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How do we know the human species arose in Africa?
I have heard (from multiple sources) that the current scientific opinion is that the human species arose in Africa. What are the reasons for this opinion? If possible, simple and non-technical explanations (as far as possible) would be appreciated.

I think this is mainly based on the fossil record.

Wikipedia exists: https://en.wikipedia.org/wiki/Human_evolution

There are two big prongs of the out of Africa theory or whichever name you wish to call it.
Prong the first: fossil evidence. There are lots of different kinds of protohuman fossils. Homo erectus/ergaster are found all across Europe, Asia, and into Indonesia from about 1.5 million years or so until about 70 thousand years ago, where they stop showing up. Up until 125 thousand years ago anatomically modern humans were only found in Africa. About 70 thousand years ago they start showing up in the Middle East, and then they spread out roughly following these paths. The fossil record shows not-humans or almost-humans (Homo erectus mostly) for millions of years, then humans show up at a certain point and then there's loads of human fossils. This point gets more recent as you get further from East Africa.
Prong the second: genetic diversity. Starting with this paper (not sure if this is behind a paywall but the details are not important anyway) human mitochondrial DNA was compared using restriction enzyme mapping. This kind of mapping is super crude (roughly analogous to grinding pottery into a fine dust and grouping the dusts by color) and the original study was pretty limited by the computers available at the time. Nonetheless, they showed that the most genetically diverse geographical group was Africa, and furthermore that any two people from outside Africa are likely more closely related to each other than any two people inside Africa. Genetic diversity goes down the further away from East Africa you get, matching what you'd expect if humans hadn't been living there long. There have only been (very roughly) 60 generations since humans colonized New Zealand. All Maori people, therefore, are at most 58th cousins. All indigenous Australians are at most 1998th cousins. All Africans are at most 8000th cousins.
More recently we've done proper sequencing on the mitochondrial DNA (actually knowing whats written there) and that's allowed much more precise estimation of this sort of thing, and estimation of the timeframes involved. The genetic evidence backs up the fossil record, by and large. (There are a few interesting examples where interbreeding with Neanderthals and maybe Denisovans can be detected, and that the settlement of the middle east by modern humans about 125 thousand years ago failed. They left no descendants.)
Fun side consideration (warning, extra science, proceed with caution): all humans inherit their mitochondria from their mother, and all males inherit their Y-chromosomes from their father. This lets us trace matrilineal lines with a relatively high degree of accuracy, since mitochondria reproduce asexually. To clarify: your matrilineal line is your mother, and her mother, and so on. Your paternal grandmother is not part of your matrilineal line, nor are your aunts or sisters. These lines are statistically guaranteed to eventually converge on a single woman whose mitochondrial descendants now live in all of us. The reasons for this are complicated. There are actually lots of these women, since she inherited her mitochondria from her mother, ad infinitum (well, not infinitum. Ad failed-endocytosis-of-an-alpha-proteobacterium-leading-to-mitochondria doesn't roll off the tongue though). Science has tight estimates on the most recent mitochondrial ancestor, or "Mitochondrial Eve". To be clear: there were loads of other women alive at the time, and we inherit a lot of their non-mitochondrial DNA. Over millennia all those other women had fewer daughters, and their matrilineal lines died out. She lived about 200 thousand years ago, plus minus 20 thousand years. As a mathematical guarantee we'll never find her body or have a really tight estimate on how long ago she lived, but she's genetically guaranteed to exist. The same principle applies to patrilineal inheritance, but the estimates for the most recent ancestor of all Y-chromosomes are a little looser (200-300 thousand years ago). See here for a more detailed handling of Eve and what's going on there.
In sum: old fossils only in Africa, everyone outside Africa is only 2800th cousins with each other or less, but intra-African relatedness is less than half that (more than twice as far away genetically).

Does this mean mitochondrial eve had multiple kids with multiple men?

No, mitochondrial eve isn't real women, it is computer reconstruction according to genetic theories, mutation rate, inheritance and so on. Change one parameter (estimated effective population size, although that one have loose connection with real population size as well) and you have different estimate of Mitochondrial Eve.

Why would matriarchial lines terminate at one person in the past instead of there being multiple lines?  That doesn't make a lot of sense to me.  It would either mean that matriarchial lines never crossed, or that initially there was only a single woman.  Does the term "mitochondrial eve" actually refer to a group of women?

It's not that all ancestral lines go through Mitochondrial Eve's exclusively, it's that she's the most recent person which everyone's 'set of all ancestors going back X years' can be expected to have her in it.

@yters It's not made explicit in the answer, but mitochondrial DNA is passed almost exclusively through the female line (sperm usually only has one or two mitochondria, if any at all, while the ovum has more like fourty). There has been many lines of mitochondrial DNA, but as soon as a mother only had sons, her line was broken. Add to this how many near-extinction catastrophes humans went through (apparently, there's been times when there were only a few thousand humans on the planet!), and it isn't all that suspicious that you can trace one line that's running in all of us. Others died out.

@yters Mitochondrial eve is not a person or a group of persons (in fact I hate these creationistic connotations). It is basically a phylogenetic calculation of the Last Common Ancestor of human mitochondria (which are specifically maternally inherited). IMO addressing to this concept as her/she can be highly misleading. Resonating: you should clarify this in your answer.

@Catalept that's not quite right, you're thinking of something else I think. Most recent common female ancestor, maybe?

@Colombo Mitochondrial Eve is a single human female who is guaranteed to have existed based on what we know about how genetics works. You're confusing imprecision in the measurement technique for imprecision in the measured thing. If you had a time machine Mitochondrial Eve would be time-consuming but trivial to locate precisely.

Mitochondrial Eve was called Hera.

@LightnessRacesinOrbit We're wondering (in chat) what you meant by that. Enlighten us, please.

@Faheem: https://en.wikipedia.org/wiki/Hera_Agathon

@LightnessRacesinOrbit I see. Thanks for the clarification. I just remarked to Resonating that apparently we don't watch enough Battlestar.

@FaheemMitha: :)

@Luaan, thanks that makes more sense.  So, to restate what you are saying, there is a single female in the past that everyone shares mitochondrial DNA with.  It still doesn't make sense that there has to be a single female.  Mathematically, it seems there could be many "mitochondrial eves" from the same period.

@WYSIWYG, correct me if wrong, but you are still saying this calculation is meant to pick out a single female individual in the past with whom everyone shares their mitochondrial DNA, correct?  The calculation is not just a mathematical construct, but is meant to refer to a real individual in the past?

@yters There could have been a person but mitochondrial genome can also accumulate mutations and the rate of mitochondrial mutations is higher than that of the nuclear genome. All I said is that 'mitochondrial eve' is a hypothetical person. I said that I think the term "eve" can be misleading.

@yters Yes and no. At any given point, there's a set of women that are the 'mitochondrial eves' of that point in time.  These women between them are mitochondrial ancestors of all living humans. At this point in time, it's all mothers. If you go back further it's all maternal grandmothers. If you go back far enough the set keeps getting smaller, until it's one person. Any further back and it stays one person. Come to chat, we can back and forth faster there.

@Resonating If I had a time machine, tracing ancestral lines would indeed be an interesting use for it...

@yters Note how the single mitochondrial "ancestor" appears so long after humans did. In the beginning, there have been a lot of different mitochondrial lines - if we take the Homo genus as a whole, that's been around 10 million years, if we go from the point where modern humans diverged from Neanderthals that's around 500 thousand years. Interestingly, anatomically modern humans actually arose around the same time as MitE. But even at the time of MitE, there has been tons of different mitochondrial lines. It's just that one won out in the end - all modern Mit lines are descendants of MitE.

@yters It is indeed possible that there wouldn't be a MitE for Homo sapiens sapiens, for example. But eventually, outside of a given species, you do come to a single ancestor - maybe it was some hominid, or a fish. But with each generation, the probability of only having a single (mitochondrial) ancestor grows. If you only have sons, your MitE line just dies out, ditto if you die. As far as I know, we don't actually know if MitE was an anatomically modern human - it's not like we have her fossillised remains. Her identity is based on probabilistic analysis of human mitochondrial lines.

@yters In any case, this is really getting dragged out. Perhaps you'd like to post a question specifically about Mitochondrial Eve? I'm sure there's plenty of people who can explain this better than me - I'm no expert on human evolution or biology in general.

People previously argued for a multiregional theory in which humans arose from many different places on the globe, but have come to the conclusion that humans came originally from Africa. I believe that their reasoning is that the oldest skulls found have been found solely in Africa. This article expands on my answer if you are interested:
http://news.nationalgeographic.com/news/2007/07/070718-african-origin.html


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Would a VR headset exacerbate myopia or could it be used to retrain the eyes?
I've learned that there are two primary hypotheses to explain myopia: not enough use of distance vision or not enough sunlight
If the distance between an eye and what it's focusing on is the primary cause, then having a VR screen inches away would seem like a recipe for exacerbating myopia.
However, since people with 20/20 vision can use VR headsets, while others need the maximum correction and still see everything out of focus, clearly there is something more than at play than simply focal distance between the eye and the screen.  Could this be used to help minimize, prevent, or possible reduce myopia?
Likewise, if the cause is primarily lack of sunlight, could sunny simulations be used to help minimize, prevent, or possible reduce myopia?  Or is the light produced too artificial?
Knowing that myopia is on the rise, and VR is going to be more prevalent in the near future, these seem like important relationships to understand.
Of course, it could be they are simply two factors of many; but they are extremely relevant to this question.
More recently, my ophthalmologist was adamant that I needed to follow the 20/20/20 rule, i.e. every 20 minutes focus on things more than 20 feet away for at least 20 seconds, which leads me to believe he at least subscribes to the distance hypothesis.

Personal medical and health questions are off-topic for this site.

This would make an interesting question when all reference to self would be removed. Voted to close but +1 for the question.

I made some edits to the phrasing of the question. Please check if this still reflects your intentions and rollback if required.

@MarchHo - Thank you.  That reflects my intentions perfectly!

When using VR headset your eyes focus on distant objects, not on the screen, that's the power of optics!

