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Why do some trees in California have dead brown leaves but also new green leaves?
It's Autumn 2015, and I just saw a tree that had mainly dead brown leaves but also some new small green leaves growing. Why didn't the tree just keep its old leaves? Does it think we are in spring already?
EDIT: To be clear, I had always thought that in autumn that all the leaves of a tree would fall off together, as a preparation for winter. It seems silly that the tree would then immediately grow some new leaves when it just decided to let all those previous leaves die. Why not just use that same energy to maintain those leaves?
I've taken some photos of the leaves and the trunk for help with identification.

More images of the tree can be seen at this Imgur link

Welcome to Bio. Without a picture or species identification any answer is mere guessing.

I don't think it would be localized to just California but a picture would definetly help. There could be so many reasons why the tree hasn't dropped it's dead foliage .

I've edited the original post with a link to some photos! Tell me if you need more.

What is your question? Are you asking why there are dead leaves and green leaves, are you asking why trees don't have their leaves last forever, or are you asking why the dead leaves didn't fall off?

I'm wondering why the tree seems to be growing new green leaves while it has many dying leaves. Why didn't it just use that energy to maintain the existing leaves?

Whether trees are deciduous or evergreen, their leaves don't last forever; they need to be replaced at intervals.  The process of photosynthesis depletes the chlorophyll in the leaves, so that needs to be replaced and this is a significant metabolic cost to the tree.  Therefore, whenever a tree is experiencing metabolic stress, it will slow down the chlorophyll replacement, and let the leaves die to save energy. It's metabolically cheaper to simply let the leaves die -- after removing the most precious nutrients -- and then regrow new leaves as needed, than to keep repairing the leaves that aren't needed because the tree is resting for other reasons.
In temperate areas, where there are well-defined seasons, this typically happens in the fall, and deciduous trees let their leaves die all at once in the fall.  In tropical or subtropical regions, where trees could photosynthesize all year, leaves may drop all year round (as with evergreen trees, like conifers, in temperate regions).  Often, though, their leaves will reflect metabolic stresses on the tree, such as drought.
(The Wikipedia article on "Deciduous" makes the point that this can be very localized, related to very local environmental differences that could only affect a single tree.)
Much of California is a subtropical region, and it has been experiencing severe drought for some time, so it wouldn't be surprising for a tree to have reached a point where its leaves have all had their chlorophyll removed.  On the other hand, as the El Nino event of 2015 increases, rainfall in California is returning, so it would also not be surprising for a tree to have recovered from drought enough to start making new leaves.
If your question is why the old leaves didn't fall off before the new ones started to regrow, it is probably simply a matter of timing.  The tree doesn't really "care" if the leaves fall or not, so long as they're not using up its resources, so there's no reason to force them off.  The new water supply may have arrived fairly shortly after the degree of drought that caused the tree to shut down the leaves.

Ah, I assumed that all the leaves were browning and falling off together because of the season. In this scenario, it seemed silly to start growing leaves again after letting them all die. If I'm understanding you correctly, in California this may be a continuous leaf dying/growing cycle throughout the year? And the recent rain (indeed, it rained for the first time in a few months last week) allowed the growth of some fresh new leaves?

Exactly right.  In fact, drought is functionally why leaves drop even in temperate zones -- in winter, all the water is locked up in the form of snow and ice that plants can't take advantage of, so they drop their leaves in preparation for this predictable period of drought.

Depending on the part of California, most deciduous trees will go through the customary winter-dormancy cycle as is seen throughout the rest of the planet, albeit often majorly abbreviated. Even as far south as Needles many "eastern hardwoods" that had been planted by landowners will dutifully drop their leaves as winter approaches, renewing their greenery he following spring.
The problem you mentioned is not restricted to California: Deciduous trees and shrubs facing severe and/or prolonged drought conditions will "go dormant" earlier than would be normal. This is a simple "survival strategy," in which the plant reduces the potential for long-term injury or harm by---in effect---hibernating. Nature has built this survival strategy into a wide range of life-forms; periods of crisis-dormancy allows the subjects to "weather" adverse conditions and, "hopefully," revive when the previously-experienced problems had passed.
I've noted deciduous plants going through leaf-drop as early as July, in New York State. Recently-planted deciduous trees and shrubs do not have the extensive root-systems of established plants, and will quite often go through early leaf-drop because they will feel the effects of a drought far more keenly than established plants. That is not to suggest that your trees or shrubs were recent plantings: It is merely a statement of fact.
A curious thing about early-dormancy is that plants will "rebound" and set new leaves---essentially, sending forth some of the leaves that had been grown for next year's spring and summer cycle.
This will come about when there has been a very recent period of increased rainfall, coupled with cooler ambient temperatures.
If you will check the recent weather-tables for California, you will note this is exactly what happened: A long, hot, period of zero precipitation and arid humidity was broken by an interval of cooler and more-moist weather, going into late-summer and fall.
The California hardwoods had "rebounded," setting a reduced number of new leaves and, essentially, tried to make up for the brutal conditions of the previous spring and summer by getting a few more weeks of photosynthesis and growth before Autumn arrived without doubt, and the cycles of shorter days and reduced temperatures obliged the plants to enter "true" dormancy.
My 12-15 hours of "Dendrology" (the study of trees) were taken nearly five decades ago, although I'd striven to maintain a B+, even in "Science electives." Besides, I'd really enjoyed "woodsy" courses as it allowed me another valid excuse to "prowl the pines & ramble the brambles!"


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Does playing music during sleep actually suppress rather than rouse the brain?
I've long been interested in the effect of music/sound on dreaming, and even built 2 apps that play music during REM period. Now I'm looking at this article about FMRI studies of a sleeping brain, and I see that it mentions:

During wakefulness, acoustic stimulation elicits activation of the
  auditory cortex (red). Similar stimulation during light NREM sleep
  stage 2 evokes transient downregulation of widespread cortical areas
  (blue), supposedly a sleep protective mechanism.

and

Acoustic stimulation in REM (rapid eye movement) sleep revealed a
  different brain activation pattern during phasic and tonic REM
  periods, with strongest suppression of cortical reactivity during
  phasic REM sleep periods.

Can I interpret information on that site to suggest that auditory stimulation during sleep actually makes the brain less active? Can one assume that playing audio during REM would disrupt dreaming due to transient downregulation?

This is a very interesting but difficult to answer question. That is because scientists are still debating about the various stages of consciousness. As it stands, there is evidence that people can learn even though they are asleep indicating that it is likely that sensory channels are open and information is being processed even when asleep. That likely means the brain is behaving as if it were awake at certain times during sleep. In this article they interpret the lack of blood flow seen by fMRI as less active which is mostly correct. Playing audio during REM is a tricky question because as you know dreaming does not require sensory input so that channel(hearing) may be free to receive information although your guess may also be true if if the music was loud enough to interfere with other cognitive processes.

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Is there a homeostatic setpoint for number of hours of sleep required by a human?
I've heard this TED.com talk about dieting and it mentions that there's a very definitive setpoint within the human brain about how much a human should weight. The speaker mentions that after as much as 7 years, the body returns to that homeostatic weight setpoing.
I'm interested if there's something similar for sleep - is there a homeostatic setpoint that says that a human should sleep X hours out of 24?
In this example by homeostatic I mean:
If the sleep setpoint is at 9 hours, the human can sleep for 8 hours for some time, but when the artificial sleep restriction is removed, the human would return to 9 hours of sleep naturally.

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What is meant by "alien" probe in a microarray?
In my lab we did a microarray to analyze differential gene expression in S. cerevisiae treated with UV irradiation. We are now analyzing the results and one of the up-regulated genes is labeled "Alien4_60." I believe this is some kind of control, but I am having trouble understanding what it is.
I would think that a probe labeled "alien" in a microarray would be some kind of negative control. The probe-list (excel file) says "Control stringency: 60% identity to oligo Alien4" as the description for this probe. What does this mean?
..As you can imagine, searches for "Alien4" only brings up sci-fi movies!
p.s. perhaps someone with enough rep could tag this question with more meaningful tags.

It's a probe to detect external 'Alien' RNA standard, a synthetic mRNA commercialized by Stratagene/Agilent.

The Alien RNA transcript is a ~500-nt, polyadenylated RNA molecule that
  is synthesized by in vitro transcription. The Alien RNA transcript is
  nonhomologous to all known nucleic acid sequences currently in public
  databases, as determined by BLAST comparisons against NIH sequence
  databases. https://www.chem.agilent.com/Library/usermanuals/Public/300602.pdf

As any other external standard, you spike in the same amount of Alien RNA standard in your different reactions and then using the Alien probe you can normalize for extraction efficiencies etc. It works not only for microarrays, but also for qPCR, RNA-seq etc.
If you didn't spike in any of it, I expect your probes giving very low signal that's probably why you thought about negative controls.


