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Online Molecular and Cellular Biology Video Lectures?
I am looking for video lectures to go through to guide my reading in intro molecular and cellular biology. I've had intro bio and I study evolutionary theory, but my molecule- and cell-level knowledge is weak.
I'm finding it impossible to know where to look in a big book like Alberts, or to read Lodish without a guide, so I really need lectures to help me out. I've tried the MIT OCW assignments and a few other similar sites, but I can't seem to find a course that includes lectures. Does anyone know of any? Ideally they'd follow Watson et al. for molecular and Lodish for cellular, but I can find other textbooks too.

MIT's OCW is weak when it comes to biology videos.
UC Berkeley has some good video content for molecular and cell biology.

See, for example, this playlist:
http://www.youtube.com/playlist?list=59C08AE05E752758
And explore the main UC Berkeley video lectures website here: http://webcast.berkeley.edu/

UCSD, if I recall correctly, has had some pretty good life science lectures available online to the public, as well.  Possibly also UCLA.
iTunes U is your friend here. Unfortunately, to really take advantage of it, you need to download iTunes -- but it's worth it.  The last time I looked, there was more there than I could possibly watch, and that was 4 years ago.

MIT OpenCourseWare provides very interesting material, and not only on biology.
You may be interested in seeing the video lectures from some of the Introductory biology courses, such as this one, this one or this other one.
There is, however, much more, check out the index of the available material for biology.

These are some of my favorite biology learning resources:
iBioSeminars
Academic Earth - Biology
Others include: Khan Academy - Biology, HHMI BioInteractive video collections, Wellcome Trust education resources.

This one is not precisely molecular and cell biology, but rather systems biology. It might help you as some kind of introduction, though:
Systems biology lecture 1
Also, if you are really really new to the subject, you can probably use "Molecular and Cell Biology for Dummies".

While not exclusively cell and molecular biology, I would also like to add the Journal of Visualized Experiments. It's like Youtube for experiments. :)

The Journal of Visualized Experiments (jove.com) is excellent but based on experimental protocols.
ItunesU also has great resources. Stay away from youtube - a lot of people there don't know what they are talking about.

I recommend two YouTube channels.

Shomu's Biology. Probably the channel with the most extensive coverage of biology, but the guy explaining it has a very thick accent that is sometimes hard to follow.
AK Lectures. Its main focus is on metabolism and physiology. I personally find it easy to understand.


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Defining paper(s) in epigenetics
For someone who is interested in learning about the discovery of epigenetics, which are the foundational defining papers in the area?

For epigenetics in humans, for me it's the Överkalix study on descendants of people who lived through the Dutch famine of the 1940s.

Disappointingly, the papers so far all highlight the heritability of epigenetics whose usefulness is rather limited, rather than epigenetics itself.

I understand that Robin Holliday was the first to discuss the possible role of DNA methylation
in the control of Gene expression. In his paper "The inheritance of epigenetic defects"
he presents what is one of the first modern formulations of what we now regard as epigenetics. The term "epigenetics" itself was coined by Conrad Waddington although this predated our modern understanding of heredity.
Holliday, R., The inheritance of epigenetic defects, 1987, Science, 238, 4824

I found two nice review papers focused of epigenetics and human disease, one from 2004, and one from 2006. But perhaps you are looking more for something like this?
I also found this article in the BBC news: The Ghost in Your Genes

They have shown that a famine at critical times in the lives of the grandparents can affect the life expectancy of the grandchildren. This is the first evidence that an environmental effect can be inherited in humans.

References:

 Jiang Y-H, Bressler J, Beaudet AL. 2004. Epigenetics and human disease. Annual review of genomics and human genetics 5: 479–510.
 Rodenhiser D, Mann M. 2006. Epigenetics and human disease: translating basic biology into clinical applications. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne 174: 341–8.
 Haig D. 2004. The (dual) origin of epigenetics. Cold Spring Harbor symposia on quantitative biology 69: 67–70. [pdf]

@Lisa: In the BBC article they discuss the Överkalix study.

There are few single papers that really drive the field by themselves, epigenetics has been a long slow progression (although more recently the definition has been muddied and started to include non-epigenetic modes of gene regulation).  A pretty good review of a lot of research, including a more circumspect discussion about what epigenetics is can be found in Youngson and Whitelaw's Annual Review (http://www.ncbi.nlm.nih.gov/pubmed/18767965).

source: Stack Exchange

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

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Is a raised baseline between T and QRS normal in any ECG lead?
Here are excerpts from an unknown ECG lead. I find it weird that the "baseline" changes after the T wave and doesn't return until after the following QRS complex. Is that normal/expected for any lead?

Click for better resolution. I've got another 10 minutes of the ECG, if that would be helpful.

Also, I should note that I'm quite inexperienced when it comes to cardiology, so this is probably a basic question -- so don't upvote me too much :)

What frequencies are the high pass and low pass filters set at?

@jonsca: I've applied a 5-point moving average. As there was no baseline drift I don't think I had applied any other filters, so that would be from the data acquisition tool. It was sampled at 360 Hz. Here are the non-averaged graphs for these intervals: 80-92 sec, 88-90 sec

@jonsca: Ok, looks like I had highpassed it at 0.5 Hz.

It looks like some kind of line noise or artifact on the unfiltered plot.  See if your software has a notch filter for 50/60Hz (depending on Europe or the States).  Put that on, then try your moving average, but remember a "boxcar" filter is always going to distort your plot a bit.  I'm not an expert on ECG, but I would hedge my bets on this being non-physiological.

@jonsca: Thanks a lot, I missed that! It didn't change the signal very much, but there was a clear spike at 60 Hz there before. Smoothed notched 1 and 2

I am not sure if I understand your question correct. What I can see here is a clear ST depression, that might be indicative of myocardial ischemia/infarction. The underlying mechanism is the shortage of oxygen in myocytes leading to elevation of resting potential and slowing of the depolarization -- this accounts for the elevated baseline after T.
I am not at all an ECG expert, but I have seen the misplaces T-P segment many times while at medical school. It wasn't indicative for diagnosis, whereas all other segments were.
So, why are you worrying about this segment?

Thanks! Then I know that the TP elevation is fine. About the ST depression, is it clear because there's a large vertical distance between the isoelectrical line (measured at P onset) and right after S, or also because of the horizontal ST segment?

Actually an MI often has ST elevation and strong negative QRS complexes

This is inexact. Both ST elevation or depression can happen. Please be careful when commenting/answering on subjects pertaining to acute health problems. @Andrey ST segment depression in humans is defined by a 1mm (0.1 mV) depression from the isoelectric line.

@Raoul The answer is in no way medical consultation, especially for an acute medical problem, as stated in the site rules. The question asked is different from your answer.

@Alexander I did not mean to be rude. Yes,this answer is not about a medical problem. What I meant is that we should be careful with sensitive topics on the website. Bad things sometimes happen to people reading about health on the net, and we should strive to be as exact as we can.I also make mistakes.

@Raoul I fully agree with you (and don't think your previous comment was rude in any way). At the time of this question we already had a clear site guideline stating that no medical advice can be given or sought here.I understood the question so, that it is asked about usual finding on ECG, rather than "normal" in the meaning of "healthy". Hence is my answer.

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


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How do you break up cell clumps when passaging?
I am working with HepG2 cells, and they really like to form clumps.  Pipetting up and down in TrypLE does not seem to be very effective in breaking them up.

Rob: can this question be answered by Google?  If it can, please come back and post an answer to your question.
Here's a hint: http://hepg2.com/index.html

I find that I only get clumps (with HeLa and similar cell types) if I leave them in Tryple too long. Generally I leave them in room-temp (not hot) Tryple for ~8 minutes, then I angle the dish, lid off, so that I can see the "sheen" of cells on the dish (this happens in the hood, of course). Then I blast the sheen with Tryple using a 1000ul pipetter, which de-adheres the cells. These are generally much less clumped than if I let the Tryple de-adhere the cells.

In some protocols for setting up primary cultures (for example from mouse bone marrow or rat endometrium), there is a step that requires pushing cell suspension through a large needle to get rid of clumps. Of course, this carries a high risk of damaging the cells, so sometimes collagenase is used instead.
It might also be helpful to wash your cells with PBS without ions before passaging and use tripsin with EDTA. That should get rid of at least some calcium from the plate, so that action of adhesion proteins would be inhibited.

Cell clumps that not dissociate with rigorous pipetting might very well be caused from free DNA in your cell suspension (i.e. if you trypsinized for too long). Free DNA attracts cells which bind altogether forming clumps.
Two possible ways to get rid of these clumps:

Centrifuge your cell suspension at 5000 rpm for 2 minutes with acceleration on (at 4) and brake (at 3) allowing the way heavier molecules to precipitate. Then aspirate ~0.5ml from the top of the suspension and transfer to a new flask. Repeat if needed.
Use DNAse at concentrations from 20-100µg/ml (concentration resulted from personal use) as long as you will not intend to carry out DNA related experiments.

You can always go back and buy a fresh ampule of the cell line you want clumps free :)


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Alternate genetic codes in newly sequenced organisms
Variations of the standard genetic code are pretty rare, but as the cost of high-throughput genome sequencing continues to drop, there is a greater possibility of discovering additional exceptions. That being said, there is a clear emphasis in genome projects on nucleotide (genome and transcriptome) sequencing, with much less (if any) effort put into proteomics work (correct me if I'm wrong there).
Let's assume we're sequencing the genome of a new organism and we're focusing completely on genome and transcriptome sequencing--no proteomics. Let's also assume this organism has slight variations to the standard genetic code. Would it be possible to annotate this genome (for protein-coding genes) completely incorrectly since the gene prediction software does not take into account these variations, or would it be pretty obvious? What would you expect to see in this case?

