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Immunology Book Suggestion
Which book will give a brief account about B-cell development so that it covers two questions about the following cells:

Plasmablast
Plasma cell
Memory B cell
Marginal zone (MZ) B cell
B-1 cell
B-2 cell
Regulatory B (Breg) cell

Where do they lie in the course of B-cell development and differentiation?
What are their functions (outline)?

P.S. I need to know the development part in details rather than the functions.

http://www.amazon.in/Kuby-Immunology-International-Judy-Owen/dp/1464137846/ref=sr_1_1?s=books&ie=UTF8&qid=1477876761&sr=1-1&keywords=kuby I feel is the best for learning.. But as said, for something like immunology, you must complement a text with nature reviews

You should probably check out a review. Most basic textbooks will not delve into the various subtypes. Wikipedia has entries on all these types of cells. Did you not find that informative?

@WYSIWYG Not really, that's why I posted here. Besides I'm skeptic about wikipedia. It doesn't always contain the right information.

In this case, the wikipedia articles are not stub and they cite relevant sources. Perhaps you can clarify what exactly you are looking for. If you want detailed information then you should go for a review. For e.g. this is a recent review on B-reg cells.

@WYSIWYG Well I have already put that in my post, questions 1 and 2. The problem with these reviews is that they though mention what the functions are but don't highlight where the cells lie in the course of B-cell development. However as a last resort I have thought of reading Kuby Immunology. I have been avoiding it because its too much detailed.

The question - "what are their functions" needs some elaboration. You can go into great level of detail with that. Kuby Immunology does not have these details; at least the version that was available 8 years ago.

Perhaps you should check this review out: http://dx.doi.org/10.1146/annurev-immunol-020711-074934

This question is a possible duplicate, as we also have a question about that: http://biology.stackexchange.com/questions/13729/modern-immunology-textbooks

I have been through it once before. That's related but not duplicate. It's a more broad question.

@WYSIWYG Thank you but I don't have access to the review article. Besides I've edited the body to make more suited to Bio SE..

@SanjuktaGhosh you could edit the title too as 'immunology book suggestion for following topics' or 'immunology book suggestion to get brief overview of B-cells development' or such. it may help.

I have found a book that explains in a quiet simple way the entire B-cell development and differentiation stepwise and covers the two questions I was looking for. It is Kuby Immunology, 7th Edition.
Except the Breg cells which is a recent discovery every cell was well discussed. I went through this to learn what the functions of B reg are.

The best immunology book hands down is Janeway's Immunobiology. There is no debate among the immunology community.  The middle section is devoted to B cell development.


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Fish ID? Small, yellow-finned, tropical fish in Thailand
I have not had any luck finding the yellow fish shown in the photo in any of my fish books. I saw them in many places, so they are fairly common. This observation was at around 15 meter depth.
I hope someone here knows it.

With a little Google search I found similar fishes. Says it is golden or yellow damselfish or possibly lemon damsel but I'm not sure because there are some different names for this picture or different pictures for searching same name can be found on Google.
Also, I found a fish identification page on which this fish can be found.
Is this your fish?

Yes, I think you found it. A Damselfish was also my first guess, but I thought I had ruled them out because none of the books or sites that I looked through had damselfish with fins like this.
Here is a link to the specific Fishbase entry: http://www.fishbase.se/summary/Amblyglyphidodon-aureus.html

source: Stack Exchange

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

sort: votes


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Why does hair know when it needs to stop to grow
I'm still not quite sure if head hair grows endlessly, or if it stops at some point, but that's not the question.
When the hair on my leg grows, it obviously doesn't grow endlessly, but it also stops at some point. I learnt that hair is dead matter, so why does the body know that my hair reached maximum length, and realizes I cut it when I did?

That's an awesome question! Let me help you rephrase, as I don't have a direct answer; why does hair stop growing at certain lengths, and differentially at various locations on the body?
There are three stages to hair growth:

Anagen phase- growth
Catagen phase- transition
Telogen phase- rest
(then falls out!)

You're asking why and how the anagen phase stops, or more concisely, what processes cause anagen phase to cease and proceed to transition to a degenerated rest.
The indirect answer I have for you is this: there doesn't exist a definitive mechanism for how the the telogen phase is induced- that is to say that the process by which the hair-producing follicle "turns off" it's cycle to come to a halt has not yet been fully elucidated in the literature and remains a discovery to be made.
I hope I've helped you understand your targeted question

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


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What is the evolutionary advantage of having polymorphisms in MHC?
The MHC genes are widely polymorphic and hence cause an issue in tissue matching pre-transplantation. Why is there such a polymorphism?
I know that different polymorphisms in MHC can lead to variation in the immune response to the same offender. But then, if there is a difference, shouldn't there be a selection for those that mount a better response?
So, why the polymorphism?


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What is PDMS used for in microfluid models?
When creating a microfluidic model using polydimethylsiloxane (PDMS), is PDMS used only as a stamp to lay proteins in coverslips or can cells be cultured in the channels or patterns created in PDMS?

can you add some information about PDMS to those users who are not as familiar with it? it would greatly strengthen/clarify your question. Thanks for your contribution!

Well, it's definitely usable for more than just stamps - you can certainly perform experiments on cells within PDMS channels/patterns, etc. Not sure about long-term culture.  (PS: I don't think this question needs information about PDMS - for those who don't know: https://en.wikipedia.org/wiki/Polydimethylsiloxane)

@AJK, it does need more information about PDMS but not much. PDMS is an abbreviation so the full name should be included in the question.

Thank you for your responses. I did include the full name. But I have no problem providing more information about PDMS. So, again, PDMS stands for  Polydimethylsiloxane. it's a bio-material with several applications. the main properties of the material are that it is bio compatible (non toxic), it is very elastic, chemically stable, transparent, so it's perfect for imaging etc. PDMS is used in soft lithography as a stamp to transfer patterns onto glass and then culture cells in those patterns. I was wondering if besides acting as a stamp PDMS structures could also be used to culture cells.

I remember a friend of mine used to make microfluidic devices by pouring it in a cast and allowing for solidification. Basically, it is a building material. It can be used for cell cultures but then the matrix has to be made "bio-compatible" by coating it with appropriate substances.

PDMS in fact is established to be a reliable material for cell culture in many microfluidic devices.
Here are several papers (Titles) including reviews on microfluidic devices using PDMS:

Microfluidic devices for cell cultivation and proliferation Here
Adhesion patterns in the microvasculature are dependent on bifurcation angle Here (Microvascular Research)
Advantages and challenges of microfluidic cell culture in polydimethylsiloxane devices Here
A physiological model of the tumor microenvironment for screening drug delivery systems Here (Cancer Research Proceedings)
A Novel Dynamic Neonatal Blood-Brain Barrier on a Chip Here (Plos One)
A novel microfluidic assay reveals a key role for protein kinase C δ in regulating human neutrophil–endothelium interaction Here(JLB - Journal of Leukocyte Biology)

My research at Temple University is actually based on a microfluidic device to study cell-cell interaction in a real-time fashion.
Majority of established protocols are using fibronectin or collagen, and in the case of tumor cells culture, matrigel for extracellular matrix. Devices are being coated with the ECM protein and then cells can be cultured in the device.
We have shown that in our microfluidic device, human umbilical vein endothelial cells (a.k.a. HUVECs) are forming a complete 3D lumen in the channels.
It is important to note that due to the elasticity of the PDMS, cells are needed to be under physiological flow conditions. Otherwise, it was shown that the cells start to detach from the PDMS. Under such physiological conditions (flow, media, gas exchange), cells can be alive and functional up to a week or two, depending on the design. In our system, the last two publications, cells are functional up to 2 weeks and 1 week respectively.

Could you link the cited papers?As of now the citations are meaningless. +1 for this answer and welcome 2 Bio.


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Dynamic instability of microtubule
Why is it said that , warmth facilitates assembly and cold facilitates disassembly of microtubule?
But till now what I  had learnt is that as temperature increases so the kinetic energy of molecules increases so does the order decreases.
So what is the reason behind the above phenomenon?

I would look at chemistry. Look for heat dependent reactions.

In the paper "Phase diagram of microtubules" Fygenson, 1994. it's evident that with increasing temperature the length of the aggregates is growing. But it of course depends on other additional parameteres like concentration and I assume the type of the protein - alpha and beta-tubulin.

thanks for showing interest, but I want reason for that graph.

There can be many reasons: simple Brownian dynamics is the best explanation I think.


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Why don't we see life form again and over again?
If life formed on earth by natural laws, why can't we observe the formation of life from matter today? Is it because this is a rare phenomenon? It seems just after formation of earth life formed on earth and around 2-3 billion years has passed. It must be enough time for life to form several times from scratch.

Evolution takes long and there has been a lot of evolution in these billion years... Also it doens't seem to be logical to start over again with evolution, It took so long to "create" the life forms that exist today and to adapt them over and over again, why do you think it would start over again?

Very colloquial comment incoming. https://en.wikipedia.org/wiki/Abiogenesis Refer to abiogenesis. It is extremely rare to have abiogenesis occur. It has, of course, occured once and once only in our world. But it is only because we are alive therefore abiogenesis has to have occurred. So the miniscule chance of abiogenesis, to us, is not there. Given that you struck the lottery, what is the chance that you have struck the lottery? 100%. To have it occur again is then extremely unlikely.

2-3 billion years is honestly nothing in the scale of abiogenesis. 10^(10^99) years, maybe. Waiting on Remi to give a legit answer to this question though.

I think one important problem would be competition. If a new kind of primitive life form formed from inanimate matter today, it would probably we eliminated ("eaten") rapidly by the overwhelming presence of current (more advance) life forms. Another problem is that the conditions in Earth at the time abiogenesis happened before may have been very different from todays conditions, as the environment in Earth has been dramatically changed by living organisms.

