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Can an influenza virus carry other infectors with it?
This idea came to my mind when thinking about how many people become ill in many locations with similar symptoms (fever and rough cough) from Influenza.
There are of course different types of influenza virus.
Can Influenza A virus work as a vector for other upper respiratory infections?
That is, much the same as the mosquito being a vector of malaria, can an influenza virus carry other infections with it?
If so, how? If not, why do some people get so sick from viral influenza, and not others?

What do you mean by vector? That it can cause other respiratory infections?

@Chris No. That it can help transport other respiratory infections which cause other respiratory infections.

Transport in the way that it helps a secondary infection to get into the upper respiratory pathways because the immune system is already dealing with influenza?

I think the meaning is much the same as the mosquito being a vector of malaria, "can an influenza virus carry other infectors with it?" @chris

I don't think there is a reason to close this question. I think it's better to ask for clarification first.

I agree with @Chris - it should get a chance to get clarified first.

@Masi - please feel free to roll back. I tried to keep it in the spirit in which it was asked.

@anongoodnurse Thank you for edits which make the body clearer! No need to rollback.

I wouldn't call influenza a vector here, but yes, an infection with the flu virus which results in a full infection can have secondary infections as complications. There are often caused by bacteria which usually live in the respiratory pathway and kept under control by the immune system.
This includes pneumonia (either viral or bacterial), inflammation of muscles and the heart muscle (myositis and myocarditis) as well as pericarditis. Less severe complications include infections like ear infections and sinusitis.
See the references for more details:
References:

Complications of Viral Influenza
Double trouble: Bacterial super-infection after the flu
A Mouse Model of Lethal Synergism Between Influenza Virus and
Haemophilus influenzae

Does this help answering the question? If not, you need to be more specific and I will work on it later today.

It helps. Is it possible that influenza is asymptomatic but it causes opportunistic diseases? This can be one explanation - influenza triggering some infections of upper respiratory tract without itself causing any symptoms. This could explain why influenza is felt differently by different people too.

I don't know right at the moment, but I will look into it. The other problem is the use of the word flu - most people which talk about having a "flu" in fact have something else. Most likely an influenzal infect (which is not caused the the influenza virus). This one feels bad as well but is not as severe and clears much faster (usually within a week, from what I know from my MD colleagues).

A vector transmits a disease or parasite from one animal or plant to another. Fruit bats are vectors for Ebola. They are a host to the virus, which can then be passed on to humans.
Influenza A, the virus responsible for human seasonal epidemics, is not a vector for other pathogens, although co-infection with two different strains of influenza can give rise to progeny viruses with mixtures of genes derived from the parental strains. If anything, that would make humans, other mammals and birds the vectors for Influenza A.[1]
Influenza A doesn't carry plasmids, and it does not insert it's genes into cell DNA as does a retrovirus.
The most frequent serious complications of influenza are pulmonary and fall into 4 categories or groups:

primary influenza pneumonia
secondary bacterial pneumonia (also called co-infection, but from different sources)
pneumonia due to unusual pathogens or in immunocompromised hosts
exacerbations of chronic pulmonary diseases

Typically, the first group is smaller than the second (except for Avian Influenza A). No additional infection is necessary in this group to cause pneumonia or death.[2]
In the second (and largest) group, typically viral influenza infection is followed by near resolution of symptoms, subsequently complicated 4 to 14 days later by a recurrence of fever, dyspnea, productive cough, and pulmonary consolidation. Common pathogens are S. pneumoniae, S. aureus (methicillin-sensitive [MSSA] or methicillin-resistant [MSSA]), S. pyogenes, H. influenzae, and some others.
The pathogenetic mechanisms of viral-bacterial co-infections result from virus induced alteration in pulmonary epithelial cells (e.g. reduced ciliary function, cell death/decreased epithelial barrier function, etc.), virus-mediated inhibition of innate immune cells (e.g., suppressed phagocytosis, impaired microbial killing, etc.), dysregulated inflammation (e.g. increased inflammation due to chemokines) and other mechanisms.[2][3]
Pneumonia due to unusual pathogens or in immunocompromised hosts, and exacerbations of chronic pulmonary diseases are less common than the second group but carry a high mortality.
The second reference is an exhaustive review which you might find quite helpful.
1 FluGenome: a web tool for genotyping influenza A virus
2 Complications of Viral Influenza
3 The co-pathogenesis of influenza viruses with bacteria in the lung

Yes, I like the second source most: Better use of influenza vaccines and antivirals
may decrease risks of pulmonary complications, but
novel prevention and treatment strategies are needed to
improve outcomes for those at highest risk. This proposes me that all coinfections caused by influenza A virus are not known or cannot be protected by the usual influenza vaccine. Meta-analysis of the development of influenza vaccine would be great. I have the general idea that newer vaccines include just recent developed strains. I am not sure if this is best approach, since some do not have old ones.

While a viral infection such as influenza can lead to secondary infections, it is inappropriate to call it a vector for those other infections. It is not the means by which those other infections are acquired. If a bacterial sinus infection follows upon a bout with the flu, that bacteria was not carried to the patient by the influenza virus. A single bacterium is immense compared to any virus. No, the bacteria most likely resided within the host before the infection, but it was under control. Or it might be introduced during the infection and find a foothold it would not have likely found in a healthy host. In a situation like this, the immune system is distracted and weakened enough to present an opportunity for this bacteria to grow out of control into an infection.
The bacteria in this scenario are a little bit like the annoying hordes of roofing contractors that recently swarmed my neighborhood after a hail storm. These guys are always around, looking for the occasional roof that might be getting old and need repair. But right after a hail storm, they find a lot more of the opportunities they are looking for. So suddenly they are all over the place. They didn't literally fall from the sky with the hail. But the hail presented the opportunity they needed to thrive.
Malaria is a microscopic germ which hitches a ride inside a comparably enormous mosquito to find it's way eventually into a human blood stream. An influenza virus is too small for anything infectious to hitch a ride inside it.

love the roofers analogy

Except the roofers are symbiotic.

@vajra78 OK. Most of these roofers are symbiotic. But let's say some are parasitic. They are extremely crooked, unlicensed fly-by-night businesses that take advantage of the home owner. They use substandard materials, and then disappear after collecting initial payment without even finishing the job. Symptoms may include drained funds, uncovered roofs, and water-damaged homes. They cannot thrive in an ordinary environment as reports of their misdeeds and lawsuits catch up with them. But after a big hail storm, the volume of need allows them a temporary foothold.

Contrarily to the main opinion expressed so far, I would say that, in theory, it is possible that an Influenza virus can be a vector for another virus.
Here is a paper about using influenza virus as vector for a variety of genes.
The same method can be leveraged to engineer an Influenza virus particle that contains, for example, genes coming from another virus. Upon infection, the Influenza virus will infect the host cells with both genomes.
In this way you will end up with an Influenza virus that act as vector for another virus.
However, such a hybrid looks very unlikely to occur in nature.
But it can be certainly made in lab.

Excellent article! Thank you for your answer! Please, add further articles and/or books if there are some which could be useful to understand this case better.

There are tons of similar articles for many different viruses. In molecular biology they are called viral vectors. Its a virus used to transfer DNA to a target cell. Just google viral vectors and you will have a nice overview.

In bacteriophage, the viral capsules serve as vectors for other DNA so frequently that there is a common name for this: transduction. The image below, from the Wikipedia, illustrates the basic process. Here a phage, with pink DNA, accidentally packages up other DNA -- in this case, from the bacterium -- in one of the capsules and thereby serves as a vector for this DNA.

Something a bit like this happens any time we have recombinational assortment in the influenza virus. The influenza virus genome segmented, with 8 "chromosomes". When an individual is multiply infected with different strains, new combinations of the 8 chromosomes can be packaged up within an given viral particle. This process is often responsible for new epizootic strains.
In principle, genetic material from another virus could be packaged up accidentally into an influenza virus particle. If it happened to enter the right kind of cell, the influenza capsule could in that way act as a vector for the other virus's DNA. In practice, I would imagine that this would require remarkable coincidence and thus would be extremely uncommon in nature.

+1 for picture and new proposal! Is this method of bacteriohpage the one of most likely methods how influenza could act as a carrier? Can you relate it to alec_djinn's answer?


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Public Pacemaker database online?
I am looking for any database about pacemakers with the leads

atria A
right ventricle VR
left ventricle VL

I did not find any in Physionet.
Is there any anonymous data about different situations online or accessible by request?

source: Stack Exchange

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

sort: votes


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Western blot alternatives
Given an in vivo sample from an experimental infection, I would like to see if a bacterial protein is present.
I've been thinking about Western Blot using sera from animals infected with the bacteria. However, this strategy needs a positive control that requires prior gene cloning and expression.
There is maybe a shorter path.
Thanks

Is the antibody against your protein commercially available?

No, they are hypothetical proteins, not common ones.

People asking same thing here: https://www.physicsforums.com/threads/western-blot-alternatives.642444/

I think that enzyme-linked immunosorbent assay (or ELISA) is the best way to do so, given you have an antibody against the protein to coat the sample wells with... You could use mice to create polyclonal antibodies against your protein by injecting the protein and collecting the serum and purifying it...as long as there isn't similar proteins to the bacterial one in the sample you are testing for...but to diagnose an infection you could use something like q-PCR assuming you can get the bacterial DNA from the sample (you could use typical bacterial DNA extraction techniques).
For more on ELISA go here. Here is a good animation on ELISA:
http://highered.mheducation.com/sites/0072556781/student_view0/chapter33/animation_quiz_1.html

You don't have to use PCR to diagnose diseases, ELISA or western blot is routinely used for this purpose.

@chris well... it depends on the disease too...

