Are there more descriptive ways of naming genes and gene interactions? I couldn't help but notice just how non-descriptive the gene names that modern genetics is using. Currently I'm reading "The new science of Evo Devo" by Sean B. Carroll and here are some examples of gene names used:

Fzrb
Krox 20
Hoxa2, Hoxb4
ZPA
FGF8
sonic hedgehog

While these names identify genes uniquely, they do very little to express what and where the gene does, or how it is related to other genes (While FGF8 may be related to FGF7, it's relationship to XYZ10 is not obvious).

I get the need to uniquely identify genes , and the book is an example of just how hard it is to presently write about a lot of genes at once. The author creates a picture of what's going on, but the gene names get in the way. Even in cases where a gene has a semi-descriptive name, like "eyeless", the reader has to remember that it's actually the gene responsible for eye formation.

Are there are any efforts underway to systematize or name genes for a given organism in an expressive manner?

As a programmer, I write code for a living, and having descriptive names makes it easier to look at someone else's code, read about code and even discuss it with novices. For example:

initializeDataModel
createViewHierarchy
userDidSelectLayerAtIndex

Modern programming tools make using descriptive names easier, because of autocomplete - typing in the first few letters of a programming structure completes the rest. Even google has a list of autocomplete suggestions.

We are all familiar with the Internet, where biology.stackexchange.com/questionname resolves into a specific page. Stackexchange is the site we are visiting, and Biology is a subset of that site. There are other biology websites, but biology.stackexchange.com uniquely identifies this site. The use of "biology" in the address gives readers a general idea of what the site is about and relates it to other biology sites. Our web browsers resolve the address into a proper string of bytes and get the right page. What if we name genes like like

com.drosophila.eyeformation
com.chicken.limb.structure.ZPA
com.human.development.geometry/XYZ10

,and whatever technology we use would actually resolve that descriptive name into a gene or a series of gene interactions?

Many gene names are descriptive, e.g. DRD1: dopamine receptor D1, TOP2A: DNA topoisomerase 2-alpha, or PTGS1: prostaglandin G/H synthase 1. These are examples of genes that have a clearly defined main function.

The genes you listed are involved in development, and there describing the function of a gene becomes much more difficult. E.g. sonic hedgehog is involved in patterning many organs, from brain structures to teeth. How would you assign a descriptive name?

The analogy to (programming language) functions does not work for many genes, because they were not designed to fulfill one function, but evolved to do many different functions. For genes that have many functions, we just need a unique name. The multitude of functions is catalogued elsewhere.

(Bonus descriptive gene family name: MAPKKK: MAP kinase kinase kinase)


Selection Pressure on Orca Whale Coloration What is the proposed selection pressure that leads to the distinctive coloration of Orca whales? I can find nothing in the literature.

You can find a discussion of this topic in the literature:

Mitchell, Edward. 1970. Pigmentation pattern evolution in delphinid cetaceans: an essay in adaptive coloration. Canadian journal of Zoology 48(4): 717-740.

Perrin, W.F., 1972. Color patterns of spinner porpoises (Stenella cf. S. longirostris) of the eastern Pacific and Hawaii, with comments on delphinid pigmentation. Fish. Bull, 70(3), 983-1003

Caro, T., Beeman, K., Stankowich, T. and Whitehead, H., 2011. The functional significance of colouration in cetaceans. Evolutionary Ecology, 25(6), pp.1231-1245. http://web.csulb.edu/~tstankow/Caroetal2011.pdf

And related helpful article:

Evans, W.E., Yablokov, A.V. and Bowles, A.E., 1982. Geographic variation in the color pattern of killer whales (Orcinus orca). Report of the International Whaling Commission, 32, pp.687-694. http://www.kasatka.com/kirsten/ColorVariation.pdf

I'll let you explore these and their citations.

Remember, Google Scholar is your friend.


Do animals get sick with hemorrhoids? Do animals get sick with hemorrhoids ?

And why Humans are most affected of it ?

Is it because the gravity center of Humans is sittuated in the anal ?

Why are haemorrhoids more common in humans than in animals?
This is due to the majority of animals, including apes, are on all fours. Only the human species stands and walks straight up with two feet. Therefore, the blood in the body has enhanced arduousness in circulating and travelling back to the heart. A justification for the commonness of hemorrhoids in humans, is there is a higher frequency of blood congestion which then further leads to hemorrhoids.
There are animals which can get haemorrhoids

Cats
Dogs
Apes
Horses

The reasons and causes why animals can also get hemorrhoids is similar to humans, besides the structural reasons. This may include:
In Horses

The horse may strain while delivering young ones

When the bowel movements are disturbed, as in constipation, it leads to an increase in pressure applied to the rectum region. Unlike humans, the increased pressure from constipation does not come from straining to get the excrements out, but from the impaction of the excrements within the horse and the resultant pressure that causes.  This in turn leads to expansion of the blood vessels around the anus and this may cause hemorrhoids and eventually bleeding.

In cats

One of the main reasons behind the occurrence of cat hemorrhoids is heredity, which plays a major role in deciding who would and who would not get afflicted with this condition.
Diets low in fiber and liquid content are the main cause of constipation, which in turn leads to excess pressure being applied during defecation and straining when bowels are passed. Too much pressure in the rectum and lower abdomen causes blood vessels in this region to expand, thus leading to the creation of lumps called hemorrhoids.

There have also been some investigations in which haemorrhoids were induced by ligation of the inferior haemorrhoidal vein into apes. The outcome of this was that after a certain amount of days, there were hemorrhoidal piles in the anus in fifty percent of the animals. The outcome was unremarkable. There was no bleeding and all animals showed no signs of pain or suffering.
References:

"Horse Haemorrhoids, Horse Hemorrhoids, Horse Haemorrhoids, Horse Piles - Web. 01 Mar. 2016.
"Result Filters." National Center for Biotechnology Information. U.S. National Library of Medicine, Sept.-Oct. 2006. Web. 01 Mar. 2016.


What is immunopanning (vs. immunoprecipitation and FACS)? I had never heard the term before today. From what I can tell, it's using antibodies to purify a cell population of interest. I would appreciate more details, especially in how it differs from "immunoprecipitation" of cells via cell surface markers, and FACS.

Immunopanning is essentially an immunoprecipitation (IP) of cells using an antibody immobilized to a solid surface, like a cell culture plate. Conventionally, an IP is performed using small agarose or magnetic beads (~50 to 150μm in size) conjugated to an antibody or Protein A/G, and can pull down individual proteins, protein complexes, and/or nucleic acid complexes.

Cells are much larger than protein complexes, obviously, and for the most part much smaller than beads, but they can be damaged during a traditional IP, so immunopanning utilizes a single solid surface coated with the specific antibody or cell-surface protein ligand of choice. In this article (free PDF here), retrograde axonal transport was used to selectively label specific populations of neuronal cells with the extracellular portion of cholera toxin β (CTB) adsorbed to fluorescent beads, then the cells were purified using an immobilized anti-CTB antibody.

Fluorescence-Activated Cell Sorting or FACS is another way to purify cell populations. Cells are labeled with a fluorescent marker (either conjugated to an antibody specific to an extra-cellular epitope, via absorption as in the example above, or by expression of a fluorescent transgene like GFP), then scanned in a flow cytometer. Cells which match certain parameters or "gates" in the machine's software are then diverted into a separate collection chamber, allowing for the generation of a quite pure cell population.

However, as the authors point out in their paper above, FACS requires an expensive piece of equipment (can be over US$100,000), can be harsh on the cells, and is dependent on the availability of an antibody to a cell surface marker specific to the desired population of cells. Immunopanning is much less expensive, is more gentle on the cells, and in the authors' case was really the only choice for purifying their cell population of interest, as no specific biomarkers were available. It certainly won't replace FACS in the long run, but is another tool for investigators to use when studying specific cell types.


Do macrophages engulf mtDNA? Let us assume that in a human body, a mitochondrial DNA is released to extracellular environment.
We know that mtDNA inheritance is solely matrilineal.

So the question is, If your mitochondrial DNA is released to the extracellular environment (or into
cell cytoplasm) due to cellular and/or mitochondrial damage, what could be the
ramification of this released DNA if your immune system cells (such as macrophages,
dendritic cells or B cells) pick up and sense these DNA as a danger signal?
Is there any chance for mtDNA to survive by establishing a new mtDNA ?

I am thinking, macrophages engulf and destroy them but cannot provide sufficient evidence.

EDITS - I appreciate the comments and have incorporated them here.  Thanks to    @Superbest and @user22406 for raising them.  I hope this makes a better answer for the community.

Under normal circumstances, genomic (self) or mtDNA released into your cell or body cause absolutely no (known) problems.   I'll explain why that is, how the body can detect bacterial DNA, and finally the circumstances in which DNA can cause problems.

Self-DNA generally causes no problems

Almost from conception, cells in your body die.  Sometimes as part of pre-programmed sequence (eg inter-digital cells of the fetal limb paddle die and form fingers) or normal replenishment of cells such as the white blood cell (hundreds of millions of neutrophils die each day) or your gut epithelium.

Macrophages consume liberated DNA, and the reticulo-endothelial system in the spleen, liver and lungs filters the blood for cellular fragments.  This paper (from @Superbest) shows that bacterial DNA, and not normal human genomic DNA, can activate macrophages.

So your immune system develops, and is constantly being exposed to, virtually every cell type and cell component (proteins, lipids, DNA and RNA etc).  If self-DNA could spark an immune reaction, normal life would be difficult.  We don't make antibodies (from B-cells) or T-cells that react with self-components due to a process called anergy in which any developing T- or B- cells that could react to self-components during their maturation are instructed to shut down and/or die.   Yes, mitochondrial are inherited matrilinearly, but they still lyse and cause anergy, preventing an auto-immune response.

(Not all cell death is harmless- @Superbest's comment reminds us that apoptosis (involved in finger formation and other tissue remodelling and cell turnover) can package cellular components into self-contained vesicles.  On the other hand, damaged or lysed cells can liberate cytoplasmic components that can be pro-inflammatory or pro-coagulant.)

Macrophages' vacuoles contain DNAse II, an enzyme that degrades DNA it encounters following phagocytosing/endocytosing fragments of dead cells.  More about that later....

