text:
DpnI over-digestion
We have a long protocol that we are optimizing that includes DpnI digestion of a PCR product (to remove any of the template DNA if it's methylated, and while we're not certain in the blind tests, likely relevant DNA will be methylated).
I'm wondering if we can extend the DpnI incubation/reaction time to 4-5 hours.  This will make concurrent steps in the screen easier to manage.  Has anyone extended DpnI digestions?  How "leaky" or nonspecific of a process can it be?
Thanks.

We used DpnI a lot for eliminating "old" plasmids after PCR based site directed mutagenesis. The incubation time varied between 1-5 hours (depending on what else needed to be done) and I never had problems with getting clones from these reactions - and never had trouble with false positives due to incomplete digestion.

If you take your DpnI digest tubes out of the 37oC water-bath after the instructed time (for me its after 5 minutes for PCR based site-directed mutagenesis) and either put at RT or preferably on ice, then you should be fine since the enzyme will not be functioning at those temperatures!

@Bez I'm trying to avoid having the person travel back to the room where the PCR machine is (from an animal facility), thus my question is more in line with Chris's response (I want to know if leaving it longer will be an issue).

According to this instruction (http://www.chem.agilent.com/library/usermanuals/Public/200521.pdf) it can be done for 1 hour but this is for large plasmids. I agree with Chris that it should not be of a problem. Alternatively you can setup your 37oC DpnI incubation step in a PCR machine and after however long that is recommended, you can set the PCR machine to cool to 10oC automatically, that way you can leave it there for as long as you want.

@bez good point.  While I hate to keep PCR machines at low temps for extended periods of time (causes more stress on the machine), dropping it to 4C after an hour is probably the best bet.  Make it answer and I'll accept.

@AtlLED Cooling is less a stress problem (this is done with Peltier elements) but this process produces heat on the other side of the Peltier element which needs to be removed. This is usually done with fans which makes the whole thing pretty loud. Additionally it takes a lot of energy (for example when compared with a fridge).

I regularly do DpnI digestion at room temperature overnight. Can't vouch for 37oC overnight, but certainly didnt notice any off-target activity in my case.

According to this instruction it can be done for 1 hour but this is for large plasmids. I agree with Chris that it should not be of a problem. Alternatively you can setup your 37°C DpnI incubation step in a PCR machine and after however long that is recommended, you can set the PCR machine to cool to 4°C automatically, that way you can leave it there for as long as you want.

My mentor taught me that we can do DpnI digestion for minimum 4 hours and maximum 12 hours. I have ever left the reaction until around 16 hours (?) but the result was okay. My mentor recommended to put at 4oC after 12 hours, if we cannot continue the work immediately.

can you add any references to your answer? also, can you check your answer for typos - is "ever" supposed to be "never"?

In the lab I'm training in, we generally add small quantities of enzyme and keep it for overnight digestion at 37 deg. So the amount of time you want to keep it for depends on the amount of enzyme you're adding. Check the units of the enzyme and add accordingly to the amount of your DNA.
We did a DpnI digestion for mutagenesis too, we added 100 ng of our plasmid with 1uL enzyme and it worked decently. We had another set with 2uL DpnI but that doesn't seem to have worked out since we had zero colonies.
Probably the excess enzyme caused a loss of specificity or some sort of negative feedback inhibition.

Sharing lab practice is great, but preferably add your sources (links, books, papers,reference works (Maniatis?)) so that folks can background-read on your topic.


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Any tool to align whole genome sequence data to another genome and give exon regions a higher mark?
I want to align WGS data from several mammals to one reference such as the human genome sequence. Since in most cases exons should be conserved and spliced in the same way and introns should vary, I want to use a tool that is aware of the annotation of exon and intron.
That is to say that matches in an exon region should have be given a higher weighting than matches in intronic regions.
Also, when a read pair maps to 2 exons, the insert size should be more flexible as the intron length can be vary among different mammals. Since the library insert is less than 2kb for short libraries, the more common situation should be one read on exon and another on intron.
This is different from RNA-seq as I am using WGS data of a whole genome, so both exons and introns are in the reads. And I want to align them to a human reference sequence.

SeqSphere and DNAstar Lasergene software are good

If you are not trying to assemble but just to align each read to the genome, you can use exonerate. On a Unix/Linux platform, once you have installed it run something like:
exonerate -m genome2genome WGS.fasta genome.fasta > out.txt

From the exonerate manual:
          genome2genome
                 This  model  is  similar  to  the  cod‐
                 ing2coding  model,  except  introns are
                 modelled on both sequences.  (not work‐
                 ing well yet)

What I would recommend though, is to align against a reference cDNA dataset, not the whole genome. In that case, you should use this instead:
exonerate -m cdna2genome genome_cdna.fasta WGS.fasta > out.txt

From the exonerate manual:
          cdna2genome
                 This   combines   properties   of   the
                 est2genome and coding2genome models, to
                 allow modeling of an whole cDNA where a
                 central coding region can be flanked by
                 non-coding UTRs.  When  the  CDS  start
                 and  end  is  known it may be specified
                 using  the  --annotation  option   (see
                 below)  to permit only the correct cod‐
                 ing region to appear in the alignemnt.

source: Stack Exchange

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

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At what substrate concentration will an enzyme work at 40% of its maximum rate if its Km = 0.095M?
The question involves the Michaelis-Menten kinetics equation.
Here is what I did: I took the Michaelis-Menten equation, replaced v with 0.4Vmax, canceled the Vmaxes (one on each side), and solved for [S].
I got -0.056 which is obviously wrong, because [S] cannot be negative.

To be honest I know very few about enzymes and absolutely nothing about Michaelis–Menten.
However, when I "took the Michaelis-Menten equation, replaced v with 0.4Vmax, canceled the Vmaxes (one on each side), and solved for [S]", my result is positive:
0.4 * Vmax = S * Vmax / ( Km + S )
0.4 = S / ( Km + S )
S = 0.4 * Km + 0.4 * S
0.6 * S = 0.4 * Km
S = Km * 2 / 3.

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


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Have proteins been observed to come into existence through mutations and natural selection?
A protein that catalyzes one reaction can theoretically be modified by mutations and natural selection and eventually catalyze another reaction completely unrelated to the original. Has this been observed, documented, or at least postulated to be where a certain protein(s) came from?

What do you mean with "in real time"? Sequencing an organisms, adding an evolutionary pressure, sequencing again and suddenly finding a new protein?

The “real time” requirement is an incompatible criterion with the rest. It’s designed to make this question essentially unanswerable.

Mutation of a (duplicated) existing protein is the usual way a new protein evolves.

This sounds dangerously close to the fundamental biblical literalist Ken Ham's distinction between "Historical" versus "Observable" knowledge, which is utter tripe (refer to crime scene analogy). Especially with the odd parameter that "homologs don't count".  As @KonradRudolph eluded to, this question is designed to be unanswerable, but fortunately, the more patient users on this site have provided awesome answers.

@James I apologize for the poor quality of the original question. I was fresh off a heated debate when I asked this question. I have modified it to better reflect my ignorance seeking understanding.

How about EWS-FLI1 and other oncofusion proteins?
One could argue that cancer progression is as close to viewing "evolution in real time" (as you say) as possible.

how was this a new protein from scratch? thnx

Oncofusion is very similar to homologues, especially when there is not modification of function.  Your link on "EWS-FLI1" explains that a virus causes a cancer by modifying gene regulation, which is a change in DNA sequence not Protein amino acid sequence. I don't see how your answer addresses a change in reaction catalyzed.

From the following free review:

Here we review some of the successful strategies in creating protein
diversity and the more recent progress in directed protein evolution
in a wide range of scientific disciplines and its impacts in chemical,
pharmaceutical, and agricultural sciences.

Quoting three examples, but the article has much more:

Directed evolution has been successfully applied to DNA polymerase for
enhanced activity (233) and conversion to an efficient RNA polymerase
(232, 333).
Naumann and Reznikoff (216) used directed evolution to generate a
mutated Tn5 bacterial transposase that could function on transposons
with mutated end binding sequences.
Organophosphate-degrading enzymes have been evolved and selected for
broadened substrate specificity (53, 335). Broadened substrate
specificity of a biphenyl dioxygenase has also been achieved (33, 87,
164, 291). Efforts in cleaning underground water contamination
prompted the evolution of an enzyme for chlorinated ethene degradation
(41).

L. Yuan, I. Kurek et al: Laboratory-directed protein evolution. In: Microbiology and molecular biology reviews : MMBR. 69, 3, September 2005, 373–392. doi:10.1128/MMBR.69.3.373-392.2005. PMID 16148303. PMC 1197809.

Assuming that the OP was really interested in "natural selection" I guess these don't provide an answer. Of course, in the broader sense, human activity could be deemed to be an agent of natural selection.

These are fascinating modifications of proteins. I was hoping for something more drastic than modified binding specificity and catalytic efficiency. Has there been a change in function from one reaction to a completely unrelated one?


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Do people even notice when insects other than butterflies and beetles go extinct?
Lists of endangered animals only include beetles and butterflies if they bother to mention insects at all. Here is an example from where I live:
http://www.dec.ny.gov/animals/7494.html
All of the insects are beetles, dragonflies, moths, butterflies and there is a mayfly, but that is kind of similar to a butterfly when it comes to their "fanbases." Where are the ants, lice, silverfish and aphids? Is there a better list?