@szulat If you can find a citation for that, it would be a good answer. I am rather skeptical of that claim though.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

sort: votes


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Looking for a dichotomous key to identify primates
I'm looking for a dichotomous key to identify primates by physical and possibly geographical traits.  Any format is fine (print, web, mobile app, etc.).
Other than classroom activities and genetic classification references the best I have found is on WikiBooks: https://en.wikibooks.org/wiki/Dichotomous_Key/Primates

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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Primer Design with Primer-BLAST over specific site
I am trying to design primers using Primer-BLAST such that the forward primer spans a specific base pair site.
I am looking at KRAS for which I believe the RefSeq ID is NG_007524.1 and the forward primer should span chr12:25398285.
However, I'm not sure how to restrict the design to accomplish this. Thanks.

Do you want to amplify the genomic DNA or mRNA?

I want to amplify DNA.

In any case, I always verify the primers on the UCSC In-Silico PCR tool (https://genome.ucsc.edu/cgi-bin/hgPcr). You can never make sure enough with genomic DNA...

I think various ways can be apply, but the easiest way could be to indicate the range to set a forward primer.
Decide the length of primer you are going to get.
Let's say you would like 25 mer.
You can set the range from chr12:25398261 to chr12:25398309.
When you identify where chr12:25398285 is in NG_007524.1, you are ready to design your primers.

If he had to sequence KRAS gene, he had to amplify fragments of a determined maximum lenght, depending of the platform used. Also, do not forget that many sequencers need some bases (20-40) to warm up, and some other to land. E.G. I want to sequence a fragment from bp 100 to 150 of a given gene: I will design primers starting from bp 50-70 and stop at about 170. Personally I design primers pairs for any coding exon of a gene.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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Why are humans mostly right-handed?
Most sources I've seen say that about 90% of humans are right handed, and 10% are left handed. Why is this?
My only guess would be that it has something to do with different parts of the brain developing differently and causing right or left "handedness", but this is coming from my very little knowledge of the brain.
Furthermore, about 2/3 of people are right eye dominant, and more people are right ear dominant than left ear dominant.
Why the right side?!?


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Textbook/lab manual for mammalian cell culture
For general techniques involving molecular biology, I know of Sambrook and Maniatis Molecular Cloning which covers many of the standard cloning techniques.
However, mammalian cell culture has many significant differences from bacterial cell culture, some of which include the many different variants of cell culture media as well as the relatively complex systems which cannot be provided using standardised media such as LB or TB in E. coli culture.
Are there any similar textbooks/lab manuals for cell culture? Alternatively, good review papers covering the different kinds of media used in mammalian cell culture and their relative benefits would also be a good answer to this question.

Culture of Animal Cells: A Manual of Basic Technique and Specialized Applications by Ian Freshney is the most popular book on the topic of animal cell culture.
You can also refer to ATCC animal cell culture guide which also has information about media formulations.


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Is this Heracleum sosnowskyi?
There's a relatively big scare in local news about the Heracleum sosnowskyi plant, considering how dangerous it can be.
I was strolling through the park when I noticed these plants - the ones I photographed were rather small, but there have been a lot bigger examples in the park as well. For reference, I live in Poznań, Poland.
I have a feeling this isn't Heracleum sosnowskyi, but the only reason I'm thinking this is because it was in a local park where there are a lot of people / kids, and if there were any dangerous plants there there would be an uproar... but I'd rather be sure, thus I'm posting this question.

Is this Heracleum sosnowskyi?

Just out of curiosity, are the leaves belong to this plant? Although it looks like  "Stalin's revenge" to me. read https://en.wikipedia.org/wiki/Heracleum_sphondylium Similar species.

Given what I know about Heracleum sosnowskyi I didn't want to touch the thing, and I took the photos with my phone (questionable quality, I know). As such, I cannot really tell which leaves belong to the plant in question and which belong to other, nearby plants @DevashishDas...

Added a source for the danger posed by the plant (and related members of the genus).

Where were the pictures taken? Species ID questions are very hard to answer without that info.

@fileunderwater I'll add that information to the question.

No, I don't think it looks like Heracleum sosnowskyi. To me, the plant in your pictures looks similar to Angelica sylvestris (which is common in Poland), but there are many species in Apiaceae with a similar apparence and I'm not familiar with all of them. Species in the Heracleum genus has leafs that are "lobed" and all leaflets aren't as separated as the plant in your pictures (overall, the leafs of Heracleum look quite different), and the stem is usually "swollen" where the leafs connect (i.e. the leaf stems are swollen). Plants of Heracleum sosnowskyi (and H. mantegazzianum) are also much larger, and they often have a fussy apparence because of the bristle hairs.
Angelica sylvestris (picture from from wikimedia commons)

I'd say it's an imposter, but depending on the stage of it's life cycle, characteristics may differ. The following webpage lists identifying factors for giant hogweed, as well as some plants that may be mistaken for it (but of course, they aren't). The lack of purple splotches and white hairs around the stalk bases, and leaves are signaling to me that this is not giant hogweed. It looks like it may just be wild parsnip. Take a look at that webpage, giant hogweed is quite... giant.

The reason I was worried is that before something gets big... it starts out small. ;) Unless only fully grown plants are harmful... PS. I'm getting a time-out on that page...


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Why are low temperatures lethal?
Why can't we (human, or even unicellular organisms) withstand low (body) temperatures (5 - 25°C). I have a limited background in chemistry and biology, so this might be obvious, but not to me.
I know that low temperature reduce the speed of chemical reactions, so any creature cold enough should just perform slower? Or are there any other cold-induced effects that prevent certain reactions? (a reaction requiring more energy to happen, would still happen, but at a lesser rate, right?)
And, supposing a bacteria/virus/small&simple organism was subjected to low temperature (above freezing, but low enough to stop working), what would prevent this organism from booting up again when subjecting to "normal" temperature?

E. coli can be routinely placed in the fridge on agar plates at 4°C for over a month (personal experience) and remain viable.

See tardigrade: http://www.popularmechanics.com/space/a11137/secrets-of-the-water-bear-the-only-animal-that-can-survive-in-space-17069978/

@MarchHo They can also be frozen at -80 and revived …

Low temperatures change the speed of different chemical reactions, throwing delicately balanced systems out of balance. How resilient a creature is to temperature changes is largely a function of how complex it is, and how buffered it is against this kind of change.
Tardigrades as kmm mentioned essentially can't be killed by cold, surviving down to almost absolute zero (absolute zero ≈ minus 273.15°C). Most unicellular organisms can be frozen (especially if frozen quickly or cryoprotected with something like DMSO) and revived later without any change. Most strain libraries of bacteria are kept frozen for cost reasons. Even human cell cultures can be frozen and thawed, even though some of the cells will die. (If even 10% of your cells died you as a person would probably die, so freezing is off the table unless you are very clever indeed.)
Humans and most mammals are pretty sensitive to temperature changes, even though reptiles are not. Most fish are cold-blooded and are adapted to cope with the relatively cold temperatures, but the human heart is not well adapted to even relatively warm temperatures. The atria and the ventricles of the heart stop communicating below 27°C (80.6°F)or so, and below 20°C (68°F) the heart can stop beating entirely. Nerves are complex systems, and absent regulation systems in the nerves themselves to compensate for the changes in temperature, they can stop firing completely. A simple heart can run with less sophisticated orchestration, and is, therefore, more resistant to temperature change. A complicated heart involving the coordination of the atria and the ventricles to produce effective pumping action is affected much more strongly by the drop in temperature.
So, in general, more complicated implies more vulnerable to temperature changes. There are exceptions, however. Bears can hibernate and drop their core body temperatures without any ill-effects, so it's possible to adapt to. Fish deal very well with cold temperatures if exposed gradually, and some fish could live quite happily in a slushie, salinity notwithstanding.

In a very general way, you answer to the question. But reptiles aren't that much less complex than mammals (are they less complex at all?) and, as you mention, there are mammals that can hibernate. The question could be rephrased as "what are the adaptations that some animals have (bears, reptiles, fish etc) and others lack (mammals in general) that allow the core temperature of some organisms to drop without negative consequences?". I think there's still room for discussion.


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How do people digest fat after gall bladder removal surgery?
How do people digest fat after gallbladder removal surgery?
How can they tolerate a high fat diet?

This is not a problem, since the gall bladder "only" stores bile, but the production itself happens in the liver. There are some cases described which can get problems digesting very fatty food, but for most people this is not a problem. Additionally eating low-fat food in the first few weeks after the removal is recommended. See here for some more details.
The picture below shows the location of the gall bladder and also the bile ducts (picture from here)


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Definitions of common and rare disease
Is there an epidimiological way to define rare and common diseases ?

How about doing it by the case numbers?

Could you please explain me better your suggestion ? I'm not sure to understand it correctly.

A rare disease has very low case numbers, while common diseases occur in much higher numbers.

Thanks for the clarification ! Do you know if there is a threshold between the two cases ?

To those who voted to close: This question is great, multiple countries build their Health systems budget according to their definitions of "rare" disease. In addition, the issue of these definitions is of great importance for the community health as well.

Thanks for the positive feedback about my question; i found this site very interesting but i need time to properly use it !

While "common disease" has obscure incidence and prevalence definitions, "Rare" or "orphan disease" is more defined.
In the US, the rare disease defined as a condition which affect one (or less) of 200,000 people in population. However, this definition can be different in other countries, p.e. in Japan 1:50,000 or less.
We can assume that "common" disease is much frequent than "rare" one, thus the incidence and prevalence are much greater than per "rare disease" definition. However, again, there is no agreement of clear cut of "common disease" incidence and prevalence.

Thanks for the answer !! I think to have read something similar years ago, but not in detail... i would vote your answer but i still have a low reputation so i can't.


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Butterfly identification: Dorset England, July.
Can you please identify this butterfly. It was seen in Dorset England 9th July. I think it is a female Silver Studded Blue.

see similar species at the bottom of this page - http://butterfly-conservation.org/50-781/silver-studded-blue.html

see this site too http://www.natureofdorset.co.uk/species/common-blue

by the way its a lovely image

Thank you for the response rg255. After continually looking at images on the sites you advised, I finally concluded that it is a Silver-Studded Blue. The spots have worn a little and should be a dominant black like wise the band of orange spots should be more dominant.