Your question is very vague.  Can you be more specific and/or more concrete?  There are a dozen sequencing technologies and even more variations to the genetic code.

Perhaps the vagueness comes from the fact that I don't know what to expect if I was trying to annotate the genome of an organism that uses an alternate genetic code. My basic question is: would I even be able to tell? Is that not clear from the original question?

I think that's a clear question.

If the organism uses an alternative code, the predicted protein sequences would always include the same type of amino acid substitution errors. This pattern should become apparent when you compare the proteins to other organisms.
In reality, the most common alternative code uses UGA for tryptophan instead of the usual stop. If you make the mistake of using the standard code for these genomes, the predicted genes would become highly fragmented so it is almost impossible not to notice.

You are correct to be a little concerned, especially with mitochondrial genomes (where non-standard genetic codes are more prevalent).  In addition to the use of non-standard codes you should also consider RNA editing (changed codons or deleted/inserted nucleotides to shift reading frames) and special amino acids (e.g., selenocysteine).  All together, the emphasis on DNA sequence to infer protein structure is safe in the bulk of cases, but don't be surprised by differences (for particular genes or for whole organisms).

The short answer is yes, you could end up with many errors.  See here for more detail:
NCBI: "The Genetic Codes"


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Are ectopic beats considered sinus rhythm for pNN50 purposes?
One quantification of the heart rate variability of an ECG is pNNx, i.e. the proportion of consecutive NN distances that differ by at least 50 ms. When a premature beat occurs, the preceding and following RR intervals are much shorter and longer than the mean. Are these intervals considered NN for the purpose of calculating the pNN50?

No, the beats originating outside of the sinoatrial node are not considered for pNN50. Moreover, this metric cannot be applied to the rhythm featuring any type of ectopic or non-sinoatrial activity.
NN50 has its name from an acronym "normal-to-normal", this acronym is used instead of RR ("from R to R") to emphasize that only the normal, e.g. sinoatrial beats are considered for evaluation.


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How can I measure bacterial alkaline phosphatase activity?
I want to measure alkaline phosphatase activity using PNPP in my mutant bacteria strains, but all the protocols I found involve purification of the phosphatase (which I have no need of).
Does anyone know a good protocol which involves using only the supernatant, without purification of the enzyme? What is the preferred buffer for the reaction?

I found this kit that appears to be compatible with biological samples.  Rather than buying the kit you may also be able to imitate / modify their protocol to do the assay with your super natant.

Thank you, but I don't think I can imitate the kit - they don't share the components of the buffers. It did give me some idea of how the protocol is done, so thank you.

There's a paper from 1973 describing a very simple protocol:
 Wolf PL, Von der Muehll E, Praisler K. 1973. A test for bacterial alkaline phosphatase: use in rapid identification of Serratia organisms. Clinical chemistry 19: 1248–9.


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What implications has the missing 2'-OH on the capability of DNA to form 3D structures?
The chemical difference between RNA and DNA is the missing 2'-hydroxyl group in the nucleotides that build DNA. The major effect of that change that I know of is the higher stability of DNA compared to RNA. But I'm wondering whether this difference has significant implications for the ability of DNA to form compex, three-dimensional structures.
RNA is known to be able to from complex tertiary structures and function as ribozymes. It clearly has the ability to form a wide range of structures and can catalyze a variety of chemical reactions.
As far as I know, there are no naturally occuring catalytic DNAs known. But a number of synthetic DNA enzymes have been created in the lab, so it is generally possible for DNA to form catalytic structures (see Breaker and Joyce 1994 for the first created DNA enzyme).
I'm wondering whether the missing 2'-OH means that DNA has less potential to form complex structures compared to RNA? I imagine it changes the ability to create hydrogen bonds, but I don't know if it would significantly decrease the potential structures that DNA could adopt.

Breaker RR, Joyce GF; (December 1994). "A DNA enzyme that cleaves RNA". Chem Biol. 1 (4): 223–9

To make sure I'm not comparing apples and pears, my (attempt to) answer the question will be broken into two parts: comparison of single-stranded nucleic acids and double stranded ones.
Single stranded DNA and RNA
Both DNA and RNA can form single-stranded complex tertiary structures in which the secondary structure elements are associated through van der Waals contacts and hydrogen bonds. The presence of a 2'-hydroxyl group makes ribose ring prefer different conformations than deoxyribose in DNA. Also, since 2′-OH moiety is both a hydrogen donor and acceptor, it provides RNA with greater flexibility to form 3D complex structures and stability to remain in one of these conformations. As Aleadam notices, this paper shows that tRNA and its DNA analog form similar tertiary structures though tDNA is not as stable as tRNA:

Therefore, we submit that the global conformation of nucleic acids is primarily dictated by the interaction of purine and pyrimidine bases with atoms and functional groups common to both RNA and DNA. In this view the 2-hydroxyl group, in tRNA at least, is an auxiliary structural feature whose role is limited to fostering local interactions, which increase the stability of a given conformation.

These authors also show that at least one loop in the tDNA analog is more susceptible to cleavage by a restriction endonuclease. In this region the tRNA has a water molecule hydrogen bonded to 2'hydroxyl group.
I was not able to find more of such interesting comparisons in the literature.
Double stranded DNA and RNA
Both DNA and RNA can form double-stranded structures. Again, sugar conformation determines the shape of the helix: for DNA helix it's usually B-form, whereas helical RNA forms A-geometry under nearly all conditions. In RNA helix we find the ribose predominantly in the C3’- endo conformation, as 2'-OH stericly disfavors the C2'-endo conformaion, necessary for B-form geometry.
Physiological significance
dsRNA and ssDNA often provide a signal to the cell that something is wrong. dsRNA is of course seen in normal processes like RNA interference but it can also stop protein synthesis and signal viral infections (cf. double stranded RNA viruses). Similarly, ssDNA is much more prone to degradation than dsDNA, it often signals damage of DNA, or infections from single stranded DNA viruses and induces cell death. Therefore, due to their functions, under normal conditions DNA 3D structure is mostly a double-stranded helix, whereas RNA has a single stranded, "protein-like", complex 3D structure.

This answer is incorrect for a variety of reasons. For one, it makes the assessment that RNA is more flexible. It isn't; DNA is. The role described in the Aleadam paper thus is minimal.
The comments about degradation has little to do with the ability to adopt 3D structures. It is more of a reflection of the presence of specific defensive mechanisms via DNases and RNases.

This is not my field so I'm risking a wrong/incomplete answer here, but I'd say that the critical difference is the almost complete occurrence of double-stranded DNA that precludes the formation of the tertiary structures in single-stranded RNA, rather than the 2'OH difference. In fact, and following the link you posted, the authors even comment in the introduction that:

"It is well known that single-stranded DNA can assume interesting tertiary structures. A tRNA and its DNA analog form very similar structures [9]".

I did not follow the citation 9 [Paquette et al (1990), Eur. J. Biochem. 189,259-265], but they seem to answer your question with that phrase. In essence, it probably does not have a major implication.

The answer lies entirely in the thermodynamic stability that is provided with having a 2'-OH. As mentioned by Aleksandra, RNA will adopt only the C3'-endo conformation whereas DNA adopts both the C2'-endo and C3'-endo. Effectively, this makes the DNA strand more flexible not RNA. In doing so, a single stranded DNA oligomer will be able to adopt more states.
DNA/RNA helix formation is dominantly enthalpically driven. When a helix forms, RNA will only adopt an A-form Helix where as DNA will adopt both a A-form and B-form. While there are more possible conformations for DNA, the reduction in the entropic contributions make it significantly more unfavorable. Interestingly, this is why RNA analogs like PNA and morpholinos have good binding properties as they will form more entropically stable base-pairing with their target sequence.
For these reasons, it is much more common so see structured Ribozymes and non-coding RNAs in nature even though it is physically possible to produce DNAzymes. Again, one of the many reasons why the RNA world hypothesis makes sense.

the OH group in the two position acts a as a nucleophilic catalyst for the cleavage of RNA or of DNA if it had such a group. Since DNA needs to stay intact throughout the life of a cell it would be disastrous if it were cleaved because of the 2'OH group. RNA on the other hand is rapidly cleaved as needed by the cell without detrimental consequences to the cells genetic code so it can have an OH group.-chem major

Welcome to BiologySE... we always appreciate some references (even if just some other websites) to back up the answer, and for other places individuals can go for further reading.


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Time from stimulus to gene expression
My understanding is that gene expression, in response to some stimulus, generally occurs on the order of minutes. I'm curious about the extremes...the quickest and the slowest cases.
What is(are) the fastest time(s) recorded for genes being expressed in response to a stimulus? What are the slowest times?

The fastest I know of is the heat shock locus in Drosophila.  The transcription factor (HSF) accumulates within about 30 seconds, and RNA Polymerase can be seen to start accumulating within 3 minutes.
Katie L. Zobeck, Martin S. Buckley, Warren R. Zipfel, John T. Lis.  2010. Recruitment Timing and Dynamics of Transcription Factors at the Hsp70 Loci in Living Cells.  Molecular Cell 40(6): 965-975


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What is the Giemsa staining of chromosomes?
I got the question in my exam and wrote the following and I do not understand what is wrong in it:

Giemsa staining is a staining method to stain particularly malaria and other parasital diseases. G-bands occur because Giemsa stain
  consists of A,T rich material i.e. poor gene such that dark and white
  bands occur. Each chromosome has an unique reaction to Giemsa staining
  so G-bands occur.

