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Why does one combine PCR and cloning as ways for amplification of sequences?
Why does one combine PCR and cloning as ways for amplification of sequences? Don't they produce the same result? I was reading the paper https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1864885/ and got confused by the following passage:

Cloning and Bisulfite Genomic Sequencing
Each bisulfite-converted DNA
  sample was subjected to PCR by primers that did not discriminate
  between methylated and unmethylated sequences, using a GeneAmp PCR
  core reagent kit (Applied Biosystems). The primer sequences are listed
  in Table 1, and reaction conditions are listed in Supplemental Tables
  1C and 1D (available online at http://ajp.amjpathol.org). Each
  subsequent PCR product was TA-cloned into pGEM-Teasy vector25
  (Promega) for transformation into Escherichia coli strain JM109,
  according to the manufacturer’s instructions. Clones were picked
  randomly and colony PCR was then performed using vector primers T7 and
  SP6 to amplify the cloned inserts. Cycle sequencing was performed
  using BigDye version 1.1 (Applied Biosystems) and an automated
  capillary DNA sequencer Genetic Analyzer 3100 (Applied Biosystems).
  The sequences obtained were aligned and compared using SeqScape
  software (Applied Biosystems). The completeness of bisulfite
  conversion was first confirmed before scoring. The CpG sites sequenced
  as cytosine or thymine residues were scored as methylated or
  unmethylated, respectively. The methylated site frequency was
  calculated for each sample by dividing the total number of methylated
  sites over all cloned CpG sites.

Can someone comment on what purpose the cloning serves when the amplification is already done by PCR?

There are several reasons to clone a PCR product but the main reasons include expressing the product and maintaining the library inexpensively.
In the study you mentioned, the cloning and transformation is apparently done for obtaining single clones (from single colonies).

Clones were picked randomly and colony PCR was then performed using
  vector primers T7 and SP6 to amplify the cloned inserts. Cycle
  sequencing was performed using BigDye version 1.1 (Applied Biosystems)
  and an automated capillary DNA sequencer Genetic Analyzer 3100
  (Applied Biosystems).

Since the original PCR would have a mix of different sequences, cloning is done to separate them out for the ease of studying them by sequencing. If they don't separate the sequences, they would have to use NGS (or more expensive methods like PacBio for longer reads). They have used Sanger sequencing. This article was published in 2007. At that time NGS was not as cheap as it is today and was hence not used by everyone. Also, the NGS machines of that time had even smaller read lengths (~40 for Solexa/Illumina GA and ~75 for GA-II). Considering these, Sanger sequencing may have been preferable to the authors of this paper. However, as I mentioned before, Sanger's method cannot be used for sequencing pooled samples; you need pure templates or else there will be mixed signals and base calling would be inaccurate.
(See the example chromatogram below: look at the position with the Y which has mixed T and C signals. It is not from a pooled sample, though).

Therefore cloning, transformation and colony picking was necessary.
Moreover, in many cases picking individual clones would be necessary for performing functional assays to associate phenotype with genotype.

Thank you for the answer. I am unclear about some points you made.
Why would they need to use PacBio? The initial PCR product is still short enough for any short read sequencing method.
I get the relationship of phenotype to genotype, but this is not the case here. Isn't the cloning just a step adding a bias to the methylation ratio quantification?

@CindyAlmighty You need to sequence single DNA molecules. That can be done using any NGS technology but not Sanger sequencing. However, for many of them the reliable read length is <300nt. With PacBio, you can sequence longer reads. Their reads are indeed smaller so they don't need PacBio. But, note that this article is from 2007. NGS was not that widespread and cheap at that time. There could be an amplification bias between methylated and unmethylated sequences but that would be there in the PCR product stage, itself.

I understand the NGS vs Sanger vs PacBio. I am unsure how it figures in this problem - how is the molecule shortened by inserting cloning between two PCRs.

@CindyAlmighty it is not shortened. This paper is from a time when NGS was not common. Moreover, Sanger sequencing can give you up to 1kb of decent quality read. However, with Sanger, you cannot sequence a pooled sample. It would just cause interference.

Oh, now we are getting on the right track I think. Your help is excellent, as it led me systematically to a solution. I think this is the exact point I was looking for - Sanger cannot sequence pooled samples. But now that I think about it, it is not interference, but we wouldn't be able to phase methylations. Do you agree?

@CindyAlmighty not just methylation. If you have multiple templates in a Sanger reaction then the chromatogram would have mixed up signals and base calling would be inaccurate. In case of same template sequence but dith different methylation, there will be two signals (after bisulfite treatment) at the methylation site (C and T), the intensities of which will depend on the frequency of the two states. However, I guess it would be difficult to calculate the frequencies accurately from the mixed chromatogram peaks (never tried it so can't say conclusively).


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Feeling of spicy
I have done a survey on my friend
When everytime they eat something spicy, They will eat ice or drink icy water. First, Mostly they feel nothing but a cool sensation. However when they finished, they feel spicy again.
Sometimes, they will drink warm mill or hot coco. Now everybody feel extremely spicy at first and less spicy afterwards
My question is:
1) Why don't I feel spicy when drinking icy water or eat ice?
2) Why do I feel spicy after the action at 1) ?
3) Why do I feel extremely spicy when drinking warm milk or hot coco but less spicy afterwards?

What kind of spice? Chili-based flavours?

Yes, mostly chili and curry

The spicy feeling essentially is the feeling of heat and pain. It is caused by the molecule Capsaicin (https://en.wikipedia.org/wiki/Capsaicin) binding to the ion channel TRPV1 (https://en.wikipedia.org/wiki/TRPV1), activating it.
You can temporarily get rid of the pain by cooling (as you would with any other injury) - hence the effect of ice.
Unfortunately, this does not get rid of the cause of the pain, i.e. the molecule bound to the ion channel. Capsaicin is not very water soluble, but only fat soluble. This is why drinking milk helps: it contains microdroplets of fat, which can solvate the Capsaicin, which then can get washed away from the "pain receptor".

What is cooling doing exactly to the perception here? Any references that would support your claim?

You can't really say pain.. These channels are sensitive to heat and are involved in temperature perception (also nociception). When capsaicin opens these channels you get the feeling of heat.

@WYSIWYG "nociception" is the encoding and processing of harmful stimuli in the nervous system, which, at a certain threshold, is interpreted as pain.

@MattDMo but TRPVs are also involved in normal temperature sensing and do not necessarily activate pain pathways.

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Expression of plasmid genes
Are plasmid genes always expressed? If so, then isn't a bacterium wasting it's resources in expressing genes (like antibiotic resistance) which are not required in "normal" conditions?
If not, then what triggers bacteria to express genes of recombinant plasmids? Can a bacterium survive in "normal" conditions if it is deprived of all the plasmids?

What makes you think that genes on plasmids are not required in "normal" conditions?

@terdon Because (as far as I know) mostly plasmids contains genes like antibiotic resistance which are useful under some conditions.

Not really, those are simply the ones we tend to add when cloning.

It would depend of the plasmid, the genes it contains and the promotors those genes have. Basically, regulation of extrachromosomal genes follow the same patterns of the rest. Bacteria, Archaea and some other organisms that can have plasmids will express the genes if the promotors of those genes are constitutive, or if they trigger by conditions that are present in a given moment. The degree of expression would be a function of the characteristics of the promoter and the number of copies of the plasmid. Finally, the number of copies of the plasmid would depend of its size and the characteristics of its replication origin.
Organisms can loss the plasmids if doing so don't suposse a negative effect (this is a big problem in industrial microbiology, since the recombinant strains may be unstable and reduce its productivity). In laboratory, a plasmid containing resistance genes towards an specific antibiotic would remain stable as long as this antibiotic is present in the media. The characteristics of its replication origin also play a big role determining the stabilty of plasmids. You can even select for the loss of plasmids, take the example of URA3 in Saccaromyces (not a bacteria, but the mechanisms are the same), wich can be used as a negative selection factor if the media contains 5-fluoroorotic acid.
So there's no particular advantage in expressing plasmidic genes all the time. When that happens, actually there exist an evolutionary pressure against the presence of the plasmid, and thus it trends to dissapear. Bacteria can survive without plasmids (with the exception of some that carry megaplasmids that acts more than little chromosomes. In some of this cases, the plasmid may contain genes for important methabolic pathways and other key elements of the cell, thought if the genes they carry are very importants, like polymerases or ribosomal RNAs, the term minichromosome is prefered). However, plasmids may contain genes that confer an important advantage to the population (like in presence of an antibiotic), and if so the plasmid spread. If at some point the ecological pressure cease, the plasmid would turn unstable again. Note that it's not impossible to have horizontal genes transfer between plasmid and chromosomes, and plasmids (alongside viruses and foreign transformed DNA) are important sources of new genetic material.

So to reduce the loss of recombinant plasmids, are bacteria kept under a selective pressure in which the plasmids would give advantage?( In Industries)

Yes. For instance, you can use auxotrophic strains that packs the enzymes required for prototrophy in the plasmid.

Could you simplify what you said in the previous comment ? I don't understand the terms. Thanks!

You can use a strain than cannot sintetize a certain compound and needs it to be present in the medium. If, alongside what genes you want to insert in your microbe, you include genes that allow them to produce that compound, the bacteria won't lose its plasmid as long as that compound isn't present in the media.

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Is the function of adjacent genes correlated?
Do genes that occupy a similar locus on the genome have correlated function, specifically in human beings? It is my understanding that adjacent genes are inherited together, and so location plays a role there. However it terms of function, I don't know to what extent location plays a role. Furthermore, if say two adjacent genes have the same expression, does this necessarily mean that their function is correlated, or is that interpretation stretch?

Trivial and maybe a bit tongue-in-cheek comment: that cannot be true, otherwise any gene in the genome would be correlated to its neighbour, hence all of the genes would be correlated to each other :)

@nico But it is true to some extent, at least when looking at co-regulation.

That only says they can't be perfectly corollated. Otherwise corollation would drop off exponentially with distance.

@Konrad Rudolph: I know, I was just joking. Anyway distance on genomic map does not mean distance in space...