I am not aware of a better list, but you are right that (1) many insects have gone extinct recently, and (2) documentation of insect extinction is poor.  An article in Conservation Biology (2005) says

The biodiversity crisis is undeniably an insect biodiversity crisis. Yet insect conservation remains the awkward “kid sister” to vertebrate conservation. Nowhere is this clearer than in what we know, or rather do not know, about insect extinction, particularly for those extinctions that may have already occurred. ... What accounts for the tens of thousands of expected but undocumented insect extinctions? What does this discrepancy mean? How important is it to our understanding of extinction and the future of ecosystems? These should be questions at the heart of species conservation, yet they have hardly been addressed. No peer-reviewed articles have been published reviewing modern insect extinctions, and no estimates of global extinction rates have explicitly focused on insects.

--Modern Insect Extinctions, the Neglected Majority (my emphases)
The book Insect Conservation Biology (2012) may have more info, though it still seems to focus heavily on the more charismatic species like butterflies.

Lots of insects are considered threatened and endangered. The global IUCN Red List (International Union for Conservation of Nature), which is arguably the most important tool for evaluating species' threats globally, is listing 1382 insects as threatened (categories: Near threatened, vulnerable, endangered, criticaly endangered and extinct) and this includes a wide variety of taxa. A large number of taxa have also been evaluated as 'data deficient', which means that they might be threatened, but we do not have enought information to say. Overall, global assessments have only been done for a small proportion of all insects. However, there are also regional (country) IUCN red lists which include a much larger range of taxa.
The knowledge level differs widely between countries though, which means that some countries have hardly evaluated any insects at all while others have relatively good information. In Sweden (which I'm most familiar with), we have a comparatively good overview of insects, probably due to a long tradition of natural history. For instance, species counts on the Swedish Red List includes 196 Hymenoptera, 855 Coleoptera, 217 Diptera, 67 Hemiptera, 545 Lepidoptera, which represents 27%, 19%, 13%, 7% and 21% of all species found in these groups in Sweden. In Cerambycidae (Longhorn beetles), which I've worked with, about 45% of all species are currently red listed.
Generally, the knowledge level on species trends over time or occurrence patterns is limited in insects though, which can make the evaluations difficult. The red list includes 5 main criteria, and indirect data (e.g. amount of broad habitat classes) are often used as proxies for species abundances or potential number of subpopulations. The process of actually determining a species as extinct is difficult though (not only for insects), since rare insects are often found very seldomly. Some "naturally" rare species might be found as singletons with several years between each occurrence, and the cut-off for considering a species as extinct can then be hard to define (a long period of no occurrences could just be a sampling issue). The situation is made easier
if there is a clear trend from relatively high abundances trending towards extinction.


text:
What are the major differences between good study habits for biology vs mathematics?
I'm a math prof. But, I've always loved reading about biology (the paleobiology of microbes and some small animals mostly) it's my hobby but I want to learn more maybe take a course. My longer term goal would be to be able to be of better assistance to my online friends who are biologists who are always asking me to help with the statistics in their papers. (I have been able to help, but I feel like I could do better)
When I study math, I aim to be able to identify and prove all major results from memory, state all definitions, and solve new problems and proofs. I have a process it works.
But with biology I often find that there are multiple definitions or there are big differences between textbook content and studies. It's really upsetting. I understand why this is true, that's just the nature of science, but I don't understand how to best navigate when a topic has multiple interpretations that are all possibly true. I get really hung up on not being able to find one definition for some terms.
Should novices and students stick to textbooks and "widely accepted" definitions? Or should one make and effort to keep up with the most recent research and learn to live with the ambiguity?
I can take one course for free at my university each term. Should I start with 101? Or can I do that through self-study and start with something more specialized?
What is a good self-study book?
My only science background is a few newtonian physics courses.
I'm kind of scared to go to the biology department and ask. Biologists are really intimidating when you teach something simple and clear like math.

Possible duplicate of Introductory biology text for an outsider

Every field is different! I am not sure if anyone could give much more advice. In general, the existence of several different definitions in the literature rarely causes any trouble in practice. Often enough, authors care about defining the terms they are using when dealing with terms that has been defined in several different ways.

It is always a bit scary to start a studying an entire new field. The teaching philosophy may differ from what we're used to, same goes with the type of mental effort but in the end, it always work out. Don't be intimidated by your fellow biologists. Most biologists are quite literate on a number of side fields (typically, data analysis, math, computer science, chemistry, ...), they will understand how lost one can be when starting to learn a new field.

Part of your question might be more on-topic on Academia.SE but I'm not sure they will be able to give much more advice. Good luck!

I don't think this question would be well-received on Academia, it doesn't really fit their scope of on-topic questions. In general, StackExchange isn't really intended for opinion-type questions like this.

Biology is the most vocabulary intensive science to learn. You are learning a lot of new terms all the time because biology is a very descriptive science. With my students I recommend flash cards, mnemonics, word banks, basically the same tricks you might use to learn a new language. Additionally draw things, a lot, and encourage your teacher to sketch things. Biological concepts are often tiered or interwoven enough that even simple diagrams can make it much easier to understand.
as you said definition are not set, basically different branches of biology will use slightly different definitions, (defining species based on ability to interbreed works ok with animals but is useless for bacteria for instance.) you are not seeing changes in definition with new research as much as you are seeing different working definitions for different branches. For the purposes of a class the exact definition is less important than the concept. think of the difference between a book and a pamphlet, you cant really say where one stops and the other starts on the spectrum of printed media but you are relatively sure most of the time which one you are looking at. As much as I don't like recommending it wikipedia often has very nuanced descriptions of biological terms which can also be helpful.
One important concept in biology is that almost everything lies on a continuum or spectrum, very few things are truly discrete. Organisms don't exist in discrete categories we invent those categories to make it easier for us as humans to think and talk about them, which works fine on the large scale but can get very blurry on the more detailed scale.  Because of this terms are often vague on the macroscale but get get more precise as you get more specialized. (this is why there are no less than eight separate definitions of species, how would you define it in fossils for instance) It also means that even basic concepts often have several conditions/assumptions that have to be true before they even apply. The fact that almost everything in biology is conditional is a big impediment to understanding when you first start.
There is an old joke in biology that there is an exception to every rule including this one. This is because biology constantly comes back to the real world for its information, it is focused on description and prediction less proofs. Even in a single organism there are so many interactions on so many levels that generalized rules simple fail to predict details ( for a comparison, imagine trying to do calculations when you are only allowed one significant digit).
I definitely recommend starting with the basics, this is important in any science, jumping right into more specialized classes is like trying to learn quadratics without understanding basic algebra, you are just making it harder on yourself. In biology it is especially bad becasue you hit a wall of terminology which biology needs just to keep from describing things as "that squishy grey bit squirts the yellow stuff on the red pastey stuff"
If you are truly very focused on math, mathematical/theoretical biology may be the most interesting as it is concerned with describing biology in mathematical ways. But really the advent of computers has led to a huge surge in applying mathematics to biology, because the complex equations are now practical. But it is important you have a basic understanding of biology first, if for no other reason than to get past the terminology/jargon wall. On the upside biologists know that terminology is an issue so they often have resources to help, that is why so many biological terms are laid out on wikipedia. Additionally a basic grasp of latin root words can be a big help, since so many biological terms use latin roots (originally to make it easier but now when no one speaks latin it makes it harder)
now an obligatory comic.

I started in cell and molecular biology, but moved to applied math and computer science, so perhaps I can give my thoughts.
Personally, I found that biology learning was more about big ideas and visualization. The first is because biology has an extraordinary amount of details (e.g. Molecular signaling pathways, biochemical properties of different molecules, the location of different foramen in certain fossils, etc...), so it is truly impossible to remember them all. You should focus on learning what to look up, not what is actually occurring. Something you work on will be gradually memorized on its own, so don't spend effort memorizing things you can look up (you're not an undergrad :) ). So don't remember that histone acetyltransferases use acetyl-coa to act upon the NH3+ groups of lysines. Just remember that those enzymes modify chromatin in a way that alters transcription, thus changing the cell and its behavior. The second (visualization) is because it is very hard to understand biology without pictures! So use them, not text (no kobayashi and nomizu style). Mathematicians like symbols but (at least in the molecular case) there are too many of them (and they are mostly useless names... e.g. P53). Much of biology is about seeing  visual results (blots, fossils, medical images,...) and interpreting them.
Note that (I think) the first suggestion is harder in biology than in math, because math partitions naturally into theorems, corollaries, lemmas, and their applications (roughly in order of importance of what you need to know :) ). Biology as a field is more of a fast moving chaos of  observations and changing inferences. But of course there is a constantly growing core of the field that is not in flux.
One good thing about biology is that one can be an expert in one area but know little about most others. Math is a little more intertwined. So there's no need to read a "general bio" book. Just read an intro book to your target topic (e.g. Ecology, evolution, cell bio, molecular biophysics, bioinformatics ...). They will cover the relevant parts of other fields, usually. I know genetics experts who know basically nothing about cell trafficking for example. But you will definitely need some background to read the latest literature (i.e. Don't skip straight to Cell papers).
One issue that occurs throughout science, but also in math, is that learning is a process of improving models. In math, we might start with linear algebra, then basic manifolds, and eventually with, say, finsler spaces. In physics, we go from Newton to Einstein. In biology, we start with a basic model and set of rules, but gradually add exceptions and details to it. I think this is where much confusion can arise, because things that were correct in the simplified model might be wrong in the better, more complex one.
Also, models are being updated at an insane rate in biology. Often that means that previous models were wrong (though the evidence underpinning them is not); hence definitions and results might change over time! Science improves over time, and this is a good thing. Of course, in math, once something has been proved, it will never change. (Although definitions, or at least notation, in math can be very inconsistent too). Of course, if there are inconsistent definitions, you can ask here and see what people think. I will agree that biologists are less concerned about detailed rigor than being correct overall. Generally scientists will either define such things themselves or cite a reference with their chosen definition.
My suggestion for your question is to learn the basic widely accepted definitions first, then go to the literature. Often it is the case that different groups think different things. Most likely, one or both will be proven wrong eventually. Each paper is likely to be internally consistent; the only ambiguity is usually in areas where no one knows the correct answer or interpretation. Two groups in conflict usually have reasonable hypotheses consistent with the evidence, and if they can't decide how to mesh their ideas, probably we can't either. So don't worry about it too much.
So when a topic has multiple interpretations that are possibly true, use your math background and consider it from a Bayesian perspective :) most likely all the interpretations are at least partly true, and have some non zero probability of being true. And as you read more papers, update your posterior. :)
Also, don't worry about talking to biologists (as the other commenter states). In fact, among the sciences and engineering fields, my opinion is that biologists are on average the friendliest and least arrogant :)


text:
What are these flitting sea worms?
I filmed the creatures below this August in the Mediterranean (specifically, the port of Fornells in Minorca of the Balleares). The images were taken from a boat moored just outside the harbor and floating above a field of posidonia in case that is relevant.
There were many of them and they were whizzing about at high speed:

This is to give you an idea of the scale. The jellyfish on the right was about the size of half a tennis ball.