0 points. I do not understand what's wrong with it, since in their comments about the same question in my first exam they wrote also the extra questions: What are G-bands? How are they formed and why? This time I answered the given things and got zero mark.
Probably, the mistake was that I did not answer to the question in the scope of medical Biology in some way. However, I am not exactly sure what it is exactly.
How would you answer to the question when you know that the course was about medical biology?
Please, add the tag Giemsa.

Giemsa is too specific for its use as a tag. Staining and Histology are enough. Maybe Karyotype?

I suggest you explain downvote.

Giemsa is not a particular methid to stain malaria or any other parasite. It stains DNA. As such, it can be used to stain any DNA-containing organism, or, in other words, any known cell.
Regarding its particular use in chromosomal banding, you can refer to many online resources, such as this one of the University of Washington:

Chromosomes in metaphase can be identified using certain staining techniques, so called banding
(...)
G-bands are most commonly used. They take their name from the Giemsa dye, but can be produced with other dyes. In G-bands, the dark regions tend to be heterochromatic, late-replicating and AT rich. The bright regions tend to be euchromatic, early-replicating and GC rich.

Very well written. - - My attempt of a summary: Staining reveals structural features of the chromosomes in metaphase by banding. Giemsa staining offers better resolution of individual bands of chromosomes along the length of the whole chromosome. It stains DNA to heterochromatic (dark) and euchromatic (white) regions resulting into G-bands, called so because of the dye Giemsa, used in staining historically first, but can be stained also with other dyes. It stains any DNA-containing organism, or, in other words, any known cell. Analysis involves the karyotyping of banded metaphase chromosomes.

Is there any other staining methods for other phases than metaphase of chromosomes? - Is it useful to stain unreplicated daughter chromosomes after metaphase? It is probably harder to do it, since the daughter chromosomes are not in a line, than in staining during metaphase.

@Masi in any other phase of the cell cycle, the DNA is much less condensed (called chromatin) and basically all DNA is intermingled, rendering a much more homogeneous staining. You still see regions of condensed chromatin, but it's impossible to identify individual chromosomes. You may do some (very limited) in situ hibridization, but again it's much more informative when cells are in metaphase.

I need one clarification. Does Giemsa staining of chromosomes stain the DNA and proteins i.e. whole chromosomes? Or does it stain only DNA, not proteins?

It seems that Giemsa staining specifically stains DNA. Sometimes it seems that some proteins are staining but the purpose is not to stain them.

Probably they want something like from here:

For differentiate nuclear and/or cytoplasmic morphology of platelets,
  RBCs, WBCs and parasites. In wright- and Giemsa-stain: the cytoplasm
  appears blue and the nucleus is relatively large, eccentrically
  located and red. The distinct, rod-shaped, red-staining kinetoplast (a
  specialized mitochondrial structure) contains extranuclear DNA
  arranged as catenated minicircles and maxicircles.

In my opinion, the question is not exact if they want the above thing. It should have been: What is the Giemsa staining of chromosomes morphologically? if the above thing correct.
It was the first medical biology course so answer should be from it.


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What do the variants on the PolyT sequence mean?
My son has been diagnosed with Cystic Fibrosis.  I am not looking for medical advice regarding his condition, but I am very interested in understanding the genetic causes of his condition.
In addition to the common CF mutation Delta F508, my son's genetic testing revealed both 6T and 9T variants of the PolyT sequence.
If I understand it correctly, it seems that the variants (I have found repeated reference to 5T, 7T, and 9T variants, but almost nothing on 6T) are tied to errors in the RNA transcription of the CFTR protein, but I don't understand how, or what the difference between these variants are.
What does "variant of the PolyT sequence" mean in this context, what are the difference between 5T, 6T, 7T, and 9T, and how do they impact the production of the CFTR protein?

A search in both PubMed and OMIM databases did not yield any result for the 6T polymorphism. It might be not yet described. If you are really interested in the molecular details, you'll have a compendium of mostly all what is known here: http://omim.org/entry/602421

I haven't read too far into this, but from what I understand the variant PolyT sequence is the number of thymine bases in a short sequence within one of the introns of the CFTR gene. Introns and exons are both parts of a gene structure, but introns are spliced out of the final transcript before its converted to protein (for more information see this article on RNA splicing).   Studies have shown that the presence of a 5T sequence in this region may increasethe skipping of exon 9 in the CFTR gene (there is a nice picture showing what I mean here).  This exon skipping will alter the final protein product translated from the spliced RNA species.
I could not find a lot of information about the 6T allele that your son has, however, I found one short article about a patient with 6T and F508 in the European Journal of Genetics. It references another paper that talks about the length of an additional repeat sequence of GT bases and its affect on individuals the the 5T variant.

I can't begin to tell you how helpful this has been to me, both in understanding what the genetic diagnosis means, and what the likely impact for my son will be.  I also found this paper with help from search terms I picked up from the paper you linked. While I'm not taking this as actual medical advice, it does seem like our son is more likely to suffer from CBAVD than symptomatic CF, which is supported by his complete lack of symptoms so far. I can't express how this will help in terms of hope and optimism.  Thank you!


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To understand why satellite cells are genetically inactive in Barr body
DAPI is used as a stain for DNA heterochromatic and euchromatic regions. The Barr body is heterochromatic.
In the slide of a normal human female cheek's somatic cells, there is apparently no other clear dark spot inside the nucleus than the Barr body against the nuclear inner membrane. - - I used an old microscope so my observation may be wrong as pointed in the comment.

How can you deduce from the given slide that the spot really contains inactive satellite cells that are not used genetically?
Why is the active X chromosome not visible by the same staining method? (It probably can be made visible by some other staining method.)

Just to clarify, do you mean "there is no other dark spot inside the nucleus?"  The Barr Body is not inside the nucleolus, and the nucleolus appears as a DAPI-dim (unstained) spot in interphase nuclei.

@KAM Yes, I mean that I did not see any other clear dark spot inside the nucleus than the Barr body. Other thing was blurr and not that clear. Thank you for pointing out the mistake: the Barr body is inside the nucleus next to nucleolus or more exactly against the nuclear inner membrane in interphase nucleus.

DAPI (4',6-diamidino-2-phenylindole) preferentially binds AT-rich DNA (although it binds CG-rich DNA, too), which can give chromosomes distinctive banding patterns if they are polytene or in metaphase.  In interphase condensed chromosomes, such as the inactive X chromosomes of female mammals (Barr Body), the relatively high concentration of tightly-packed DNA makes the chromosome appear as a brighter spot in the nucleus.  When the DNA of a chromosome is decondensed (such as the rest of the chromosomes in interphase), it appears as more-or-less homogeneously stained DNA in the nucleus.
A great picture is here (see below), A is the DAPI staining, B is a protein localized to the Barr Body, C is the RNA (Xist) which binds the Barr Body.

Since the active X is not condensed, it appears as do the rest of the chromosomes, so cannot be identified among the mixture of autosomes.  The difference in DAPI appearance has nothing to do with activity per se, but rather differences in how tightly packaged the chromosomes are.
I do not understand the first part of your question, though.  You cannot tell from a still image that the Barr Body is relatively inactive.  If your were doing experiments on live cells, you could measure RNA production (using a labeled nucleotide), immunofluorescence to show localization of e.g. RNA Polymerase, or reporter genes located on the inactive versus active X chromosomes.  If you clarify your question, I can answer better.

Do you mean that you can see Barr body and the active X chromosome as dark spots to the eye in the given slide? - Assume yes. Then my classmate was wrong in claiming that she can differentiate between the two X-chromosomes from the slide. Like you said you need to measure RNA production to verify the thing.


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What is the most difficult feature to explain evolutionarily?
I wonder what are examples of organs/structures/behaviours/cooperation that evolutionary biologists themselves find most difficult to explain -- to explain how they could appear evolutionarily -- within known mutation rates, generation frequency, and known time frames.
Excluding issue of appearance of life itself.
Knowing rates of mutation and generation cycle (and population size), it would be possible to estimate time needed for appearance of new feature.
Thus it would be possible to spot counter-examples, such examples that are probabilistically beyond possibility to appear in given evolutionary time. Are such examples known ?
I might be naive, but I think some rare behavioral trait can be a candidate, behavior that does not trigger even once in a lifetime of organism, on average, that triggers really rarely.

Some people keep presenting the bombardier beetle...

@J.M.: sure, but their point is absolutely unexistent...

That's why I left it as a comment, @nico; I'm staving off answers that might bring it up.

This is a classic survey question that begs for arguments not based in fact, but on a gut "feeling" about the likelihood of the evolution of characteristics

@Tyler try suggesting a way to improve this question. It is always valid to question even if it is the paradigm.

@Tyler: According to Dawkins, speed of evolution of not gut feeling but is subject to numeric estimates and computer simulation. Rates of gene mutations are known, cycle of reproduction can be estimated, sizes of population can be estimated, hence pace of evolution can be estimated, even if with large estimation error, but still, simulated.

@Andrei: this question assumes the existence of a metric by which we can 1) quantify rate of evolution, and 2) find anomalous development under that metric. Maybe it's better to ask questions about this metric before speculating that it has been used and then asking for the ranking.