Our bodies can detect bacterial DNA.  Same DNA, different decoration

However, invaders (bacterial, viruses, worms etc) may activate a family of receptors called Toll-like receptors (TLRs).   TLRs have evolved to have specificity for antigens not seen in mammals e.g cell walls, bacterial flagella and so on.  Some TLRs do recognise DNA or RNA.  You may know that DNA contains 4 nucleotide bases, A,T,G and C.  In mammals, special sequences of two bases, C-G, (called "CpG"s) can be enzymatically modified by a methyl group.  In bacterial CpGs are not typically methylated and so a TLR (e.g TLR-9) that detects un-methylated CpGs is generally detecting bacterial DNA.

Mitochondria are different

Mitochondria have features that resemble bacteria: a cell wall, a genome and the production of proteins that begin with the amino acid N-formyl-Methionine (f-Met).  Mammalian proteins don't have f-Met at the start ("N-terminus").  Macrophages have a receptor that can recognize f-Met sequences (especially f-Met-Leu-Phe, fMLP) and activation of the fMLP receptor stimulates phagocytosis.

This 2013 paper describes the controversy whether mammalian  mtDNA is methylated (at CpGs) and offers strong evidence that it is methylated.    In contrast, the Oka paper  gives 5 citations where mtDNA is not CpG-methylated.

So..do mitochondria look like bacteria to our innate immune system?

@user22406 flagged this paper by Oka et al which cites this paper by Zhang et al as evidence that mtDNA can be pro-inflammatory.  The Zhang paper provides evidence that mitochondria can stimulate the immune system's receptors for (1) f-Met-peptides (i.e detecting mitochondrial proteins that look 'bacterial") and (2) receptors for un-methylated CpGs, the TLR-9 receptor.  The Commentary on the article has a great figure of how mito components might promote inflammation which copyright prevents me adding.

The Oka paper uses 2 key techniques: (1) surgical constriction of the aorta to cause heart enlargement (cardiac hypertrophy) and (2) a mouse strain with the gene for DNAse II deleted (noted as -/-, two minuses, both alleles gone).  In the hearts of DNAse II -/- mice, they observe higher levels of deposition of mtDNA in the damaged heart (Supplemental Fig 2), greater heart damage and many animals die.  This suggests that excessive levels of DNA (not degraded in these DNAse -/-  mice) may be driving the damage. (The general phenotype of DNAse -/- mice was studied by Kawane et al  and the mice get an arthritis).  In Oka's DNAse II -/- mice, the degree of heart damage can be reduced by blocking TLR-9 (using an inhibitory oligo).  In aortic constricted mice where the DNAse II gene is intact (+/+), adding the TLR-9 blocking oligo gave some improvement, suggesting that the level of unmethylated DNA liberated in tissue damage may stimulate TLR-9 in normal animals.
The authors also examined aortic constriction in TLR-9 -/- mice and found they had less lung and heart damage compared to controls.

In summary, the Oka paper suggests something is signalling  via TLR-9 to drive inflammation and damage in this model and implies (but does not prove) that the 'something' is mtDNA.

mtDNA in the plasma

Another Zhang paper  detects up to 1ug/ml of mtDNA in the blood following major trauma (car and motorcycle crashes, falling 4 stories etc).  Their paper shows that this level of liberated mitochondria could stimulate immune cells (via TLR-9 and f-Met receptor).

mtDNA won't get back inside the cell

Extracellular DNA and RNA is generally broken down and cleared rapidly.  DNA, being a large, negatively charged molecule, will have extreme difficulty passing through an intact cell membrane.  In the laboratory, cells need to be exposed to high voltage electric shocks to make transient 'pores' in the cell membrane to allow DNA to enter or have the DNA formulated in liposomes.  Even if endocytosed, there is no known pathway to direct endocytosed DNA to the nucleus or an new mitochondrial 'host'.  So mtDNA would be extremely unlikely to re-seed into a new cell or a mitochondria.

But self-DNA can be harmful if released in large quantities

During successful cancer chemotherapy, large numbers of tumor cells lyse and may give rise to tumor lysis syndrome.  Among the products released when a tumor is killed is DNA. A and G - the 'purine bases' - can be further metabolized into uric acid.    Uric acid can crystallize in the kidney and cause damage.

Summary

Mitochondria may be the remnants of endosymbiotic bacteria but, absent major trauma or mutations in both of your DNAse II genes, mitochondria come (and stay) in peace.


How many people's DNA were involved in the compilation of the reference human genome? I know that the reference human genome is complied from DNA portions from different people, most of whom were European. Do you know how many of them were involved? Do you know which ones were involved? Perhaps scientists like James Watson and George Church's DNA were in the reference genome. Also, I would assume that the NIH funded Human Genome Project's reference genome must be slightly different from the privately funded one.

tl;dr: In the Human Genome Project, they used the DNA of four people (though one male provided >70% of DNA. The Celera genome was compiled from five people.

  In the [...] Human Genome Project (HGP), [...] scientists used white
  blood cells from the blood of two male and two female donors (randomly
  selected from 20 of each) -- each donor yielding a separate DNA
  library. One of these libraries (RP11 [anonymous donor from Buffalo,
  NY]) was used considerably more than others, due to quality
  considerations.

  [...]

  In the Celera Genomics private-sector project, DNA from five different
  individuals were used for sequencing. The lead scientist of Celera
  Genomics at that time, Craig Venter, later acknowledged (in a public
  letter to the journal Science) that his DNA was one of 21 samples in
  the pool, five of which were selected for use.

  On September 4, 2007, a team led by Craig Venter published his
  complete DNA sequence,[21] unveiling the six-billion-nucleotide genome
  of a single individual for the first time.)

Source: Wikipedia


Where can I find a picture of the inflorescence of Epipremnum aureum (golden pothos)? Epipremnum aureum (golden pothos) is a very popular house plant - attractive and almost impossible to kill.

Also, it is a flowering plant with flowers produced in a spathe up to 23 cm (9 in) long, according to Wikipedia.

I have been trying to find further documentation of these flowers, in particular a picture, without success. Can anyone help?

(Google image search produces some stock photos that claim to show E. aureum flowers but I am skeptical about these.)

Figure 4d on page 6 of (Hung, 2016) shows a flower the authors managed to induce in E. aureum (This is one of the papers that mgkrebbs cited in his answer).

Hung, 2016 - Chiu-Yueh Hung, Jie Qiu, et al., "Gibberellin deficiency is responsible for shy-flowering nature of Epipremnum aureum", Scientific Reports 27 June 2016, DOI: 10.1038/srep28598 Creative Commons Attribution 4.0


Assays during drug discovery After researching the definition of Assay, I am left with the idea that an assay refers to scientific screening. It could be of chemicals, microbes, etc.

I understand that during drug-discovery assays scientists screen for chemical compounds that may make up an effective drug.

But could someone explain, or provide me with some links that further discuss the process of assays, or how they work or take place during drug discovery?
Frankly, I'm also still a bit confused about the definition of "Assay" itself.

Thank you.

An assay may be thought of as a trial or test that is designed to quantitatively determine the amount of a substance in a sample.

Thus a biochemist might use a protein assay to quantitatively determine the amount of protein in a sample, or a pharmacologist might assay a sample to quantitatively determine the amount of drug present, or an enzymologist might carry out an enzyme assay to determine the amount of enzyme activity in a sample.

Let's take the case of the enzymologist. I take a liver sample, homogenize it, centrifuge and take the supernatant (soluble) fraction. I want to quantitatively determine the amount of a given enzyme activity.

I do this by performing a test by (say) adding a sample of the supernatant to a cocktail that 'does something' only if the enzyme of interest is present.  The 'do something' could be a color change, where the cocktail  contains  everything needed for the enzyme to work (all substrates, cofactors etc) and where the enzyme transforms one of the substrates to a coloured product.  I now have an enzyme assay which tells me if the enzyme is present (the trial), which may be made quantitative with reference to the amount of color produced in a given time.

As I remember things, Sherlock Homes was pretty good at the assays, using them to make trials of his geological samples, but I cannot find the quote.


Is post-transcriptional regulation of gene expression an epigenetic process? Is post-transcriptional regulation of gene expression (for example regulation by microRNAs) a type of epigenetic gene expression regulation?

I think we can categorize it as epigenetic since the DNA sequence is not changed, but I have never come across that terming in any papers. Does someone have any idea, or know of any papers that categorize post-transcriptional regulation as epigenetic?

miRNAs and other post-transcriptional regulators are very well "genetic". They are encoded by genetic elements, are expressed and are affected by mutations. Just because this mode of regulation was not well known previously, it should not be classified as an epigenetic mechanism while the traditional protein based transcription factors (TF) are not.

Epigenetics, as it is originally defined (the "formal definition") is about mechanisms that can perpetuate the state of a cell to its next generation. Inheritance of gene expression programmes is therefore epigenetic. Although the gene expression programmes themselves can be implemented via different factors including protein and RNA based regulators, they would not necessarily constitute the epigenetic mechanisms that lead to inheritance of this state.

rg255's point of view is that any mechanism that causes a variation in the functional aspects of the genome without altering the genome sequence itself, would be epigenetic. This is technically correct but in that case all gene expression regulators including TFs should constitute epigenetic mechanisms.

Now, the main issue is where to draw the line between gene regulation and epigenetics?

In my opinion, the epigenetic mechanisms are one of the ways to regulate the gene expression. Although histone modifications and DNA methylation regulate gene expression and also confer heritability to the gene expression programme, the heritability can be implemented without them as well.

You can imagine a cell as a vessel which runs a system of biochemical reactions. This system can have multiple steady states (for e.g. multiple fates of a stem cell). To perpetuate a state, the new cell just needs to have the right initial conditions. This can be proved mathematically too. Such a system can be implemented via the traditional transcription factors as well. So what is epigenetic?

IMHO epigenetic was a loose term to denote something that people were not fully aware of, at that time. Anything that was not directly mediated by transcription factors was termed as epigenetic, including long distance regulators, non-coding RNA etc.