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


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fastq-dump using mkfifo to stream data
So, fastq-dump has the ability to be run on just an SRA file accession number, such that the SRA is converted to FASTQ on-the-fly, and the SRA doesn't have to be written to disk.
I'm curious whether it would be possible to use fastq-dump to write to a named pipe (using mkfifo) and feed that into another program, for example Trinity, to run an assembly on the FASTQ file without ever having to write all that data to disk. For large datasets, this could actually save quite a bit of time in aggregate.
Has anyone done something similar? I am going to try and experiment with the technique soon, but I a) don't know much about the mkfifo process to begin with and b) am unsure of how this procedure would work for paired-end data where fastq-dump is splitting the SRA file as it goes. How would one specify which output would go to which pipe?
EDIT: A (hypothetical) example:

mkfifo fileStream
fastq-dump SRR123456 > fileStream
Trinity --single fileStream misc_args

That should take the fastq-dump data and stream it into the named pipe "fileStream", which can then be used to stream data into Trinity. I don't know enough about all of the commands, however, to know if this makes any sense.
I would welcome any thoughts from more experienced users!
EDIT: Added update as an answer below.

Can you give an example of the kind of piping you are trying to do? Frequently I just try something like bin1 infile | bin2 - and see what happens.

I you don't get an answer here you should try asking at http://stackoverflow.com/ or http://unix.stackexchange.com/, since this deals a lot with tools and piping in Bash.

I agree with @fileunderwater ... this should be migrated to stack overflow (I just don't have the power to do so!)

@fileunderwater, @T Abraham: I am not super familiar with the culture on here, and I am fine with having this question go wherever. It's possible, however, that with the updates this post might prove useful to someone else in bioinformatics using Trinity.

@glarue You should post the last update as an answer instead, since that is what it is. It is perfectly fine to post answers to your own questions, and then the community can decide (by voting) on which answer is the best.
And for the record, with regards to my suggestion to move/crosspost; I don't think the question is off-topic here, since it clearly deals with methods in bioinformatics.

fastq-dump can write to stdout ; the -Z option allows you to do that. This, you can pipe to any downstream process. [An example]. Also see the SRA-toolkit manual.
I guess someone asked this question in biostar too.

As WYSIWYG pointed out, fastq-dump can output to STDOUT, so if you want to combine it with named pipes, you'd do:
mkfifo mydata.fifo
fastq-dump -Z mydata.sra > mydata.fifo &
cat mydata.fifo # or whatever
rm mydata.fifo

If you try to catch the output from fastq-dump without -Z it fails with the Illegal seek(29) error:
mkfifo mydata.fastq
fastq-dump mydata.sra &

By the way, be careful with your downstream analyses: if the input is to be read more than once, respective program will fail to re-read from your pipe. For single-end data and Trinity that's probably not the case, but I suspect that for paired-end data Trinity will attempt to read the input files at more than one step.

Thanks for the additional info. I am now much more familiar with the commands and have gotten it working. I also appreciate the note on PE data; I believe for Trinity however it's not a problem because the first thing Trinity does is write the data to FASTA files (which it later concatenates). The trick with PE is to deal with the convolved data such that it gets properly split into separate streams for feeding into Trinity. I will update post with a working example soon.

Okay, so just for others who might stumble upon this, here is a brief description of one implementation of this technique to run with paired-end RNA-seq data:
fastq-dump SRA_file --split-files -I -Z | tee >(grep '@.*\.1\s' -A3 --no-group-separator > namedPipe_1) >(grep '@.*\.2\s' -A3 --no-group-separator > namedPipe_2) >/dev/null

This first requires the creation of two named pipes using mkfifo. For paired-end data, the -Z flag becomes problematic because it forces the data into a single stream. There are many ways to regain the two pairs, but the way I've elected to do it is to use --split-files to break up the stream beforehand, -I to append either ".1" or ".2" to the end of each header, and then use tee to duplicate the stream plus grep with a regex to parse the info from each pair back out into separate pipes for downstream use.
I have tested this with Trinity, running on each named pipe just as I would with a FASTQ file, and it seems to be working fine. While I am not 100% sure that Trinity won't try and go back to the original FASTQ files, the first thing Trinity does is take those FASTQ files and parse them into FASTA format, which it later concatenates into "both.fa", and so I'm pretty confident that this will work.
UPDATE: This implementation will not work (at least, not as far as I can tell) with the Trimmomatic plugin for Trinity. Something seems to get screwed up because of the way Trimmomatic pulls from the streams - just a cautionary note, I haven't figured out the cause.


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Would biotechnology in agriculture actually decrease biodiversity, as many people say? Does it have to?
I've heard the claim that because farmers would be using the same seed, you would end up with an entire crop population that could be susceptible to a disease. Like if you had a diverse population of potatoes, not many of them could become blighted, but if you have only one kind of potato on your farm and that kind is susceptible to Phytophthora infestans, then all your potatoes would become blighted.
I was wondering:

Is this really how it works? Like once a seed with a desired characteristic is found, is it cloned? Or would they implement the same gene into many different crops?
If they do clone them, why couldn't they implement the same gene into a diversity of crops? Is it too costly?
Could one use mutagenesis to create diversity? If the seeds are cloned, could a certain number of the seeds be modified to try to account for natural diversity?


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Why does DNA have its name?
Why is DNA called deoxyribonucleic acid and not something else? I get the nucleic acid part (because that's what DNA is made of) but what about the deoxyribo- part, especially the ribo- part. Maybe because DNA doesn't have oxygen, hence the "deoxy-"?
(Also, please tell me what is wrong with my question or whether there was a duplicate I didn't find so I can fix this question or delete it.)

Ribo- comes from ribose, which is a -ose(sugar). desoxy-ribose is a ribose with one oxygen missing. DNA uses desoxyribose while RNA uses ribose.

@Remi.b - perfect answer! Please convert to save the question from the closing frenzy. As never having received proper Latin training I sympathize with my fellow analphabetics :)

It is not "the" perfect name. Someone just named it that way. Friedrich Miescher called it nuclein. In earlier times DNA was actually called desoxyribonucleic acid. If your question was about why "deoxyribo-" then I guess it is mentioned in wikipedia. Hence I am voting for closure.

@WYSIWYG - I commented 'perfect answer' not 'perfect name'. I think it's a valid question with a valid answer, provided the comment is converted.

@ChrisStronks Oh I did not comment at your comment.. The "perfect" term is co-incidental

Deoxy because oxygen is missing at the second position

I'm voting to close this question as off-topic because it is a trivial question about chemical nomenclature that could be found easily.

The name is derived from the sugar which is bound to the base. For RNA it is Ribose (that why it is called ribonucleic acid) and for DNA it is Deoxyribose (hence the name deoxynucleic acid). The deoxyribose is missing an OH-group at positition 2 of the sugar ring, the name literally means "without oxygen". See the image below (from here) for further clarification:


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Why don't McDonald's fries decompose?
So I was cleaning out my car and found a McDonalds French fry. as I don't eat anything in my car I know exactly who and when this fry is a result of. The when is + 10 months old and it could pass off as one just prepared. How could this be?

Dehydration prevents decomposition. Frying stuff basically replaces water with fat. Your once-upon-a-time potato was basically mummified at maccers.

Although arguably not the most ordinary question, this question is not opinion-based.

Thank you @ChrisStronks I wasn't expecting the initial  down votes here this is pretty much day one biology. I guess we have to shove it down peoples throats. McDonald's french fries are soaked in hydrogenated oil. Saturated fat's which are entirely hydrogenated have a very linear structure thus making a molecule stack one on ...

top of another, sealing off all moisture. Decomposition occurs from the inside out. At the time the french fry was fried it was essentially sterilized on the inside and then as it cools it is sealed by the hardening saturated fat. I had to start taking Lipitor yesterday so I thought i would post this question. Good choice with the mummification analogy :-) i'll give it to t. Abrams and less you want to post something

Is this straight out of 'Supersize Me?'

@HDE226868 think you might be right I forgot where I learned this from.

I was a little disappointed that the mechanism wasn't discussed in the documentary, so I'm glad you asked here.

French fries and cigarettes will satisfy any dietary need for acrylamide

This controlled experiment of burger decomposition explains in detail why fast food burgers do not decompose easily. The same can be applied to fries, which are smaller and come dehydrated from the frying.
The main take-aways from this experiment are:
1: Dehydration is the main reason why fast food fries/burgers do not decompose easily. Placing the burgers in a ziplock bag, preventing dehydration, causes the burgers to decompose.
2: Since an unsalted, home-made burger did not decompose, preservatives, chemicals, saturated fats, and other components are unlikely to be the case of the fast food burgers not rotting.

+1 for using "take-aways" - even though I suspect it was not a deliberate pun seeing as we are talking about fast food, it tickled me. Good clear answer with references too.


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Why deoxyribose for DNA and ribose for RNA?
Why is DNA made out of deoxyribose and RNA made of ribose? Why can't they both use ribose or deoxyribose? I think that the deoxyribose gives an advantage in storing genes, the job of DNA and ribose is better dealt with outside the nucleus...but why?

The vast majority of RNA in most cells is found in the ribosomes, where it is largely double-stranded and quite stable (and ribosomes are not typically in the nucleus), so answers about relative stability, sub-cellular localization, and strandedness are not germane.

The nucleus is irrelevant. DNA and RNA arose in non-nulceated organisms (prokaryotes).

Nice question which leads to the fundamentals of DNA and RNA.
DNA (Deoxyribonucleic acid) is the core of life in Earth, every known living organism is using DNA as their genetic backbone. DNA is so precious and vital to eukaryotes that its kept packaged in cell nucleus, its being copied but never removed because it never leaves the safety of nucleus. DNA directs all cell activity by delegating it to RNA. RNA (Ribonucleic acid ) have varied sort of biological roles in coding, decoding, regulation, and expression of genes. RNA carries messages out of the cell nucleus to cytoplasm.

The structure of RNA nucleotides is very similar to that of DNA nucleotides, with the main difference being that the ribose sugar backbone in RNA has a hydroxyl (-OH) group that DNA does not. This gives DNA its name: DNA stands for deoxyribonucleic acid. Another minor difference is that DNA uses the base thymine (T) in place of uracil (U). Despite great structural similarities, DNA and RNA play very different roles from one another in modern cells.
http://exploringorigins.org/rna.html

RNA has three main characteristics that differs it from DNA

RNA is very unstable and decomposes rapidly.
RNA contains Uracil in place of Thymine
RNA is almost always single stranded.