@Andrei, would it be possible to clarify your last paragraph? I can't make any sense of it.

I won't claim that these are the most difficult things to explain evolutionarily, but these two are hard:

Host-Pathogen dynamics. They start out easy enough, but the interaction between a pathogen and its host is intensely complex. You have the immune system, pathogen-pathogen interaction, the balance between weakening a host and killing a host, dozens of different transmission mechanisms, at least two levels of evolutionary pressure (inter-host and population), etc.
Social/Societal level traits. Evolutionary psychology has, for example, been criticized for not being able to get much past the level of "Just So Stories" in terms of its ability to explain human societal traits using evolutionary theory.

I agree with (2) simply because it’s very hard to find good evidence (as you mentioned with the “just so” stories). I disagree with (1) since this can be explained by quite easy models and is a classical example of evolutionary arms race.

@KonradRudolph I work on some of those models, and they're less than "quite easy", especially when multiple pathogens are pulled into the equation, or you start working on multiple scales.

Fair enough, point taken.

To answer your question directly, there are a number of examples which creationists like to bring up, such as woodpecker's tongue which is wrapped around its brain or the archer fish which shoots down insects with water and has to adjust it's aim for refractive difference between water and air. These features supposedly 'couldn't have evolved' but of course one's disbelief doesn't make anything true or untrue. This is what Dawkins calls 'argument from personal incredulity'.
Let me also point out a few evolutionary counter arguments to such reasoning.
The presence of selection radically changes what is 'likely' or 'possible' to happen. For example, you wouldn't argue that it's highly improbable that the stones on the beach are ordered by size, if you know that the action of waves orders them in a certain way. Dawkins' weasel (http://en.wikipedia.org/wiki/Weasel_program) also demonstrates this principle.
Another Dawkins' argument is that, contrary to what creationists claim, complex features such as eye don't have to be completely functional to be useful. In the early history of life, when no organism had eyes, any simple system which could distinguish light from darkness could provide a huge advantage to its owner. The simple system can then evolve to a more complex one to provide a competitive edge etc.
Finally, evolution happens over time scales we cannot grasp. We don't have a good feeling of what billions of years of small changes which are selected for can add up to.

I am avolutionist myself and I have read Dawking. You misunderstood my question. I did not ask what looks unbeleivable in eyes of creationists. That would be easy question.I am asking which examples looks difficult to evoluion biologists themselves. Dawkins gives impressive explanations about evolution of the eye etc. Again, are all feature that easy to explain to evolutioninsts ? Evolutionists not only beleive in evolution. They seek specific explanations. Are not sometimes explanations difficult to find ? What are examples ?

@andrei what role does belief play in science?

The Nautilus eye used to be (still is?)  a "problem" and became a poster boy for creationist arguments. It has a pin-hole camera eye, which is the highest resolution non-lens eye. However, I understand that several genera arose during the Cambrian and the existing species haven't changed much since. So, the Nautilus saw fit to develop a sophisticated but non-optimal eye several hundred million years ago (other cephalopods have much better vision), but not develop it further.
This may hard to explain in evolutionary terms, although I note that they probably hunt via olfaction not vision.

At which depth they live. Is there light at this depth at all.

I found myself skipping the Grasso "olfaction not vision" paper when seeing "marine vertebrates at every scale from small crustaceans to sperm whales" in the abstract.

@mgkrebbs Yes, I admit not the best start to a paper.

saw fit to develop? Please explain this in an evolutionary framework


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Smallest viable reproducing population
What is the smallest viable reproducing population, such as in a human population. By viable I mean a population which keeps genetic defects low (enough).
A very strongly related question: what is the expected number of generations a given population can survive?

http://en.wikipedia.org/wiki/Minimum_viable_population ?

The conservation biology literature has a great deal of information, particularly with reference to developing species survival plans (e.g., Traill et al. [2007] report a minimum effective population size of ~4,000 will give a 99% persistence probability of 40 generations).
Because the question specifically mentions human populations, I'll focus my answer on the genetics of small human populations, though considerably less information is available.
Hamerton et al. (1965; Nature 206:1232-1234) studied chromosome abnormalities in 201 individuals from a total population size of 268 from the small island of Tristan da Cunha. These authors report increasing chromosome abnormalities (aneuploidy; hypo- or hyperdiploidy) with age and suggest that it may result in decreased mitotic efficiency. This population is thought to have developed from a founder population of only 15. According to Mantle and Pepys (2006; Clin Exp Allergy 4:161-170) approximately two or three of the original settlers were asthmatic, which has led to a very high prevalence (32%) in the current population.
Kaessmann et al. (2002; Am J Hum Genet 70:673-685) present a more modern study of linkage disequilibrium in two small human populations (Evenki and Saami; ~58,000 and ~60,000 population sizes, respectively) compared to two large populations (Finns and Swedes; ~5 and ~9 million). The authors find significant LD in 60% of the Evenki population and 48% of Saami, but only 29% in Finns and Swedes.
Lieberman et al. (2007; Nature 445:727-731) discuss the potential for human kin detection to avoid inbreeding. Such mechanisms have been found in other species, "from social amoebas, social insects and shrimp, to birds, aphids, plants, rodents and primates." Lieberman et al. propose mechanisms contributing to sibling detection in humans, including "maternal perinatal association" and "coresidence duration." Beyond these behavioral cues, the authors also suggest physiological cues such as major histocompatability complex as playing a role.

I suspect the answer would definitely include a parameter that would state how 'diverse' the reproducing population is to begin with - including how heterozygous each individual is (versus inbred);  as well as across individuals -  i.e. how different these individuals are from one another.


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How many human proteins have a solved 3D structure?
I was wondering how many human proteins have a solved 3D structure. Is there a database with only human proteins? I looked at pdb but couldn't find a filter.

I think you are going to have a lot of issues with redundancy, especially if you want to know the number of unique proteins.

@GWW I guess that writing a small script can get rid of the redundancy.

You may have better luck asking this question on biostar.

Notice that “solved” is very subjective. Not all of the structures are of high quality, and some of them are just plain incorrect due to experimental errors.

This is a very subject question for two reasons: The Protein Databank accepts NMR and crystal structures of proteins which offer different degrees of resolution and accuracy. These structures are also somewhat subjective because the protein may adopt different conformations depending its relevant biological context. Thirdly, the solvent extractions may impose erroneous structure.

many of these proteins only have a domain or two solved as structures. animal proteins are hard that way.  that's where this question becomes a little difficult imho.

6405 proteins mapping to 5220 genes, according to Ensembl.
In Ensembl's BioMart, you can select the PDB ID as external reference. Export the results and count the unique proteins/genes that have a PDB ID.

PDB is a good resource for answering such questions, since it will let you filter results by many additional parameters. To count and extract 3D structures of human proteins:

Open Advanced search tab of the PDB website.
Select Biology -> Source organism from the menu.
Type Homo sapiens (human).
You can reduce redundancy by checking Remove Similar Sequences at n% identity below.
Submit query.

To add further filters, click Refine Query with Advanced Search. There you can extract structures by deposition date, quality (eg. resolution or R-factors for structures solved by X-ray diffraction), ligands, enzyme classification, etc. (by checking Add Search Criteria)
Search for human proteins with removal of homologues with 90% identity cutoff fetches 7117 structures. The number of good quality X-ray protein structures (resolution < 2.5A) is currently 3964  (with the same identity cutoff).
You can then download the fetched list or create custom reports (menus below).
A good tool (also used by PDB) for generating non-redundant protein datasets is cd-hit.

From your comments it doesn't seem like you are adverse to writing some custom scripts so one option would be to take advantage of the NCBI Structure database.  You can filter it by organism and then download the results as a text file / XML.  If you need access to the raw PDB data you could then download the PDB archive and examine the ones in your filtered list.

PDBe's new search system is designed to answer just such questions
http://www.ebi.ac.uk/pdbe/entry/search/index?organism_synonyms:HUMAN&view=macromolecules
shows there are 6964 unique human macromolecules with structure data in the PDB.
Of course, many will be fragments of proteins rather than the whole molecule.


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Why are restriction enzymes not frozen?
We all know restriction enzymes are proteins, but we never freeze them. They are instead provided in high glycerol containing solutions by companies and stored at -20C. Is there a reason why this is so?

It's just so much more convenient to have the enzymes ready without having to thaw them. The main reason you freeze enzymes is to keep them active, if you figure out a buffer that keeps them unfrozen without compromising activity, that is a huge increase in convenience.
Not having to thaw the enzymes before use saves a lot of time, if you can manage to keep the enzymes active in those non-freezing conditions that is a clear advantage.
Glycerol also stabilizes proteins in solution, and multiple freeze and thaw cycles can negatively affect enzyme activity for some enzymes.

Just as an addition: you can do the same with antibodies. On reception, dilute them 1:2 in glycerol and you can avoid aliquoting them and don't have to worry about freezing cycles (remember to double the amount when you use them, though)!

Glycerol is added as an anti-freeze agent as well, so that the enzyme can be kept at low temperature (low kinetic energy) and therefore stay stable for longer periods of time.

Freeze-thaw cycles denature proteins through local pH change effects

A little brief? :)

It does get the point across.


text:
Effects of Polyphasic vs Monophasic sleep in humans
Why do humans practice monophasic sleep cycles?
When altering one's circadian rhythm to a Polyphasic sleep schedule, how much would that affect development?
Is Monophasic sleep (once per day) chosen because of biological evolution or is it due to cultural influence?

