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Models of quorum sensing for multi-agent systems
Quorum sensing is a system of stimulus and responses correlated to population density that is used by bacteria to coordinate gene-expression. I am looking for a simple computational/mathematical model of quorum sensing that abstracts away from the details of the mechanism implementing it inside the agent, but keeps the key inter-agent properties like diffusion rate, range, and timing.
Is there a standard abstract mathematical model of quorum sensing used by biologists?
I am not interested in the particulars of a specific organism, but would like a general model I could apply to capture the 'gist' for any organism that relies on quorum sensing for part of its behavior.

Bernardini et al. (2007) provided an extension to P-systems incorporating the basics of quorum sensing, and Romero-Campero & Pérez-Jiménez (2008) have used their approach to model bioluminosity in vibrio fischeri. This approach is conceptually appealing to me, but that is because I am predominantly a computer scientists. Although P-system can be used for modeling biological systems (Ardelean & Cavaliere, 2003), they still feel fundamentally computer-science-y and are typically not published in orthodox biological venues. This makes me suspect there is a more standard approach among biologists, probably via dynamic systems and diffusion equations.

It may not be what you are looking for, but there is a quorum sensing model available here at the EBI repository.

I found this paper[1], which might be relevant; it uses is a more chemically inspired approach. Another paper[2] also might be interesting, it takes a more dynamical systems approach.
My personal instinct would be to use ordinary differential equations: generate a population of cells in random positions, assign each cell levels of any relevant molecular species, and come up with a list of ODEs that describe the rates of change of the species in a particular cell in terms of gene expression, degradation, and diffusion. You should then be able to simulate the time evolution of the system just by solving the (large) system of ODEs given your initial conditions. Something like the approach in this paper[3] (read the supplemental info), only your cells would move around during the simulation, rather than remaining still as part of a tissue. The implementation would get thorny, because you would have to accommodate the motion of the cells as you solve the ODEs. I imagine that this could be accomplished by simply treating the initial positions of the cells as part of the system's initial conditions and then defining the ODEs that govern the rate of change in each dimension (either randomly, or perhaps they move in a coordinated manner) so that this aspect of the system can evolve during the integration.
References:

 Rai N, Anand R, Ramkumar K, Sreenivasan V, Dabholkar S, Venkatesh KV, Thattai M. 2012. Prediction by promoter logic in bacterial quorum sensing. PLoS computational biology 8: e1002361.
 Chiang W-Y, Li Y-X, Lai P-Y. 2011. Simple models for quorum sensing: Nonlinear dynamical analysis. Physical Review E 84.
 Lubensky DK, Pennington MW, Shraiman BI, Baker NE. 2011. A dynamical model of ommatidial crystal formation. Proceedings of the National Academy of Sciences of the United States of America 108: 11145–50.

Since the accepted answer is nearly a decade old, I'm adding a new answer to address a recent piece of research that presents a good framework for modeling quorum sensing over small distances.1
First, the authors consider two types of signal diffusion systems.

Absorbing -- the signal molecule is imported into the recipient cell, where it interacts with its receptor to induce a response. This process is irreversible (the signaling molecule is "used up" once imported). Many peptide-based quorum sensing systems found in Gram-positive bacteria are absorbing systems.2
Non-absorbing -- the signal molecule interacts with a receptor on the surface of a recipient cell, inducing some response cascade. The signal then dissociates and diffuses into the intercellular space, where it can interact with other recipient cells. Examples of non-absorbing systems include autoinducer networks in Vibrio species 3 and acyl-homoserine lactone quorum sensing systems in Proteobacteria.4

Next, they made three modeling predictions, and tested each prediction in synthetic communities grown in microfluidic chambers. Their model organism, B. subtilis, was transformed with signal-recipient gene pairs from both absorbing and non-absorbing systems, though the bulk of their paper is spent discussing the less well-studied absorbing modality.

Signal response in signal-receiving cells ($Y$) is inversely proportional to their distance from the signal source boundary ($x$) and is a function of the communication range ($\lambda$). For a absorbing systems, the authors define $\lambda$ as "...the distance from the boundary of signal producers over which the signal response reduces one order of magnitude ... on a natural log scale". Unsurprisingly, they predict absorbing systems to have much shorter signaling ranges than non-absorbing systems, assuming a high signal uptake rate among recipient cells.

$$Y(x) \propto e^{-x/\lambda}$$

In absorbing systems, communication range ($\lambda$) is a function of signal diffusion rate ($D$) and signal uptake rate ($\alpha$). Using the Stokes-Einstein equation 5 and an estimated radius of 0.5 nm for small peptides, the authors estimate that signaling molecules diffuse through water at a rate of ~
400 μm2s-1.
$$\lambda ≅ \sqrt{\frac{D}{\alpha}}$$

In both absorbing and non-absorbing systems, the signal concentration (and thus the signal response $Y$) is related to the width of the cluster of signal-producing cells ($W$). Simply, more cells produce more molecules. For non-absorbing systems, the signal concentration is unbounded. However, the concentration of signaling molecules in absorbing systems saturates when the cluster radius is larger than $\lambda$.

$$Y \propto W^2$$
The authors find experimental justification for each of their model predictions (I suspect the predictions wouldn't have been included in the paper, otherwise). For the nitty-gritty math behind their models and other assumptions / simplifications, read Section 2 from the supplementary discussion, Mathematical modeling of quorum-sensing designs. An excerpt:

While bacterial communities consist of cells, we use a continuous framework to model the community. That is, instead of modeling cells that produce and receive signal molecules explicitly, we simplify the model by assuming a constant production rate per unit volume and a decay rate per unit volume of the community.

References

van Gestel J, Bareia T, Tenennbaum B, Dal Co A, Guler P, Aframian N, Puyesky S, Grinberg I, D'Souza GG, Erez Z, Ackermann M, Eldar A. Short-range quorum sensing controls horizontal gene transfer at micron scale in bacterial communities. Nat Commun. 2021 Apr 19;12(1):2324.
Neiditch MB, Capodagli GC, Prehna G, Federle MJ. Genetic and Structural Analyses of RRNPP Intercellular Peptide Signaling of Gram-Positive Bacteria. Annu Rev Genet. 2017 Nov 27;51:311-333.
Papenfort K, Bassler BL. Quorum sensing signal-response systems in Gram-negative bacteria. Nat Rev Microbiol. 2016 Aug 11;14(9):576-88.
Schuster M, Sexton DJ, Diggle SP, Greenberg EP. Acyl-homoserine lactone quorum sensing: from evolution to application. Annu Rev Microbiol. 2013;67:43-63.
Miller CC. The Stokes-Einstein law for diffusion in solution. Proc Roy Soc. 1921;106:724.

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How to prevent protein precipitation?
I'm trying to label a protein with fluorescent dye (TMR succinimidyl ester), but having trouble getting the protocol to work.
The protein seems to be stable in distilled water at a the recommended concentration of about 2mg/ml (determined by OD280 with an absorption coefficient calculated from its sequence).
However, the protocol calls for the addition of 1:10 1M sodium bicarbonate to raise the pH to ~8.5. When I perform this step the solution immediately turns cloudy. I have also encountered this precipitation problem when dialyzing against PBS.
What steps can I take to get around this? I assume a lower concentration of protein might prevent precipitation, but I have read that the labeling reaction becomes very inefficient below 1mg/ml.

What is the pI of the protein? If you get near that one you'll usually precipitate the protein.

Thanks - literature says pI can range between 7.1 and 7.4, so this is probably the issue.

Is there a standard technique to get around this? I guess I could dilute a bunch, adjust pH then reconcentrate? Or would I be better off just looking for another labeling chemistry?

There are a lot of possibilities here - i) Depends on your protein, what is it? ii) You should be using molar concentrations for everything, pls make the conversions.

that sounds like a good thing to try.  also changing salt concentration , mono and di cations can help.

Alas, the great problems with protein formulation. I assume that the labeling chemistry forces you to use the 8.5 pH. (I don't think this is necessarily true since succinimidyl chemistry does work at pH=7.2 and the NHS ester is fairly unstable above pH=8.6)
We usually tackle this problem entirely by brute force ie. testing multiple buffer condition with different bases and different salt concentrations. First attempt would be to try out all of the Good's Buffers notablely HEPES, TRIS, MOPS, Tricine, Maybe you should look at both zwitterionic buffers and non-zwitterionic buffers. In your case, the succinimidyl is vunerable to primary amines so avoid things like Tris/Glycine.
The second thing to test would be various salt concentrations. Since you're already dumping in Sodium Bicarb, NaCl should be great. Unfortunately, this is where things get tricky since it is hard to know if your protein precipitates at low salt or high. A test from 20 mM, 50 mM, 100 mM, 150 mM, 200 mM, 500 mM should cover most of the interesting regimes.
Alternatively the sudden change in the ionic environment around your protein may be causing it to precipitate. You probably should dialyze or purified your protein in PBS to allow it to refold appropriately.

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Why do most breast cancers occur in women?
According to Korde et al. (2010):

Male breast cancer accounts for less than 1% of all cancers in men and less than 1% of breast cancers.

This raises the question: Why do most breast cancers occur in women?
Two plausible explanations I can think of:

A male is less likely to get breast cancer for anatomical reasons (such as a smaller quantity of breast tissue, or breast tissue that is less susceptible to cancer),
Women have higher significantly levels of estrogen, which is linked to mutations that cause breast cancer (see Cavalieria et al. (2006)).

Although, I have no evidence to suggest that either of these is predominant factor.

I agree that estrogen plays a very important role (among other hormonal cues). Another significant explanation that follows from your first example is the sheer quantity of female breasts to male breasts. While only some men have fatty breast tissue, all women do, and so the diagnoses are largely skewed by the anatomy. Something else to keep in mind is that women have breasts from puberty through the rest of their lives, while many men only develop them later in life.

There is another problem with breast cancer in men: Its usually not detected and searched for. Its probably happening more often than doctors think.