They were a very strange sight since there were so many of them and moving so fast. You can see a video of them in motion here:
http://www.youtube.com/watch?v=GJCzjXALRJ0
The image quality is not very good but you can see how fast the things were moving. So, any idea what these are? I am assuming they are larvae of something or other but what?


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What's the difference between life expectancy of cigarette smoker and general population?
Some say that smoking cigarettes will shorten lifespan. By how many years is the lifespan of a typical smoker shortened? What are the common cause(s) of death among smokers? Are there any known statistics for cigarette smoking and life expectancy?

The difference in life expectancy between smokers and non-smokers appears to be at least 10 years on average, in a survey of American adults between 1997 and 2004.
The same paper lists causes of death (higher among smokers than non-smokers, as measured by hazard ratio), although this is not exhaustive: lung cancer, other cancers, ischemic heart disease, stroke, other vascular disease, and respiratory disease have an adjusted hazard ratio of 1.7 or more, with 94% of lung cancer deaths attributable to smoking among female smokers, and 93% to smoking among male smokers.
If you have access, you will probably find Table 2 (hazard ratios) of interest.
Figure 2 shows the survival probability:

I have added Figure 2 to the answer (it is free to view and it is clearly fair use anyways)

@nico: may I ask how you extracted it? I couldn't find a link.

There is a link to the PDF on the right, copied, saved it on my HD then uploaded it here (or you can just grab a screenshot).

What is interesting is the multiplicative effect of industrial disease with smoking,  in lectures (regrettably unreferenced slides) we are advised that in the case of asbestosis risk ratio for lung cancer (not mesothelioma)  is 7 in a non-smoker but a staggering 93 in smokers with asbestosis.

Bravo. I am speechless. Do we have the same data for ganja?

@JimThio: I think that data is a little harder to come by, given the different legal status in different states (I am not aware of research outside the US).  You might find this interesting though: http://www.nap.edu/catalog.php?record_id=6376

@JimThio while marijuana actually has some protective effects (as demonstrated in mice, don't have the reference at hand), the basic problem in smoking is the act of smoking itself not what it is that you are inhaling. Whether you smoke weed or tobacco, you are still inhaling carbon monoxide and screwing up your haemoglobin and you are still ingesting free radicals and screwing up your DNA. Sorry (and I truly am, I am a heavy smoker of various substances).

@terdon: seriously doubt you would ever "ingest" (although inhale would be the correct word) free radicals from smoking. They are too short lived and reactive to be actually directly inhaled.

@nico, The gas phase of cigarette smoke contains small oxygen- and carbon-centered radicals that are much more reactive than are the tar-phase radicals. and that's just the first random reference I found. Also, although I live in France, English is my native language :). Ingest is quite correct in that context. The Oxford Dictionary Online even uses this phrase as an example of the word's usage: "they ingest oxygen from the air"

@terdon: I mantain that you inhale smoke, you do not ingest it. Ingest is mostly used for food (Oxford English Dictionary, offline edition :P). English aside, I do not doubt that smoke contains radicals, what I am saying is that they are most likely not those that directly affect DNA. They will rather generate cascade reactions creating new radicals, oxidising proteins and so on, especially in such a oxygen-rich milieu as the lungs.

@nico I only used ingest to avoid a third repetition of inhale so I won't push the point :). As for whether they directly affect DNA or start a cascade, I honestly have no idea. The abstract of the paper I linked to seems to claim that both are true: "Cigarette smoke contains two very different populations of free radicals, one in the tar and one in the gas phase. [...] In addition, we have shown that the principal radical in tar reacts with DNA in vitro, possibly by covalent binding". Anyway, my main point was just that whatever you smoke, the act of smoking is harmful.

@terdon: agree. I was just nitpicking


text:
Definition of Dye- Reduction Test?
Can some one give a simple explanation or definition on what a dye-reduction test is.

Dye reduction tests (and there seem to be loads of different ones) are simply assays in which a dye becomes decolourised to give you a visual indication of whether a certain process is occuring. Here you can find an example of a dye reduction test with Methylene Blue and Reazurin which indirectly measures the bacterial densities in milk and cream. See this google book for more info.


text:
Improving Gel Extraction yields
How can I improve my Gel Extraction yields. We use the standard protocol from Qiagen, gel extraction, dissolve in QG buffer at 42C and purify via anion exchange columns. However, with 500 ng we ultimately get 100 ng for a 20% yield. I was curious what else has been tried for gel extraction.
We also add IPA and NaOAc to the dissolved mixture prior to the column purification.

When I optimized gel extraction in my hands, two factors turned out to be critical in maximizing gel extraction yield:
The pH of the eluting solution. I used to elute the final product with DEPC-treated water initially, but the yield would vary a lot as the pH of the water changed. Using buffer EB is better, since it maintains a stable pH 8.
Most importantly, *incubate the eluting solution with the column as long a possible (and also elute twice). * I incubate for about 10 min, which is longer than what they recommend but it works much better.

I also want to use this post to mention there are cheaper alternatives to the Qiagen kits, such as the ones here: http://www.mn-net.com/, that work just as well and sometimes better. Using those can save you a lot of money. This is not an ad: I or my lab are not in any way affiliated with the company or website I'm linking to. I'm just sharing customer experience.

Try dissolving at 50C.  In the Qiagen gel extraction kit, it says to dissolve at 50C or until completely dissolved.
The size of the gel is important too.  Make sure it is 1.5% or less, and the size of the gel needs to be less than 400 mg.
Also, pay attention to the first step.  If the liquid is not the same color as the color of the first QG buffer then there is a pH problem.

Elute from the column with Elution Buffer that has been preheated to 50-60 degrees. I stick mine in the incubator for the duration of the extraction so it is warm when I come to elute. It seems to help yield.


text:
205 nm UV-Vis readings
Typically we determine the concentration of proteins using a 280 nm reading. However, it is reasonable to use 205 nm. I was curious about the effectiveness of this method.

What evidence do you have for the reasonableness of reading at 205?

@MattDMo: I guess it is because usually nucleic acids are measured at 260. However, I am not sure 205 would remove DNA background noise... These are very approximative quantifications anyways, and only give a general idea of protein concentration.

@MattDMo, I didn't want to lead the question but I was looking over this paper. There is a scientific basis for the quetion. http://onlinelibrary.wiley.com/doi/10.1002/pro.2253/abstract


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Why does the PR form of phytochrome exist?
I know how it gets converted because PR is more stable and when there is neither red or far red light PFR naturally converts to PR. But what is the point of it? If PFR is the biologically active one why didn't evolution just make one pigment, PFR. At night neither is active so PR again has no point, in the morning PR gets converted to PFR. So why do we need a PR?

First off, "evolution" doesn't necessarily lead the most efficient system for anything - it works with what we already have.  Once something has evolved, it might not go away, if there is no particular harm to having it around. You might take a look at the evolution tag, as other people have asked similar questions about the "usefulness" of biological mechanisms and molecules.
Aside from that, having both isoforms is important for the detecting the color of light. When Pr absorbs red light, it gets converted to Pfr, and when Pfr absorbs far red light, it gets converted to Pr.  The ratios of Pr to Pfr allow plants to determine light levels and adjust their growth accordingly:

Sunlight has a R:FR ratio of 1.2

Light under a canopy of leaves has a R:FR ratio of 0.13

Light under 5 mm of soil has a R:FR ratio of 0.88

A higher proportion of FR light allows plants to detect when they are
shaded. Plants adapted for growth in full sun will display greater
stem elongation when they are transferred to shade.  They also develop
smaller leaves and less branching.  This change is due to greater
proportion of Pr to Pfr.

Seeds of certain plants require red light for germination; FR light inhibits germination.  Many small seeds with low amounts of storage reserves (such as lettuce) show such a red light requirement.
If these seeds they are buried below the level of light penetration in the soil, they do not germinate.
If they are shaded by a leaf canopy, causing a high proportion of FR, germination is inhibited, [as] Pfr is required for germination.

Source: Missouri Botanical Garden


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Does the existence of one species imply the existence of many other?
Reading one of Sir Arthur Clarke's scifi stories, I came across a statement something to the effect of, existence of a single species automatically implies the existence of many other species. So considering multi-cellular organisms, something more complex than a virus/bacteria, if we know for a fact that there is one species (plant/animal whatever) then without directly observing any other species or any obvious evidence, can we deduce that there must be other species? Assume we are in a completely new environment like a brand new planet discovered with life on it. Does the existence of a  species imply existence of many other species?
Thanks.