You might look into the homeotic genes. They are involved in patterning embryos during development. Interestingly, in vertebrates especially, their pattern of expression on the anterior-posterior axis of the embryo (and the proximal-distal axis of the developing limb) is the same as their order on the chromosome. They are said to be colinear, though no one really knows why.

In bacteria, this is often true.  This is because more than one gene is often transcribed onto a single RNA.  This grouping of genes is called an operon.  It is usually true that these have a related function because they are being translated to protein in very much the same proportion - a convenient way to regulate the function as a whole.
Once you get into eukaryotes this is no longer true (except for v. rare cases most of which are viral genes), one mRNA transcript contains just one translation region.  This is true even for yeast and other single celled organisms.  Gene regulation can be correlated, but the relationship on the genome has little to do with it.
There is some importance to the genomic relationship of two genes because of the crossing over that occurs in meiosis, but this is more of a relationship that is important in speciation and evolution, it doesn't have any recognized importance to how the genes act within the eukaryotic cell.

A group of tightly linked genes that are involved in similar molecular pathway is called a supergene.
For the pleasure to formulate a slight opposition to @shigeta's answer, I will give some examples of supergenes in eukaryotes.

In Primula, heterostyly is controlled by a supergene.
In Papilio memno, mimicry is controlled by a supergene.
In some species of ants, some social behaviour is caused by a supergene.
Sexual chromosomes (and this is quite common) can be considered as supergenes.

Globally speaking, every locus that is under antagonist sexual in different sex/castes/ecotype/whatever is likely to start forming a supergene as soon as another locus that has antagonist effect appears in its vicinity because the presence of two such genes on the same chromosomal region will select for arrest of recombination.
But of course, those represent exceptions (however common these exceptions might be) but in general, I don't think you should expect that adjacent genes would have similar functions.


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Breaking a gene during recombination
I just started reading about recombination frequencies of genes and related stuff, and can't find an answer to this (possibly naive) question.
Can recombination possibly "kill off" a gene ?
To be more specific, say a gene is located at position $x$ to $y$ on some chromosome.  Then, we are so unlucky that recombination decides to cut off the chromosome at location $x + (y - x)/2$, right in the middle of the gene.
So both halves will get recombined with the other halves of the gene on the homolog chromosome.  If the allele on this chromosome was different, could it result in destroying both alleles of the gene ?  Is there something that prevents this ?

Yes, you could imagine a situation where two functional alleles could produce a recombinant which was non-functional.

chromosome 1 has A and B at positions x and y - functional
chromosome 2 has C and D at positions x and y - functional
Recombination between positions x and y produces A/D and C/B versions of the gene. Either or both of these could be non-functional.

Nothing prevents this from happening, but natural selection will act on the recombinants.


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miRNA analysis just using BLAST against mirbase.org
I have sequencing data (Illumina). Library prep was focused on short ncRNAs. I would like to identify human miRNAs. Do you think it is feasible to simply BLAST against a current version of mirBase and filter the output for mature, human miRNAs without using bowtie/tophat against hg19 first?
Thanks

You don't need to use TopHat but it is better to use bowtie instead of BLAST. First of all you need to get rid of the adapter sequences (along with other processing steps prior to alignment).
Now there are two aspects here:

miRNA quantification
miRNA discovery

First one is relatively straightforward whereas the second one requires you to perform additional tests such as prediction of stem loops etc. There are published software that can handle both the aspects (mirDeep, miRScan etc). See this review for details on different miRNA gene finders. I have used miRdeep and it uses bowtie-1 to align.
BLAST would work but you have to set parameters which are suitable for small sequences (increase E-value cutoff, reduce word size etc). Moreover, BLAST does not have a cutoff option for the number of mismatches and the length of alignment (it only has a post alignment filter for percentage identity).
I also personally prefer bowtie because it has something called as n- alignment mode. In this mode the entire read is divided into seed and non-seed regions. You can specify the length of the seed region and the mismatch cutoff. Since for miRNAs the seed region (bases 2-8) is critical for its function, I generally set the seed mismatch cutoff to zero while allowing one or two mismatches in the non-seed region (note that in bowtie the seed always starts at 1).
In general, I would advise that you should go for miRdeep instead of BLAST. However, miRdeep doesn't straight away perform an alignment against the mature sequences. It maps the location of mature sequences in the pre-miRNA sequences (stem loops) and then aligns the reads to the pre-miRNA sequences. If the location of reads has a significant overlap with the mature region (you can adjust the window) then the read is considered as a valid miRNA.

Thanks alot. I would give bowtie a try first. So i set -N to 0. What value do you recommenf for -L (length of the seed substrings to align during multiseed alignment)?

@twckr you can set it to 10; I use 10. I set -e to 80. However, this is for the fasta file of the reads. The e option is for the max quality cutoff for mismatches. For fasta files the default quality is 40; so 80 means 2 mismatches. This would not be true if you use fastq files

I think a few mismatches in the miRNA seed might be tolerated regarding miRNA function, depending on their position.

@bli Seed is quite important. miRNAs are classified into families based on seed sequences. So, if your seed is different, it technically becomes a different miRNA. However, depending on the conditions and context seed mismatches (not exceeding two) may be tolerated.

Using bowtie I get quite different results compared to BLAST. Even setting the -L option to 22 (which should avoid any mismatches as far as I understood) I find significant differences in the results of both programs. Do you have an explanation for this finding?

@twckr You need to show me the files otherwise I cannot give an explanation. If the files are huge then just paste a section that shows the difference.


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Does a cell suspend or exit cell cycle at G0?
In an exam, there was one question which asked whether the cell exits or suspends cell cycle at G0 phase.
I answered that it exits cell cycle but the official answer key says it suspends cell cycle.
I marked exit because a cell in G0  undergoes differentiation and maturation. Is there a difference between the two terms?

The answer is exit. I had given this exam this year and marked the same answer as yours and its correct.

and also if you wanna know the difference between the two words , a similar terminology has already been answered on SE. Visit - https://unix.stackexchange.com/questions/265911/what-are-the-differences-between-kill-suspend-and-terminate-of-a-process

I've always heard of it referred to as exiting and re-entering the cell cycle. Of course some cells do not re-enter. This seems to be a matter of semantics. I don't think it's prudent or even sensible to make an exam question based on what verb to use to refer to the process of delaying or avoiding entry into the G1 phase of the cell cycle. Mandatory reading.

It is actually suspend and yes the words do differ. This is because the cells that enter the G0 stage is not actually exiting the cell cycle because when situation demands it will divide. It is metabolically active and therefore the word suspend suits better

Please add some references so this doesn't get downvoted :)

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Why can't gametes of one species fuse with that of the other species?
I have read that gametes of one species cannot fuse with that of another? For example the sperm of a dog can't fuse with the ova of a cat or a horse?

Note that it does happen and hybrid offsprings are born in case of some pairs such as lion-tiger, donkey-horse and camel-llama.

But its only some why not all ?

Do you have any initial ideas on how to explain this?

You should also narrow down your question such that it is about some few species. Or at least you can restrict your question to different mammals or even better, organisms of different genera but same family; like Rats and mice or gorillas and chimpanzees, etc.

The implied subject of your question is the prezygotic barrier and is one of the possible determining mechanisms of speciation, the others being temporo-spatial (meaning different time or place), behavioral, and mechanical (the organisms don't fit together, physically).
Fundamentally, this means that gamete cells of each organism are chemically incompatible. While the details specific to each species vary, we can take a look at a few examples to illustrate the point.
In order for eggs of Arbacia Punctulata to attract sperm of the same species they secrete a specific chemoattractant peptide we call Resact (a selection of different species' chemoattractants can be found beyond the former link), which is adapted to diffuse well in seawater. Sperm then follow the chemical gradient in the direction of the egg, which is called positive chemotaxis. Resact doubles as an activating peptide for that species' sperm. Pycnopodia helianthoides starfish, which also reproduce through broadcast spawning, use an attractant we call startrak. Internally fertilized animals use roughly the same mechanism to guide sperm through the reproductive tract, though with different chemical adaptations specific to their evolutionary history.
Once the sperm reaches the egg, an acrosome reaction leads to the fusion of the two gametes into a potential zygote (for the reason why I say potential, see  Speciation by polyploidy). The chemistry of this reaction also varies between species.
In summary, the reason is this:

A change in gamete chemistry (chemotaxis, activation, reaction, adhesion) alters the chances of successful fertilization between one or more members of the same species.
Thus, the altered group reproduces more often within itself than it does with the parent group, allowing it to grow in population.
Changes in the altered group further reduce the chance of success with the parent group.
Eventually, the chances of the altered group successfully mating with the parent group are practically zero.

This process is, of course, typically assisted by one or more of the other aforementioned mechanisms. Where two species are capable of producing offspring and successfully do so, you get hybrid speciation.
Further reading

Study.com - Speciation II: Prezygotic Barriers
Recognition of Egg and Sperm
Egg and sperm recognition systems during fertilization

This example applies to only one organism (or few). OP is interested to know why this does not happen generally.


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Why is it often the case that an enzyme is favorable only towards one direction of a reaction and not both directions?
In class when we're studying enzymes like amylase or protease it only works well when you're using it to break down compounds like polysaccharides.  I'm just curious but why is it not possible for enzymes to work efficiently in a reverse reaction?  I mean a formula like
$\ce{amino\ acid + amino\ acid + energy<=>H2O + protein}$
does imply that our reaction can go both ways , right?  But why is it that the enzyme favors the catabolic reaction?

An enzyme does a specific task. Sometimes there is one that does the opposite task. For example, for the protease that cleaves a protein at a specific site, there is the ribosomal complex that builds proteins amino acid by amino acid. Enzymes are generally too reaction-specific to perform both forward and reverse reactions.

@MattDMo - But enzymes merely enhance the speed in which equilibrium is reached? the fact that the reaction keeps on going is because of the fact that the product is being taken away, or because substrates continue to being added (I hope that last part is proper English but you'll likely get my point  :-).

Enzymes only alter the rate of a reaction, not the equilibrium. Since Keq=kf/kr and Keq is constant, an increase in forward rate (kf) requires a corresponding increase in the reverse rate (kr). Therefore, enzymes do catalyze the reverse reaction.