The silver-studded blue is frequently found feeding on this plant, cross-leaved heath. There are good numbers of this species to be found on the heaths of Dorset in July and I would suggest that this is certainly silver-studded blue.

Peter, it would be great if you can add some references.


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What is the simplest autotrophic cell?
Very simple cells, such as Nanoarchaeum equitans, require a host to provide certain essential ingredients for life. Complex life-forms (like humans) require a whole ecosystem of other life-forms to survive (either externally, to provide food, or internally, in a symbiotic relationship).
What is the simplest cell that has been discovered so far that can live in an environment where there are no other life-forms, not even in a decomposed state? Does such an organism exist, or is all life inextricably dependent on other life?

I guess one of the chemoautotrophs.

What kind of environment with 'no other life-forms' are you thinking about? Amino acids are found in comets, and the oxygen in the air is biological in origin.

I'm imagining an artificial laboratory environment. I doubt that such an environment would exist naturally so long after the first proliferation of life.

@WYSIWYG  I'm not sure that the word "autotrophic" is entirely accurate here. I can imagine that there are simple organisms that create their own energy but which require molecules created (and perhaps discarded) by other organisms, so they are still dependent on the other life forms. Does the word "autotroph" explicitly exclude such interdependence?

@JamesNewton yes

@WYSIWYG In that case, my question can become: what candidates for the status of pure autotroph exist?

If by "simplest" you mean smallest genome, then according to Brock's Biology of Microrganisms (13th ed, p 319) the smallest autotroph is Aquifex aeolicus, a chemolithotroph bacterium. It's genome is 1.5M bases, about 1/3 of that of E.Coli, and was sequenced in 1998 (https://www.ncbi.nlm.nih.gov/pubmed/9537320).
The genome is densely packed though and still carries some 1,500 open reading frames. The authors of the genome sequencing paper states that "metabolic flexibility seems to be reduced as a result of the limited genome size", which I guess is some evidence of "simplicity".

I'm not sure if this is exactly what you are looking for, but since I was looking for an answer to a similar question to you (what's the simplest living organism), I just found about this,

"The Simplest Living Organism Ever Has 437 Genes and Was Made in a
  Laboratory"
"a self-replicating bacterium invented by Venter and his team that
  contains just 437 genes, a "genome smaller than that of any
  autonomously replicating cell found in nature,"

Now I dont know if artificial organisms count in your question, and if it complies with the other requirements you were asking
https://motherboard.vice.com/en_us/article/craig-venter-created-the-simplest-living-organism-possible-in-a-laboratory


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Pitch shift in hearing after wisdom teeth removal
Yesterday I had my wisdom teeth removed. This morning, when I heard our phone ringing, it sounded a little lower-pitched than usual (I have perfect pitch). Sure enough, when I opened FL Studio (music-making software) and loaded up one of my projects, I had to adjust the master pitch up by about 20 cents for it to sound "in-tune". What could cause this shift in pitch perception?

The change in blood flow to, or damage to the cochlea by vibrational trauma (drilling) were implicated in a hearing loss case here after some dental surgery. You'll want to consult a physician, however, for any of your worries. If this is a personal case, we cannot provide medical assistance, nor do we have enough information about your or your procedure to begin consideration.

Because it's not really hearing loss, I'm not too concerned about it. I'm mostly just curious as to what could cause a shift in pitch perception.

Temporary swelling or edema from the extraction would be my assumption.

Perfect pitch with respect to what note? (A440?) Also, how broad is the supposed pitch shift? I find it rather hard to believe that swelling can cause a logarithmic pitch shift across the entire audible spectrum.

@MarchHo yes, A440. And as far as I can tell, it affects my entire hearing range, although I haven't thoroughly tested it.

Does it affect pure notes or only chords? I'm not sure what tests you've done or what perfect pitch is like(I don't have it and I can't really imagine how it works), but my very first guess would be that higher pitches are more attenuated by your newly detoothed skull, so higher harmonics sound quieter and the overall sound is lower. That would work on a ringing phone but should work less noticeably on pure tones.

I once had an ear infection that, when done, left that ear's perceived pitch shifted by about a quarter tone, which really messed up listening to music (google ToneTester and you'll see the testing app I wrote afterwards). I recovered after a few months.

I just had my wisdom teeth removed, and I'm experiencing the same thing. What I used to hear as 440 for A is now actually at around 450 - 460. When I hear people talking, I don't notice a difference, but when I was tuning my violin today it felt kind of off. Same with the Discord sounds when people left or joined calls; they sounded lower pitch than I was used to.


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Blomberg's K and branch length
Do different values of the smoothing parameter lambda for estimating the divergence times (in situ Sanderson 2002) will affect trait conservatism (e.g., Blomberg's K)?

I don't know if lambda for estimating divergence times works in the same way as it does for scaling internal tree nodes, but I'm going to assume it does given the context of your question.
My gut reaction was: of course it must because K is the ratio of observed to expected variance and tip variance is moderated in part by branch lengths. So if you change the node positions, the expected tip variance should also change.
A quick simulation shows that this appears to be true.
library("ape")
library("picante")
library("geiger")

set.seed(5)

tree <- rtree(30)
y <- rTraitCont(tree)

lambdas <- seq(1.0, 0.05, by = -0.05)
M <- data.frame(lambda = lambdas, k = numeric(length(lambdas)))

for (lambda in lambdas){
  tree_trans <- rescale(x = tree,
                        model = "lambda", lambda = lambda)
  M$k[M$lambda == lambda] <- phylosignal(y, tree_trans)$K
}

plot(k ~ lambda, data = M)

Generate a tree with 30 tips and generate random data along the branches. Then rescale the tree for a series of lambda values and calculate k for each lambda scaling.


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Is there a mechanism by which mammals lose interest in a partner after mating?
I'm reading the book called "Cupid's poison arrow", which revolves around a rather simple assumption: most mammals, including humans have a genetic program that is responsible for ever increasing dissatisfaction with a mate after intercourse with orgasm.
The book proceeds to give a number of examples, here's what I remember:

Coolidge effect, where libido is revived upon exposure to a novel, receptive partner.
Male rate copulating on average 8 times with a receptive female before losing interest
Sexual satiety setting off a 14-15 day hormonal cycle where [a male rat] would lose all interest in a partner

The book contains a large amount of anecdotal evidence of humans experiencing negative outlook on their partner after orgasmic intercourse, with more intense intercourse producing more intense dissatisfaction.
The author proceeds to formulate a hypothesis that humans and other mammals have a genetic program that fosters sepratation between mates and seeking of a novel mate as a mechanism to promote more genetic diversity in offspring (as opposed to monogamy)
Is there a scientific basis for such claims -  do mammals have a mechanism that draws them apart after intercourse or sexual satiety is achieved?

Looking for scientific justification? :-)

Scientific is the best kind of justification :P  But seriously, that hypothesis sounds really solid and like it has a lot of evidence. I want to know if it is valid.

Why should something like this be a genetic program specifically for this one thing, rather than just the expression of a general taste for diversity?  E.g. most people have favorite foods, but we'd regard an adult person who ate only one particular food as decidedly weird, and their diet would almost certainly be unhealthy.

Well from what I have been taught, and have studied, is that multiple partners for men does not equal more of their DNA persisting, because they are needed to provide for the offspring. So if they impregnate 10 different females and don't stick around, that really doesn't help them pass on their DNA because most would die. So having a family with the same partner does ensure more offspring survive. Humans are picky selecting their mate for the reason of wanting to get the best genetic combination possible to have the most offspring survive. A human child takes a lot of effort to raise to reproductive age, we aren't like some animals who are off and running. So our bodies invest a lot in making sure that happens, being flooded with bonding hormones after sex, women's bodies changing to nurse (and then not being able to hunt/gather/protect themselves) etc. So there is a hormonal cascade that happens to ensure you are going to stick around after mating.
I am really talking about our ancestors, but obviously some of their behavior has carried to us.
However having multiple partners DOES benefit the female. Males can't tell they are the father to a child until much later, after they have supported the pregnant mother, etc. Females can then have their DNA pass on in multiple combinations to ensure survival of more children. Pubic hair in women is thought to have evolved to hide any physical evidence of a recent mating with different males outside of the family. And if current statistics say anything - just as many women cheat on their spouse as men. And when cheated on women want to go after the other woman, because that's our competition and they may be taking the mate we worked so hard to get.
Humans are hard to compare to other animals because we can manipulate so much of what happens to us. But if the ultimate goal is to ensure the passing of DNA then that hypothesis (to me) doesn't fit with humans.
But then again, I am a woman and therefore could be biased haha. If you read an animal behavior textbook it will go into this in in detail, and state it much better than I can, and with supporting scientific evidence. As a biologist the term "anecdotal evidence" makes me cringe :)

Hi Whitney - Welcome to BiologySE! Thanks for your answer - generally we value references to back up the claims in individual answers. I know that some of this may be common knowledge to you (as much of what my answers are), but please try to include some citations of published works that support your answer. Feel free to edit the current answer and add to it - thanks for your contirbution

Thanks for an answer. From my knowledge of evoutionary psychology, your statement is incorrect. An attractive "bad boy" casanova can leave 50 children with single mothers and would outperform a pure pair bond partner.


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

You can easily drown them in a glass of plain water; they stop moving within 10-20 seconds, but you could leave them longer to make sure. Just don't look closely at them during this, as some may find it upsetting.

Short answer: Mire them in a viscous liquid then leave them in there long enough for them to die, instead of immediate disposal.
Cooking oil is viscous, so yes you can viably use it to mire the fleas. You'll need to wait until they die though to dispose of them or else they'll come crawling back as you've stated. The DIY option is generally a water/dish soap mixture in a container: you'll put the fleas in and they sink to the bottom almost immediately. Just leave them in there and they'll eventually die in about 5 minutes. Some individuals suggest Dawn dish soap, much like here, where the claim is that the Dawn contains compounds which suffocate the fleas.
You can also make a flea trap for around the house, with a bowl of dish soap and water near a night light. They'll jump for the light and end up falling into the flea trap.


text:
What is the standard protocol for creating permanent stocks from freeze-dried bacteria?
I've received freeze-dried bacteria that I intend to use for a study I'm doing on slime mold; however, I've never dealt with freeze-dried, only frozen, bacterial cells. After reconstituting these cells in 6mL media, is it alright to split this in to halves and place one aliquot into DMSO or glycerol to make a permanent stock right away? Or is it best to plate, isolate, suspend, grow, and then make a permanent stock?