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What is the energy balance of cooking?
If I cook some food, I get apparently several energetic advantages:

thermal : the temperature of the food is closer or superior to the temperature of my body or internal organs, so I do not have to produce energy to warm it.
chemical : the transformations of the organic compounds during cooking operations may store energy in a potential form: more energy will be released by the digestive process from these compounds than from the raw ones.
mechanical : the food may become easier to chew, absorb, conduct in the digestive tract, leading to less muscular force used.
The cooking procedure may involve water immersion, and the water may penetrate the food and improve all three energetic aspects outline above.

(I may have forgotten a few things)
But what are the respective scale of these advantages, compared to the Joule intake of the raw food ?
Focusing on meat, for instance, is there an optimal cooking duration/temperature and eating temperature for human eaters, independently of personal tastes, for say, beef or chicken meat ?

If I cook some food, I get apparently several energetic advantages...

Let's make things a little more explicit. If you are talking of energy within the body, you are talking proteins, alcohols, fats, and sugars. You are not talking Vitamins or Minerals or any of the unique compounds (like specific antioxidants) that are available in the food.

thermal : the temperature of the food is closer or superior to the temperature of my body or internal organs, so I do not have to produce energy to warm it.

You cannot eat enough to significantly alter the temperature of your body. The average American will eat roughly 5.4lbs of food per day - or roughly 2lbs of food per meal. Given that even raw food is at room temperature, the metabolic requirements to warm food you've eaten is negligible.
What's important is acidity and exposure. Food is generally broken apart and utilized by catalysts and proteins which have specific operating boundaries - which is why your stomach contents is acidic. However, your normal meals will not significantly alter your digestive capabilities either via pKa values or thermoregulation requirements.
What cooking can do is denature the raw food's proteins or compounds so as to make the usable energy sources more readily available. However, it can also just as easily destroy them (the 'char' on barbequed steaks is the meat exposed to high heat long enough to destroy almost everything but the carbon in the tissue). Whether a food gains or loses macronutrients depends upon the specific food and its preparation. A good example is potatoes, which are full of starch (sugars) in their natural state. However, french fries / frites / chips are often blanched before they're fried. The blanching dissolves much of the starch into water, leaving fewer sugars in the end product. However, the process of frying essentially adds fat to the food, and fats have a higher energy density than sugars so you have a net gain in caloric content.

mechanical : the food may become easier to chew, absorb, conduct in the digestive tract, leading to less muscular force used.

For some foods, this is true. Steaming vegetables often makes them easier to chew/eat. The broth of stews and soups often contains micelles of fat and dissolved sugars, affording them greater and faster exposure to the digestive system. Keep in mind, you are not getting a net gain of caloric content from food by doing so, but merely reducing the time to utilization.
The calories saved by chewing less is going to be pathetically small, so to amend the previous paragraph: Yes, for some foods it's true that cooking will allow easier mastication and thus save energy. However, an extra chocolate chip or sip of spoon of rice could easily cover the energy spared.

The cooking procedure may involve water immersion, and the water may penetrate the food and improve all three energetic aspects outline above.

If the energy source is water-soluble (that is: alcohols, ketones, and sugars) then water immersion - assuming you are also digesting the water solution after - will offer faster utilization, not necessarily more.

But what are the respective scale of these advantages, compared to the Joule intake of the raw food?

Negligible in almost all cases. What cooking does is make things more palatable, has the potential to make micronutrients/vitamins more available (not macronutrients), and make the food edible in the first place as is the case with Taro plants, whose roots must be cooked in order to eat.

Focusing on meat, for instance, is there an optimal cooking duration/temperature and eating temperature for human eaters, independently of personal tastes, for say, beef or chicken meat?

No. Cooking meat makes it safer to eat (unless you end up overcooking the meat and end up with a bunch of charred bone) and more palatable. Properly cooked meat has a very low chance of passing on parasites or other harmful organisms. Beyond that, there aren't compelling reasons to expose meat to heat - although as someone who's picked up stomach flus in his travels, it is a very compelling reason to do so.
*The above is based mostly on sporadically gained knowledge. If there are studies indicating otherwise, please alert me to them and I will rectify my errors.


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Finding confidence level of miRNA disease associations
I'm an undergraduate computer engineering student, and I have a project about bioinformatics. In this manner, I need to find prediction( or association I'm not sure the correct terminology) confidence of miRNA disease relationships. Let me make more clear my question with an example. For instance, in one of the bioinformatics related databases( HMDD) it is said that, miRNA X is related with disease Y. I want to find that what is the confidence. I mean  you're 100% sure about such releationship? Do you know any database for that purpose? In HMDD I can only find miRNA - disease name couples it does not give any statistics.

I'm not familiar with the particular database, but isn't there any reference for such entry?

@poka.nandor Actually neither I am, after I asked this question, I looked at HMDD again and I saw that in the explanation of hmdd, it is said that "HMDD  is a database that curated experiment-supported evidence for human microRNA (miRNA) and disease associations." so, since it is curated experiment-supported I think they're 100% sure about their associations

I haven't come across with a reliable database. For the one that you are talking about, if they haven't provided any association 'scores' then you can download the entire data and calculate them yourself. Read the paper/additional data corresponding to the database; they must have done normalization and must have calculated some scores

You can start off by studying how an miRNA regulates the functioning of a gene. it basically binds to the 3'UTR and 5'UTR of an mRNA and restricts its translation. There will be genes associated with the disease of your interest,  find out the miRNA's related to those genes. You can use micro array data to find out the up-regulated genes. Target scan human, miRDB, are various databases for retrieving the miRNA's related with the genes.
The confidence level for finding out the association of certain miRNA's with the disease can never be 100%. but a relationship can be established by simply viewing the complementarity between the miRNA and the mRNA expressed during the diseased state.

Could you add links or citations for people to read further into this topic?


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How do birds deal with their eyes drying out at high speeds?
My eyes tear up when cycling at 15 mph, which is nothing compared to bird airspeeds.
Do birds continuously produce lots of tears and blink a lot, or do the eyes self-moisturize from the inside without need of blinking, or are their eye surfaces just dry most of the time and they don't mind?

I realise that this isn't the point of your question but wearing glasses may solve your cycling problem.

I do wear glasses. I imagine the tearing would be much worse without them.

Birds have a body part known as the nicitating membrane otherwise known as the "third eyelid". This part has become vestigial in humans, where it remains as the plica semilunaris.

This image of a masked lapwing clearly shows its nicitating membrane in action, where it covers the eye in a horizontal motion. This is analogous to blinking in humans, and the membrane moisturises the eye and removes debris while the bird is in flight.

This paper explains in detail how the peregrine falcon (the world's fastest bird) clears and moisturises its eyes when diving at speeds of over 300km/h.

The paper you cited also mentions that most birds' eyes have, in addition to the lacrimal gland, an extra secretory gland at the base of the nictiating membrane. At least in falcons, this secretes a fluid that is more viscous and resistant to evaporation than thinner tears. The nictiating membrane then spreads this over the eye on each blink. The membrane also has microvilli lining the inside of the leading edge that scrubs away the old layer of this viscous fluid, and any tiny debris that got stuck in it since the last blink.

Amphibians also have this membrane to help them visualize underwater @SuperElectric

Birds, like amphibians, have a third eyelid (the nicitating membrane) that helps them keeps their eyes moistened and allows them to better visualize at high speeds (or, for amphibians, underwater). The glands in birds' eyes allow them to secrete a fluid that is more resistant to evaporation than tears. The membrane also acts as a 'windshield wiper,' with each blink a birds' eyes are wiped free of excess fluid and debris.


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Why do people with Down syndrome get fewer cancers?
I'm coming across some conflicting information regarding the correlation between cancer incidents and trisomy 21. I read a report from nature that discusses how Downs are only a tenth as likely to develop cancers, but at the same time are 20x more likely to develop certain B cell malignancies.
One of the more prominent findings show that a regulator of angiogenesis, DSRC1 plays a significant role.
What I'm trying to find out is what gene(s) on 21 contribute to the associated risk for lymphoma?
And does there exist a good list of those genes on 21 that suppress or enhance tumor genesis.

Do the sources you're reading consider the fact that life expectancy is reduced to ~55 in those with downs (http://www.nads.org/pages_new/facts.html), and cancer is generally a late life disease (http://www.cancerresearchuk.org/cancer-info/cancerstats/incidence/age/#Cancer) ? Just a thought..

Certainly an important thing to consider. But in many ways people with DS show a progeroid phenotype in that their blood/brain/intestinal systems seem to prematurely age. Other than the cancers mentioned here, they do precociously develop Alzheimer's Disease. Though many doctors like to explain this by the presence of APP on Chr21 rather than a premature aging phenotype.