I am not sure I'm providing the kind of answer you would expect.
Your question is very conceptual. For such question it is important to very well define the concepts you're using. For example, the concept of species is not well defined (and will certainly never be well defined as it does not represent a natural category to my point of view). Also, the separation you do between complex and non-complex species might not be obvious. For example, you create two categories which are bacteria/virus and multicellular. But you kind of forget the many of the eukaryotes which belong to non of these two categories. Or some bacteria that might almost be considered as multicellular.
I think it would help answering your question if we had the arguments of Sir Arthur Clark for saying such things. Below are two arguments I could use to defend your statement.
Speciation:
If you consider than one population rarely (or virtually never) go under sufficiently major changes before undergoing speciation, then you would never have only one species which is very different from the others.
Ecology:
One might consider that one species cannot by itself be responsible of a whole cycle of elements. Therefore, if the species we observe can theoretically live forever (equilibrium), then, it implies that other species must exist to recycle their wastes. But this hypothesis has nothing to do with the separation of species per complexity that you do.

Update:
Following your comment: So what you had in mind seem roughly the same than my "Ecology" argument. The difference is that I emphasized on the fact that one species alone cannot live for ever because they degrade their resources through time. I did not want to say that one individual of one species cannot live without the presence of another individual of another species. This individual would need the presence of the other species not for himself but rather but its great-great-grand-children when one resource would have been totally consumed by the ancestors.
For your curiosity, here is base of the tree of life. What is eukarotic but not plants, animals or fungi are called protista and are all (or almost all?!) unicellular. You'll notice that viruses/viroid and prions does not belong to this tree. It would be a bit long to explain why they are no represented and it would have nothing to do with your question :D

I don't have much of a biology background at all so I just assumed naively that viruses/bacterias are "simple". I read all of his short stories back to back so I don't specifically remember which story it was. But if I remember correctly, humans see some giant whale-like creatures on Jupiter and a character remarks about how there must be many other species here. I myself interpreted it to mean like how we humans have a symbiotic relationship and need help like for metabolism, etc.


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Statistical Analysis of Protein Folding Problem
I’m new to the field of protein folding. I’ve been searching and came across some books for predicting structures (Introduction to Protein Structure Prediction: Methods and Algorithms). Does anyone know whether I can find some code (say in C++, Java, or R) related to the prediction of protein structures? Or, do you know other good articles or books related to the statistics of the protein folding problem?
Thanks for the help.

Welcome to Biology.SE. As your question stands currently, it will likely be closed as "non-constructive." The Help page gives guidance on the types of questions to ask and not ask. We're looking for questions that have straightforward, factual answers, whereas "what's a good book to learn about ..." questions can have many, equally-valid answers. Additionally, a quick Google search will easily answer your first question.

One of the quickest ways to get oriented on what is going in the world of protein folding and modeling is to look at the proceedings of the Critical Assessment of Structure Prediction (CASP).  CASP is basically a contest, held every 2 years where anyone can use their algorithm to predict the 3D structure of a protein whose structure is known, but not publicly available.
Its been a few years since I reviewed them results much - it looks like this year was interesting, but a perennial winner has been Rosetta, which has turned into an edifice of many suites of software which each execute different tasks in protein folding and modeling.
Open source software is pretty hard to find in this field.  The software is complex.  It usually includes components of machine and statistical learning, molecular dynamics, specialized algorithms that build up the protein one residue at a time, others which manipulate blocks of the protein structure around in space, electrostatic calculations, you name it.  In addition, the software, once it gives some sort of result is quite valuable.  I don't think any of these suites has really been released.  I know that Rosetta is available to use as a web service, but you have to apply for access to the source.  I don't think its an easy thing to get.
Some of the most complicated components are available open source.  Molecular modeling and molecular dynamics open source software is quite sophisticated.  I think we need an open source protein folding suite open source.  I think David Shortle's algorithms might be a candidate for such a suite as its not so complicated and it works in some cases.
This field is pretty obscure and difficult to get around in.  There aren't any easy introductions that I know of.  Protein structures are computationally expensive and painful to work with in terms of writing software.  On the other hand protein folding that really works is a revolutionary breakthrough, at least equal to the impact of the development of computers as a technology.


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Why do veins look blue?
I know that veins carry oxygen.
Veins look blue because the oxygen-depleted blood in them is blue.
Is this true??

It's not because the blood is blue. You can easily confirm this by noticing that when the nurse draws blood from your vein for a test, it looks quite red, and neither does it turn blue inside a sealed test tube even though the living cells would presumably use up the oxygen. Furthermore, even if you hold your breath and blow it on blood, it does not turn blue (and even pure CO2 won't make it blue).

If you have "the flying circus of physics by walker", it has a very good explanation of this phenomena.

Well, even though most people presume that it appears blue (reference) is due to the blood being deoxygenated, it is actually not the truth because blood is never blue whether it is deoxygenated or not. In a paper by Dr Alwin Kienle titled Why do veins appear blue? A new look at an old question, the authors measured how much light of various wavelengths was reflected from both real blood vessels in skin and imitation vessels in a skin-like environment. The synthetic vessel (which was a capillary tube filled with blood and placed in a milky substance with optical properties similar to skin) allowed the authors to experiment with a variety of parameters (particularly vessel depth and diameter), and they were then able to validate their results by taking measurements on actual vessels in skin. They eventually came to the conclusion that the optical properties of skin and blood is what makes the veins appear blue.
I quote from the paper as to the reason of blood appearing blue.

"Blue light does not penetrate as deeply into tissue as red light.
  Therefore, if the vessel is sufficiently deep, the reflectance in the
  blue will be affected to a lesser extent. Deoxygenated venous blood
  has a greater absorption coefficient than oxygenated arterial blood in
  the red spectral region, and this difference of two, rather small,
  values is amplified because of the long path length of red light in
  scattering tissue. As a result, veins are more likely to look blue
  than arteries at the same diameter and depth. Often arteries are not
  seen at all because they are generally smaller than veins and have
  thicker vessel walls. It has been shown that a small vessel will look
  red when close to the surface. However, if a superficial vessel is
  large it can still look bluish, particularly in the case of the vein.
  On the other hand, if the depth of a vessel is large, even red
  remitted light will not be influenced by the vessel, and it will not
  be seen."

So in short, the blue appearance could be attributed more to the location of the vein than just the deoxygenation.


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Why would a single celled organism evolve to be multi-celled?
I read a story this week on Richard Lenski who has been 'evolving' E. coli for more than 50,000 generations now.  One comment I read was from someone who doesn't accept Evolution who pointed out that we haven't seen a single celled organism 'evolve' into a multi-celled organism.  Another person responded and said that a bacteria is not going to evolve into something that isn't a bacteria.
So, if Evolution created single celled organisms and then multi-celled organisms how might that change have happened?  And is it possible to recreate that set of driving forces to make a bacteria something other than a bacteria?
To that end, what advantage does being multi-cellular have over being unicellular (if that's even a word)?

There are quite a lot of books addressing this question. Here are some few examples: Major transitions, levels of selection and Major transitions revisited. Note concerning the question of level of selection versus kin selection one might be interested by this article

Two things:

Although there are a number of hypotheses, as others have pointed out, this is not an entirely solved problem. Attempting to figure out which hypothesis (or hypotheses) are most plausible is an ongoing area of research.
2.Clearly, saying that "a bacteria is not going to evolve into something that isn't a bacteria" is an oversimplification. Eventually this is possible. But it would take orders of magnitude longer than we can test in a laboratory - even with such impressive experiments as Lenski's.

@seaotternerd, If we use 20 years as a human generational time period then 50,000 generations is 1,000,000 years.  Looking at the 'conventional' timeline for human evolution we have progressed quite a bit in the last 1,000,000 years - easily changing 'species' more than once.  Given that, why do you say that 'orders of magnitude' more generations are required to see a change in bacteria?

@CramerTV - While it's true that the lineage that lead to humans has transitioned between "species" multiple times within the past 1,000,000 years, the evolutionary distance between two different species (say Homo sapiens and Homo erectus) is orders of magnitude smaller than the evolutionary distance between two different kingdoms (bacteria vs. non-bacteria). Bacteria would have to undergo multitudes of changes in order to be considered something other than bacteria.

Take a look at the social amoeba, Dictyostelium discoideum to see an example of how a single celled Eukaryotic protist can exhibit social, cooperative behavior that leads to the formation of a cooperative multicellular spore that allows for species survival under starvation conditions.

The question suggests that you might want to have a look at Understanding Evolution (UC Berkeley), a free online introductory course to evolutionary biology

How did multicellularity evolved?