I was under the impression that glycerol stocks should be made from log phase cells. Therefore, I would definitely grow up the cells before freezing a glycerol stock.

I am not sure, if the cells would survive this procedure. I would reconstitute them first and then make glycerol or DMSO (which I prefer for easier handling) from fresh cultures.


text:
Do our belly buttons consist of scar tissue?
I read an interesting post on Facebook the other day saying that we all have a visible scar since birth - our belly button. This got me thinking (and research for me only found results regarding belly button piercing) is the belly button made up of scar tissue?
I seem to recall that there are some stem cells still within the umbilical cord (which is why doctors tell you to spend the money to have it saved (I think)) so I was wondering if scar tissue closed the hole left by our cut umbilical cord, or if the stem cells divided to produce normal skin tissue.

According to Wikipedia they are scar tissue.

@canadianeradianer I'd like something more definitive than Wikipedia that can be changed by anyone (like when the lunar eclipse said that the moon would blow up)

I think the question hinges on the definition of scar tissue and the histology of the navel tissue. Given that the navel is not a functional organ, other than as a locus for piercings, I think finding a conclusive scientific answer is next to impossible.

@SolarLunix I'm sure you are, which is why I didn't post an answer. Just thought you might like to know.

The place where the cord was cut do not stay with us - it falls in a week +- after the birth, while the umbilicus is the only visible natural scar formed by natural processes, not by gynecologists:

Multiple sources say the umbilicus has a scar tissue in it.

After birth the umbilicus is the only naturally formed visible scar on
  the body.

Br J Plast Surg. 1998 Oct;51(7):538-41. Umbilicosculpture: a concept revisited.

Umbilicus is a scar, which is the place of the previous merger of the
  fetus with the umbilical cord.


text:
What determines whether an action potential is inhibitory or excitatory?
What determines whether an action potential is inhibitory or excitatory? Is it determined by the receptors, the neurotransmitters, or some other mechanism?

Short answer
The physiological state of the postsynaptic cell ultimately determines the effect of an incoming action potential.
Background
An action potential occurring in a chemical synapse is neither inhibitory or excitatory. An action potential is a binary '1', an-all-or-nothing signal without any information, i.e., there is not a -1 or +1 action potential. Similarly, there are no excitatory or inhibitory neurotransmitters.
Notably, the principal excitatory neurotransmitter in the nervous system, glutamate, can have inhibitory effects dependent on the receptor activated. While most metabotropic glutamate receptors (mGluRs) and ionotropic AMPA and NMDA receptors are indeed all excitatory, the inhibitory glutamate receptors (iGluRs) are not (Cleland, 1996).
Conversely, GABA, the principal inhibitory neurotransmitter in the nervous system, can have excitatory postsynaptic effects. For example, hyperpolarized neurons may actually depolarize upon GABAA receptor activation, simply because the resting membrane potential is more negative than the reversal potential of Cl- (i.e., Cl- flows out of the cell due to the negative membrane potential) (Marty & Liano, 2005).
The existence of both excitatory and inhibitory glutamate receptors shows that it is the postsynaptic receptor that determines whether an action potential will inhibit or excite the postsynaptic neuron. The excitatory effect of GABAA activation shows that on top of that, even principal inhibitory neurotransmitters (GABA) with principal inhibitory receptors (GABAA) can excite a neuron dependent on its physiological state.
Besides chemical synapses there are electrical synapses. In these synapses action potentials are transmitted directly electrically through gap junctions. In this case, any action potential is excitatory as the signal will be carried forward if it is strong enough (Purves et al., 2001).
References
- Cleland, Mol Neurobiol (1996); 13(2): 97-136
- Marty & Liano, Trends Neurosci (2005); 28(6): 284-9
- Purves et al., Neuroscience, 2nd ed. Sunderland (MA): Sinauer Associates; 2001.

After reading your answer, my impression is my question is a bit nonsensical. Does it seem that way to you? I can't tell if I asked a meaningless question or the answer is "it depends and without further info that can't be specified." Thanks for replying btw.

I think your question makes a lot of sense, because too many people talk about excitatory neurotransmitters and the likes. There are no inhibitory or excitatory neurotransmitters. +1 for the question.

@AliceD, I'd vote for peppering in a few judicious "strictly speaking"s to your answer, since I'd bet most working neuroscientists would give a minor eye roll to your italicized comment point.

@Chelonian - I'm a working neuroscientist. Which comment are you addressing?

@Chelonian - and given the nature of the question I don't think any eye roll would be rather misplaced.

@AliceD I was addressing "There are no inhibitory or excitatory neurotransmitters." in your comment to Stan Shunpike, but it also applies to "Similarly, there are no excitatory or inhibitory neurotransmitters." in the answer you gave. I wasn't quite sure what you meant by the 2nd comment to me; do you mean you do think they would be misplaced? I think you're right, just that maybe putting "strictly speaking," in these sentences (or something like that) may be helpful, since there are thousands of pieces of legitimate text that refer to "excitatory neurotransmitters", etc.

The state of the postsynaptic cell does NOT always determine the outcome of an action potential. You seem to be neglecting the whole presynaptic and autoreceptor literature in your answer. The neurotransmitter released doesn't even have to reach the postsynaptic side, it can lower or increase the probability of release in the presynaptic cell for example so your answer needs to be toned down.                                                                                c.f Tzingounis, A. V. & Nicoll, R. A. Nat Neurosci 7, 419–420 (2004).

@V_ix in the light of the question, the answer is valid. Further,  autoreceptors by no means change the effect of an action potential, only subsequent ones. The fact whether neurotransmitter reaches the postsynaptic neuron, in the light of the basic nature of the question that's a bit of an overkill detail. I'd rather not tone down anything and I think you are overinterpreting the question.

@AliceD I have a related question: You say that NTs are not per se inhibitory or excitatory, but neurons themselves are typically classified as one of the two. How is this possible, given that say the NT released by an inhibitory neuron can also have excitatory effects (depending on the receptor it binds to)?

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Definition of "essentially diploid"
While researching the F12 cell culture medium (Ham, 1965), I came across the term "essentially diploid Chinese hamster ovary cells". The terms "subdiploid" and "near diploid" were also used to refer to the same cells.

Attempts at searching Google Scholar and regular Google failed to turn up a definition of the phrase.
What exactly is meant by "essentially diploid", and how is it different from regular diploid cells?

Secondary cell lines often show aneuploidy. I think it is a reference to that.

I think that the rest of the paragraph that you left out of your quotation helps to clarify. The CHO have 21 chromosomes, while the somatic lung cells have 23.
Neither case is exact for Chinese Hamsters, 2n = 22. So they have almost the complement of chromosomes that a diploid Chinese hamster somatic cell would have but they are missing one or have one extra. For the most part they will behave like normal somatic cells in culture, but it is an important fact to note as you can have cases where dosage dependence of a missing chromosome in a pair or an additional chromosome (trisomy) can affect the outcomes of research.
In the back of your mind you always need to be thinking how does the missing/extra chromosome affect the data I am collecting.
This Nature article may also be of interest.

@MarchHo, if you are not a native English speaker, then one thing that you need to remember about the English language is that it is contextual, and definition can often be defined from the context of usage. Here "essentially diploid," combined with the knowledge that 2n=22 and that the cell lineages are 21 and 23 chromosomes, means that while they are almost the same as somatic cells, they are not exact, which as I stated above has implications. If the CHO cells are missing an X-chromosome, then maybe it doesn't matter, as we now know about X-chromosome inactivations...

... while a different chromosome might be problematic. They are "essentially diploid" but one should keep in the back of their mind that there could be effects to the missing/extra chromosome in these lines that could have implications to the research results and the conclusions drawn from the data.

"Essentially diploid" means that a normal (most common normal) state is diploid, while any other state will be considered rare (can be normal yet) or abnormal or unusual.
The "essentially diploid" is in some way a tautologic, since we can say "human somatic cell is essentially diploid" as well as "human somatic cell is diploid" omitting "essentially". But the goal of "essentially" is to clarify other states:
If some essentially diploic organism has one chromosome set it will be called "monoploid", while cell/organism etc which normally has one set will be called "haploid".
Sub-Diploid and Near diploid means there are incomplete (aka less than normal) sets of genetic material.

Do you have any references for your answer?

@MarchHo Please, look at this one - http://www.ncbi.nlm.nih.gov/books/NBK21229/  You can easuly find additional supporting refs if you need them.


text:
Secretion in Gram negative bacteria
Among the 6 secretion systems in bacteria, can these 6 ways be sorted out in the order of how harmful it is to the human host? Like say type 3 is highly virulent so that comes first, but I don't know about the rest of the systems. Being a computer science student, I have failed to understand the Wikipedia article to derive this order. Does a discrete order even exist? Can anyone answer this question?

Theoretically there are two very basic things to consider in judging virulence for the secretion systems:
a) Can it secrete into any human cell? (If not, chances of being virulent are smaller, but not zero as whatever is secreted in the environment of a cell could also be harmful for the cell.)
b) Does it secrete some agent (protein, RNA, molecule), which is potentially harmful for a human cell?
a) alone is not sufficient for it to be virulent if b) is not also given.
(As it could inject something in a cell that the cell can handle without a problem.)
b) alone is not sufficient, as it has to get inside the cell somehow. Although, b) alone can work, if the agent has another way to get inside a cell or to harm the cell from outside.
So, generally, without knowing ALL the bacterial secretion systems and secreted agents, it is impossible to decide if one secretion system (alone) is always, sometimes or never harmful.

So these 6 categories does not include all the secretion types?

All we know, I would say. But that was not what I meant to point out. The mere existence of a secretion system does not mean there is something harmful to be secreted, or that it can be secreted into a human cell. Even if the "generalised system" is said to be able to secrete into a human cell, there might be mutations in some bacteria which change it into being less or more effective. Even if the secretion system is not mutated, the bacteria might need additional systems to adhere to a cell or adhere more strongly.

