of the body?

The human body has about $3.72 × 10^{13}$ cells according to Bianconi et al. 2013, although this is disputed.

It also has about 5 liters of blood, which is made approximately 40-45% of erythrocytes. Let's assume 2.5 liters = 2500 $cm^3$ of red blood cells (RBC). Assuming a mean value of 5 millions RBC per $mm^3$ there should be in total $5 \cdot 10^6 \cdot 10^3 \cdot 2500 = 7.5 \cdot 10^{12}$ RBC.

By completely taking out white blood cells and thrombocytes out of the equation, a number of ${7.5 \over {3.72 \cdot 10}} \cdot 100 = 20 \%$ of number of cells are contained in the blood (approximately).


How many cells does the hermaphrodite version of Caenorhabditis elegans have? Wikipedia states:

  The male C. elegans, for example, has 1031 cells

How many cells does the female version have?

959 Somatic Cells according to WormBase and The WormBook.


What causes sinus pain and congestion? When the sinuses flare up, it can get very painful.  Thus, my question - what biological mechanisms cause the congestion and especially the pain associated with sinusitis?

Inflamed sinuses are often associated with some kind of illness or irritant such as flu, the common cold, or hay-fever. As an example the cold causes sinus pain and inflammation because the virus is attacking/located in the nasal passages which causes swelling in the mucus membrane (the mucus membrane lines the sinus cavities). The swelling, along with increased mucus production, combines to create clogging and the pressure associated causes pain. Humidity will help loosen the mucus and anti-inflammatory medication should help reduce pain by reducing the mucus build up and swelling - thus relieving pressure.

The increase in mucus production is because of the role it plays in our bodies - it is produced to trap foreign bodies and help keep our system clean. The more mucus we produce the more our bodies are trying to clean up. This can cause an excess which is difficult to clear such that our sinuses become blocked and dried mucus becomes an irritant.

Sinusitis is the painful condition of swelling in the mucus membrane. Sinus comes from the latin for bent or curved surface, and -itis is from greek meaning swelling or inflammation linked to disease.

In summary: Painful sinuses, aka sinusitis, are painful because of infection in the mucus membrane producing swelling and excessive mucus build-up.


How to explain the colour of these scots pines? I would like to know why the trunks of scots pines have a particular colour, at least in Estonia, as shown here.

The bottom part of the trunks is darker than the upper part. What could explain this?

Thank you for your help!

The bark of some pinus species, like pinus sylvestris and pinus pinaster naturally turns orange when they are a bit older. Other species stay grayisch black, like pinus nigra (hence the name).

By the way: I have never seen pinus sylvestris grow so straight. Is it possible this is another species, for example P. pinaster?

Sources: Den nya nordiska floran (Mossberg&Stenberg 2003) and Heukels' flora van Nederland (van der Meijden 2005).


Why does hemoglobin electrophoresis in sickle cell trait gives two bands but not three? Electrophoresis of hemoglobin from a patient with sickle cell trait (carrier for sickle cell anemia) shows two bands. Why not three?  Since there are two beta chains in each hemoglobin, it seems to me they should have three types of hemoglobin: HBB/HBB, HBBs/HBBs, and HBB/HBBs. Does the HBB not form hybrids with HBBs? Aren't both polypeptides produced in the cell?

*HBBs signifying mutated beta chain

This is a really interesting question and again reminds of how ignorant we are about things as subtle as this which otherwise should have been an obvious question.

First of all, although there seems to be no confusion, I'd like to clarify that we are talking of the protein being separated on electrophoresis. Hemoglobin electrophoresis classically refers to the cellulose acetate/citrate agar electrophoresis where the RBC hemolysate is used as the sample. This method uses the fact that, hemoglobinopathies generally have mutated Hb which differ in charge from the original HbA. Charge is a property of separation in cellulose acetate electrophoresis unlike SDS-PAGE where separation is on the basis of mol. wt.