Interestingly, a greater proportion of male breast cancer is estrogen receptor positive (90%) than female breast cancer (80%)

Yes, this is mostly about estrogen. Most breast cancers rely on endogenous estrogen to sustain proliferation.
Some general reading: Cancer Medicine, Chapter 18
More in-depth reading: Endogenous Hormones as a Major Factor in Human Cancer
Requested summary of mentioned readings:
First of all, there is an established link between breast cancer cell proliferation and concentration of estrogens and progesterone, which is logical, because normal breast cells divide in response to those hormones (e.g. puberty, pregnancy, even luteal phase of the menstrual cycle). Secondly, the incidence of breast cancer in women correlates with major changes in their hormonal profile - girls and elderly women (i.e. women with lower levels of sex hormones) don't get breast cancer.
Many factors, that influence the risk of developing breast cancer are in fact tightly connected to the hormones' levels. For example - early age of menarche (or, more importantly, first ovulation, because physical activity at young age disturbs ovulation AND is protective against breast cancer) and Hormone Replacement Therapy raise the risk, early age of first full-term pregnancy or any form of artificial menopause (such as preventive oophorectomy for women with mutations in BRCA1 or 2) reduce the risk.
The first table from the book chapter lists known risk and preventive factors. The review article explains the same ideas, but connects them to other types of cancer (e.g. ovarian cancer) and suggests mechanisms, which might be the cause of those risk changes.

Can you summarize some important points of those links?

estrogen and prolactin are hormones that stimulate mammary development and growth of the breast tissue.  They greatly enhance the chance of cancer since that tissues is proliferating at a great rate.  Males do not typically experience these developmental phases.

This is a bad and poorly referenced answer. The age vs. cancer incidence for breast cancer follows essentially the same curve as every other adult cancer. There's no drop at menopause, and the highest incidence is in women over 70. There's a decrease in diagnosis in very elderly women, but this is seen in all adult cancers. Autopsy studies show us this isn't due to a magical protective age threshold, but different clinical choices due to age.

For two reasons: Women are

exposed to estrogen,¹ and
the lobules in a woman's breast go through 4 stages:

Type 1: prepubescent & Type 2: pubescent

Type 3: reproductive & Type 4: lactation lobules²

The sooner a woman progresses to Type 3 and Type 4 lobules, the lower her risk of cancer. An interruption of the progression from Type 1 to Type 4 lobules (such as with a late-term miscarriage or induced abortion) increases the risk of cancer, as cancer generally arises in Type 1 and Type 2 lobules.³
References

Miller, Katherine. Estrogen and DNA damage: The silent source of breast cancer? J Natl Cancer Inst 2003: 95:100-102.
Schwartz, Shires, Spencer, Principles of Surgery (McGraw Hill) Russo J, Tay LK, Russo IH. Differentiation of the mammary gland and susceptibility to carcinogenesis. Breast Cancer Res & Treatment 1982;2:5-73.
Daling JR, Malone DE, Voigt LF, White E, Weiss NS. Risk of breast cancer among young women: relationship to induced abortion. J Natl Cancer Inst 1994;86:1584-92.

"or induced abortion" Isn't a(n adult) woman already at phase 3 (or what does it mean)? According to the source 3 non-adult women are in the category of increased risk. Women above 30 have increased risk of breast cancer probably due to the same reasons as people have other types of cancer, though.

@rus9384 All adult women, regardless if they have ever been pregnant, have reached at least phase 3?

That was a question. I guess your responce is "no". But after the woman stops breastfeeding what phase does she turn to?

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Digital Genomic Footprinting for ENCODE
I'm reading over the ENCODE Nature papers, and one of the papers referred to is "Global mapping of protein-DNA interactions in vivo by digital" by Hesselberth et al[1].
Genomic footprinting is a massively parallel variant of DNAse I hypersensitivity screening, which I feel I have a good handle on, but I don't understand this paragraph from the beginning of the results (the troublesome part is in bold):

To visualize regulatory protein occupancy across the genome of Saccharomyces cerevisiae, we coupled DNase I digestion of yeast nuclei with massively parallel DNA sequencing to create a dense whole-genome map of DNA template accessibility at nucleotide-level. We analyzed a single well-studied environmental condition, yeast a cells treated with the pheromone α-factor, which synchronizes cells in the G1 phase of the cell cycle. We isolated yeast nuclei and treated them with a DNase I concentration sufficient to release short (<300 bp) DNA fragments while maintaining the bulk of the sample in high molecular weight species (Supplementary Fig.1). These small fragments derive from two DNase I “hits” in close proximity, and therefore their isolation minimizes contamination by single fragment ends derived from random shearing. Because each end of the released DNase I ‘double-hit’ fragments represents an in vivo DNase I cleavage site, the sequence and hence genomic location of these sites can be readily determined by sequencing (Supplementary methods).

There's a reference to another paper by Sabo et al.[2] about genome-scale DNase assays using microarrays in that paragraph that I'm reading, but if someone understands the biology well, I'd really appreciate an answer.

Hesselberth JR, Chen X, Zhang Z, Sabo PJ, Sandstrom R, Reynolds AP, Thurman RE, Neph S, Kuehn MS, Noble WS, Fields S, Stamatoyannopoulos JA. 2009. Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nature Methods 6(4): 283–289, doi:10.1038/nmeth.1313.
Sabo PJ, Kuehn MS, Thurman R, Johnson BE, Johnson EM, Cao H, Yu M, Rosenzweig E, Goldy J, Haydock A, Weaver M, Shafer A, Lee K, Neri F, Humbert R, Singer MA, Richmond TA, Dorschner MO, McArthur M, Hawrylycz M, Green RD, Navas PA, Noble WS, Stamatoyannopoulos JA. 2006. Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays. Nature Methods 3: 511-518, doi:10.1038/nmeth890.

Is it the emboldened section that is causing a problem? Or the previous sentence about yeast? (I can help you with the latter.)

The section in bold is what's confusing me.  The rest is provided as context.

After reading the paper cited I think the logic goes like this: DNAse I will create free ends at accessible sites in the genome. However shearing during subsequent DNA isolation is also a source of free ends, and these represent noise in the analysis. You have to put in a lot of energy to shear DNA to very small fragments, so I infer that mild shearing during DNA isolation is very unlikely to create a new end that is near to an existing DNase I-generated end. Therefore, under the conditions used, any small fragments are much more likely to have been generated by two closely-spaced DNase I hits. By limiting the analysis to these fragments the noise from shearing is minimised.
Now that I've written this answer it doesn't seem like much more than a rewrite of the emboldened sentence, but I hope it is helpful anyway.

This is very helpful.  I didn't understand what "random shearing" was, or how it would add error to the results.  If I'm understanding correctly, random shearing during processing of DNA is unlikely to generate fragments that are relatively short (300 bp), which means that the 300 bp fragments are, with high probability, coming from short segments of DNA that have been clipped by DNase twice.

Yes that's right. Large DNA molecules are easily broken by physical handling. The low-tech way of doing it is to pipette up and down but if you Google "DNA shearing" you'll find lots of companies selling equipment that use shearing to produce random fragments in a desired size range.

DNA shearing can also be accomplished by vortexing the sample. This is not something you normally want to do, however, such as when genotyping animals.


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How are DNA polymerase error rates measured?
It is well known that the first DNA polymerase, Taq, is quite error prone. Newer generation commercial enzymes that have either been isolated from different thermophile species or have been improved by recombination are less error prone. How are these error rates compared? For instance, if this is done by Sanger sequencing, the average signal will dominate in reading the output and so it will be very unlikely to pick up on errors by this method.

The Taq products could be cloned before sequencing. It's still complicated though, because the same error in two products could represent the same error arising de novo twice, or the propagation of a single error that arose in an early round of amplification.

This is why I was sceptical about a sequencing-based approach. I suppose the method described by Alan Boyd below is a functional approach, but this still masks synonymous mutations and therefore under-represents the true error rate.

According to their website New England Biolabs use a version of the approach pioneered by Wayne Barnes, as described in:

Kermekchiev, M.B., Tzekov, A and Barnes, W.M. (2003) Nucl. Acids Res. 31, 6139–6147

This is basically an assay for the mutation rate in a PCR-amplified lacZ (β-galactosidase) gene, assayed by transforming E. coli, plating on the chromogenic β-galactosidase substrate Xgal, and then scoring white colonies as mutated genes. Also according to NEB, Agilent Technologies use a similar mutational assay, but based upon the lacI (lac repressor) gene.

Thank you for the reference. This seems like the most pragmatic approach to this problem. Even though by design this method under-reports the error rate, it would be a consistent bias across polymerases.

It's possible that they have calibrated the mutational assay to a more rigorous approach somewhere along the line, but I'm just guessing. As you say, for them the relative fidelity is more important than the absolute value.


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Which enzyme catalyzes transcription and which translation?
My attempt:
Transcription - RNA polymerase
Translation - aminoacyl tRNA synthetase
I know that the ribosome almost runs translation, but I don't think ribosomes are enzymes, which is why I went with aminoacyl tRNA synthetase.  Is this right?

Depending on how specific you want your answers, you should define which steps you want the enzymes for. Transcription uses several enzymes, and Translation the same - including Ribozyme activity at the aminotransfer site in the Ribosome.

This would be a great time to look up what the 2009 nobel prize was awarded for.

Sorry, but you started on the right track. What you're looking for is called the central dogma of protein synthesis.
Genomic DNA is transcribed in the nucleus into messenger RNA (mRNA) by RNA polymerase. RNA polymerase is DNA-dependent; it needs a DNA template to make an RNA version of the message.
The messenger RNA moves into the cytoplasm where it gets translated by ribosomes into an a polypeptide (protein). Ribosomes are the enzyme that do the translating, and perhaps your confusion is because ribosomes are made up of both RNA molecules and proteins (a ribonucleotide complex).
Aminoacyl tRNA synthetases are the enzymes that make aminoacyl tRNAs (tRNA for short). These tRNA bring individual amino acids to the ribosome as the ribosome is extending the polypetide product of the mRNA message.

I read "the David" today,...rather elated "that's why I go with" Ligase! Easy as pie?! Just ligate what the first guess up above "aminoacyl tRNA synthetase" has shipped to your ribos'? "as a newbie" sure I don't get it...:-)


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Do fish break a water molecule to absorb oxygen?
How do fish separate oxygen from H20 & consume it? Do they break the water molecule and absorb  the oxygen only?