@LiuTianyi: We have no idea how many times abiogenesis has occurred on Earth, all we know is that all life on Earth traces to a single common ancestor but that ancestor need not be the only time life emerged. There may have been competing life forms that lost out to our ancestor.

@LiuTianyi "It is extremely rare to have abiogenesis occur" That's not clear at all. There is no evidence that it is unlikely under the conditions that actually led to abiogenesis (which are unknown).

@LiuTianyi Given that you struck the lottery, what is the chance that you have struck the lottery? 100%. To have it occur again is then extremely unlikely. Since you pose this as a statistical argument, be aware that the odds of the event happening again are the same as it happening the first time, unless the event occurring impacts the conditions for the event happening a second time in a statistical sense. (if you just flipped a heads, a tails does not become "more likely" for a future flip).

@James And I did not say it would be. My point is that if a condition is already given, P (tail | tail) is 100%. So however small the chances of P(tail), it wouldnt matter. What would matter is another event of tail. This time, it would acquire its original probability. I'm arguing more closely towards philosophy in the sense of determinism than statistics.

@LiuTianyi It is unclear what this has to do with determinism. Please elaborate.

No-one knows how life was originated.

How do you know there have not been any? Whether we have the capacity to find and observe it is as much of a question as to whether it has happened.

The first life was probably so fragile and simple we would likely not even recognise it if it did appear. We don't know exactly how, or where, life first appeared but nearly all theories suggest simple collections of enzymes in protected environments that slowly gather the mechanisms needed for free-living life over time.
This works in the ancient world because there is no competition so even the simplest and most inefficient replicator is able to reproduce, spread, and advance. Today, any new life would have to compete with existing life which has had billions of years to evolve into highly efficient forms. A new abiogenesis event would simply pass unnoticed, a brief flicker quickly snuffed out by modern life.

It doesn't work in the ancient world, simulations in the laboratory can simulate sterile prebiotic conditions perfectly well.

@CountIblis Therefor we are still missing something from the simulations. Probably time.

Time doesn't solve the problem, the number of replicating steps of a self replicating system is in principle the important thing. If nothing happens, then you can wait till the cows come home, nothing will happen, because none of the steps necessary to get to the result are being executed. Simulations have yielded interesting results, as I point out in my answer,  nitrogenous bases, ribose, amino acids have been synthesized in the lab from simple inorganic chemicals, but under cryogenic conditions and intense UV irradiation.

@CountIblis: I cannot agree with your assertion that labs can simulate probiotic conditions perfectly well. We do not even know where life first emerged and even if we did our knowledge of the Earth that far in the past does not necessarily allow us to simulate those conditions precisely. Even then we do not know the timescale over which life emerged, a lab experiment running for days, weeks, or even years does not necessarily sufficiently represent a process that could have taken hundreds, hundreds of thousands or even millions of years.

@CountIblis we have RNA that spontaneously arises under lab conditions,  we know there are strands of RNA that can self replicate, so all you need is the laboratory conditions on a sufficiently large scale(like say the ocean instead of a beaker) to get one of the self-replicating strands. see a review of the study here, turns out we were trying to hard.http://www.nature.com/news/2009/090513/full/news.2009.471.html

@John This is interesting research, but I'm always going to be skeptical of  "sufficiently large scale" or "sufficient amount of time" wild cards being thrown around to make up for gaps. The larger scales being invoked must be based on rigorous science.

@CountIblis it not much of a gap, the sequence of the RNA formed is essentially random, the shortest know self replicating RNA is 165 bases long although shorter probably does exist. But that means you would have to run the lab experiment tens of billions of times to get one of those self replicating strands.  but with no other life to compete with it in nature the natural experiment would have occurred trillions of times a week over millions of years. Nature could stumble on the right sequence code through pure brute force.

@John Note that the fundamental problem with explaining abiogenesis is explaining how the chemistry of life evolved, not per se how the biomolecules arose. While explaining the latter has also been a big problem, it's the former that is seen to be the main subject of the theoretical debates, e.g. Leslie Orgel decades ago already suggested that you could get to RNA molecules in scenarios like described in that Nature article, but he demonstrated that it wouldn't get you to larger and larger functional biomolecules.

I find the study particularly interesting becasue of how little they did to get it to happen,  it turns out distilling and separating which everyone else did to speed up the process was the problem you need to leave the "soup" together becasue some of the early chemicals that form act as catalysts and buffers the later ones.

What you really need is to get the chemistry of life already implemented in a more primitive form before you even have RNA molecules. This is pretty much what Addy Pross is saying, while he dismisses the idea that life may not have evolved on Earth, his main message is to take serious the auto-catalytic properties of simpler systems.

Why wouldn't it, RNA is what constructs all the other biomolecules. RNA makes protein, DNA, RNA, ect. once you have something that self-replicates Evolution takes over pushing it to make better copies, collect and use resources more efficiently. ect. The thing I want to see is an attempt to make a functional cell using nothing but RNA and its products.

@CountIblis What do you mean by the "chemistry of life", he does a good job of explaining the formation of precursors, they persist becasue there is nothing to consume them, Clay is not needed in the experiment I linked. I'm confused your speaker does a good job of explaining how wholly terrestrial formation of life could occur, so whats the issue?

@John From a thermodynamic point of view I don't see how you can on the one hand avoid the OP's problem and get life started on Earth. A living organism is ultimately a machine that can e.g. exploit chemical potential differences to function and make copies of itself. Within an isolated system where there are such chemical potential differences to be utilized, a living organism is therefore a catalyst not just to make copies for itself, but for the chemical potential differences to be equalized, so it's just a way for the system to get closer to thermal equilibrium.

But if the system could get closer to thermal equilibrium without life forms being present from the start, then the life forms would not arise in the first place. What the life forms are doing, after all is exploit the fact that there exists a metastable state away from equilibrium, and letting the system get a bit closer to equilibrium instead of a lot closer, this allows for some room for the living organism itself to live far from thermal equilibrium. Clearly this requires the organisms to have arisen elsewhere where there were conditions that were even farther from thermal equilibrium.

Thermal equilibrium is not involved much in biology at least not at the micro organism level, they operate at the ambient temperature of the surroundings. Energy is what life exploits, very few things in nature are at the their lowest energy state, the sun, and winds, and volcanics and a hundred other things pump energy in to the surface of a planet. Its the reason the earth has lots of high energy potential molecules. Life exploits Gibbs free energy for the most part since temperature and pressure tends to be more or less constant in life.

with or without life the earth is nowhere near energy equilibrium there is plenty there for life to exploit, and the surface of a planet is not a closed system plenty of energy is flowing into it any given moment. life doesn't increase the entropy of the system a little it increases it a lot, to decrease it by a small amount in itself. It is a bit like mountain building in geology, pushing a mountain up is an increase in its potential energy but the underlying system that causes it is releasing so much energy that the small local reversal does not matter.

Well.. consider this... once life already exist... and a new life form spontaneous came into came into existence, how likely is the newcomer going to be able to compete with the current contender, who now has time to develop all sorts of abilities from being in an arms race between members of its own group. (A bit like how likely is a newly arrive group of cave men going up against a nation armed with Abrams tanks)
Also note... the first group of earthly life started polluting the sea and atmosphere with a highly toxic and damaging chemical... oxygen (the Great Oxygenation Event @The Oxygen Holocaust 2.5 billion year ago). And oxygen damages reactive chemical  group required to catalyse chemical reactions and oxygen also pretty much destroyed the rich chemical soup that life first arose. Even today there are many groups bacteria and archea that cannot tolerate oxygen.
tldr once life evolved, it destroyed the environment that allowed it to arise in the first place. Environmental destruction is a long held tradition of earthy life.
Also the free for all chemical buffet that was on early earth...  the first life to emerge would have would have eaten it all up. Leaving nothing, no building block for later life to to emerge form.

For a start you need an aseptic environment for a new, defenseless kind of life. All water containing environments on our planet conducive to new life are septic.
Primitive life forms are rare and less competitively robust and performant. The new life forms would be like worms that can't dig, and the current microbes would be like chickens, all mixed together in the same room.
I you had a stable warm C/H/N/O rich cave/seafloor environment which stayed protected for millions of years, you might get the first kinds of organism appear there. They would have 4 billion years less genetic sophistication than current microbes and funghi for attack, defense, fast adaption, diversification, speciation, pH tolerance, mobility, food selection, digestive processes, which today pervade and feed off every environment on earth.
The new life which took very long to evolve has to defend itself agains a lot of species of funghi, procariotes, eukariotes, animals and plants, while it is in the cave and after it leaves it.
If you brought back all weird jellyfish type ediacaran species today, and put boat loads of them into the sea, the fish and advanced jellyfish would decimate them and consume them. their primitive design makes them only food sources.
The advancement of a modern procariote compared to an instar life-form as the difference between 1970's calculator and an iphone in terms of performance.