@GriffinEvo I think that's due primarily to high incidence of cardiac disease in persons with trisomy so maybe a different issue

@The Nightman, what's interesting is data shows critical genes in AD such as ApoE, PS1, APP etc. are also critical in development in some cancers.
http://www.nature.com/nm/journal/v18/n12/full/nm.3033.html
http://www.cancerci.com/content/9/1/15
http://www.ncbi.nlm.nih.gov/pubmed/17332312

This is great I never saw this paper, thanks for bringing it to my attention. And maybe you know a bit more about this than I do, but to me it looks like ApoE is the only protein associated with this metastasis and angiogenesis. How would APP play a role? And also how does that factor into to reduced angiogenesis in DS?

@rhill45 my point was that, if downs sufferers die on average before cancer becomes prevalent, then that could explain the pattern

@GriffinEvo ah is see now. Good point. &I would hope whatever epidemiologist would have restricted the control group down to  include only people under the median survival age of people with downs

This is a great question. Just to make it clear people with DS do have a reduced risk of solid cancers and an increased risk of blood cancers, (B-ALL and AML).
You are correct in picking out DSRC1 because of its angiogenic implications. The current hypothesis centers around people with DS being less capable of driving angiogenesis, and therefore having an internal environment that is less nurturing to metastasized or even developing solid cancers. Current unpublished work I have recently seen shows this very clearly in the eye, where the vasculature in DS is far less branched than in the wild-type population.
Why however they show an increased risk of leukemias is a largely unanswered question, with one exception being AMKL (Acute Megakaryocytic Leukemia). People with DS are at a ~500X increased risk of AMKL over the unafected population, and it appears to be entirely driven by the in-utero introduction of a stop mutation in codon 2 the transcription factor GATA1. This transcription factor is important in driving differentiation of progenitor cells in the bone marrow to become erythrocytes and megakaryocytes. Thus inactivating this transcription factor plays a large role in disrupting normal hematopoiesis such that megakaryocytes are overproduced and become a leukemia.
All that being said, and as you mentioned people with DS have around a 20-50X increased risk of AML and B-ALL. There are certainly some chromosome 21 genes that have been implicated in this like Bach1 (important in DNA repair) Ifngr2 (plays a role in cell death) Usp16 (epigenetic regulator Really important recent Nature Paper) and Runx1 (important in stress response) but the field is entirely unsure why this directly leads to increased risk of leukemias. Many current cancer biologists favor the direct gene-dosage problem that people with DS face in that a some ~120 genes are overexpressed when they shouldn't be, and assume that these gene level cocktail directly leads to this increased risk of leukemogenesis, and this very well may be in part the answer. There is however a great 'contrarian' view, in that hematopoietic stem and progenitor cells will become pro-apoptotic and pro-differentiative when faced with certain stresses like aneuploidy. The effect of this on a global scale would be that many of the stem and progenitor cells in the bone marrow would die or differentiate prematurely. This would then result in teenagers with DS having far fewer blood stem cells then they should, and these cells would then be tasked with pumping out more blood per cell than originally meant for them quite possibly leading to an exhaustive phenotype. In this way the blood systems of people with DS will 'prematurely age', and might thus rapidly increase the risk of cancer.
Make sense?

I know a little soon but I'm gonna take this answer there's some good info and perspective on here.  it's a big area of study and author did a good job of summarizing. Thank you for mentioning additional genes

Glad to hear it. I think this is a really important question, and is an intriguing area of study, especially because the causes of blood cancers in DS may be part of the key to understanding oncogenesis in the unaffected population.


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Is the amount of blood that flows through every vein and artery per minute really a constant?
I was listening lectures from Mark Saltzman via Open Yale Courses. Now, if I did not understand him wrong, he said that the amount of blood that travels through every vein and artery in our bodies per minute is a constant. Five liters of blood go through the aorta every minute, and since the blood circulation is a closed system, also every other vein/artery must pass that amount of blood per minute. Is this true? How could I (mathematically) show that it is true?

I found the video you have seen at https://youtu.be/It_cV56Dxtk and watching from about 40:00 I can not recognize what you are stating here, more on the contrary though. I suspect you misunderstood him, or can you refer to an exact statement?

I think he is referring to the Bernoulli's principle which states that the sum of kinetic energy, potential energy and the internal energy due to pressure, is constant.

I think the question is not whether the blood flux is constant in time, but rather in space: if 5L/min is the flux through aorta (in given physiological conditions), then at the same moment 5L/min will cross the capillaries. This is volume conservation, for a closed system filled with an incompressible fluid, see this sketch:

If 5L are pushed through the main pipe, the same volume needs to be pushed through the system downstream of it.
Then comes the fact that the system is not perfeclty closed, and some water (and solutes) will "leak" in and out, as @inf3rno points, so this is only approximatively true. Another limitation is that vessel walls are actually elastic, so a change in vessel radius does occur during blood flow. However I believe it is a fair approximation.

It is ofc. not true, because it is not a closed system. The kidneys filter blood and excrete water and other compounds (which are reabsorbed or go to urine), the sweat glands remove water and salts. By drinking daily 2 liters (the total blood volume is about 5 liters) of fresh water and salts are absorbed from the intestines to the circulation, by eating just the opposite happens. Every cell has aquaporins which are responsible for water transport, so they can dilute the blood for a while, if necessary. The spleen can withhold red blood cells (before injury) which reduces the blood volume. The white blood cells can leave the circulation. By inflammation water leaves the vessels because of increased permeability, and so on...

Nope. All blood flows in the body can change at any time(more or less).
If the heart rate and blood pressure, etc, is constant the amount of blood that travels through the aorta is constant, yes. But there is far more capacity in the arterial and venous systems for the actual amount of blood flow there normally is. Veins and arteries contract and expand to route blood flow to different parts of the body, so the amount of blood flowing through any particular artery can change without changing the aortic flow.
A good example of this: Vasomotion. It happens all the time in your hands (sometimes it's even visible as patches of red/white skin. On my hands they're a little smaller than the head of a thumbtack) on the order of minutes. fMRI is a neat technology based around watching brain blood vessel changes in flow as a proxy for activity.
All the flows through all your arteries don't even have to sum to the aortic flow, due to compliance(a fluid dynamics term. essentially, the aorta or other arteries/veins can 'inflate' so more blood is flowing in than is flowing out. Then later they 'deflate' and more blood flows out than in. Arteries tend to be more compliant because they have to be springier to deal with heartbeat). There are also osmotic effects where fluid leaves the arteries and becomes lymph, which then later drains back into veins. It's not a huge effect but it's there. If you measure total blood flow through the aorta and then total blood flow through all the capillaries, there will be less total blood flowing through the capillaries. Not much less( 10% at the most) depending on blood salt and blood vessel position and whether you count the kidneys, etcetera etcetera.
So: the amount of blood that passes through a given artery given the aortic blood flow is not fixed. The amount of blood that passes through all arteries given the aortic blood flow is much closer to fixed, but even that can be different(even if you're not bleeding). And if you were asking if the amount of blood that flows through the aorta is constant, that's absolutely not true. That can vary through the heart rate, the contractility of the heart, the venous return pressure, the overall blood pressure, and a bunch of other things that very slightly affect flow rates.

The amount of blood flow is not constant in general.  As you exert yourself, your heart rate and therefore blood flow increases.  Furthermore, individual vessels dilate or constrict to increase or decrease flow by modulating their resistance to flow.
Your circulatory system is closed however, so all of the blood leaving the heart must eventually come back to it.


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How is the blood volume of a living organism measured without killing it?
How is the blood-volume of an organism measured without killing it?
Note:The blood-volume of an organism is defined as the total volume of blood present inside that organism.

I guess it is possible with plethysmography. If someone confirms this I'll look for a detailed answer.

Could this be done with radioisotopes? I'd imagine a set of scans from different angles could give a reasonable estimate of blood volume.

Polynomial, can you please illustrate a bit more?

@Polynomial, This seems to be it. http://tech.snmjournals.org/content/35/2/55.full

Yeah, that's kind of what I was thinking about. My method was a little less refined and involved a lot of "glowing area measurement", but it's essentially the same principle.

Polynomial gives a good hint. By adding in a known tracer of known amount that should only circulate in the blood stream, the concentration of the tracer when completely distributed will give the volume of distribution.

If the tracer only stays in the bloodstream (and that's a fairly large IF), then the VD will be equal to the VBlood. However, as many pharmacologists know, interactions with proteins and cells can skew that number. The blood volume is also reduced by the volume of the blood cells. However, using Andrei's method of dilution, one can merely swap the cell counts with the tracer concentration.

How it is done according to my bioengineering textbook is injection of a water-soluble tracer into the heart or aorta, then 'listening' for the tracer somewhere else in the bloodstream. If you inject into the atrium and listen at the aorta, you can get cardiac output as well. It takes a minute or so, and gets a measure of the amount of fluid circulating, not counting blood that's trapped or basically not circulating(veins from leg muscles while sleeping, compartment syndrome, etc) while counting fluid that freely exchanges with the blood. Not technically accurate, but gives extra information.