The answer to this, I reckon, is that they don't.
They use molecular oxygen (O2) dissolved in the water for respiration, where it acts as a terminal electron acceptor, just as we use molecular oxygen in the air for respiration. We can speak of the water as being oxygenated.
Water is split in photosynthesis, where reducing equivalents from water are used to reduce NADP+ (giving NADPH).
One of the great discoveries of biology, IMO, is that the oxygen formed in green-plant photosynthesis comes from water, not CO2.
Tricarboxylic Acid Cycle (Krebs Cycle) Rant
Despite claims to the contrary, most infamously by Racker (1976, pp 28 - 29) and Wieser (1980), but also by Madeira (1988) and Mego (1986) for example, water is not split in the tricarboxylic acid cycle (Krebs Cycle). Banfalvi (1991) also sails pretty close to the wind on this one.
That is, reducing equivalents from water are not passed down the respiratory chain, or in any way used to make ATP, or are in any way a 'source' of free energy.  Such claims, IMO, are nonsense.
The definitive answers to the Wieser (1980) paper are given by Atkinson (1981) and Herreros & Garcia-Sancho (1981). Both of these articles are models of clarity, and categorically refute the claims of Wieser (1980).  Nevertheless, as shown by the references above, the controversy surfaces periodically.
The only sources of reducing equivalents in the TCA cycle are carbon compounds, and the only electrons passed down the respiratory chain are those 'held' in C-H and C-C bonds (Herreros & Garcia-Sancho, 1981).  An ionization is neither an oxidation nor a reduction (see Atkinson, 1981) and neither is a hydration. Adding water to (say) a double bond does not make the compound any more oxidized or reduced.  As far as oxygen and electrons are concerned, and to generalize from a biological point of view, what is has it holds - except in photosynthesis.
As you may have guessed, the splitting of the water in the TCA cycle is a pet rant of mine.  Thanks for the opportunity of airing my views!
Edit 3
Found this one when searching Google (Brière et al, 2006).  In an invited review for the American Journal of Physiology (Cell Physiology) at that!

Finally, TCA cycle should also be considered as a water-splitting process generating oxygen for acetyl-CoA oxidation [they quote Wieser]

So now the TCA cycle is producing oxygen from water.  Wonders will never cease!
(end edit)
(end rant)
Edit 2
As rwst and Alan Boyd have drawn attention to, the concentration of dissolved oxygen in water is all important, and varies with (for example) temperature.
In air-saturated buffer at 25oC the concentration of oxygen (O2 molecules) is about 0.24 mM (0.24 μmoles/ml, or about 0.474 μg-atoms of oxygen per ml). [Chappell (1964)]. This figure decreases with increasing temperature.
Great question, BTW.
References
(Apologies for the incomplete Atkinson and Herreros & Garcia-Sancho references. I have a photocopy of these papers but have been unable to trace the full source. They are both in the 'Letters to the Editor' section of the February 1981 edition of Trends in Biochemical Sciences. They do not appear to be in Pubmed, or anywhere else on-line.  Has anyone ever seen these references quoted, or can provide me with a full source?.  I'll update if I find anything)

Atkinson, D.E. (1981) TCA Cycle Confusion.  Trends in Biochemical Sciences (February 1981 edition; full ref to follow)
Banfalvi,G. (1991)  Conversion of Oxidative Energy to Reductive Power in the Citrate Cycle. Biochemical Education, 19, 24 - 26  [see here] (pdf apparently free to all)
Brière, J.J., Favier, J, Gimenez-Roqueplo, A.P. & Rustin, P (2006) Tricarboxylic acid cycle dysfunction as a cause of human diseases and tumor formation.  Am J Physiol Cell Physiol, 291, C1114-20. [Pubmed]  [pdf]
Chappell (1964) The oxidation of citrate, isocitrate and cis-aconitate by isolated mitochondria. Biochem J., 90, 225-237.[pubmed]  [pdf]
Herreros, B. & Garcia-Sancho, J. (1981) TCA Cycle Confusion.  Trends in Biochemical Sciences (February 1981 edition; full ref to follow)
Madeira, V.M.C. (1988) Stoichiometry of Reducing Equivalents and Splitting
of Water in the Citric Acid Cycle.  Biochemical Education 16, 94 - 96 [pdf] (apparently free to all.)
Mego, J.L. (1986)  The Role of Water in Glycolysis Biochemical Education,  14, 130 - 131. (see here)
Racker, E. (1976) A New Look at Mechanisms in Bioenergetics.  Academic Press, New York.
Wieser (1980) Textbook Errrors: The splitting of water by the tricarboxylic acid cycle.  Textbook error or textbook omission? Trends in Biochemical Sciences, 5 (Issue 11), 284. [see here].  [pdf], apparently free to all.

Edit 4
I have not been able to locate the exact reference for the incomplete Atkinson and Herreros & Garcia-Sancho references cited above but, in response to this great question, I have put a copy of a very bad scanned version here
Another great reference to this controversy which I should have quoted is the
following:

Losada, Manuel
. (1978) Energy-Transducing Redox Systems and the Mechanism of Oxidative Phosphorylation. Bioelectrochemistry and Bioenergetics, 5, 296-310 [Science Direct].

The following is the relevant section, for those who do not have access:

A more complete version of the Racker reference quoted above by Losada (1978):
However, pyruvate has only 4 hydrogens to donate to 2 oxygens and with a P:O ratio of 3 should therefore yield only 6 molecules of ATP (Table 1.2). Where are the other 6 hydrogens coming from so that 15 ATP can be formed? The answer to this question gives us what I think is the key to the puzzle why nature has designed the complex acrobatic scheme of the Krebs cycle. Its major purpose I believe is to increase the energy yield by catalyzing cleavage of water.
There are three steps at which water enter the Krebs cycle. - one at the transformation of fumarate to malate an the other two somewhat more indirectly during the utilization of acetyl-CoA and succinyl-CoA. In the course of the Krebs cycle the hydrogens of these water molecules are separated from oxygen and are donated to DPN or to a flavoprotein (e.g., succinate dehydrogenase) and then transported via the oxidation chain of mitochondria as electrons and protons as we shall discuss later.
[Racker, E. (1976).  A New Look at Mechanisms of Bioenergetics, pp 5-6, Academic Press].
IMO, the last sentence of this quote is complete rubbish. (For DPN, read NAD. DPN, or diphospo-pyridine-nucleotide (or something close), is an old name for NAD)

It would also be worth noting that if the fish absorbed ONLY the oxygen, then all of the H2 would be racing out of solution in a gas before entering the atmosphere, implying that the water breathed by fish would eventually run out. :-)

Yes, and to emphasize it: gases can be dissolved in liquids like salts. They escape when the liquid is getting hotter (water bubbles when boiling) or when you put sugar into soda water, for example

@MCM, & rwst.  Yes, very good points.  I'll incorporate later, but feel free to edit

In the Antarctic Ocean the temperature of seawater can fall as low as -1.9 C. Because of the resulting high levels of dissolved oxygen in Antarctic seawater, fish of the family Channichthyidae (icefish) can survive without hemoglobin, relying entirely upon oxygen dissolved in plasma. They have numerous physiological adaptations which increase blood volume and blood flow to support their low metabolic rate.

@TomD This answer is a little research paper in itself. Thanks for taking the time in compiling such a comprehensive reply!!

Great answer (+1), but remove 'I reckon' from the first line; this isn't just a personal opinion!

so your answer could begin with "no, they don't break the water molecule plants do, fish don't"?

authors: ʇolɐǝz ǝɥʇ qoq


text:
What determines testosterone exposure in womb, baby's genetics or mom's body?
I read this article which has the following quote:

The ratio between index and ring finger is believed to be linked to exposure to the male hormone testosterone in the womb.

And I wonder what determines the amount of exposure to testosterone in the womb. Is it testosterone produced by the fetus itself, in which case the baby's own genetics is the answer, or does this exposure the article speaks of more likely refer to testosterone produced by the mother and exposed to the baby?

Fetal testis produces testosterone from cholesterol. There is a peak of production around 15 weeks of gestation (the "masculinization programming window"). So the genotype of the fetus can affect testosterone levels directly via effects on the biosynthesis of the hormone, or indirectly by defective regulation of the pathway's activity.
However, exposure to chemicals in the mother's environment is also thought to play a part in determining testosterone levels. The classic example of this is the phthalate esters used as plasticizers.

Scott et al. (2009) Steroidogenesis in the Fetal Testis and Its Susceptibility to Disruption by Exogenous Compounds. Endocrine Reviews 30: preprint freely available here.

It has long been evident that human fetuses produce the hormones that dominate their development in utero.  (Ref: Robinson et. al., J Clin Endocrinol Metab. 1977 Oct;45(4):755-61. Amniotic fluid androgens and estrogens in midgestation.)
There is a baseline increase in maternal testosterone during pregnancy regardless of fetal sex, and I can't find whether that is due to production by the mother's endocrine systems vs. transfer from the fetus.  But in any case transfer from the fetus dominates: A male fetus produces so much testosterone that the serum levels detectable in the mother's blood ranges up to 4 times the amount found in typical non-pregnant women!  (Ref: Meulenberg & Hofman, J Steroid Biochem Mol Biol. 1991 Jul;39(1):51-4.
Maternal testosterone and fetal sex.)


text:
Age-associated neurodegenerative diseases
Age-associated neurodegenerative diseases encompass Alzheimer's Disease and Parkinson's Disease. What other neurodegenerative diseases could be described as age-associated? Multiple Sclerosis? Brain tumors? What might be the criteria for defining a disease as age-associated, specifically in the realm of neurobiology?

Dementia with Lewy bodies (DLB): It is characterized anatomically by the presence of Lewy bodies, clumps of alpha-synuclein and
  ubiquitin protein in neurons, detectable in post-mortem brain
  histology.[1] Lewy Body dementia affects 1.3 million individuals in
  the United States alone.

http://en.wikipedia.org/wiki/Dementia_with_Lewy_bodies

Binswanger disease is a form of small vessel vascular dementia caused by damage to the white brain matter.[1] White matter atrophy
  can be caused by many circumstances including chronic hypertension as
  well as old age.[2] This disease is characterized by loss of memory
  and intellectual function and by changes in mood. These changes
  encompass what are known as executive functions of the brain.[3] It
  usually presents between 54 and 66 years of age, and the first
  symptoms are usually mental deterioration or stroke.[4]

http://en.wikipedia.org/wiki/Binswanger%27s_disease
To name the two with the highest prevalence after Alzheimer's and Parkinson's.