BOTTOMLINE

I would not classify non-coding RNAs as "epigenetic" for the very reason that they are encoded by genes and have more or less a direct effect on the target genes, just like TFs (which are apparently not epigenetic). As for the papers, there were many papers that used to assign these under epigenetic mechanisms, but that is IMO just too vaguely arbitrary. (Ironically, I happened to come across miRNAs and lncRNAs while I was doing a summer project on epigenetics and was reading relevant papers.)

What should be considered epigenetic would be a subject of another debate.


What is the difference between a paralog and an isoform? I am reading a journal paper about the protein kinase GSK3 and I have come across the following statement:

Although commonly referred to as isoforms, GSK3α and GSK3β are
actually paralogs, homologous proteins derived from different genes.

I am not sure what the difference is between an isoform and a paralog. I have Googled both definitions and paralogs refer to 'genes that derive from the same ancestral genes'.
Whereas isoforms refer to 'any of two or more functionally similar proteins that have a similar but not identical amino acid sequence and are either encoded by different genes or by RNA transcripts from the same gene which have had different exons removed'
These definitions seem quite similar to me so I was wondering if there are any significant differences between paralogs and isoforms? Any insights are appreciated.

I think the confusing thing here is that the two terms come from different fields of biology. While describing something similar, they emphasise different aspects.
The term paralog is mostly used in evolutionary biology, when one wants to find out how genes developed. Paralogs are, as you correctly found out, genes that originate from the same ancestral gene which duplicated. Thus, you would use this word when you want to emphasise the evolutionary relationship.
The term isoform on the other hand is not interested in evolutionary origin, and in fact it is not perfectly defined. This word is used when people studying the molecular biology of an organism discover that there are proteins in this organism that have a very similar amino acid sequence. Here, the interesting question is what differences in function these similar, but slightly different proteins might have. The evolutionary origin is not asked for, and thus there are two different definitions of isoforms:

Some people define isoforms only as variants of the same gene that underwent different post-transcriptional modifications (e.g. English Wikipedia), thus, paralogs would not be isoforms.

Other people also allow paralogs in addition (e.g. German Wikipedia).

In your paper, I guess that the author wants to emphasise that the proteins are not the results of different splicing but encoded by two different genes.


Why can you graft two unrelated cacti successfully, but you cannot do this on garden trees? Any cactus can be grafted onto any other cactus, and even the most unlike of them grow together. My latest graft was a Schlumbergera truncata scion on an Opuntia microdasys rootstock. This kind of graft is always successful. Why can't garden trees be grafted in a similar way, between genera?

Firstly, different genera of trees can occasionally be successfully grafted. For example, quince, genus Cydonia, may be used as a dwarfing rootstock for pear, genus Pyrus.

However, it is true to say that this is the exception rather than the rule.

In the case of plants in the family Cactaceae, I would suggest that grafting is usually successful for two main reasons:

Genetic similarity. Plants in the family Cactaceae while known to be morphologically often very different, have relatively little genetic diversity. This will increase the likelyhood of a successful graft.
Ease of aligning vascular cambium. This is required for a successful graft, and in Cacti this is quite easy to achieve since the cambium is clearly visible when you prepare the scion and stock.

It is also possible that Cacti readily form callus tissue, which would also aid in the grafting process.

Nyffeler, R., 2002, doi: 10.3732/ajb.89.2.312 Am. J. Bot. 1 February 2002 vol. 89 no. 2 312-326


What would be the best dredging/trawling tools to collect macrofaunal priapulids? Title says it all. I've been searching for the best way of collecting macrofaunal priapulids and would like advice on sampling methods and particularly sampling tools. Since large priapulids are usually found in low densities any form of grab-sampler would probably be inefficient and a dredge/trawl would be preferred. Any ideas on what tool(s) would sample at the right depth and filter efficiently?

My first question would be is there any external indication of them such as air holes or anything else that you can assess from the surface?  I would think that if there is, you could use transects and a quadrat.  If you need to dive for them you can obviously make a weighted quadrat by filling pvc pipe with sand and gluing it together.  Then take an area and lay out transects and and randomly choose different lengths along each transect to put the quadrat down and that will give you an estimate of density.  If you actually need to extract them from the mud, I imagine that varies by species and you could make due with a grab sampler of the right size, something on the small end I would imagine.  That way you aren't dredging up tons and tons of mud to sort through.  If they are even rarer than I imagine, you could just lay out transects and swim them until you see something and do away with the quadrat.  Hope this helps.


Why do negative ions flow into a cell in an inhibitory synapse, even though a neuron has a negative resting potential? In my spare time I have been reading an introductory Psychology textbook and this question came to my mind after reading about action potentials.  I have no previous knowledge in chemistry so if I do need some sort of other knowledge I would appreciate if I could be told what I need to learn in order to understand the physiology of the nervous system better. So Why do negative ions come into a cell during an inhibitory synapse even though a neuron has a negative charged resting potential?

I understand this question might be extremely vague and impossible to answer without previous knowledge of the physiology of the nervous system. Any help would be greatly appreciated.

Short answer
Negative ions can flow against the electrical gradient into the cell, provided their concentration gradient across the cell membrane is large enough.

Background
When an ion channel opens, the resultant ion flow is dependent on two things; the membrane potential (which is indeed negative at rest) and the concentration gradient of the ion.

Consider the activation of a GABAA receptor. GABA is the principial inhibitory neurotransmitter in the nervous system. GABA opens the associated Cl- channel on GABAA receptors.

Using the Nernst equation one can approximate the membrane potential (Veq) at which an ion is in equilibrium. It mainly depends on the concentration of the ion X outside and inside the cell ([X]o and [X]i, respectively).[Cl]o is approximately 103 mM, and [Cl]i 4 mM. Hence, there exists a large concentration gradient with lots of it outside the cell.

Nernst equation. Source: Physiology Web

In a neuron, the Nernst potential of Cl- is around -71 mV. Hence, given that the resting membrane potential is approximately -70 mV for a typical neuron, no Cl- flux will occur when Cl- channels open, because the resting membrane potential is equal to the equilibrium potential of Cl-. However, when a neuron is depolarized by stimulatory neurotransmitters (e.g., glutamate), the membrane potential may be reduced to, say, -60 mV. This is still more negative than the action potential threshold (about -55 mV), but very close to it. So without any inhibition the neuron would be close to firing a spike. However, when GABA is released presynaptically, opening of the Cl- channels coupled to GABAA receptors will result in Cl- influx, because the membrane potential is higher (more positive) than the equilibrium potential of Cl-. In effect, Cl- will enter the cell until its equilibrium potential is reached, re-polarizing the neuron back to -70 mV and hence inhibiting it.


Enzyme inhibitors against common cold viruses Would some inhibitors of viral enzymes work against common cold viruses? Are there any studies? What could a treatment look like?

A lot of common cold viruses are rhino viruses which are picorna viruses. All picorna viruses contain two cysteine proteases, designated 3C and 2A according to Handbook of Proteolytic Enzymes
Volume 2, 2013, Pages 2402-2406
David S.Wishart Would it suffice to inhibit either of them?

A human enzyme involved in the production of rhinovirus capsids has been successfully inhibited.

  Fragment-derived inhibitors of human N-myristoyltransferase block capsid assembly and replication of the common cold virus https://www.nature.com/articles/s41557-018-0039-2

The article also says that targeting a human enzyme could be more efficient since the risk of mutation is lower compared to a virus enzyme.


Hot water and bacteria I know that it is common to say, "use hot water when washing your hands" or when you've got a cut, "wash your hands with warm water," etc. I was wondering, why is this the case? Since bacteria grow in warm environments, you would think that it might be beneficial for bacteria. Is this just another myth or is this actually true?

The bacteria wouldn't see any benefit from the warm water in the ~30-60 seconds you're washing your hands, neither would hot water "sterilize" your hands at temperatures you could tolerate. The reason you wash your hands with hot water is because the hot water+detergent soap mix is better for removing oil and dirt than cold water+detergent, which is supposedly where bacteria reside.

Interestingly, there was a study published saying that washing with hot water doesn't have much of an effect on bacterial load. Hot water for handwashing--where is the proof? (Laestadius and Dimberg, 2005). I'd be interested to look more into their methods but the paper is behind a paywall and I don't have access at home.

Also, this paper, Water temperature as a factor in handwashing efficacy by Michaels et al. is open and shows no evidence that hot water is any better than cold water for removal of microbes.

  [W]ater temperature exhibits no effect on transient or resident bacterial reduction during normal handwashing with bland soap.


What are primary reasons for the failure to localise/anchor sequences in genome assemblies? My question concerns the incorporation of individual sequence reads into chromosomes during gene sequencing projects, especially those with larger genomes such as Drosophila melanogaster or Homo sapiens.

There are some sequences or short contigs that it has not yet been possible to incorporate into the larger chromosome assemblies.

What are the reasons for this failure?

I'm going to re-interpret this question slightly to make it easier to answer:

"Why do genome assemblies frequently consist of large numbers of short contigs rather than a relatively small number of long chromosomes (or full replicons of other types)? And how could I make my assembly better?"

De novo sequence assemblies (usually) consist of a set of contiguous sequence fragments ("contigs") that have been derived from shotgun sequencing by some heuristic. If sequence assembly did a perfect job, we would expect that these contigs would be full chromosomes. Instead, what we observe is lots of sequence fragments with uncertain relationships to one another. In this common case, we think that some of the contigs could be stitched together ("localized", "anchored", "scaffolded") meaningfully into chromosomes, but we aren't sure how.

For de novo sequence assembly, there is no ground truth to compare to. So all of the information for generating assemblies comes from the starting sequences (which are usually "reads", small shreds of sequence that come off of a sequencing instrument). The heuristics that generate contigs from reads consist of finding overlaps between different starting reads and trying to extend them into the largest possible partially overlapping groups of reads, using some assumptions about rates of error in the sequence of the reads (and other variables). See wikipedia or this paper (figure inset) for a little more information on this.

It turns out that there is a body of statistical theory that governs how large these overlaps will be, and therefore how big/complete your contigs will be. This body of theory says that the size and number of contigs is predictable to some degree from the size of the genome you're trying to assemble, the length of the reads, and the number of reads you have.

Some genomes, like maize, wheat, or the human genome, are also harder to assemble because they are "repetitive". This means that there are lots of very similar sequences in different places in the genome. So when you take a read from one of these places, you are uncertain which one of these very similar regions it comes from. These repetitive regions are hard to resolve unless you have very long reads or some parallel information, so they also lead to gaps in sequence. Such regions will also tend to be "collapsed", meaning that you only have one contig representing a repeat that should actually be present as several contigs with different locations in the assembly.