The answer may be that life did not form on Earth. There is not even the slightest hint of evidence that life formed on Earth. The known facts about early lifeforms on Earth from fossils and everything we know about geology of the early Earth and the Early solar system is at odds with abiogenesis having occurred on Earth. One of the arguments against abiogenesis on Earth is precisely the question asked.
The problem is not just that we don't see life forming in a natural environment, as this can be easily explained away by invoking competition from other life forms. Also one can note that the conditions on Earth today are different from that of the early Earth (oxygen is poisonous to early life forms). A more fundamental problem is that we can't reproduce some of the fundamental chemistry needed for abiogenesis in the lab under conditions that have existed on our planet during the time life could have evolved.
E.g. the synthesis of ribose, which is the backbone of RNA from inorganic chemicals does not seem to be possible under Earthlike conditions. A recent experiment demonstrated that under intense ultraviolet irradiation of water, methanol and ammonia under cryogenic conditions at extremely low pressures one can form ribose in the lab. Similarly, we cannot get amino acids to form under Earth-like conditions, we again need to resort to irradiating interstellar ice analogues in near vacuum conditions.
We also need to consider how can we end up with only left or right handed molecules of each type as found in Nature. It has been demonstrated that replicating systems where both variants are presents, will lead to an end state where only one type will survive. But we then get domain formation where in different disconnected farts the symmetry will be broken in a random way. This may be good enough to explain why we only have left-handed life on Earth today.
An alternative idea is to invoke the fact that the Weak interaction does not respect parity symmetry. Now the Weak interaction is too weak to be relevant for molecular dynamics. But in radioactive beta-decay, this interaction plays a dominant role, beta-radiation consist of only left-handed electrons. One can then postulate that abiogenesis happened in an environment where there was irradiation by cosmic beta radiation, which would lead to an asymmetry in the breakup of chiral molecules, which would then be further amplified by auto-catalytic processes. This is the Vester-Ulbrict hypothesis, which was recently been successfully put to the test in the lab.
Another argument against abiogenesis on Earth is that the required far from thermal equilibrium conditions never existed on Earth, while they do exist in objects like comets and proto-planets. This is more general argument than the examples given above. Basically, what you want is to get to a collection of self replicating molecular machines from their simple building blocks, without there being any machines to build them from scratch.
Molecules in living organisms are synthesized using extremely complex molecular machinery such as the ribosome. Without such machinery, the natural environment has to play the role of the agents involved in the construction. What is needed are both far from thermal equilibrium conditions and places where half build, unstable molecules can be metastable, allowing the complete molecule to appear. This suggest that cryogenic conditions should play a role here.
We can also note here that life on Earth exists in a compartmentalized form, all the chemistry happens inside a lipid membrane (a cell). Many of the essential molecules would not be stable in a hypothetical environment that could have existed in Earth's geological history. Then just like life today exists mainly in conditions that were hostile to early life forms (the oxygen in our atmosphere would kill them), similarly it may well be the case that conditions on Earth have always been hostile to processes that could lead to abiogenesis.
The molecules essential for life as we know it may have evolved without any compartmentalization in the interior of comets or proto-planets (this would qualify as life in the sense of an auto-catalytic process that is capable of evolving), compartmentalized lifeforms could have arisen later there.
A different argument comes from the conditions in the early solar system and what we know about life on Earth from the geological record. The earliest evidence for life on Earth dates back to 3.7 billion years ago. These are stromatolites, which then shows that 3.7 billion years ago there were very sophisticated life forms on Earth.
Petty much all of the enormously complex molecular machinery found in modern cells had to be present already in the bacteria that formed these stromatolites. Abiogenesis would thus have had to occur quite some time earlier. However, from 4.1 to 3.8 billion years ago, the inner solar system was subject to what is called the Late Heavy Bombardment (LHB). During this period the conditions on Earth were rather inhospitable for life. Whether life could have survived impacts so large that oceans on Earth would have evaporated is a matter of ongoing debate.
One has to note here that the people who argue that life did evolve on Earth during this period, tend to favor LHB scenarios that are one the extreme limits of the geological scenarios, one then assumes that it was not that much of a big deal, e.g. the largest impacts could have been smaller than what most geologist think. However, recent geological evidence points in the opposition direction. It has recently been found that the size of the impactor that formed Mare Imbrium on the moon was enormously larger than was previously estimated. The impactor is now estimated to have had a diameter of 250 km.
Taking into account that the Earth is a much larger target than the Moon, so it would have been hit more frequently than the Moon and the largest objects to hit the Earth would also be larger than the largest ones to hit the Moon, the idea that perhaps the LHB was not so bad for life on Earth becomes quite problematic.
But the main argument against abiogenesis on Earth is simply the lack of evidence in favor of it; it shouldn't be a surprise that that things don't add up when one assumes the truth of a hypothesis that is not supported by any facts.

Is this your personal opinion, or original idea? If not, please cite where you got it.

@James There are entire journals devoted to this subject. My personal opinion is that life likely did not form on Earth, but it's not a personal opinion to say that there are arguments for this idea and then elaborating about these arguments.

The journal of astrobiology is a broad journal which ranges from education strategies to abiotic chemistry. Please refer me to the article that says "life came from space". I have heard similar arguments before and am curious to understand more on the topic. For example, when people refer to extra-terrestrial role in biogenesis, they usually refer to trace compounds required for nucleic acids which were found in meteors. They do not discuss complex life (which can be inferred from your answer - exciting if true!).

There was a meta discussion about citation a while ago. You have a lot of citations, but not the key ones people/I would want to follow up.

@James I'll try to dig up a few of such articles. But the essential thing here is not the chemicals but to get a complete working system. Addy Pross explains the importance of taking that view here. While he brushes away the possible extraterrestrial origin of life, the main point is that the chemistry had had to evolve into the chemistry going on in living organisms. He explains the crucial importance of exponential growth of self catalytic systems. It's not good enough to get molecules on Earth from space,  the chemical processes are also needed

I think part 2 is more interesting: https://www.youtube.com/watch?v=zkGb12xBKlM

While I think you raise a number of interesting points, I think you're strongly over-stating your conclusion and ignoring the major problems with any model that life emerged elsewhere. At most, asserting that life evolved extraterrestrially moves the problem but leaves it unsolved.

@JackAidley, and even more brings up a new question: if life emerged outside of earth, why don't we see life coming to earth over and over again? But other than that, I do not think this answer is so bad to be at -4. The individual statements are well-referenced (even if overstated a bit - but note the more careful 'may'-statements - which is merely a thing of style), explained in detail, and it is not off-topic. It is inherent to the question to be based on hypotheses (to not say opinion ...) as there simply are not enough data to explain the phenomenon. +1

This is an interesting and well-researched answer .. but to the wrong question. There is a lot here about what is often called 'Panspermia' but the question is surely about 'continuous generation' from the Earth. Although a possible extra-terrestrial origin for life is relevant it is only part of an answer - could this be revised to be closer to the question?

It turns out you don't need to make ribose, other more easily formed sugars will convert to ribose when bonding with phosphates.  RNA can be made with just easily formed feeder chemicals. http://www.nature.com/nature/journal/v459/n7244/abs/nature08013.html

There isn't currently enough evidence to put a significant probability against the idea that life formed on mars, and that life did not form in a previous solar system. The first life on earth for the moment are greenland stromatolites at 3.7bn yrs. If life formed on planets in the 9 billion years of sequence i/ii stars with less heavy elements to choose from, it would also have to escape the supernova and radiation of those larger and faster burning more violent stars, take refuge in ice and rock, and land on earth in favorable conditions. It's as likely as having a planet with a giant moon.


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Do pulled hair from the root grow back?
There is not much to explain, I'm wondering if pulled hair, for example of the head, normally does grow back again or not. In reddit, It says this may depend on the follicle integrity, if the follicle is  not hurt then it will grow back and viceversa. It is the case?

There's no harm in plucing a hair, but it won't do you much good

Plucking the hair will indeed get rid of the hair - but only temporarily

"The follicle (the little tube beneath the skin that produces the
  hair) is still alive and will produce another hair to replace the one
  that was pulled out

So actually if you DON'T damage the follicle (which is really rare, this could be the case if you remove skin) the hair will definitly grow back.
To get into more depth here is a figure that shows the root and the follicle so it's clear what the difference is:

I don't know in how much depth you want this question to be answered but if you are interested in the growth stages (which can influence the hair regrowth) you should take a look at this answer, I won't copy someone else effort here..
source: Randy Schueller (link)


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Can't identify this fish caught off NC coast

It was caught approximately 35 miles off the coast of North Carolina. I've been a charter fisherman for more than 25 years and never seen anything like it. Thanks for your help!

Could you add the size? It's quite difficult to judge from the photo.

i think this is a frogfish. there is multiple types of this fish. i think this is an Ocellated frogfish. frogfishes related to anglerfishes. memorizing animals by classification eventually helps with identification. little google search and using fishbase site about information helps. this sites very helpful about finding fishes.
fisbase frogfishes
frogfish site
this link says it can be found on North Carolina


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Where can I get a file/list of the common and scientific names of species?
I am searching for an un-encoded data file with common and scientific names for example of a few hundred species or tens of thousands, where I can search the common and scientific labels of organisms.

English common names or from different countries/languages?

I suggest using Wikidata, although extracting the information may not be straightforward.

English common names would be fine for myself, if you have various related resources it's always good to know.

Uniprot has a list of the controlled vocabulary for common and scientific names of species listed here.
An example entry:
ACAER E  111511: N=Acanthodactylus erythrurus
                 C=Spanish fringe-toed lizard
                 S=Lacerta erythrura

In the example the N is the scientific binomial name (Canthodactylus erythrurus), C is the common name (Spanish fringe-toed lizard).
ACAER is the id code, 111511 is the code for the taxonomic node, E means it is a eukaryote, and S is a synonym of either name.

The list contains 25336 scientific names currently, which falls short of the ~2.5m species in GBIF, or the 10s, or 100s of millions that are estimated to exist. The Uniprot list does, however, represent every organism included in Uniprot, which is widely regarded as being among the most comprehensive protein databases that exist today.

That's a fairy short species list though, if it is meant for general-purpose use (i.e. not specifically in relation to Uniprot data).