We can also do a DNA electrophoresis (digressing) to identify a Hbpathy after digesting with restriction enzymes which would give a different results, depending on the restriction enzyme that has been used to differentiate the mutation from the original. Here is an example using MstII for RFLPs. This isn't the topic of discussion here. Our sample is the protein, and not the DNA.

So it is important that the electrophoresis we are going to talk of, is of a protein electrophoresis based on charge.

Considering the sickle cell trait, let us clarify the terminology now. HbA is normal hemoglobin tetramer which composes of $\ \alpha_2\beta_2^A $. HbS on the other hand is $\ \alpha_2\beta_2^S $. The terminology you have used not only isn't standard but also is conveying a different meaning. Now logicaly, in a person with sickle cell trait, one should be expecting a hemoglobin with both different beta chains. And it does happen! Literature calls it the assymetric hybrid. Let us indicate it with AH which is $\ \alpha_2\beta^A\beta^S $. Let's sum this up a bit.

HbA = $\ \alpha_2\beta_2^A $

HbS = $\ \alpha_2\beta_2^S $

AH = $\ \alpha_2\beta^A\beta^S $

The assymetric hybrid that has been mentioned here is only for the sickle cell trait. There are many other hemoglobinopathies and in their heterozygous states one can obtain other assymetric hybrids with a different beta chain.

Now that we know that assymetric hybrids are formed, why do they not show up on the Hb electrophoresis?

It is generally believed that under physiological conditions, at equilibrium, hemoglobin is a mixture of tetramers ($\ \alpha_2\beta_2$) and dimers ($\ \alpha\beta $) as $$\ \alpha_2\beta_2 ⇌ 2\alpha\beta $$ The dissociation equilibrium constant for oxyhemoglobin is approximately $\ 2x10^{-6} M $ (heme) and is much less for deoxyhemoglobin. The asymmetric hybrid is generally not isolated by conventional techniques, since the tetramer-dimer dissociation constant is much lower in-vitro than in-vivo . Thus the asymmetric hybrid dissociates into dimers $\ \alpha\beta^A:\alpha\beta^S$ and reassociates into more symmetric forms during the separation process.

There are slightly modified methods to isolate the assymetric hybrids under deoxygenated conditions such as isoelectric gel focussing, cross linking the chains, etc. The amount of AH formed in proportion to HbA and HbS can be measured in these kind of experiments and has been found to be comparable to the expected binomial distribution of $\ a^2 + 2ab + b^2 $. This implies that the stability of the AH is comparable to HbA and HbS.

Hope it helped.

To delve further, here are a couple of reference that should be of use.

  HF Bunn and M McDonough (1974), Assymetrical Hemoglobin Hybrids.
  An Approach to the Study of Subunit Interactions, Biochemistry,
  13(5)989-93.
  MK. McCormack, TG. Westbrook, RM. Paull & S Berman (1981),
  Identification of the Asymmetric Hybrid of Human Oxy Hemoglobins A
  and S (α2βAβS) at 4° C by Cellulose Acetate Electrophoresis,
  Hemoglobin, 5(3)251-56.


Determine whether aromatics originate from polyketide or shikimate pathway Is there a way to determine whether an aromatic compound  originates from the polyketide or shikimate pathway by looking at its structure? If so, how?

Aromatics that stem from the Shikimat Pathway result in a structure like this

Whilst aromatics originating from the Polyketide Pathway have an alternativ structure in the distribution of the OH groups.


How to calculate extent of Sequence similarity I had a problem that I was wondering if it could be solved by one of the techniques/algorithms used in bioinformatics to give the extent of similarity.

I have a Problem Statement: we have a sensor (its like a magnetic compass and has a dial with twelve equal zones- 30 degrees each) that every second outputs where its pointing. The typical random output of the sensor may look like (for example):

  30 30 30 30 30 30 120 120 120 120 120 120 60 60 60 60 60 60 330 330 330 330 30 30 30 30 210 210 210 210 210 60 60 60 60 60 60 60 60 60 60 60 60 60 ……… etc.