The second question is quite different from the other two, and should probably be asked as a separate question. If it should be asked at all -- from the FAQ: "If you can imagine an entire book that answers your question, you’re asking too much."

You may be interested in this question over at Skeptics:  http://skeptics.stackexchange.com/questions/999/does-polyphasic-sleep-work-does-it-have-long-term-or-short-term-side-effects

Reading "Polyphasic Sleep: Facts and Myths (Dr Piotr Wozniak)", it is pointed out that infant humans do undergo polyphasic sleep. As this is where most of our development is obviously done, I do not know where I can further proceed with the question about how it would affect development?  Perhaps the issue is more how it would effect the day to day performance of a developed individual?  If this is the case then it is suggested by Dr Wozniak that this is likely to be highly disruptive to the individual

Those well-defined effects of natural sleep affecting stimuli on sleep patterns lead to an instant conclusion: the claim that humans can adapt to any sleeping pattern is false. A sudden shift in the schedule, as in shift work, may lead to a catastrophic disruption of sleep control mechanisms. 25% of North American population may work in variants of shift schedule. Many shift workers never adapt to shifts in sleep patterns. At times, they work partly in conditions of harmful disconnect from their body clock, and return to restful sleep once their shift returns to their preferred timing. At worst, the constant shift of the working hours results in a loss of synchrony between various physiological variables and the worker never gets any quality sleep. This propels an individual on a straight path to a volley of health problems...
It appears that polyphasic sleep encounters the precisely same problems as seen in jet lag or shift-work. Human body clock is not adapted to sleeping in patterns other than monophasic or biphasic sleep.

It would therefore seem that polyphasic sleep is certainly detrimental to health, if not development.
However studies into cognitive performance resulting from differing sleep patterns run by Dr Claudio Stampi (Published ISBN 0-8176-3462-2), he concluded that polyphasic sleep was more efficient than monophasic sleep.  Therefore it may be possible that polyphasic sleep patterns have no detrimental effect on development.

Individuals sleeping for 30 minutes every four hours, for a daily total of only 3 hours of sleep, performed better and were more alert, compared to when they had 3 hours of uninterrupted sleep

There are a couple of theories mentioned in the above book (beginning pg 5) which support the development of monophasic sleep as evolution rather than a social convention:

Polyphasic sleep is regularly seen in smaller mammals that have very high metabolic rates, requiring them to spend most of their time foraging or hunting.  Therefore a long sleep would be highly impractical for them as they would wake without the energy required to hunt their next meal. Humans do not have this need as they are larger and do not require such regular meals.
Monophasic sleep would be beneficial for the early human hunter gatherer as our eyes are not well adapted to see at night.  Therefore any time spent not using the daylight is wasted and any time without the light is not nearly as useful.  This makes it more beneficial to sleep for an extended period when the sun is down.

I am sure that social factors would have an effect, however I would imagine the evolutionary pressures to be more significant.
I really would recommend the book (http://sleepwarrior.com/Claudio_Stampi_-_Why_We_Nap.pdf) if you have not yet encountered it as I found it very informative and packed with references to studies that you may find helpful.


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Why was it so hard to decode the corn genome?
My teachers growing up told me it was impossible to decode the maize genome. But yet its been done.
Why was decoding the genome so significant, and what made it so difficult?

If I remember correctly : it's huge and has lots of repetitive regions.   It's very hard to accurately sequence repeats de novo with high fidelity.

The short answer is that corn genome is large and has a huge amount of duplication events. Around 80% of the genome are repeated. It's hard to assemble genomes with large amount of duplications because our sequencing technology, practically, at best can give ~500 base pairs. Figuring out the ordering of duplicated regions relies on scaffold sequences or comparative assembly to rice genome.

Why was decoding the genome so significant?
Because decoding the genome gives us a complete picture of the genetic makeup of an organism.
What made it so difficult?
The repetitive sequences as mentioned by other people is a main problem. Imaging you are trying to complete a big puzzle with millions of pieces. Each piece represents a sequencing reads that we get from the experiment. If there are repetitive sequences in the genome, basically the pieces that representing these regions would look very similar (or even entirely identical). Undoubtedly, this would make the puzzle very difficult to finish. To give a scale, the maize genome is ~2.3 billion base pairs and each sequencing reads is <1,000 base pairs.


text:
Why did the process of sleep evolve in many animals? What is its evolutionary advantage?
The process of sleep seems to be very disadvantageous to an organism as it is extremely vulnerable to predation for several hours at a time. Why is sleep necessary in so many animals? What advantage did it give the individuals that evolved to have it as an adaptation? When and how did it likely occur in the evolutionary path of animals?

e.g. dolphins can't afford to lose full consciousness when they rest, otherwise they would drown. So their mammalian brains have evolved in such way that only one half of the brain sleeps at a time.

Many migratory animals, like turtles and birds, have also developed this half-brain sleep.

According to one paper I have read, sleeping helps with learning process and many neural connections are reinforced in sleep.

There is the suggestion in the community (nothing published that I can find) that sleep evolved to stop animals venturing out when conditions weren't favorable for hunting (for example hunters of the day became hunted at night, or slow stealthy nocturnal animals becoming obvious in the sunshine). It's better if they just hunker down when their senses aren't attuned for the situations they may face.

Answering parts of your question is the aim of the book Why We Sleep by the sleep scientist Matthew Walker. The book is quite popular and up to date (2017).

This good non-scholarly article covers some of the usual advantages (rest/regeneration).
One of the research papers they mentioned (they linked to press release) was Conservation of Sleep: Insights from Non-Mammalian Model Systems by John E. Zimmerman, Ph.D.; Trends Neurosci. 2008 July; 31(7): 371–376. Published online 2008 June 5. doi:  10.1016/j.tins.2008.05.001; NIHMSID: NIHMS230885. To quote from the press release:

Because the time of lethargus coincides with a time in the round worms’ life cycle when synaptic changes occur in the nervous system, they propose that sleep is a state required for nervous system plasticity. In other words, in order for the nervous system to grow and change, there must be down time of active behavior. Other researchers at Penn have shown that, in mammals, synaptic changes occur during sleep and that deprivation of sleep results in a disruption of these synaptic changes.

This might explain why sleep deprivation affects heart rate.

This is a bit circular, in that sleep being "required for nervous system plasticity" simply means the dependence of nervous adaptation on sleep was never selected out. It doesn't answer why

This argument also fails to mention why there couldn't be a highly modular and redundant brain architecture with at least 2 modules for each neuroplastic subsystem that alternate sleep and wake cycles. Such technology already exists for large-scale server clusters and racks (called a rolling update) where a load balancer is used as a client-facing front end (routing requests to servers ready to accept them). When an update is deployed, servers are shut down, updated, and restarted in a "rolling" manner such that most servers are up at any time during the update.

I found this paper by Benington and Heller that expands on the previously mentioned theory of sleep as a mechanism to renew metabolism.  They hypothesise that sleep is necessary to replenish glycogen stores (mainly within astrocytes) in the brain.  These stores are normally used to supplement blood glucose due to the high energy demands of the brain.
It is suggested that this may also result in the manifestation of feeling sleepy as a consequence of the exhaustion of glycogen supplies in specific small areas of the brain.  Brief and localised depletion of glycogen stores mean that cells are operating with less energy than they normally have to work with.  This causes an increase in synthesis of adenosine from the breakdown of AMP.  The paper maintains that the increased levels of adenosine are detected by adenosine receptors which then triggers or increases (as seen on EEG scans) the feeling of the need for sleep:

In NREM sleep (which may lend some support to the theory as NREM sleep accounts for 80% of sleep and is most physiologically different to waking), this glycogen is most efficiently replaced.  During NREM sleep the release of glycogenolysis inducing neurotransmitters is reduced, allowing glycogen-synthase to predominate and glycogen levels to be restored.  However, these same neurotransmitters are key in the processing sensory stimuli (by tonically depolarising neurons in the sensory cortex).  Therefore glycogen replenishment will always be associated with a (strongly) reduced response to stimuli.
This leads to finally answering the question as to why sleep has an evolutionary advantage, which I will quote verbatim to maintain the authors momentum:

Glycogen replenishment during waking would be maladaptive because it would impair the organism's ability to to process and respond to sensory stimuli.  Sleep has therefore evolved as a state where animals retreat to a safe environment, behaviour is suppressed and glycogen stores are replenished.

So is it just a coincidence that the metabolic pathway of glycogen synthesis in brain evolved to be regulated by neurotransmitters? If it had evolved independently - we wouldn't need any sleep?

@MartaCz-C that's a really good point, and if I'm honest I've struggled to find an answer in literature for you.  However it could be said that as the glycogen reserves are in essence a backup power supply, even if neurotransmitters were not involved such a supply is not likely to be replenished without a greatly reduced energy demand (i.e. in sleep) as otherwise any glucose that arrived would be quickly used rather than stored in glycogenesis.  It could be an adaption rather than a co-incidence if this is the case - forcing an organism to take a period of rest to rebuild these supplies.

A sluggish response to stimuli is better than no response, so it still does not explain what sleep is for. animals don't need to be forced to retreat to safety by going unconscious the same behavior could evolve without going unconscious.

From what I've learned, there are two theories to answer that question:

Restoration - the body needs to rest in order to renew its metabolism (if an animal is active 24/7, it will constantly use up a lot energy and metabolism). It has been shown that mice that have gone a while without sleeping have a compromised immune system.
Preservation - sleep is assumed to confer a survival advantage. Night time is a dangerous time, so sleep sort of 'forces' an animal to lay low for a few hours.