The same book described measuring cardiac output using ice cold saline injected directly into the atrium as a tracer, and it was written quite some time ago(70s iirc). On the whole I trust it as far as I can throw it.

It is easy.
Method A, simple, is based on "counting the fish in the pond" method.

Make rough estimate of amount of blood in the organism.
Choose a component of blood that is replenished slowly [from liver or marrow etc]. That takes time to replenish. Red blood cells are probably OK. Some easily measurable and slowly replenished component of blood. Let's call this component of blood G.
Take small blood sample and measure level of G, denote result G1.
Drain N ml of blood, ands refill same amount back with infusion of normal saline.
N can be taken as 10% of estimate of amount of blood.
Take small blood sample, measure level of G, denote result G2.

G2 will be smaller than than G1.
Now from G1, G2, and N it is easy to calculate organism's amount of blood.
You can derive exact formula yourself.

How long would you wait between samples given that you would presumably have to wait for "G" to diffuse throughout the entire blood stream?

@Rory M: I would suspect diffusion in the blood stream to be almost negiglible. If I remember correctly it takes ~1 min for a complete recirculation of blood in a human, and for smaller animals it would be even less than that.

@Rory M: I'd expect minutes. Pharmacokinetics manual shall have answer to this. Wrt drugs administered intravenously, manual shall have the answer (speaking of humans of course).

Your model isn't very accurate since it depends on making a "rough estimate" of the amount of blood before making any measurements. That's a huge bias that can't be overcome later. I also think your suggestion of removing 10% of the estimated blood volume isn't commendable. What happens in a case where you over-estimated the blood volume? Your model works, but only for an estimation. I think you should provide the equation for any readers who aren't very mathy.

@CHM, I believe that N doesn't need to any particular value. The dilution series will allow one to back-calculate what x% N consist of.

You can use ultrasonography (echography) to measure blood flow.
From the blood flow measurements and vessel dimensions you can then determine blood volume!
If you want a full explanation on how blood flow is measured by Doppler ultrasonography, make sure you ask the question to the right people. They'll help you with the technicalities.

I didn't downvote your answer, I'm not really in much of a position to judge it, but it does seem to be unnecessarily complicated.


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What is the difference between meristem and bud?
Keep reading both terms quite frequently while studying plant physiology. I did some research trying to establish their differences and I learnt that meristems are undifferentiated cells that can generate more cells that eventually could grow to form any part of the plant. But I really mess up both concepts, so I would really appreciate a comprehensive explanation of both of them separately. Thank you in advance for your help!

I looked in Taiz and Zeiger. Plant Physiology 5th ed and this is what I found:

Plant growth is concentrated in localized regions of cell division called
meristems. Nearly all nuclear divisions (mitosis) and cell divisions
(cytokinesis) occur in these meristematic regions. In a young plant, the
most active meristems are called apical meristems; they are located at the
tips of the stem and the root (see Figure 1.1). At the nodes, axillary buds
contain the apical meristems for branch shoots.
The root and shoot apical meristems formed during embryogenesis are called
primary meristems. After germination, the activity of these primary
meristems generates the primary tissues and organs that constitute the
primary plant body.
Most plants also develop a variety of secondary meristems during
postembryonic development. Secondary meristems can have a structure similar
to that of primary meristems, but some secondary meristems have a quite
different structure. These include axillary meristems, inflorescence
meristems, floral meristems, intercalary meristems, and lateral meristems.
Axillary buds are secondary meristems; if they are also vegetative meristems, they will have a structure and developmental potential similar to that of the apical meristem.

So, briefly, I could say that meristems are localized regions where undifferentiated cells reproduce themselves and originate new plant tissue. Axillary buds contain secondary (formed after embryogenesis) meristems. This meristem can behave like an apical meristem if it becomes vegetative i.e. either apical dominance disappears or it is excised and subcultured elsewhere.

A bud is capable of developing into a new individual while meristem can develop into any part of the individual. Buds can produce shoots, flowers, etc. while meristems have more variability - capable of developing into the tissues within the stem, a new individual, etc.

Thank you for your answer, but I was looking for a more comprehensive explanation.

Meristems in plant's kingdom are functionally similar to stem cells in animal kingdom, even you can see it in their names, meriSTEMs & STEM cells ,stem cells are more flexible,okay going back to meristems ,buds are complex of apical or lateral meristems which are covered by special kind of leafs according to enzymatic change,photoperiod and climate conditions buds can produce new leafs,branches or reproductive parts such as flowers, so we can say that buds are some kind of meristems themselves,but there are some other kind of meristems which act more particular and they are referred as cambium which usually cause the production of cork and cause the lateral growth and vascular elements reproduction.


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D/L configuration for amino acids
Why would this be "L-cysteine"? This is taken from the answer key for my biochem final.

From what I understand if the -NH3(+) is on the left then the alpha-amino acid is in the L-configuration.
Am I wrong, or is my prof wrong?

We can look at the list of amino acids on wikipedia for a start. And we can look at this L-alanine:

What makes your image confusing is that it's a Fischer Projection, and I hate those because you have to remember what way the stereochemistry goes. In Fischer Projections, vertical lines face away from you, while horizontal lines face towards you. So if we convert the L-alanine I provided to a Fischer Projection, first we have to rotate the alpha carbon to put the methyl side chain in line with the rest of the carbon backbone. Now we look at the alpha carbon with the NH2 and H looking at us to create the Fischer projection. Here, the amine is on the left, not the right. You drew the amine on the right, which would give you the opposite orientation. If your professor had the amine on the right, I think he was wrong.

Additionally, the D vs L nomenclature is confusing. I prefer the S vs R nomenclature because that's what I was taught for molecules in general. Most amino acids fall into the S configuration, but cysteine is an R, because the sulfur atom has higher priority. However, cysteine is still an L, and the amine would still appear on the left in the Fischer Projection. This is why biologists stick to D and L for amino acids.


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Identification of an insect from Florida
Any entomologists or there that can identify this bug? I live in north Florida, found this guy in my bedroom and thought it was a bedbug but I think it was too big, about half an inch long.

It looks like a cockroach. Not sure which species

@bodonk agreed; definitely a cockroach.

It's a cockroach nymph. Unfortunately it's barely visible given the angle of the photo, but it looks like the pronotum (head shield) has a pale margin - which, coupled with the pale markings at the sides of the tergites, makes me think this is a late-instar nymph of the Australian cockroach (Periplaneta australasiae). This looks very similar to the American cockroach apart from the pale markings, and is found in the southern US as well as many greenhouses. Within the US, it is most abundant in Florida and the coastal southern states. It is found primarily outdoors, where it prefers to live under tree bark, in piles of firewood and other locations that are moist and sheltered, but it can also be found indoors (source). It is the most prevalent cockroach outdoors in south Florida.
It mostly eats vegetable matter but when it enters homes it may eat holes in clothing and feed upon book covers (source).

(image copyright J L Castner; source: University of Minnesota).

This looks like a nymph of the American cockroach, Periplaneta americana. The nymphs differ from the adults in that they do not have wings. The egg sac (leftmost object) is approx. 8mm long.

(source)
 (source)

Not sure about this - the abdominal markings look different and the abdomen itself appears more flattened in OP's post.

@arboviral I agree regarding the markings at the sides of the abdomen, but I feel that the flatness is probably an artifact of the example images being mounted cockroaches. I found another photo which shows less bright abdominal markings, which makes it likely that it was due to intra-species variance.

Could be; I agree it's difficult to tell. On a separate note, could you add a scale bar or something to your photo?

@arboviral Photos are not mine, but P. americana nymphs can range from 2mm-2cm long, which is within the range of ~1cm reported by OP.

Second photo certainly looks more convincing - good find!

Sorry for the poor picture quality, it was 1am and I was trying to sleep haha I freaked a bit because I thought it was a bad bug at first, it was more oval and flatter than I'm used to i, a cockroach, not to mention the white spots. So these nymphs are from Australia? Are they common in Florida?

@yaymuffins I've added some more detail on distribution and behaviour to my answer. Basically, they're the most common outdoor cockroach in south Florida but prefer to stay outdoors.

Thanks! Stack exchange is always a good bet for info because of people like you.


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What are those huge plants / fungi on trees called?
I've seen them in Scotland in August 2015:

The plants / fungi were quite high (over 2m) on the tree. They are almost circular if you view them from the top, I guess (except for the part where they are connected to the tree). I guess the diameter of them might be over 14cm.
What are they called?

I'm asking this question because I would like to upload the photo on Wikipedia Commons. And for personal curiosity.

From a basic google search they look like hoof fungi, but I could be totally wrong.

Are you asking for the species name or the general term for this type of fungi with "woody" fruit bodies? If you are asking for the general term, that is Polypore.