DNA and RNA use a ribose sugar as a main element of their chemical structures, ribose sugar used in DNA is deoxyribose, While RNA uses unmodified ribose sugar.
Ribose and Deoxyribose

From the fig above we can see that the principal difference between
  the two molecules is the presence of OH in ribose (2' tail) and absence
  in deoxyribose. There is a difference in one Oxygen atom as the name
  stands de-oxy ribose. Both Ribose and deoxyribose have an Oxygen(O)
  atom  and a Hydrogen (H) atom (an OH group) at their 3' sites. The OH
  groups are very reactive in nature, so the 3' OH tail is required for
  phosphodiester bonds to form between nucleotides in both ribose
  and deoxyribose atoms.

Answer
DNA is such an important molecule so it must be protected from decomposition and further reactions. The absence of one Oxygen is the key for extending DNA's longevity. When the 2' Oxygen is absent in deoxyribose, the sugar molecule is less likely to get involved in chemical reactions( the aggressive nature of Oxygen in chemical reactions are famous). So by removing the Oxygen from deoxyribose molecule, DNA avoids being broken down. In an RNA's point of view the Oxygen is helpful, unlike DNA, RNA is a short-term tool used by the cell to send messages and manufacture proteins as a part of gene expression. Simply speaking mRNA (Messenger RNA) has the duties of turning genes ON and OFF, when a gene needed to be put ON mRNA is made and to keep it OFF the mRNA is removed. So the OH group in 2' is used to decompose the RNA quickly thereby making those affected genes in OFF state.
Finally, the ribose sugar is placed in RNA for easily decomposing it and DNA uses deoxyribose sugar for longevity.

References
Flesh and Bones of Metabolism -  Marek H. Dominiczak
Genetics For Dummies -  Tara Rodden Robinson

Do you have a reference for the claim that the 2'OH is important for regulating mRNA? My intuitive guess would be that active degradation by RNAses would be far more important than the chemical instability by the 2'OH.

@MadScientist: References are attached on the bottom of the answer. It must be  the selective advantage of DNA over RNA as the genetic material.

As far as I know, the hydrolysis of RNA via the 2'OH doesn't play any role in regulating mRNA levels, there are lots of active RNA degradation mechanisms that are responsible for that.

"RNA is very unstable and decomposes rapidly.".. this is not a correct statement... it is not thermodynamically unstable.. It is chemically unstable given the physiological or alkaline environment.

@WYSIWYG: I meant it is chemically unstable

@MadScientist: As mRNA is unstable due to the presence of 2' OH and degrading enzymes(ribonucleases) involvement. But the question is related to the usage of ribose & deoxyribose in RNA & DNA. The 2' hydroxyl in mRNA is frequently methylated, so I think the instability of OH in RNA is reasonable for the degradation.

"DNA is so precious and vital to eukaryotes that its kept packaged in cell nucleus, its being copied but never removed because it never leaves the safety of nucleus." You do realize that in most Eukaryotes, the Nuclear Envelope breaks apart during Mitosis and Meiosis? Prokaryotic bacteria and Archaea also use DNA, but don't have nuclei. Mitochondria have their own DNA and genome, yet they are organelles inside the majority of Eukaryotic cells. Red Blood Cells discard their genomes when they terminally differentiate, and those are kind of important to the life of most land animals.

"RNA is almost always single stranded." Nope. RNA forms double strands frequently, and needs to be straightened out when entering the ribosome. RNA that is not formed into some kind of secondary/tertiary structure is unusual, not the other way around.

Then why do many viruses use RNA?

I am obviously biased, but find this a very poor answer to have been accepted. It is puffed out by unedited quotes of basic information and empty statements about molecules being 'important'. It contains factual inaccuracies  "every known living organism is using DNA" (RNA viruses?) and sloppy expressions such as "genetic backbone". There are no links to original literature. No links are given to the listed references, but the citing of "Genetics for Dummies" does not engender confidence in them. Oh well, @Tanmath, you pays your money...

Another importance of RNA (specifically tRNA) is also its responsibility for the transcription of information from codons in protein synthesis

Addition to Jvrek's answer based on the comments. Most RNA degradation mechanisms catalysed by different RNAses (RNAse-A and RNAse-S, for example), involve the 2'-OH. Therefore the repertoire of RNAses is selective towards RNA and not DNA because of the 2'-OH.

Why DNA for the genetic material?
I think the correct and sufficient answer to this is the one so frequently repeated that it is difficult to find the original source. For example, G.F.Joyce wrote in a 2002 Nature review article:

The primary advantage of DNA over RNA as a genetic material is the greater chemical stability of DNA, allowing much larger genomes based on DNA.

To expand, RNA is unsuitable for large genomes because the 2'-OH of ribose (obviously absent from the 2'-dexoyribose of DNA) renders the phosphodiester bond susceptible to alkaline hydrolysis (see illustration adapted from Wikipedia article).

This will occur slowly at pH 7.6, but at a rate calculated to be sufficient to degrade a 1000 nucleotide RNA in about 70 days. This explains why all RNA viruses have small genomes (and why some, like flu virus, are segmented).
Why RNA for other informational functions?
There are a variety of ad hoc arguments here, but none as conclusive as the argument above for DNA. This is partly because there are a variety of functions RNA performs — one can make different arguments for each. Before making a point that I don’t think has been made above, I would say that RNA most likely preceeded DNA (whether or not one believes it preceeded protein) and that there would have had to be a selective advantage for organisms to switch from RNA to DNA. One can see that for the genome, but not for the other functions.
This argument also applies catalysis, but in a slightly different way. If RNA enzymes (ribozymes) preceeded protein enzymes, most ribozymes have been dumped because protein enzymes are more efficient and organisms which developed them were at an advantage. Those that are left are so intimately involved with RNA that replacement by proteins would have been difficult. So answers to this question about DNA not being able to replace catalytic RNA, though correct, seem to me peripheral the general question of RNA function.
The central function of RNA is surely in protein synthesis — mRNA, rRNA, tRNA. One thing that these perhaps have in common is a three-dimensional structure that differs from an extended double helix. (Yes mRNA has tertiary structure too.) RNA lends itself more readily to such structures because the chemical difference between ribose and deoxyribose leads to a different helical structure (A-helix) from that of DNA (B-helix). To quote Fohrer et al.:

The presence of the ribose 2'-hydroxyl group in RNA engenders a preference for the C3'-endo puckering, thereby providing the decisive factor for the differences in conformation, hydration and thermodynamic stability between canonical RNA and DNA helices.

(Image from Niel Henriksen showing C3'- and C2'-endo pucker of ribose. C2'-endo pucker is found in deoxyribose in the B-DNA helix.)
The RNA A-helix involves less stringent base-pairing than the DNA B-helix (hence the greater error frequency in replicating RNA virus genomes), which is also reflected in non-WC base-pairing in rRNA and tRNA. (The presence of U in RNA, rather than T in DNA should also be mentioned — GU base-pairs are found frequently in rRNA.)

+1 for the RNA hydrolysis point. Could you mention what the half-life of RNA in water is? Would help to judge how serious the RNA hydrolysis issue is.

@Roland - According to J. Am. Chem. Soc., Vol. 121, No. 23, 1999 (p.5371) the rate constant for RNA hydrolysis is 1.4 × 10-7 min-1 at 37C and pH 7.4, which works out as a half life for a 1000 nucleotide RNA of 70 days. (The paper quotes half lives for the much greater rate constant at 100C, in relation to thermophiles).

Excellent! That definitely shows RNA is too easily degraded to be viable as genetic material.

If the degradation mechanism is alkaline hydrolysis... does that mean RNA is more stable in acidic environments?

@LoganR.Kearsley —  Yes, I think that is so, and I seem to recall it is one of the arguments used against the RNA world theory. I'm just off for a week's vacation and will check and answer more fully when I get back. Oh, just found the type of paper I was thinking of. Haven't had time to read it though: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3372908/


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Can swallowed fingermails, hair, or skin get caught in your appendix?
There is a common saying in my place: If you eat your skin, hair or nails, it will be deposited in the cecal (Vermiform) appendix, and can cause appendicitis. (This is mostly told to children to discuourge them from eating their own.)
Is there any reality in this statement? In the case of hair and nails they are dead cells, but what is the issue with skin? Skin is normally living and the cells are active.
So is there any problem digesting ones own skin?
Do nails, skin and hair must be trapped in Vermiform appendix?

Hint: Keratin. Usual proteases in our gut cannot digest keratin.

This is something that Proteinase K can do - hence the name "k".

Most questions in SE are placed "on hold", I think there are straight forward answers exist to this question. Can someone enlighten me, for what reason this question is put on hold ?

Skin is safe to chew, and digestible. Fingernails are not digestible, so really shouldn't be swallowed if avoidable. In the medical literature, there are at least 225 cases of foreign bodies in the appendix. They include:

a metal drill bit that was ingested unintentionally 3 months earlier
pins (81  cases)
lead shot (81 cases)
seeds (34 cases)
bones (16 cases)
eggshell
glass
teeth
nails (hair causes problems with bezoar formation)
a die (dice)
the clinical end of a thermometer.

Most (71%) patients were symptomatic, typically with intermittent abdominal pain for months or years. Pins were most likely to elicit symptoms (93% of cases).
So it seems there is some truth to this nugget of folk wisdom.
The above were found over many, many years. Since most cases are asymptomatic, it's likely there are many cases that never come to light, but not remarkably so (lots of appendices are removed and examined every year!).
Foreign Bodies in the Appendix

What about digestion of skin, WYSIWYG commented that Keratin is indigestible.

@Jvrek - please see the first line.

Wow, it's really kept here for years! How do they send the  little cameras to the digestive track so they get out?