We wanted to see if we can calculate a measure of similarity of two 4-minute sequence samples taken at different times during the day. (It would be great if we could state something like - the sequences are similar and there is a 1 in million (say) chance that we may be wrong.)

Well. You perhaps need not use the bioinformatic algorithms of string matching. These algorithms were primarily developed because of the extensive search space.

In your problem you just need to compare two recording experiments and you should use mathematical metrics for it. You have a 60x4 i.e 240 dimensional random variable. Moreover this variable is not discrete, it is continuous. For similarity measurements you have to use statistical tests or otherwise define a cutoff either on each element of the vector or the total magnitude defined by any norm.


What type of snake is this? We came across this snake when were on a hike in a typical dense forest in the Philippines. . Been wondering if this snake is venomous or not.

It is a green tree python (Morelia viridis)


What in neurons and their connections changes during the process of learning? I'm not sure if this question belongs more in physics or biology (or maybe even computer science)... but biology seemed to fit more.

What changes in the state of our brains when we learn things?  Because I looked on the internet and I learned about artificial neural networks, and every resource I've found teaches of neural networks that have weights that are trained/evolved and then are static at runtime; you simply train the weights and then once you use them in simulations, they never change.

Purely feedforward neural networks that rely on this can't react to new situations differently if they've experienced it before.  They react exactly the same each time.

I suppose that theoretically, a recurrent neural network that was big enough could really learn, but in practice, these have been used as purely memory slots for an existing method defined by the weights, not as storage of new methods of doing things.

So my question is, physically, chemically, biologically, what changes in the neurons and the connections between them when we learn things?  I don't think we really understand how it comes together on a grand scale yet, but I'm pretty sure we've figured out that much.  I want to learn how to model a simplified version of it mathematically/programmatically.

What changes in the process of learning:

The connections (the way one neuron is connected to another). New synapses can form or dissolve in the process of learning. The glial cells such as astrocytes and microglia can facilitate this process.
Strength of connections: Existing connections can be made weaker or stronger in the process of triggering the same circuit. This happens by up/down regulation of the ion channels at the synaptic junctions.

This process is not fully understood and is an active area of research. You can find some mathematical models too for learning processes such as Long Term Potentiation etc.


Does opening of ion channels alter the membrane potential directly? Does the opening of a voltage-gated ion channel (i.e. the change of configuration of the protein) by an appropriate local change of the membrane potential directly and significantly alter the membrane potential in turn? Like the influx of ions that was caused by the opening of the channel does directly alter the local membrane potential?

(Assume there were no ions going through the channel: would there nevertheless be a significant change of the membrane potential by the mere opening of the channel?)

Not in any substantial way from the perspective of the overall membrane potential; it could be possible to measure the charge moving as a way to study channel gating, but that's a completely separate issue (and the scale of measurement would have to be incredibly precise, way more precise than is relevant for neural function).

Although very few ions have to move across the membrane to change the membrane potential, this "very few" is in relationship to the total number of ions present in a solution, which is massive and difficult to imagine. A single ion channel can flux millions of ions per second.


Rationale behind washing off unbound protein antigen in indirect ELISA My question is with regards to the usability of the indirect ELISA in measuring protein concentration. Suppose we want to quantify the concentration of a protein. The indirect ELISA method would require one to coat the bottom of the well with protein antigen and wash off unbound antigens.

My question is that wouldn't washing off unbound proteins mean you are 'diluting' the actual protein concentration? Your resulting colour intensity will not reflect the actu protein concentration. Thanks!

The method is based on the principle that the amount of antigen bound to the plastic will be proportional to the concentration in the sample being tested. And of course an ELISA will usually be run with a calibration in parallel so that the signal from your sample is compared to that from standards.

The wells will be rinsed anyway in subsequent steps to remove unbound antibody molecules: if you didn't wash off unbound antigen it would simply compete for binding the antibody then disappear later in the procedure.


What physical traits are derived from the Neanderthal DNA in human DNA? Some researches had found that Human DNA has a bit of Neanderthal DNA. So they suggested there would have been crossing between Homo sapiens and Neanderthals.