Sources of parallel information that are helpful are proximity ligation (methods such as Hi-C), genetic maps from crosses, or optical mapping. These orthogonal sources of information express relationships between contigs in terms of their closeness on a chromosome. Here is a paper with more information on these topics. Recently, long read technologies such as PacBio or nanopore sequencing are starting to read through large repeats, but they are still usually not reliable enough to fully assemble even smallish genomes "telomere-to-telomere".

So, if there is a recipe for localizing/anchoring/scaffolding fragmented assemblies, here is roughly what can be done:

get more reads
get longer reads
get orthogonal information about contig placement (e.g. proximity ligation, genetic maps, a closely related assembly, etc.)

Hope that helps.


bioinformatics /genomics i am looking for likely truncation sites to prove recombination in sequences. i have 4 sequences. i believe one to be the "real sequence" and the other 3 to be recombinants caused by cleavage possibly due to Arg c proteinase. I know my sequences overlap due to multiple alignments i have performed using UniProt and i have chosen the enzyme due to carrying out cuts on Expasy cutter. If anyone could point me in the right direction this would be much appreciated.
many thanks in advance

The sequences you have posted seem to be (protein) amino acid sequences. The stop codon are present in DNA sequences and in mRNA sequences.

In DNA, the bases are A, G, C and T; stop codons are TAG, TGA and TAA.
In RNA, the bases are A, G, C and U; stop codons are UAG, UGA and UAA.
In DNA and RNA, other letters are used to specify degeneracy.

What you have here looks like protein sequences. So, there are no stop codons in sequences you have posted.


Do Ants have a sense of Direction? Do ants understand which way is up or down?

Could they differentiate between uphill and downhill?

Actually No.

Amazingly there is this paper published on the motions on Ants which says:

  The isotropic distribution of average speed appears as a surprising
  result since it would be expected, for instance, that ants progressing
  uphill should be slower than when moving downhill. For instance, Seidl
  et al. found lower speeds on steeper inclines in desert ants moving
  uphill, but indicate that desert ants progressing downhill displayed
  high velocities [42]. This is in contrast with our finding with Lasius
  niger in the present set-up where the velocity showed no dependency to
  the walking direction, even for the steepest inclination. However,
  Wohlgemuth et al. report, also in the desert ant, that speed was
  reduced in both their uphill and downhill channels (+540 ) compared to
  their flat channel, thereby excluding metabolic cost as a reliable
  means to gauge walked distance on various inclines [28]. In an attempt
  to determine the effects of inclination on the gross metabolic cost of
  locomotion in leaf-cutter ants, Holt & Askew report that ants
  travelled the fastest on a horizontal plane, and indeed moderated
  their speed with the inclination, both on the incline and the decline.
  They suggest that ants adapt their behavior so as to keep their
  metabolic rate constant despite changing mechanical demands.

Source: How Do Ants Make Sense of Gravity? A Boltzmann Walker Analysis of Lasius niger Trajectories on Various Inclines


What does "kcal/mol" mean when speaking of enzyme catalysis? After thinking about it, I'm confused by what the reaction barrier of an enzyme actually means.

Imagine a reactor containing enzyme and substrate.

If the enzyme in the reactor has a reaction barrier of 15 kcal/mol,

a) then when 1 mole of product has formed, that means 15 kcal have been consumed, independent of how much enzyme is present in the reactor.

b) then when 1 mole of enzyme is present in the reactor and 1 mole of product is formed, 15 kcal have been consumed.

Is it option a), b) or otherwise?

Let us imagine two companies A and B.
Both companies use very similar technical equipment to carry out a biotechnological process where a chemical reaction is catalyzed by an enzyme.
Company A uses an enzyme with a reaction barrier of, say, 15 kcal/mol, while company B uses an enzyme to catalyze the same reaction but this enzyme has an activation energy of only, say 12 kcal/mol.
For every Mole of product, company B saves 3 kcal worth of energy needed to drive the factory.

Does that make sense?

The reaction barrier (also termed activation energy) is the energy that is needed for the reaction to take place. An enzyme is "only" a catalysator which lowers the necessary energy (and/or makes the reaction possible under the conditions) but some energy to start a chemical reaction is still needed. See this image (from here):

To your questions: A and B are essentially the same - but the reaction time necessary with small amounts of enzyme is much longer than when 1 mole of enzyme is present. The amount of energy needed to catalyze the production of 1 mole of product stays the same.


Why does inbreeding cause genetic defects, but cell division in one's own body does not? I was watching a DNA transcription video when I realized that cells basically create copies of DNA all the time in our body. There may be a few mutations/errors, but it works out fine. However, when the haploid DNA in sperm combines with the one in the egg, there's so much extra work to be done to avoid errors. It's like if I write some software in one project and try to combine it the code I've written in another project, it's easier for me to do it because my coding style is similar and I know the code. But if I have to merge somebody else's code into my code, there would be a heck of a lot of merge conflicts and errors. Sure, I may learn better programming from the other person's efficient code, but the amount of bugs, testing etc. will be much more cumbersome.

Some research says:

  Malformations or harmful traits can stay within a population due to a
  high homozygosity rate, and this will cause a population to become
  fixed for certain traits, like having too many bones in an area, like
  the vertebral column of wolves on Isle Royale or having cranial
  abnormalities, such as in Northern elephant seals, where their cranial
  bone length in the lower mandibular tooth row has changed. Having a
  high homozygosity rate is problematic for a population because it will
  unmask recessive deleterious alleles generated by mutations, reduce
  heterozygote advantage, and it is detrimental to the survival of
  small, endangered animal populations. When deleterious recessive
  alleles are unmasked due to the increased homozygosity generated by
  inbreeding, this can cause inbreeding depression.

But bed bugs for instance, have managed with inbreeding without any problem (goddamned creatures!).

The question I'm asking is from the perspective of how the DNA combination and copying happens. Since the regions chosen during meiosis is random, shouldn't a similar DNA from sperm and egg resulted in a more stable genetic code since they are similar? I'm not looking for simplistic answers like "because Nature wanted diversity" or "because recessive alleles are unmasked".

I'm looking for a more fundamental explanation about the property of DNA, or the process of copying/merging these complex structures. Why does merging two similar things cause more problems than merging two dissimilar things?

I suspect your problem is grasping what is a deleterious recessive allele. Wikipedia and textbooks explain it much better but I will try to illustrate with respect to your question.

  I have to merge somebody else's code into my code, there would be a heck of a lot of merge conflicts and errors.

Problem with this analogy is that when merging code both variants are written by people. People tend to write code that works on its own. This is not the case for DNA since mutations are usually random and more often than not result in gibberish. Better analogy would be maybe combining information from two coppies of the same data to overcome bit rot.

  Since the regions chosen during meiosis is random, shouldn't a similar DNA from sperm and egg resulted in a more stable genetic code since they are similar?

Lets consider two made up genes A and B.

A is a dominant functional version of A gene involved in development of hand. In very abstract (code-like) way it could be read as: "If at the end of hand initiate 5 fingers"
a is a mutated nonfunctional version of A gene. In very abstract way it could be read as: "If at the end of hand initbzngers". It produces nonfunctional protein. In biological terms "a" is called deleterious recessive allele.
B is a dominant functional version of B gene involved in development of brain. In very abstract way it could be read as: "If in neuron keep junctions together"
b is a mutated nonfunctional version of B gene involved in development of brain. In very abstract way it could be read as: "If in geuron keep junctions together". It never produces the needed protein.

Now lets consider cross between two dissimilar individuals:

father AaBB X mother AABb

Following Mendel's laws they produce progeny:

AABB - has at least one functional copy A and B gene and thus develops fine.
aABB - has at least one functional copy A and B gene and thus develops fine.
AABb - has at least one functional copy A and B gene and thus develops fine.
aABb - has at least one functional copy A and B gene and thus develops fine.

now let's consider cross between two similar individuals:

father AaBB X mother AaBB

Following Mendel's laws they produce progeny:

AABB - has at least one functional copy A and B gene and thus develops fine.
AaBB - has at least one functional copy A and B gene and thus develops fine.
aABB - has at least one functional copy A and B gene and thus develops fine.
aaBB - fails to properly develop fingers.

  cells basically create copies of DNA all the time in our body. ... Why does inbreeding cause genetic defects, but cell division in one's own body does not?

During normal cell division AaBB cells should produce only AaBB copies which have at least one functional copy A and B gene and thus are fine.

Big picture

In a real population imagine every individual has tens of thousands of genes and each of them can be made nonfunctional by random mutation. The nonfunctional copy often does not have effect since the individual has another functional copy. When two non-related individuals procreate, chances are mutations they carry are in different genes and their progeny are fine as illustrated above. When related individuals procreate chances are thay both have the same deterious mutation(s) and not all their progeny will be fine.

  But bed bugs for instance, have managed with inbreeding without any problem (goddamned creatures!).

Species for which inbreeding is normal have much less recessive deleterious mutations prevalence in populations for simple reason. If new deleterious mutation appears the inbreeding leads in two generations to aa homozygots that die or fail to procreate and the "bad" mutations are selected out fairly fast. Inbreeding is normal state for some species. Today inbreeding-resistant species are descendants of individuals who have survived many generations of inbreeding.


If a person is infected with an RNA virus what percentage of the RNA in the blood of the person contains RNA of the virus? Karius uses DNA sequencing of everything that's contained in a sample to detect all bacteria and DNA-viruses in the sample. Given the way that costs of sequencing are falling this approach seems to be the future of detecting bacteria based infections.

It would be great if the same approach would also work for RNA-based viruses. For it to work it would of course be necessary that there's enough RNA of the virus in comparison to the other RNA.

How much virus RNA is there in a person who's infected by an RNA virus in comparison to the other RNA?

I think your question is:

  Can you diagnose someone with an RNA virus by looking for that RNA in their blood?

The use of nucleic acid tests, or NATs in diagnosis has been around for a long time. The specific for profit company you mention is not the first to use them. Almost all NATs work by first amplifying the genetic material with PCR or other methods, so there does not need to be a large proportion of pathogen RNA vs total RNA in a sample in order to use a NAT.