I think I did not quite get this answer. I think the questio is much easier than you say. In general the majority of the secretion systems are know to be used by symbiotic and pathogenic bacteria to interact with other bacteria and eukaryotes. Now, there is a huge amount of literature on the T3SS. It is used by pathogenic bacteria to alter immune response and cytoskeleton of the host and allow the delivering cells to colonize the host cells without being digested.

So if you refer to pathogens, well then you can consider the T3SS as an archetype of virulence factor. Instead, T4SS, T5SS and T6SS can also have other function besides virulence. So in general is the bacteria you are dealing with is described to be a pathogen, and has a T3SS, 99% this T3SS will be involve in virulence.

The presence alone of the SS does not allow you to define if a bacterium is pathogenic or not, but knowing the lifestyle of the bacterium you can be quite sure that if these systems are present, they are used for virulence. Just keep in mind that T1,2,4,5,6 can have additional function than virulence.

Additional comment, recently was discovered a T7SS, so no the 6 you mention is not all we know. Look the review in my previous answer.

I think you cannot find a better answer then the following review:
http://www.nature.com/nrmicro/journal/v13/n6/full/nrmicro3456.html
It was published in 2015, and it gives a good overview about the secretion systems. Anyway, T6SS can also be virulent. Vibrio cholerae can use an effector of this SS to cross-link actin in the host cell and modify its morphology and its cytoskeleton behaviour.
In general I think that there is not a general order of virulence, also because the T3SS was discovered long ago. Whereas, the T6SS just recently, so the amount of information about its function is still somehow limited.
Hope this helps.


text:
Is Insulin-Glucose dynamic Lotka-Volterra?
From Wikipedia:
The Lotka–Volterra equations, also known as the predator–prey equations, are a pair of first-order, non-linear, differential equations frequently used to describe the dynamics of biological systems in which two species interact, one as a predator and the other as prey. The populations change through time according to the pair of equations:
\begin{align}
\frac{dx}{dt} = \alpha x - \beta x y \\
\frac{dy}{dt} = \delta x y  - \gamma y
\end{align}

This looks very similar to how Insulin and Glucose interact with each other in the body.

Glucose uptake release insulin and glucagon offsets the effect of insulin through glycogenesis.
Can the Glucose-Insulin dynamic be described as Lotka Volterra?

Is there a model for glucose-insulin relationship. I guess there may be several. Lotka-Volterra is basically a negative feedback model and there are several examples of negative feedbacks (they are not referred to as Lotka-Volterra because it is model for a specific case and not a modelling strategy). You should clarify your question. Without looking at the model no conclusions can be made.

Is the standard Lotka-Volterra (LV) model an exact fit for insulin-glucose (IG) dynamics? No. Can a similar model built on the same principles capture most of the essential features of the IG dynamics? Absolutely.
How to capture most of the insulin-glucose dynamics using a slightly modified Lotka-Volterra model
We can figure out how to change the LV equations to fit the IG dynamics by figuring out how our assumptions have changed. Like Daan mentioned, neither insulin nor glucose undergo self-reproduction. So we'll drop those terms from the equation, and we'll represent an influx of glucose (as from, say, a meal) as a simple time-dependent linear spike. Your rate equations will now look like:
$\frac{dx}{dt} = \alpha[t_{gi} < t< t_{gf}]-\beta x y$
$\frac{dy}{dt} = \delta x-\gamma x y$
where $x$ is glucose concentration, $y$ is insulin concentration, and $[t_{gi} < t< t_{gf}]$ is equal to 1 if the current time $t$ is greater than the time when the glucose spike starts $t_{gi}$ and less than the time when the glucose spike ends $t_{gf}$, and is equal to zero if the time $t$ does not meet this condition.
Simulation of insulin-glucose dynamics using the above LV model
I ran a simulation of the above model in Matlab, and here's what it looks like:

The basic features of the insulin-glucose dynamics from the example graph the OP posted are present. Just like in the real system, first the glucose spikes, then the insulin spikes after a short lag, then they both return to baseline.
With some small improvements, the LV model can capture the dynamics of the infamous "sugar crash" phenomenon
Now for the really cool part.
As can be seen on the OP's graph, glucose levels tend to fall somewhat below their baseline following a large glucose spike. This is the physiological basis for the sugar crash that people sometimes get a little while after eating something really sugary like a candy bar. Regardless of whether the psychological symptoms actually occur, the dip in glucose levels is a real thing.
In order for a model to be considered "good", it has to be able to capture these kinds of complex but important phenomena in their underlying systems. The glucose dip did not show up in my original LV model, so the question is, can the model be modified in a simple way so that it will capture the dip? Let's take another crack at it!
Part of the problem with trying to study phenomena related to baseline levels using the previous model is that the baseline levels of both insulin and glucose are effectively fixed at 0 in that model. We can set the baseline levels by adding what's called a zeroth-order production term (essentially a fixed constant that isn't multiplied by the concentration of anything) to each of our rate equations. The rate equations now look like:
$\frac{dx}{dt} = \alpha[t_{gi} < t< t_{gf}]+\epsilon-\beta x y$
$\frac{dy}{dt} = \delta x+\eta-\gamma x y$
where $\epsilon$ is the 0th order glucose production term, $\eta$ is the 0th order insulin production term, and everything else is exactly the same.
Simulation of insulin-glucose dynamics using the "dip-enabled" LV model
Again using Matlab, I ran a simulation of the "dip-enabled" LV model:

and this time the dip shows up.
Notes:
-The term with the times in it is called an Iverson Bracket.
-You could make this model more physiologically relevant by using a more complex function for the glucose spike, but for simplicity's sake we'll stick with a linear function. A smoother function, like for example a Hill function, would probably help to reproduce your original graph of the IG dynamics.
Matlab code
function dxdt = insulin_glucose_birth_death_dxdt(t, x, kip, bip, kid, kgp, bgp, kgd)
dxdt = [kip*x(2) + bip - kid*x(1),
    kgp*(t>1 && t<2) + bgp - kgd*x(1)*x(2)];
end

function [t,x] = insulin_glucose_birth_death_odesol(tspan, x0, kip, bip, kid, kgp, bgp, kgd)
opts=odeset();
[t,x]=ode45(@(t,x)insulin_glucose_birth_death_dxdt(t, x, kip, bip, kid, kgp, bgp, kgd), tspan, x0, opts);
end

function [t,x] = insulin_glucose_birth_death_plot(tspan, x0)
%run with:
%   tspan = [-10, 5];
%   x0 = [0,0];
%   [t,x] = insulin_glucose_birth_death_plot(tspan,x0);

kip = 2;
bip = 0;  % set to .01 for the "dip" simulation
kid = 1;
kgp = .1;
bgp = 0;   % set to .1 for the "dip" simulation
kgd = 50;

[t,x] = insulin_glucose_birth_death_odesol(tspan, x0, kip, bip, kid, kgp, bgp, kgd);

figure(gcf)
hold on
plot(t, x(:,1), 'b', t, x(:,2), 'r')
legend('insulin','glucose')
xlabel('time')
ylabel('concentration')
axis([0 inf -inf inf])
hold off
end

You need not include the code. That is not really necessary. Instead you can explain the mathematical model better.

Interpreting your question as "would the Lotka-Volterra predator-prey model be a good model for the glucose-insulin system?" my answer is "no". The predator-prey equations capture assumptions about how prey and predator interact with each other, and how they would fare on their own. These assumptions are not equivalent to any reasonable assumptions about the glucose-insulin system. The fact that both prey and predator population sizes as well as glucose and insulin concentrations oscillate is not enough to say the two systems may be modelled by the same equations. In fact, the oscillations in the figures you show are very different form each other.
Let us go through some of the assumptions of the Lotka-Volterra predator-prey model to see why most of them do not resemble anything related to the glucose-insulin system.
1) In the absence of predators, the prey population grows exponentially without limits. This follows from self-reproduction. If glucose were likened to prey, glucose would increase exponentially in the absence of insulin. If prey were likened to insulin, insulin would increase exponentially in the absence of glucose. Is that reasonable?
2) The population growth rate of the prey is reduced by a quantity proportional to the population sizes of both prey and predator. The underlying assumption is that prey and predator meet a rate proportional to their population densities and that a fraction of these encounters leads to the death of the prey. The assumption about the encounter rate is called the Law of Mass-Action, and applies well to chemical compounds in a liquid, like glucose and insulin. However, glucose and insulin do not interact directly, and it is not clear to me how realistic assumptions abut their interaction would work out.
3) New predators are born at a rate proportional to the encounter rate in 2). In the glucose-insulin system this would mean that more insulin is produced if more insulin is present. Is that realistic?
The answer to these questions is, according to me, "no".
(On a side note: the Lotka-Volterra model is structurally unstable, meaning that slightest change in the assumptions would fundamentally alter the outcome of the model. One of these outcomes are neutrally stable predator-prey cycles, that is, cycles of which the amplitude and period depend on the initial population sizes. Changing the assumption that the prey population grows exponentially by including a term - $m \times x^2$ to the first equation changes the oscillations into damped oscillations so that the populations settle at a stable equilibrium.)

No, the Lotka-Volterra model is a description of predator-prey dynamics. Although in some respects over-simplifying it is well suited for educating population dynamics and basic research.
The physiology of carbohydrate homeostasis is different. Although, similar to population count in the Lotka-Volterra model, the elimination of both glucose and insulin depend on their respective concentrations (which represents a very basic form of autoregulation), their interdependence is different. Here, we have to consider distribution processes, receptor binding, enzyme kinetics etc.
Numerous mathematical and cybernetic models have attempted to describe glucose-insulin homeostasis. The following review articles provide a good overview of the topic:

Ajmera I, Swat M, Laibe C, Novère NL, Chelliah V. The impact of mathematical modeling on the understanding of diabetes and related complications. CPT Pharmacometrics Syst Pharmacol. 2013 Jul 10;2:e54. doi 10.1038/psp.2013.30. PMID 23842097; PMCID PMC3731829.
Palumbo P, Ditlevsen S, Bertuzzi A, De Gaetano A. Mathematical    modeling of the glucose-insulin system: a review. Math Biosci. 2013    Aug;244(2):69-81. doi 10.1016/j.mbs.2013.05.006. Epub 2013 Jun 1. Review. PMID 23733079.