I would have put bezoars in big flashing letters at the top of the answer, as the number 1 reason not to do it... ugh.


text:
Effect of Western chicken and GH
I heard this clause from my teacher one week ago:

Chicken are grown in half a year until eaten in Baltic countries - Estonia, Latvia and Lithuania, for instance, [probably in other parts of Europe, too]. How do you imagine this to happen so fast? - - Growth hormones are used to grow them fast. This affects your endocrine system and can replace its natural function. We cannot even know the withdrawal symptoms when you stop eating food of growth hormones. - - Eat pork instead. No growth hormones used in their life cycle because not needed and not so useful in practice.

I started to think what. Can this really be true that the effect of growth hormones is big economically on poultry but not on pork so it is not used.
The size of chicken is small compared to pork so they have different muscular structure.
So probably more musculature in chicken and bigger effect therefore.
Why does growth hormones have bigger growth effect on chicken?
Is it true that growth hormones are used more in the growth of chicken than pork in Western countries?
I do not understand the critique presented against poultry industry here, in favour of pork industry.
Probably, there is some truth too.

Their conclusion relies on 1) chickens being fed more growth hormones, 2) that growth hormone leaves some sort of chemical trace in the meat we eat, 3) we absorb those trace chemicals, 4) those chemicals are bad for us - this is of course irrelevant to the question but if I were you I'd be asking the teacher for some evidence, there's too much of this sort of thing based on myths and hearsay.

@GriffinEvo Yes, I know that there is much myths and hearsay about this. I want evidence based thinking. The main argument is that chicken meat growth needs GH, but pork not, therefore GH is used in chicken.

Poultry raised for meat in the US (called broilers) reach butchering size in 5 to 8 weeks (compared to 10 weeks for half the size 40 years ago. It's not a GH miracle; it's a result of generations of selective breeding (as cows have undergone for unhealthy udder size).
GH use is illegal in the US and many other countries. Honestly, it's an unnecessary additive/expense.
I raised poultry for more than a decade, mostly chickens and ducks (but almost everything else as well). Once I bought 25  1-day-old broiler chicks (early broilers were a Plymouth Rock X Cornish) alongside my usual mix.  Within 2 weeks the broilers were at least 3 or 4 times the size of the other chicks, and more than a couple of them died (under ideal conditions - all free-range outside, cooped only at night). By 10 weeks, they were enormous.
They were also dumber than a bag of hammers, unfortunately. I felt so sorry for them that I let them live out their natural lives, which wasn't terribly long, partly because of their docile stupidity.
Growth hormone is unnecessary in the poultry industry.
Murray McMurray Hatchery: Jumbo Cornish X Rocks
Modern Meat Chicken Industry

Thank you for your excellent answer with indepth knowledge in the area! I will discuss this issue with my teacher more detail what he meant. Is there anything else used in the growth which may be more harmful for people, in contrast to pork -industry? I cannot think anything.


text:
Resource for finding Repressive/Inhibitory factors for a given gene?
I have a list of genes for each of which I'd like to find:

A list of transcription factors that up-regulate the gene
A list of inhibitory factors that down-regulate it.

I used this tool on Qiagen's website to find transcription factors (and will be thrilled if someone can share a better tool). Its less than ideal for my purposes because I need to search each gene individually and there doesn't seem to be anyway of downloading or copy/pasting the transcription factors it returns; but it works.
What I really need now though, is a way to find inhibitory factors by gene. Does anyone know how I can do this?
I have already tried using  wikipathways and found it to show almost none of the transcription factors I found on Qiagen's website leading me to conclude that their data is far from comprehensive. I have applied for access to Ingenuity only to discover that I will not be granted access soon enough to make use of it.

I don't think such a tool exists simply because there are too many interactions possible. They also depend on the cell type, state of the cell and so on. I have been working with a transcription factor for quite a while and I would have loved such a tool. We endet up analyzing new targets ourself.

There is no tool and there is no direct way. There are databases that have predicted transcription factor binding sites (TFBS). There are experimental data (ChIP-seq) for TFBS too; however it is difficult to ascertain if the TF is activator or repressor without further experimentation. Moreover, same TF can act as either repressor or activator in different circumstances.


text:
How to attract spiders to my house?
I've been living in my apartment for a year now, and noticed something lately. During spring and summer I have quite a lot of midges indoors, and even now there are some. But there are no spiders! So my question is a bit of the opposite of what all spider/house related articles are about: how do I get more spiders to my house?
Some info about my place: I live in a 40 year old apartment in Rotterdam, Netherlands on the second floor. It's always between 17 and 20°C, and the place is poorly isolated; plenty of cracks for visitors to crawl through. Also, I usually have a window open a bit. I have quite a lot of plants, and an aquarium, so I guess air humidity is relatively high. There is a large backyard with lots of weeds and some trees, however people use it for dumping old furniture so it is not a real garden (it's most likely the source of the midges).
Can I do something to stimulate spiders to come to my house?

Spiders are naturally attracted to areas where preys are abundant, insects are primary source of spider prey. So you must create proper environment for insects in your home,  lights to attract nocturnal insects, flowers to attract butterflies and moths are attracted towards decaying vegetation(It may make your place smelly). Once insects are abundant then spiders are attracted towards these areas. Some parasitic wasps are predator to spiders like those belonging to Ichneumonidae, try to avoid these species. Also you can collect spider eggs and place it inside your home, so they will hatch out in your place.Some times you can see web full of spider nymphs, take it out and place it in your home.
Attracting spider to home can be achieved through buying some spider traps like poison free spider glue, which contains pheromones. Spiders are attracted to it and they will stick on them and eventually die, so you need to be careful and use the phenomenal effect of the spider trap to attract spiders or it will be dead and become useless.
The analysis revealed that the wasp spider pheromone is methylcitric acid trimethyl ester, a derivative of citric acid.
Some other techniques to attract spiders

An unspecified Cheiracanthium species is attracted to the smell of petroleum and has caused problems by weaving webs inside the canister vent of particular models of Mazda vehicles, resulting in blockages and build-up of pressure that could potentially cause fuel leakage from the fuel tank and an increased risk of fire. Mazda issued a voluntary recall of Mazda 6 models built between 2010-2012, to fit them with software which would alert drivers if problems were developing.
Reference

A spider that preys on the malaria-carrying mosquito is attracted to the odour of people's smelly socks, say scientists.
Reference

Eugenol baited traps we found seven individuals of two species of Thomisidae. In contrast, with the control traps, no Thomisidae were caught . Since Thomisidae were caught only in traps baitedwith eugenol, whereas no crab spiders were attracted to control traps, we postulate that eugenol served as an attractant for these spiders.
Reference

We had a tractor with a clogged fuel filter once because a spider somehow got inside it, so an attraction to gasoline might be more widespread than just that species.

These seem like great tricks. I think I'll try Eugenol first, smelly socks and petroleum don't seem like such attractive options to use indoors;) Done some research on Eugenol, Apparently there's quite a lot of it in clove buds and leaves. Will see if I can get myself a small clove tree. Also just lay some cloves around and get some oil from them.

In addition, here's more details on growing a clove tree: http://gardendrum.com/2013/11/27/how-to-grow-cloves/

in order to attract spiders in to your home

make sure there is plenty of light to attract prey for the spiders
leave a window open
put some leaves in the corner
if you find some insects or flies try to catch them then get some glue and stick them on the window seal

thanks for reading

Welcome to Biology.SE! It isn't clear that this adds anything to the existing answer.
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text:
Number of transcription factor genes in the human genome
What is the number of the transcription factor genes present in the human genome? Does this value differ compared to Mus musculus, Drosophila melanogaster, Arabidopsis thaliana, C. elegans and S. cerevisiae? Additionally, does the proportion change between eukaryotes and prokaryotes?

do you mean the number of genes? Or the proportion of TFs relative to something?

either the proportion of number of TF genes in the entire gene pool, or the number of TF genes and I can make the math myself

I slightly edited the question. It may be advisable to specify your model organisms as the 2nd question is very broad as of now. For example, name a few such as Drosophila, Canis, Arabidopsis or whatever suits your question.

There are some things to be clarified here. For example would you consider enhancer binding proteins such as C/EBPs or epigenetic modulators like HDAC as transcription factor. In any case you can look this up and unless more details are provided this question would be considered homework (It would take me the same effort as you to find out the answer. I would appreciate if you ask - "how to find out the number of TF", instead of the question as it is).

I meant DNA binding elements

I disagree with closing votes but agree the question could be narrowed down a little bit. For example, "DNA binding elements" may be certainly too broad. Also, assume by proportion the OP means the percentage of TF genes relative to total number of genes in each species. Disagree with changing the question to "how to find out the number of TFs"- thats a completely different question (but an interesting one, mind you).

"Also, assume by proportion the OP means the percentage of TF genes relative to total number of genes in each species" correct

Here I will assume we are talking about eukaryotic sequence specific transcription factors (ssTFs) and try to answer your first and part of the second question. There is in any case not definitive answer yet.
An estimate of ssTFs genes in humans is given in the 2009 Nature Reviews Genetics paper by Vaquerizas, JM et al, A census of human transcription factors: function, expression and evolution.
An excerpt from the abstract:

Here, we present an analysis of 1,391 manually curated sequence-specific DNA-binding transcription factors, their functions, genomic organization and evolutionary conservation.

The numbers are somewhat higher now. Wingender et al. have counted 1,558 human genes in their TFClass database 2013 NAR paper. In their 2014 NAR paper they included 1,557 human, 1,147 mouse and 1,105 rat orthologs.
Another way to look for this information is to see the number of entries listed in TF databases, like for example JASPAR. This has the advantage of including other species. However, the coverage here depends on the availability of position weight matrices (PWMs) for the binding specificities. Many uncharacterized TFs may not be found.