And what of MS, and a definition? Should age-association be defined by epidemiological studies or some other way?


text:
Which way to run BLAST?
I have a set of scaffolds from a genome assembly, and I want to align a collection of proteins from various species to it. I can do this using BLAST in two ways:

Create a BLAST database of the scaffolds, and run tblastn on it with
the proteins as the query.
Create a BLAST database of the proteins, and run blastx on it with
the scaffolds as the query.

Should both of these produce the exact same hits? Will there be any significant difference in running time between them?

Quick answer: use tblastn.
As a general rule, when comparing two datasets using BLAST, it is recommended to use the larger of the two sets as the database and the smaller as queries. The main difference is one of computational time. Blast is optimized for large databases.
You are also likely to get different hits. Blast's e-value is calculated based on the size of the database, among other parameters. Roughly, the e-value answers the question: "How many high scoring sequence pairs with X% of sequence identity and Y length would I expect to find in a database of size X by chance?". Your e-values could be artificially high if you use the protein sequences as a database. I am not sure about this, but there may also be differences in the way gap penalties are dealt with by tblastn and blastx.
That said, I would first try doing this using a tool specifically designed for the task. BLAST has no model for dealing with splicing and it is a pain to build gene models from BLAST results. To align protein sequences against genomic DNA I would use either exonerate (with the p2g model) or genewise. Both programs incorporate splicing models and will give you a decent prediction of the gene structure of your target genes. The following are extracts from each program's man page:
GENEWISE:

Genewise2 compares a protein sequence to a genomic DNA sequence,
  allowing for introns and frameshifting errors.

EXONERATE:

exonerate is a general tool for sequence comparison.
GAPPED ALIGNMENT OPTIONS
-m | --model
protein2genome
This  model  allows  alignment of a protein sequence to genomic DNA.   This is similar to
                       the protein2dna model, with the addition of modelling of introns and intron phases.  This
                       model is simliar to those used by genewise.

In general, genewise gives slightly better results but is much slower and cannot deal with multi fasta files. It is best when you know that your query protein will align against a specific nucleotide sequence.
Exonerate is fast but uses some heuristics that can give slightly worse results in some cases. Personally, I use exonerate to get my hits and then, if necessary, refine the gene model using genewise. In most cases, exonerate should be enough though.
EXAMPLES:
exonerate -m p2g -q proteins.fasta -t scaffolds.fasta > output.txt
genewise -pretty -pep -gff single_prot.fasta single_scaff.fasta > output.txt

Thanks for your response. I'll be using the BLAST results to construct a "hints" file for use with the Augustus gene prediction program, so this isn't generating my final gene model. That said, it still might be better to use one of the programs you mention.

If you want to go the BLAST way, use tblastn. I really recommend exonerate though, it knows about in-frame stop codons, splice sites, exons etc. Otherwise, you will need to filter out pseudogenes and duplications from your  BLAST hits.


text:
Preserved alpha complementation over evolutionary time?
Has the result of alpha-complementation ever happened via mutation through evolutionary time, and been preserved in modern day organisms?
In other words, has a functional gene product ever been split or terminated by mutation, exhibit alpha-complementation, and has since been preserved as a quaternary protein? This could be found out by comparison of proteins in closely-related species, but don't know of any specific examples. Has such a thing ever happened?

Would trans-splicing or chimeric transcripts qualify?

Those two are almost "the opposite" of the answer I was expecting. Two genes which "came together" through evolutionary time. Although it might be interesting to point it out in the answer, I am thinking along the lines of "one gene becoming two associated ones though evolutionary time".

Yes, there are cases where one gene has become two. Or, at least, where multiple  functions carried out by a single protein, the product of one gene, are carried out by distinct proteins, the products of different genes, in another species.
One case I have personally worked with is the bacterial SelB protein. It is essential for selenoprotein biosynthesis and has a dual function as an elongation factor and RNA binding protein. In eukaryotes, these functions are split between two proteins coded for by different genes. The Sec specific elongation factor EfSec and the RNA binding protein SBP2. See here [1] for more information.
Chimeric transcripts are also examples of this. One I happen to know of is the protein secp43 which in the mosquito A. gambiae is encoded by genomic sequences found on two different chromosomes [2]. Essentially, by two different genes.
The problem is that although we can easily find such cases of one protein's function being shared between multiple proteins in other species, or of one protein being coded for by multiple transcripts, it is hard to reconstruct the evolutionary history that gave rise to the current situation. So, whether the current situation has arisen because of alpha complementation or other causes is hard to know.
REFERENCES:
1) Lescure A, Fagegaltier D, Carbon P, Krol A., Protein factors mediating selenoprotein synthesis. Curr Protein Pept Sci. 2002 Feb;3(1):143-51.
2) Chapple CE, Guigó R., Relaxation of selective constraints causes independent selenoprotein extinction in insect genomes. PLoS One, 2008, 3(8):e2968.

Great answer, but I'll wait to see if anyone has any evolutionary evidence of the described situations.

AFAIK, there is no way of knowing if alpha complementation was involved. We can only infer the ancestral situation from what is available today and the specific mechanisms by which genes were split cannot really be seen.


text:
Are there any strictly chloroplast/mitochondrion-residing ribozymes?
A simple question that had occurred to me. Considering the small doubt of transcribed genes in both organelles, I would doubt it, but are there any known ribozymes strictly found in either mitochondria or chloroplasts?
UPDATE: Actually, I just thought of rRNA acting as a peptidyl transferase in mitochondrial ribosomes... Any other ideas?

can't we consider ribosomes as colossal ribozymes ?

You've already mentioned rRNA. An interesting review (Tanner, 2006), outlines some more:

Group I Introns - self-splicing; "They are abundant in fungal and plant mitochondria..."
Group II Introns - some have been shown to self-splice; "...they are found in fungal and plant mitochondria, in chloroplasts of plants ... and especially in the chloroplasts of the protist Euglena gracilis."
RNase P - involved in tRNA processing, found in mitochondria

None of these are strictly found in mitochondria or chloroplasts. However, the paper goes on to describe VS RNA ribozyme:

The mitochondria of certain strains of Neurospora contain the Varkud plasmid (a retroplasmid), which encodes a reverse transcriptase, and a small, unrelated, RNA (VS RNA). The VS RNA is transcribed from circular or multimeric VS plasmid DNA by a mitochondrial RNA polymerase, and the resulting transcripts are subsequently site-specifically cleaved and ligated to form circular, 881 nucleotides long, RNA monomers. These monomers are then reverse transcribed and made double stranded to form the mature VS plasmid.
In vitro transcribed VS RNA precursors are cleaved and ligated by the RNA itself and this is presumed to occur in vivo as well. Of all the self-cleaving RNAs, the catalytic properties of VS RNA are the most poorly understood.

References

Tanner NK. 2006. Ribozymes: the characteristics and properties of catalytic RNAs. FEMS Microbiol Rev. 23(3):257-275.


text:
Is it more likely that the very first living organisms had a linear genome?
Is it right to assume that the first living organisms on earth had a linear genome? I base this on the fact that linear macromolecules are clearly much more common in nature that circular ones. To be honest, I can't even think of any naturally-occurring circular macromolecules that aren't already a part of current living organisms.
Were the very first living organisms more likely to have linear genomes? If so, when during evolutionary time did circular chromosomes originate?

I would say this is a question that might not be resolved yet.
Going back to the earliest days of DNA - a billion years ago - its hard to imagine circular DNA being the first sort to show up.  Its speculated that in the transition from RNA world to DNA world, early on each gene had a separate piece of nucleic acid coding for it which would not have been circular.  It's been proposed for example that RNA viruses might have been a next step to cellular life.  Although I can see an old electron microscopy reference, not it does not seem as if any RNA viruses with circular RNA have ever been found.  How the first DNA chromosomes came about and what they looked like seems unclear to me.
In any case, though not typical, its not unusual to find linear chromosomes in prokaryotes.  I could not find reference to archaea with linear chromosomes, but in prokaryotes, the link above points to the observation that even close relatives can have linear or circular chromosomes.

A remarkable property of the 8.2-Mb chromosome of S. erythraea was that, contrary to the expectations and the earlier data (Reeves et al., 1998), it proved to be circular. The chromosomes of its close relatives, Streptomyces coelicolor and Streptomyces avermitilis, are both linear, as is the chromosome of Rhodococcus sp. strain RHA1. These chromosomes are the largest in actinobacteria (8.7, 9.0 and 7.8 Mb respectively) and comprise some of longest DNA molecules in the prokaryotic world. In contrast, the shorter chromosomes of other actinobacteria are all circular.

It seems that linear vs circular genomes are a 'lifestyle' choice or connected to selection critera we don't understand yet:

Hence, it was tempting to speculate that the linearity of streptomycetal chromosomes was somehow linked to and perhaps beneficial for the maintenance of these extremely long DNA molecules, even though it resulted in the instability of their termini. This idea has been contradicted by the discovery of equally long but circular chromosomes in the acidobacterium Solibacter usitatus (9.97 Mb), δ-proteobacterium Myxococcus xanthus (9.1 Mb), cyanobacterium Trichodesmium erythraeum (7.8 Mb), and, now, in the actinobacterium S. erythraea.

I really doubt the instability of the chromosomal terminii is a real consideration - there must be genes that help maintain those, just as there are in eukaryotes.  S coelicolor is a soil bacterium that is so common most people can find it in the dirt right outside their door - its not hard to live with a linear chromosome as a bacterium.

Nifty! Learn something new every day.