@fileunderwater The more exact you can say it, the better. But I'm already happy about "Polypore" :-)

It's a bit similar to the common Fomes fomentarius (which grows on birch), but I don't know the group well enough to say.

@fileunderwater That was my guess at first, but a quick check seemed to show their fruiting bodies look rather different.

Ok, it's now on Wikipedia: https://commons.wikimedia.org/wiki/File:Inverarnan-Tyndrum-2-Polypore.jpg

Well I will agree with fileunderwater, it is a Fomes fomentarious. For more info check this: Fomes fomentarius is a tough perennial polypore that usually becomes hoof-shaped with age; it is found on standing and fallen hardwoods. Its woody upper surface develops grayish zones, and its brown pore surface features tiny round pores. When sliced open (no easy task, given its toughness) it is usually composed more of vaguely layered tubes than flesh.
Along with Piptoporus betulinus, Fomes fomentarius is one of two mushrooms that the Tyrolean Iceman was carrying around 5000 years ago. He apparently used Fomes fomentarius as tinder.
Description:
Ecology: Parasitic and saprobic on the wood of hardwoods (especially birches and beech); causing a white rot; growing alone or gregariously; perennial; fairly widely distributed in northern and north-temperate North America
Cap: Up to about 20 cm across; shell-shaped to hoof-shaped; with a dull, woody upper surface that is zoned with gray and brownish gray.
Pore Surface: Brownish; 2-5 round pores per mm; tube layers indistinct, brown, becoming stuffed with whitish material.
Stem: Absent.
Flesh: Brownish, thin, hard.


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What limits chromosomal length?
What are the upper and lower limits for chromosome length? Are these limits different in different species or kingdoms? If there is any limit, which cellular or molecular factors are reasons?

There is both an upper and lower limit which are species specific. The upper limit is caused by incomplete segregation of sister chromatids and subsequent trimming of the long arm(s). The reason for the lower limit is, as far as I can tell, unknown.

Upper Limit
Schubert I, Oud JL. 1997. There is an Upper Limit of Chromosome Size for Normal Development of an Organism. Cell 88:515-520.
Hudakova S, Künzel G, Endo TR, Schubert I. 2002. Barley chromosome arms longer than half of the spindle axis interfere with nuclear divisions. Cytogenet Genome Res 98:101-107.
Rens W, Torosantucci L, Degrassi F, Ferguson-Smith MA. 2006. Incomplete sister chromatid separation of long chromosome arms. Chromosoma 115(6):481-490.
In these papers they found that in mono- and dicotic plants and one animal, the chromosome arm length is limited to half of the average length of the spindle arm axis (the length between the centromeres). Due to the mechanism and its presence in both plants and animals, it might be reasonable to expect that other domains of life are subject to similar constraints. Schubert and Oud (1997) speculate that the spindle axis length is fixed species specifically.

These are confocal microscope images of dividing Vicia faba (bean) cells (Schubert and Oud, 1997). (a) Wild-type cell at anaphase. (b-d) When the chromosome arms are longer, the chromatids cannot be completely separated at anaphase. (e) Wild-type cell at telophase. (f, g) Longer chromatids cannot be separated sufficiently and a bridge forms between the two daughter nuclei. (h-j) The bridge is broken when the cell plate forms. (k) Wild-type cell at interphase. (l) Breaking of the bridge between cells with lengthened chromosomes creates irregularly shaped nuclei and micronuclei - these micronuclei represent loss of DNA from the genome and are eventually lost outright through further cell divisions.

Lower Limit
There is a lower limit, but it doesn't seem that anyone knows why, which makes it impossible to accurately define.

Schubert and Oud (1997): Data from various eukaryotic kingdoms indicate the existence of a lower limit of chromosome size for stable mitotic and meiotic segregation. Yeast artificial chromosomes do not exhibit normal meiotic stability until they are of a size between 120 to 500 kb which comes close to the order of size of native yeast chromosomes, in addition to functional telomere and centromere sequences (Niwa et al., 1989). For a Drosophila minichromosome, an island of complex DNA of 220 kb was shown to be necessary for proper centromere function (Murphy and Karpen, 1995). However, for stable mitotic and meiotic segregation an additional 200 kb of a flanking satellite sequence was required. For stable achiasmate disjunction of minichromosomes during meiosis in female Drosophila, 1000 kb of overlapping centric heterochromatin sequences are necessary (Karpen et al., 1996). Schriever-Schwemmer and Adler (1993) have shown that a minichromosome representing the small centric product of a translocation between chromosomes 7 and 15 of the mouse and comprising about 1% of the haploid genome got lost during meiosis in the female carrier organism while the corresponding product of a translocation involving chromosomes 4 and 8 did not. The latter was somewhat larger. Either this different behavior was due to the presence of essential genetic information on the small translocation product 4⁸, or the minichromosome 7¹⁵ was just too small for stable segregation, although it contained a complete centromere as well as telomeres. Finally, we have observed that the frequency of meiotic missegregation, but not of transmission to the next generations, is inversely correlated with the size of translocation chromosomes in Vicia faba (Schubert et al., 1986). Thus, the existence of a proper length range for eukaryotic chromosomes is obvious.
The physical reasons for the lower limit that still enables stable mitotic and meitotic segregation are less clear at present than the constraints for an upper limit of chromosome length

Of course, "present" in that paper refers to the late 90's but, in my admittedly brief search, I have been unable to find too much in the way of more recent results. The following paper seems somewhat promising, but I don't have access to it and can only quote from the abstract. It's not much more recent, either.
Schubert I. 2001. Alteration of chromosome numbers by generation of minichromosomes -- is there a lower limit of chromosome size for stable segregation? Cytogenet Cell Genet 93:175-181.

[A] lower size limit for a stable chromosome transmission … might be based, for instance, on insufficient lateral support of centromeres or on insufficient bivalent stability due to the incapability of chiasma formation.

I must say the effect of a chromosome being so physically long that the sister chromatids cannot divide anymore between the daughter cells is amazingly interesting. I wonder if there is any kind of quantifiable equilibrium between a genome length and the number of chromosomes, i.e. having "short enough" chromosomes yet not too many as the more of them the higher the chances of chromosomal nondisjunction events. (disclaimer, I couldn't find a link between chromosome number and occurence of disjunction events, was just a wild guess). Anyways thanks for this great answer!


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How to determine genotype?

In humans, the ability or inability to roll the tongue is a single
  gene trait.  The allele for tongue rolling (R) is dominant to the
  allele for not being able to roll the tongue (r).  Whether or not an
  individual can taste PTC is also an single gene trait.  The allele for
  being a taster (T) is dominants to the allele for not being able to
  taste PTC (t).

Claudia cannot roll her tongue but can taste PTC. Her mom also can taste PTC but her dad is not a taster. Claudia's grandparents were all unable to roll tongues.
1)  Based on the Info, what is Claudia's GENOTYPE?
I know she is "rr" because she cannot roll her tongue and it is recessive. However; I do not know the complete genotype for the PTC taster.  I know it for sure is a "T," but is it "TT" or "Tt?" How do we know? Do we have enough info to figure it out?

Claudia's dad is not a taster, so he is tt. He passes one allele on to his daughter. Since he is homozygous, he can only pass t. Claudia is a taster, so she must have the dominant allele from her mother, who is also a taster. Thus, Claudia is Tt.

Thank you canadianer. That makes perfect sense. I have one additional question.  What would the phenotypes be of Claudia's parents regarding tongue rolling? Because all the grandparents cannot does that mean both claudia's mom and dad cannot roll their tongues?

@Kyla Yes, that's a logical conclusion. All grandparents are homozygous recessive which means they can only pass on the recessive allele to their children. Thus, Claudia's parents are also homozygous recessive.


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Is it possible to insert DNA without cutting the recognition site with CRISPR/Cas9?
We are looking for a way to insert DNA into a genome, but we would like to do it in a way that the recognition site stay intact to be able to add again DNA at the same location. Do you know if it is possible or if it is already the way CRISPR/Cas9 does it? Apparently multiple systems were already engineered but the few papers we read weren't about our problem.
Sincerely,
Emilie

Inserting into the genome of what organism?

Why not just make sure your inserted DNA segment contains the same CRISPR/Cas recognition site, so you can just cut it again?

@MarchHo I had the same thought initially, but then Cas would cut your target DNA as well. Furthermore, the target DNA would also have a region of homology which doesn't contain your desired insert and repair could occur which doesn't result in insertion of your desired sequence.

We would like to use it on E.coli genome.

@canadianer And Cas9 ignores methylation too. Perhaps try another nuclease (eg ZFN or TALEN) which is affected by methylation?

@EmilieCuillery Is there any reason you cannot just use a plasmid?

The nice thing about CRISPR/Cas is that target recognition is done by RNA, which is relatively easy/cheap to obtain. Could you just get another gRNA which recognizes the new sequence after insertion?