To try to answer your third question, that is, what is the proportion of TFs in the different species, a naive approach would be to divide the number of predicted TFs by the number of predicted genes in the target genome. For example, taking the latest estimates above with the predicted number of coding genes from Ensembl database (version 78) will return these percentages:
# Human
100 * 1557 / 20364 = 7.64%
# Mouse
100 * 1147 / 22606 = 5.07%
# Rat
100 * 1105 / 22777 = 4.85%

This suggests humans have a slightly higher proportion of TFs than rodents. However, these differences are not too big and may be dependent on the accuracy of the different estimates on TFs and gene numbers. An in itself, these numbers are not so interesting.
A much more interesting question is whether TF families have expanded more or less in different species (that is, whether the number of  proteins within each family has increased, regardless of the proportion to the total number of genes in the genome). I could find at least one paper where this has been done systematically for several eukaryotic species, covering animals, plants and fungi, and focusing on TFs common to the ones found in plants. The main conclusion of the paper is that some TFs families have expanded more in plants than in other organisms. Quoted from the abstract:

To investigate if differences exist in the expansion patterns of TF gene families between plants and other eukaryotes, we first used Arabidopsis (Arabidopsis thaliana) TFs to identify TF DNA-binding domains. These DNA-binding domains were then used to identify related sequences in 25 other eukaryotic genomes. Interestingly, among 19 families that are shared between animals and plants, more than 14 are larger in plants than in animals. After examining the lineage-specific expansion of TF families in two plants, eight animals, and two fungi, we found that TF families shared among these organisms have undergone much more dramatic expansion in plants than in other eukaryotes. Moreover, this elevated expansion rate of plant TF is not simply due to higher duplication rates of plant genomes but also to a higher degree of expansion compared to other plant genes.


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Well to well variation in thermal cycler fluorescence?
We have an old BioRad ICycler Thermal Cycler with MyIQ single color fluorescent detector. While it's meant for RT-PCR, we've been using it for melt curves and binding assays for different types of RNA using thiazole orange as the intercalating fluorophore. However, when we tried to get serious about this assay and do things in triplicate we noticed that the well to well variation was terrible, making statistical significance difficult to get.
After reading through the manual I tried to get "persistent well factors" for the instrument to correct for this variation. However, the instrument's protocol for this requires heating to 95⁰C, so intercalating fluorophores won't work, the RNA melts and fluorescence is lost, so I tried with fluorescein. This didn't solve the variation.
So I tried to make my own well factors by making 10mL of Poly(rA) Poly(rU) RNA solution with thiazole orange and filling 96 PCR tubes with 100µL each and measuring fluorescence. Then I calculate the average fluorescence and divided the average by the value for each well to determine a factor, F, for each well. Then I tried to normalize subsequent experiments by multiplying each well's fluorescence by its F to get a corrected value. However, while this reduces the variation a little, it's still pretty bad.
Do you have any suggestions to reduce the well to well variation in these experiments or otherwise correct the data?
I have no prior experience with RT-PCR instruments, everything I know about it comes from playing around with the instrument. I don't know if I'm missing something really basic.
Step by step protocol

Prepared 1xSSC buffer, 150mM NaCl, 15mM Sodium Citrate, pH 7.5
Weighed 5mg Thiazole Orange, dissolved in 1mL Methanol
Diluted Thiazole Orange 1000 fold in 1xSSC
Took 71.4µL (100µg) Poly(rU) Poly(rA) solution, 1.4µg/uL
Diluted RNA with 8.93mL 1xSSC
Added 100µL diluted Thiazole Orange to diluted RNA, final volume 10mL
Set up 96 PCR tubes, used 8 channel pipette and trough to transfer
100µL RNA solution to each
Placed PCR tubes in all 96 positions of thermal cycler
Ran melt curve protocol, start at 25⁰C, increase 1⁰C every cycle,
60 cycles, so final temp is 85⁰C. Each cycle is 10 seconds.
Measure fluorescence every cycle.
Repeated melt curve 3 times, total of 4 curves.
Put data from each curve into spreadsheet. 96 data points at each temperature.
Averaged fluorescence across the whole plate at each temperature.
Used this average, standard deviation, maximum, and minimum
values to make the plots below.
Calculated correction factors for each well at each temperature by
dividing the whole plate average fluorescence by each well's
fluorescence for melt curves 2, 3, and 4. Averaged correction factors from each curve.
Calculated corrected fluorescence for curves 1, 2, 3, and 4 by
multiplying the averaged correction factor for each well by the
observed fluorescence for that well.
Replotted the corrected values to show reduced variation.

Data is shown below. I repeated the melt curve 4 times because the first melt usually has a lower intensity than subsequent melts. Y axis is fluorescence, X axis is temperature in celsius, and I plotted the average fluorescence at each temperature with the standard deviation along with the minimum and maximum to show how far outside the standard deviation some wells are falling. I calculated the correction factors for melt curves 2, 3, and 4 and averaged them. When I used these averaged factors on melt curves 2, 3, and 4 it did a good job at eliminating variation. When I applied the correction factors to melt curve 1, it reduced the variation, but not by much.

Are you sure that part of the variance is not due to the processing of the triplicates? How do you prepare them? This is a very important factor and a serious error source.

@Chris edited the question to include how I prepared the samples.

@user137 In questions like these it is best to describe the protocol that you used, step-wise.

@WYSIWYG A step by step protocol has been added. Feel free to ask about anything that isn't clear.

@user137 There should not be any necessity to do a well to well fluorescence correction. There should not be variation from any source other than handling. Is your machine serviced and all?

@WYSIWYG The variation exists despite trying to minimize variation by creating 1 large batch of solution and using a multichannel pipettes. The bright wells and dim wells seem to be the same wells in every experiment. The machine is not serviced at all, we don't have a service contract and I don't think I could convince my advisor to pay for maintenance.

@user137 I have had troubles with multichannels. sometimes the tips don't fit properly and it causes variability. In any case there are more sensitive equipments for melt curve analysis. In qPCR machines the lamp also has to be replaced after some time (it has some 'life'). Is this not a crucial experiment? All I can suggest is do another meltcurve experiment with a different concentration (or whatever parameter you want to change) and see if the inter-well variance makes the difference statistically insignificant. If it doesn't then go ahead with the experiment.

@WYSIWYG Thankfully it's not a critical experiment yet, and won't be for me because my thesis is finally almost finished. However I suspect my advisor will want the new student taking on my project to do a lot more with it. I'll see about the lamp replacement because I'm pretty sure it's never been replaced and the instrument has to be 10 years old.

@user137 Do these comments kind of answer your question?

@WYSIWYG They've been helpful, probably as close to an answer I can get without bringing you to the lab to debug it in person.

There can be several reasons for variability and since you said that the machine has not been serviced for a long time, I guess that should be one main source of errors. Multichannel pipettes can also sometimes cause problems (based on personal experience) and it is mostly because the tips don't fit properly in all channels.
Try varying some parameter (for e.g. concentration of RNA) and see the effect on melting temperature; if the inter-replicate variability is not high enough to make the inter-sample difference insignificant then you can continue with your experiment. Take more number of replicates to minimize variance.
If the variability is very high then I guess you would need to get your machine repaired or use more sensitive equipments designed specifically for these kind of studies.


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How can site-directed mutagenesis be used to suppress the production of anti-antibodies?
In a previous post of mine, I asked how to supress the creation of anti-antibodies in vivo. In the answer, it was mentioned that site-directed mutagenesis could be used. Currently, I can't find mcuh on how to do so... How does this work?
Update: As people want to know where this idea is coming from, here is the link to my previous question about it.. look in the answer for more info:
How to inhibit formation of specific antibodies (to antisera)?

Could you link to your previous post for context? Site-directed mutagenesis is nearly impossible to perform in vivo, so I'm wondering what the comment poster was getting at...

You want to do site-directed mutagenesis in unspecified living cells in a living body? How do you want to select the cells which make the auto-antibody? This will never work.

@Chris it was just a comment provided by the answer for my previous question.. I will give you the link


text:
Why are most transcription factors enhancing the expression rather than repressing?
One can classify the effects of Transcription Factors (TF) on gene expression into two types: it either enhance or repress the gene expression.
I have always been told that most of transcription factors functions act to enhance gene expression rather than repress gene expression. Assuming this is true, my question is why are activators more common than repressors?. Is there for example a mechanistic explanation for that (cost less energy to enhance or the enhancement pathway is easier to evolve)?

From wikipedia

While activators can interact directly or indirectly with the core machinery of transcription through enhancer binding, repressors predominantly recruit co-repressor complexes leading to transcriptional repression by chromatin condensation of enhancer regions.

The mechanisms are different and it sounds a likely cause of the overrepresentation of enhancement function of transcription factors in genomes but it is not obvious to me why activators and repressors have to have use different mechanisms and it is not obvious to me either why these different mechanisms would yield to a ratio of repressors to activators other than $\frac{1}{2}$.

Do you have a reference for this claim? Also, keep in mind that simply the absence of an activator can be repressive. In other words, one mechanism of repressing gene expression is to not express the activator.

They do not fall into clear groups. A transcription factor can activate one gene and repress another. Either by binding to its regulatory region or by upregulating another suppressor (which would be a secondary effect).

No I don't unfortunately. But as I have heard that several times I kinda felt that this was common knowledge. "absence of an activator can be repressive". That sounds weird to me. Isn't just a matter of relativity? The point is that still, activators are more common than repressors (assuming this is true) and so why? is it easier to evolve activator than suppressor?

@Chris Oh good point! But still most functions are repressive (assuming this is true) so the question still hold. If it is not common knowledge that activators are more common than repressors I may have better to first ask a question about that to make sure my assumption is correct.

Hypothesizing I would say this is because of different control pathways. You can turn on genes on a pretty sensitive way (fine regulated and only a few at a time with a lot of regulators). You can then use different circuits to regulate the downregulation.

Also worth mentioning is that the same protein can directly activate or repress the same gene depending on post-translational modifications.

I edited my post following your comments on the categorization of TF into groups. I now made sure that I categorized the function/activity/role of a TF and not the TF by itself. It might still have some cases that won't let easily fall into one of my two bins but I think it generally speaking offer a good categorization.

@Remi.b This is tending to be opinion-based. There are some situations where repressive control is favourable and there are others where activation is better. You really need to add details and also provide the reference for Repressors < Activators.

I too have heard the statement "TFs generally enhance expression", but it should be something more like "TFs work to enhance correct expression by repression or expression."