NATs, rather than culture or antigen/antibody based tests, provide the definitive diagnosis for many viruses, RNA viruses included. As the CDC describes, NATs (among other tests) are also used to screen donated blood for RNA viruses (HCV, HIV, and West Nile).

Incidentally, the for profit company you mentioned does NOT detect all bacteria and DNA-viruses in the sample as you said. It screens for a large number of specific pathogens in their

  proprietary micro-organism reference database


Has the age at which menopause occurs changed throughout history? I was reading recently that the age of menarche has decreased in the last 150 years, and was wondering if the age of menopause in humans has also changed recently?

Would there be selective pressure for it to increase currently, given that the average age of women having their first child is increasing in the West anyway?

Quick answer: Yes, but not in the last 150 years.

There seems to be no clear link between age at menarche and age at menopause (taken from [1]):

  While earlier studies were able to establish an association between
  early age of menarche and later menopause (Frisch 1978; 1987), more
  modern studies have not been able to confirm this effect (Whelan et
  al., 1990; van Noord et al., 1997).

  Aristotle's assessment was similar to those of Hippocrates and also
  Roman authors, so it seems that 2000 years ago most women entered the
  menopause in their early 40s. Mediaeval authors, however, gave the 50s
  as the age when menses ceased-much closer to the timing for twentieth
  century women.

Jean Ginsburg in [2] states (emphasis mine):

  In the past 100 years data from schoolchildren have shown a steady
  fall in the age at menarche in industrialised communities. Has
  there been a corresponding change in the age at the menopause?
  Unfortunately, reported surveys of the menopause have suffered from
  methodological defects. [...]

  Nevertheless, those studies least subject to bias show a striking
  agreement that the median age at the menopause is currently around 50
  in Western industrialised societies. In Britain it is 50.78, in the
  United States 49.8 and in white South Africans 48.7 with little
  apparent change over the past century. In non-European women, however,
  the menopause seems to occur earlier-in South Africa and the United
  States black women have an earlier menopause than white women.

So, while early menarche is, apparently, irrelevant, age of onset of menopause has increased since antiquity but has remained relatively stable since the middle ages. Therefore, there have been no significant changes in the age of onset of menopause in the time frame you defined (150 years).

Finally, Bengtsson et al [3] state that:

  Our study has, thus, not supported the view that the menopausal age is
  rapidly changing.

C. Keck, Predictive Factors to Determine Age of Onset of Menopause, PAMJ
, 3, 2005
Ginsberg J. What determines the age at the menopause? BMJ. 1991 Jun
1;302:1288-9.
Calle Bengtsson, Olof Lindquist, Lasse Redvall, Is the menopausal age rapidly changing?, Maturitas, 1(3), February 1979, Pages 159-164


Why are monarch butterflies attracted to particular flowers but not others? I have a "Purple Emperor Butterfly Bush" (Buddleia davidii 'Purple Emperor') and sure enough it does attract butterflies.
I have seen monarch butterflies using it, which confuses me, because I thought that monarch butterflies only fed from milkweed.
What makes this type of bush a substitute for the milk weed, but not other flowers?

It's the Monarch caterpillars that only feed on milkweed. Adult Monarchs, like many butterflies, feed on the nectar from flowers. https://www.fs.fed.us/wildflowers/pollinators/Monarch_Butterfly/habitat/index.shtml


Why reference genome is a reference? I have heard that a reference genome such as humans is generated by randomly choosing samples from a group of donors. But why do we call the DNA sequence generated as a reference? Why should we believe those few samples can represent all humans, from which we need to align with?

The main reason is because the genetic differences between individuals of the same species are tiny. For the vast majority of studies, they can simply be ignored.

Differences between individuals are usually (not always, but mostly) differences in SNP genotypes. These are single nucleotide differences which, while they can have phenotypic effect, don't really affect the ability of sequences to align. Sequence alignment software is designed to be able to deal with such small differences. For example, consider these two random sequences:

>seq1
ACCTTGCATCGGATCGAATTCGCGTTAGCGATCG
>seq2
GCCTAGCATCGGACCGAATTCCCGTTAGCAATCG

If we align them, we will get:

seq1            ACCTTGCATCGGATCGAATTCGCGTTAGCGATCG
seq2            GCCTAGCATCGGACCGAATTCCCGTTAGCAATCG
                 *** ******** ******* ******* ****

As you can see, despite the small differences in sequence, the two can be aligned very well. The same is true when you look at real data. My haemoglobin gene, for example, will align perfectly well against both yours and the one in the reference genome. In fact, they will almost certainly be identical or, at best, have a couple of different residues.

So, when doing work that is not about studying specific polymorphisms, we need a representative genome. Anyone's will do, unless they have a particularly serious mutation such as a chromosomal translocation.


Could anyone please identify this Indian bug? Photographed by a friend recently in central India. next to Panna Tiger Reserve.

The species from the photo is almost definitely a Catamiarus brevipennis.

The bulged and striped abdomen
The non-striped legs
The unique pattern on the wings
The antenna thick at the beginning and becomes thinner towards the end.
The protonum also has a unique granular structure unique to Catamiarus brevipennis.

Source : India Biodiversity Portal


Do insects respond to the detection of dead insects? Are there insects that change their behavior upon detecting the nearby presence of other dead insects? If there are, can you provide an example?

Yes, it is a common behaviour and is called necromone signaling (Yao et al 2009, see references in paper for many examples), and is probably used to avoid predators, parasites and disease. The chemicals used are often similar (unsaturated fatty acids), and seem to have an old evolutionary history (~400 million years). Many groups of species can also detect infected, not yet dead, conspecifics. Removal of dead individual is also common in e.g. ants (necrophoric behavior).

The paper referred to earlier (beside reviewing earlier evidence) also provides experiments of detection/avoidence in isopods and Tent
caterpillars (Malacosoma americanum), where they show avoidance based on crushed conspecifics, unsaturated fatty acids and (for isopods) intact corpses.

Naturally, the same type of compounds are used by e.g. species of carrion beetles (Silphidae) to find their animal hosts, but then for the purpose of reproduction.


What is the rest state for eyelids - Open or Closed? If one were to not apply any efforts on the eyelid muscles, will they remain open or closed?

In movies when we see a person die, either case could happen - their eyelids could be open or closed when they pass away. (Not sure if that's the case in real life, as I have been fortunate enough to not witness any deaths).

I started thinking about this when I got into meditation. During meditation one is supposed to relax all their body muscles. I wonder, if I were to reach that perfect stage of relaxing what will happen to my eyelids. Will they automatically open? I feel like I've to make tiny yet finite deliberate effort to keep them closed. Not sure if that's the case with everyone.

This depends to some extent on how you define "resting state" (it matters).

Innervation of the eye occurs in the brainstem and upper spinal column, so is, like most brainstem functions, on autopilot (like breathing.)

If you define resting state as that which the lids would assume without any innervation, then the resting state of the eyelids is semi-open. This is the state of the eyelids of most people who die.

However, that position is not beneficial to the living eye, as it would lead to corneal breakdown. When people lose eyelid innervation, for example, following a stroke, the lids don't close completely. Ointment must be applied several times daily and the eye is often taped in the shut position to protect the cornea.

If you define resting state as that which occurs in sleep and in most comatose states, the eyes close completely, because innervation of eye muscles is intact and a main function is to protect the cornea, i.e. vision. This is done with a completely closed eye.

Comprehensive Review in Clinical Neurology, Cheng-Ching et al.


How can I compare rates of evolution for two sets of proteins? I have a list of candidate proteins as the result of my analysis. I am now trying to find various characteristics that they have in common. One of the things I would like to check is if my candidates are evolving faster or slower than the rest of the proteins in my dataset.

Now, I know how to do this manually by building multi species alignments for each of my proteins and calculating ka/ks ratios for each set of alignments. This, however, is not a trivial process and I really do not want to do this manually for my ~1500 candidates.

Can anyone suggest a tool that will take two lists of proteins and return an estimate of evolutionary rate for each one?

I am primarily interested in human but also mouse, yeast, fly and worm. Ideally, I would need a tool that can take a list of proteins, assign them to an orthologous group and return a value representing the rate of evolution for that group.

If protein alignments are sufficient for you, I suggest that you look at the eggNOG database. There you can download mappings from proteins to protein families, and for the families you can also download pre-computed multiple (protein) sequence alignments.

I guess depending on the type of analysis you want to do you would have to trim the alignments to get only homologous regions (for example, see this recent paper[1]).

Wu M, Chatterji S, Eisen JA. 2012. Accounting For Alignment Uncertainty in Phylogenomics. PLoS ONE 7(1): e30288, doi:10.1371/journal.pone.0030288.


Why do we need deep sequencing? Why do we need deep sequencing? Why cannot the sequencing technologies read all the nucleotides correctly at the first read? Sorry since this question is too trivial, I don't have a biological background at all, and I have just started doing research in CompBio. Thanks.

Short Answer

In a nutshell, DNA sequencing technology has a limit to how long a stretch of DNA it can read in one go.

Long Answer

So what most commonly occurs is the length of DNA you wish to sequence needs to be (almost randomly) chopped up into given lengths (depending on the technology) and each length or read is sequenced in parallel. But now you don't know which lengths to stick together! i.e. the ordering of these chopped up lengths. So you sequence it many times over (deeper) and this way you can align contiguous ends of these lengths together like a jigsaw puzzle. The more times you sequence the more accurately the 'contigs' will be aligned.

DNA Assembly Diagram

Comment if you want more details, but the technical term you want to google is "sequencing assembly".

Here's the wiki

:)


How do insects breathe? Do ants even breathe? If they don't, how do they stay alive? On what resources do they depend upon to stay alive? How are they different form mammals?

The main difference between tracheal gas exchange, and other forms of gas exchange (except simple diffusion) is that it is generally a passive process. Organisms with lungs, gills, or other modified respiratory organs can actively pump the oxygen-containing medium (usually air or water) across their respiratory surface, and some also pump their blood across in the opposite direction to cause a countercurrent exchange to enable maximum efficiency of oxygen/CO₂ transfer.