@MarchHo we could do that but then we would have little sequences coming from the former recognition sites "polluting" our added DNA. Our question would be more then: Do you know if Cas9 cuts in the middle of the recognition site or if a special engineered protein Cas that cuts after the recognition site (Whatever the sequence to cut is) exists?

What we want to do is to insert again and again the same sequence at the same location using only one recognition site. Does it seem crazy? we've been searching, looking for few days now but still have problems understanding real mechanism of CRISPR/CAS9... @MarchHo we'll use a plasmid for sure to get the protein we want be then we want our protein to act over and over by adding DNA again and again each time increasing the genome (with notion of order)

I'm not sure about an engineered Cas, but I think nucleases like TALEN don't cleave the recognition sequence. The problem I think you'll face is that your insert must also contain the recognition sequence to be homologous and would thus also get cleaved. You might consider using a mutated recognition sequence in the insert so that it isn't cleaved but still has sufficient homology to be used for repair. Even then, I would expect the target sequence in the gDNA to be replaced by the mutated version in the insert as nucleotides are resected from the double strand break.

@canadianer "Cas would cut your target DNA as well" - what about protecting the target DNA somehow?

I think the best option would be to add protecting groups which can be removed later after Cas9 is cleared. If it is cleared ever. I have low skills by genetic engineering. :D

Look into site-specific recombination.  You can use a site-specific recombinase, specifically an integrase, that can insert a sequence of DNA at a certain attachment site.  You can add an identical attachment site into the DNA sequence to insert, allowing for the reintegration of a new attachment site.  Note however that you might get SSR onto the insertion plasmid itself, so don't do this if you need a specific amount of integration.

Look at the bottom subfigure of A for an example of integration.  Recombinases can also do other things, such as excision and inversion, based on the orientation of the attachment sites.

Doesn't use CRISPR though. Right?

It seems that this also suffers from the same issues as pointed out in the comments. If your insert has the recombination site, it may recombine with copies of itself.

Our projects is basically based onto recombinase. And work...published 2 months ago ... but not by us :( So we are looking for a better efficiency (10^-4 with recombinase) allowing a faster system. As i understand CRISPR/Cas9 doesn't allow insertion of several piece of DNA at the same place butCas9 is a very powerful tool do you think we could engineer it to cut not the homologous sequence but just after of before? (We really have problems understanding where the DNA we want to insert is coming from and the exact mechanism of it. Are you thinking of another way faster than recombinase?

Anyway thank you all for your help but i think we will abandon the idea for now as we learned in our researches that the Cas9 rate and efficiency is much too low to do what we want... i'm sorry ! But thank you again for your help :)


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What are the roles of cadherins in epithelial mesenchymal transitions?
I know that cadherins control the expression of cancer cells involved in the epithelial-mesenchymal transitions, but I was wondering exactly how the process worked.

It's kind of a broad question, can you narrow it down? Simply, loss of cadherins is necessary for breaking cell-cell junctions.

Cadherins have a relatively well-characterized role in EMT, answer is straightforward and actually rather specific.

@Kendall The figure on signalling that you posted shows just how broad this question is; asking "how the process works" is in no way specific. Your answer, while good, is in no way exhaustive and therefore does not answer the question (note I'm not trying to diminish your contribution, only trying to explain why I think the question is too broad). Furthermore, the exact role of EMT in carcinoma metastasis is still under investigation and, while there are clear parallels with the developmental program, their are also differences. The question could easily be narrowed with effort from the author

So let's just quickly define what cadherins are, using general information from wikipedia,

Source: Wikipedia
Cells express E-cadherin (epithelial), N-cadherin (neuronal, or P-cadherin (placental). These generally interact with ß-catenins to modulate cell adhesion. There are pathways intrinsic to cancer which downregulate the expression of cadherins,

Source: Epithelial–mesenchymal transition in development and cancer: role of phosphatidylinositol 3' kinase/AKT pathways
We see in the above pathway described in a study of PI3K/Akt signaling in cancer, some of the ways E-cadherin (encoded by CDH1) becomes downregulated. We also see that ß-catenin may be sequestered by E-cadherin at the plasma membrane, and cytosolic ß-catenin actually interacts within the nucleus as a transcription factor for SLUG (or snail2) where Snail2 is an essential mediator of Twist1-induced epithelial mesenchymal transition and metastasis. In the above figure this modulates reduced cell-cell adhesion, but we also see there's a number of other pathways which modulate the entirety of the EMT process.
What I found interesting, maybe unrelated
An interesting concept currently being investigated involves many of the shown membrane receptors, most of which are involved in some sort of crosstalk in aggressive cancer types. ROR1 was identified as a critical component for modulating EMT, and was shown to participate in Wnt signaling through it's frizzled domain, as well as crosstalk with Met tyrosine kinase, EGFR, and TGFß in some way. These interactions were able to increase expression of snail1/2, vimentin, etc. i.e. characteristics of EMT in breast adenocarcinoma (The linked article provides most of this background, but some may be missing, I'm unsure), and decrease expression of epithelial biomarkers like E-cadherin. When they used a ROR1 Ab to target ROR1, they found cadherin levels could be rescued, and morphological components returned to a more epithelial phenotype. Other articles showed this targeting could induce apoptosis in CLL and this occurs through interaction with PI3K/Akt.


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What is an adjective that describes the property of conferring fitness?
I find it wordy to repeat

trait X is a trait that confers fitness.

I wonder if I can instead write

trait X is useful.

If not, is there an adjective that describes this property of conferring fitness?

Terms
A trait variant that is associated to a higher fitness than another variant is said to be beneficial or sometimes adaptive. On the other hand, a trait variant that is associated to a lower fitness is said to be deleterious or sometimes maladaptive.
"beneficial / deleterious" vs "adaptive / maladaptive"
The terms are very similar but I would tend to think that there are tendencies of using either "beneficial / deleterious" or "adaptive / maladaptive" depending upon the specific context.
These terms can also be used when talking about genetic variants and not only phenotypic trait variants. In evolutionary genetics, the terms "beneficial / deleterious" are used more often than "adaptive / maladaptive".
Also, in general, the terms "adaptive / maladaptive" are often used in absence of variation for the trait in question in the population while the terms "beneficial / deleterious" are most often used when there is variation in the population.
Note
Note that trait X is a trait that confers fitness does not make much sense as is explained here.

I'm not sure "conferring fitness" is the correct way of thinking about things, since fitness is typically a complex combination of traits, but I think the adjective you are looking for is "adaptive" - though this adjective implies that it has been selected as well as that it has contributed positively to fitness, for any inheritable trait that has been around through a reproductive cycle both would necessarily be true.
From https://www.merriam-webster.com/dictionary/adaptive one of the example sentences is:

Webbed feet is an adaptive trait in aquatic animals.


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Sensitivity of eyes to flashing lights
My eyes are very sensitive to flashing lights - for example I'm always the first person to notice that a fluorescent tube is about to fail because I see it flickering when other people can't.
When I'm driving at night, I perceive LED rear lights on cars as being a series of unconnected dots when I scan my eyes quickly across the scene. Evidently, many, if not all, LEDs are actually flashing at a high rate which most people don't perceive.
It almost seems as though I have a higher "refresh rate" than most people. How unusual am I? What is the physiology of it?
EDIT: I suppose what I find most fascinating is that at times when I see a trail of flashes, the spacing between them is remarkably consistent. This implies to me that there is an incredibly accurate timing mechanism somewhere in my visual system that is taking "snapshots" with clockwork regularity - probably between 50 and 100 samples per second. I'd like an insight into this "clock" and why mine seems to be faster than anyone I've ever met.
This similar to what I perceive:

two related Qs and maybe partial answers: http://biology.stackexchange.com/questions/7445/perception-of-artificial-light-flickering?rq=1 and http://biology.stackexchange.com/questions/9277/are-human-eyes-equally-sensitive-to-ac-and-dc-lamps

@fileunderwater Thanks for that - I couldn't find anything when I searched the archive, hence the question. I know about the peripheral vision thing and rod density. I can verify that the fluorescent tube thing is much more sensitive at the periphery of my vision - which makes it even more annoying! It's much more difficult to say with the rear-light scenario, I mainly notice it when I sweep my eyes rapidly so I guess the periphery is playing a greater part in vision at that time than during normal, focussed driving.

4 clarifications would come in handy to answer this question. (a) You speak of LED lights being unconnected dots. Often these are in fact unconnected dots? Is this so extraordinary?; (b) Comment (a) seems to address spatial resolution, whereas the rest of the question seems to address temporal resolution. Are you saying both spatial and temporal resolution are extraordinary? (c) the edit: what trail of flashes? A trail is spatially defined while sampling rates are temporal characteristics (d) where do you live? The mains in the US is 50 Hz, which is not unusual for folks to perceive.