I can answer this question only based on guesses because I am not really sure about your claim that activators are higher in number than repressors. So consider this as an extended comment.

While activators can interact directly or indirectly with the core
  machinery of transcription through enhancer binding, repressors
  predominantly recruit co-repressor complexes leading to
  transcriptional repression by chromatin condensation of enhancer
  regions

Not really true. A repressor can simply sit on the the promoter and prevent RNAP from binding the to the latter.

Abstract
Transcriptional repressors are usually viewed as proteins that bind to
  promoters in a way that impedes subsequent binding of RNA polymerase.
  Although this repression mechanism is found at several promoters,
  there is a growing list of repressors that inhibit transcription
  initiation in other ways. For example, several repressors allow the
  simultaneous binding of RNA polymerase to the promoter, but interfere
  with subsequent events of the initiation process, eventually
  inhibiting transcription initiation. The recent increase in the number
  of repressors for which the repression mechanism has been
  characterized in detail has shown an amazing variety of strategies to
  repress transcription initiation. It is not surprising to find that
  the repression mechanism used is usually exquisitely adapted to the
  characteristics of the promoter and of the repressor involved.

Some justification on why the number activators would be more:
A network perspective:
Lets assume an that gene-A somehow causes the repression of the gene-B. This repression can be either direct (A being a repressor of B) or indirect via some other genes. In the case of indirect regulation you just need one repressor in the network path A → B to result in repression of the latter.
So all repressive paths would minimally require only one repressor, all other steps in the path can be activation; whereas in an activating path you would need 'n' activators for 'n' steps.
Post-transcriptional Regulation:
Now if you include post-transcriptional regulation then you can find more number of repressors: miRNAs (2588 reported in humans: miRbase-21) and many proteins as well (For an e.g. see here). Most cases of events leading to translational activation are actually derepression. It is logical in a way because an mRNA is a temporary product; it should not by default require an additional signal to start producing proteins.

Thanks. I appreciate these speculations based on my non-referenced statement. Your explanations make quite intuitive sense.


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Studying effects of alcohol on cells
I am wondering about the logistics of a simple experiment with say 3 types of alcohols, and various concentrations of each, with a control(s)
I would like to research the effects of alcohol on mitosis. Do I need any expensive equipment or is it do-able with standard equipment? I am looking specifically at what I expect to be a negative impact on cell growth. Potential cell death and slowing of mitosis.
"We expect mitosis to slow and stop entirely or become corrupted as the amount of alcohol used increases. Of the three alcohols we will be testing, we expect some to be more damaging than others. The 3 chosen alcohols, listed in order of their hypothesised toxicity are Methanol, Ethanol and 2-methyl-2-butanol."
I am basically trying to see if tertiary alcohols are safer due to ethanols main metabolites acetaldehyde & acetic acid being more harmful/toxic? Since Tertiary alcohols for example, aren't metabolised into aldehydes. Which makes them less toxic than ethanol in theory.
Now I am unsure as to which cells to use to test upon, I'm also unsure as to the legitimacy of my hypothesis. Budget, time and a lack of knowledge is against me. I am researching as much as possible as quick as possible. Thankfully I have help available soon or I would be totally out my depth. This is me out of practice in the field trying to get a head start and help a friend out as best I can. I'll be his assistant and feel thats more than appropriate.
I realise I can't test for too many things. I need one clear goal. If we choose to test certain cells over others do you have any suggestions? and why?
The liver processes ethanol into acetaldehyde & acetic acid. So I would need these chemicals potentially in order to properly test ethanols effects on cells?
I am so out of my depth I feel right now I'm hoping for a prod in the right direction.
The 3 chosen alcohols, listed in order of their hypothesized toxicity are Methanol, Ethanol and 2-methyl-2-butanol. - concentrations of each yet to be considered.
I suffer from dyslexia and my wording is bad at the best of times. But please realize this is a very first draft / ideas on the table. Any help at all is appreciated, apologies for my lack of knowledge in the field. I'm trying to refresh my studies from 10 years ago in 2 days.

Great idea! It seems that this research has been done before and your hypothesis is correct, but testing a wide variety of alcohols and testing your hypothesis for each one of them would be a great project.
Now, to do this, I would expect you would need to check the growth of the cells after certain periods of time. How would you do this? Well, the best device would be a hemocytometer. It looks like the price varies from 10.00 - 400.00 which is pretty cheap. Of course, there would be mitosis if there is growth during periods of time, which means there would be more cells after certain periods of time.
What cells to choose? I would choose something easy to work with, such as E.coli. It is safe and easy to work with. It needs minimal resources. Here's a link to a simple culture you can probably make at home:
http://makezine.com/projects/how-to-make-bacterial-brothagar/
Later, however, when you get good data, you can use mammalian and human cells to show that the research is relevant to human beings. However, mammalian cells are harder to grow because mammalian cells grow slower than bacteria and fungi and moreover contamination can cause problems. You would also need biosafety cabinets or laminar flow hoods and learn of aseptic and sterile technique.

Based on T Abraham's answer, a hemocytometer would work. However, a hemocytometer requires a microscope, but if you are in a cell lab, you probably have access to a microscope. I would recommend using mammalian cells instead of bacteria, they're larger and easier to see, and more relevant to human health. If you're interested in liver toxicity in particular, try getting HepG2 cells. These are human liver cancer cells, but extra paperwork might be involved because they can potentially carry hepatitis virus.
Should also use trypan blue staining with your hemacytometer to mark live and dead cells. Dead cells can't export the dye and turn dark.
Alternatively, an MTT assay is a nice way to measure cell viability if you have access to 96 well plates and plate readers. Using a cuvette based spectrophotometer is possible with this assay if you can grow your cells in larger containers, such as 10cm dishes.
The hemacytometer assay can get you total cells and percent of cells that are alive. The MTT assay tells you number of live cells. To get percent of cells that are alive you need a control that represents 100% viable.
Neither of these can tell you much about mitosis specifically, just the number of cells and percent viability.

I didn't realize about dead cells... but would it matter? Sure, it you want a quantitative and really accurate measure on whether the cells are undergoing mitosis, then maybe it matters... But if you are just thinking about whether mitosis is occurring, I think we can still get a reasonable estimate without worrying about dead cells...

The trypan blue staining just gives you some more options for collecting data. You can still count total cells, but with the stain you can differentiate between live and dead. I find it also makes seeing the live cells easier when you have a slightly darker background.

For assaying effect of alcohol on cell growth:
    Prokaryotic Cells

Take ~5ml medium (LB for E.coli) in test-tubes/plastic tubes and add appropriate concentration of alcohol(s) in these.
Inoculate 1% bacteria from a starter culture (OD~0.6)
After different time intervals or a fixed time point take some culture, dilute and spread plate it (for each tube).
Count colonies (CFU)

    Eukaryotic Cells

You can try this in a 6-well plate.
Seed the cells such that they attain 60% confluency in 24 hours
After 24 hours: Change the medium and add the medium with appropriate concentration of alcohol
Wait for at least one division time (varies for different types of cells). 24 hours would be a fine interval for the treatment.
As mentioned in the other answer, you can use MTT assay or Trypan blue to detect viable cells (It would be difficult to differentiate inviable cells from the viable ones by just looking in the haemocytometer without staining)
You can use indirect assays similar in principle to bacterial spread plating; split the cells (if the cells are adherent) and inoculate a small percentage of them into another flask/plate. Count the number of cells in the new flask after 24hours.
You can also do flow cytometry of cells stained with propidium iodide to identify cells in different stages of mitosis.
For yeast you can simply grow them as you would grow bacteria and assess cell viability by either colony based methods or flow cytometry


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How are bones growing, if bones are not connected to the brain?
If the bones are not connected to the brain, how is their growth controlled?
This question is not a duplicate of the question Mechanisms of bone growth, as this question deals with how bone growth is controlled, and not which bone structures or bone tissues are involved.

The developmental growth of bone tissue is hormonally controlled. It is, as far as I know, not under direct neuronal control. Before reaching adolescence, the long bones (mainly in the arms and legs) grow in the epiphyseal plate, the area of the bone where cartilage is formed and ossified on the diaphyseal side, thereby lengthening the bone. The longitudinal growth of long bones continues until early adulthood at which time the chondrocytes in the epiphyseal plate stop proliferating and the epiphyseal plate transforms into the epiphyseal line as bone replaces the cartilage (boundless website). The growth and stop of growth in adulthood is hormonally controlled. Bone tissue growth is controlled by various hormones including parathyroid hormone and growth hormone.
Growth hormone (GH) is secreted by the pituitary, in turn controlled by the hypothalamus in the brain. So although the brain is involved, it is not directly involved, in that it regulates growth, and cessation of it through hormone release. Growth hormone is probably the most important hormone and is released by the pituitary, but parathyroid hormone released by the thyroid, among other hormones, may play a role as well.
Edit: Your question implies bone growth, which at first seemed to point toward developmental growth to me. However, there is also the more dynamic control of bone mass due to the forces that act on them in everyday life, referred to as bone mass accrual. This process is controlled by the sympathetic and parasympathetic system (Bajayo et al., 2012):

This system acts through direct neural innervation of bone tissue and stimulates bone formation when needed (after imposed strain on the skeletal system), but by default stimulates the breakdown (resorption) of bones to salvage its components for other uses (use it or loose it principle). So yes, the skeletal system is directly connected to the brain (with credits to @anongoodnurse).


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Maximum heart rate increase/decrease while physically active
I'm a computer scientist and implementing a heart-rate monitor for physical exercise. While I try to improve my code, I stumbled over the question how fast the heart rate can change within a given time slot.
Let's say someone in rest has a pulse of 60bpm. If he now gets physically active and exploits himself, how much time will it take at least to reach his maximum pulse of (supposed) 200? How long will it take, after hitting that point to slow down his heart rate again?
Or to rephrase the question, so it fit's more to my specific code-problem.
How much can the pulse change (increase/decrease) within a small time-slot of, let's say 8 seconds.
Annotation:
Susan pointed out, that might be dependent on the trainings-state of each individual. If so, what is (might be) the highest possible increase/decrease?
I suppose the pulse increase of a bad trained person might be faster then that of a well trained person, whereas the the decrease of the pulse should be way faster of that trained person.
Annotation 2:
The question was already posted here: How quickly can the human heart rate rise and fall.
But not really answered. The answer here says, the rate can change within one beat. But it does not say by how much it can change, which bothers me. Especially how much it can change within a given period.