It is an ongoing field of research - Some insights about the origin of multicellularity
This is a big ongoing field of research. To start with an example, there was relatively recently (2012) an important article by Ratcliff et al. that shows that yeast can quickly evolve multicellularity under selection on the speed they sink to lower water layers. This article is one among many others and is far from being able to explain everything we would like to understand about the evolution of multicellularity. Typically, I think that this yeast species had a multicellular ancestor and we might think that this species would already have fixed alleles (=variants of genes that is fixed meaning that the whole population is carrying this variant today) in the population predisposing this species to easily (re-)evolve multicellularity. Also, they may have kept some standing additive genetic variance in their genome from their past and they would therefore very quickly respond to selection as they don't need de novo mutations. (Sorry if this last sentence was slightly technical).
One of the first traits that we usually refer to when talking about the evolution of multicellularity is the presence of sticky proteins allowing individual cells to paste to each other.
Some insights about the evolution from simple multicellular to more complex multicellular
Then, we could talk about more complex multicellular and argue how do these simple multicellular evolve into some more complex organisms. A common argument is that multicellular can have specialized cells are very could at doing what they're doing as they are specialized. Also, some level of complexity is thought to have raised due to the fact that multicellular organisms tend to have smaller population size than unicellular (see Lynch and Conery, 2003). It is important not to confuse evolution of complexity with the evolution of multicellularity although these two notions are somehow related.
What do you mean by multicellularity?
The evolution of multicellularity can be discussed in the context where sister cells form an organism together or when unrelated cells (among the same species or even cells from different species) come together to form an organism. Also, the multicellularity can be discussed at a different level depending on how we want to define multicellularity. Is a stack of cells reproducing individually, working for their own benefit a multicellular? Do we need a division of labor? Do we need a division between germline (reproductive caste) and soma line (non-reproductive case)?
How many times did multicellularity evolve independently?
Some people consider that there are multicellular bacteria (biofilms) but we will avoid discussions that are based on limit-case definitions. Let's talk about eukaryotes. Most Eukaryotes are unicellular and multicellularity evolved many times independently in eukaryotes. To my knowledge, complex multicellularity however evolved only (only?) 6 times independently in eukaryotes.

Metazoa (animals)
Ascomyceta (fungi)
Basidiomyceta (fungi)
Viridiplantae (green plants)
Florideophyceae (red algae)
Laminariales (brown algae)

Model organisms and interesting cases to study multicellularity
There are a bunch of specific clades that are particularly interested in studying multicellularity because they present transition states. For example Volvox is a chlorophyte genus and the species in this clade present different stages of multicellularity; Some species are exclusively multicellular, some form small groups, some create big colonies, some have some division of labor and some even have separation between the germline and the soma (Some castes don't reproduce). (ref1, ref2, ref3, ref4, ref5, ref6). Yeasts are also a good model organism for studying the evolution of multicellularity.

Not trying to quibble, but there are multicellular green algae, are they included in Embryophyta for the purpose of the list, or are they independently multicellular too? Or are they not complex?

Good point. I think I was no inclusive enough when saying Embryophyta. According to tolweb.org (here), charales (who are multicellular) aren't Embryophyta. I think it would be correct to say Streptophyta. However, because the phylogeny doesn't seem to be perfectly solved yet (and because I don't know if groups such as ulvophycae are multicellular or) I just edited my answer to say viridiplantae (green plants).

As you say though, the level of complexity of the non-embryophita, green plants might be low enough to not be considered but I am not quite sure how complex is their multicellularity compared to the brown algea typically, so I'll just go safe and include everybody! Thank you

A model organism used for the study of cell signaling that transforms from a vegetative state to a cooperative multicellular spore is Dictyostelium discoideum in the absence of food. This organism demonstrates how simple cell signaling can lead to cellular aggregation and cooperation, in order to insure the propagation of the species, even to the point where some cells are sacrificed to form the stalk of the spore, which elevates the spore above the surface to where it is more likely to encounter food.

For one thing, larger organisms are much more energy efficient.  This is what is known as Kleiber's Law where the caloric requirement scales as the 3/4 power to the body mass.
Another thing is that when all the cells cooperate to form a multicellular organism, each given individual is more likely to reproduce and less likely to die due to environmental variation because cooperation creates stability.
There are several theories about how this came about,but those are the elements of why.  Collaboration and efficiency improve the chances of survival, which is to say that selection will favor multicellular organisms however they came to be.

Disclaimer: Not my field of research, and not a field where I know the litterature well. See it as a complement to the other answers.

A distinct advantage of multicellularity is specialized functions of different cells. This can allow for higher efficiency of e.g. metabolic processes, and also that redundant functions can be removed from some cell lines, since they can be handled by other cells. Therefore, the constituent parts can become simpler, while the resulting organism becomes more complex at the same time. Mathematical modelling of cellular systems have shown how this type of division of labour can evolve from unicellular lines (Ispolatov et al. 2011), through the steps of aggregation and differentiation from preexisting functions.
An interesting intermediate step that can provide some clues to how multicellularity can evolve, is in cyanobacteria, where some unicellular species can show partial specialization e.g. when part of cellular biofilms. A phylogenetic study of cyanobacteria has also shown that they have reversed from multicellularity to unicellularity at least five times, and most extant cyanobacteria seem to descend from multicellular ancestors (Schirrmeister et al. 2011). This means that the evolution of multicellularity is not a one-way process, but seems to be a much more complex process.

I STRONGLY encourage to read work from the lab of Nicole King - she studies Choanoflagellates, which are the "out-group" for animals - they are, in some sense, the most animal-like single-celled organism that exists.
Chaonos are also amazing because they go through a single to multicellular transition in there own life cycle, so they provide an amazing opportunity to understand when it is more beneficial to be single-celled vs. multi-celled. Currently, one of the working hypotheses of the group is that one of the main drivers of the push towards multicellularity may have just been simple fluid dynamics: the flows around a spherical multicellular "rosette" of chaonos bring more food to them.
If you are interested in the evolutionary transition to multicellularity you must read work from the King Group.

If single cells are capable of surviving on their own then why did multicellularity evolve?

This situation can be compared with the evolution of family and society, in a way; during the time of crisis, the survival chances increase when someone stays in a group.
Similar conditions would have resulted in the evolution of multicellularity. The difference between being truly multicellular and just being a group of cells is that in multicellularity, the individual cells cannot survive in the absence of the other. Moreover, different cells in a multicellular organism perform different kinds of functions. However, it is certainly likely that grouping without a strong dependence would have constituted the early stages in the evolution of multicellularity.
One of the complex kinds of microbial colonies is biofilm. In a biofilm different "regions" of the colony have different kinds of functional roles; the "outer" cells take up nutrients for the colony from the surroundings whereas the inner cells reproduce and keep the colony thriving. Bacteria have also evolved a way of signalling (or "talking") to other bacteria (of the same species) by a mechanism known as quorum sensing, which in a way changes the behaviour of the bacteria when then stay in a group.
Dictyostelium or slime mold (or affectionately called dicty :) ) is an example of early evolution of multicellularity in eukaryotes. When there is plenty of food, dicty stays as unicellular amoeba. However, when there is a shortage of food, the dicty amoebae start grouping up and give rise to a multicellular "slug". The dicty slug roams around and when it encounters right conditions (such as humidity), it differentiates to give rise to a "fruiting body", which more or less looks like a fungal spore. In a fruiting body some cells form the spores (which will produce new dicties) whereas some cells form the stalk (which supports the spores). Apparently, the choice of what part will a cell become, is random and at this stage the individual dicty amoebae are no more selfish. The aggregation of dicty amoebae is co-ordinated by a signalling molecule called cAMP and this works in a way similar to quorum sensing.

 Taken from Wikipedia

Volvox is another example of an early stage of multicellular evolution.
To sum up, as you said single cells can very well survive on their own. However, in some situations being multicellular would have given the organism some survival advantages. You should understand that this is just one of the survival strategies and not all organisms needed to adopt this. In fact, there are many more unicellular species in the planet compared to the multicellular ones.
I would reiterate Remi's suggestion that you should have a look at this site called Understanding Evolution, hosted by UC Berkeley.
You can also look at this post on our site about a recurrent doubt faced by many students and non-experts in the area of evolution: "Why do some bad traits evolve, and good ones don't?"

For the same reason that sociality evolved so many times among animals. There are lots of advantages in having similar fellows. And multicellular organisms are, after all, just a colony, sometimes a society, of individual cells.

Interesting perspective.  I never equated multi-cellular evolution with symbiosis.

Thanks, @CramerTV. I remember coming to this conclusion after studying Volvox algae.

The eucaryote that became the modern organelle mitochondria, combined with procaryotes. This probably occurred as a result of the mitochondria being absorbed by the parent cell but not destroyed as it usefully created energy rich ATP molecules using Oxygen and Water through respiration.
These were the first Eukaryotic cells, they went on to become Eukaryotic, multicellular life.

Various benefits to Eucaryotes becoming multicellular include:

The volume to surface area of a cell gives cells a natural size of a few micrometers. Larger single cells find it increasingly difficult to absorb enough nutrients or oxygen for the volume of there cytoplasm.
Amoebas can be larger due to being so irregular in shape, this ensures that so nowhere inside the cell is it too far from the cells surface. Various more spherical centimetre scale single celled life also exists in nutrient rich parts of the deep ocean, such as the Valonia Ventricosa.
https://en.m.wikipedia.org/wiki/Valonia_ventricosa

Another advantage is that structures can form between cells, outside of the cell walls, that can still be protected inside the creatures body. Such a connective network in animals called the extracellular matrix.
https://www.khanacademy.org/test-prep/mcat/cells/cytoskeleton/v/introduction-to-cytoskeleton

Note that creatures like the sea sponge are multicellular, but do not have distinct areas of the body such as organs in the same way as animals do.
"The genes I discuss in my article were not present in the common ancestor of all life on Earth. They do not exist in bacteria, for example. They do not even exist (as far as scientists know) in sponges. Only after the ancestors of cnidarians and bilaterians diverged from sponges did they emerge." (A planet of viruses, Carl Zimmer) This is the quote I could find, as I remember, relating to "bodybuilding" in many creatures, but not the sea sponge.

Why the downvote?

There is no obligation to give feedback with a downvote. Given the frequency of your posts getting downvoted I'd suggest you read on how to write good answers in the help pages, look at some well received answers on other posts etc. Also given that you have previously been confrontational and defensive in the face of comments and criticism then perhaps downvoters are less inclined to comment (it would be a waste of time).