@Chris Stronks I've added an image to explain what I mean a little better. I'm not talking about the individual LEDs in the light cluster - the entire group of LEDs must flash in unison because I see the multiple images like the photo. So as you can see, the movement across my vision (in time) captures the rear light as images separated in space. I'm in the UK - our mains is 50Hz too - but I've never met anyone who can see the flashing of a fluorescent tube the same as me. In what way do you think people are able to perceive 50Hz?

The site where I got the image has a few people who can also perceive these light trails. The suggestion there is that these rear-lights actually flash with a frequency of 200Hz!

seeing trails of dots means you are NOT perceiving individual flashes - otherwise you would see a single moving and flashing dot. but you may be still able to detect something IS flashing, this is probably handled by a different part of our brain visual circuitry.

Interesting point @szulat. Arguably my visual system is failing 100 times per second. It's really the accuracy and regularity of the timing that interests me. It's not something I associate with biological systems at all, hence the question - but maybe biologists see nothing strange in this at all...?


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Are corn kernels considered a grain
I have seen corn described as a seed, a grain and a fruit.
What are the kernels or a corncob considered to be? A grain, a seed or a fruit?

The fact that you asked about corn kernels is important, I think.  @March-Ho's answer is good, but the maize plant itself is a cereal grass.

I think the answer has to depend on the context.  To a farmer at harvest, it would be grain; at planting time, it would be seed.  And to a cook it might well be a vegetable most of the time, but a grain when making cornbread or tortillas.

The grain of corn is known as a caryopsis, which Merriam-Webster defines as:

a small one-seeded dry indehiscent fruit (as of corn or wheat) in
  which the fruit and seed fuse in a single grain

This image by Encyclopedia Britannica shows that the corn seed, enclosed by the seed coat (testa) is then further surrounded by the pericarp, which consists of the layers of tissue around the fruit.
Therefore, the corn kernel can be described as any of the terms that you have mentioned.

I like this line here: "Corn, Zea mays, belongs to the Poaceae family, and while eaten sometimes as a vegetable and sometimes as a grain,it is actually classified by botanists as a fruit, as are tomatoes, green peppers, cucumbers, zucchini and other squashes."


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Do the claims in this paper have any degree of validity?
The paper The waiting time problem in a model hominin population talks about a problem of waiting time, etc. Is the methodology of this numerical simulation, and the conclusion right or is it wrong?
(A quick search reveals that the first author is an intelligent design advocate and apparently believes or believed that the earth is less than 10,000 years old)

I had a quick look at the paper and it is quite hard to understand it as they are using a very unusual vocabulary. For example, they are using the term selective elimination in the abstract which is not a defined concept. Also, they build their own model instead of using existing numerical framework which make it harder to understand what they really did.

If you feel like giving a try summarizing their methods, results and interpretation concisely, I'd be happy to consider reading the paper a bit more and expressing my opinion.

Here is a possible pitfalls in their paper. They are calculating time for a specific sequence (what they seem to call string) to fix in the population from an ancestral sequence that is 100% different. Of course it takes time. The fraction of pairwise differences is very low between related species such as chimps and humans.

Does anyone know of a good take down of this paper I can reference? It is appearing more and more as though it has some value!

I have zero interest in giving a click to what looks like a journal of hogwash.  Can you provide a link to the pubmed abstract?  And if you can't, because the paper can't be found in pubmed, that's a pretty good answer to your question right there.

I'm afraid I laughed a bit when reading that paper for the first time.
Why? Well, here's what they essentially did: They tried to model evolution by implementing an algorithm. They had a population of 10000 individuals, represented by their genetic sequence, and had an algorithm do mutations of those sequences and modeled selection and reproduction to get the next generation. They did that for a long time. Why did that make me laugh? I did both my BSc and MSc theses in the field of Evolutionary Bioinformatics. Almost every student there implements something like that when they first start, to learn to write that kind of program. It's not exactly novel. They even cite several other studies doing this kind of analysis.
Now, their result is basically that human evolution from human-chimpanzee ancestors couldn't have happened because it would have taken way too long. Not only would the whole difference between these two species have taken too long, every single difference of more than two nucleotides would have taken too long to get fixed.
Since this goes against established science, this algorithm better be good... The paper is lengthy and much of it isn't all that interesting or related, in my opinion. But here's the big problems, in my opinion:

When natural selection successfully amplified the target string to the point of fixation (i.e., when the allele frequency reached 99–100 %),

Their target is for their target sequence to reach a frequency of at least 99 percent. That's unnecessarily high, and will of course take a long time, especially as they hold their population constant at 10000 individuals. They don't show a figure with how frequency changed over generations - I'd assume that 90 percent is reached a lot earlier than their threshold.
Holding the population size constant is of course also not a realistic model for human evolution. It wasn't at 10000 individuals for millions of years.

initialization : initialize every individual to the same random or user-specified string (e.g., AAAAA)

Humans didn't start with random sequences and then mutated them to make them do something useful, we started with useful genetic material that then changed. If you start at AAAAA, expect a target of TAGGC, don't confer any benefit to intermediate steps (as they did) at a mutation rate of something like 1 per ten million nucleotides per generation, of course you are going to wait a long time. Mutation rate in genomes also isn't uniform, it varies by region. From what I can see, this was neither taken into account nor discussed.
There is also the problem of them only looking at single nucleotide mutation, not gene duplication, insertions, etc. that also make up a lot of the difference between humans and their ancestors.
Then there's random "mate-choosing", which is a valid simplification to make if you are just looking at some mechanisms of evolution, but not valid if you are going to use your model to estimate time needed for speciation.
They also only allow for one beneficial mutation to arise, then wait for it to be fixed, claiming that anything else would have just resulted in even longer times, without, as far as I can see, just implementing this and then testing that assumption.
At some points, their paper is just going to going for some kind of dramatic effect:

waiting time was 500 million years – which is still extremely prohibitive. This amount of time approximates the estimated time required for the evolution of worm-like creatures into people

500 million years ago, we had the first animals emerging on land and the first chordates. Chordata and the "worm-like" phyla had already diverged.
Basically, in my opinion, they took a very simple model and drew sweeping conclusions from it. This kind of analysis is suited for looking at how evolution might result in speciation, what parameters might play a part, etc. but it is not suitable for estimating the time this takes.
But these are just my first thoughts, I hope there'll a more thorough review of this on the internet somewhere soon.

Actually the estimate of the genetic diversity of humans that made it through the genetic bottleneck in human evolution is accepted as being about 10K individuals, give or take. One think that I don't think you mention is the idea that Evolution, through Natural Selection keeps its successes and throws out its mistakes, which is what allows the Cambrian Explosion to make sense. 3 billion years of working out all the kinks and building the foundation, then 500 million years of diversifying on the successful themes.

@AMR yes, I know that estimate. But those 10K individuals didn't randomly interbreed with each other, they probably formed subpopulations pretty soon, and they didn't stay at 10K for the next 5 million years.

It is only 60-70K years since we were down to around 10K humans... I am not agreeing with the paper, just that it points out how they take facts and warp then to their cause. As you said "a mutation rate of something like 1 per ten million nucleotides per generation." That is the mutation rate per cell division as that is the inherent error rate for DNA Pol with DNA Repair Mechanisms in place. Also they do not take into account events like meiotic recombination or as you mention gene duplications. Many of the differences have more to do with amount of gene product, not differences in genes.

A very late comment however, the time frame presented in paper referenced the OP is actually based on external research by Michael Lynch & Adam Abegg Dep't Biology and Dep't Mathematics @ Indiana University. The claim from this research is that it would have taken at least 200 million years for just 2 mutations...and that is based only on 98% similarity. The figure now is that we are only 85% similar...so the 200 million years would need to adjust dramatically to that now accepted figure...which is significantly worse for evolution!