This is a worthwhile point. Uniprot hold additional lists for different strains that may account for some of the difference (i.e GBIF count each strain as a separate name, Uniprot packs many strains under 1 species name-not negligible for bacteria). I cannot verify any redundancy measures taken by GBIF and I cannot find any peer reviewed article of GBIF. This would explain a lot of over-estimation since both Uniprot and GBIF are pulling species names from many of the same external databases.

Just a note here, this list includes many viral strains, which may or may not be something you want.

Maybe not a direct answer to your question, depending on what you mean with "unencoded data file", but the Global Biodiversity Information Facility (GBIF) has an API where you extract data for species names. Their database includes common names (aka vernacular names) when they have that, and often common names from different languages. Using this API, you can extract data and construct a name file for a particular taxa that you are interested in.
As an example, this is the list of the first 20 vernacular names found for Passer domesticus (House sparrow):
{
   "endOfRecords" : false,
   "results" : [
      {
         "language" : "",
         "sourceTaxonKey" : 100220560,
         "source" : "Global Invasive Species Database",
         "vernacularName" : "English sparrow"
      },
      {
         "language" : "",
         "sourceTaxonKey" : 100220560,
         "vernacularName" : "Europese huismuis",
         "source" : "Global Invasive Species Database"
      },
      {
         "vernacularName" : "Gorrion domestico",
         "source" : "Global Invasive Species Database",
         "language" : "",
         "sourceTaxonKey" : 100220560
      },
      {
         "source" : "Integrated Taxonomic Information System (ITIS)",
         "vernacularName" : "GorriÃ³n casero",
         "language" : "spa",
         "sourceTaxonKey" : 102101640
      },
      {
         "vernacularName" : "Gorrión Común",
         "sourceTaxonKey" : 123213203,
         "language" : "spa"
      },
      {
         "language" : "spa",
         "sourceTaxonKey" : 101186844,
         "source" : "The European Nature Information System (EUNIS)",
         "vernacularName" : "Gorrión Común"
      },
      {
         "language" : "spa",
         "sourceTaxonKey" : 114130266,
         "source" : "Colaboraciones Americanas Sobre Aves",
         "vernacularName" : "Gorrión casero"
      },
      {
         "vernacularName" : "Gorrión casero",
         "source" : "Yanayacu Natural History Research Group",
         "sourceTaxonKey" : 119245200,
         "language" : "spa"
      },
      {
         "vernacularName" : "Gorrión casero",
         "source" : "Catalogue of Life",
         "sourceTaxonKey" : 119950016,
         "language" : "spa"
      },
      {
         "language" : "swe",
         "sourceTaxonKey" : 101186844,
         "vernacularName" : "Gråsparv",
         "source" : "The European Nature Information System (EUNIS)"
      },
      {
         "vernacularName" : "Gråspurv",
         "language" : "dan",
         "sourceTaxonKey" : 123213203
      },
      {
         "vernacularName" : "Gråspurv",
         "language" : "nob",
         "sourceTaxonKey" : 123213203
      },
      {
         "language" : "deu",
         "sourceTaxonKey" : 116795880,
         "vernacularName" : "Haussperling",
         "source" : "Taxon list of animals with German names (worldwide) compiled at the SMNS",
         "country" : "DE"
      },
      {
         "language" : "deu",
         "sourceTaxonKey" : 100483595,
         "source" : "Belgian Species List",
         "country" : "BE",
         "vernacularName" : "Haussperling"
      },
      {
         "language" : "deu",
         "sourceTaxonKey" : 123213203,
         "vernacularName" : "Haussperling"
      },
      {
         "sourceTaxonKey" : 101186844,
         "language" : "deu",
         "source" : "The European Nature Information System (EUNIS)",
         "vernacularName" : "Haussperling"
      },
      {
         "source" : "The Clements Checklist",
         "vernacularName" : "House Sparrow",
         "language" : "eng",
         "sourceTaxonKey" : 113987294
      },
      {
         "vernacularName" : "House Sparrow",
         "source" : "Taxonomy in Flux Checklist",
         "language" : "eng",
         "sourceTaxonKey" : 100159046
      },
      {
         "source" : "Colaboraciones Americanas Sobre Aves",
         "vernacularName" : "House Sparrow",
         "language" : "eng",
         "sourceTaxonKey" : 114130266
      },
      {
         "sourceTaxonKey" : 102101640,
         "language" : "eng",
         "vernacularName" : "House Sparrow",
         "source" : "Integrated Taxonomic Information System (ITIS)"
      }
   ],
   "limit" : 20,
   "offset" : 0
}

Using this type of search: api.gbif.org/v1/species?name=Passer%20domesticus, you can look for all info for a particular species, starting from either a scientific name or a common name (in example, Passer domesticus).
GBIF includes information in 1,643,948 species (and counting), but I don't know for what proportion they have common names (or where there are common names).

species names in many languages. Awesome thankyou.

They seem to have some Unicode encoding issues, though. Not only does the API not specifically indicate via HTTP headers that the text it's returning is UTF-8 encoded, but some of the vernacular names (like "GorriÃ³n casero" above) actually appear to have UTF-8 encoding applied twice.

@IlmariKaronen True. And thanks for the reformatting.

A lot of this data is also downloadable from GBIF: for example, if the Global Invasive Species Database seems to have the names you want, you can search for it at http://www.gbif.org/dataset -- many (most? all?) of the datasets can be downloaded as a "Darwin Core Archive" (a ZIP file containing CSV files) from the dataset page (http://www.gbif.org/dataset/b351a324-77c4-41c9-a909-f30f77268bc4).

If you're looking for marine species, the World Register of Marine Species is probably the best place to find this information.
The Ocean Biogeographic Information System also contains a tremendous amount of marine species.

Thanks alot. I was looking at flying fish today, the Uniprot list has at least 11 flying squid and flyingfish. thanks for the resource.

A late answer, but I think the mentioned sources are limited and the awesome download page of Observado.org offers a much better alternative.
The  website of Observado, an initiative to collect species observations worldwide, has global species lists in csv format that are as complete as possible. The plant list currently has 381.473 records! You can download local species names in more languages you might have heard from, from English to Russian and from Frysk to Dzongkha.
Note that these lists are meant for observations in the field, and hence also contain multispecies, hybrids and synonyms. But these can be filtered out easily.


text:
RT-qPCR for RNA quantification
I'm really new to RT-qPCR and probably I've just a minor problem than I think.
So, what's my problem about.
I want to quantify a virus by a specific area within a gene on its genome. I've specific primer which are working fine with the extracted virus rna from my samples. But now I need a template for a dilution series to quantify this virus. And there's my little problem. And maybe you can help me.
So I know that the genome of my virus is a negative sense single stranded RNA, so -ssRNA, and moreover I know the virus strain and the gene, which RNA I want to synthesize for the quantification. So I looked it up on ncib and I found the sequence of the gene, but it is listed as the complete cds of the gene and not the RNA sequence. And as I'm right the cds is the same sequence as the positive sense RNA, with Us instead of the Ts?!? So is it right for synthesizing, that I have to translate the cds first in +ssRNA and then in -ssRNA and this -ssRNA sequence I have to synthesize to get a standard?
If the cds would be: ATG , the +ssRNA would be: AUG and therefore the -ssRNA would be: UAC and this UAC , I would have to synthesize? Sorry for this stupid question but I am a lil bit confused at the moment with the difference of - and + ssRNA regardind the RT-qPCR. Another question would be, whether the Reverse transcriptase with Random hexamer primer is specific for -ssRNA or +ssRNA. It isn't ? So my quantification would also work with the AUG as a template for a standard curve?
Thanks a lot!
dan

To start off with your last question, strandedness is something the reverse transcriptase does not care about. If you use random hexamers it will simply translate your -ssRNA into a + single stranded cDNA. Perhaps this diagram from Wikipedia makes things more clear, it is for an mRNA but the principle is the same:

This cDNA will then serve as a template for your primers in the qPCR which will turn it into a double stranded DNA molecule. In other words, after one round of amplication in a PCR reaction the DNA products of the + and the - RNA strand would be indistinguishable!
It therefore does not matter which strand you synthesise as DNA to make your standard curve. It will be double stranded so you just need to compensate for the other strand being a template in the PCR as well.

First thanks for your answer. I thought that the RT would not care about strandedness, but I wasn't sure. Now, I am.
Okay, for my example above you would say it doesn't matter whether I would synthesise the RNA as AUG or UAC? But what I didn't get is:
What do you mean with 'I just meed to compensate for the other strand being a template in the PCR as well' ? Can't I use the synthetic +RNA dilution series as a standard curve for my unknown sample with -RNA?
Sorry for my questions.

I was not aware you were going to make synthetic RNA as the template. It is certainly the most accurate but it also a lot more expensive to synthesise. Usually people use things like DNA gBLOCKs from IDT but I have no experience with ssRNA viruses and what the acceptable standard is there.
If you do go for dsDNA then you need to keep in mind that there are two strands that can be bound by primers and you will underestimate the amount of ssRNA in your sample if you do not divide by two.


text:
What happens to the hollow nerve cord?
The dorsal nerve cord of vertebrates is a hollow structure that develops into the nervous system. This embryonic tissue is hollow and I wonder what happens to this 'hollow' later?
Does it form the ventricles of brain?

The "hollow" i.e. the neural canal develops into the ventricles, the cerebral aqueduct and the spinal canal (Wikipedia; also see this site).
For a more authoritative reference, see this book by Haines and Ard† (page 82 onwards in google books; google book links are apparently transient and they expire; therefore I didn't provide one).