There is an important difference in the dynamics of the 2 situations.
The Lotka-Volterra model undergoes repeated oscillations in predator and prey levels. Changes in one population affect the changes in the other population, and vice versa.
In the glucose-control model, what you have plotted are the changes in glucose and insulin levels following a meal or infusion of glucose. Note that there is no subsequent peak of glucose after the insulin levels have dropped, unlike the peaks in prey levels after predator levels have dropped in the Lotka-Volterra model.

Negative feedbacks can lose oscillations if certain parameters are  changed. This is called the Hopf bifurcation. Just because a system ceases to oscillate doesn't mean that the model structure has changed. Anyways, since the OP has not really shown the mathematical equations underlying the glucose-insulin plot, nothing can be said. I am surprised why this question is not closed yet.


text:
Why do we produce so many sperm?
So apparently we produce roughly 300 million sperm daily. Is there a reason why this is necessary? Wouldn't a much smaller (but still large) number be sufficient? Like, one million?

Can you add a source for this number?

@Chris it's something they just taught us in the biology class (I imagine it is also in the book http://www.amazon.com/Biological-Science-MasteringBiology-3rd-Edition/dp/0321543270). Google searches yield ranges from 80 to 250 million - either of these numbers serve the purpose of my question though. I don't really care how many are produced, but rather, what's the point of making so many.

The one winner out of millions is more special than the one out of two :)

so the question is, how does 300 million sperm cells are better than one? like, one sperm -- one egg?

@aaaaaa yeah exactly :D

It's interesting that you think 300 million is "so many" but 1 million is not. My point is, one's intuition for what is a "reasonable" number of things in nature is often a poor guide.

@Chelonian "Wouldn't a much smaller (but still large) number be sufficient? Like, one million?" I don't think I ever said one million is a small number. I said it is much smaller compared to 300 million. So the question is mostly about whether or not a much smaller amount would be sufficient.

One might guess that it is simply a hangover from fish doing external fertilization.  Evolution is not intelligent design: if something works, it tends to be conserved even if it is not 'perfect'.  To get to say 1 'sperm' fertilizing 1 egg, you'd have to back down a bunch of evolutionary paths, and take different branches...

@Voldemort Notice I didn't write that you said 1 million is a small number. I said that you didn't think it was "so many". Which was the case, wasn't it?

@Chelonian no, I never said that 1 million was not "so many". I said that it is much less than 300 million, but still large. So yes, I think that 1 million is still "so many", and the question is therefore "why not 1 million instead of 300 million? Both numbers are still massive"

@Voldemort Fair enough. My point about our intuition not being a good guide to what the numbers for things like this ought to be still seems applicable to human intuition generally; that is, why should 1 million, for example, be enough? Why not 24,500? The point is, the numbers are what they are, and maybe 300 million is the appropriate number (or maybe the system isn't optimized?).

https://biology.stackexchange.com/questions/39612/why-are-so-many-spermatozoa-produced-when-only-one-of-them-fertilises-the-ovum/39618#39618

The term you should look up is sperm competition, there is an introductory wikipedia article about it here, where you can get the basic picture and get some references to explore.
Simply said, males often compete with other males in the reproductive tract of the female, thus a higher number of sperm will lead to a higher chance of fertilizing the female in competition with other males - leading to an arms-race of the number of sperms a male eject into the female.
There is a lot more to it, of course, but I believe this well explains the most fundamental driver of why males generally produce and eject so many sperms.

If a male mates with the female, and then comes another male, wouldn't the first male be much more likely to succeed because he introduced the sperm beforehand? I imagine that just a few hours are a huge advantage, so I'm not sure why would one need so many millions of sperm anyway.

@Voldemort I think it's safe to say that any advantage of being first for a certain amount of time would be highly dependent on the nature of the species in question. But if the production of sperm is relatively cheap and the competition is relatively significant, I think it's easy to see that we might reach an arms-race here, even if the amount of sperm would not always have to be the most important factor.

@Voldemort And if we look at humans as an example, we are curiously unique in an unexpected way as our penises seem to have evolved to displace semen of other males from the vagina, so sperm competition seems to be very real even in humans.

Great reference Alex, right on track. Also high production of sperm also has to do with male health and dominance. In the wild a more dominant healthy male will produce more sperm and healthier sperm. Females pick up on this and will want to mate with someone strong. I'm humans this characteristic is not as widely perceived but women will tend to be attracted to a male that seams strong because psychologically he can " protect her and their young" of course we have evolved to money being a statement of power and dominance thus this can also serve as competition. All in all it boils down to ove

The answer, if you search for a bit, boils down to geometry. It takes X amount of sperm cells to successfully fertilize an egg. If you optimize delivery system (e.g. vagina geometry), you'll need less. In species where one male fertilize number of eggs (aka polygamy) and are able to have progeny from number of females, you need less cells in ejaculate to produce single child, because chances are higher with higher number of matings.
In humans it is quite often one male-one female relationship, so you have to bump number of cells in ejaculate so that mating season is fruitful.
Final point of real-life statistics:

Of the 300 million sperm ejaculated, only about 200 or so will survive to reach the egg cell and only one will succeed in fertilizing it.

You need to beat these odds ($10^{-6}$) in order to reproduce. Why female reproductive organs are so restrictive? Probably because there is some link between male's overall fitness and number of sperm cells. Fit males (those that hunt better than others) are able to spend more energy for generating sperm, rather than "feeding" their own body. If they able to "feed" 300 million sperm cells, they probably will be able to feed a child.

Your theory seems to go straight against the sperm competition theory?

I'm a bit suspicious of the implied statistics here... If there were 300 million sperm, and 40 million reached the egg, still only 1 would fertilise it (except in rare cases). Also you're relying on something like bodily system integrity to imply sperm count reflects general fitness. I'm not sure if something like this has been demonstrated. I'd be very interested if you could provide a citation for that line.


text:
How to compare two RNA transcripts?
In this paper, the cuffcompare RNA package is reported:

Because of the stochastic nature of sequencing, assembly of the same
  transcript in two different samples may result in transfrags of
  slightly different lengths. A Cufflinks transfrag was considered a
  complete match when there was a transcript with an identical chain of
  introns in the combined annotation.

What does this mean in terms of comparing two transcripts to see if they are the same? Does that mean two transcripts are considered equal if they have the same introns, even some exons are missing in one of the transcript? What do they mean by transfrag? Is there an example?

Another way to look at this question is that. What's the precise definition that two transcripts are considered equal and thus my experiment has positively assembled the transcript.

If some exons are missing in one of the samples then the introns will, by definition, be different. What this allows is for the bounds of the outermost exons to vary a bit. This is particularly useful for exon 1, which often has lower coverage.

Thanks for the reply. However, I'm still not very sure how two transcripts are compared as stated in the paper. In this context, what's the precise definition of a match? Does that mean if I have 10 exons in the reference, and I get 8 of those exons (excluding the first and last exon), it's a match?

Forget about exons, you can clearly see that what you posted doesn't mention them.

Yeah, that's my question. What do they really mean in the paper? I tried to digest it but I couldn't understand what they meant.

Draw out a few example isoforms on a piece of paper. Have one skip an exon. Are the introns then the same between them (no). What if the exons are the same except the TSS or TES differs a little, are the introns then the same (yes).


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IC50 calculation
I am a computer science student and I'm in an internship at a genomics and biotechnologies research institute. My current task is to calculate the IC50 and the EC50 given a set of data as a table.

The thing is, I am required to find a way to automate these calculations, currently working in excel. Which proves to be really difficult for me having no biology background. I have asked around and the people there kindly explained to me what the IC50 is and why it is needed, how the data is gathered, what tools they use to gather it and so on.
My problem though, is that what I need is a way to calculating it. A mathematical way, something I could use to write a formula in excel, or preferably a software I could write.(Once I know how to calculate it)
During my research I found this video on how to calculate the IC50 using an excel macro function, but I do not know if it actually works, having been provided a limited ammount of test data. (I am not sure on how reliable that algorithm is either)
https://www.youtube.com/watch?v=ynMcHziZhvs
Can someone please help me with an actual mathematical way to calculate the IC50/EC50?
My reading seems to not be of very much help no matter how much I try to use the internet's free resources to gather theoretical information about the topic.
Ok the question seems to have been marked as off-topic homework because I didn't present my way of solving it. First of all, it's not homework, it's a work problem I've encountered and need help with. Second, here is my attempt at solving it using an excel Macro

Function HalfWay(Ys As Range) As Double
    Dim pMin As Double, pMax As Double
    pMin = WorksheetFunction.Min(Ys)
    pMax = WorksheetFunction.Max(Ys)
    HalfWay = pMax - (pMax - pMin) / 2
    End Function
Function ECIC(X As Range, Y As Range) As Variant
    Y50=HalfWay(Y)
    Dim iRow1 As Integer, iRow2 As Integer, Asc As Integer, X1 As String, Y1 As String
    If Y.Cells(1, 1) < Y.Cells(2, 1) Then Asc = 1 Else Asc = -1
    iRow1 = WorksheetFunction.Match(Y50, Y, Asc)
    iRow2 = WorksheetFunction.Match(Y50, Y, Asc) + 1
    X1 = X.Cells(iRow1, 1).Address & ":" & X.Cells(iRow2, 1).Address
    Y1 = Y.Cells(iRow1, 1).Address & ":" & Y.Cells(iRow2, 1).Address
    ECIC = WorksheetFunction.Trend(Range(X1), Range(Y1), Y50)
    End Function

This code basically draws a line in memory between the points that are before and after the IC50/EC50 point on the graph and calculates the EC/IC's corresponding concentration based on its actual effectiveness. I am not sure how reliable this method is though.

Hm... Does it answer your question - https://www.youtube.com/watch?v=fMghQw2Ry2c

I'm voting to close this question as off-topic because it is poorly researched. Formula's can be found o'plenty by a simple google search. As a computer-science student, implementing a few numbers into a regression based on a known function should be peanuts.

See wiki pages on  IC50 and EC50.