The tracheal system is a more efficient mode of gas exchange than diffusion since it does not only involve the oxygen passing over the organism's body surface (a semi-permeable membrane) which limits the rate of movement. Instead the epidermis is invaginated to form tracheae (tubes) through which air can travel passively. The tracheal system is highly branched and terminates at tracheoles (fluid-filled sacs) which closely line respiring tissues to provide oxygen and allow release of CO₂.

Tracheal respiration limits the size of insects since their oxygen demands will not be able to be met if the air has to diffuse very far. Some insects require more oxygen than others: many larger insects and more active insects have evolved to supplement the tracheal system with pumps, gas gills (permanent or temporary bubbles of air which aquatic insects carry), or mechanically ventilated air sacs (honeybees have these, see Gullan & Cranston, 2005; and Snodgrass, 1956).

Furthermore, tracheal systems can be 'open', 'closed', or the insect can engage in discontinuous gas exchange. Insects with open tracheal systems have spiracles (holes in their cuticle). Closed tracheal systems are more common in aquatic insects, they come in two major designs: highly branched systems over the internal surface, allowing cutaneous gas exchange; and filamentous or lamellate  arrangements, which are analogous to a primitive gill (see Wigglesworth, 1964 or Gullan & Cranston, 2005 chapter 10 for more on aquatic insect adaptations). Discontinuous gas exchange involves co-ordinated opening and closing of different spiracles which results in a uni-directional current allowing more effective ventilation.

References

Gullan, P.J. & Cranston, P.S. (2010) The Insects: An Outline of Entomology. John Wiley & Sons.
Snodgrass, R. (1956) Anatomy of the honey bee, Comstock Publ. Assoc. Ithaca, New York,.
Wigglesworth, S.V.B. (1968) The Life of Insects. New American Library.


How do B and T cells work incorrectly in a person with Systemic Lupus Erythematosus? Systemic lupus erythematosus is an autoimmune disease in which the body's immune system attacks healthy cells. How exactly do B and T cells attack these cells they mistake for pathogens?

The initial trigger for the disease is unknown and can be different from person to person. However, we do know that there can be environmental or infectious triggers that are further potentiated by genetic and hormonal factors.

The pathology of SLE is associated with the development of "auto-antibodies" or "anti-nuclear antibodies," so saying that B cells and T cells attack healthy cells is not exactly correct - More accurately they produce antibodies against proteins on healthy cells, which form immune complexes, activate complement and induce apoptosis.  To produce auto-antibodies, events occur as follows:

The trigger causes macrophages or antigen-presenting cells (APCs) to display self- or auto-antigens
APCs recruit B cells to start producing antibodies against the antigen
APCs activate T helper cells, which stimulate inflammation and perpetually activate the B cells to produce auto-antibodies

The following immune abnormalities are associated with SLE (particular focus on B cells and T cells)

High levels of circulating B cells
Decreased levels of T suppressor cells, which would otherwise regulate the immune system and auto-antibody production
Abnormal B cell signalling and persistent activation of B cells (IL-6, IL-10)
Prolonged life span of B cells, possibly due to poor immunoregulation (#2)

Reference:
Schur PH, Hahn BH, Pisetsky DS, Ramirez Curtis M. Epidemiology and pathogenesis of systemic lupus erythematosus. Up to date. Topic last updated: Feb 5 2016. Subscription access only.


Can we make a rough estimate of the number of generations since the origin of life? According to what we've learnt :

we can approximate the number of generations since the first human pretty much like us (depending what / who we talk about).
we have an idea of the series of life forms we come from.

So is it possible to give it a very rough number ? Or it's not, because of some issues - but which ones ? (I only think about the many, short generations of the first forms, which moreover we don't really know about, as a limit to counting)

What if we stop counting at "unicellular" (or else) ?

If you're willing to accept many orders of magnitude and define life as the Last Universal Common Ancestor.

For the rest of this answer, life begins 3.5 Gya with cyanobacterial mats and stromatolites and so on. Genetically the LUCA is dated to around this time, which matches the fossil record and everything's great. The LUCA can't have sprung from nothingness, so there may(will) have been (many)generations before the LUCA of things we would recognize as life, but I'm ignoring them. If they wanted to be considered they should have left descendants.

The fastest doubling times for modern bacteria are about 7-9 minutes but most are longer. E. coli takes about 20 minutes, and yeast takes hours. Given the 3.5 billion year clock, that gives an upper bound of about 1x10^14 generations. (Green sea turtles take 20-30 years to reach sexual maturity, or 1.1x10^9 generations). Something a bit representative is probably Pelagobacter ubique, which is vastly successful and takes about 29 hours to divide. Averaging out ice ages and so on and skipping the slowing of generations multicellularity probably implies(the Cambrian explosion is 82% of the way to the present day, being only 543 million years ago. We could account for it, but our guesses on generation time are way more inaccurate than any possible effect that could have) would estimate about 1x10^12 generations.


Assay for Beta-galactosidase activity in single cell microscopy I'd like to be able to measure the activity of $\beta$-galactosidase in living cells with simple optical (maybe fluorescence) microscopy. Ideally I'd like to do a minimum of genetic engineering, and use this assay with strains I already have (that have a WT lactose system), i.e. a fluorescent lactose-mimic would be ideal. Additionally, it would be nice if the lifetime of the fluorescent byproduct of $\beta$-gal activity was short, so I could detect a decrease in $\beta$-gal activity as well as an increase. Does such a fluorescent analog exist? I'm hoping to look at the switch from lactose to glucose utilization under the microscope, so I want lactose-using cells to light up and glucose-using cells to be dark, or vice versa. It does not have to be fully quantitative--a qualitative sense is fine.

I found this paper.

Zhang GJ et al. (2009) In vivo optical imaging of LacZ expression using lacZ transgenic mice. Assay Drug Dev Technol.7:391-9. doi: 10.1089/adt.2009.0195.
Abstract
beta-Galactosidase (beta-gal) (encoded by the lacZ gene) has been widely used as a transgene reporter enzyme. The ability to image lacZ expression in living transgenic animals would further extend the use of this reporter. It has been reported that 7-hydroxy-9H-(1,3-dichloro-9,9-dimethylacridin-2-one)-beta-d-galactopyranoside (DDAOG), a conjugate of beta-galactose and 7-hydroxy-9H-(1,3-dichloro-9,9-dimethylacridin-2-one), is not only a chromogenic lacZ substrate but that the cleavage product has far-red fluorescence properties detectable by in vivo imaging. In an attempt to noninvasively image lacZ expression in vivo, we applied fluorescence imaging to a G protein-coupled receptor (GPR56), knockout (KO) mouse model, in which the lacZ gene is introduced in the GPR56 locus. Compared to wild-type (WT) mice, GPR56KO/LacZ mice showed three- to fourfold higher fluorescence intensity in the head area 5 min after tail-vein injection of DDAOG. beta-Gal staining in sections of whole brain showed strong lacZ expression in homozygotes, but not in WT mice, consistent with lacZ activity detected by in vivo imaging. The kidneys were also visualized with fluorescence imaging both in vivo and ex vivo, consistent with beta-gal staining findings. Our results demonstrate that fluorescence imaging can be used for in vivo real-time detection of lacZ activity by fluorescence imaging in lacZ transgenic mice. Thus, this technology can potentially be used to noninvasively image changes of certain endogenous molecules and/or molecular pathways in transgenic animals.

The work in the paper is cited in a more recent paper which reports beta-gal-based chemiluminescent imaging in mice.
It's unclear if any of this would be successful at a single bacterial cell level.


What vegetation would thrive in the Martian atmosphere? Most plants require carbon dioxide for their photosynthesis, which Mars has in overabundance.

Would atmosphere composition (let's ignore temperatures for the purpose of this question) of Mars allow vegetation to grow?

I'll stick to considering the atmospheric composition, as referred to in the original question: Although there may be some rare exceptions that I can't recall, under normal circumstances all green plants use aerobic respiration with O2 as final electron acceptor for energy production. This means that they require oxygen, which is essentially absent from the Martian atmosphere (0.13%). Even though our hypothetical Martian crop could produce oxygen as a byproduct of photosynthesis, that oxygen would be lost into the atmosphere, and would not be available for respiration.

I believe that under waterlogged conditions some plants can switch temporarily to some sort of anaerobic metabolism as a stress response, but I don't know if this is just to survive or whether the plants can grow in this way - I suspect it is the former.


What does it mean to have square brackets around a genus name? For example [Eubacterium] rectale

The NCBI Taxonomy staff places square brackets around the genus for some species (examples: [Bacillus] aminovorans, [Candida] auris) to indicate that they are misclassified*, meaning placed incorrectly in a higher taxonomic rank.

References:

https://support.nlm.nih.gov/knowledgebase/article/KA-03379/en-us


Why half of the protein is saturated when [L] =Kd let's suppose the following reaction:

At equilibrium we can calculate the Kd (Dissociation constant) using the following formula:
Kd = [P][L] / [PL]  or kd / ka
We can then use the Hill equation to calculate the fraction of binding sites which are occupied:
occupied binding sites = [L] / [L] + Kd

  When [L] euals Kd, half of the ligand binding sites are occupied (Lehninger principles of biochemistry)

Why is this true? This would mean that at equilibrium half of the binding sites are occupied?

The Hill equation in that link uses the simplifying assumption that all ligands bind simultaneously and that the binding sites are identical. The reaction is then P + nL = PL,
and Kd = ( [P][L]^n )/[PL]
Then by rearranging you get the expression in the link.

The equation "fraction occupied binding sites = [L] / [L] + Kd" Is not the Hill equation. It is called the binding isotherm. You can see that if Kd = [L] then the fraction of occupied binding sites (let's call it theta) = 1/2. Thus half of the binding sites are occupied.


Why do most mammals have long snouts? It seems like most mammals, e.g. dogs, have long snouts. My pet dog's snout would seem to me like an evolutionary disadvantage, since her canine teeth are way out at the end of her jaw, which acts as a force-reducing lever. I suppose the lever does increase the jaws' range of motion and possibly allow the jaw to snap shut more quickly. For an herbivore such as a horse, I don't see any advantage to the long snout. It doesn't need to snap its jaws shut rapidly, and it doesn't need to wrap its mouth around anything very large.