Reactions have their set equilibrium constants, which are determined by the free energy of the reactants involved, and this cannot be changed by catalysts, including enzymes. Let's look at your example of peptide bond formation between two amino acids A and B,
A + B + energy $\leftrightharpoons$ H$_2$O + AB
This reaction might proceed in both directions; the rates of forward and reverse reactions depend on the free energy of A,B and the dipeptide AB, as well as how much "energy" we are talking about in the left-hand side. Let's ignore the energy term to start with, and just consider
A + B $\leftrightharpoons$ H$_2$O + AB
As it turns out, this reaction is not favorable: the $ \Delta G$ is about 10 kJ / mol (it depends a bit on which amino acids we're talking about). So this reaction goes in the reverse direction; dipeptides actually spontaneously decompose in water. But the rate of this reaction is very slow, because the peptide bond is quite stable. We say that there is an "energy barrier" between the substrates and products. Catalysts, including enzymes, lower this barrier, which increases the rate of reaction in both directions. It is physically impossible for enzymes to change the equilibrium by catalysis alone. There are plenty of enzymes that catalyze the above reaction, causing peptides to break down rapidly (peptidases, for example trypsin).
But enzymes don't just provide catalysis: an important role of enzymes is to couple two (or more) reactions together, so that a favorable one can drive an unfavorable one. This is how we obtain the "energy" term in the first reaction. The most common mechanism is to couple the unfavorable reaction to ATP hydrolysis,
ATP + H$_2$O $\leftrightharpoons$ ADP + P$_i$
which itself is highly favorable ($\Delta G$ around 40-50 kJ / mol). The coupled reaction is then
A + B + ATP + $\leftrightharpoons$ AB + ADP + P$_i$
which is now both favorable (due to ATP) and fast (due to catalysis). This is pretty much what ribosomes do (well, the actual mechanism is much more complex, but the principle is the same).
So, catalysts cannot change the equilibrium of a given reaction, but enzymes can couple reactions together to come up with something that is favorable. This is a central theme in biochemistry, allowing cells to drive reactions in the desired direction; but there is always a "price" to pay, often in the currency of ATP.


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Heterochromatin v Euchromatin. Which is more abundant?
So I was just reading that whether heterochromatin or euchromatin is more abundant in a particular human cell depends on how active that cell is. But considering that most of the 25,000 or so genes in the human genome are transcriptionally inactive in any given cell, how is it possible for cellular activity to affect the chromatin structure to a degree that significantly alters how a nucleus looks on microscopic images? Since, after all, whether the cell is active or not will only affect little of the chromatin.
And since most of the genome is inactive, shouldn't it be in a heterochromatic form, and thus most of the chromatin in any given cell will be heterochromatin?
(I know this is not true, but I was wondering why)

I think whether DNA is in the heterochromatic or euchromatic stage depends on the stages of a cell's life cycle. There is a page on wikipedia with a good comparative image: https://en.wikipedia.org/wiki/Chromatin#/media/File:Chromatin_Structures.png    I think to answer your question though, it varies?

I dont think the forms of chromatin are stages but are rather states that depend on the transcriptional activity of the cell. And yes it does indeed vary but my question was how come such variation affect the overall structural conformation of the chromatin since most of it is inactive anyway.

Percentage of euchromatin varies between cell types and organisms. It has been shown that upto 88% of the human genome is transcribed; a phenomenon called pervasive transcription [1]. Highly specialized cells may have a lower percentage of transcribed regions and in females one entire X-chromosome is silenced (some regions in the silenced-X do show transcriptional activity).
Euchromatic regions not only constitute the geneic regions but also regulatory intergenic regions such as enhancers, locus control regions (LCR), silencers etc. It has been found that ~97% of these elements fall in the DNAse hypersensitve (DHS) region of the chromatin [2].
DNAse hypersensitivity is directly proportional to the chromatin state such that open/accessible regions are more prone to DNAse-I digestion. You may call these regions as euchromatin.
Though the total DHS density is not reported in the paper [2] or supplementary data, the ENCODE project that the paper concerns, will have all the detailed information. You can can find these datasets here, from which you can calculate DHS density distribution for different cell types. However, most of these cells are actually cell lines and not from primary tissues.


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What is the fastest way to crystallise lysozyme (for student course)?
High school sudents are going to visit my university and I plan to demonstrate crystallisation of lysozyme. I ordered pure lysozyme from VWR. I can easily crystallise this within 15 min in batch (4% w/v NaCl, 35 mg/mL Lysozyme dissolved in 0.2M NaAc). However, as many different student groups will go through this experiment sequentially, it is preferable that it takes even less time (5 min waiting time maximum). I can of course try to optimise this on my own, but I am wondering if anyone has experience with the absolute fastest way lysozyme forms crystals in a batch setup (to save time and chemicals).
In summary: What are the most optimal buffer/pH/lysozyme concentrations that will give crystals (in a batch experiment) within a very short timeframe (<5-6 min)?

I think you have better chances to find an answer here than on [chemistry.se]. Your question is on-topic on both sites.

Check this out https://hamptonresearch.com/product_detail.aspx?cid=28&sid=173&pid=524

Cool, I could try this out and report back

I don't have an expertise in this field but don't you think 15min is quite fast? Most biology protocols take much longer. I have seen protein-crystallography people waiting for several days to get their protein to crystallize.

Yes it is, my PhD-project crystal normally take about 3-4-day. However, lysozyme is insanely easy to crystallise - and this is for a open research day with high-school student that have a very limited time to conduct the experiment. I just think its interesting to get the absolute optimal way of doing this fast. The answer may be that its not possible in less than 15 min (but I dont know).

Perhaps you could start a new crystallization with each group (every 5 min) and then show them the results of previous groups. Each group could then be able to observe what is happening at 0, 5, 10 and 15 min.

One try would be to see if also for lysozyme a powder of previously generated lysozyme crystals would nucleate and hence speed up the crystallization if added to lysozyme solution.

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Can a rotten egg actually hatches to a real life?
First of all, I'm no expert in biology. I failed a lot in high school. Please bear with it if it's a stupid question.
For the past few days, I got a rotten smell as if an animal died in my kitchen. I cleaned and didn't find anything until I found the culprit today: leakage of rotten eggs.
There were two eggs in a hard plastic container, and one of them leaked a bit. Then I saw around 4-5 insects-kind of thing lurking around. It looks like a worm and if you ask me how those things look like, it's as if the egg yolk itself separated into the shape of worms and started moving. If I remember correctly, I believe I saw a pair of white dots (their eyes) in each.
Did those eggs (which was stored in a warm place) actually hatched and gave to a life? I threw all of them away, but I still feel really sick. Is it because of my carelessness that the egg yolk actually became alive in such shape?
Thanks beforehand.

The eggs only come to life when they get fertilized, which is not the case for hens which lay eggs commercially. Of course insects can live from the broken egg - it's pretty nutriceous.

The only thing that is going to hatch from a chickens egg is a chicken, not a worm. As chris said - commercial eggs are not fertilised so will just go rotten. The worms you saw can from another source.

Even if it were a fertilized egg, it wouldn't give rise to worms. If fertilized eggs are not refrigerated properly, they will also rot, not hatch a chicken. This is a question almost akin to spontaneous generation.

A chick can't develop outside of it's egg, so you won't see an embryonic chick growing and wiggling in a pool of substance leaked from a cracked egg.
Centuries ago, people believed in spontaneous generation: that life can arise from non-living things. A common example of this was the fact that maggots would "arise" from rotting meat if left to rot.
Although this theory was disproved, it is not rare to find someone that still believes it, because they seem to see it happen.
In the 1800's, before DNA was discovered, it became accepted that "like gives rise to like" - that is, chicken eggs will hatch chicks (not peacocks or mice), pea seeds will always give rise to peas, etc.
DNA was 'discovered' in the late 1800's by Johann Friedrich Miescher. He extracted a new king of organic moleculr out of cell nuclei, which he called "nuclein". Although Miescher did develop some hypotheses about how "nuclein" might be involved in heredity, he ascribed to the view at the time that any one type of molecule would be too simple to account for all the variation seen within species.
It would be about 75 years before the magnitude of Miescher's discovery would be fully understood, and that DNA is the basis for heredity.
Chicken eggs, if they give rise to anything (which will depend on if it is fertilized and properly incubated) can only give rise to chickens. Whether they are fertilized or not, they can't give rise to worms. A chick can't develop outside of it's egg, so you won't see an embryonic chick growing and wiggling in a pool of substance leaked from a cracked egg.
If you buy bananas and let them ripen and rot on your kitchen counter, you will suddenly find a lot of fruit flies in the house. The fruit flies did not spontaneously arise from the bananas; they came from eggs laid on the bananas before you bought them.
If you buy bananas and wash them well when you get home, and let them rot, you will not find fruit flies buzzing around them.
That is why your rotten egg didn't give rise to those little worm things.

In response to your first statement - that a chick can't develop outside of an egg - please see my new question. http://biology.stackexchange.com/questions/47924/can-a-chicken-really-be-hatched-outside-of-the-egg


text:
Cigarette consumption dose-response function WRT health outcomes
I'm curious how health risks (mortality, lifetime probability of cancer, etc) change with cigarette consumption.  Specifically, treatring cigarette consumption like a continuous variable, rather than a binary for "smokers" and "nonsmokers".  I've got access to academic literature, but I'm not a doctor or a PhD health researcher.  This article states in the abstract that the dose-response relationship between cigarettes and incidence of lung cancer is linear.  This website (CDC) states that "smokers" have a 25-fold increase in risk of lung cancer.
How to reconcile the two?  The latter reports odds ratios, which means that they did a logistic regression, which means that the raw logistic regression coefficient was 3.2.  If the average smoker smokes 20 cigarettes a day, and the dose-response relationship is linear, then the relative risk for someone who smokes one per day should be exp(0.32) = 1.37.  So someone who smokes one cigarette per day would be 1.37 times more likely to get lung cancer than someone who never smoked (on average).
Is this a reasonable estimate?  I can certainly understand why public health types wouldn't promote this sort of conclusion, as smoking one cigarette can be a slipper slope to smoking a lot more cigarettes.