† Haines, Duane E., and M. D. Ard. Fundamental neuroscience for basic and clinical applications. Philadelphia, PA: Elsevier/Saunders, 2013. ISBN: 9781437702941


text:
What is the optimal sampling method for modeling of microalgae growth?
Recently, I am performing microalgae (Chlorella sp.) cultivation experiments for the mathematical modeling of microalgae growth with respect to time.
The main issue is that an analysis of lipid contents in microalgae requires a large volume of culture media per data point. Especially, in the early stage of the cultivation, the density of the microalgae is very low, so almost 20% of the total culture media needs to be consumed for obtaining just a single data point. Due to this limitation, sometimes, I measured only three times (the beginning, middle, and last).
More data points are obviously desired for the accurate modeling but it ends up with huge loss of the media. This may affect the quality of the overall experimental results. This seems like a sort of trade-off. The problem is that I cannot increase the size of the reactor volume at the moment.
Could anybody recommend how to come up with the optimal sampling number in this situation?
Any experience, ideas or recommended papers are welcome.
Thank you.

I would adjust the title of your question as it has more to do with lipid analysis rather than growth

For these kind of experiments, especially when you talk about modelling, it can be worth to set up a chemostat or at least a turbidostat. An example of such a study can be found in: Simultaneous growth and neutral lipid accumulation in microalgae by Klok et al. (Pubmed).
Alternatively you can use lipid dyes such as Bodipy but these are often very tricky to get to work and they might not penetrate in your Chlorella. Nile Red in any case is almost impossible to get working quantitatively despite it being used quite extensively, see details in this publication. Be very cautious when going down this route.


text:
What is the mechanism by which myelination reduces the capacitance of the axon membrane?
There are two mechanisms that have been proposed to me.
1) Layering of Schwann cell membrane with conducting fluid between the layers is analogous to several capacitors in series. Since capacitance in series add by the reciprocal rule (as resistors do in parallel), this reduces the total capacitance.
2) The myelin increases the distance between the 'plates' of the capacitor. For parallel plate capacitors $ C = \epsilon A/d$ where d = distance between the plates. Thus increasing the distance reduces the capacitance.
Which of these explanations best applies to myelin, or is it in fact a mixture of both?

Isn't the 2 events behind reduced capacitance, is depending same mechanism? you adding capacitors at series that means you increase acting distance between 2 most-terminal plates. Isn't that?

Adding more capacitors in series does move the terminal plates on either side further away, but I wasn't sure this applied to the equation involving d because adding another capacitor means the charge stored on each plate is reduced also.

Circuit analogies don't 100% apply to myelin because membranes have complex electrical properties, but both of those explanations work and they are in fact essentially interchangeable: Take a membrane with distance d across the membrane and capacitance c. Then we add some myelin to get a new capacitance C at a new distance D.
If you 4X the distance between plates (D = d * 4), C=c/4 (from the formula you posted as (2) ); if you add 3 extra plates (so now you have a total of 4 plates), C=1/(1/c + 1/c + 1/c + 1/c)=c/4.
Importantly, myelin also increases the membrane resistance, and because myelin is typically very thick compared to a normal membrane (~10nm for one layer vs. 500-2500nm for myelin), you can almost consider myelination to increase resistance to infinity (compared to the axial resistance of cytoplasm) and the capacitance to zero.
See this page for some more info.
Note that the reason these explanations are interchangeable is that there is effectively no distance between the added plates in series and no difference in capacitance for each individual capacitor/piece of membrane (for example, see this page).


text:
Asymmetric volcano plot
Nearly all volcano plot I've seen tend to be roughly symmetric around the y-axis, with a fairly equal number of up- and down-regulated genes. What are the potential reasons for a volcano plot that is heavily unbalanced (i.e., many more negative fold change genes than positive)?
In my analysis, I have identified two populations of patients within a disease cohort, representing the "interferon high" and "interferon low" sub-populations. I then calculate differential expression between these groups, and visualize the results with a volcano plot (log(p-value) of differential expression vs. log(fold change)). The volcano plot is quite asymmetric, with a maximum log2 fold change of 1 on the positive end, and a minimum log2 fold change of -3 on the negative end, with many more genes significantly down-regulated in the IFN-low population.
Is it reasonable to suppose that there are lots of genes up-regulated in IFN-high, with no down-regulated genes defining this population, or is there something else going on?

I have no experience on mammalian expression analysis but I have seen these asymmetric plots quite a few times when cells were highly stressed. During one treatment they shut down protein biosynthesis and photosynthesis so downregulated genes vastly outnumbered the few genes which were involved in the adaptation response. I don't know if something similar could be happening in your samples?


text:
The effect of pH on catalase
Why does catalase still produce oxygen when mixed with 1 mL of 0.1M NaOH (pH 13), but not when mixed with 1 mL of 0.1M HCl (pH 1)? Catalase's ideal from what ive researched is 7. In other words, since both are on opposite side of the pH scale and equally distant from catalase's ideal, why does the acid mixture stop working, but the base still function, even if a little slower? Why did the catalase denature after the acid, but not the base? Thanks for any help, I'm pretty curious

The pH profile of an enzyme is not necessarily symmetrical. As random examples, see Figure 7 here, or Figure 5b here. Or if you have access, a pH profile for Magnaporthe grisea catalase can be seen in Figure 7 of http://dx.doi.org/10.1042/BJ20081478
The reasons for this go back to why enzymes are pH dependent in the first place. One of the major reasons for a pH dependence is that key catalytic residues become  (de)protonated as the pH changes. But different residues have different effects and different pKas, so you need to look at the sum of all their effects.
Example:
Imagine that a key catalytic residue must be in a deprotonated form, and has a pKas of 4.0. At any pH above about 5.0, it's all in the deprotonated form, so that residue should work. Any pH below about 3.0 and the enzyme is completely dead.
But an enzyme might have more than one residue that's pH sensitive. So now imagine that there's another residue which in the protonated form helps the reaction, but isn't as critical to catalysis such that the deprotonated still has residual activity. For the sake of argument let's say this residue has a pKa of 9.0.
Now imagine a third pH sensitive residue with a pKa of 6.5, but it's even more removed from the active site and has an even lower effect on catalysis (for example, it's a remote electrostatic effect based on the polarization of the transition state).
What would the pH profile for this enzyme look like? Here's an example:

"Activity" is the estimated total activity, and Residue 1/2/3 are the fractions of "active" form of each residue. - Diagram was made using the Henderson–Hasselbalch equation to determine the fraction of "active" states of each individual residue, and then assuming that the inactive forms are 0%, 80%, and 33% the activity of the fully active form for the pKa 4.0, 6.5, and 9.0 residues, respectively.
Note that the maximal activity occurs at about pH 5.7, but the activity drops off asymmetrically - the enzyme is much more sensitive to low pH than high pH.
A similar thing happens with natural enzymes, except that they may have many more residues which have minor contributions. They also may have $\ce{H+}$ and $\ce{OH-}$ playing a role as reactants (thus affecting the intrinsic reaction rate), and pH may play other effects, such a denaturing the enzyme. That's what leads to the complex pH profiles: multiple small effects all adding together.


text:
Topological property of DNA
I was reading a course about DNA Supercoiling, and I stopped at this definition :

[...] In the case of DNA, a topological property is one that is not affected by twisting and turning of the DNA axis and can only be changed by breakage and rejoining of the DNA backbone. (Source)

I didn't understand what they mean, can anyone clarify it please.

I think when you get to the later section entitled "DNA Underwinding Is Defined by Topological Linking Number", it will help explain what that means.

The classical explanation of topology is that donuts, coffee cups, and humans all have the same topology (this is a reference to the mammalian gastrointestinal system which is just a simple tube, the food goes in one end and out the other).  If you understand this analogy, then an intact circular rubber band (or elastic band) has the same topology as your covalently closed circular DNA plasmid.  You can twist and knot a rubber band all you want and you will never change its topology.

Not only for DNA; topological properties of object doesnt' change by definition until you cut/fuse. topology is a branch of mathematics, which includes discussion about various sorts of knots, loops, surface-boundaries, etc. The basic difference from traditional geometry to topology is; topology doesn't look for the exact-shape or exact positions of objects. Rather it looks the 'manner' or 'way' an object 'locks' or 'leaks' something. Something got 'locked' means you must have to 'unlock' (= cut) it and something not-locked means you have to 'lock' (fuse) somewhere at a specific rule...

.... (contd)... so the 'manner' or 'way' topology looks for; is mathematically defined as; properties that could not be changed until you cut or fuse at somewhere.

DNA supercoiling can be described numerically by changes in the linking number $L_k$, it's the most descriptive property of supercoiled DNA.
The linking number $L_k$ is equivalent to the sum of $Tw$, which is the number of twists or turns of the double helix, and $Wr$ which is the number of coils or writhes.
$$L_k = Tw + Wr$$

[...]  If there is a closed DNA molecule, the sum of $Tw$ and $Wr$, or the linking number, does not change. [...] Since the linking number L of supercoiled DNA is the number of times the two strands are intertwined (and both strands remain covalently intact), L cannot change.

I don't know how to explain it more but I think the main idea is represented in the image below.

Edit:
From DNA Topology: Fundamentals :
There are two important features of the $L_k$:

$L_k$ is always an integer.
$L_k$ cannot be changed by any deformation of the DNA strands, i.e. it is topologically invariant. The only way to change it is to introduce a break in one or both DNA strands, rotate the two DNA strands relative to each other and seal the break. This is precisely the role of DNA
topoisomerases.