Now the Neanderthal looked a bit different from Homo sapiens, so is there something in human that has some neanderthal looks?

And is it only found in European people or also in Asian or African people. Could it be be possible that a larger hairiness of European man is due to Neanderthal DNA?

There was a very readable piece on this topic by Chris Stringer in Nature in 2012. At that time his general conclusion was:

  It is not yet clear whether the archaic DNA many of us carry is tied to any visible traits.

Although he added:

  More controversially, some of the known differences in coding DNA
  between Neanderthals and recent humans are associated with brain
  development and function

quoting the paper in Science (2010) in which the Neanderthal sequence was published. There may be more recent information of which I am not aware.

As to your question about Neanderthal DNA in different populations, it is not present in people of African origin, but is present in those of Europeans and Asian origin.


How do lilies sense day and night and open and close their flowers? We have lots of lily flowers inside our garden. Their flowers are open in day and closed in night. How do lilies sense day and night and open and close their flowers?

The three main cues for flower opening/closing used by plants are temperature, light and humidity (van Doorn & van Meteren 2003, freely available pdf), with the first two being most common. Plants with daily opening and closing of flowers can be divided into nocturnal (open at night) and diurnal (open at day). There exists several different mechanisms for how flowers open and close, and these include e.g. reversible expansion and contraction of cells by changes in water balance and differential growth of cells due to temperature (in either the petals themselves or cells at the base of flowers). See the previously referred paper for examples.

The evolutionary advantages and molecular mechanisms (along with the circadian clock of plants) behind opening and closing of flowers are open research fields. Several evolutionary hypothesis exists for explaining different flowering strategies, and these often deal with efficient pollination (close when good pollinators are absent), protection against frost, conservation of resources (e.g. water) or predator/pathogen defence.

I do not know what the specific mechanism in lilies is, and it can possibly/probably differ between different species.


Can the eye distinguish between pure and composite colours and how do we measure this? Red light plus green light makes yellow light.

Suppose I shone a pure red light, say 650nm, onto the same spot as a pure green light, say 550nm. The eye sees this two-peak spectrum as yellow.

This presumably means we are tricking the eye, since a pure yellow light source would also be perceived as yellow.

Do the cells on our retina treat composite spectra equivalently to corresponding single-peak spectra? If not, how do we quantify the gap?

Yes, we do perceive a composite spectrum in a way which is analogous to how we perceive the corresponding single-peak spectrum. Human beings have trichromatic vision, meaning that there are 3 types of specialized cells in our eyes for seeing color. Each one has a different color of light which produces peak stimulus, although they all perceive a range of colors:

(the axes are wavelength and normalized response)

None of the color-sensing cells has a peak color of yellow. In order to perceive something as being yellow it either has to be pure yellow or stimulate the 3 types of color sensing cells in a very similar way as pure yellow would. However, if you took very careful readings of the output signals from the color sensing cells you might see some subtle differences in the exact waveforms of the responses.


What are "intrinsic hypothalamic fibers"? (From an article on neuronal mechanisms of sexual desire) I came across the phrase intrinsic hypothalamic fibers which I cannot understand. What is meant by intrinsic - that these fibers (long myelinated axons?) start in the hypothalamus? Or that they start and end in hypothalamus? Or something else?
The article is "Pathways of Sexual Desire" by James Pfaus (2009).

Figure 8 Brain opioid systems overlaid on opioid binding regions (high density of receptors indicated by red to yellow, lower density in green to blue). Three systems exist: the pro-opiomelanocortin (POMC)-derived opioids such as р-endorphin, which arise from the same population of projection neurons that produce the melanocortins; the interneurons in the cortex, limbic system, hypothalamus, and brain stem, which produce enkephalins and dynorphins; and the intrinsic hypothalamic fibers, which contain endo- morphins. These systems are activated at orgasm in humans, at ejaculation in male rats, and during paced copulation in female rats. They shut down hypothalamic regions associated with sexual arousal and desire, thereby inducing refractoriness. However, opioids are also released in the VTA during phases of sexual arousal and desire and help to disinhibit DA neurons and, thereby increasing DA release in mesolimbic terminals. This is an important mechanism by which experience with sexual rewards sensitizes sexual excitement once the inhibitory effects of refractoriness and satiety wear off. VTA = ventral tegmental area; DA = dopamine; mPOA = medial preoptic area; mPFC = medial prefrontal cortex; NAcc = nucleus accumbens; PIR = piriform cortex; MeA = medial amygdala.