I have been through that, Ilan, but there's the IP and the SP there that I cannot gather from my data so that's a dead end for me aswell. And thanks for the links AliceD, but I've already gone through them with no significant breaktrough. I mean seriously, who doesn't look at wikipedia first...

Problem with question is that you should ask about biology here, and about programming on StackOverflow. It is two different issues: biological -- how to model, programming -- how to implement.

Again, if you have a model, you should be able to ask how to fit data. Or learn on your own. These are two different issues: fitting/math and model/biology. Is that clear?

I am not voting to reopen - the homework vote to close is not just used for homework (http://biology.stackexchange.com/help/how-to-ask), but those showing poor research effort. You ask for a "mathematical way to calculate the IC50/EC50" - the script you've posted doesn't really show an attempt of self help, try finding the calculations for yourself, then show the maths - not a computer script, and tell us what you don't get. Also as it stands the question is only accessible to those familiar with excel macros

You don't seem to understand me. I have done my fair share of research, meaning 2 days with no actual results. The thing is, I can read all the articles I want, I don't get what they're saying though. Because I have no biology background. And all I can research is following that path which again, yields no results for someone who wants to calculate not know in theory. The reason I'm not posting on Stack overflow is because programming is not my problem here. I don't know what to implement. I know what they all mean, but not how to process the data, what to do with it.

Also, the script uses a virtual graph which is geometry which is math... I don't have what calculations to show besides that, as that's exactly what I'm asking here. How do I calculate. I need to be able to solve it on paper. My mind isn't able to comprehend a process of calculating something just by knowing what it's used for or what it means. I need formulas, statistics, something palpable... Only from there am I able to build my way to the result.

You don't have to post the excel macro. By effort we mean the basic idea or an approach that you have tried or you think is reasonable. The macro would be of no help if you do not explain what approach or analytical methodology are you trying to implement. First step is to understand what IC50 really is. I had answered a similar question in chemistry.SE; you can have a look there.

As I understand, what you really asking is:

What is the mathematical model one can use to fit drug lethality/efficiency data?

With answer to that you can go to stackexchange and bug them for fitting solution in language of your choice.
However, answer to that is quite complicated, it depends on your system and experiment. And also, how well you want to model your observation.
I'd suggest start with something like 4-parameter sigmoid, which in your case will degrade to two-parameter sigmoid: LD50 (shift along X) and steepness (how fast you transition from life to death) with edge cases that are either 0 or 1.
Now, this paper discusses one model (4-parameter sigmoid). It looks roughly like $y=\frac{x}{1+e^{\alpha(x-LD50)}}$, where $\alpha$ is steepness parameter
Another way to do such fit is to use error function. That is an integral of gaussian distribution. I do like that approach (theoretically) because normal distribution is important in data analysis of independent observations, and many random values in biology behave normally.
Let me reiterate. You have to have a model for your data in the first place. Maybe lethality drops down a little after LD50. Maybe you have some other weird stuff. What you can do is to pick a model and then see how well it describes your data.

The drfit and drc packages in R provide tools for such fitting of dose-response curves. Working with these R tools may be more efficient than writing new code or trying to force Excel to do things it really isn't meant to do.

@EdM It is not about what software you are using to implement the model. What is important is to understand or formulate a model and aaaaaa is talking about an example model.

@WYSIWYG : agreed, but the OP seemed so focused on the implementation that I hoped that knowing tools were available would allow more focus on the model.

that is useful, also those pages discuss models.


text:
Why and how does uniprot list around 150,000 proteins in the human genome?
Using organism:"Homo sapiens (Human) [9606]" as a query in uniprot returns about 146,000 proteins. I was under the impression that there were only 20-25,000 protein coding genes in the human genome. Is this something to do with splice isoforms, like those from SpliceProt, or another splice isoform database or tool?

Well you are assuming one sequenced genome/proteome per NCBI tax id. That is no longer true. So if you click on the proteome filter it decreases by half.
Which gets you into the 60,000 range. Now not all of these are "different" conceptual proteins, many are artifacts from the way GenBank/EMBL/DDBJ interact with the TrEMBL section of UniProtKB i.e. they are not normalized in db speak.
So for the human case you also want to add the Swiss-Prot filter to get a decent proteome that gives you about 20,000 proteins. Corresponding to the predicted/confirmed human gene count.
In all bioinformatics databases you need to pay attention to difference between database records and biological concepts. They rarely map cleanly one to one. In this case an UniProt record is not a protein, but information about a protein and a different record could have information about the same "protein". Or at least the same under some definitions of "same".
See the announcement of the draft human proteome in UniProtKB
The known isoforms are most often stored in the alternative products section of an UniProt entry. In some rare cases when the splice variant has a completly different biological function they are described in separate UniProt entries. For UniProtKB/Swiss-Prot Human there is a near 1 to 1 relation between genes and proteins. Cases as above and fusion proteins are the exceptions to this rule.
TrEMBL tries to automatically reduce redundancy in INSDC by auto merging entries in the same taxid and now proteome that have an identical reported sequence. However, variations of single gene products due to mutations and or limit what auto merging can do. For example there are 8 records for the P53 gene in TrEMBL today. Many of them from mutants, i.e. cancer genomes etc...

Since most proteins exist in more than one isoform, the number should be higher than 20.000.

@chris in UniProtKB isoforms do not get an independent record. See neXtProt for an isoform centric database of human proteins.

Very insightful answer, thanks. To be clear, these some 100,000 isoforms and artefacts are coming from GenBank, EMBL and DDBJ and are presented as TrEMBL entries?

The key point is that there are more proteins than genes because so many genes exist in multiple splice forms. You should not expect number of genes and number of proteins to match up.

There are 20+ thousand genes in the genome, but each of these can produce multiple proteins. In addition to this, you have protein fragments and cleavage products further increasing the number of entries.

I was also hoping to find out specifically where or how uniprot finds the information on those additional products.

@GoodGravy Proteomics data I presume

@GoodGravy A lot of them come directly from papers and other databases like NCBI. For example, B7U540 is an entry originating from me (via NCBI, since I never submitted it directly to UniProt).


text:
Operators and Enhancers/Silencers
Wikipedia has two images, of a eukaryotic gene and of a prokaryotic gene.
They show the difference that the prokaryotic gene also has an operator while the eukaryotic gene does not. Both also have enhancers and silencers separately. I thought enhancers and silencers were types of operators. Is this wrong?

Operators were classically defined by cis-Dominant mutations, located upstream of the protein-coding region of a gene, that rendered the gene's expression constitutive, or un-regulated.  This was before the promoter was defined as a separate control element.

Enhancers and silencers are binding sequences for transcriptional activators or repressors, in which case the sequence is often located some distance upstream or downstream of the gene it regulates. See regulation of transcription for information about how these interact with their target genes (through DNA bending, mediator, etc.). A note about enhancers and silencers, though, they're not necessarily required for transcription: they help the gene attain robust up- or down-regulation of transcription.
The operator, on the other hand, influences whether the promoter will do something, or nothing. If we're talking about inducible systems, the repressor is bound to the operator, blocking action to/from the promoter (an inducer will bind the repressor and keep the operator from blocking the promoter). If we're talking about a repressible system, the repressor will need a corepressor to bind the operator to abrogate transcription by blocking action to/from the promoter.


text:
Why is there a seeming dichotomy between mobility and photosynthesis?
At least among more complex organisms, I cannot think of any examples of highly mobile species (like animals) that also incorporate photosynthesis. Perhaps there are examples that I'm unaware of, but even so it seems to be exceedingly rare.
Is there some good reason for this, or is it a mere chance of evolution?
I could speculate, perhaps, in that photosynthesis just doesn't provide enough energy for the relatively high metabolism of mobile species; but even then, there seems there should be a "sweet spot" where some level of mobility would still be "worth it" for a photosynthesizing species, rather than the strict dichotomy that seems to be observable, so I naïvely find that explanation somewhat dissatisfactory. There just seems to be little reason for animals to not practice photosynthesis, if only to be able to eat less than they need to without it.

Interesting question. I would think that if you are mobile, and able to eat other non-mobile organisms that can't run away, then there's a pretty strong reason not to do photosynthesis: it's way faster to just swallow a bunch of carbohydrates in one bite rather than synthesize them all from scratch.

@Roland, I think nature shows that it's not always easy to "just swallow a bunch of carbohydrates". ;)

The difference in energy requirements of a motile species make photosynthesis an unsuitable form of primary energy generation for them.
Since plants are sessile, their energy consumption rates are lower. Plants have approximate respiration:photosynthesis rates of 0.35-0.9, as can be seen in this table (click to enlarge):

Once the energy consumption rates exceed 1, the organisms will, by definition, no longer be full autotrophs, as they will need to obtain their energy from alternative sources. Therefore, the relative low energy content of sunlight makes it impossible for motile animals, which have a larger energy requirement, to survive fully via photosynthesis.

Why be mobile? To follow the sun?
Plants are mobile. Their seeds are. We have plants living on other plants.
Once they have a spot on the sun though moving does not necessarily improve your situation, being stationary and defending your territory though does. (Growing taller, deeper roots, wider crowns)

There is at least one species of highly mobile animal that can photosynthesize, depending on your definition of "highly mobile":
Sea Sheep? This Adorable Sea Slug Eats So Much Algae It Can Photosynthesize
The catch is that this animal does not produce its own chloroplast.

There are unicellular eukaryotes that photosynthesize and are very mobile.
Many are in the phylum Chlorophyta.
This one mentioned below is used for research and protein production, and can live on eating organic compounds in the dark. In the lab you dont need to stir small containers growing them - they move themselves to the light.
https://en.wikipedia.org/wiki/Chlamydomonas_reinhardtii


text:
Human Bones classification and anatomy quiz
I'm a junior Biology Student and I came across this Human Anatomy Question:
In respect to the bone characteristics, mark the correct answer:
A) Even bones: Palatine, Inferior jaw, Parietal.
B) Examples of Long Bones: Sternum and Radius-clavicle.
C) Some Mixed Bones are (I couldn't find a better translation for "ossos mistos" in portuguese): vertebrae, ribs, hip bones.
D)Plane Bones protect organs and form cavities, for instance we have: Ribs and Sternum.
E)Odd and Plane Bones: Occipital, Frontal and Sternum.
I am almost sure that options A through C are incorrect. I'm between options D and E, but in option E I am really sure only that the Sternum Bone is correct. I couldn't find a reliable source that said explicitly that the Occipital and Frontal Bone are Plane and Odd.
And I think option D has a flaw mainly because the Sternum Bone does not form any cavities.