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Are non-coding RNAs introns?
I am slightly confused as to what part of the genome codes for non-coding RNAs. Is it the introns? This would make sense to me as to why they are not transcribed as the introns are not transcribed. Or is non-coding RNA actually exons which are simply not transcribed? If so, what are the introns actually for? I cannot seem to find a succinct answer to this. Wikipedia, for example, seems rather vague:

While introns do not encode protein products, they are integral to gene expression regulation. Some introns themselves encode functional RNAs through further processing after splicing to generate noncoding RNA molecules.[18] Alternative splicing is widely used to generate multiple proteins from a single gene. Furthermore, some introns play essential roles in a wide range of gene expression regulatory functions such as non-sense mediated decay[19] and mRNA export.[20]

In either case, does anyone also have any information as to why the ncRNA is not translated? What is the mechanism that prevents it from being translated? My guess is that, for some ncRNAs, it is a matter of them not being able to leave the nucleus as I understand many ncRNAs deal with post-transcriptional gene silencing, although tRNA and rRNA clearly do leave the nucleus...
I would be very grateful for any help about introns/exons/ncRNAs. Thank you :)

A clarification on introns and exons.
While it is true that introns are not a part of the mRNA as March Ho said, they are essentially transcribed. This may seem trivial but it is important to note. So:

Both introns and exons arise from the transcribed region
Exons need not necessarily form the ORF (i.e. be translated to proteins)

Regarding intronic RNAs:
The community does not have a good definition of intronic RNAs. Most of these RNAs have been identified by sequencing and the sequencing experiment can only say which region of the genome a read maps to. It does not give any clue about how the RNA was produced.
So any read mapping to intron of another gene has been classified as intronic RNA which IMO is not fully correct. Only reads that truly arise from the intronic region of the nascent transcript (via RNA processing) are to be considered as intronic RNAs, and not merely based on their genomic overlap. Any independent transcript that overlaps with the intronic region is to be considered an overlapping gene. However, ascertaining the mechanism may not be that simple. miRNAs and some snoRNAs are known to be produced from processing of the intronic region.
A statement such as this (from the cited article [18] in your quotes):

Examining the data for intronic and exonic DNA from the human genome,
  piRNAs are significantly more likely than expected ($\chi^2_{1df}$ = 1353.2;
  P < 2.2 × 10−16) to reside in exons rather than introns, given that
  introns are on average, approximately 15 times larger than exons.
  […]
  we found 36 sequences with a perfect match to regions overlapping the
  exon–exon splice junctions of mRNA, suggesting that these piRNA are
  produced from mature mRNA.

may be misleading because it just talks about genomic overlap. Most piRNAs are synthesized as a long RNA that is exonucleolytically chopped from the 3' to yield the mature piRNA. Without further experimentation, making such a statement can be dangerous.

In either case, does anyone also have any information as to why the
  ncRNA is not translated? What is the mechanism that prevents it from
  being translated?

Apart from your reasoning on nuclear retention (many ncRNAs are cytoplasm-localized), there can be many other reasons, chiefly the absence of an intact ORF. Even if an ORF is present, translation initiation requires other features like Kozak consensus sequence etc. Having said that, some reads mapping to lncRNAs have been found to be associated with ribosomes (Guttman et al. 2013). Whether or not they translate is not really known.

While Ankur's answer is correct, it must be noted that not all non-coding RNAs are introns.
An intron must be excised from an mRNA, which therefore means that any non-coding RNA that is not part of an mRNA cannot be an intron.
For example, rRNA and tRNA are all examples of non-coding RNAs that are not introns, since they are not part of mRNA. miRNA may in some instances be produced from introns, but when transcribed separately, they are not introns.
mRNA translation depends on many factors that bind to processed mRNA (a very long process). Other RNA do not undergo this process, and therefore are not reconised by ribosomes and are not translated.

You are correct. I would only say, as your answer is based on exact definitions, that for your third paragraph, it is probably more accurate to say not part of the precursor mRNA, as that implies that is the transcript that started from the TSS and includes all introns and exons prior to splicing.

Yup - in a lot of cases the transcription of non-coding RNAs is from introns. Some of them are within genes (intragenic) and others are intergenic (between genes). In humans, a large number of both have been documented http://www.nature.com/ng/journal/v47/n3/full/ng.3192.html
Coming to your question about why they are not transcribed - it again comes down to the same histone marks and promoters that regulate the transcription of coding genes; there is nothing fundamentally special about the transcription of ncRNA ; differences emerge later when mRNA is capped and polyadenylated, and therefore prone to less degradation.
Also, lots and lots of ncRNAs are transcribed , but are less abundant. Some of the interesting roles they play include interacting with chromatin modifying enzymes, regulating DNA methylation along with the traditionally known functions involving gene silencing by antisense transcripts or miRNA-driven suppression of expression.

Independent transcripts overlapping with intronic region of another RNA cannot be in true sense considered an intronic product. They are just called overlapping transcripts. The ncRNA has to come out of processing of an intron to be called an intronic RNA.

There is evidence for introns themselves giving rise to ncRNA though; not just in the sense of overlapping transcripts. http://www.sciencedirect.com/science/article/pii/S0888754308003042

Yes I agree but in many cases an overlapping transcript has also been called as intronic RNA and I just wanted to clarify on that point.


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Using RNA-seq to compare gene expression across patients instead of between Control and Experimental conditions
I am working with RNA-seq data from the Cancer Genome Atlas TCGA and I have been reading about how people have compared gene expression levels measured by RNA-seq. Many of the papers I have read talk about "differential expression" for comparing each gene's expression levels in the Experimental and Control conditions.
In TCGA data, I typically have a patient cohort who have had the mRNA in their tumors sequenced just once so there is no Experimental-vs-Control dynamic. I am interested in finding which patients' tumors show gene-expression that is significantly higher than the rest of the cohort but I have not had any luck finding literature describing this kind of comparison. I'm thinking maybe I can apply existing differential expression techniques to my situation but that seems cumbersome and not-necessarily appropriate so thought I'd ask the community here if there's a better way of finding which members of a cohort are outliers for specific genes.
Also: all of my RNA-seq data has already been RPKM normalized for me. I have been advised that using RSEM instead would be better for comparing gene expression across multiple samples but, for logistic reasons, I'm probably stuck with my RPKM-normalized expression levels.
Fundamentally, I'm looking for the best way to compare gene expression across samples to determine which samples have outlying high/low gene expression. Intuitively, I figure I could just compute median z-scores for each gene's expression levels within my cohort and consider anyone with a |z-score| greater than 2 to be an "outlier" but I haven't found any literature to support this kind of approach either.
Any suggestions, papers, or advice will be greatly appreciated.

When you say RPKM do you mean crude RPKM or the estimates that you get using expectation maximization methods like cufflinks and eXpress?
It is better if you get your RPKM or FPKM values from one of these programs because you can differentiate between transcript variants.
I have mostly used cufflinks and eXpress. Cufflinks package is better for multiple datasets. You can use cuffquant (which takes SAM/BAM) files to compute FPKM. Cuffquant will also need a reference GTF file. Cuffquant gives a binary .cxb file which you cannot read directly. Once you have generated the .cxb files for all your cohort samples, then pass all these files to cuffnorm. It will normalize the data and give you FPKM values for each gene in each sample in the form of a huge table.
Next point is which genes do you wish to compare. Do you want to compare known oncogenes which show consistent upregulation in all cancers? Actually there is a paper in which they have done this (I'll let you know the reference when I find it. Not able to recollect now).
You can then see how many of these genes show consistent expression in your cohort. Basically you need to identify a set of genes before you go on to study which patient shows anomalous expression.

I've been supplied with the kind of RPKM values you'd get from the Tuxedo suite but I have no insight into the specific pipeline used. I would love to see a paper that compares RNA-seq data between oncogenes across cancers; please post a link when you get a chance. Also: my collaborators have already identified a set of genes to focus on.

I just don't remember which journal it was but I am sure I read one.. Perhaps it is about miRNAs and oncogene interactions in different cancers.

Nonetheless if you want to compare differentially expressed from different cancers then you can get it by doing a principal component analysis on the RNAseq data for different cancers from TCGA

I expect to use PCA later on to see which expression patterns have the greatest impact on clinical data. For the time being though, my focus is comparing a small set of genes across patients who all have the same cancer (I guess I should have included that in my original question). Don't worry about the paper, I never thought to look for papers comparing expression across different cancer types and I've found some useful literature that way.

Seems like you want to have a general approach for comparing gene expression signatures.
A recent paper,Clark et al, takes a geometric approach which is elegant. The idea is to do dimensionality reduction (singular value decomposition) of the expression data, and then calculate the cosine distance between the gene expression signatures in the reduced space.
If you apply this methodology you will be able to group together patients with very similar signatures (small distances) and identify outliers (larger distances). Moreover, based on the loadings from the singular value decomposition, you will be able to identify which genes are driving the differences in the measured distances, and thus identify 'relative differentially expressed genes'.


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Why does high pH result in the denaturation of DNA?
In the Southern blot method, for example, a solution of NaOH is used to denature the DNA in the sample.
I find this counterintuitive since I expected that $\text{Na}^+$  cations would neutralize the negative charges of phosphate groups, hence stabilizing the double helix.

Both high and low pH can affect H-bonding especially in complexes formed by bases such as pyridine, quinoline, imidazole (ref). The bond is most stable when pH = pKa. I am not really sure if this is the case here. Perhaps alkaline denaturation is preferred because it won't cause hydrolysis. This question can be migrated to chemistry SE if no suitable answer is posted.

The pKas of (neutral) guanine and thymine are 9-10 (ref). At high pH (>~10), those bases will be deprotonated and exist as negatively charged conjugate bases. As the deprotonated species, part of the G/C and A/T hydrogen bonding networks are eliminated. In the figure below, green dotted lines represent the hydrogen bonds that explain the observed base pairing. Red dotted lines represent disrupted interactions.

I can add figures if that would help.

That would be great - it illustrates the answer better.

@jerepierre the figures you added were great. Thank you very much