Related question: Reason behind formation of positive supercoils during DNA replication/transcription.
Sources : DNA supercoil and DNA Topology.


text:
List of amino acid frequency of different foods?
I'm trying to write a little application calculating the biological value of protein content of different meals using the amino acid frequency of different foods.
The idea is that the user can choose amount and type of different ingredients and finally obtains the biological value index for the meal.
For this calculation I'd need a list of amino acid frequencies of the different foods.
Any idea how I could obtain this?
My first idea was to just use the DNA of the different plants to extrapolate the proteins synthesized and then obtain the amino acid frequency from there but I know that genome and proteome is not correlating.
Any ideas / thoughts?

try the US FDA's website - it's a vetted website that has this database information - it is listed in this questions as well that appears to be a duplicate... biology.stackexchange.com/q/41844/16299

A reasonable starting place could be the Food and Agriculture Organization of the United Nations:
http://www.fao.org/docrep/005/AC854T/AC854T03.htm#chI.I
This source looks by no means complete or easy to parse, but some simple web scraping may help you wrangle the data into a database.

try the US FDA's website - it is listed in this questions as well that appears to be a duplicate... http://biology.stackexchange.com/q/41844/16299


text:
DNA genetic testing from dried sweat crystals?
My sons' dad died and I wanted to do any sort of genetic testing possible, as a gift to my sons.  The only item available is dried, crystallized sweat from the bridge of his Oakleys, sadly.  Would there be any significance found in such results?  And, who does this sort of testing?  Thank you.   JK

He wore these sunglasses while bicycling, intensively, 14 miles or so in one trip, mixed terrain, so I'm thinking the sweat residue may have a high concentration of his cells.


text:
If someone A has lung cancer
and the lung cancer has not spreaded to other parts of A, does transplant help to remove cancer?
If someone B transplants a lung 'contaminated' by cancer, does B necessarily get cancer too? His body may kill cancer?

The standard procedure for curing cancer (besides chemotherapy) is to surgically remove parts of the organ with the tumor in it (or the whole, depending where it occurs). You also keep some safety margin around the tumor to be sure you definitely removed it. But in principle removing the organ in which the tumor grows and transplanting a healthy one would help.
There is indeed a problem with tumor cells in transplanted organs. If small (and thus undetectable) tumors have formed in these organs, they will be transplanted with the organ. Since the patient receives high doses of immunosuppressing drugs to avoid a reaction of the patients immune system, the activity of the immune system is greatly reduced.
Since the immune system also plays an important role in detecting (and fighting) the malignant cells of a cancer, this is also reduced which favors the appearance of tumors. There are reports for example from cystic fibrosis patients who received a lung transplant from a smoker and later died of lung cancer (see here, at the moment I only have a news source for it).

To the best of my knowledge, the only solid organ neoplasm routinely treated by Tx, at the moment, is hepatocellular carcinoma (liver), and even that under very strict conditions. For the rest, transplantation is currently not a standard therapy because of the very real possibility of accelerated growth of micrometastases under severe imunosuppression after the transplant.
And yes... a tumour transplanted into a person would grow, and fast, again because of immunosuppression.
If you're asking this for a practical reason, I'd advise you to talk to the oncologist involved in treatment for a thorough explanation of why this wouldn't work / referral to an applicable study, if there is one.


text:
What is a good multiple alignment of large genome sequences when working with limited hardware?
I need to align bacterial genomes (namely mycobacteria, over 4 Mb in length), and my choice would have been either 'muscle' or 'clustalW'; however these algorithms are too memory demanding for such long sequences thus I can't run the multiple alignment on my machine.
Is there any other program that I could use to align multiple bacterial sequences?

There are many others. I'm surprised you run out of memory... How much RAM do you have? If working on Linux, swap space is easy to allocate and can be used as a sort of memory if time isn't a constraint. Since this is the issue, please do provide information on what biology you are looking for with the sequence alignment, and what are the exact memory limitations. What specific errors do you get. Be aware that this site aims to address biological problems, not computational ones, so do shift the emphasis onto maintaining biological accuracy rather than overcoming memory constraints.

Ok, I'll try to keep it on the biology rather than bioinformatics; however I have 15 Gb of RAM.

First of all, do not, I repeat not, use ClustalW. That is horribly out of date and was never very good to begin with1. It was just the first to become common. At least use ClustalΩ. Anyway, while I haven't done much aligning in the past few years, back when I did, I got the best speed/quality ratio from MAFFT.
MAFFT has been used in various sequencing projects and can deal with whole genomes easily. Whether or not it will run correctly on your machine depends on the specs of your machine, of course. However, it should be considerably more efficient than clustalW, although not necessarily more than muscle.
Before doing any of this though, are you sure you need to align whole genomes? Could this be an XY problem? You might want to consider posting a new question here and explaining what your final objective is. Also, if these are published genomes, you might be able to find an existing alignment.
If you really do need to run a whole genome alignment and your machine can't use MAFFT or muscle or any of the other modern aligners, you need a new machine. No matter how efficient your aligning algorithm, a genome is a lot of data and you need a strong machine with serious RAM for it. If you are on a *nix machine, you could ask about how to create a swapfile to increase your memory on Unix & Linux.

1Don't get me wrong, it was state of the art and everything back in the day, but the state of the art wasn't very good, that's all.

The issue of aligning long sequences came out already somewhere else (actually from the developer of muscle); what is such issue? If I have related species (in this case the members of the Mtb complex) doesn't it make sense to align the whole genome and see where differences in genome (especially indels) arise? Isn't this the reason of being of the Whole Genome Sequencing research?

@Gigiux sorry, for some reason I never saw this comment. The alignment you need depends on the question you want to answer. Yes, sometimes whole genome alignments are useful. Often, however, they are not and you are only interested in specific areas. I can't help you choose unless you explain exactly what you are trying to do.

I think I understood why whole alignment is not good as such for inter-species comparison: regions of homology can be dispersed in different parts of the genomes thus there is no co-linearity between sequences. I have found Mauve an excellent tool for inter-species alignments.

I have used LASTZ in the past, you can set the word size and thereby control memory usage. You might be better off asking your question on Biostars, there are more skilled bioinformaticians lurking around there.

I'd say there are skilled bioinformaticians here too so as not to offend this community ;) but you're right. Here we're more interested in the underlying biology than at biostars, which is a biology SO mashup.


text:
"producer cell line" vs. "host cell line" in biopharmacology
I'm translating a text that describes the creation and testing of a cell line that produces a drug (a protein) and also procedures for creation and maintenance of cell banks.
Example sentence:

Assessment of the morphology, viability, and cell concentration of the producer cell line

I wonder if I can use host cell line instead of producer cell line, or "host cell line" would mean "a line that has not yet been subjected to transformation using viral vectors" (a line that cannot yet produce the needed drug; a "pure" line). Just making sure.

What is uclear about my question? I'm asking whether the two expressions can be used synonymously.

I would lean towards staying with "producer cell line". In my mind, a host cell line is hosting something, like a virus, while a producer produces something. The non-transformed cell line would be the parent cell line.
On the other hand, "host cell line" also implies hosting the recombinant protein product that is later purified, so there's an argument to be made for either phrase. I still prefer producer, though, as I think it's more directly descriptive of what the cells are actually doing - producing the protein of interest.


text:
Why are Mendelian mutations considered rare?
I was reading the Wikipedia articles about genome-wide association studies (GWAS) and whole exome sequencing.
As I understand, GWAS is used to identify most common SNPs that are proved to be associated with a disease/disorder. On the other hand there is an article about whole exome sequencing method where it said that it is more sensitive to identify Mendelian mutations in contrast with the SNP genotyping methods used in GWAS.
As the graph shows below, there is a distinction between Mendelian mutations and common mutations. What exactly does Mendelian mutation mean (why do we call it Mendelian)? What makes a Mendelian mutation so rare but effective in contrast with common mutations? Aren't common mutations inherited with the same rules as Mendelian ones?

I will focus more on the question of rarity, which the comments have not addressed. Recall that natural selection is operating on the human population. Because of this, bad mutations of large effect (disease mutations such as CFTR in your figure) are very rare, because selection is removing them at some rate from the population (people with cystic fibrosis are unfortunately very sick and are not as fertile as healthy people), whereas mutations with very little effect are not subject to much selection. Paper one and paper two are reviews describing the population genetics in more detail.
As suggested by commenters, Mendelian mutations are so named because they are single loci of large effect controlling traits (approximately). Common variants, by this logic, must have very little phenotypic effect, because they are not purged by natural selection (assuming that they are deleterious, or disease-causing).
Rule of thumb: 'Mendelian' alleles can easily be used to predict phenotypes (like disease) and are acted upon by natural selection. 'Common' alleles are individually not informative about phenotype and are thus mostly ignored by natural selection. Not exactly true, but close.

In reality, Mendelian variants are very rare compared to non-Mendelian variants. Why would evolution evolve dominance or recessiveness? If you didn't learn about this in grade school, it would likely come off as a very weird and specific thing to evolve. More likely, there is an optimal value for whatever phenotype you are going for (enzymatic efficiency, height, disease, etc.), and it wouldn't make sense to want 25% of the population to have the trait completely turned off and the other 75% to have the trait completely turned on.
Mendelian alleles only account for a fraction of the variance in most diseases, because they are so rare, whereas common alleles, taken together, explain the bulk of the genetic variation in most diseases. However, when there is a Mendelian variant, its effect is so large that it is obvious. This makes them easy to study.

I'd like to see some sources for your answer, specifically your claim that Mendelian variants are very rare.

@bob1 There are certainly much fewer than 100,000 Mendelian variants. Even if we say there are only 10 million SNPs (some sources say 600 million), Mendelian variants are 100x rarer.

"Why would evolution evolve dominance or recessiveness?" - recessiveness basically evolves from regulation that is useful whether or not a defective copy of a gene is present. Typically recessive alleles are recessive because they cause a defect in function and because the transcription/translation of the other copy happens to a level that doesn't depend strongly on the number of copies. Dominance similarly doesn't evolve directly, it's just a consequence of a gene product having an effect.