It is hard to give an answer to this question that is not just speculation.  We can be reasonably confident that the most recent common ancestor of bacteria and archaea had circular genomes.  However, we currently have no way to get any conclusive evidence earlier than that.  3 billion year old DNA doesn't fossilize.  So it's just speculation what DNA looked like back then.
On the other hand, my understanding is that most experts think that RNA genomes predated DNA genomes.  These RNA genomes would be linear.


text:
Translate DNA to Protein
Assuming the sequence shown is read left to right, what is the sequence of the protein produced?
sequence: 5’-ATGTACTTCCATCTGGAATAG-3’
MY ATTEMPT: I know RNA is synthesized 5 to 3.  This is throwing me off because if we read the above sequence from left to right then we are going to synthesize 3 to 5.  If I ignore this for now, I get an mRNA of 3'-UACAUGAAGGUAGACCUUAUC-5'  from this i could easily get the protein looking at a mRNA to protein chart.  Is this correct?

Since the sequence starts with an initiation codon and ends with a stop codon I think it's safe to conclude that this is the coding strand.  The coding strand has the same sequence as the transcribed RNA (except T>U). This is because it is the other strand of the DNA that is the template for the synthesis of an RNA. The RNA is indeed made 5'>3', but the template it uses has to run in the opposite direction.
5’-ATGTACTTCCATCTGGAATAG-3’
3'-TACATGAAGGTAGACCTTATC-5' template strand

5'-AUGUACUUCCAUCUGGAAUAG-3’ mRNA transcript
3'-TACATGAAGGTAGACCTTATC-5' template strand (read from left to right by the polymerase)

and the sequence of the protein is MetTyr...etc

but this way the sequence i gave is not being read from left to right.  you read the complement from left to right

Depends what you mean by "read". The polymerase moves from left to right reading the bottom strand as template and making the RNA from left to right. You read the top strand from left to right as you look up codons in a genetic code table. You use the top strand for this because it is this DNA strand that has the same sequence as the mRNA.

EMBOSS has a tool for doing this:
http://www.ebi.ac.uk/Tools/st/emboss_transeq/


text:
Is there an evolutionary reason for the 5 electron transport complexes in plants and animals?
The electron transport chains of both the light reactions of photosynthesis (in plants) and oxidative phosphorylation (in animals) both contain 5 complexes including ATP synthase, as shown below.

Image Source

Image Source
Is this coincidence, or does this possibly suggest that both chloroplast and mitochondrion precursors derived their energy-obtaining mechanisms via an ancient evolutionarily-related metabolic pathway which diverged?

Your latter assumption is the best we have so far, to my understanding.
Here are a few excerpts from "Early Evolution of Photosynthesis" published in Plant Physiology, October 2010 (emphasis mine):

There is suggestive evidence that photosynthetic organisms were present approximately 3.2 to 3.5 billion years ago...
Overwhelming evidence indicates that eukaryotic photosynthesis originated from endosymbiosis of cyanobacterial-like organisms, which ultimately became chloroplasts (Margulis, 1992). So the evolutionary origin of photosynthesis is to be found in the bacterial domain.

And then there's the abstract from this paper: "Do photosynthetic and respiratory electron-transport chains share redox proteins?"

In purple nonsulfur bacteria and cyanobacteria, there is close interaction between the photosynthetic and respiratory electron-transport chains, which share identical redox proteins.

Purple bacteria and cyanobacteria are some of the oldest known lineages (>3BY, whereas Mitochondria parallel Eukaryotic origins at about 1.4BY - and the endosymbiosis which created Chloroplasts probably came after [plants have both Chloroplasts and Mitochondria, whereas most Eukaryotes just have Mitochondria]), and since the respiratory chain and photosynthetic chain share identical proteins in cyanobacteria and purple bacteria it's not a huge leap to assume that - yup - the 5-protein structure is probably the template used by both Chloroplasts and Mitochondria because of a common source.

The second paper and associated paragraph is EXACTLY what I was looking for. +1, thanks.

Well, according to the endosymbiosis theory both mitochondria and chloroplasts derive from ancestral bacteria that invaded/were phagocytosed (fancy word for eaten) by eukaryotic cells.
So, the electron transport chains of both mitochondria and chloroplasts would indeed share a common bacterial ancestor.


text:
Similarities Between Cells?
Which of the following are usually identical between a lung cell and a brain cell, from the same person, assuming that they are normal (non-cancerous) cells?  Circle your choice(s).
a.  Size
b.  Shape
c.  Specific proteins found in the cell
d.  Specific genes in the cell’s genome
e.  Which genes are expressed
f.  Which parts of the DNA are methylated
g.  The specific DNA sequence of chromosome 12
h.  All of the above
i.  None of the above

I said only D and G because all cells have the full genome.  The difference between cells is how the these genes are expressed.  All of the other options are results of different amound of gene expression.  Is this the correct thinking?

Seems right. I would choose those answers as well.

I would also go for d and g. All the others may vary. Strictly speaking, you may even have random, point mutations that have changed the genomic sequence between two given cells so even d and g might not be true in some cases.
I would also like to point out that recent evidence implies that differential expression of non coding, regulatory RNA molecules may play as, or even more, important a role as differential expression of proteins. See the ENCODE papers or here for a recent review.


text:
Since Darwinian times, has there been any striking/notable effects of evolution on humans?
I understand that evolution is constant process that acts on a population in successive generations. Thus, it is obvious that evolution is happening. However, I'm curious as to the  stricking examples of evolution that have occurred since Darwin's publication of the theory.
Essentially, how different are we now from the humans at the time at which evolution was conceived?

Well, "On the origin of species" was published in 1859. If we assume that for humans a generation is approximately 20 years, that means that there have been between seven and eight generations since 1859. That is nowehere near enough time to observe evolutionary changes.
So, in answer to your question, not very different at all.
EDIT:
I think I need to clarify my answer. When we talk about a species evolving or a species being different today than it was X years ago, we are referring to the species as a whole. Of course evolution is an ongoing process, selective pressures are shaping our gene pool constantly. However, in order to say that humans are different today to those of 1859, we would need to show that the prevalence of particular genotypes has changed. That a specific trait (a gene or a mutation in a gene) has become "fixed", or, at the very least, that it has spread to a significant percentage of the population.
@niallhaslam's answer gives a link to a wired.com article about genetic resistance to HIV. This is not something that has recently evolved in response to HIV but is the result of an ancestral mutation. The article itself states that:

Using formulas that estimate how long genetic mutations have been
  around, researchers have discovered that the mutation dates to the
  Middle Ages.

Granted, this could be a good example of selection in action. If, after many, many more generations, this mutation has spread to the majority, or a significant percentage, of the population, we could point to it as an example of how humans have changed under the selective pressure of HIV infection. In order for this to happen, HIV will have to become common enough that having a resistance to is beneficial to a very large subset of humanity. I would expect to see such selective pressure in, for example, countries like South Africa where 12% of the population is HIV positive. Such pressure, however, will be negligible in countries with lower infection rates. In the US, for example, a recent study found HIV incidence among persons aged 13 years and older to be 42,200–54,000. Since the US has ~312 million people, 54,000 represents ~0.02% of the population. This will not provide enough of a selective pressure to observe differences in the short term evolutionary scale.
We do not, in fact, "evolve quickly in response to parasites viruses etc". Pathogens may apply selective pressure yes. But this is not a quick process. In any case, we do not evolve in response to them. Mutations occur, randomly usually, and if they confer an advantage they may be selected for. Said advantage may be because they confer resistance to disease but even then, the original mutation was not "in response" to the pathogen, However, such selection happens over many successive generations and will spread relatively slowly (quickly by evolutionary standards perhaps, but still slow for us, and certainly slower than 7 generations) across the population. The same holds true of epigenetic changes. Even if they can (as now seems likely) be transmitted down the generations, any selective advantage they confer will still act at the generational level.
So, while we are, of course, constantly evolving, there are no significant differences between the humans of today and those of Darwin's times. Sure, some genotypes may exist today that did not then and vice versa. These, however, are not representative of the species' genome. They may become so after many generations but, even if they exist, they have not had time to propagate through the gene pool and cannot be taken as evidence that H. sapiens as a species is "different" today.

In my opinion you are taking a very narrow view of what evolution means. However, with your clarification I have removed my downvote.

I am not expressing an opinion on evolution as such. Simply on what it would take to be able to say that a species has changed (has "evolved" as much as I hate that term in this context) since date X.

I would say that a species has changed as soon as the frequency of some gene has changed. Thus all species are always changing, and no generation is exactly like the previous one.

Even that is hard to define. For a species to have "changed" that change needs to be persistent. Otherwise it may just be a random fluke in a specific generation that will not survive to the next. Unless the frequency of a given mutation remains different over a few successive generations I do not consider that the "species" has changed.

We're constantly evolving resistance to disease, for example HIV.
It's reasonably fair to say this is still a contentious issue, but I think the point is that we still evolve quite quickly in response to parasites, viruses etc.
Another answer, though not strictly Darwinian is our epigenetic response to things.

Yes, the epigenetic, or Lamarckian, response is important +1. The environment - air/water quality, physical activity, availability of energy-dense food, antibiotics and other drugs - have all exerted influences on the epigenome.

But are epigenetic changes evolution?

@Alan Boyd - Epigenetic changes have been tracked across multiple generations, so they are inheritable. Obese mice will sire offspring who weigh more despite given the same diet and exercise as a control mouse. The effect can last for several generations, but that's a good question. I want to say yes, since evolution really just relies on inheritability and selection - but I'm not sure if epigenetic modifications could become permanent.

In this paper the authors identify many human genes that are under recent positive selection pressure, that is to say where natural selection is acting to promote the spread of certain genes.

They are indeed recent. The authors claim that the most recent changes were ≈6,600 years ago. While very recent indeed from an evolutionary point of view, they are still slightly older than Darwin :).

@terdon: Unless I'm missing something, isn't that 6,600 an estimated average age?  They are discussing several hundred different genes, some may be more recent. Furthermore, as they say, the timeframe is not precise and may only indicate when the gene became common.

I am just pointing out that the time frame here is not of the same order of magnitude. They show no evidence for changes that have become fixed in the last couple of hundred years. I only skimmed the article though, so please let me know if I am wrong.

I agree that they don't appear to produce specific evidence of that any of their examples are in the 200 year time frame. However, I don't think there's anything in the paper that precludes some of them being very recent.

Nor do they offer any evidence that they are very recent so I see no reason to assume that it is true. At least in my experience (in my defense, I did my PhD on comparative genomics), evolutionary changes simply are not observable in the kind of time frame (~7 generations) discussed here.