"Intrinsic hypothalamic fibers" are fibers instrinsic to the hypothalamus; so yes, these are fibers either projecting from somewhere in the hypothalamus to somewhere else in the hypothalamus, or locally in the hypothalamus (the hypothalamus itself is a pretty complex structure containing many distinct nuclei). The paper you reference specifically mentions the medial preoptic area, mPOA, as a target:

Infusions of mu opioid receptor agonists to the mPOA inhibit sexual behavior in male rats

and

infusions of a mu antagonist to the mPOA, but not NAcc, block sexually conditioned place preference

"Fibers" does not necessarily refer to myelinated axons, just axons of any sort.


Plant disease identification I’ve noticed recently strange formations on the leaves of my flower.
No idea what could it be.
Could anyone help with the identification?

The white things look like scale insects, you can scrape them (and their waxy fluffy coats) off the leaves.
If you can identify the plant, that would also help.
The gardening SE is also a good place for these questions.


19th century Latin species description While reading a 19th century text of new species description, I'm confused by some Latin phrases.

The case here is:

  Corp. long. 8 poll., caud. 9 poll.

I guess 'corp.' and 'long.' are abbreviations of some Latin terms, and the whole meaning of the combination of these two words is probably "body length". But I still can't figure out what "caud." and "poll." (the number seems like is in inch though) are stand for.

The species described is a rodent species. Full text could be found here (p.185).

The pollex was a Roman length measurement, approximately equivalent to an inch. The pollex was also known as the uncia, which is where the word "inch" comes from. There were 12 unciae in a pes ...


Where do trees get their shape? Does anyone know any good resources dealing with shapes of trees?

For example, pine trees are cone shaped for optimal absorption of sunlight, but lone pine trees growing in isolation (and other commonly cone shaped conifers) often grow very high above ground and have no well-defined shape. Presumably, when there aren't neighbours to compete with for sunlight or space, the optimal shape is..well, whatever shape absorbs most sunlight; less constraints = more possibilities.

Looking for an answer that explains this sort of phenomenon. Thanks.

Dr Karl Niklas from the Cornell University has written a book about the effects of factors that influenced the shape of early trees. He created a computer model in which he drew trees in the shape that favored particular characteristics.

  When Niklas favored plants that could gather light from the sun, they
  had non-overlapping horizontal branches. When reproductive success was
  favored, the plants grew tall, in order to spread their seeds. When
  the trait selected for was mechanical stability, the plants had few
  horizontal branches.

When he combined these three favourable traits, he noticed that most of the trees today are in a form that favors these three traits (reference).

L is light favourability, M is mechanical stability and R is the shape of trees that favor reproductive ability.

Explanations for a few shapes found commonly with examples can be found in this article.

Illustration for the common tree shapes Columnar, Pyramidal,Vase, Round, Spreading, Weeping and umbrella with a few more examples can be found in this article (reference).

Another interesting thing about trees is the way in which their shapes can be influenced for the purpose of landscaping (reference).

What you mentioned about pine cones in isolation having no definite shape at all, I would like to see a reference that this is a fact before I can elucidate on it further (I couldn't find any articles that mentioned such a phenomenon).

The reason you felt so could be because it were two completely different species of pines. Counting varieties and subspecies, the plant list of the Royal Botanic Gardens, Kew and Missouri Botanical Garden accepts 175 names of pines as current(reference). Here is a list of different pine species (reference).

Here is an article on how tree shape and light available influence yield in cherry trees.