Your point #2 says exactly the opposite of the question's premise. Would you care to expand a little bit (e.g. give some references)?

Point 1 seems to be a circular argument (or flat out wrong): if the animal weren’t sleeping it could hunt / forage for food. Even in sleep, we expend some energy so this calculation will always come out favourably on the side of staying awake.

@KonradRudolph - the body always expends some energy, but the energy the body uses while sleeping is a fraction of the energy it takes to stay awake/hunt/etc.

@nico - I found an excerpt from a book- here

@Innab It’s irrelevant that the energy expense is only a fraction. The important thing is that there is any at all. Do the math, it will never be beneficial to rest instead spending the same time hunting, because the net energy balance of hunting is positive (i.e. energy take-in rather than expense), so in sum, resting will always spend more energy than hunting.

@KonradRudolph surely that is only the case if the hunt is successful - therefore sleeping can be less disadvantageous in terms of energy expenditure if the odds are heavily stacked against successful predation at a certain time of day.

#2 also doesn't apply to nocturnal animals; especially animals that are active at different times of the day specifically to avoid predators.

Why sleep persists is fairly easy, why it is needed is an unknown.
Sleep appears to be necessary in any organism with a brain, that is anything with any kind of concentration of neurons. That is when denied it said organisms die. So all that has to happen is that the benefits of a brain outweighs the cost of sleep.
The length of sleep needed correlates with brain size, at least the REM part of sleep other parts correlate with metabolic rates. Now this can be seemingly confounded in larger complex brains (birds and mammals especially) when organisms start folding the brain to increase neuron density without increasing overall size. In this case these organisms are increasing hte "size" of the brain without making the brain larger, by increasing density.  Worse some organisms "sleep" for long periods, but only a short portion of that time involves the neural activity associated with sleep (like REM), sleep in more complex animals (those with very large complex brains) contains many functions.
In organisms with tiny brains and slow metabolisms (aka the earliest things with brains) sleep does not take very long so the cost is minimal, the benefits of a brain (and thus learning) can be high. Later as brains get larger the cost goes up but so does the benefit, if it was possible for a brain to be retained without the need for sleep it should have been selected for at this stage. So in all likelihood the need for sleep is something fundamental to how neurons function and can't be changed without seriously disruptioin their function. It is not uncommon for unfavorable things to get locked in evolutionarily in this way, the cost to change them (in this case the loss of brain function) is far larger than the cost of sleep so selection keeps it around.
Now the complexity of sleep makes sense, if you already have this required period of downtime, it makes sense evolutionarily to tack on anything else that would be best done during said time. Better to use the triggers and time for existing downtime activities for any others that get added then have even more downtime. So now we have a slew of confounding factors that muddy studies and make it hard to tell what parts are essential.
We don't know why sleep is necessary, there are many ideas but not a lot of evidence. Given the complexity of sleep this is not surprising, teasing out which functions are fundamental is not easy. There is a current leaning towards it being necessary to clear out metabolites that disrupt neural function, it appears this process is highly disruptive to the brain if the brain is awake, to the point simply shutting down brain activity (movement in particular) is far safer for the organism. But as with all research this is very preliminary and sleep is poorly understood so acceptance is and should be very tentative.

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


text:
Could Junk DNA be used as a Turing Machine by nature?
In what ways has DNA been studied to see if there a "programmable" aspect to it?
Has nature produced anything resembling a Turing machine within the cell, perhaps using the "junk DNA" as its code? I expect nature's way would probably be very round-about and not compact.
NOTE: I am not asking about building DNA computers, as this question had recently been contorted to become.

What evolutionary disadvantage would it give if it did not encode for anything? (not saying it doesn't, I am just not a fan of the "Nature must have thought of xyz in all these years" questions)

The whole cell is definitely capable enough to exhibit all features of Turing-complete computer, so there is no reason why to use ncDNA to this task, especially when it works well as a separator and variability reservoir.

@nico If it didn’t code or regulate, it would be garbage which the cells have to drag around with them. More expensive to replicate and maintain, more material cost (just because it’s longer and requires more material to form), requires more space in the cell. There are evolutionary disadvantages to having a large, partly non-functional genome.

@Konrad: one could argue, however, that our body is all but efficient, and has plenty of redundant mechanisms. That said, it is known that certain mutations on ncDNA can have visible effects so, as I was saying, it may have a function, and it probably does, but from there to saying it encodes for some sort of Turing machine...

@nico Redundancy is required for a fail-safe system, it provides a direct evolutionary advantage. And while our bodies aren’t particularly efficient in many aspects that cannot be controlled by evolution (laryngeal nerve …), most isolated systems under evolutionary control have been highly optimised. For instance, a eukaryotic cell’s energy turnover is orders of magnitude more efficient than any engine or generator ever created by humans (intelligently designed).

@Konrad Rudolph: sure, but cells are far from being 100% efficient. An interesting book that touches the subject of how our brain is inefficiently built, for instance, is "The accidental mind" by David J Linden. But I am digressing. My point was only that "Nature must have thought of that in 4 billion years" is NOT a good excuse for a question. I was NOT saying ncDNA is useless.

Can one consider living (biological) cell to be Turing Complete?

Perhaps this question is whether the regions between genes sometimes known as 'junk DNA' has any function.
In the human genome, out of ~5 billion bases there are something like 20-30,000 genes which take up perhaps 10s of millions of base pairs, depending on how you count it. 1% of all human DNA is the common figure.
It is sometimes asked as if biologists commonly think of it as having no use, but in fact this is a researched topic, and few feel that it has no evolutionary or biological function at all.
Some of the most common uses for intergenic DNA in eukaryotes (bacteria are an entirely different topic with very different responses.

Transcriptional Regulation

Outside the coding sequences of the gene, there can be an extensive set of binding sities for proteins which regulate the gene.  In this paper in Figure 1 the celebrated regulatory sequence of ENDO16 is can be seen in Figure 1. As you can see for almoat 2000 bp there are numerous binding sites for many sorts of promotors and inhibitory factors, as well as factors which may splice the gene in various ways.
As I recall, ENDO16 only  turns on for a brief period in the development of the sea urchin and so its very tightly controlled, which means that its got a lot of regulatory elements upstream of it, controlling transcription. Its one of the most exhaustively studied genes ever and the believe they have most of it.  Other human genes ive seen perusing medical literature have seen 20kb are necessary to reproduce the regulation of a gene. Still all this might at best only triple the amount of DNA actively involved.

Centromeres and Telomeres
The physiology of the chromosomes have large regions as Deniz mentions are necessary for cell reproduction and for development.  In animals (like humans) the regions are devoid of transcribed genes and might be 10-15% of the genome length (I'm eyeballing this from the UCSC genome browser on chr21 - in some organisms like yeast the centromere can be just a few hundred base pairs.  So anyway we are getting somewhere now!
Non translated genes.
There are lots of pieces of DNA that might be copied into RNA and then do not function as templates for proteins.  some folks say there is a lot of this stuff.  The typical view is that there are a few thousand of these sorts of beasts known, and humans are currently thought to have about 1500 of them.  A small tweak in the number of genes, but they are there nonetheless.
Chromatin binding and organization sites
Although Centromeres are places where chromatin binds, the several families of proteins which bind DNA and wrap them into organized coiled coils thought to be like spools of telephone wire to form the Nucleosome which makes the chromosomes look like the little stick men you see in text books.  Chromatin can spool up just about any sort of DNA but seems to have a preference for regions which are at the ends of genes.  They can be modified by enzymes (acylated, methylated) to modulate their affinity for some classes of DNA sequence.  This is a hot topic of research.  The ability for RNA polymerase to find transcribe a gene is not good if its wound onto chromatin and though its not a precise binding like a transcription factor, chromatin binding and regulation must be affected greatly by changes in the distance between genes and the DNA sequences which surround a gene for thousands of base pairs, which is one of the main differences between species.

Of all biological systems (at least that I know of) this one accounts for the most bulk DNA sequence and is probably as related to the difference between different species as transcription factors and almost certainly is an older system of gene regulation, if you think about it.

Copy Number Variations and repetitive regions
just a side note, but small and very long repeat sequences can show up in the intergenic regions as well as inside a gene boundary to account for some of the differences between individuals.  they can be quite short or quite long.

Well hope this helps?

Just to be more accurate, about 1.5% of the human genome is coding DNA (Nature 409, 860-921 (15 February 2001))

wow - thanks for the bounty vote.  I'd like to add that the mathematical Turing machine would involve using the DNA as memory and sequences over long distance affecting each other in a systematic way.  chromatin sort of behaves like this, but the analogy is a stretch...

just found this nice blog post with some hot links on 'Junk DNA' and how its being studied recently. http://phylogenomics.blogspot.com/2011/06/selfish-dna-symbionts-and-parasites.html

Depends on what you mean by "non-coding".
There are structural elements in telomeres & centromeres -- although the DNA there does not code for proteins, it contributes to the three dimensional structure of the chromosome.
"Non-Coding" DNA can also act as a binding substrate for many proteins: transcription factors,  enhancers, histone proteins; and thus control regulation indirectly through these intermediaries.
Promoter regions upstream of transcribed/translated regions are the combinatorial control switches/dials of our genome, and have tremendous regulatory importance.
Non-Coding DNA also acts as repertoires of mobile DNA elements, which enable fast evolution / "plasticity" by copying&pasting exons around (L1 transductions) or by copying into coding regions & interrupting them.
Lastly,  they can act as the sandbox of evolution: Non-coding regions not genetically linked to functional regions are very likely to not suffer from  purifying selection, so they can act as templates of random evolution - where the vast majority of mutations won't have any impact positive or negative.  This enables exploring brand new combinations, which may then become new exons / miRNA / regulatory regions or get shuffled into other regions to enable new functionality.