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evolution and mutation of microrganisms against medicines?
I presume microorganisms would have very short life span and they would multiply more creating millions of their kind. Is it really a threat to consider when we use anibiotics and other stuff more making these creatures becoming resilient to the medicines. On the other hand bodies becoming dependent on the medicine making us weaker .we clean our office spaces homes etc with bleaching agents, acids killing microorganisms and thus making our body unaware of these and letting these organisms survive and create more deadly strains.
I believe there are examples like malaria microbes becoming resistant to quinine perhaps many more.  If someone tries not to take medicines when he suffers from common cold and small fevers and let the body fight but is it right to do so considering that mecines are available and one should take them.
There is an article also published today.

A few throughts about this: Microorganisms have a short life span but they replicate very fast with a short generation time. So this create vast amounts of "offsprings" with some mutations naturally occurring. Due to this large numbers the chance of developing resistances is much higher than for slowly replicating species.
This is especially true, when the selection pressure is high, as this is the case when you treat with drugs which usually kill these microbes efficiently. When people are not taking these drugs (antibiotics for example) according to the necessary scheme, the concentration of the drug in the body is lower than necessary to kill of all microorganisms. This leads to the survival of microorganisms which are a bit adapted to survive the drug and so on.
The real problem are people who are not following their treatment regime necessary and thus causing resistancies. A case for this is tuberculosis. Regarding taking medication: Always take them when necessary and leave them out when not. A simple cold for example can not be treated antibiotics since it is viral, the secondary middle ear infection usually can.

Great answer.  I'll add that there is debate in medical circles (especially primary care) whether to treat mild ear infections (without hearing alterations) with antibiotics at all, since statistical analyses are showing that the vast majority resolve on their own naturally without treatment (source: UpToDate, PubMed) and the more antibiotics are used, the more resistance develops.

Also, there used to be widespread overuse of antibiotics for upper respiratory infections when most URI are viral, sinus infections are usually secondary to viral and far more rare than people think, and (similar to ear infections) frequently resolve on their own (sources same). Overuse of antibiotics has caused resistance, as discussed.  We're causing bacterial evolution right in front of our eyes.  Look up MRSA, VRE, and multi-drug resistant organisms (MDRO).  It's scary to wonder how close we could be to an epidemic of bacteria resistant to everything we currently have!


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Are there any examples of sudden leaps in evolution?
As far as I understand, various abilities like flying, sight, hearing etc. were caused by slow evolution, where those with a greater ability to to these things had better chance of survival. (If this assumption is wrong, then I am happy to delete this question).
Are there, however, any documented examples of by evolutionary leaps being made, over the course of just a few generations? I understand, that some abilities have a tipping point where one gets the ability suddenly, but there is not a lot of physiological change made. An example of this would be the ability to climb a tree, which could suddenly be possible if the body weight is reduced with just a few percent. What my question is about, are sudden changes to the characteristics of a creature.

How sudden is sudden enough for you?

@Kevin It depends upon the magnitude of change in the characteristics of the creature.

E. Coli being able to subsist on cellulose?  That was a nice laboratory controlled experiment, showing the 2 mutations change required for that.  Although that was only rapid in chronological time, since it was 40,000 generations of bacteria.

@Brightblades This is certainly interesting, but with this question I was primarily thinking about things happening over the course of tens of generations. On the other hand, what really counts for the survival of the fittest is of course adaptability to adapt in chronological time. How long time did this adaptation take?

@David I don't recall precisely, but it was over a period of years (one scientist doing the experiment).  It's only been going for 24 years:  http://en.wikipedia.org/wiki/E._coli_long-term_evolution_experiment

@Brightblades Thank you for the link. It is certainly interesting reading!

I see my memory is failing on several levels...  It wasn't until 2008 that the processing of citric acid happened.  Man, I need a check up I think.  I think the whole idea of Punctuated Equilibrium may fall in to your question of rapid evolution:  http://evolution.berkeley.edu/evosite/evo101/VIIA1bPunctuated.shtml

I believe that the technical term is a "Hard Sweep".

@kmm and @shigeta provided you with a nice observational account of sudden leaps in large organisms. However, if you want to look at where this is the norm and try to build a mathematical theory then you need to look at something much smaller; the prime candidate is affinity maturation.
In the human immune system, when exposed to an antigen B cells produce antibodies. If it is your first exposure to the antigen then the antibodies produced will probably have very low binding affinity. However, after some exposure time, your B cells will start to produce antibodies with much higher affinities for the antigen and thus you will be able to better fight off the disease. The cool part, is that the antigen produced is tuned via an evolutionary process!
There is differential survival, with only antibodies with the highest affinity being able to survive. Variability is introduced by a very high mutation rate in the complementarity determing region (CDR). (Tonegawa, 1983). The length of this evolutionary process is very short, typically a local equilibrium is found after only 6-8 nucleotide changes in CDR (Crews et al., 1981; Tonegawa, 1983; Clark et al., 1985), so you need only a few point mutations to quickly develop a drastically better tuned antibody.
The standard mathematical model for this is Kauffman's NK model. With a protein sequence on $N$ sites, we say that evolution is fast (and we have a sudden leap) if after our fitness landscape changes, we can get to a new local equilibrium in a number of generations that scales with $\log N$. Kauffman & Weinberger (1989) showed how this model can be used to study affinity maturation, and showed that to achieve a sudden leap we need high epistasis and low correlations between pointwise mutants. In particular, their model suggests that typical epistasis in the CDR is on the order of 40 proteins (out of the total 112 proteins in the CDR).

References
Clark, S.H., Huppi, K., Ruezinsky, D., Staudt, L., Gerhard, W., & Weigert, M. (1985). Inter- and intraclonal diversity in the antibody response to influenza hemagglutin. J. Exp. Med. 161, 687.
Crews, S., Griffin, J., Huang, H., Calame, K., & Hood, L. (1981). A single V gene segment encodes the immune response to phosphorylcholine: somatic mutation is correlated with the class of the antibody. Cell 25, 59.
Kauffman, S. and Weinberger, E. (1989) The NK Model of rugged fitness landscapes and its application to the maturation of the immune response. Journal of Theoretical Biology, 141(2): 211-245
Tonegawa, S. (1983). Somatic generation of antibody diversity. Nature 302, 575.

Zuk et al. (2006) document the rapid evolution of song-less crickets in a population of crickets that previously used song for courtship.
In less that 20 generations, over 90% of male crickets of the species Teleogryllus oceanicus evolved to a novel morphology ("flatwing") that rendered them unable to call to females. They hypothesize that this shift resulted from the presence of an North American invasive "acoustically orienting parasitoid fly."
Basically the flies detect calling males and parasitize them, rendering them unable to reproduce. Were it not for the presence of the parasitoid fly, the flatwing flies would likely not have survived. Non-calling individuals rely on the presence of calling males to bring females near for mating.

Even though it is a nice example of evolutional change, I am just wondering whether the loss of a previously existing ability to produce songs can be seen as an evolution, not devolution or involution?

Evolution is just descent with modification -- adding or subtracting doesn't matter.

@Alexander Galkin: wouldn't you consider evolution a fish evolving into a land animal and losing the ability to breathe under water?

The ability to drink milk by the inheritance of lactase persistence via a single allele change. Sociology and genetic studies have shown that the immigration of a few lactose tolerant people into large non-lactose tolerant populations, the lactase persistence gene quickly spreads through the population, a sign of a dominant mutation and survival of the fittest at work.
Not in the mood to dissect the papers but here are a few commentaries:

http://sciencelife.uchospitals.edu/2011/09/14/lactose-tolerance-in-the-indian-dairyland/
http://news.discovery.com/human/got-milk-drinking-common-ancestor-india-and-europe-do-110914.html

Is lactose intolerance really likely to stop an organism reaching reproductive age and being successful?

There is a good amount of genetic evidence that does suggests so. Examples of natural selection are seen in pastoral communities that shifted from a farming community to a dairy community. Unfortunately I don't know the field well enough to find good sources.

This is selective sweep (i.e. a given allele’s abundance is sweeping through a population via selection). But that isn’t in itself a sudden leap in evolution since the allele is already in existence (= “has already evolved”).

@Konrad: However, the lactase persistent allele itself is the result of a single spot mutation that is believed to be of rather recent origin. (Some studies suggest it happened around ten thousand years ago, which is an eyeblink in evolutionary timescales.) This is another case of evolution via function loss: the mutation that causes adult lactose tolerance basically disables the switch that, in most mammals, turns off lactase production after weaning.

I think that this might refer to evolution in punctuated equilibrium as described by Stephen Gould et al way back in the 70s.  If this is the case, it refers more to the idea that changes and speciations can be quite rapid in time and for long periods you don't see morphological changes or speciation events in the record.
If so, then this is influenced by the study of evolution in cases where there are large changes in the environment very rapidly. The classic case is when there is a bare island and new animals arrive only rarely. This is all very much inspired by Darwin's observations in the Galapagos, but has since been studied quite a bit.  In such cases you see just handful of sets of birds suddenly appear and you find a finch that can scrape bugs out of bark, another that can dig into narrow niches in the rock for food, where in a broader ecosystem two completely different species would be utilizing those 2 food sources.
It should be said that no evolutionary leap should be understood as an acceleration or deceleration of evolution.  Only a change in the rate of adoption of variations because of a wider set of possible advantages those variations can represent.

Even under punctuated equilibrium, acquisition of new traits happens over a period of thousands of generations, not “just a few generations”. It is punctuated on the geological timescale only.