Fair enough. What would you say the minimum time frame is? Certainly there are plenty of examples of substantial changes happening in less than 100 generations.

Wouldn't presume to offer an opinion :). It is a very complex question that depends on many variables and I doubt there is one answer. It will also change depending on the level of stress (ice ages, disease pandemics and the like) that a species is being subjected to.


text:
Patch-Clamping Neurons Resources

Are there any lectures available on Patch-Clamping?
Were can I find a mathematical model of Patch-Clamp? (that can be easily implemented in matlab).
I have found some step-by-step protocols on (Springer book site) but nothing to useful--I am setting up a new rig. Where can I find protocols that have worked and have been tested?

"The Axon guide for electrophysiology & biophysics laboratory techniques" is a very good starting point, albeit a bit biased towards Axon instrumentation. The book used to be hosted and freely downloadable on the Axon Instruments website but since they have now been acquired I cannot seem to find an official link anymore. However many other websites still host it (I won't directly link to them, as I am not sure about the licence of the book. Anyway, again, it used to be available for free).

That is one of the basics of neurophysiology. You will find video lectures on youtube. 2. See GHK (Goldman-Hodgkin-Katz) model

@nico : could you perhaps convert your comment into an answer? This question may not survive. The question is quite broad, but your comment is equally broad and is quite apt. I like it!

@ChrisStronks if nico doesn't respond then we can paste the comment and post it as community wiki

@WYSIWYG I didn't know that was possible?! Interesting! (I'd like to know more about that - something for chat:-) Anyway, I would definitely prefer your suggested option above waiting for the question to be deleted, which will be anytime soon

@ChrisStronks well, the question is on hold now...


text:
Tubing connector identification request
this may not be on topic but I'm hoping someone here can tell me the name/manufacturer of the connectors used with the thin teflon tubing in this picture:

Try looking for "Luer valves" or "Luer fittings".
For instance, we buy this kind of supplies from WPI.

Thanks, but I don't believe these are Luer fittings - as I understand it they are some type of compression fitting, you can push the teflon tubing through to the desired length, then screw tighten the fitting to seal it in place.

@zephyr: aren't those the ones on the bottom right of the link in the answer (not sure)?

hmm not sure, they do look similar. Looking at the kit contents link though I don't see anything that sounds right.

I think this is what I'm looking for: http://www.westernanalytical.com/pdf/VLp5-8.pdf


text:
Average number of gene products in (a) eukaryote(s)
Due to alternative RNA splicing, it isn't uncommon to ultimately find multiple gene products expressed from one gene in eukaryotes. I'm looking for a reference value for the average number of final gene products expressed per gene for:

... a particular eukaryote (preferably humans).

This can't be too hard to do for one species like humans. I would expect the following formula to provide me with a rough answer. Is this correct?
(number of distinct proteins + numbers of distinct non-translated RNAs) / number of genes

... all eukaryotes as a whole.

This one is slightly more problematic.

Are you referring to protein products only? Also, many alternative splicing events do not affect the protein but the untranslated regions (UTRs).

I'm looking for protein products as well as non-translated RNAs.

One answer can be found in the UniProt FAQ:

What is the human complete proteome?
In 2008, a draft of the complete human proteome was released from
  UniProtKB/Swiss-Prot: the approximately 20,000 putative human
  protein-coding genes were represented by one UniProtKB/Swiss-Prot
  entry, tagged with the keyword 'Complete proteome'. This
  UniProtKB/Swiss-Prot complete H. sapiens proteome (manually reviewed)
  can be considered as complete in the sense that it contains one
  representative (canonical) sequence for each currently known human
  gene. Close to 40% of these 20'000 entries contain manually annotated
  alternative isoforms representing over 15'000 additional sequences ...

http://www.uniprot.org/faq/48
So, we have 20,000 genes and 35,000 products yielding about 1.75 gene products per gene. Alternatively, the 8,000 genes undergoing alternative splicing give about 2.88 proteins per gene.

I thought it was much higher than this! More in the region of 100's of thousands, because the majority of genes have at least 2 alternative isoforms, usually more... I'll try to find some evidence. If this is the case then I am surprised (also I'm not getting at you - I realize you have cited UniProt, arguably the authority on this!)

The number given here is very debatable... The sequences considered are only manually curated sequences - generally manual curation is way behind the actual data, so it is a bad idea to look at these numbers. For example, see ENSEMBL: http://useast.ensembl.org/Homo_sapiens/Info/StatsTable?redirect=mirror;source=www.ensembl.org , which mentions ~200,000 transcripts. And as I mention below, protein-coding genes are the easy part: ncRNA are much more difficult to count.

Like the number of genes dwindled in the years after 2000 from 100k to 20k, I expect such unconfirmed numbers to get more close to reality in some years, too.

@Bitwise, just wanted to point out that the number of transcripts is not necessarily correletaed to the number of different, mature, gene products. A lot of alternative splicing events only affect gene regulation (think spliced UTRs).

Well, there are a number of problems. First, the discovery of noncoding RNAs is relatively new and they are difficult to detect, so their number is unknown. In addition, it is unknown how many of them are functional. This has also made it very difficult to define what a gene is and thus made it difficult to count how many genes there are.
Protein coding genes, however, are much easier to deal with, and if you like you can enter any public protein database (at NCBI, for example) and easily query the number of distinct proteins.
Finally, the last problem is that with an organism like human, experimental methods are generally limited by sensitivity (might not detect proteins/RNA at very low concentrations) and the fact that you can't measure all possible cell types/conditions (many gene products will be cell type/condition specific).
Who said life is easy? Somehow things are always complicated in biology...


text:
What is the title of Darwin's paper on cellular structure?
I read somewhere that Darwin wrote a paper that dealt with cellular structure, but I've been unable to find the title or contents of the paper because Darwin wrote such a volume of material. What is the title of this paper or papers?
A google search does not turn up any helpful results, and a similar search in google scholar yields equally ambiguous results (at least to me, since I do not have a background in biology).

Darwin had written lots of papers which dealt with fertilization (which involves single cells), as he primarily dealt with the reproduction, continuation and thus evolution of a species, but these did not deal with cell biology specifically.
After a closer look at the complete list of all his publications, I found that he did have two cell-related publishings, specifically about the size of cells, one entitled Bees in Jamaica increase the size and substance of their cells, and the other, Bee-cells in Jamaica not larger than in England, in which he retracts the statement he had made in the previous article.
Ultimately, to answer your question, it seems as though none of his works dealt with cellular structures.

References

Charles Darwin. "Bees in Jamaica increase the size and substance of their cells". Journal of Horticulture (15 July): 305.
Charles Darwin. "Bee-cells in Jamaica not larger than in England." Journal of Horticulture (22 July): 323.


text:
Biology view on trait variability
In reading the annotated Origin... I have come to the following note by Costa on p. 168:

Again, modern biologists would disagree with Darwin's idea that especially well-developed traits vary to a greater degree than expected simply because they have been varying and undergoing selection in the past (as evidence by their considerable development)...

I am not sure I understand what the problem with Darwin's view is. From reading his work I understood that he, Darwin, is simply saying that traits that have been more recently acted on by natural selection would vary more than those that have been acted in the past and over a longer period of time (given that conditions remain relatively the same - I assume).
What is the modern view of biologists on this?
P.S. The excerpt to which this side note refers, follows:

In these remarks we have referred to special parts or organs being still variable, because they have recently varied and thus come to differ; but we have also seen in the second Chapter that the same principle applies to the whole individual; for in a district where many species of any genus are found - that is, where there has been much former variation and differentiation, or where the manufactory of new specific forms has been actively at work - there, on an average, we now find most varieties or incipient species.

Could you please clarify? Do you mean well-developed (whatever that means really) or recent? The two are not synonymous. Could you maybe include Darwin's original sentence that we modern types are supposed to disagree with?

I cannot really clarify it as I don't really understand what the author means. I can, and will, include the original passage to which this side-note refers.

In fact, I can't find what Costa is saying in Darwin's words, as it seems Darwin is saying complete opposite.

The variance of a trait's allele frequency can follow different trends over time depending on several factors such as whether one or several of the alleles are consistently selected for or the population dynamics. For example Disruptive Selection will tend to increase the allele variance. On the other hand Directional selection, or Stabilizing selection will tend to decrease variance by driving the allele frequency to one side of the distribution (in the first case) or by "cutting down" its sides in the second case. It is true that stabilizing and directional selection processes are more common especially under relatively stable environments. Therefore for the majority of cases, during the first phase of selection for a trait variance will most commonly decrease . This, however, is not a rule.
There are additional, rare, but from an evolutionary point of view extremely important cases where allele frequency variance can see a sudden "ballooning". Consider for example the case of selection processes after mass extinction events. Then, because of the sudden availability of previously occupied niches, genetic drift due to small population sizes as well as changed conditions the previously stabilized traits will start...well...drifting. The same is true for almost any circumstances that will destabilize equilibrium and lead to speciation.

But that has little to do with the actual theory, which is trying to explain the "general principles" of things. The events such as catastrophe will in a sense "revert" things back to an earlier time, after which the quickening of variability will commence. BUT it will still tend to slow down, eventually, and vary to a lesser degree, again satisfying the theory. N.B.: I haven't read about the Disruptive Selection or Directional Selection yet, so I am only talking about your latest point here. Thank you and excuse me!

Now that I've read about Disruptive Selection, I don't see how it impacts the argument. For once the selection is stabilized, it will tend to vary less. E.g. in the example of white/black rabbits - once the black color is chosen, it will vary very little compared to when the rabbits were initially specialized from, say, previous-rabbit-species, which were, for example of green color. Nor is there anything in Drawin's theory to suggest that simultaneous "genes" cannot exists in species at the same time, if selection deems them useless.

Directional selection sounds just like a regular natural selection to me. Perhaps I am missing some fine detail? Excuse my ignorance - I am just starting this subject!