Is there a mechanical reason for the long snout, or is the evolutionary advantage due to some other factor such making the nose have enough surface area to give a sensitive sense of smell?

Obviously there is an evolutionary advantage for those animals which has a long snout/muzzle. That is why they are still around.

For carnivores the canine is the most important tooth and it is positioned strategically at the front corners of the jaw. Canines are meant to pierce and is essential for holding on to the prey and preventing from escaping. They are also essential for tearing flesh.

Lower jaw or the mandible is a class 3 lever. The lesser mechanical advantage is compensated by the extremely powerful muscles. Since the muscles are closer to the joint or fulcrum the movement produced by the muscles are amplified at the outer end of the jaw allowing for wider opening of the mouth. Since the canines are sharp and long there is enough force to pierce.

Herbivores like cattle and sheep have no canines (horses do have canines). The longer snout/muzzle may help in grazing as it would help in reaching the ground along with longer necks. The longer snout/muzzle means more space for the premolars and molars which can be more in number or larger fro grinding the food.

Crocodiles which are not mammals also have long snouts.

In short the longer snout/muzzle in different animals developed due to evolutionary advantage based mainly on diet.


Do men have a higher genetic variance than women? I've heard that with the  distribution of our genome women have less variation on the bell curve than men.

Is there any basis for this? It was my understanding that women have more genetic variation than men due to having two X chromosomes and there being more variation on gene expression within the X chromosomes.

I've also seen a theory that with traits linked to genes on the X-chromosome in women being averaged across the genetic variants found on each of a woman's two X-chromosomes, this would reduce the likelihood of extreme traits (men have just one X-chromosome, precluding this averaging process).

Is there any biological possibility for men to have more genetic variation than women, and if so what would be a potential reason for it?

This question is very interesting and I would love to have a reference to an article that provides such evidence.

Decomposing your question:

Is it true that there is more genetic variance among males than among females (in humans I guess)
If the answer to (1) is yes then: Why is it so?

I am trying to address these two points below

1. Is it true that there is more genetic variance among males than among females ?

There are different ways of understanding your question 1. Do you want to talk about…

Allele richness
Heterozygosity
Polymorphism
Part of the genetic variance in phenotypic variance (heritability). I don't think it is what you meant though!

Therefore, the question is slightly unclear and I don't know of any paper who address any of these questions anyway. So... I don't know!

2. Assuming (1) is true, then Why is it so?

There are many possible explanations for such observation (assuming this pattern has been observed). Below I give some hypothesis I can think of.

There might have a higher selection (survival differential) among females than males. In a consequence, genetic variance among young females is higher than among older females. In total, genetic variance among females would be lower to that of males.
There might have a very high variance on the Y-chromosom but not on the X-chromosom. This might for example be a consequence of the arrest of recombination that occur on the Y-chromosom. As a consequence of this arrest of recombination, selection hardly purge deleterious mutations (see Muller's Ratchet). See Shigeta's answer for a more detailed overview of this point. See shigeta's answer for more information.
Males might migrate more. If one look at the sex-specific genetic variance in a population (and not on the world-wide metapopulation), this variance might be greater for the sex that migrate more because different genetic background might be brought from other neighbor populations.
Higher selection within mitochondria in females very early in life (in the egg for example) resulting in a decreased mitochondrial genetic variance in females. This is maybe a bit far-fetched.
There might have other hypotheses for species for which sex of an individual is not determined by sex-chromosomes. (see Sex Determination System)
Depending on what you mean in your question, I guess we might find many other hypotheses when thinking of migration, different fitness landscape (different optimum), different selection intensity.
We might as well think of genetic variance of gender-specific gametes (especially for haplon-diplontic species for example)
This evidence (assuming it has been observed) was a False Positive!

Note:
@terdon provided a very good explanation (which was deleted) of why males might cause most of the genetic diversity but as @terdon and I discussed (in the comments that were also deleted) this is not an explanation for greater diversity among males. The reason is that the variation is created via mutation in the testis and the ovary. The fact that most mutations happen in males does not influence the sex-specific diversity because males sire as many male offsprings than female offsprings (so do females!).


Do memories have mass? If it were possible to live forever, would our brains grow infinitely with the number of memories that we store? Or would we remove old memories as we create new ones?

You would need to live a long, long, long, long time for this to become remotely problematic.

Your question seems to suppose that a memory is "stored" by a neuron, and since neurons have mass, then the more memories we have the more our brains will weigh. Actually, neurogenesis is pretty rare in the adult brain--most of the cortex is fixed, and new neurons do not grow. (The hippocampus is the best known counterexample, but it's important to note that contrary to lore, the hippocampus doesn't store memories per sé, though it is involved in the formation and retrieval of memories).

Memories are represented in the brain as patterns of firing neurons. Let's say, for simplicity, that each neuron can either be on or off. Since there are 86 billion neurons in the brain, we can experience 2^86bn possible brain states. That's a lot.

Of course there are a lot of simplifications here--most notably, there is a lot of structure to the brain, and so i'm not suggesting you can store 2^86bn memories--but the logic is the same. Even with only 1,000 neurons, we can store a ridiculous amount of information (2^1000).

I would like to comment on MCM's answer as well, because I don't think it's true that we "remove" old memories. Or rather, the topic is still being debated in cognitive science today. For an old take on it, see renowned memory researcher Endel Tulving's (1974) article, in which he says:

  When we forget something we once knew, it does not necessarily mean that the memory trace has been lost; it may only be inaccessible

The idea is that some memories are suppressed (no, not repressed), being rendered inaccessible. Robert Bjork and John Anderson have (separately) done some nice work in this area.

So before you worry about this becoming a problem, I suspect you need to work out the secret of immortality first.

  Tulving, E. (1974). Cue-Dependent Forgetting: When we forget something
  we once knew, it does not necessarily mean that the memory trace has
  been lost; it may only be inaccessible. American Scientist, 74-82.


What causes tree lines? There is an area of where there is a distinct line of only trees on one side and only shrubs on the other (right next to each other). What could cause this?

My attempt: I said there could be a difference in sunlight, but I'm not sure.

There are a bunch of possible answers;

On my own property I have such a line.  Turned out it was an old fence line.  One side was farmed intensely for 90 years, the other side left in bush.  The farmed soil is enough different that it doesn't grow good trees.  Even the grass is different.
Another place I have an abrupt line of willows.  That one turns out to be water level from the local creek.
A third one has an abrubt chaange in types of grass.  That one is caused by a clay seam coming to the surface.  Uphill the surface soil is sandy.  Water hits the clay, and moves downhill, coming out at the grass line.
I've seen another one, in the mountains, that I think is due to cold air drainage.  The valley floor and 20 feet up the sides are bush.  I think the cold air settles and kills young trees.


Plant dependence on CO₂ levels I was wondering which kind of plants would survive longest without CO2 : plants with fatty, thick leaves or plants with thinner, less fatty leaves?
And can we conclude that the plant species that are more dependent on CO2 levels, would benefit from the greenhouse effect?

Plants do not need CO2 for survival. They need it just for photosynthesis; if you supply them with alternate carbon source such as glucose then they would survive (See here for non-CO2 Carbon-source utilization). There are non-photosynthetic plants which are totally dependent on carbon sources other than CO2; some are carnivorous like venus fly-trap.

I am not sure what you intend when you correlate leaf thickness to CO2-dependence. Leaf morphology can affect photosynthesis rates but afaik there is no relationship between leaf morphology and CO2-dependence.

  can we conclude that the plant species that are more dependent on
  CO2 levels, would benefit from the greenhouse effect

Greenhouse effect is not equivalent to increase in CO2; increased CO2 levels can cause greenhouse effect which is a physical phenomenon of entrapment of IR radiation.

CO2 is fixed by an enzyme called Rubisco; like most enzyme catalyzed reactions this will reach a saturation limit i.e. addition of more CO2 will not increase the rate of photosynthesis. However the rate of photosynthesis is limited at the Rubisco step because of low levels of CO2 (See here) and it can be expected that most photosynthetic plants will be benefited by increase in CO2. However, not all plants would be resistant to increased temperatures and moreover the rate of enzyme catalysis would also change with temperature. So it is not that easy to predict.


How do you design a drug to be delivered to the CNS? I have just started reading up on structure-based methods for drug design (this is completely not my field so apologies for stupid questions that will be coming along!)

Clearly, some drugs are designed to target the central nervous system. However, I understand that the extracellular fluid of the central nervous system is separated from the blood by the "blood-brain barrier" which restricts the passage of large molecules between the two systems.

My question is : how do you design a drug to be delivered to the CNS?

In a nutshell: in order to pass through the blood-brain barrier (BBB) the substance has to mimick soee properties of the substances that are allowed to pass through.

There are different types of "transporters" -- integral proteins going through the cell membranes and accounting for the active transport of the substances they can actively bind to. Smaller molecules of drugs can use solute carrier transporter (SLC), whereas bigger molecules (oligo- and polymeres) would use the receptor-mediated transporter (RMT).

There is a nice article on this topic published by ScienceDaily.

Here is the quote:

  One technology for enabling active transport of small molecule drugs
  across the BBB involves targeting endogenous nutrient transporters.
  These transporters are members of the solute carrier (SLC) transporter
  superfamily. Transport of small molecules across the BBB by these
  membrane proteins is known as carrier-mediated transport (CMT).

  In order to design drugs that utilize CMT to cross the BBB,
  researchers modify their chemical structures so that they resemble
  nutrients that are transported across the BBB by specific SLCs. The
  prototypical drug that uses this strategy (which was developed long
  before mechanisms of CMT were known) is L-DOPA, the major current drug
  for Parkinson's disease. L-DOPA is used to replace dopamine that is
  lost due to degeneration of dopaminergic neurons in the substantia
  nigra of the brain.

  Another major system that is used in normal mammalian physiology to
  enable needed molecules to cross the BBB is receptor-mediated
  transport (RMT). The brain uses RMT to transport proteins, peptides,
  and lipoproteins that are needed for brain function across the BBB.
  Examples of biomolecules that are transported into the brain via RMT
  include insulin, insulin-like growth factor (IGF), leptin,
  transferrin, and low-density lipoprotein (LDL).