Personal medical questions are off-topic here. Could you edit your question to remove those implications? See http://biology.stackexchange.com/help/on-topic

Its a general population-level question with personal interest.  But if it bothers you, I'll lose the last paragraph.


text:
Is it possible to derive the Michaelis-Menten equation under conditions where the product formation is reversible
Text books etc generally derive the Michaelis-Menten equation for the irreversible case i.e $$\ce{E + S <=> ES -> E +P}$$ I can't see how to do it for the reversible case i.e  $$\ce{E + S <=> ES <=> E +P}\;$$ Is it possible?

The Michaelis-Menten equation is based on the explicit assumption that substrate is at a much higher concentration than the products. This is in fact what you have written and is true at the start of a reaction. At later stages it is generally not true and therefore the Michaelis-Menten equation no longer holds. If you ever do a biochemistry kinetics class you will always plot the initial rate of an enzymic reaction.

Now I understood what you mean to say. I was thinking you were referring to the first reaction of enzyme-substrate binding. Okay, there is no particular reversible conversion model that I have come across with but you can build a model based on a few assumptions. "Substrate concentration is much greater than the enzyme concentration" is true for the QSSA approximation. The original model used an equilibrium approximation which assumes that binding/unbinding reaction is much faster than the conversion.

The Reversible Michaelis-Menten Equation
An equation for the reversible form of the Michaelis-Menten equation was first derived by Haldane (1932, p 81), and the form shown in Eqn (1) was first given by Peller and Alberty (1953).
$$ v = {
  {{{V_{max}^f}\over{K_{m}^s}}\ s\ -{{V_{max}^r}\over{K_{m}^p}}\ p }\over{1 + {{s}\over{K_{m}^s}} + {{p}\over{K_{m}^p}}}}\ \ \ \ \ (1)$$

$v$ is velocity

$s$ is substrate concentration
$p$ is product concentration

$K_{m}^s$  is the Michaelis Constant for $s$
$K_{m}^p$  is the Michaelis Constant for $p$

$V_{max}^f $ is the maximum velocity in the 'forward' direction
$V_{max}^r $ is the maximum velocity in the 'reverse' direction

Setting $p$ to zero gives the more familiar form of the Michaelis-Menten equation (where $v_i$ is now the initial velocity)
$$ v_i = {
  {{V_{max}^f} s }\over{K_{m}^s + s}}\ \ \ \ \ (2)$$
Derivation of the Rate Law
How can Eqn (1) be derived?
This has been done by (among others) Cornish-Bowden (2004, pp 48 -52), and the derivation given below closely follows this source (with some help from  Wolfram Mathematica).
Let's consider the following form of the reversible single-substrate, single-product enzyme mechanism

A substrate $s$ may reversibly bind to $E$ (the 'free' enzyme) to give $ES$.  This in turn may be reversibly converted to $EP$, and reversible dissociation of product gives back the original form of the 'free' enzyme together with $p$.
The complexes $ES$ and $EP$ are sometimes called 'central complexes'
However, in order to simplify the algebra, I will derive the rate law for the following simplified (and unrealistic) mechanism containing a single central complex.

We need to be very, very careful here.  This simplifying assumption will not change the overall form of the  kinetic constant form of the rate law, that is both mechanism (3) and (4) will give rise to Eqn (1), but it will make the definition of kinetic constants simpler.
We must not assume that these simplified definitions necessarily apply to any realistic case. The definitions for $V_{max}^f$  (Eqn 10) and $V_{max}^r$ (Eqn 11), for example, contain a single rate constant but those for the mechanism of Eqn (3) are more complex (Eqns 15 & 16).
Thus statements such as 'for unit enzyme concentration, $k_{3,2}$ equals the maximum velocity in the forward direction' are fraught with difficulties. (It probably is valid to argue, at least for the type of mechanisms considered here, that 'for unit enzyme concentration, the maximum velocity cannot exceed $k_{3,2}$').
But we digress. Let's return to the derivation.

Let  $e_o$ be the total enzyme concentration
Let $x$ equal the  concentration of $ES$
The concentration of $E$ is therefore ($e_o$ - $x$)

In addition, let's make two fundamental assumptions (see here for a great elucidation of the steady-state method in enzyme kinetics).

Very soon after the reaction is initiated, a steady-state is established so that the rate of formation of $x$ equals the rate of breakdown of $x$.  This is the steady-state assumption. (What happens in the pre-steady-state period does not concern us here).
The concentration of $e_o$ is so low that formation of $ES$ and $EP$ may be ignored in calculating  substrate and product concentrations  (this also greatly simplifies the algebra)

The following differential equation, which describes the rate of breakdown of $x$, may now be written:
$$ {dx\over dt} =  {k_{1,2}\ (e_o -x)\ s + k_{3,2}\ (e_o -x)\ p - (k_{2,1} + k_{2,3})\ x = 0}\ \ \ \ \ \ \ (5)$$
Let's solve for $x$. I am going to be lazy here and allow Wolfram Mathematica to do the work.
(A more detailed version of the Mathematica notebook may be found here).

The above command produces the following output (how cool is that?)

Now let's define the velocity equation in terms of $x$, taking the reverse reaction into account
$$ {dp\over dt} =  {k_{1,2}\ x\ -\  k_{3,2}\ (e_o -x)\ p}\ \ \ \ \ \ \ \ \ (6)$$
We now need to substitute for $x$ in the above equation. Again, using Mathematica

Using substitution

the following output is obtained:

That is, the rate-constant form of the rate law may be expressed as follows:
$$ {dp\over dt} =  { {(k_{1,2}\ k_{2,3}\ s - {k_{2,1}\ k_{3,2}\ p)\ e_o}}\over{{k_{1,2}\ s} + k_{2,1}+ k_{2,3}+{k_{3,2}\ p}}} \ \ \ \ \ \ \ (7)$$
The 'trick' now is to define kinetic constants in such a way that the more useful kinetic-constant form of the rate law may be obtained.
Let's define the kinetic constants as follows
$$K_{m}^s = {{k_{2,1}\ +\ k_{2,3}}\over{k_{1,2}}}\ \ \ \ (8)$$
$$K_{m}^p = {{k_{2,1}\ +\ k_{2,3}}\over{k_{3,2}}}\ \ \ \ (9)$$
$$ k_{cat}^f  =  {{V_{max}^f}\over{e_o}} = k_{2,3}\ \ \ \ (10)$$
$$ k_{cat}^r  =  {{V_{max}^r}\over{e_o}} = k_{2,1}\  \ \ \ (11) $$
Dividing Eqn.(7) 'above-and-below' by ($ {k_{1,2}\ + k_{2,3}}$) gives the following expression:

Substituting the values of the kinetic constants into the above expression leads logically to the following kinetic-constant form of the rate law:
$$ v = {
  {({{k_{cat}^f}\over{K_{m}^s}}\ s\ -{{k_{cat}^r}\over{K_{m}^p}}\ p)\ e_o }\over{1 + {{s}\over{K_{m}^s}} + {{p}\over{K_{m}^p}}}}\ \ \ \ \ (12)$$
Kinetic Constants for the More Realistic Mechanism
The definition of kinetic constants for the more realistic mechanism of Eqn (3) are as follows: (see here for the Mathematica derivation).

In general,  different mechanisms may give rise to an identical rate law.
The following mechanism will also give rise to Eqn (1).

In fact, adding any number of central complexes to the mechanism of Eqn (3) will give rise to a rate law in the form of Eqn (1).
An Extension to the Michaelis-Menten Mechanism
Here is a mechanism that won't give rise to a rate law as shown in Eqn (1):

In the above mechanism, the form of the 'free' enzyme generated upon product release ($F$)  is different from that which combines with substrate ($E$), and emphasizes that we may need to take their inter-conversion into account in any complete description of a single-substrate, single-product enzyme (see Taraszka & Alberty, 1964).
The rate law for this mechanism contains an extra kinetic constant, here called $K_{sp}$
 $$ v = {
  {({{k_{cat}^f}\over{K_{m}^s}}\ s\ -{{k_{cat}^r}\over{K_{m}^p}}\ p)\ e_o }\over{1 + {{s}\over{K_{m}^s}} + {{p}\over{K_{m}^p}} + {{s p}\over{{K_{sp}}}}}}\ \ \ \ \ (19)$$
This mechanism could, for example, describe membrane transport where $F$ represents the carrier on the inside of the membrane and $E$ represents the carrier on the outside.  But it also could apply to any single-substrate, single-product enzyme. This again emphasizes the danger of over-simlification.
The rate law of Eqn (19) is well reviewed by Darvey (1972), and the pdf is freely available to all.
Final Thoughts ...
As the number of enzyme species increases, obtaining the rate-constant form of the rate law becomes difficult, as the equations very quickly accumulate many terms. Before the days of Mathematica and the like, enzymologists used the schematic method of King and Altman (1956), or one of its many variants, to obtain the rate-constant form of the rate law.
So what are the advantages of deriving the kinetic constant form of the full rate law?

If the reaction is demonstrably reversible, it may studied in both directions
For a multi-substrate enzyme, the product inhibition equations are easily written down.
It allows a relationship (or relationships) between the kinetic constants and the equilibrium constant to be obtained.  For the reversible Michaelis-Menten mechanism of Eqns (3) & (4), the Haldane relationship is as follows:

$$ K = {{k_{cat}^f\ k_{m}^p }\over{k_{cat}^r\ k_{m}^s }}\ \ \ \ (20)$$
where $K$ is the equilibrium constant for the reaction (Haldane, 1930)
References

Cook, P.F. & Cleland, W.W (2007) Enzyme kinetics and mechanism  Garland Science.
Cornish-Bowden (2004) Fundamentals of Enzyme Kinetics 3rd Edn. Portland Press (London)
Darvey, I. G. (1972) The application of product inhibition studies to one-substrate one-product enzymic reactions. Biochem J. 128, 383 - 387 [pdf]
Haldane, J.B.S (1930) Enzymes Longmans (London)
King, E. L. & Altman, C. (1956). A schematic method of deriving the rate laws for enzyme-catalyzed reactions.  J. Phys. Chem. 60, 1375 - 1378
Peller, L. & Alberty, R. A. (1959). Multiple intermediates in steady-state enzyme kinetics.  I.  The mechanism involving a single substrate and product.  J. Am. Chem. Soc. 81, 5907 - 5915
Segel, I. H. (1975) Enzyme Kinetics. Behavior and Analysis of Rapid Equilibrium and Steady-State Systems Wiley
Taraszka, M. & Alberty, R. A. (1964). Extensions of the steady-state rate law for the fumarase reaction. J. Phys. Chem. 68,  3368 - 3373.