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Can epigenetic changes affect reproductive success?
This is prompted by niallhaslam's answer to this question [Since Darwinian times, has there been any striking/notable effects of evolution on humans?]. A comment by Alan Boyd asks whether epigenetic changes count as evolution.
Transgenerational epigenetic inheritance can occur, and does increase the natural variation of a species (although this review is more about plants, this does apply to animals too) [1]. Based on this alone I'm inclined to say that epigenetics can affect the fitness of a species, and thus could contribute to evolution.
I am interested to know if, in practise, this does occur, and whether epigenetics have been shown to affect the reproductive success of a species? Because the changes are not permanent I could imagine that they actually have very little impact "species-wide", as environmental effects (infections, toxic exposures) also affect epigenetics. So, is there any evidence for epigenetics affecting the reproductive success of a species? This also includes whether epigenetics can influence traits enough to create a new sub-species.

Becker, C., & Weigel, D. (2012). Epigenetic variation: origin and transgenerational inheritance. Current opinion in plant biology. doi:10.1016/j.pbi.2012.08.004.

This article deals with the effect of phenotypic variation brought on by epigenetic patterns, and how these are inherited to the next generation. Their conclusions?

Our results show that epigenetic variation is inherited in chickens, and we suggest that selection of
favourable epigenomes, either by selection of genotypes affecting epigenetic states, or by selection of methylation
states which are inherited independently of sequence differences, may have been an important aspect of chicken
domestication.

However, I personally prefer this article, as it has a more profound implication on reproductive success and addresses your question specifically. They found the there is a species-level difference in DNA methylation between humans and chimps, but more importantly that this difference is responsible for the causation of numerous lethal diseases/conditions, which has a direct impact of the fitness of the species as a whole.

Finally, we found that differentially methylated genes are strikingly enriched with loci associated with neurological disorders, psychological disorders, and cancers. Our results demonstrate that differential DNA methylation might be an important molecular mechanism driving gene-expression divergence between human and chimpanzee brains and might potentially contribute to the evolution of disease vulnerabilities. Thus, comparative studies of humans and chimpanzees stand to identify key epigenomic modifications underlying the evolution of human-specific traits.

In summary, evidence has shown that epigenetics does seem to play an active role in the evolution of species, although the exact mode of inheritance of DNA methylation from generation to generation is unknown.

References

Nätt, Daniel, Carl-Johan Rubin, Dominic Wright, Martin Johnsson, Johan Beltéky, Leif Andersson, and Per Jensen. “Heritable Genome-wide Variation of Gene Expression and Promoter Methylation Between Wild and Domesticated Chickens.” BMC Genomics 13, no. 1 (February 4, 2012): 59.

Zeng, Jia, Genevieve Konopka, Brendan G. Hunt, Todd M. Preuss, Dan Geschwind, and Soojin V. Yi. “Divergent Whole-Genome Methylation Maps of Human and Chimpanzee Brains Reveal Epigenetic Basis of Human Regulatory Evolution.” The American Journal of Human Genetics 91, no. 3 (September 7, 2012): 455–465.

Very welcome, nice timing for the question too. The second article came out less than a month ago.


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Does DNA react in all of the ways most other acids do?
As I understand it from my basic chemistry, there are some fundamental reactions that exist between any acid and other substances for example acid-base reactions that form a salt, and the existence of a state of equilibrium in water.
Do these reactions and equilibria occur to DNA (or, for that matter, RNA), which has only ever been described to me as an 'acid', and does this affect the processes DNA goes through, like replication and transcription?

It may seem counterintuitive that deoxyribonucleic acid has nitrogenous bases. Nonetheless, nucleic acids (thus including RNA) were called that way because the phosphate backbone (linked by phosphodiester groups) is a derivative of phosphoric acid.
Phosphoric acid

Image Source
Phosphodiester group

Image Source
Note that the only difference between these two groups is that in the case of the phosphodiester, two O-H bonds are replaced by O-C bonds. This make the last remaining hydrogen atom quite acidic (can quickly be identified by how the conjugate base exhibits resonance). In fact, it is so acidic that at physiological pH, the phosphodiester group is deprotonated, giving that nucleotide a negative charge. This property does have a profound effect on DNA's structure and "behavior" in a cell, and is often exploited in genetics, such as in gel electrophoresis.
An interesting fact is that this acidity of the phosphodiester group actually competes with the basicity of the nitrogenous bases. However, since most often DNA is double-stranded, individuals bases will hydrogen-bond with its partner to make base pairs, which stabilizes and thus reduces this basicity.
TLDR: Although different acids of different molecular composition can act in very different ways, the overall acid-base chemistry is seen in nucleic acids.


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What really happens when a body is tired?
This may be anecdotal; please feel free to vote to close.
After staying awake for an extended duration, I usually find myself having to take extra effort to focus my eyes on an object. Similarly after exerting myself to the extent of near total exhaustion I find it necessary to consciously focus to perform actions that would otherwise require little conscious effort (E.g. Writing a note). There're other similar symptoms almost all of which mandate 'conscious effort'.
What really happens when a body is tired?
As a corollary, why does making conscious effort usually beat the initial error?

Its still not clear why we need to sleep (as distinguished from the question of why our body gets fatigued in physical exertion).  A popular idea is that the brain needs to 'catch up' and reorganize itself given all the stimulus it has had from the previous day.  This 2010 National Geographic article says it all:

I asked William Dement, the retired dean of sleep studies, a co-discoverer of REM sleep, and co-founder of the Stanford Sleep Medicine Center, to tell me what he knew, after 50 years of research, about the reason we sleep. “As far as I know,” he answered, “the only reason we need to sleep that is really, really solid is because we get sleepy.”

It is clear that we need sleep and that we become less reliable at tasks when we are sleep deprived.  eventually we become completely unable to function.
I'm not sure anyone can answer the last question - why does conscious effort help us to perform tasks?  one would have to understand/define the neurology of consciousness to answer that question.  That is still a bigger question that remains open I think.


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Why is offspring of identical twins not identical?
When identical twins marry identical twins, the children of the couples will be full genetic siblings but why are they not genetically identical?

I think we need more information. What is the evidence for your assertion?

Apparently this phenomenon (twins marrying twins) is called "quaternary marriage." Useful to know because (1) you can change the title of your question to be more precise (and maybe get better answers to your question); and (2) you now have a starting point to dig around to find answers.

They are not identical for the same reason full siblings are not identical.
A simplistic Mendelian setup would be the following:
X1/X2 = Mothers
X3/Y = Fathers
That means the children could be:
X1/X3
X1/Y
X2/X3
X2/Y
So children born to two married couples composed of identical twins only have a 50/50 shot at being the same gender, much less have the exact same set of genes and express them in the same way.
Now, the simplistic view above only concerns 4 alleles - but the human genome is composed of thousands. By the end, the chances of genetically identical offspring from a set of identical twins is still very, very low.
And you haven't even began to include epigenetic variations, which often arise as a response to the environment! One cousin might be shorter due to their diet as an infant, one might have allergies the other does not depending on if they played outside as a child, and for non-Mendelian traits (incomplete dominance, co-dominance, phenotypes that rely on more than one allele [especially hair, eye, and skin color]) there's even more opportunity to introduce differences!

Exactly. And then there is crossing over that will produce even more variability.

Let's not forget possible environmental influences on development.

There was actually a 1960s TV sitcom based on the notion of identical cousins. It was called the Patty Duke show. In reality the only way to have cousins that look alike would be through a quaternary marriage. That is when twins marry other twins. The children from the two marriages would technically be 1st cousins yet genetically they would be siblings as well. In other words, it would be impossible to figure out who the biological parents are based on the DNA alone since the parents (being identical twins) would share the exact same genetic material. The truth is the Patty Duke show scenario is highly unlikely. Patty and Cathy could not be identical cousins because the only way we get identical offspring is when a fertilised egg splits into two cells. Those identical cells grow into identical twins. So there would be a strong resemblance between Patty and Cathy but the odds of them looking like identical cousins is unlikely. More likely they would look like fraternal twins. Patty would indeed look like Cathy but you could tell the difference between them just as you could between any pair of sisters. The cousins wouldn’t look identical but they wouldn’t look like cousins. They would look like sisters.

Hi Toussaint, welcome to Biology.SE! Nice anecdote! It would be useful to add reference for the "scientific" part of your answer and improve the formatting for better reading.


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Why does squinting allow you to see objects more clearly?
How does squinting alllow one to see clearer pictures? What are the harmful effects?

This is an optical pinhole effect.  If the amount of light passed through the lens decreases, the sharper the image is at the focal point.  For a camera this is accomplished by increasing the f stop (f22 is a smaller aperture size than f6 — f-stop is an inverse number).  For the eye the iris will dilate (get larger) or contract to be smaller.  In very bright light, you can cut down on large amounts of light coming in by squinting, which creates a slit in front of the eye lens.
In photography this increases the "depth of field". Which is to say that more objects are in focus and sharp.  It works the same for our eyes of course.

In this image you can see as the aperture is smaller, any given point on the focal plane (right hand line) receives light from a smaller angle (i.e. from less of the image field).
I am not a physicist, but that's a first order explanation
@Luke reminds me that there was a question about whether squinting is harmful.  There is another reason that we squint.  If we are nearsighted or if we are getting older, we have a tendency to squint not because there is too much light coming into our eyes, but because our lenses are not focusing very well.  Is it harmful to strain our eyes?  Maybe, but it won't kill you.  Reading glasses won't either.

I can't think of any harmful effects, can you? Maybe constantly squinting would actually alter the shape of your eye/retina slightly, thus meaning you'd always need to squint (or get glasses)?

@Luke i added some thoughts to the answer.  I think eye strain that results from squinting when your eyes are not really seeing things well might tend to hurt your eyes.  squinting because the light is too bright is probably a good thing and might be as good or better than sunglasses.

squinting may be harmful b/c it reduces number of blinks?  affects the production of tears?

its probably better to be in a not too brightly lit temperate environment


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Experimental techniques to measure protein-protein and protein-ligand structure and dynamics
We would like to compare our simulation results with experimentation. When one wants to follow experimentally the dynamics (and possibly structure) of protein-protein or protein-ligand docking (involving both small and large conformational changes for the complex), which are the most useful hydrodynamic techniques? If not hydrodynamic, which others?

NMR would be a method to get structural and dynamics information, but that is not a quick and easy method. Are you looking for atomic-resolution data, or for simpler methods that only give you some global information on the shape and dynamic of the protein?