As you not in your question, I think there are some difficulties in translation. I suspect that "plane" should be translated as "flat", that "mixed" is likely "irregular", and "odd" and "even" are "paired" and "unpaired". Does that sound right?

If you are voting down, please leave a comment.

Why do you think the answer C is incorrect?  %)

@kmm - here a new downvote. I am downvoting because this is a schoolbook example of a  set of dry, contentless textbook-answerable questions not quite interesting for this community at large. I can't vote for closure as it is on topic. So, a downvote it is.

@AliceD I disagree. Here's a question with a valid attempt at answer, seeking clarification. Seems like a reasonable homework question. Maybe not the more interesting, but valid and worthy of answering.

@kmm - it's a downvote, nothing more. I voted to leave open. I support this question, I just don't think it rocks because it is so textbooky.

It would be good if you posted the original text in Portuguese so someone fluent in both languages can translate it better, as is the translation issues are preventing the question from being answered.

@Jessica Veloso (if you ever return to SE), did you ever get the answer to see if our attempts at translating were correct?? :p

@KMM's comment above appears to be on the right rack.
"plane" = "flat"
"mixed" = "irregular"
"even" & "odd" = "paired" & "unpaired"

That being said:

A = FALSE because jaw bones are not paired
B = FALSE because sternum is not a long bone (it's a flat bone)
C = FALSE because ribs are not irregular bones (they're flat bones)
D = TRUE because both are flat bones and protect organs
E = FALSE but ONLY under the assumption of the persistence of a metopic suture (frontal suture) causing the frontal bone to be split (and therefore "paired").

If I had 90 seconds to answer this question I'd mark answer "C".
Vertebrae & Ribs & Hip bones all are mixed bones.


text:
Can we change our dopamine baseline levels?
Can we change our dopamine baseline levels? High dopamine levels improve alertness, problem solving, but may also cause anxiety and aggression.
I've read that smiling and laughing, eating certain foods, or having unexpected rewards can elevate dopamine levels in the brain. I also read that expecting a reward in the future (such as an upcoming vacation) elevates dopamine levels. Can these actions, if repeated over a prolonged period, increase baseline dopamine levels? Or will dopamine return to original levels once these actions are stopped?

Welcome to Bio. I slightly changed the wording of the question. Feel free to roll back if it is not to your liking.

Usually the nervous system undergoes an adaptation. So you would need stronger stimuli to elicit the same response.

Feelings of pleasure and reward are transient in nature. Similarly, the dopamine release in the reward centers (the limbic structures) is transient, namely in the order of seconds (Rebec et al., 1997).
One way to chronically elevate dopamine levels is by administering certain drugs. A notable/notorious example is methamphetamine, which elevates mood and generates euphoria for 8-12 hours. However, after chronic use, people may report a lack of motivation and anhedonia when they stop taking the drug. Anhedonia is an absence of pleasure in response to acts that had previously been pleasurable. Anhedonia may be reported as long as 2 years after the last use of methamphetamine in addicts. Chronic use of the drug overstimulates the dopamine neurons in the limbic system (and elsewhere), and destroys the dopamine receptors, explaining the anhedonia.
Hence, even with hard drugs like meth, the effects on dopamine levels are transient, just less transient as with physiological reward responses.
Reference
- Rebec et al., Brain Res (1997); 776(1–2): 61–7

Actually, I was wondering what would happen if a person was born with naturally high baseline dopamine levels. From what I've read, high baseline dopamine levels can also cause anxiety, like low baseline dopamine levels. So I was wondering if this person could permanently lower baseline dopamine levels.

That is an entirely different question altogether, as your original post is quite explicitly asking for dopamine enhancement. When formulating questions be aware that folks like me can't read your thoughts, only your post. I suggest to post your question as a new one. It sounds interesting :)

No worries Yvonne. We're here to help.


text:
Is Circle of Willis unique to humans?
I understand that Circle of Willis is a circulatory anastomotic system that provided blood to the brain.  I want to understand if this system is unique to humans or does it exist in other species or mammals to be more specific?

This is very trivial - it's a one word answer, no. I got my answer by go ogling "circle of willis dogs" hence closing as poorly researched.

I agree that the question could have been rephrased in a better way. Also, 90% questions here can be googled. It's more about getting pointed in the right direction - to publications and established research.

See the help pages on writing good quality questions

I found two references that talk about the circle of Willis in different kind of mammals so i think it's right to say that this particular anastomotic system of arteries is not exclusive to humans.
Here are the two references:
http://www.neuroanatomy.org/2008/054_065.pdf
http://www.ncbi.nlm.nih.gov/pubmed/14651482


text:
How to mimic / approach some animals/insects' anabolism?
This article states that some shelled animals - spiders, scorpions, crabs, worms and other creatures - have metal atoms in their claws, jaws and fangs.
I believe through anabolism, since they eat sand, soil and insects that are full of a mix of those.
For most human beings, it would seem silly to eat soil or sand, or even insects - and yet, I wonder if our bodies would be able to digest and create anabolic processes around, for example, metals, in such way that we would end up having stronger bones / teeth / hair / nails (or other things).
To a certain extent, I also wonder how anabolism isn't use to regenerate cells that become old or faulty in the body as we age or get sick (a special diet would help "regenerate" blood balance, feeble skin, brain cells, etc, if we knew what foods would turn into these cells the best by anabolic process).
This question is becoming a bit confused, so I'll end up rephrasing it: is there a document / research / map / experiences of all the foods & materials that the human body can not only digest (and in what quantities) but also how they transform into our cells (and a list of foods / materials that are NOT taken into account by anabolic processes). I.e., at what speeds they can become part of us, and how they can/could change and alter the body cells in a strengthening kind of way (not in a way that makes us sick or dead).
NOTE: I am not a scientist, just a writer, but I am fondly interested in the subject.

Teeth do have a metal - Calcium. Calcium phosphate also mineralizes in the bones.

I'm not sure if bumping is a concept on this forum but I am interested to see if there are any answers. Did the OP find anything satisfying? I can see the creative implications here and I'm intrigued.


text:
What would happen if brain neurons did not reduce their sensitivity to neurotransmitters after prolonged exposure?
From my understanding, neurons decrease their sensitivity to neurotransmitters by reducing the amount of receptors on the cell membrane in response to sustained neurotransmitter activity. One explanation I heard is that cells do that to protect themselves from damage.
This makes me ask - what kind of damage could be caused by sustained neurotransmitter activity in the brain, if cells did not reduce their sensitivity? Can a brain survive/thrive if neurons always had the same number of neurotransmitter receptors?

I never heard about damage. However, decreasing number of channels/receptors in synapse leads to lower noise among other things. for example, you need to support number of channels metabolically.

Short answer
As far as I am aware, neurotoxic effects of chronic excitatory stimulation are not prevented by receptor trafficking.
Background
I think the question assumes that 1) neural damage related to continuous activation (excitotoxicity) is preventable by 2) the dynamic regulation of receptor numbers on the neuronal membrane. As far as I can see, these two processes are unrelated.

Excitotoxicity is

...the ability of glutamate or related excitatory amino acids to mediate the death of central neurons [...] for example, after intense exposure. [...] Excitotoxicity has substantial cellular specificity and, in most cases, is mediated by glutamate receptors. On average, NMDA receptors activation may be able to trigger lethal injury more rapidly than AMPA or kainate receptor activation, perhaps reflecting a greater ability to induce calcium influx and subsequent cellular calcium overload (Choi, 1992).

Hence, it is the influx of toxic amounts of Ca2+ that induce cell death. Not much Ca2+ is needed to accomplish this. For example, a status epilepticus (a sustained epileptic seizure) can lead to hippocampal damage, due to persistent excitation and glutamate release (Meldrum, 1991). Epileptic seizures lasting longer than 5 minutes are regarded as dangerous in this sense and after 30 minutes they are potentially fatal (often not directly related to excitotoxicity though) (Cherian & Thomas, 2009). In this short time span regulation of cell-surface receptor densities are unlikely to play a substantial role. For example, serotonin-specific reuptake inhibitors need 2 weeks to lower the amount of 5HT1A receptors (Tylee & Wolters, 2009).

Dynamic regulation of receptors. The regulation of the number of receptors is linked via feedback loops. A great example is the way glutamatergic AMPA receptors are regulated through endocytosis (Fig. 1).

Fig. 1. AMPA receptor trafficking. Source: Anggono Lab.
AMPA receptors are the principal receptors that mediate most of the fast excitatory synaptic transmission in the mammalian brain (Purves et al., 2001). The dynamic trafficking and proper synaptic targeting of AMPA receptors are crucial in determining the strength and plasticity of excitatory synaptic transmission. This dynamic regulation may also impact learning and memory processes. The process of receptor trafficking is, as far as I know, typically not associated with emergency rescue operations to prevent excitotoxicity. Nonetheless, these mechanisms, are essential to sustain an adaptable brain capable of learning, forgetting and restructuring itself.
References
- Cherian & Thomas, Ann Indian Acad Neurol (2009); 12(3): 140–53
- Choi, J Neurobiol (1992); 23(9):1261-76
- Meldrum, Epilepsy Res (1991); 10(1): 55-61
- Purves et al., Neuroscience. 2nd ed. Sunderland (MA): Sinauer Associates; 2001
- Tyllee & Wolters, BMJ (2007); 334(7600): 911–2

In principle, many neurotransmitter receptors work as ion channels and the actual mechanism of signalling involves allowing the influx/efflux of calcium, potassium, magnesium, etc. A good example of this is the acetylcholine receptor. Presumably, if the cell retained the same number of receptors even in the presence of abundant ligands, the cell would flood with ions. Not only would this render the signalling pathway insensitive it may lead to survival issues for the cell/inappropriate cross-talk with other pathways.
That is at least how it should work in the models of neurotransmitter signalling I'm familiar with, it seems quite likely that a neuro lab somewhere has a cell, or animal model that can provide a real world answer.