Are you looking for a constant? To my understanding, this parameter is highly dependent on age and training status.

I think there will be too many variables for this to get a precise answer - if I were you I'd ask myself whether it is important to track the heart rate so precisely, if it's for exercise then sampling/recording the heart rate every 5 seconds or 10 seconds isn't going to make much difference to the data.


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Bug Identification: Is this small tubular, black bug a bed bug?
So I found this tiny bug on my wall in the bedroom of my apartment. I estimate it is about 3mm long by 1mm wide.

Is it a bed bug?
It does not seem to match any of the pictures I've seen online.
The apartment is very clean by most standards. The only other bug I've seen in here is the odd stink bug.
Northeast coast of USA.

Not a bed bug - some kind of carpet beetle larvae maybe (judging by the hairiness)

Related: What kind of insect can this be? This appears to be just a shell after and insect went through a metamorphosis process

Related: What kind of insect can this be?..., Can anyone help confirm this tiny insect larvae?, How to protect my mounted insect specimens..., Varied Carpet Beetle Larvae, What is the name of the critter depicted...,
What small insect is this?, What bug is this...

I'm going to suggest it is the larvae of a carpet beetle. Initially I thought possibly the Varied carpet beetle because of the lighter patches near the posterior end similar to this picture from the wiki page on this species:

Having said that the geographical range might not be correct so it could be a similar species so I've dug a bit deeper. There are some 120 species in North America, from this link I'd say that the Buffalo carpet beetle is a contender.
Carpet beetles are classified as a pest species:

"larvae feed on natural fibers and can damage carpets, furniture, clothing and insect collections"

Not all bad though, the larvae are also known as wooly bears, how nice.

Well that's good news. Better than bed bugs. Phew! Thanks!

well, woolly bears more often refer to a species of tiger-moth caterpillar: Pyrrharctia isabella


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Estimating RPM to RCF in Methods from Older Papers
I'm attempting to replicate a cell biology method from a 1958 Laboratory Investigation paper. The protocol is for the isolation of an extracellular matrix protein, and a key step is a centrifugation carried out for 2 hours at 2300 rpm. Apparently it was not common practice to list make, model, and rotor size of centrifuges, so I am a little lost as to what settings to use on my own centrifuge to get the same rcf.
Are there any good starting points for estimating the proper settings? e.g. who the major centrifuge suppliers were at the time or what models would be seen as 'standard' for a cell biology lab?

Do they at least list what kind of tubes the samples were in while spun? Knowing the size of the tube would help narrow down possible rotor sizes.

CAn you provide a link to that article.

@user137 Good point! They use "250 mL centrifuge bottles"

@WYSIWYG here is the pubmed link, but I don't know where to find the article online. http://www.ncbi.nlm.nih.gov/m/pubmed/13540204/

I am not sure about what they used in 1958 (perhaps Sorvall). However you may look at recent papers for ECM protein isolation (if that was your objective).
Have a look at this article.
From materials and methods:

ECM protein isolation.
Fibroblasts or A431 cells were removed from the
surface of the culture plate with 2 mM EDTA in PBS for 3–5 min at
37⁰C. Detached cells were discarded, and remaining ECM proteins
attached to the surface of culture plates were washed with the same
solution. Cell removal was controlled under the microscope. After
cells were completely removed, matrix proteins were covered with 5%
acetic acid and incubated at 4⁰C overnight. Then, acetic acid was
removed and exchanged with a buffer containing 125 mM Tris-HCl, pH
6.8, 0.1% SDS, 10% glycerol, 1% DDT, 0.05 mM PMSF, protease inhibitor cocktail (Roche, Germany), and incubated at 37⁰C for 1 h. Proteins
were removed with a scraper. The procedure was repeated three times.
All protein extracts, including acetic acid, were combined and ECM
proteins were precipitated by five volumes of acetone. After
incubation at –20⁰C overnight and centrifugation at 7000 g for 15 min,
the protein pellets were dissolved in an appropriate buffer for
further analysis by one- or two-dimensional gel electrophoresis.
In addition, we obtained a Triton X-100-soluble fraction of ECM
proteins. Cells were removed as described above; dishes were filled
with 1% Triton X-100 and incubated at 37⁰C for 30 min. The extraction
was repeated three times. The following procedure of ECM extraction
was the same as described above. Samples obtained from both fractions
were dissolved in a buffer for one-dimensional (Laemmli) or
two-dimensional (rehydration buffer containing 8 M urea, 2% CHAPS, 20
mM DDT, 0.1% Triton X-100) electrophoresis. Proteins that remained
after Triton X-100 extraction were dissolved in Laemmli sample buffer.

Thanks! That seems like a really good way to get the ECM into a pellet, but the purpose of the centrifugation in the article is actually to keep the ECM protein in the supernatant while letting the tissue it is digested from pellet.

@Chastain The tissue is removed prior to protein precipitation.


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Does DNA analysis allow determining amount of chromosomes?
Nowadays it is possible to sequence the DNA of extinct species, such as the Neanderthals, the Denisovans, and others.
Is it possible to determine, solely from the sequenced DNA or from known bone fragments, how many chromosomes the individual (or the species represented by the individual) had?

This depends completely on the quality of the DNA. Since each chromosome is essentially a very long strand of DNA, breakages and missing sections are very common in extinct species due to degradation over time.
If a full DNA read is absent, no determination of chromosomal number can be performed.
Assuming a full read (covering all breakages) of the DNA is present, the telomeres of each chromosome can be found, and since chromosomes usually only have one set of telomeres each, this may be useful for chromosomal number determination.
Caveat 1: Chromosome 2 (human) is an example of how this method may fail, since a recently fused chromosome will still possess the tandem repeats characteristic of telomeres.
Caveat 2: Telomeres may vary in length due to the age of the cell, as well as be broken in multiple regions. Due to the tandem repeat nature of telomeres, it is nearly impossible to tell these different states apart experimentally.

If you had full coverage (I'm not sure how common this is), wouldn't you then be able to assemble across relict telomeres, such as in Chr 2? Presumably this was how they worked out the human Chr 2 was one chromosome in the first place? Similarly, I suppose another option (assuming full coverage) would be just to assemble and count how many sequences are produced (over size x).

Currently, detection of chromosomes seems to still be largely based on karyotyping and FISH. Relic DNA is usually highly fragmented on its own despite having full reads (100% coverage), and if the DNA happens to break between two telomeres in all the shotgun sequences taken, it would be nearly impossible to tell one from the other.

Yes, that makes sense. However, wouldn't this imply that the fragmentation would also prevent full detection of telomeres from sequencing? i.e. there might be fragmentation within telomeres, or joining telomeres to non-telomere regions?

Yes, it would. This is a nontrivial problem in sequencing, especially for tandem repeat regions, and the fact that telomere lengths change with the number of cell divisions only compounds the issue further. In fact, your point makes a good addition to the answer.

Thanks. One other thing I thought of would be to use synteny with close relations, but I guess that's cheating.


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Skin porosity in glans penis when erect
(Apologies if this is a too weird/inappropriate question in this forum. I only thought that I ask it since it happens to be part of human life.)
The skin on a human typically blocks many substances that could be harmful for the organism. One area that is not covered by skin, however, is the "glans penis" (the tip of the penis).
Considering that the surface on this area seems to become more stretched during erection, it would look like erection causes the tip to allow more substances to pass through than otherwise.
Are there any studies about how erection affects the porosity in this area of the body?

What kind of porosity are you thinking of? Do you have an example of a substance you think would pass through the glans in larger amounts? Substances normally exit the penis through the meatus, not the glans.

@March Ho, I would think that if porosity is increased, it is increased for all substances. Why would it not?

I think better title would be Dynamics and Histological Characteristics of Glans Penis. Like AtlLed Says the porosity is just one factor.

So if you're interested in the detailed anatomy of the glans penis, I recommend this as a nice article to go to after you've checked general references.  Opening two sentences are worth quoting here:

The human glans penis is covered by stratified squamous epithelium and
  a dense layer of connective tissue equivalent to the dermis of typical
  skin. Rete ridges of the epidermis are irregular and vary in height
  depending on location, age, and presence or absence of a foreskin. The
  papillary layer of the dermis blends into and is continuous with the
  deep connective tissue forming the tunica albuginea of the corpus
  spongiosum of the glans penis.

And as pointed out in The Last Word's answer, foreskin covers the penis if you look at humans in an evolutionary scale of time.  The exception being an erection, which should lead to foreskin retraction (at least at some level).
So the question then becomes if the squamous epithelium and connective tissue are more prone to infection than the dermis. First, it's worth pointing out that the epidermis is not equally protective across the body. Think about the skin on your face vs. the bottom of your foot, or vs. a baby's.
I think comparing the glans penis directly to the surrounding tissue -- the prepuce (foreskin), fossa navicularis, and urethra -- makes the most sense. To make a plumbing analogy, is it the pipe (urethra), the fitting (glans penis), hole (fossa navicularis), or insulation (prepuce) that is most prone to infection?
Well, first we need to look at our pathogen, "what's doing the infecting?" For HIV, probably the urethra, but if you're interested in bacterial infection, the best things to look into are balanitis and balanoposthitis.  That would be the inflammation of the glans or glans & prepuce. Here is a good review on infectious causes.
Unfortunately, there is going to a strong sampling bias due to circumcision rates.  Also most studies are not going to be asking the the specific question we are trying to answer here. And it would be hard to prove that infection occurred during the erection, not immediately before or after.
I have found little evidence of bacterial infection of the prepuce but not the glans penis.  I do know of cases of the reverse however, which may indicate that the glans has a greater infection rate.
However, I think it's worth pointing out the difference is not likely to be drastic, and that the surface of glans has many similarities to skin.  For example, it has an epidermis and dermis. It stretches quite well, and I think dryness will be an issue far before porosity.