Hey.. While you are at it, can you also try obtaining the rate as purely a function of substrate (by using the conservation relation). I haven't used mathematica.

No it is not possible to derive the equation for the reversible case. This is because the Michaelis-Menten equation is derived on the explicit assumption that the substrate concentration is much greater than the product concentration so that the back reaction does not occur. This is true at the start of a reaction in the lab when you add enzyme to your substrate. At later times when product builds up these conditions no longer hold and the M-M equation breaks down.
It is possible to derive a different equation for the reversible case (as some other posters do) but this begs the question of the importance of the Michaelis-Menten equation for biology. The poster seems to think that it is some universal truth, important in its own right or because it models the reaction in the living cell. I think this misses the point, which I think is as follows.

It originally was a prediction from, and hence a test of, the hypothesis that enzymes have a single active site at which the substrate binds and is converted to products.
It allowed two fundamental aspects of this enzyme model to be quantified: (i) the binding affinity of the substrate for the active site, as the inverse Km, and (ii) the catalytic efficiency ('smartness') as the turnover number or kcat, which is derived from Vmax (and enzyme concentration).
These enzyme constants can be used to address biological questions, for example whether an enzyme capable of a particular reaction in the test tube is able to account for the observed reaction rates in a tissue. Or whether the substrate you find the enzyme can use is likely to be the physiological substrate in a tissue.
It turns up enzymes that do not exhibit M-M kinetics, implying that some aspect of the model does not apply to them. This can be of mainly chemical interest (ping-pong kinetics and the like) or of physiological importance, as in allosteric kinetics (S-shaped rather than hyperbolic curve) shown by multi-subunit enzymes where the individual subunits show co-operativity, allowing more finely tuned regulation.
And if you do want to model reactions within cells, the kinetic constants can be of use. However as one is normally dealing with a chain of reactions in an open system the mathematics are complex (and nothing to do with the equation for a single reversible reaction in the test tube).

Most biochemistry students (and many teachers) would be hard pressed to explain why they should learn the derivation of the Michaelis-Menten equation. The answer is partly so they see that it is based on a particular model of the enzyme, but also so that they are aware of the assumptions on which it is based. Hence they need to be aware that the Michaelis-Menten equation is only true for initial rates of reaction, otherwise their determination of the practically and biologically useful Km and Vmax will be incorrect.

Well, I disagree.  I think the reversible case is almost always considered in enzyme kinetics, especially for more complex mechanisms, and then simplifying assumptions applied to the full rate law.  The equation for the reversible Michaelis-Menten equation is derived, for example, by Cornish-Bowden 'Fundamentals of Enzyme Kinetics', p 31 (of the first edition).  See Cook and Cleland for more details.

The Reversible Michaelis-Menten Equation (after Cornish-Bowden, Fundamentals of Enzyme Kinetics)$$ v = {{{{V_{s}^f}[s]\over{K_{m}^s}}-{{V_{p}^f}[p]\over{K_{m}^p}}}\over{1 + {{[s]}\over{K_{m}^s}} + {{[p]}\over{K_{m}^p}}}}$$

$ {V_{s}^f}$ is the maximum velocity for s (substrate) in the 'forward' direction, $ {V_{p}^r}$ is the maximum velocity for p (product) in the 'reverse' direction,   $ {{K_{m}^s}}$ is the Michaelis Constant for s, and   $ {{K_{m}^p}}$ is the Michaelis Constant for P.  Set [p] to zero to get 'classical' Michaelis-Menten equation.

It is always possible to derive some mathematical model given the right assumptions. You perhaps mean to say that the reversible case would not be compatible with the MM model. Well, of course because MM model assumes irreversible conversion. The assumptions are different altogether.

It is possible to derive AN equation to describe the reversible reaction, however that equation is NOT the Michaelis-Menten equation. The point about the Michaelis-Menten equation is not that it models reactions in the cell, but that it can be easily tested and fundamental properties of the enzyme calculated. These are important from a biological point of view. Writing equations to describe the reverse reaction may be an interesting exercise for a chemist, but has little biological relevance and I doubt is what the questioner had in mind.

@TomD. I had assumed from the other comments that Cornish-Bowden had done this, or even if the average chemist couldn't do it the modern mathematician (or his computer programs) could. But I don't really care. As my modified answer shows, I'm trying to point out the relevance of the 'text-book' M-M equation to the novice. If the poster was more interested in the chemistry or mathematics than the biology, I'm missing the target.

@TomD I just meant that Michaelis-Menten is a model. Any deviation from it is not a Michaelis-Menten model (we can say they are MM-like) but similar approximations can be applied, as you rightly put, in other situations. And actually my comment was intended for David as he is the one who was emphasizing of reversible case not being MM :P

@rhody — I bow to your superior knowledge on this. I am not an enzymologist.

The derivation for the equation mentioned by TomD in the comments:
$$ v = {{{{V_{s}^f}[s]\over{K_{m}^s}}-{{V_{p}^f}[p]\over{K_{m}^p}}}\over{1 + {{[s]}\over{K_{m}^s}} + {{[p]}\over{K_{m}^p}}}}$$
can be found here. This formula assumes a three step reaction. This equation uses product as a variable in the equation. Ideally, since there is no formation/degradation of the reactants/products (closed system), the product can be represented as a function of the other variables ($\ce{[S0] -[ES] -[S]}$). In short, the product formation rate can be simply represented as a function of the substrate concentration.
What I am going to show is not a full derivation but one approach that you can start with.
For this two step reversible reaction:
$$\ce{E + S <=>[k_1][k_2] I <=>[k_3][k_4] E + P}$$
You would have the system of ODEs:
$
\dfrac{d\ce{[E]}}{dt}=-k_1\ce{[E][S]} + (k_2+k_3)\ce{[I]} -k_4\ce{[E][P]}\\
\dfrac{d\ce{[I]}}{dt}=\quad k_1\ce{[E][S]} - (k_2+k_3)\ce{[I]} +k_4\ce{[E][P]}\\
\dfrac{d\ce{[S]}}{dt}= -k_1\ce{[E][S]} + k_2\ce{[I]} \\
\dfrac{d\ce{[P]}}{dt}= -k_4\ce{[E][P]} + k_3\ce{[I]}
$
Assuming QSSA for $\ce{[I]}$ (and hence also $\ce{[E]}$) and setting $\ce{[E]} = \ce{[E0] -[I]}$, you'll get:
$$\ce{[I]}=\frac{\ce{[E0]}(k_1\ce{[S]}+k_4\ce{[P]})}{k_2+k_3+k_1\ce{[S]}+k_4\ce{[P]}}$$
Since $\ce{[P]}=\ce{[S0] -[I] -[S]}$, the equation for $\ce{[I]}$ shown above, will become quadratic when you substitute this relation. This expression can be finally plugged into the fourth ODE to obtain the expression for the product formation rate, purely in terms of the substrate.
If you keep product as a variable then you can substitute the above expression for $\ce{[I]}$ in the fourth ODE.
$$V=-k_4\ce{[P]}\left(\ce{[E0]} - \frac{\ce{[E0]}(k_1\ce{[S]}+k_4\ce{[P]})}{k_2+k_3+k_1\ce{[S]}+k_4\ce{[P]}}\right) +k_3\frac{\ce{[E0]}(k_1\ce{[S]}+k_4\ce{[P]})}{k_2+k_3+k_1\ce{[S]}+k_4\ce{[P]}}$$
Some algebraic rearrangements will yield:
$$V=\ce{[E0]}\frac{k_3k_1\ce{[S]}+k_4k_2\ce{[P]}}{k_2+k_3+k_1\ce{[S]}+k_4\ce{[P]}}$$
Dividing both numerator and denominator by $k_2+k_3$ yields:
$$V=\ce{[E0]}\frac{\frac{k_3k_1}{k_2+k_3}\ce{[S]}+\frac{k_4k_2}{{k_2+k_3}}\ce{[P]}}{1+\frac{k_1}{k_2+k_3}\ce{[S]}+\frac{k_4}{k_2+k_3}\ce{[P]}}$$
This is the form of equation mentioned by TomD (just create new constants from the old ones).
For some more details have a look at this paper by Keleti [1] and the other papers citing it.

[1] Keleti, T. "Two rules of enzyme kinetics for reversible Michaelis‐Menten mechanisms." FEBS letters 208.1 (1986): 109-112.


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Detect differentially expressing cells
I have data (RNA expression values, obtained with in situ hybridization) collected from 1mio human cells. For each cell, I have the expression value of a negative control (non-human RNA) and single-cell measures for different RNA species. I know that the values from the negative control correlate in a linear fashion with all the other RNA species. For example, when a cell has a high expression value of the negative control, the signal for all other RNA species will also be high. I now want to detect the cells that express an RNA without having a high negative signal, e.g. the "real" expressing cells.
One thing to have in mind is that some RNA species are abundantly expressed in many cells, other are very rare and have a low expression value.
I tried to do this with a linear model (for each of the RNA species, negative control vs. single RNA), computing z-scores, infer p-values and correct for multiple testing. For some RNA species, it works just fine. As soon as I have many cells expressing a certain RNA, the thing gets more tricky because the slope of the linear model doesn't reflect the linear relationship of negative control vs. RNA species in non-expressing cells because it is more shifted towards the "real" expressing cells.
To visualize the problem, I attached two plots. One plot showing high RNA expression many cells (left plot) and one from an RNA species which is expressed on a very low level in few cells (right plot). Blue colored dots are considered as expressing cells according to the linear model. As you can see, for the scenario shown on the left side, many "real" expressing cells are not detected.

Any ideas which statistical model would better fit to detect those cells?
Thank you for your suggestions!