I think that "Mendelian" is being used by the OP due to confusion, not because they are interested in the population dynamics of dominance. I think that what you are talking about may be true in the context of the genetic architecture of traits and we have to some extent discussed that here. But they seem to be more interested in the dynamics that lead to the plot that they show, which is basically the result of selection.

@MaximilianPress Yes, absolutely. I meant this more like a footnote to your answer

@BigMistake I think it would be appropriate to say that there are <100,000 Mendelian variants that we know of. I really really doubt that we have studied enough genomes to know whether many of those SNPs is Mendelian or not, even with GWA studies going on.

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Is RFLP markers are dominant or codominant?
there are several markers used in molecular biology,. marker analysis. RFLP is most commonly used marker which having several advantages. is RFLP marker co-dominant or dominant ?

Your question doesn't make any sense. Do you know what a restriction fragment length polymorphism actually is? It's not a gene, so the terms "dominant" and "co-dominant" don't make any sense. It's essentially like asking if an EcoRI fragment is dominant. The terms don't apply.

The concept of Genetic markers are similar to genes; but not same as genes. We don't see their phenotypic output (expression). We directly see their occurrence in DNA after enzyme-digestion of DNA. so how the term "dominant" or "recessive" or "co-dominant" could be apply

I suspect that you "know" the answer to your question and are just seeking confirmation.  First, let's get some terms straight.  Dominant and recessive are used in reference to phenotypes, so one needs to have a transmissible phenotype to score among the offspring of our genetic cross.  Phenotype are usually due to (or caused by) mutations.  In a diploid species, if you can only score the phenotype in offspring that are homozygous for that mutation (denoted m/m) then the phenotype is recessive to the wild-type allele of the gene.  In other words, a heterozygous offspring, (m/+) will have a wild-type phenotype.  On the other hand, if a heterozygous (m/+) offspring has a mutant phenotype then we would say that the mutation is dominant over the wild-type allele.
Your question is asking about a test cross of a +/+ individual to a homozygous mutant (m/m), however, in this case the RFLP does not typically have any mutant phenotype, it is just a convenient genetic marker for the purposes of this discussion.  All of the cross-progeny will be (m/+), and if you go to the trouble of preparing genomic DNA from those F1 cross-progeny and perform a Southern blot with a probe that detects the RFLP, then you will be able to demonstrate this.  Typically, unless the RFLP-bearing chromosome is homozygous, the probe will also detect the wild-type restriction fragment, so there will be two bands on the film, one for each allele.  Since you can detect the genetic marker in the F1 generation, the RFLP is dominant, but since you can also "score" the wild-type fragment, the two fragments are indeed co-dominant (after you do the Southern blot).

Your answer gave a clear identification. thanks in advanced .


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How to calculate Oxygen consumption?
I am looking into Glycolysis and TCA cycle.
I have learnt that oxygen is the final electron acceptor.
So, let's say we know the amount of NADH and FADH2 produced under some circumstance related to the Glycolysis and TCA cycle.
How would we calculate the amount of oxygen consumption level?

Assuming that you know the amount of NADH and FADH$_2$ produced by glycolysis and TCA cycle, you can determine the reducing equivalent produced: for each NADH or FADH$_2$ produced, two reducing equivalents are produced. It means that the re-oxidation of NADH and FADH$_2$ will release 2 electrons. Here are the corresponding half-reactions:
$\textrm{NADH} = \textrm{NAD}^+ + \textrm{H}^+ + 2~\textrm{e}^-$
$\textrm{FADH}_2 = \textrm{FAD} + 2~\textrm{H}^+ + 2~\textrm{e}^-$
Knowing the total reducing equivalent produced, divide it by four in order to obtain dioxygen consumption: O$_2$ is reduced into 2 H$_2$O by accepting four electrons. Here is the corresponding half-reaction:
$\textrm{O}_2 + 4~\textrm{e}^- + 4~\textrm{H}^+ =  2~\textrm{H}_2\textrm{O}$
Of course this only applies to aerobic organisms: some microbes are able to use other electron acceptors than O2.

This is of course correct, though I think it might help to just write the reaction: 2 NADH + O2 -> 2 NAD+ + 2 H2O

The half-reaction for oxygen reduction is not balanced, missing 4 H+.


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Why is aneuploidy usually lethal?
So, I was reading about aneuploidy and how a zygote with one extra or less chromosome usually would not survive to full term. I suppose this happens because aneuploidy leads to some kind of protein imbalance. So, in case of monosomy we would have a shortage of proteins, and in case of trisomy we would have an excess of proteins.
On the other hand, a conventional argument for having two copies of each gene is that, if one gene gets corrupted because of some kind of mutation, we still have another copy that produces the correct protein. So, in case of a recessive genetic disorder, the zygote can survive even with half the amount of protein.
My question is then, why can't monosomic aneuploidy be looked at the same way? Moreover, I read that monosomic aneuploidy is almost always fatal, while trisomic aneuploidy is sometimes tolarated.

What causes zygotic termination in aneuploidy often isn't an issue with proteins or other gene products i.e. being "too sick" to live. It's that the zygote is basically "self error checking" and if it encounters a serious genetic error (e.g. aneuploidy) it self-terminates, as it would likely not survive anyway. Sometimes this self-termination fails, and the zygote develops. Depending on the specific aneuploidy, it may not make it to term, or perhaps it will, and you will have a child born, albeit the child will usually have a decreased quality of life/life-span.
A similar mechanism works in your somatic (non-reproductive) cells everyday when they replicate and divide - if they detect and error in their DNA that cannot be repaired, the cells SHOULD kill themselves. Sometimes this fails, and can give rise to cancer.

Thanks for your reply, can you add something more about the "self error checking" mechanism, maybe a link?.

Just one doubt, but people with aneuploidy have problems because their aneuploidy translates into some sort of protein imbalance,  and that brings me back to my question

This sounds self-contradictory: you're saying that extra chromosomes are not harmful in themselves, but the cell detects them and self-terminates because extra chromosomes would be ... harmful? I'm no expert on this topic, but I would guess the main underlying problem is that aneuploidy causes problems in cell cycle/mitosis, which is lethal. Also, it probably would result in even more scrambled cells in the next generation (after meiosis), and so would endanger the whole genetic material.

@Roland Forgive me, my response was written past midnight. I meant to say that rather than progressing to the stage of dying from protein imbalance, the cell terminates before this point, usually.


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Can one switch the DNA present in a sperm cell?
Can a donated sperm cell be stripped of its original owners DNA and be replaced with DNA of another person to make a biological child of a man who has low production in sperm?

Not with present technology. There is next to no cytoplasm in a sperm cell. You cannot suck out its nucleus. If your remove its nucleus, the whole thing will just collapses on itself.
As for you question of replacing nucleus?. One current technique (Intra-cytoplasmic sperm injection - ICSI)  is to  inject a single sperm of a man with low sperm count with minimal mobility directly into an oocyte. (Ie sperm that is so bad that they effectively cannot swim on their own)
Unfortunately there is some indication, that this technology has made an entire generation of sons, who have also inherited their father's low sperm count and limited mobility. And now have a higher than average chance of needing IVF assistance.
https://www.newscientist.com/article/2108218-male-fertility-treatment-seems-to-pass-infertility-on-to-sons/


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Meaning of phrase with term, "intelligent design"
I am am mathematician, kindly correct me, If I am wrong somewhere.
I am reading a book titled "Sapiens " by Noah Harari.
He says

Organism are increasingly shaped by intelligent design rather than natural selection

I am not able to understand what he is trying to say.
What does he mean by "intelligent design".
What I know is that natural selection is the main process that brings evolution. Is he trying to say that natural selection is no longer the driving force ?

Any reason for downvotes, Please explain. I want to know what went wrong.

-1, Intelligent design is a common term. An internet search will provide a definition, does that definition fit with what the author means? If that doesn't make sense then more context is required. Also, it appears to be a misquote as it isn't grammatically correct.

@Sri You used the right format for quotes before and you changed it. I changed it back but don't hesitate to let us know if there is any reason you prefer not using the quote format.

downvoted - based on the good research by @tomd

I've changed your title as nobody reading a list of titles would know what the question was about with "this phrase". Try to do better in future.

Welcome to Biology.SE! You have seen some criticism about your question here, but some of that might not have been very useful for you. Please consider taking the tour and look at our guidelines for good questions. Enjoy! :)

@David thanks that edit will help me too in future for better sentence and grammar.

Please first note that Noah Harari is not a scientist but a historian.
What does he mean by "intelligent design"?
Intelligent design is a set of fallacies invented by christian extremists to try to contradict a set of evidences that they have a hard time to include into their faith. Intelligent design has nothing to do with science. It is therefore impossible to state anything about this sentence except that it does not mean much.
However, from this quotation alone, one can't be sure that Noah Harari chose the term "Intelligent design" in reference to the commonly referred concept of intelligent design. He might have meant something else and might have tried to use some term that sounds sensational and poetic as talking about this book some have said that the attractive features of the book are overwhelmed by carelessness, exaggeration and sensationalism. (see theguardian.com). My first feeling is that you could try to ask him (contact information are there)!
@tomd found this source which clarifies the author intention.

Not all people accept this idea. Religious fundamentalists insist that intelligent design rather than natural selection has shaped life on earth. They argue that the intelligent designs of a great god sculpted the long necks of giraffes, the colorful tails of peacocks, and the jumbo brains of humans. To the best of our scientific understanding, these religious zealots are completely mistaken. The past history of life owes nothing to divine intelligence. Ironically, however, the zealots may well be right about the future. Very soon, the four-billion-year-old regime of natural selection may be overthrown, and life in the universe will increasingly be shaped by the intelligent designs of divine beings. For in the medium future, we humans are likely to turn ourselves into godlike beings, possessing divine abilities of creation by design.