You may wish to expand on the 'sandbox of evolution' point =)

@Rory Good point, will do.

I am very suprised nobody mentioned the field of DNA-computing. It is proofen by Leonard Adleman and Richard Lipton that you can compute with DNA molecules.
In the article of Adleman they present an experiment to solve an instance of the Traveling-Salesman-Problem. Because this problem is in NP one can say that the DNA is turing-complete.
Article of Adleman
For a deeper understanding see

-1: a) DNA can be used to compute, but the cell does not naturally do that. b) specific sequences of DNA/RNA are requested to do nucleic acid based computing, which are not necessarily present naturally, and/or not necessarily in ncDNA. c) the apparatus needed to do that is not only DNA based, specific enzymes, added in specific sequences are needed.

I dont see the sentence in the question where your restrictions are mentioned. Can you help me?

sorry, I did not notice that someone edited the question, I was still thinking about the first version of it, so my comment does not really apply anymore. However, the system does not allow me to remove the -1 now, please do some edit to your answer so I can change my vote.

By programmable, I suppose you mean that it contains information or can be altered in response to some input or stimulus.  The answer is "no" for both.  Well, sort of.
Does noncoding DNA contain information?  By definition, no.  There are probably many regions of the genome that appear to have no information, only later to be found to contain introns, regulatory elements such as enhancers, boundary element, MAR/SARs, targeting sites, etc.  Even functional tests (such as removing the region) may not reveal anything because the effects could be minor, or only evident under special conditions.  But arguably, if you remove a region and it has an effect on the organism, then it's not really a noncoding DNA, it's just you didn't see the coding before hand.
As for the latter, can it altered, the answer is again "no," or at least "apparently not."  Intergenic regions (those stretches of DNA that do not contain obvious or characterized transcribed regions or their control elements) are very stable between organisms and even between species.  They seem to have a mutation rate expected for having no information, and thus free to mutate slowly without being swept away.  There is no evidence (as far as I know) of any region of the genome being purposefully altered, with the exception of a handful of specific genes whose regulation is controlled by DNA nicking or some such.
Perhaps I am missing your question, being a biologist and not really knowing what a "Turing Machine" is.  If I misunderstood, please clarify.

I don't have a reference to give right now, but mutations in introns can, for instance, affect splicing.

Nico, that's not necessary.  I'm well-aware that mutations in introns can affect splicing (as well as expression should the gene have intronic enhancer elements).  However, I was talking about mutations outside of transcribed regions.  Part of the problem with the question is divining what he or she means by "noncoding DNA."

Sure, mine was just an example

@KAM Noncoding DNA does contain information, it just doesn't encode for protein sequences.

@Gergana Vandova, OK.  I guess it's a difference of definition.  If you define "coding" as open-reading-frames, then you're right. I look at "coding" as carrying useful information.  Overall, though, I think it's a vague term.  I've heard some describe rRNAs as coding, since they code for structural information.  It's a semantic argument.

@KAM I think that this is the common definition of noncoding DNA. Tried to find a reference, but couldn't find any except wikipedia and some dictionaries. Would be nice if people don't spend time trying to infer what the asker meant....

Nature has done pretty well in the subject of formal computation. So much that we are still trying to keep its pace.
As about your question, it depends on your definition of "non-coding DNA".
In general, DNA together with the machinery in charge of its maintenance is Turing-complete in several senses. Take a look, for example, to the existence of mobile genetic  elements: some of them are "subprograms" coding for reverse transcriptases which in turn are able to reproduce the original program. I must note that for doing this with a Turing-complete formalism like the lambda-calculus, well, you need to do a fairly long and complicated program: http://crpit.com/confpapers/CRPITV26Larkin.pdf .  And the lambda calculus is "easier" than bare Turing-machines, meaning that you can write shorter programs than with Turing machines for doing the same thing. So, my (somehow specious) argument is that any real-world information machine capable of self-replication is with high likelihood Turing-machine equivalent.
It just happens that the essential feature of mobile genetic elements is to ensure its survival, so, that's probably the reason we haven't found a fragment of DNA able to do something as interesting as calculating square root.
If you refer to the part of DNA that can not do anything at all, well, for talking about Turing-machines and computation you need a way in which some "data" can be "interpreted"  as a program. A totally inert piece of DNA does not fill that role, by definition.

Unfortunately, it can be shown trivially that self-replication isn’t sufficient for being Turing complete (imagine the programming language “Rep” which has a single command, “rep”, which prints “rep”; clearly this language allows to write self-replicating programs and clearly it isn’t Turing complete).

@Rudolph: that's what I meant by "specious". So, it is not a formal proof, and you will need to do some more work to have one. However, it would surprise me that a machine more complex than anything we have invented (including our beloved computers) would be not Turing-complete.

The problem is not that the proof is specious, it’s that the proof is impossible since the assertion is provably wrong. I agree with the more specific point that cells in particular are Turing complete – but not all self-replicating information machines are.

@Rudolph: Agree, my mistake.

Let me answer your question by splitting it into two parts:
Can DNA be used as an programmable medium (=band) for Turing machine?
The answer is YES.
Starting from the breaking paper by Shapiro et al. in Nature, followed by another great article by Parker, there are many scientific publications about how to use DNA for computing. Unfortunately, these findings are still not applicable for classic computations and DNA computers will hardly substitute the normal ones in the nearest future.
Can a junk DNA work as Turing machine?
There is a known principle in Computer Science called "Junk In, Junk Out". Same in the case of DNA -- there is a way to use junk DNA for computing, but the result of the computation will mostly be junk too: as long as we don't know what this DNA is for, and this doesn't seem to operate as Turing machine on its own, there is hardly possible to get something reasonable by running this DNA on a turin machine...

"Junk" here has a specific meaning. And by the way, its usually written "Garbage in, garbage out"

Thank you. I am aware of what "junk DNA" means, just wanted to play around with the word a little bit to make my point clearer.

My question wasn't so much using a dna strip in place of the paper for a turing machine. That's not very interesting. I am asking if nature already has computation machines in a cell, which might help explain some of the non-coding DNA

Oh, I see. I misunderstood your question then. Maybe you try to re-formulate it to clarify your point, because other answerers might have understood it wrong way too.

You understandably misunderstood the question because some moron has hijacked my question and changed it into something completely different. If you look at the comments under the question and the high rated answers you see they are discussing my original question, not the one you saw. I've tried to edit it back to what I asked.

Indeed, I noticed the mismatch between the question and the comments, but I thought that it is because the question was improved in reply to comments. Now it is much more clear, thank you for your efforts!


text:
Why are there nail growth differences  between humans and other mammals?
When a cat is growing, his nails are growing with him to some extent. A grown cat has a fixed nail length that is not extending.
By contrast, human finger nails just keep on growing, so we have to cut them to keep an aesthetically pleasing look.
Nature clearly has a mechanism to control nail growth.
What is the most probable reason as to why this is not implemented in humans?

Cat claws are growing all the time, like horse hooves, or human nails. However, cats and horses usually use their claws/hooves, so they get shortened through mechanical action.
An indoor cat may need their claws trimmed if it doesn't use them enough (that's why cats will want to scratch everywhere), or if has supernumerary toes that don't normally touch the ground. Similarly, cattle that doesn't get to move will suffer from hoof overgrowth, which appears to be very uncomfortable to the animal.
Consequently, if you were to use your fingernails more often for digging and scratching, you wouldn't have to trim them all the time.

Thank you Jonas for clarifying it for me. I guess the mechanism for limiting the growth when an optimal length is reached is non-existent, since there is no probing mechanism to know how long the nail actually is at a moment of time. The same may apply to hair.

Hair has a maximum length. A hair grows to full length, then sits idle, then falls out and is replaced by a new hair.

@Maxim Of course there are mechanisms for that. How else does a leg know when to stop growing? Or any other organ in the body. Most of the mechanisms behind that aren’t yet completely understood though.

@Konrad, well, the leg don't regenerate in case it's part is removed mechanically, whereas nails are in a constant growth state. Leg is a complex organ that has a feedback. It can tell the brain how long it is by the lenght of a neural connection network. Nail does not have it, so there may not be a mechanism to know how long it is.

@Jay, thank you. Good point. This proves that the hair provides an informational feedback to the brain about it's length also, unlike nails.

@Maxim Not in humans. But in plenty of other animals, and there doesn’t seem to be a fundamental reason why this couldn’t in principle work in humans.

@Konrad, sorry, I've lost you. Plenty of other animals have what?

@Maxim The ability to regenerate legs (or other parts).

@Jay, Maxim : I am not convinced hair has informational feedback. I think it's more that the skin provides the feedback e.g. heat retention information, or stress info due to the weight of the hair.

@JohnSmith I never suggested there is informational feedback. hairs grows for a certain length of time. Cutting the hair doesn't change the clock.


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Coincidence that navel is near the womb?
The attachment point of the umbilical cord in a baby girl is very close to where her own baby would develop. Is there something in the evolutionary history of mammals that explains this, or some anatomical constraint? Or is it just a coincidence?