Have you tried just substracting the values for the negative control from each RNA species X? I think that should both improve your actual measurement and make it easier to detect with cells have non-detectable levels of the RNA.

good point @Nicolai, I will try that.. but how would you then define expressing cells? with a manual cut-off? I have to say that I'm not a big fan of manually defining things for such analyses because I think that will just introduce an unnecessary bias.

You can try linear mixed effects model. I'm not 100% sure if it would help but the cell to cell variability of the slope/intercept can be modelled as the random effect.

Welcome to Biology.SE! This question seems like it might be a better fit for the Bioinformatics site.

@tyersome may be a better fit at [stats.se] but this isn't really a bioinformatics question.

@tebiwankenebi is the negative control and the expressed genes measured in the same cell (i.e. a two color FISH or something)? If not, you cannot simply subtract the negative control values. In that case, it is really not possible to differentiate a high false signal from a low true signal. However, if you consider each cell as a replicate population then would have to do some kind of two sample test or LM fit (using the expressed gene and negative control as predictors). LM may be less stringent than t-test or Mann-Whitney. Can you provide some more details on how you fitted the LM?

@WYSIWYG thanks for your answer. Yes, the expressed genes are measured in the same cell (it is actually multi-channel ISH). The linear model I use models Y = "mRNA of interest" ~ "negative control", assuming a linear correlation between the negative control signal and mRNA signal. I don't know if my approach is valid because I know that there is no linear correlation in real expressing cells (high mRNA, low negative control).


text:
Cause of a extra vertebra in the human body
Most people have five vertebrae in their lumbar (lower back) region, which are named L1 to L5. However, some people possess an additional lumbar vertebra located below the L5. This extra vertebra, known as the L6, is called a transitional vertebra. About 10 percent of adults have some form of spinal abnormality caused by genetics, and a sixth lumbar vertebra is among the most common of these abnormalities.
Question- What is the current explanation to why some humans have developed this extra vertebra in the spine?

What do you mean by genetic link? Are you looking for the names of the genes which variation explain variation in number of vertebrae? Or are you looking for the fraction of the phenotypic variation that is explained by genetic variation (namely, the heritability)?

Your phrasing suggests some confusion on these concepts and you might want to read on the concept of heritability (even if it may seem unrelated to your right now). On this post I linked 4 other posts (and the wikipedia article) that talk about heritability.


text:
Why is there only adrenoreceptors and no active adrenergic innervation in bronchus and uterus?
Our bronchus and uterus has beta adrenoreceptors, but they have no active sympathetic nervous system innervation in these organs. Was there a sympathetic innervation in trachea and uterus, earlier, that we lost it during the course of evolution, if no, why did nature gives us only adrenergic receptors and no adrenergic nerves in trachea and uterus?

If endocrine system is an alternate signalling system to nervous system. Epinephrine and Norepinephrine have endocrine roles as well apart from being neurotransmitters. In fact I had learnt about their endocrine function long before I realized that they also act as neurotransmitters.


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What are the differences between cancer and tumour?
What are the differences between cancer and tumour? I mean is it in the DNA or shape or something else... And how can a benign tumour turn into a malignant tumour? The body has a lot of tumours all the time, however not all of them become cancerous, why is this so?
So my main question is: What is so special about cancer cells that they can get out of control unlike an ordinary benign tumour?

please accept an answer. It is considered impolite when the question has been answered to the fullest and the OP (original poster) has not accepted an answer. It means that the OP is expecting something more. So if you feel that the question has been answered, then please accept the answer which has suited you.

What is the difference between "a car" and a "Volvo XC60"? What is difference between "disease" and "sarcoidosis"? What is the difference between "planet" and "Earth"?

A tumour is simply a space-occupying lesion (something that should not be there, that is; a "lump") caused by abnormal cell replication.
(In medicine, the word "tumour" literally means "swelling", and can sometimes refer to that instead, but that's a different story).
Cancer is a disease in which cell replication is totally out of control. What causes cancer is damage to the genes (DNA) which normally stop cell replication when it needs to be stopped.
There's no such thing as an "ordinary tumour"; all tumours are abnormal. However, what makes a benign (harmless) tumour different from a cancerous tumour is that there is still some mechanisms stopping the cells inside the tumour from replicating; they are doing it more than they should, but they are not totally out of control. When those last mechanisms are broken too, the tumour is cancerous.
(This is a simplified explanation; the actual explanation is a semester-long university course. It's mostly accurate for the layman, though)

Thanks! and where can I get the "actual explanation"? can you give me an outer source for that?(book/site etc)

Wikipedia is always a good start; the article on cancer has a "Further Reading" section down near the bottom.

Uterine smooth muscle tumors other than the ordinary leiomyomas and leiomyosarcomas: a review of selected variants with emphasis on recent advances and unusual morphology that may cause concern for malignancy. ') Just nit picking here, but I do believe many kinds of "tumors" are so common that they deserve the appellation "ordinary". Subcutaneous lipomas, for instance.

Hallmarks of Cancer: The Next Generation is a review article that'll provide a great understanding, sorry for no link, on my phone.

@Kendall here is the link to the 2011 Cell article by the same name. I could download the PDF at home, so I believe it's open-access.

@anongoodnurse You make a good point; I think it depends on your definition of "ordinary". All tumours are out-of-the-ordinary in one sense because they come about due to cellular dysfunction - cells doing what they would not ordinarily do. In another sense, though, I suppose some "ordinary" tumours do exist.

@anongoodnurse I am confused about the title, does it imply that leiomyosarcomas are also ordinary? I agree that leiomyomas are ordinary as are lipomas

Tl;dr answer, tumors are abnormal growth (or swelling, thanks to Malic for pointing out) of any kind. The kinds of tumors are benign and malignant.
Benign tumors are usually slow growing and harmless. Example would be a lipoma.
Malignant tumors are otherwise called cancers. They generally have a bad prognosis. Very few cancers are curable.
Swelling over an injury (which is also called tumor) is due to local transudation (shift of plasma from capillaries). This is temporary and usually goes down one the injury heals.

All of the tumors are abnormal?  I heard that if part of the body get hurt, the body does a tumor on purpose to fix the part that get hurt, is it true? and there is a lot of small tumors in the body at a given moment?

When a part of body swells, it is also called tumor. Thanks for pointing out! @MalicOfSdom. But that swelling is also considered pathological. As it is a deviation from physiology

haa! so every time a part of the body swells it is tumor...scary! and does a benign tumor can turn to a malignant tumor?

Yes, it can occur. Some benign tumors are more prone to malignant change while some practically never do

In general, though tumor can denote any swelling regardless of the presence of any growth, practically speaking, doctors rarely use the term tumor to denote an edematous swelling. So for practical purposes, the word tumor means abnormal growth

ha ok, and when I get hurt for example in the bone, the swell on it is benign tumor?  what is the chance that it will convert to malignant tumor?

@MalicOfSdom Tumors due to swelling in response to injury will never turn malignant. Only benign tumors due to abnormal growth has the potential to turn malignant

and how this turn from benign to malignant obtained?  is it in the genome of the tumor or something else...?

@MalicOfSdom you should post this as a new question. There are many theories in that. Searching in wiki will be of great help too.

one more thing: malignant tumor always strarts from a benign tumor?

Not always, can start from normal cells too

@CRags - you've given a number of incorrect answers here. Curable cancers are not few and far between. Malignant tumors are not always deadly (see, for example, basal cell carcinomas). You should try to stay within provable statements when answering questions.

@CRags - no, I don't agree; if I did, I would not have left that comment. I define "cure" like any normal person: it's gone and will never bother you again. It is possible, and it is done every day, to declare a cancer patient cured. Childhood leukemia is now a largely curable disease; others include some lymphomas, cervical cancer, and others if caught early. Clearly there are some that, regardless the initial response, can still come back. I'm just saying, don't make claims which are untrue. BCC is a malignant cancer with a very good prognosis, if not even excellent.

Yes, I got it. I will be more careful @anongoodnurse Thanks for helping me answer better


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Relationship Between Evolution and the Increase of Entropy of Earth
I was confronted by this question:
Biological evolution of life on Earth, from simple prokaryote-like cells to large, multicellar eukaryotic organisms,

A) has occurred in accordance with the laws of thermodynamics.
B) has caused an increase in the entropy of the planet.
C) has been made possible by expending Earth's energy resources.
D) has occurred in accordance with the laws of thermodynamics, by expending Earth's energy resources and causing an increase in the entropy of the planet.
E) violates the laws of thermodynamics because Earth is a closed system.

Answer:  A
However, I do not understand. Biological evolution does cause the system (living organisms)'s entropy to decrease. So, by the second law of thermodynamics, the entropy of the universe (in this case Earth), must have overall increased.
I would answer D... Where am I going wrong?

Life (excluding chemosynthetic bacteria and such) doesn't expend Earth's energy resources, it uses energy from the sun.  So entropy increase on Earth is much more than balanced by the decrease on the sun.  (Or is it vice versa?  I forget which way it goes...)

This sounds like a question a creationist might ask.

The second law of thermodynamic states the entropy can only increases in a closed system. Life is definitely not a closed system. I think that this question would be a better fit for physics.SE

@Remi.b I think this question is a good fit here as well (even though I'm a physicist): this is the application of physics to a primarily biological problem and I think looking at and becoming well versed in this kind of thing is pretty essential for biologists, particularly of they don't want to get wiped out by well funded creationists with very big megaphones.

This area is extremely complicated and has been the subject of historical scientific disagreement, as the Wikipedia entry shows. At the best of times MCQs are, in my opinion, the antithesis of education, but to use them in this context seem to me quite absurd. It suggests to me that the so-called educators of the poor poster were force feeding him some glib line, which they then expected him to regurgitate. I feel for him, but as this was six years ago, I hope he may have recovered from the experience by now.

Related question: Is the principle of “the least energy” a fundamental principle of evolution? How does it stand with the rule “the one who replicate the most”? https://biology.stackexchange.com/questions/101626/is-the-principle-of-the-least-energy-a-fundamental-principle-of-evolution-how

certainly not just based on the expense of Earth's own energy resources but Solar as open system

However, I do not understand. Biological evolution does cause the system (living organisms)'s entropy to decrease. So, by the second law of thermodynamics, the entropy of the universe (in this case Earth), must have overall increased.