With all due respect, a few of these answers, although good examples of selection at work, were voted too high given the specific question asked: “documented examples of by evolutionary leaps being made, over the course of just a few generations?”
Sometimes we’re better being honest and identifying something as an ‘unknown’ or ‘yet to be observed’ than to list (and have people up-vote) poor examples.  We do evolution a dis-service when we promote poor examples as answers to questions like these.
To expound:
The cricket losing the ability to sing (communicate) examples does demonstrate mutation and natural selection at work, but really only shows the REDUCTION of a capability.  It’s not a good example of evolutionary leaps.  It only happens to be beneficial in one SPECIFIC context.  This would be analogous to tanks on a battle-field which communicate via radio, vulnerable to radio-frequency tracking missiles.  Any tank with a broken radio would not be vulnerable to these missiles.  Although technically ‘beneficial’ in this context, it’s an example of a loss of capability, not a gain of capability.  We need to promote examples of mutations that PRODUCE capabilities.
Lactase persistence example likewise is an example of mutation and natural selection, but not a good example of a GAIN in functionality (as some have pointed out in the comments).  It’s technically the loss of the normal switching-off mechanism of lactase production following weaning.  So once again, a loss, that happens to have a beneficial side-effect.
Regarding punctuated equilibrium, I’m not surprised that was mentioned but was surprised that it got some votes.  It’s a hypothetical explanation for why we see gaps in the fossils, but not conclusive ‘evidence’, or in the case of the question asked not “documented examples”.
Again: We do evolution a dis-service when we promote poor examples as answers to questions like these.  Let’s focus on quality, not quantity when it comes to presenting evidence for evolution.

I disagree. The designation whether a loss of a switch-off is a 'loss', or whether it may be a 'gain' in a genetic switch-on is purely semantic if we don't know about the epigenetic mechanism. Even then, I think it's semantic. I think lactase persistence specifically is a nice case of neoteny. When there is a strong and sudden positive selection for neoteny, and when this becomes stabilized quickly in a large fraction of a population, I think this can be confidently discussed as a case of a gain of function and as 'punctuated', or as OP puts it, a sudden leap. My $0.02.


text:
What portions of the brain have drastic changes in activation when we "sense" someone is there?
I was watching an old Arnold Schwarzenegger movie ("Commando") where he plays an elite soldier (surprise).  An enemy tries to sneak up on him, and Arnold says that he smelled the other guy approaching.  While this is possible, I find it to be more hyperbole than truth, but what modalities and areas of the brain would he would harness for this detection task?
All of us not being super soldiers, we do occasionally get a feeling when someone has entered a room silently behind us.  Is it audible clues that fall below a certain threshold, is it the sensation of air moving in a the room, some sort of vibrational or proprioceptive sensation, or a combination of all three of these?

First of all one should tell that one can attribute the activation of certain brain zones with some indepent events only when the activation takes place along the signal input (receptors, sensory pathways towards the cortex and the sensory areas in cortex) or motor action (=output) (along the motox cortex => motor neuron => target organ). Those zones in brain are also termed as primary ones, for there is a clear mapping between the event/action and the activity here.
In case of your "sneak feeling" as you describe in your post, there seems to be more not the sensory input from some unknown type of receptor, but rather a subconscious processing of the complete sensory input that reveals some potential danger and is percepted as a kind of "smell of danger". Since this processing happens in secondary zones and can be well distributed throughout the whole brain, there is no possibility to find a single focus with high activity change here (in my opinion, of course) -- those changes in activity are beyond the measuring/imaging capabilities of modern examination methods.
Possible sensory inputs here might include (but not limited to):

Optical (some shades, moving asyncronously etc).
Acustic (some sneaking sounds, normally disguised by the background sound).
Air move, air stream blocking sense etc (tactile feeling).

So, everything you suggest might apply here.


text:
What specific membrane adaptations do cells have for saline-rich environs?
Are the cells of marine animals and flora equipped with special ion exchange pumps to mitigate the effects of a saline-rich environment?
Or have the cell's membranes adapted through structural changes to counter the osmotic forces?

This 1969 Steensland paper seems to suggest that the membranes of halophiles are stabilized by sodium ions and they rapidly denature at lower-salt conditions (2.2 vs. 4.3 M).  The protein composition of the membrane was generally acidic, stabilized by all the Na+.
As far as what the role of the halophile membrane is in sheltering the cell from the high ionic strength solution seems left unsaid.


text:
Largest extinct clade?
What is the largest (by large I mean most general) clade of organisms that has gone extinct?
domain > kingdom > phylum > class > order > family > genus > species
So, for example, an extinct kingdom would be larger than an extinct class.

What do you mean by large? Do you mean in terms of number of species, number of individuals, weight of the individuals, ...? Is there any reason why you wrote the taxonomic ranks at the end of your question?

domain > kingdom > phylum > class > order > family > genus > species

added a comment to clear this up

@futurebird There are genuses that contain more species than some classes.

I'm not interested in the number of species, I'm interested in extinct creatures most genetically distant from everything alive today.

Semantics aside, I think the OP wants a group of animals which are  grouped together as related and which are extinct.  I propose trilobites.  They are no more but at one time they ruled the earth.
from https://en.wikipedia.org/wiki/Trilobite

Trilobites ( /ˈtraɪləˌbaɪt, ˈtrɪ-, -loʊ-/;[2][3] meaning "three
  lobes") are a fossil group of extinct marine arachnomorph arthropods
  that form the class Trilobita. Trilobites form one of the earliest
  known groups of arthropods. The first appearance of trilobites in the
  fossil record defines the base of the Atdabanian stage of the Early
  Cambrian period (521 million years ago), and they flourished
  throughout the lower Paleozoic era before beginning a drawn-out
  decline to extinction when, during the Devonian, all trilobite orders
  except the Proetids died out. Trilobites disappeared in the mass
  extinction at the end of the Permian about 252 million years ago. The
  trilobites were among the most successful of all early animals,
  roaming the oceans for over 270 million years.[4]


text:
Michaelis-Menten Kinetics: Does measuring apparent Km and Vmax take into account competing reactions?
I am learning about why it is important to measure Km and Vmax for each experimental setup because measuring the "apparent" Km and Vmax includes enzyme inhibitions of which one might not be aware.
However, what if there are entire reactions going on that are consuming the product or substrate that are not known? Are these accurately aggregated into the Km and Vmax measurements?
Here are some of the links that I read through:
http://www.bio.upenn.edu/media/pdf/courses/F02/BIOL202/Handouts/BIOL202.ApparentKmandVmax.pdf
http://en.wikipedia.org/wiki/Enzyme_inhibitor

Obviously no. If you read any text describing the derivation of the equation you will see that the reaction is considered in isolation. How can it take into account the unknown?

Have you heard of something known as "Occam's Razor" ?
It says when you have multiple possible explanations/hypotheses then select the one which is simplest (i.e least number of assumptions)
Same with mathematical models. Chemical kinetics models usually assume first order unless there is some evidence against it. Similarly, for enzyme kinetics, as long as you don't think there is something anomalous going on, use Michaelis-Menten model.

What if there are entire reactions going on that are consuming the
  product or substrate that are not known

Many physiological enzyme catalysed reaction are not Michaelis-Menten. If you happen to have an insight about it or if the simulations dont match the experimental data, you can revise the model.
However, Michaelis-Menten model for for competitive inhibition exists, as you yourself indicate in the link.

As Arthur Kornberg said: "Don't waste clean thinking on dirty enzymes."

Discovering an assay for a biological event in a cell-free extract opens the way to its molecular resolution and reconstitution (Commandment I). Trying to devise a mechanism with a crude extract, even with ingenious experiments, is generally a waste of effort. An extract is too dirty; purification is the only way to go.

Added in response to a comment from Dexter:
Kornberg was quoting Efraim Racker. And in any case my original link is dead.

+1 for awesome quote. But original quote is by Efraim Racker -- http://jb.asm.org/content/182/13/3613#sec-4

Thanks, I didn't know that. My link appears to be dead so yours is an excellent replacement.

The answer is no really, but some variants might allow you to study inhibition.
Michaelis Menten kinetics are experiments which try to characterize the catalysis characteristics of a reaction but to do so the numbers are obtained at concentrations of substrate that you dont find in a cell.
Vmax is defined as the maximum rate at which the reaction is run in question.  To measure this the substrate concentration is also maximal - the binding sites of enzymes must be fully occupied during the entire experiment. So by definition there is no competitive reaction possible here.
Km is a binding constant obtained where the reaction rate is found to be half Vmax.  This definition is free of any competing reactions.  You can use Michaelis Menten kinetics to study competitive inhibition though and by comparing a reaction rate and comparing it to the reaction rate (called Vo) you can derive a Ki which gives you how much your inhibitor has affected substrate binding.


text:
What is the oldest example of DNA identified?
What is the oldest sample of genetic material (presumably DNA) identified? What are the prospects of pushing back much further into the geologic record?

419 million year old DNA from halophilic bacteria.
http://news.discovery.com/earth/oldest-dna-bacteria-discovered.html

My understanding was that DNA in non-living matter had lifetimes of thousands of years, not millions. How did such ancient DNA manage to be preserved? Does this result hold up?

Before DNA there was RNA. But ever heard of the polymerase chain reaction? See DNA and RNA don't actually need enzymes to replicate or a live cell. If you heat up and cool down DNA or RNA at certain temperatures and add in bases/nucleotides it will go ahead and do it by itself to make more DNA or RNA. Evolutionarily it's likely RNA came first, whilst the molecule itself was preserved (because it could self replicate) it wasn't conserved (the order of bases didn't matter so they swapped a lot). DNA is more stable, put RNA on a bench and it quickly degrades, so that's why DNA was required.