  In RMT, molecules in the circulation may bind to specific receptors on
  the luminal surface of brain capillaries (i.e., the surface that
  interfaces with the bloodstream). Upon binding, the receptor-ligand
  complex is internalized into the endothelial cell by a process called
  receptor-mediated endocytosis. The ligand may then be transported
  across the abluminal membrane of the endothelial cell (i.e., the
  membrane that interfaces with brain tissue) into the brain. This whole
  process is called receptor-mediated transcytosis.


Could super-caffeinating somebody's bloodstream be dangerous? I'm currently planning out an RPG based on Misfits. Basically young offenders get super powers. I want one of the villains to have a really lame power that they use to become incredibly dangerous. I thought about using a power to caffeinate drinks. If someone used that to super-caffeinate somebody's bloodstream, could that hurt or kill somebody? Or would it not cause any real damage?

In extreme doses, caffeine can - like almost any substance - cause death. Wikipedia has this to say on the subject:

  Extreme overdose can result in death.[59][60] The median lethal dose
  (LD50) given orally is 192 milligrams per kilogram in rats. The LD50
  of caffeine in humans is dependent on individual sensitivity, but is
  estimated to be about 150 to 200 milligrams per kilogram of body mass
  or roughly 80 to 100 cups of coffee for an average adult.[61] Though
  achieving lethal dose of caffeine would be difficult with regular
  coffee, it is easier to reach high doses with caffeine pills, and the
  lethal dose can be lower in individuals whose ability to metabolize
  caffeine is impaired.

You may wish to consult the references mentioned in the Wikipedia article for further details (As we all know, one should not trust Wikipedia too much). Note that caffeine administrated directly to the bloodstream will be more dangerous than the same amounted ingested.

Information on caffeine toxicity can also be found at Medscape. I you need concrete examples, Holmgreen, Norden-Petterson and Ahlner have published case reports on four recent cases of coffeine-related fatalities. (3)

To cover all bases, it should be said that none of the information mentioned should be used to estimate a safe level of caffeine intake.


Western blotting with multiple antibodies Normally I wash/detect with one primary/secondary-HRP antibody pair, strip, then wash/detect with the other primary/secondary-HRP pair which works well. However, I recently started working with a HRP-conjugated primary antibody for my protein of interest and wondered if I might add this together with the secondary antibody for my loading control to save the stripping and second washing.

Are there any general guidelines for Western blotting with multiple antibodies at the same time, i.e. changing antibody dilution?

An obvious first step is to make sure the HRP-conjugated primary isn't from the animal recognized by the secondary. I anticipate blotting with mouse HRP-conjugated anti-GFP and a secondary rabbit anti-mouse would not be a very good decision.

What you can do depends on your proteins: If both proteins (your target protein and the loading control) are seperated far enough, you can detect both of them in the same step by adding both primary antibodies and both secondary ABs into the buffer at the same time. They will bind only to their specific epitope and you will get nice signals. This is something I have done several time. This avoids the stripping process (which can be tricky sometimes) and you have both signals on the same film. Additionally you save chemicals, film and time.

There is another way with which you can come around the stripping: Do you first primary/secondary antibody combination and then incubate the blot with a buffer containing sodium azide. This inhibits the enzyme irreversibly, you have to make to wash very carefully afterwards. Then you can proceed with the second antibody combination.

If you want work with a marked primary antibody (which is unusual, but will of course work) and your loading control at the same time, I would definitely make sure that the secondary antibody with the HRP is not binding to your marked primary, otherwise the signal might get very strong (from the primary and also from the bound secondary), but I don't think it would cause other problems.


How do we see and/or detect neurons? I'm curious as to how we "see" neurons, for lack of a better term. Is it the detection of the neuro-transmitters? Can we literally see the electricity firing and moving throughout the pathways? Is it a combination of both, or something completely different, like scanners?

What kind of technology is used to do these things?

thank you!

Currently, the big thing in Neuroscience is imaging in vivo Calcium release which correlates with neuron action potentials, seen here. Each white speck is a neuron, the black lines and circles are blood vessels. Using this method you can visualize distribution and activity of neurons in real time.


Is it theoretically possible to create two humans by splitting one human in two? There have been cases where a person has had one of their brain hemispheres removed, and they ended up living a fairly normal life. Could it be possible to split a normal person down the middle and create two people, each with a brain hemisphere? Machines could be used to replace organs that can't be split, like the heart.

I'm assuming there would exist some very advanced technology to prevent excessive blood loss and other problems with splitting a person down the middle.

If you split a human early enough (in the first weeks after fertilization), you can get monozygotic twins.

Other than that, you are in the field of science fiction and we cannot safely answer such question on a science website. I am not sure your question will be accepted in its current format but you may try WorldBuilding.SE.

And if you like fantasy novels, I recommend The Cloven Viscount by Italo Calving! You will definitely not learn much about biology in this book though.


Are mitochondria transferable between cell types, individuals and species? I'm curious about what happens when you insert organelles from a cell into another. In particular, mitochondria.

Take two cells from your own body. Somehow extract a mitochondria from one cell and somehow insert it in the other cell.

Will the cell with the foreign mitochondria make use of it (respiration), or will it dispose it?

What if the foreign mitochondria comes from someone else's body?

What if the foreign mitochondria comes from another species' cell?

There is evidence that cells can exchange mitochondria. There are some donor cells that transfer mitochondria to recipient cells via cytoplasmic nanotubes (within the same species). This happens endogenously and triggering factors may include stress.

References:

Pasquier et al. 2013
Ahmad et al. 2014
Wang and Gerdes. 2015
Hayakawa et al. 2016

On interspecies mitochondria transfer.

In a study by Yang and Koob, the feasibility of mitochondrial transplants was studied. Mitochondria isolated from donor cells were initially injected into mouse oocytes/embryos. Then mitochondria, along with a chunk of cytoplasm and membrane was taken out; these cell-like structures were called  mitocytoplasts. Then, these mitocytoplasts were fused with recipient cells (mouse rho0 cells - these lack mitochondria) with the help of a viral fusion protein.

They found that the recipient cells supported mitochondria from the same species (donor species include mouse, rat, Mongolian gerbils and Golden Syrian hamsters).

The success of the "mitochondrial xenograft" depends on how different the species are and as shown in the abovementioned experiment, a donor cell (mouse) would not support the mitochondria from even a closely related species (rat). This incompatibility would primarily be based on the dependency of mitochondria on the nuclear genome which may be different for different species. It is possible that "mitochondrial xenografts" may be accepted; the impossibility of it has not been exhaustively verified.


What do the acronyms in C.elegans neuron names stand for? In this site, I see a variety of acronymic names for C.elegans neurons but what do these names mean (for example AVAL, AVAR)?

Unfortunately, there doesn't seem to be a very systematic nomenclature. Some of the letters are acronyms while others describe a class of neurons. The letters V and D usually describe the ventral and dorsal counterpart of a pair of neurons. The same goes for L and R (left and right).

This list names all C. elegans neurons and you can see that, for example, the "ring interneurons" or motor neurons start with RI or RM. "Inner labial" or "outer labial" neurons are called IL or OL. Ventral cord motor neurons start with a V and their different classes are called VA, VB, VC and VD plus a number. The classes are determined by lineage origins or historic reasons ;) And there are a lot of exceptions to these rules, because their historic names remain even though we continue to learn more about these neurons.

The example AVAL/AVAR are ventral cord interneurons. They form a class with other ventral cord interneurons called AVB, AVD, AVE. So, the first two letters refer to the main class, the third letter to the subclass. The L or R refer to the left and right member of this pair.

Some friends working in C. elegans neuroscience told me that you basically just treat these letter codes as individual names for the neurons without bothering about their origin and meaning too much.


Relationship between turgor pressure and osmotic pressure? I would like to know if there is a relationship between osmotic pressure (inside and outside of a cell) and turgor pressure. If so, is there a way to formalize it mathematically?

Thank you in advance,
Eorn

Turgor Pressure(T.P) is defined as the amount of pressure inside a cell solely due to its water content, whereas Osmotic Pressure(Pi) is defined as the pressure required to stop osmotic flow between the cell and a pure solvent when the pressure exerted by water is zero.

Osmotic Pressure is often given as the negative of the Osmotic Potential(or Solute Potential) of the Cell.(Because more the solute, more pressure will be required to stop the osmosis, but against the gradient). (1)

Therefore, it can be easily seen that Osmotic Pressure is solely dependent on the solute concentration of the cell.

The Total Suction Pressure(S.P) of a Cell is the pressure required outside of a cell to stop the water flow in a pure solvent.

The T.P in such a situation would try to reduce the S.P (More the T.P, less would be the pressure on the outside). Whereas, the O.P in such a situation would try to increase the S.P (More the solute inside a cell, more would the water on the outside try to get on the inside)

Hence, Mathematically (considering no other pressures to be responsible for Total Suction Pressure)

S.P = Pi - T.P

This can Also be proved in the following way:

Water Potential(Psi W): Total Pressure inside a Cell.

Solute Potential/Osmotic Potential(Psi S): Reduction in Water Potential Magnitude due to addition of a Solute(solute reduces kinetic energy of water due to bonding)

Pressure Potential(Psi P): Hydrostatic Pressure, i.e, pressure exerted by the water present inside a cell if there were no solute particles.

By definition

Psi W = Psi S + Psi P

(We know, Psi S = -Pi) As written above in (1)

Psi W = -Pi + Psi P

(We know, Turgor Pressure is the same thing as Psi P)

Psi W = -Pi + T.P

Suction Pressure is the negative of Total Pressure inside a Cell

(S.P = -Psi W)

(Water flows from high water potential to low potential, but from low Suction Pressure to an area of High Suction Pressure)

Therefore

-S.P = -Pi + T.P

multiplying by -1

S.P = Pi - T.P


Linkage Disequilibrium - What does it mean when D < 0? What does it mean when you have a situation where your D<0?

Consider two bi-allelic loci, A and B with alleles A1, A2 for A and B1, B2 for B. Negative values for D means that A1 is more often associated with B2 than expected. Similarly, A2 is more often associated with B1 than expected.

More info on Wikiedpia > Linkage Disequilibrium or on any intro book to population genetics (see here for recommendations). If there is anything in particular you do not about the definition of LD, feel free to ask a question by highlighting what is unclear to you.