The universe and the earth are not equatable. Earth is not an isolated system. Life causes entropy of the earth to decrease. This is offset by increased entropy of the sun, which is the primary source of energy for the earth. Overall, the entropy of the universe increases.

It's somewhat disconcerting that this is my highest rated answer…

Yes, for example entropy of the sun decreases, because of nuclear reactions. I suggest to improve this answer so that it wouldn't be overrated.

What if we had no Sun and all the biological process got their energy from Earth's internal energy? There would be no evolution? Please help me understand.

@anthony You should post your own answer.

Okay, added a quick and dirty one, could use some restructuring maybe.

I would say A or D are acceptable, but A is probably the better answer: firstly, the entropy of the planet system alone is probably not increasing (indeed, it's probably near to constant) and as noted elsewhere, you need to consider a closed system to apply the Second Law, so you need to think about everything that comes to and leaves the Earth. This is the key to understanding why life on Earth doesn't violate the second law: Earth absorbs and re-radiates roughly the same amount of light, but that light's state is radically changed as this happens, and this state change and the huge entropy increase it brings about overwhelmingly offsets the decrease in Earth's organisms' entropy as they build themselve whilst making use of that light.
Let's look at the radiation balance in more detail.
The thermodynamic entropy of a system is basically the system's conditional information content (also known evocatively as equivocation in information theoretic circles) conditioned on the given macroscopic properties of a system. It's the logarithm of the number of ways a system's internal microstates can be arranged consistent with the observed outward properties. A simple explanation of the logarithm is that when you add two systems together, the number of ways that they can be arranged multiplies (think of two car number plate letters: one letter yields 26 different number plates, two letters $26^2$ number plates, three letters $26^3$ number plates, three letters and two digits yields $26^3\times 10^2$ number plates and so forth). So the entropies add when the possibilities multiply.
The entropy of a system of identical particles is proportional to the number of particles in that system. Think of each particle as like a letter in an alphabet of its states and then think of long "number plates" of concatenated particle states.
So now: let's look at the input to the Earth: around about $1{\rm kg}$ of energy in the form of sunlight per second is available to Earth systems to do work. It comes as $\frac{c^2}{h\,\nu}$ photons per second, where $\lambda = \frac{c}{\nu}$ is of the order of 500nm so $\nu\approx600{\rm THz}$. That is, about $2\times 10^{35}$ photons per second.
The energy output of the Earth is basically infrared heat: it's the same amount of energy as comes in, but it is now composed of many more photons, because now $\nu$ in the photon number $\frac{c^2}{h\,\nu}$ is of the order of $30{\rm THz}$ (corresponding to $\lambda=10{\rm \mu\,m}$). The Earth therefore radiates roughly twenty times more photons than it absorbs: about $4\times 10^{36}$ photons per second. Each photon can encode the same amount of information, so the entropy increase is roughly twentyfold. Life systems on Earth use about one thousandth of the incident Solar energy: it has been estimated that photosynthesis fixes energy for use by life systems at the rate of about $100{\rm TW}=10^{14}{\rm J\,s^{-1}}$, compared with an input of $1{\rm kg\,s^{-1}}\approx 10^{17}{\rm J\,s^{-1}}$. So, no matter how complex life organisms get, this barely makes a dint on the massive entropy "production" of the total Earth energy cycle: the nett production of entropy by the whole Earth system is still strongly positive notwithstanding the presence and evolution of life, and therefore in keeping with the Second Law.
An interesting calculation has been done on how much Solar energy is needed to evolve life on Earth to the present day. This is presented in the paper:
Emory F. Bunn, "Evolution and the second law of thermodynamics", Accepted for Publication Amer. J Phys.
Bunn calculates that less than a year of sunlight would be enough to power the evolution of all life on Earth over the last four billion years and still be in keeping with the Second Law.
I should cite where I first saw this idea for explaining the life versus second law problem: I took this line of argument from:
Roger Penrose, "The Road To Reality: A Complete Guide to the Laws of the Universe", 2004 Chapter 27, "The Big Bang and its Thermodynamic Legacy"
but I have heard it used in several lay explanations of physics since.

My 2 pennies on this discussion
Entropy in general is the total number of states a system can occupy which is also called degrees of freedom (so is with the supply of heat, the molecules vibrate and can occupy more states). Any system tries to avoid confinement and maximize the number of states it can occupy. However if the system is in a stable state and any movement would cost it energy, then it would remain in the present state at the cost of reduced degree of freedom.
This relationship is described by this equation: ΔG = ΔH -TΔS Where ΔG is change in the Gibbs free energy, ΔH is change in enthalpy, ΔS is change in entropy and T is the temperature.
Though the process of natural selection destroys the number of phenotypic states that life can occupy, thereby causing a decrease in entropy, there are other processes which lead to gain in entropy (for example population growth and migration). Note that the process of reproduction itself creates order from disordered molecules, but as the population expands and spreads entropy is again maximized. As already pointed out by bobc, catabolic processes which fuel life processes increase entropy but anabolic processes do the opposite.
So my opinion is that the process of Natural Selection reduces entropy, so is the formaton of the eukaryotic cell. A free living bacteria has more freedom than a cell-locked mitochondria. However there are other energetic benefits that balance this reduction of entropy.
For earth I would guess that the overall entropy has reduced because the earth has cooled down since its birth. Since heat is removed entropy has reduced.
There is no violation of the second law in any of these cases. It is a universal law.

The correct answer is almost D: Life on Earth has occurred in accordance with the laws of thermodynamics by consuming Earth's free energy (which is continually being replenished) and causing an increase in the entropy of the universe. Life maintains it's own low entropy by increasing the entropy of it's environment. The Earth radiates energy of lower entropy than it receives (see citation 3), thus increasing the entropy of the universe. This happens by re-radiating the short wavelength radiation received as longer wavelength radiation. Life contributes to the process of converting the former to the latter. The outgoing radiation is in the form of more but lower energy photons than the incoming higher energy photos from the Sun. Keep in mind that the energy into the Earth is approximately equal to the energy out of it.
Useful resources for looking into the subject more:

Ulanowicz, R.E. and Hannon, B.M., 1987. Life and the production of entropy. Proceedings of the Royal society of London. Series B. Biological sciences, 232(1267), pp.181-192.

Schneider, E.D. and Kay, J.J., 1994. Life as a manifestation of the
second law of thermodynamics. Mathematical and computer modelling,
19(6-8), pp.25-48.

Kleidon, A., 2010. Life, hierarchy, and the
thermodynamic machinery of planet Earth. Physics of life reviews,
7(4), pp.424-460. – Anthony 1 hour ago

The answer is A because D implies a fallacy that Earth is a closed system.

Read carefully and notice that I didn't propose D and specifically point how it is not a closed system. The closed system is the universe.

Yes but some of the other answers were much more clear on that.

Well I guess time will tell us where voters' reading comprehension is at.

Excellent reference list - at least, from a physicist's point of view!

The Second Law is one of the most misunderstood and misapplied laws of thermodynamics. It has a scope largely confined to physics, nothing more should be read into it. Simply put, it states that "Heat cannot spontaneously flow from a colder location to a hotter location". (Wikipedia) There is nothing about life that violates that, or creates "negative entropy".
When you get into the details, you need to consider closed vs systems, and equilibrium vs non-equilibrium systems.
In fact, life contributes to positive entropy, like everything else. Energy at high potential is transformed to low potential, at the same time creating useful work and waste heat. Note that "useful work" can include storing energy in a form useful for future use.

Although I agree with the broad scope of your argument, however I requires some further referencing! but still a nice response!

Sometimes the reduction of entropy is balanced by reduction in enthalpy (for e.g. RNA folding).

It is A for one simple reason the ultimate source of energy that drives evolution may be earth or the sun.
First Additionally it is arguable if a multicellular organism has less entropy than ancestral prokaryotes since there were far far more iterations of prokaryotes.
Evolution has no effect on individual organism's entropy. Evolution can only occur in a system that is consuming energy. To put it a different way if I build one car and then build a second more complex one, building the second car has no effect on the entropy of the first. So you can only be looking at the process itself, in which case the traits of the organisms are irrelevant.
Consider sorting in geology, particles can be sorted into organized patterns, but only if there is enough energy to move them in the first place. Sorting in theory might decrease entropy, but it can only occur if there is an overwhelming increase in energy to drive it. for living things ,depending on the organism, that energy/entropy may be coming from the earth or the sun, in the latter case the entropy of the planet may not be effected depending on how you define it.
That said that is a horribly written question, because sunlight could be considered part of earths energy resources, and it is written in a way to confuse different usages of entropy.

Evolution increases complexity (entropy)
e.g., developing a new citrate path way in E. coli
It does this process by of expending energy.
i.e., via lifeforms's metabolism
So to answer your question:
A,B,C are all correct (or part of a correct answer)
However D is the most correct answer (It is an all of the above type answer)
E is a none of the above answer (and most incorrect)

There is no way of breaking the second law of thermodynamics. And you "don't get away with it" by "using the the 0th and 1st". The second law is only valid for closed (energetically) systems, which the earth is not. So it is not correct to use this law here.


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Why is the Trendelenburg position used when placing and removing Central Venous Line catheters in the sub-clavian vein?
The title says it all. Why is it that patients are placed in the trendelenburg position when a catheter is inserted in the sub clavian vein? What would happen if the patient wasn't placed in the trendelenburg position when placing the catheter?
Thanks in advance for the help.

Positioning the patient in Trendelenburg will increase the size of the IJ vein. From http://www.med.uottawa.ca/courses/cvc/Landmark%20Techniques/e_landmark_techniques.html

There are 2 main reasons for using the Trendelenburg position when placing and removing a central venous line catheter into the subclavian or even internal jugular vein.

Exactly what C Rags mentioned-- to increase the size of the vein. This position utilizes the force of gravity to pool blood towards the head from the lower extremities. This makes the vein of interest easier to visualize compared to surrounding structures, to palpate since this increases pressure within the vein, and to ultimately puncture.
To avoid air embolisms, which are particularly more damaging if they get into the brain causing a stroke than if they travel inferiorly to the leg, for example. Air embolisms can be introduced when inserting or removing a line.