I am interested in both, atomic resolution data, and/or "coarse grain" model data


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Why is the floral biodiversity of grazed grassland higher than that of mown grassland?
I have collected some data to compare the biodiversity of a field in which the plagioclimax is maintained by machine mowing with a field in which the plagioclimax is maintained by sheep grazing.
What I found was that there was a significant increase in floral biodiversity in the field which was managed by agricultural grazing when compared to the floral biodiversity of the machine-mown field.
I am trying to explain my findings, and I believe that it is due to the comparitively short amount of time that machine-mowing has been a grassland management technique, so there has been little time for natural selection to take place and for species to develop adaptations to machine-mowing (such as being low-lying, or extremely fast-growing). Whereas the field which is managed through sheep-grazing, contains multiple competing species which have adapted over time to grazing sheep, such as Cirsium arvense.
Moreover, the field which is managed by grazing has nutrients returned to it through defecation of the grazing animals, allowing for more favourable conditions for growth.
Is my explanation valid? Are there any other reasons why the floral biodiversity of a field managed by sheep grazing would be higher than one managed by machine-mowing?
Thanks in advance!

I think you may have covered the answer in your question... but here's my take;
The 'mowing' occurs at a distinct time-point and is highly destructive and uniform, so the selection pressure is very high and only highly competitive species that are fast to grow and reproduce will be successful.
As you point out, animals will defecate and naturally fertilize the land, thus favouring growth. Other favourable factors in an agricultural environment will be that the 'mowing' will be much less uniform; the animals may favour one plant over another - so a plant that is not eaten by the animals will continue to grow and reproduce, whereas in the mowing environment this plant would not succeed; this will allow various other species to succeed where they would not in the mown environment. Also, depending how many animals are in the area the height of the grass may be higher overall, so slower-growing plants could grow enough to reproduce.

Other possible reasons except your and Luke's:

Different agriculture techniques. I could imagine machine-mowed grassland could be processed by different chemicals (fertilizers, insecticides). I could imagine machine-mowed grassland could be sown with different grass that grows faster but dies when trampled with hoofs.
Most agriculture machinery works on fossil fuel i.e. emits CO₂ and other compounds.
You could also flip cause and effect. It could be that there're some reasons (dunno: soils, humidity, etc) why fields with lower biodiversity is more suitable for mowing.


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Why do the two hemispheres of the brain control the opposite sides of the body?
Why does the left hemisphere control the right and the right hemisphere control the left? I googled it but didn't find a good answer regarding this. Could someone explain?
Does this adaptation help in the speed of transmission of nerve impulses?

I'd bet it's non-adaptive.

You seem to accept that we have two brain hemispheres that each control one half of the body without questionning this fact and then ask why does the left part control the right part and vice-versa. If we do so, as @NoahSnyder, I would tend to think that such thing is not adaptive because I think there were two possible solutions (cross wiring or no same-side wiring) that are equally fit and one was randomly chosen!

See also: http://cogsci.stackexchange.com/q/5771/301

Just to get the ball rolling here.  This particular aspect of brain evolution is very old. The cross wiring of the hemispheres of the brain seems to be as old as the right and left hemispheres itself.  It predates lizards - i.e. hundreds of millions of years ago. It  possibly predates right/left dominance and the organ asymmetry which puts the heart on the left side of the body.
Digging back deeper, we can see that worms have bilateral brain structure, but as noted in the comments below, the nervous systems do not cross.  I would guess that this means that the phenomenon appears sometime before lizards - putting the development having been done by the early Carboniferous period when the first animals came to the land and the first reptiles appears, which is the perhaps 350 million years ago.
Echinoderms (like starfish) are 'missing links' in bilateral symmetry as their larval stage has bilateral symmetry even though the adult has radial symmetry.  Such wiring may be so embedded in the way most animal body plans develop that it hasn't changed in evolutionary history. If that is related to other animals trait, it could be a billion years ago. Some argue this is not the case.
One might guess that the cross over of neurons in brain control is good for integrating the signals from both sides of the organism. There are quite a few theories.

layperson, here... just a theory, but if it goes far back enough, I could imagine that a small enough organism had some advantage to having fewer kinks/bends in the nerve fibers when going through a "neck", so the left half of the body being connected to the right half of the nerve... clump(?) allowed a straighter path... just a thought, unless we can find something REALLY small that seems to demonstrate this...

this is how the evolutionary biology game is played.  we try to understand the dynamics of selection by looking for examples that illustrate a point about the relative advantage of some configuration in living things.  If we don't see what we're looking for, then we have to re-think our logic.

Question, if there is an answer (?): how do the nerves go from one side of the brain to the other side of the body? Are they intermingled/intermeshed, or do the left hemisphere nerves typically go on front of the right hemisphere nerves? Or typically behind? If there's a significant correlation in dorsal/ventral or anterior/posterior based on hemisphere of origin, that could indicate some amount of "twisting" that occurred at some point way back in evolutionary time, where the head/brain bucket used to "point" the other way ..

symmetry in biology is inherited v. early in and is the result of genes that maintain the bilateral symmetry in our class of animals.  (radial symmetry and assymmetry exist too).  Those same factors that generate these symmetry are probably playing a part in the crossing from one side to another if they are symmetric crossings... just a guess.

This answer is very old, but I just came across it...Contralateral motor control is, as far as I am aware, a vertebrate phenomenon. Yes, worms have a lateralized nervous system, but they do not have contralateral control, so I think it is quite misleading to mention them in this context. There is not evidence that contralateral control is as old as bilateral symmetry. Mollusks and arthropods also have fairly advanced nervous systems but do not show a primary contralateral control.

thanks for the above - i was really just taking a stab. i corrected this however. i think the point about the starfish is still interesting but it could have been an independent development.  It doesn't seem to have cropped up too often though.

When I was in school it was discussed as an evolutionary survival advantage... If you are attacked from the right side, the left side of the brain is less likely to be damaged and can use the right sided limbs to fend off the attack as opposed to the right side being damaged and less responsive..

I've also head this repeated at undergraduate level

There's a good answer to this on https://www.quora.com/Why-does-our-left-hemisphere-of-brain-control-our-right-side-of-our-body-and-the-right-our-left.
In summary, a biopsychologist states that vertebrates and invertebrates have the digestive system and the nervous system in reverse locations. He also points out that the hearts are in the dorsal area for invertebrates and in the ventral area of an invertebrates. The evolutionary theory of these observations is that the body of an early vertebrate must have been turned upside down, and the easiest explanation is that a vertebrate ancestor swiveled its head 180°. In conclusion, it's believed that one vertebrate had its head turned around and that contralateral arrangement was conserved because it decreased chance of error in nervous system wiring (compared vs simpler same-sided wiring schemes).

Certainly an interesting idea.

Being a keen student of game theory and behavioural sciences one reason that comes to my mind is for the opposite wiring of brain hemispheres might be that

if right hemisphere controlled the right side and left hemisphere controlled the left side than cross hemisphere links and activity would be hard to achieve so the most efficient way of increasing cross hemisphere communication, links and activity with the least stress on physical resources is the opposite hemisphere wiring.
The second view that also compliments this cross arrangement might be the underlying law of increase in complexity and entropy (second law of thermodynamics), which is embedded in the universe from its births, dictates an increase in complexity hence cross wiring also achieves this underlying goal of increasing complexity because if you think about it straight wiring would have been too simple for such a complex structure as the brain.

It seems a bit voodoo indeed! I don't think the second law of thermodynamic can bring any insight into the general tendency observed in living things to increase in complexity through evolution. But the discussion might be interesting. But if your answer was an real explanation, you could use it to explain so many different weird phenotypes on earth. That makes me think that it is not really a satisfying explanation. But it's good to try such voodoo-like suggestions ;-)

It is simple.  The brain through evolution split into two hemispheres when binocular vision was evolving.  If you follow the neurons from the eye, the lateral neurons travel to the ipsilateral hemisphere.  The medial neurons cross to the contralateral hemisphere.  I would bet the protopathic pathways were around in evolutionary terms before binocular vision and the epicritic pathways developed after binary vision.  Vision drove the hemispheres into two compartments. I could draw the diagram but unable to do so on this response

Welcome to Biology SE. This answer could do with some references - see the guidelines on how to write a good answer http://biology.stackexchange.com/help/how-to-answer

It's for control, coordination and balance. From a mathematical point of view, parallel lines won't intersect and thus line A won't affect line B unless they intersect and thus would hardly influence the other unless and an external force is applied to any of the lines.
This is also why corpus callosum connects the left and the right side of the brain.

Could you please add references to this response!


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Can a plant be induced to accelerate transpiration?
Just what the title states.
I wonder whether it is possible to fire a chemical switch - sort-of like injecting adrenaline in a human, to accelerate a particular process in a plant. For example, transpiration.

With high(er) temperatures, especially in drier air with a bit of breeze, a plant will transpire more. While not a chemical solution, it is indeed a mechanism that serves to cool the plant.


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Number of spindle fibres during Metaphase?
During metaphase, the chromosomes are arranged on the equatorial plate and are attached to spindle fibres. After S phase, can the cell be said to attain the configuration of 4n?
Also, during metaphase, since two spindle fibres (one from say right centriole and other from say left centriole) are attached to one tetrad, so can it be said in a well defined pattern that for a human being, 46*2=92 spindle fibres are formed in order to proceed with mitosis? Also how would the number vary in case of Meiosis I and Meiosis II?

The number of spindle fibres is actually more than total number of kinetochore pairs. The fibres attached to kinetochores are called K-fibres and the others are called polar fibres. I cant surely say that there is exactly one K-fibre per kinetochore but as per its definition and from the microscopic images you can conclude that there is one per kinetochore.
In a normal mitotic metaphase there are 2n kinetochore pairs, and as you rightly calculated, there will be 96 K-fibres.
In meiosis-I there is a tetrad which has 2 kinetochore pairs but the ones in sister chromatids behave as a single unit. So there would be 23 fibres.
The fusion of kinetochores of sister chromatids is relaxed in meiosis-II and again a separation would require 23 fibres.
Please have a look at this article. Molecular biology of Meiosis nicely explained:
http://www.sciencedirect.com/science/article/pii/S0092867403000837
More about K-fibre formation:
http://link.springer.com/article/10.1007/s00412-005-0028-2/fulltext.html