I rather think that if the proper chemical conditions can preserve the molecules within tissue, you can find very old DNA.  In this case the bacteria were preserved in crystalized salt and this seems to have kept the DNA intact.  Other examples are from insects preserved in amber and tissues from animals who were buried in permafrost.


text:
Confusion related to a term probe-by-background interaction
I was reading a paper related to bioinformatics where it uses the drug response on the cancer cells and the gene expression of the individual cells are studied to find any useful insights. Specially, using the gene expression of the cells a predictor of the drug response is created.
They have stated that just using the correlation between the gene expression and the drug response might not be a good predictor. But the genes interact through signaling pathways to drive a particular drug response.
What these guys have done is like used PCA on the gene expressions of the cancer cells to use the components which preserve the greatest variance.
Actually, I didn't get what they mean by probe-by-background interaction and how it is calculated.
Can anyone please explain. I googled for a while but didn't get it.
Here are some quotes from the paper where the term is used

Towards this end, we have compared how well drug response can be
  predicted by simple statistical models, which either directly relate
  probe and background networks to drug response or consider
  probe-by-background network interactions.
To generalize this approach, the term ‘probe’ could be
  replaced by individual transcript expression levels measured through
  other gene expression methods. Similarly, ‘background networks’ and
  principal components are used interchangeably. Generally, ‘background
  networks’ could be represented by any data reduction method that
  summarizes the expression of a gene network. We demonstrate that
  probe-by-background network interactions significantly enhance drug
  response predictions, over and above the predictive power garnered
  through utilizing individual probes and background networks alone.

cross-posted with BioStar: http://www.biostars.org/p/68510/

Posting the paper here is likely to get everyone into trouble, as the content is owned by Nature Publishing Group.  I added a link to your post - at least a few of us do have institutional access. Also, I do not expect anyone to try to read the article from screenshots.

Rather than including screenshots, can you provide a few examples of where the authors use the term that you are unsure about? Just a sentence or two, quoted, would be fine and within fair use, I think.

I rolled back your edit. We do not want screenshots, as that is very likely a copyright violation. My suggestions was to quote several instances where the term is used.

The "probe by background" interaction is the response of different probes as a function of background gene expression. For example, depending on which of the 6 backgrounds a probe is in, the drug response may go up or down. Probes as a function of background is probably easier to imagine than background as a function of probe (which is equally valid). For 39,115 probes and 6 background networks, there are 234,690 interactions.
In a technical sense, "probe by background" is the interaction term in the linear model that the authors fit for each drug. The details of the analysis are in the supplemental methods. The model they fit is
Drug_Response ~ Probe + Probe * Background + Background

which translates to "Drug response is modeled by Probe, the interaction of Probe and Background, and Background". The middle term (with the *) is the interaction term. Here is a page that helps to explain how to understand significant interaction terms in linear models.

I didn't understand how it is calculated. I mean probes are the original probes. Background are formed by applying PCA and taking the best 6. I didn't understand how this interaction term is calculated. How do I know which background a probe is in

I didn't understand how it is calculated. I mean probes are the original probes. Background are formed by applying PCA and taking the best 6. I didn't understand how this interaction term is calculated. How do I know which background a probe is in. Also I didn't get why it is called background. I mean they have just applied PCA to capture the decorrelated basis which capture the most variance. Why is it called background?

I am wondering if they  used the ttest values for the interaction term?

I just found out that it is just the product of the probe values and the background values. However, they have mentioned probe-by-background term(paired t-test P-value=7,510^-5, paired Mann-Whitney test P-value=5.210^-5). What is meant by this?


text:
Superposing DNA
I have a series of protein models with DNA docked. I now want to superpose the DNA on a reference DNA molecule and extract the translational distance applied and the rotation angle used.
I can superpose DNA molecules with Chimera, but I can't extract the translational distance and the rotational angle that was applied to superpose.
I have also had a look at MODELLER but it seems MODELLER cannot not superpose DNA.
Does anyone know of software/code by which I can extract the information I want?

Try this out with BioPython:
from Bio.PDB.PDBSuperimposer import PDBSuperimposer as superimposer
from Bio.PDB.PDBParser import PDBParser

parser = PDBParser()
sup = superimposer()
struct_1 = parser.get_structure("XXXX","first_pdb")
struct_2 = parser.get_structure("XXXX","second_pdb")

atoms1 = struct_1.get_atoms()
atoms2 = struct_2.get_atoms()
sup.set_atoms(atoms1,atoms2)

print sup.rotrans #print the rotation translation matrix from the SVD

#then to complete the alignment
sup.apply()

You can look here for further details. SuperPoser


text:
How do amino acids become attached to tRNA?
Is there a protein that catalyzes this or does it happen spontaneously?
In which part of the cell does this happen?

The process to which you refer is called tRNA charging and is catalyzed in the cytosol by a class of enzymes called aminoacyl tRNA synthetases.

...and it happens in the cytosol.

@ohcanada, sorry for blowing off your suggested edit. I should have given the original question and your suggestion more consideration.


text:
Is anaerobic activity during ketosis possible?
When a person's glucose and glycogen stores are depleted, which can occur due to fasting or due to a diet consisting largely of fat (like eskimo diets), the body produces its energy by breaking down triglycerides into fatty acids.  Fatty acids can be then converted to Acetyl-CoA, which can consequently enter the citric acid cycle, generating ATP.*
Now normally when a cell does not receive sufficient oxygen to undergo its natural processes, it usually breaks down glucose anaerobically to generate ATP and lactic acid.  However, in the case where the body is running off fatty acids (e.g. fast, or fat/protein only diet), how does the body respond to such anaerobic situations?
*(Note:  In this situation many fatty acids are first taken up into the liver and converted to ketone bodies, which are subsequently converted to Acetyl-CoA after being taken up in the required tissues, hence causing "ketosis" as in the title)

You are correct in thinking that fatty acids cannot be metabolised anaerobically. However, in the type of metabolic state that you are describing, blood glucose will be maintained by the liver to support tissues or cells which are more or less dependent upon anaerobic metabolism. The classic example of such a cell type is the red blood cell which as no mitochondria and so cannot use the TCA cycle. The brain is also heavily dependent upon glucose.
The liver exports glucose that it has produced via gluconeogenesis from amino acid skeletons, as well as from glycerol produced as a result of fat metabolism.

In reality, a cell will die almost immediately in such anaerobic conditions.  The question itself can be taken another way.  That is, how does the body fuel anaerobic metabolism in the relative absence of glucose.  It is important to understand that stored ATP and CP (creatine phosphate) provide energy anaerobically, but can be refueled by beta oxidation of fatty acids that occurs between bouts where energy needs exceed oxygen supply.  So someone on a high fat diet with virtually zero carbs is going to perform their anaerobic work mostly from ATP-CP without having to turn to gluconeogenesis.  Glucose obligate tissues, primarily the brain, nerves, liver and pancreas will require glucose (or ketones) in the absence of endogenous glucose, and so they will need to receive these via gluconeogenesis of canabalized tissues or consummed protein, however the brain does not last for more than about 30 seconds on fast glycolysis anyway so to say that the body makes glucose from protein to allow anaerobic metabolism to go on is not accurate.  The body turns to gluconeogenesis primarily to provide substrates for glucose dependent tissues to use in oxidative phosphoylation, not in anaerobic pathways.
At any rate, the ANSWER to the question as posed "Is anaerobic activity during ketosis possible," YES because you have stores of CP and ATP that don't require oxygen to access, but gluconeogenesis during ketosis is not activated by a need for anaerobic energy sources (fast glycolysis) but by glucose dependent tissues need for glucose for oxidative phosphorylation.

Two points to you as a new contributor. 1. It's best to provide sources in support of assertions, e.g. "the brain does not last for more than about 30 seconds on fast glycolysis" (what do you mean by fast glycolysis, anyway?). 2. Wbat do you mean by "the oxidative phosphorylation needs of the brain"? Oxidative phosphorylation is a means to an end (production of ATP), not a need in itself.

It may take a few posts on this S.E. to get a feel fort what is considered to be a baseline level of knowledge in biochem.

Will work on an edit. "Oxidative Phosphorylation needs" should be "aerobic energy needs" "Fast Glycolysis" is glycolysis that results immediately in lactate/pyruvate rather than "slow glycolysis" which is going to send substrates directly into the TCA cycle.

http://www.biomechanix.net/a-quick-breakdown-of-fast-and-slow-glycolysis/

Something wrong with your link. It points to a page that gives me a "401 Forbidden".

The link gives me the article with no problem

Just rechecked on my iPhone (previously was from my Mac desktop or laptop) and still get the 401. Not sure why this would be. Seldom get 401s.

Actually it's giving me a 403 (forbidden) on my office Mac using Safari, Chrome or Firefox, and on a Windows machine I had never previously used with IE. Looking up Biomechanix on the web gives me commercial sites in US and Oz concerned  with physical therapy and "professional trainers" (the latter giving me a 403). Having read the Google extract "CSCS professional trainers are the absolute highest level of trainer you can work with and we take pride in the fact that BioMechanix Strength and Conditioning", I wouldn't think anything they say about glycolysis would be of interest here.

It is a textbook cited article on a commercial sports performance website.  To summarize, fast glycolysis is a term that refers to glycolysis that proceeds to lactic acid because the cell has insufficient oxidative capacity to process all of the glucose through the Krebs cycle.  In humans is is primarily present in high work output type IIb msucle cells which are low in mitochondrial density.  It fuels short bursts of work output that exceed the cells ability to produce energy through oxidative glycolysis, or when oxygen can not be brought to the cell fast enough.

Fast glycolysis then is the exercise physiology term used for anaerobic glycolysis, but it generally refers to the pre-Krebs cycle portion of glycolysis even if it ends in Acetyl-CoA entering the mitochondria.  I suppose that in exercise physiology it has garnered the name "fast" glycolysis because it is mostly important in providing short term energy for energy needs that outpace oxidative glycolysis.