Ref:

http://emedicine.medscape.com/article/422189-overview#showall

I'm sorry if this seems to be too picky, but how does being in the Trendelenburg position make an air embolus travel against the flow of the blood (as you state, inferiorly?) Will an air embolus introduced into the subclavian vein go to the leg if a patient is placed in Trendelenberg? If so, how does it navigate back into the superior vena cava -> inferior VC -> etc.?

Great question, it is theoretically possible for an embolism to travel retrograde to blood flow depending on the position of a patient. This paper does not specifically test the subclavian vein, but the authors created a simulation of blood flow through a vein-mimic to determine at which angles an air embolism could flow retrogradely.

Thanks for answering! Your paper states @ angles between 0 - 45°, air bubbles followed fluid flow (these are smaller bubbles, though). Trendelenburg is  <45°. While it's is recommended for insertion and removal (it's always good when an answer sparks my curiosity), I read that it's to create a pressure gradient (blood is more likely to back up into the line than air to enter the vein). Once an air embolus is introduced, however, the left lateral decubitus (sometimes +Trendelenburg) position is recommended to trap the embolus in the R atrium until reabsorbed. Fascinating.


text:
Why do eyes water in response to particular emotions?
It is common for people to experience very moving situations (sad movies, etc) and have a physical reaction to it (such as crying). I am curious about how emotions can physically lead to the act of crying. Why/how does this happen? What is the mechanism?

Can you please clarify this question, and also support your assertion with a little bit of the background reading you've done about it?

@anongoodnurse Many questions about biology are so obvious from the human perspective, that no reading should be asked.

When we are sad, our emotions are in an overdrive and the parasympathetic nervous system triggers lacrimation i.e. tears, and we cry.

Great succinct answer for a vague topic.

You're only answering the proximal (physiologic) why, i.e. the mechanism. What about the distal (evolutionary) why?


text:
Play Mimicking Normal Behaviour In Cats
I tried to word my question so it will be given serious consideration. Rather than ask in Pets SE (which doesn't have the brightest questions or answers), I feel it's better suited for Biology SE - specifically animal behaviour.
Generally, the play behaviour of adult cats mimic their interaction with siblings when young, and as adults, their hunting behaviour. It's in regard to play mimicking hunting that my question likely fits best.
The stealthy stalk and pounce while playing is almost identical to what's used in actual hunting but with far more playful abandon. Leaping in the air to grab an escaping bird is seen when they leap and grab at a feathered toy that's whipped about. Tossing a small fuzzy weighted toy about mimics how they act when they've caught a mouse. The same with chasing after a small rolling ball.
But there's one play behaviour I can't find an equivalent. It's cats' fascination with a simple dangling string or cord. A person doesn't even need to move it. As long as it hangs and dangles near the ground, many cats can't resist playing with it. (I'm referring to an average active cat, not one of the unfortunate inbred creatures that do little.)
Does anyone know, or can think of, an equivalent natural behaviour that explains this? It's not similar to a mother cat flicking the tip of her tail as that involves tempting movement. But it's the closest thing I can think of. I've given this a lot of thought for a long time. Hopefully, someone else has wondered too and found a reason.
(No tags really fit my question so only one given.)

I dont have any sources for this, but I'm pretty sure this is somehow connected to a hunting instinct. Even though cats probably don't mistake the cord for actual hunting game, they have to learn and train hunting behaviours - therefore it makes evolutionary sense that they react to small movements in the environment (I'm imagining grass rustling) with hunting like behaviour.

Yes, I'm quite sure it relates to hunting behaviour too but what? I have a cord tied to my bathroom door handle. The cord doesn't move but my cat plays with it a lot. I've seen photos of cats playing with cords (as the internet is full of cat photos). I've even seen a photo of a cat happily playing with a rope tied to a horse's halter while the horse just stood there.

Thanks, Geraldo. I understand that any answer to my question would be very complex. I'm not a scientist, of course, but I've read articles dealing with ethology in wild and domesticated animals (which ones I could without a paid subscription to some of the journals). I can understand not all behaviour would be related to hunting but certain play behaviour, while some fit a range of mammals, many are specific to that species only. Do you have any suggestions that could point me to certain publications about cognitive ethology? Or are you allowed to do so?

I've never heard, read or seen photos of other animals attracting to a hanging cord. I'm curious how and why it proves so attractive to cats but not other animals (as far as I'm aware).

Complex is better as far as I'm concerned. I read science and nedical journals for recreation so I prefer something not readily understandable to most people. I appreciate the link. Thanks.

Gregory Bateson talks about play behavior in Steps to an Ecology of Mind and in Mind and Nature; @GerardoFurtado is correct that play behavior is much more complex than it appears. Not all animals play, for instance, but some play with other species, e.g, cats. Think about that a minute; this is not a simple evolved behavior.

jlawler, I fully realise it's not simple evolved or hard-wired behaviour. I'm not trying to imply it is in my question. But all animals are hard-wired with certain behaviour along with the ability to learn new ones. Often, though not always, new learned behaviour stems from or is related to other more hard-wired behaviour. I'm looking for the background of the dangling cord play (if there is one). Thanks for the book suggestion. Even if my question gets side-lined, I'm grateful for the chance to learn more on my own. I never take anyone's answer as 100% correct without  checking further.


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What is this beetle looking fly creature?
I found this fly in my back garden that looks like a beetle with wings and it hovers.

]1
]2

What is it?

@Remi.b I did add what environment I found it and where in the world I found it

Did you know that all beetles do have wings, and many of them do fly? I think it's going to be hard to identify based just on that picture, since it is quite blurry, but who knows, there are some masters here. It's almost certainly a beetle of some kind, though.

I got a clear video, shame you can't post videos.

It's slightly frowned upon because StackExchange likes to have everything contained on this site where possible to preserve the content of both questions and answers, but in this case I think it would be fine to link to a youtube video, or some other video service or video-to-gif host. Just if you do so, please don't remove it after you get an answer. If someone is able to answer your question they can put a high quality image in their answer.

It is of course it is difficult to tell exactly from the quality of the image, but with mandibles of that size relative to the body (approx. 20-25% of total length) it is very likely to be a male Stag Beetle Lucanus cervus, the mandibles will grow much larger. The antenna sticking out from the side of the head just in front of the eye matches your photo (note: in the image below it looks like two on each side, but it is just the shadow in the photo)

Picture from Wikimedia commons https://commons.wikimedia.org/wiki/File:Lucanus_cervus_1922.png
They can be found flying at dusk, and are found in the SE of England from late May to August.
If you are looking for a good insect ID book, I can recommend "A comprehensive guide to Insects of Britain & Ireland" by Paul D. Brock, published in 2014


text:
How is the probability of Rh type inheritance calculated?
I found somewhere on the Internet that, if parents are both Rh-positive, their children have 93.75% chance of being RH-positive and 6.25% chance of being RH-negative.
My question is: How is this calculated?

There are four possible parental genotype combinations (R = Rh+ allele, r = Rh- allele):
m  f
RR RR
Rr RR
RR Rr
Rr Rr

Only the last can produce Rh- offspring. The probabilty that the Rr Rr combination leads to a rr genotype in the F1 generation is $1 \over 4$. Since there are four combinations, the probability that the Rh+ parents are Rh Rh is also $1\over4$. Thus the probability of the offspring to be Rh- is $${1\over 4} \cdot {1 \over 4} = {1 \over 16} = 0.0625$$ Thus, the probability of Rh+ in the F1 generation is $$1 - {1 \over 16} = {15 \over 16} = 0.9375$$
Note: This is the rationale behind the values you state in your question. I am pretty sure that these four combinations are not equally distributed in a population. You would have to need to know the allele frequencies.


text:
What's going on when roots turn green and grow into the air?
You're looking at a hibiscus and an orchid growing in the same pot. I'm curious why the hibiscus started growing green roots into the air. Or am I looking at a third plant that somehow made its way into the pot?
July 27th
All it does is branch and get longer.

There are no leaves and the shoot doesn't thicken or turn to bark.

A new sprout appears every few days.

Is the hibiscus so root bound it's trying to escape the pot?

July 9th

While I'm not familiar with hibiscus (too cold & dry where I live), it's perfectly normal for many plants to spread by underground roots, which spread out from the parent plant a bit, then send up a new shoot.

I found this article online that does describes hibiscus plants as having a "spreading" type root system that will also form new shoots away from the parent plant ... http://homeguides.sfgate.com/type-root-hibiscus-have-49085.html
I also noticed that you have an attached orchid with aerial roots attached to the hibiscus plant.  If you are misting the orchid roots periodically, you may be dampening the surface soil in the pot and encouraging the growth of shoot forming spreading roots on the hibiscus plant to develop and grow upward.

I haven't seen any leaves on the green shoots. And the stems are flimsy. Wouldn't a new plant look something like a seedling? I do water the orchid every day, and the shoots started a few months after adding the orchid to the pot. I had been pulling out the shoots but I'll let them grow now to see what happens.

See if they develop leaves.  It could also be a combination of new environmental conditions (including low light) that would cause them to look like they do.


text:
Taxonomic clasification of BLAST output
I am working with Next Generation Sequencing. I BLASTed the bovine de novo assembled contigs to the NCBI nucleotide database. I got a matching with a lot of species i.e. different kind of bacteria, viruses and mammals. I want them to group in a logical way i.e. all the bacteria in one group (bacteria group) similarly viruses and mammals. This is hard to arrange manually, can anybody help how I can arrange my vast number of species into some logical grouping. Thanking in anticipation.

I think this question is missing a few key details for it to be answerable. Do you have the NCBI IDs? A "logical way" will depend on protein context (membrane or globular, what is the enzymatic function, etc). Would the super-kingdoms be enough resolution?

This is basically metagenomics.
Congratulations, you already did the most time consuming step.
There are several ways to go from there, but I will talk about the one I know best.
There is the metagenomic analysis tool MEGAN. It can read your Blast Output, if it is in the correct format (normal XML or tabular) and will automatically do what you want.
For a start, just use the default values, for more help you an then go to the Community Website of MEGAN for help.
Analysing your data may take a little, depending on how many contigs you have. But if you were able to blast them in reasonable time it should be no problem. As I said, you are through the most time consuming step already.