What I know is that natural selection is the main process that brings evolution.
Natural selection is one process yielding to evolution. There are other processes such as genetic drift. Stating natural selection is the main process that brings evolution all depend upon what statistic of evolution you would like to consider. For example, you might want to know that most fixed genetic variation among species is due to neutral mutations (and therefore genetic drift) and not due to natural selection.
You might want to have a look at Understanding Evolution by UC Berkeley for a short introduction to evolutionary biology

+1 for quoting the review. Hopefully the question gets update with a little more context.

Natural selection is not hard to comprehend. and even-if in epigenetic studies shown exception to Darwin's theory, where acquired characteristics could be inherited; natural selection remains as a very normal and acceptable process.


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Why is the human ear most sensitive to 4000 Hz tones?
Human hearing sensitivity is dependent on frequency, which can be visualized by equal-loudness (iso-loudness) contour plots. An example is given below (Taken from here).

This plot shows that a tone with around a 4 kHz frequency (minima above) needs the least amount of actual energy in order to be percieved well as compared with a tone of any other frequency, while on the other hand it shows that tones of frequencies below 100 Hz and above 19 kHz need to have a lot of energy for us to percieve it.
My question is, how does one explain the clearly uniform/persistent fluctuations in these iso-loudness contours? Why are our ears most sensitive to 4 kHz tones, and why is there a "shoulder" in the contours at about 7 kHz? My first guess would be for proper perception of human speech - but the characteristic frequency of human speech is around 80 - 260 Hz!

EDIT:
My question is similar to this previous question, but it is a bit different in detail (they are only concerned with the overall dip, whereas I'm concerned with the dip, the shoulder, etc.). Moreover, that question has no accepted answer.

Uhp,... my question may be a duplicate of http://biology.stackexchange.com/questions/26067/why-do-humans-hear-better-between-2khz-and-5khz.

So many evolutionary "why's" questions around. Really hard to answer..

@LiuTianyi They're easy to answer! It's just that they're hard to answer with objectivity or empiricism... ;)

Close-voters - I don't see reason why this question is pob?

You started with an erroneous teleological argument: that the ear should hear best at the frequencies of the human voice. Teleological arguments are usually wrong. Who knows why  the ear evolved this way? (Also note that it was very likely pre-human.)

@Christiaan - Your own answer (which is good, btw) demonstrates why this question is POB: "But this is entirely and purely speculative and remains an unreferenced statement for which I do not wish to be held repsonsible in any way." One can explain the mechanics, as you did, but the why cannot be explained except possibly by a forensic anthropologist.

@anongoodnurse - that makes sense I guess... Speech understanding does come to mind in this regard I guess, as speech was probably a pretty important factor in who we are know. I might add something along those lines in my answer to clarify. Thanks for your comments.

@Christiaan - Speech recognition comes to mind to me, too, but in a slightly different way: I see hearing loss charts all the time (we do drivers' physicals in the oc med section) and am amused at the fact that men lose hearing in the higher frequency ranges of women's voices. :) Evolution?

@anongoodnurse hahaha whoooo that's a really nice perspective to explain the evolutionary beneficial role of presbyacusis :-D The survival of men kind :-)

The frequency-selectivity of loudness perception was first shown in the 1930s, when Fletcher and Munson published a set of curves showing the ear's sensitivity to loudness compared to frequency. These equal-loudness curves, as shown in the question above, are now known as Fletcher-Munson equal-loudness contours.
One straightforward physical explanation is the fact that sounds with frequencies around 4 kHz are amplified in the middle ear canal through the process of resonance. In effect, they are perceived 10 to 20 dB louder than other audible frequencies. The pinna also affect resonance and hence the outer and middle ear together join forces to create humps and bumps in the equal-loudness curves.
The evolutionary reason why 4 kHz, and not, e.g. 0.5 or 8 kHz, is difficult to pinpoint. First I can clarify some misconceptions in the question, before getting back to the question proper:

Firstly, you mention that the "characteristic frequency" of a human voice is between 80 and 250 Hz. You are referring to the fundamental frequency; the characteristic frequency is a measure used in electrophysiology to determine the frequency-specificity of inner-ear neural structures.
Secondly, the fundamental frequency does not determine the frequency-selectivity of speech understanding. A useful picture is given below in Fig. 1, which shows which frequencies convey which speech components.

Fig 1. Frequency dependence of speech components. source: The Essential Guide to Hearing Loss
It becomes apparent from Fig. 1 that consonants (f, s, h etc.) are higher pitched than vowels (a, o, u etc.). Arguably, consonants convey most of the word information. Indeed, speech understanding is generally less affected by removing the vowels than by removing the consonants. One may deduce from all this that high-frequency hearing (say 2 - 8 kHz) is most important to understanding speech.
And then, to get back to your evolutionary motivation behind the Fletcher-Munson equal-loudness contours, it may, purely hypothetically be so, that our ancestors with a middle-ear resonance around 4 kHz were advantaged over those that had resonances elsewhere in the audible frequency range, if any, because of an enhanced perception of the spoken word. But this is entirely and purely speculative and remains an unreferenced statement for which I do not wish to be held responsible in any way.

+1 - Really nice answer. A question, though (and I truly don't know the answer to this, whereas you might): do you think this frequency range evolved with language, or do you think it was there in primate ancestors?

@anongoodnurse see Figure 5 here of the chimp audiogram compared to the human: http://onlinelibrary.wiley.com/doi/10.1002/ar.a.20117/full Chimps appear to have a pronounced insensitivity where humans have their best hearing. This is also consistent across studies, albeit very low sample sizes: http://laboratoryofcomparativehearing.com/uploads/Chimpanzee__Pan_troglodytes_.pdf


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What factors should I consider when selecting a reference genome for mapping?
I am under the impression that the most recent reference genome is typically the best case. What other things should I consider when selecting a reference genome? For example, is there any particular reason not to go with the most recent reference genome when aligning short reads from RNAseq?

There are many, and it depends on information that you haven't presented.

Welcome to Biology.SE! If you are not convinced by the answer given, please elaborate on your question and provide some background information to what type of analyses you are thinking off. Also consider taking the tour and look at our guidelines for good questions. Enjoy! :)

@James I am aware of that lack of information, but on my level of expertise on the matter, I unfortunately cannot ask more detailed questions. Though I do hope that other users on my level of knowledge will find use in the answers given (which is kind of the idea behind stackexchange, isn't it?). Researching on my own did just not yield any comprehensible result for me...

@SebastianLobentanzer SE is designed to answer specific technical questions. It doesn't perform so well at providing answers for 'intro to topic' questions like this. Whilst some users are more than happy to try to answer these questions, seldom will you actually get the answer you want. There are plenty of ways of improving your question in order to make it more answerable by more people. See the tour as recommended by Alex.

@James Specific questions? Yes. Technical? Not necessarily.

@DanielStandage I think I was going for a word that encompasses "non-trivial to answer". 'Technical' probably isn't the best word to use.

There are many reasons!
Let's assume you are using the Human reference genome. The latest version is hg38 or GrCh38. This came out roughly three years ago (Dec 2013). Although now these same reasons do not really apply to this particular assembly, but no other assembly comes to mind where these reasons are demonstrable. When dealing with RNA-Seq data you carry out a few common tasks.

Annotations: When a new assembly comes out, all existing annotations are standardised on the previous assembly. Take for example GENCODE, that particular links to the current version of gencode, which is now based on hg38. But, more importantly notice that they still maintain the same release for hg19/GrCh37. From my experience, it takes about 1-3 months for annotation databases to migrate to a new genome assembly after the assembly is released.
Conservation tracks: These are the tracks which take the longest to get updated. I will not post a link to the tracks here. But, here's the UCSC table browser, you can go to the comparative genomics tracks and view the conservation tracks (Phylop, Phastcons) which are available for each assembly. Again from experience, it took more than a year for these tracks to be generated for hg38. So it is just better to work on the previous assembly if you want to this particular information, because generating these tracks by self is a very tedious and computationally intensive task.
Risks associated with unfinished genomes: This does not really deal so much with the human genome as the gain is ever smaller with each consecutive assembly. But considering a assembly which consists of 70% scaffolds, the variation between assemblies tend to be huge. For functional studies as opposed to insilico studies, it makes no sense to redo the entire analysis every time a new assembly comes out, since the insilico part of the study is the predictive pillar on which functional validations are based. Although the same does not apply to insilico studies where the results presented to the public are solely predictive.
Incoherence with existing studies: This is a major obstacle for using a newer assembly, especially applicable towards unfinished genomes, wherein the results may be widely variable and do not align with pre-existing knowledge. Of course, you may be the one who is correct but it is also possible that the variability in your results is the result of human error. Therefore, it is just better to wait for a "landmark" study to introduce the assembly to the public, allowing your study to undergo less stricter perusal and also allowing you to validate the expected variability in your results.
Pitfalls during functional analysis: For RNA-Seq analysis it is common practice to use RT-PCR for a particular gene to establish the expected expression level for that gene, which in turn will validate a successful RNA-Seq experiment bereft of shady PCR duplications and artefacts. For this particular part you would first create a primer, which validates the expected expression level of that gene. But this particular primer originates from a particular assembly. It is also possible that the region which is amplified may have shifted or changed between assemblies. So when you align your data on a different assembly from the one which was used to create the primer, you may get an unexpected expression level for that gene, as the original primer amplified an incorrect region, which got fixed in the newer assembly.

I know there are many more. But, these are the only ones which comes to mind at the moment.

Thank you for elaborating. I am new to Genomics, coming from a pharmacological perspective. It does not matter that your answer is not comprehensive. This definitely is a starting point from where on I can read up on aspects on my own. Thanks again!