That is a pretty good answer, as I was curious about overall porosity (or "the level at which the surface of the tip may allow anything to pass through", for lack of better word).

@x457812 If you're interested in more of the bio-physics, I recommend reading up on the elastic fibers of the dermis.  Incidentally they are quite abundant in the glans penis.

I do not think that it is a correct statement to proclaim that the "glans penis" is uncovered by skin. This would be true only if the penis is circumcised. Under foreskin section of this article it is clearly stated

The foreskin in the adult male either partially or completely covers
  the glans penis (reference).

So, it would be safe to say that unless erect, the penis is completely protected by the foreskin against the entry of foreign particles (reference). The second part deals with the porosity of the penis while erect.

Some males, well endowed with a generous foreskin, have the glans
  fully covered even when the penis is fully erect (reference).

I couldn't find any studies that compared the entry of bacteria in an erect or a flaccid penis but I would say that even if circumcised, your chances of getting an infection without indulging in unsafe sexual practices remain quite slim. Of course, in case of cuts or abrasions on the penis, chances of infection increase.

Diabetes is actually a good way to get an infection w/o risky sex, just as an aside.

Diabetes $\to$ penile ulcer $\to$ infection / STD. Risk factor even poor hygiene then. http://clinical.diabetesjournals.org/content/23/4/191.full

Thanks for pointing that but I did say that the chances of contracting the disease were slim and not non-existent. There might be other reasons too and not just diabetes. Nothing to down-vote over.

@TheLastWord Don't know why this was on my notice so much later, but I actually up voted...


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Why does weight loss lower blood pressure?
I have read that weight loss is an effective lifestyle modification for people with hypertension, and systolic pressure may be reduced by up to 1-2 mmHg for every 1kg of weight lost.
What is the physiological reason for weight loss reducing blood pressure or weight gain increasing it?  Please provide a physiologically detailed response rather than simply saying that more weight means the body must work harder to pump blood.  I understand this but I want to know the mechanisms of how the body detects the increased weight and adjusts the blood pressure accordingly.  Thanks!

As someone in the health-care field, it's great to see someone who wants to know more than the surface of things. I would like to answer this question, but I don't want to repeat stuff that you already know. What did you find out when you researched this? Thanks.

Weight gain increases blood pressure, the reason for this process is due to the effect of hormone called Leptin.

Leptin is made by fat and circulates in the bloodstream to reach the brain, where it acts as a signal for energy reserves, adjusting both energy expenditure and the sensation of hunger – hence it is sometimes referred to as the ‘satiety hormone’.
The group showed that some obese people who were lacking the hormone leptin because of a genetic disorder had low blood pressure despite being very heavy. This was also the case for people lacking the gene for the leptin receptor in the brain, meaning that the brain was unable to respond to the hormone.
Reference

The team lead by Professor Michael Cowley, Monash University, Australia, in collaboration with Professor Sadaf Farooqi, from the University of Cambridge, UK suggests that the leptin signalling is necessary for obesity-induced increased blood pressure. The clinical studies in severely obese humans showed that these observations are relevant to humans.

Professor Cowley said: “High blood pressure is a well-known consequence of obesity. Our study explains the mechanism behind this link, showing that leptin, a hormone secreted by fat, increases blood pressure.”
Professor Farooqi, from the Wellcome Trust-Medical Research Council Institute of Metabolic Science added: “We now know that leptin regulates both our weight and our blood pressure through its action on the brain. Targeting this action could offer a useful way of helping people fight obesity and associated problems such as high blood pressure and heart disease.”
Reference

It is thought that Leptin's only task is to activate the sympathetic nervous system connected to the brown fat and there by directly burns energy. But it is also behind the activation of sympathetic nervous system of heart and kidney, thereby increase the blood pressure.

Genetic and drug experiments in mice, they have pinpointed an area in the mouse brain that increases blood pressure when it is exposed to high leptin levels.
This region is called the dorsomedial hypothalamus, and is thought to be involved in controlling energy consumption. Their findings show that high levels in leptin do indeed boost blood pressure, via this brain region.

Reference
http://ndt.oxfordjournals.org/content/15/8/1115.full.pdf+html


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Why do we still have genetic disorders that show anticipation?
Anticipation whereby symptoms of genetic disorders occur earlier and with more severity as it is passed from one generation to the next.
So wouldn't these inherited diseases over a few hundred generations affect offspring before they can reproduce and thus shouldn't these diseases like Huntington's disease no longer be with us today?
Or are most of these genetic diseases generated through sporadic mutations at a high enough rate to persist?

I can think of 3 explanations (not mutually exclusive) for the maintenance of important genetic disorders that prevent the sick carrier to reproduce.

Following what you said, the frequency of a given allele in a population is influenced by selection, drift, migration and mutation. Some disease present at low frequency can typically spontaneously de novo appear in a population. This is typically the case of cancer and trisomy 21 where new mutations (mutation in the broad sense) likely explain a big part of why such disease do not disappear through time.
Many genetic disease are carried out by recessive alleles. In consequence, only homozygotes for the recessive allele express the disease and the disease can persist through drift. Note the interesting case of hemophilia and Malaria resistant where the heterozygote actually has higher fitness than any homozygote (heterozygote advantage), particularly in regions where there is a high prevalence of malaria. In this case, the disease is not washed out of the population not only due to drift but also due positive selection on the heterozygotes.
Many so-called genetic disease actually have an important environmental component. For the Huntington's disease, the carrier of the autosomal dominant mutation does not necessarily express the disease. From wikipedia:

The disease is caused by an autosomal dominant mutation in either of an individual's two copies of a gene called Huntingtin, which means any child of an affected person typically has a 50% chance of inheriting the disease.

As a result the Huntington's disease can still segregate thanks to drift in the healthy heterozygotes.

I don't see the environmental component in the final part of your answer, the quote doesn't seem to mention an environmental factor, and I won't consider luck to be an environmental factor.


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Can plants directly use sulfuric acid?
In the explanation of the sulfur cycle, it is often said that sulfur moves from the atmosphere to the ground by acid rain in the form of sulfuric acid. Can plants directly use sulfuric acid to assimilate sulfur?

Plants have sulfate transporters which they use to assimilate sulfur. Since sulfate is the conjugate base of sulfuric acid, this could be construed as a "yes" for your question. Sulfuric acid would be present in its conjugate base form at physiological pH values.
However, it would be unwise to water your plants with sulfuric acid, as many plants have an optimal pH range which will quickly cause death when sulfuric acid lowers the pH of the soil below that range. As a result, areas afflicted by acid rain may require treatment with alkaline limestone to resolve this issue.

Not just the pH. Sulphuric acid is also a strong dehydrant

I would presume that since the question is talking about acid rain, we don't mean concentrated sulfuric acid.

Yes.. Didn't notice that..


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How to validate the regulatory interactions inferred from gene expression data?
My algorithm learns regulatory interaction between genes using Bayesian Network approach from gene expression data. After the algorithm has converged to a network of interacting genes, how to validate that the interactions are correct? I have used Lung Cancer dataset from NCBI GEO with ID: GDS2771. Also, how to get the set of genes responsible for a disease (in this case lung cancer) , and how to quantify their expression levels as over or under expressed?

this may need some more detail of the model you use, for example, the model could have just randomly picked 10 genes and said they are interacting - though I assume it's doing something a bit more complex :)

And yes I concur with GriffinEvo that you should first make sure the algorithm was used correctly;the parameters rightly adjusted etc.

Some important parameters of the algorithm are the discretization thresholds for classifying genes expression values as over, under or normal expressed. I am also quiet unsure about what should be the threshold values, and the other important parameter is atmost how many regulators can be there for a gene? Any idea about how to sort that out?

I have tagged your post as bioinformatics too. If your query is related to model optimization then clarify that in the question.

You can validate the interactions by knockding down (KD) or overexpressing (OE) a gene and checking the change in expression levels of the downstream nodes. You can do this in a high throughput fashion using microarray or RNAseq. For protein you can do an LC-MS. However this method cannot help you in:

Differentiating direct vs indirect interactions
Finding regulation in case of loops and other non-linear interactions in the network

Loops are tricky but sampling at multiple time intervals can let you know if oscillations exist or not. For most usual cases this approach works out.
Usually this is followed by another round of validation using a relatively low throughput but sensitive technique such as

Real-time PCR (KD vs OE)
Western blots (KD vs OE)
Reporter assays (KD vs OE) would detect direct interactions. For e.g. possible promoter for a (Transcription Factor) TF (upstream of gene-Y) is used to express GFP to see if GFP responds to the TF; thereby validating the effect of TF on Gene-Y via the promoter.

In some cases you may have to do ChIP-seq to find out if a gene has binding sites for a TF in its promoter/enhancer. You may also use predictions for TF binding sites. For finding regulation by miRNAs you can see this post.
For finding complex dynamics such as pulses and oscillations you have to collect time-course data.

how to quantify their expression levels as over or under expressed?

For that you first need to define your control (up/down regulated wrt what?). Having done that you can compare the expression and use right statistical tests to check differential regulation. If you have just one sample then most tests won't work. For RNAseq,  EM algorithms are used which use a bayesian model to obtain likelihoods and p-value (I have used cufflinks and eXpress). Then a FDR correction can be performed when comparing the test vs control. I am not very sure about algorithms used for comparing LC-MS data for proteins.

well i am not doing any wet lab experiments, i am using machine learning techniques on expression data matrix. Then how would i knock down or over express a gene's expression pattern??Is it by setting low values for knock down and high values for over expression and then check how the regulatory interactions change for that gene?

@Aparajita You said "validate".. You have to do wet-lab experiments to validate. Your model can only do predictions from a given data. You would need to test if it predicts correctly, a control experiment. If not you should update your model parameters.