I would say that they are not that close. Yes they are both around the abdomen, but the navel is central to the abdominal cavity and the uterus is quite low in the pelvic cavity, in a non-pregnant woman, (it is even below the pelvic brim, and not even in the peritoneum).

I would say it is a coincidence because:

the navel is in the same place in males, so if it was there for some evolutionary advantage the charachter would be sexually dymorphic, which clearly is not the case.
I cannot think of any specific function of the navel that is related to pregnancy or delivery (or of a specific function of the navel at all for that matters)

Why would it be dimorphic even if it didn't carry an advantage? Usually, sexual dimorphism has to be selected for. Even if the advantage was only to the female, why would the SRY gene code for anyplace else?

@C. Lawrence Wenham: I'm not sure I follow you... what I meant is that if the position of the navel was selected because it was somehow advantageous for pregnancy I would expect the selection pressure not to exist in males...

@nico unless the locus for naval position wasn't sex linked, in which case males would have it in the same place as a side effect of selection for that location in females...


text:
Is there evidence that some non-human species perform sexual selection based primarily on intelligence? How do they do this?
I'm a biology amateur, but it seems like sexual selection is almost always performed based on physical characteristics, the outcome of physical contests, or some sort elaborate courtship. But do any non Homo-Sapiens perform sexual selection based on intelligence factors, like problem solving abilities? If so, how does the species accomplish this? I know natural selection as a whole would definitely favor intelligent individuals, but I'm curious if any species actually takes this into account when choosing mates.

Alas, selection based on intelligence is often absent in Homo Sapiens...

Super question.

Very intresting question. The problem is that animal intelligence is hard to measure not only for scientists, but probably also for the potential mate. Paradoxically, that is why selection for intelligence, if it occurred, may be very strong. One has to be smart in order to recognise smart behaviour, so preference and preferred feature are strongly connected. But that's only my opinion.
Boogert et al., 2011 1 reviews the current knowledge about animal preferences for cognition skills. They conclude that there is very little data on this subject. The given examples are:
1) Preference for elaborating birds songs (as songs are not inborn and have to be learned)
2) Spatial abilities:

In meadow voles (Microtus pennsylvanicus), males with better spatial learning and memory abilities were not only found to have larger home ranges and to locate more females in the field (Spritzer, Solomon, et al. 2005 2) but were also preferred by females in mate-choice tests, even though the females did not observe males’ performance on spatial tests (Spritzer, Meikle, et al. 2005 3).
In guppies (Poecilia reticulata), males that learned faster to swim through mazes to gain a food reward were found to be more attractive to females (Shohet and Watt 2009 4). However, females were not able to see the males’ performance in the mazes. Although male learning ability was weakly correlated with saturation of the orange patches on his body (a sexually selected trait (...)), orange saturation surprisingly did not correlate with female preferences. Thus, the cues leading female guppies to prefer faster learners are unknown.

It is possible, that females base their choose on some factors that correlates with cognitive skills or on total wellness, what may depend on intelligence.
3) bowerbird's abilities to build bowers (courtship constructions):

Comparative studies across bowerbird species have shown that relative brain size is larger in species that build bowers than in closely related nonbuilding species (Madden 2001 5). In addition, relative brain size increases with the species-typical complexity of the bower (Madden 2001 5), and a comparative study on the relative size of specific brain regions showed that species with more complex bowers have a relatively larger cerebellum (Day et al. 2005 6).

4) foraging performance

A recent experiment by Snowberg and Benkman (2009) 7 using red crossbills (Loxia curvirostra) showed that, after observing 2 males extracting seeds from conifer cones, females associated preferentially with the more efficient forager of the 2. The authors were able to exclude female choice for correlated traits by experimentally manipulating foraging efficiency, such that fewer seeds were available in the cones of one of the males. The males were also swapped between treatments (i.e., slow vs. fast forager) so that male identity could not explain the females’ preferences for the most efficient forager.

Another way that intelligence may be favored by sexual selection is "cheating" during courtship. For example most frog species call to attract females. But this signal may also attract aggresive rivals or predators. Some males, especially the weaker ones, do not call  but stay near calling individual.  This allows them to avoid confrontation and wait for approaching females [8]. The successfulness of this strategy may depend on how "smart" the individual is (only my opinion).
[1] Boogert, N. J., Fawcett, T. W., & Lefebvre, L. (2011). Mate choice for cognitive traits: a review of the evidence in nonhuman vertebrates. Behavioral Ecology, 22(3), 447-459.
[2] Spritzer MD, Solomon NG, Meikle DB. 2005. Influence of scramble competition for mates upon the spatial ability of male meadow voles. Anim Behav. 69:375–386.
[3] Spritzer MD, Meikle DB, Solomon NG. 2005. Female choice based on male spatial ability and aggressiveness among meadow voles. Anim Behav. 69:1121–1130.
[4] Shohet AJ, Watt PJ. 2009. Female guppies Poecilia reticulata prefer males that can learn fast. J Fish Biol. 75:1323–1330.
[5] Madden J. 2001. Sex, bowers and brains. Proc R Soc Lond B Biol Sci. 268:833–838.
[6] Day LB, Westcott DA, Olster DH. 2005. Evolution of bower complexity and cerebellum size in bowerbirds. Brain Behav Evol. 66:62–72
[7] Snowberg LK, Benkman CW. 2009. Mate choice based on a key ecological performance trait. J Evol Biol. 22:762–769.
[8] Bateson P. 1985. Mate choice. Cambridge University Press. 181-210

I know nothing about biology however I did watch an amazing PBS documentary on cuttlefish that I think is fairly relevent.
From http://www.pbs.org/wgbh/nova/nature/kings-of-camouflage.html

NARRATOR: During mating, males outnumber the females, sometimes 10 to
  one. And they're all looking for the chance to pass on their genes.
  While a female lays eggs beneath a rock, a big male tries to
  monopolize her, staving off the other hopeful suitors.
Sometimes intimidation alone won't work, and the competitors hurl
  themselves into a violent and bizarre looking wrestling match.
Like an octopus, they'll squirt out an inky smokescreen when it's time
  for a hasty retreat.
But size and strength aren't the only ways to impress the ladies.
Thanks to the cuttlefish's skin morphing talents, the smaller males
  have a clever trick up their sleeve.
MARK NORMAN: The really interesting thing in this system is actually
  far less obvious, and when you first dive with them, you don't see it.
  It takes a while before you realize what's going on.
The small males, who have no chance in a contest with a big male, are
  actually doing something completely different. They're effectively
  cross-dressing. They're dressing up as a female, by pulling in their
  webs and putting on this mottled color pattern and gliding past these
  big, aggressive male, pretending to be a female, and will come in to
  the female underneath.
And what happens is, as another big male comes in and a potential
  conflict between these big guys starts up, the sneaker males start
  mating with her, successfully mate with the female, while the big guy
  isn't even aware of it.
NARRATOR: The cross-dressers' success is all the more impressive
  because the females often play hard to get, as Roger Hanlon has seen
  firsthand.
ROGER HANLON: These females are very picky. They reject 70 percent of
  approaches for mating. Yet they only reject 30 percent of the
  cross-dressing males. So this trick gets them in the door, so to
  speak, past the fighting male, and they're accepted by the female.

Sounds a lot like humans to me. Explain why females pick jerks rather than normal guy with money. If guys with money approach females, they got beaten up by stronger males with anti prostitution laws. Then some guy just seduce, and it works. Maybe it's how we are set up.

@JimThio I think Cracked has an answer for that here. http://www.cracked.com/article_18804_the-6-wrong-questions-men-love-to-ask-about-women.html


text:
What is the base cancer rate for an arbitrary carcinogen?
Are all carcinogens equally potent? Is the relationship between dose and probability of cancer roughly equal, or are there some carcinogens that provoke cancer significantly more than their cousins?

To answer this question in its entirety we have to split it into two questions:

What are the underlying mechanisms of carcinogenity?

One of the main mechanism behind carcinogenity is the mutagenity of the cancerogens, i.e. the ability to cause mutations, that are abberations of the cell DNA leading to uncontrolled proliferation. This classical paper investigates the relation between cancerogenity and mutagenity.
One should mention here that there are many types of mutations possible, mutations are not equally dangerous for cells and some mutations can be successfully repaired using the intact strain.
Therefore the following parameters of the source substances need to be measured to estimate the cancerogenity:

Substance concentrations or absolute amounts (both being indirect measures of their chemical activities, the lower concentration is needed for causing cancer the higher is the chemical activity and vise versa).
Substance radioactivity (for the mutagenesis due to radiation).

How can we measure the carcinogenity of different substances?

The most general approach here is to introduce certain amount of cancerogen into the animal body or to the cultured cell and to see the effect. The effect is calculated as the percentage of cells that undergo the transformation from normal into cancer cells. Two metrics are available here:

DT = Tumorigenic Dose (the amount of substance causing certain
  percentage of cancer in treated animals, all treated animals are taken
  for 100%)
CT = Tumorigenic Concentration (same, but adjusted for
  concentration and used in cell cultures).

(They are written CT and DT because in science people tend to used Latin abbreviations where the adjective actually follows the noune).
The common metrics are DT5/CT5 (5% cells/animals get cancer) and DT50/CT50 (50% of the animals). Those are similar to other common metrics, the most common is LC50/LD50 -- lethal dose for 50% of the animals/cells.

Unfortunately I couldn't not find any pre-compiled list with most known cancerogens and their TD/TC values. These seem to be interesting primarily for scientists. But going back to your question: you are absolutely right: some cancerogens are much more potent in causing cancer than the others!