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When did vision evolve for the first time?
Today I wondered what the first organism to evolve vision would have been. I assume that it would have been kind of primitive and basic, but of course extremely innovative and eventually useful to a wide variety of beings.
It also makes sense that the evolution of vision would have accompanied the evolution of advanced brain functions in almost every case. So, do biologists have any idea as to what the first species to use vision would have been?
(By vision, I mean having some organ on your body that receives photons and has some signaling pathway that converts photons into a biochemical set of signals)

I think I read in one of my textbooks that vision likely arose from  photoautotrophs developing a photosensitive spot in their cells.  This was advantageous as the organisms could move into areas where light conditions were favourable

What do you mean by vision? How complicated of a system? Photoreception has a long evolutionary/phylogenetic history and can render a fitness advantage without an eye or central processing unit. But as for eyes/brain, that's a different question, I think.

vision has evolved independently at least 10 times, likely more.  the simplest multicellular vision system we know of is literally one light sensitive cell attached to a single nerve cell. that nerve cell is inhibitory, it inhibits the swimming muscles impulse on that side of the worm, making the worm turn towards the light.

I'll address the question in the title "At which time did sight evolve for the first time?" by assuming that by the evolution of vision, we mean the evolution of the eye.
Molluscs are an excellent phylum to investigate this question because they exhibit a wide range of eye designs and levels of complexity.
At the most basic level, limpets such as Patella exhibit small patches of photoreceptor cells lying in a relatively flat configuration. Slightly more advanced is Pleurotomaria which has photoreceptors and pigmentation cells held in an eyecup. We then have the pinhole camera style eye as seen in Nautilus (see this post), and more complex eyes with a cornea, retina, and lense such as those seen in squid (e.g. Loligo).
Assuming that "a patch of photoreceptors" in an animal counts as an eye, then we should probably looking for marine invertebrates. The problem here is that if they had only soft body parts we might struggle to identify the oldest examples in sediments.
One candidate for the "earliest eye" might be urbilatarians - the hypothesized last common ancestor of the clade bilatarians - which probably evolved at the end of the Ediacaran period (~555 Myr). An example would be Kimberella (described here) which might or might not have been a mollusc and might or might not have had photoreceptors!

(credit : wikipedia)

"To me, it also makes sense that the evolution of sight would have accompanied the evolution of advanced brain functions in almost every case."

Not necessarily! For instance, think of phototropism: the plant detects the presence of light and uses it to grow towards the light, but that's a very simple process regulated by auxins. Or the light-sensitivity (phototaxis) shown by Euglena, a single-celled protist, which reorients its entire body towards a light source. Really simple vision (is there a light, and if so, where is it?) can help organisms absorb more energy than rivals, giving them an evolutionary advantage.

It also makes sense that the evolution of vision would have
  accompanied the evolution of advanced brain functions in almost every
  case.

Untrue. Behold the box jelly. With eyes that have similar structure to vertebrate eyes. Able to form an image but yet no brain to understand what it is seeing. http://www.livescience.com/13929-box-jellyfish-eyes-navigation-brain.html
Also a single cell organism (warnowiids) that may have an eye (retina and cornea like structure).
http://phenomena.nationalgeographic.com/2015/07/02/single-celled-creature-has-eye-made-of-domesticated-microbes/


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Where is the line between Anaerobic and Aerobic?
I am well aware of traditional anaerobic respiration (lactic acid or alcohol produced - no Krebs cycle) and traditional aerobic respiration (O2 is used at the end of the Citric acid cycle).
I am wondering how to classify respiration that uses the Citric acid cycle, but consumes a nitrite/ate or sulfite/ate instead of O2. Is that anaerobic or aerobic?

I could only find this image on Google image search catch but it said it was from http://lecturer.ukdw.ac.id/dhira/Metabolism/RespAnaer.html

http://toxics.usgs.gov/definitions/aerobic_biodegradation.html

Your question is based on a bit of confusion about electron acceptors that is very common and that drives microbiologists crazy. Energy (as ATP) is generated when electrons are moved from an electron donor to an electron acceptor. In respiration, the electron acceptor is inorganic -- oxygen for aerobic respiration or an inorganic molecule such as sulfate or nitrate for anaerobic respiration. Use of an organic molecule such as pyruvate as an electron acceptor is properly called fermentation. Both anaerobic respiration and fermentation are termed anaerobic because they don't use oxygen. Any introductory microbiology textbook will cover these concepts in detail, because they are important to understanding the metabolic diversity of bacteria. Brock Biology of Microorganisms is a good text.

A friend of mine checked 8 different introductory biology textbooks: 6 of them described respiration as using oxygen. However 2 of them did not specifically state oxygen as the terminal electron acceptor, which I am convinced is technically correct. Nitrogen as a terminal electron acceptor is an exception and not the rule, which is why it is so often overlooked in textbooks.

Anaerobic respiration is a respiration where the final electron acceptor is different than oxygen. The final acceptor can be a less oxidizing than oxygen, like sulfate (SO42-), nitrate (NO3-), or sulfur (S). For example bacteria that use sulfate are obligate anaerobs.
The Krebs cycle cannot take place in the absence of oxygen, although oxygen is not directly involved in the cycle. The oxygen is required for the electron transport chain, which oxidized NADH and FADH2 back to NAD+ and FAD+, which are involved in the four reduction reactions of the cycle.
Thus, aerobic respiration includes both Krebs cycle and final electron acceptor of oxygen, whereas anaerobic respiration does not.

I thought that NADH and FADH2 could be recycled using Nitrites - I edited in a diagram.

I still don't think that denitrifying bacteria will utilize Krebs cycle. Why would they do it anyways if no energy whatsoever comes from it?

One GTP (ATP) still comes out of one turn of the Krebs cycle. Although inefficient, there is still some sort of gain.

@jp89 All energy produced in the Krebs cycles comes from the electron transport chain, i. e. energy cannot be produced without oxygen.

"Most microbes respire (use an electron transport chain), although oxygen is not the only terminal electron acceptor that may be used. " - http://en.wikipedia.org/wiki/Microbial_metabolism , see also; http://nitrificationnetwork.org/Introduction.php (Ctrl+F, electron transport chain)

@JoeHobbit It might be that denitrifying bacteria have Krebs cycle, but I think that this still classifies them as anaerobs. I will do more research and will let you know.

The Kreb cycle can indeed take place. You speak of the final electron acceptor being different than oxygen, but for what process? Surely you are referring to the electron transport chain? That would power the regeneration of NAD+ and FAD+. Thus anaerobic respiration includes the Kreb and the ETC.

@GerganaVandova Good One! I would suggest you to format it (just a little bit) by highlighting the bottom-line

Agree that anaerobic respiration involves the electron transport chain and alternative terminal electron acceptors such as nitrate. However, respiring cells (whether respiring aerobically or anaerobically) can run the Krebs cycle. As long as there is a terminal electron acceptor, the NADH/FADH2 generated by the Krebs cycle can be oxidized back to NAD+ or FAD.

Welcome to biology.SE. Your answer, while interesting, does not address the question asked: "I am wondering how to classify respiration that uses the Citric acid cycle, but consumes a nitrite/ate or sulfite/ate instead of O2. Is that anaerobic or aerobic?"

The status of this question and its answers is completely messed up. This post has the correct answer - use of anything other than oxygen as a terminal electron acceptor is anerobic respiration. Cells using anerobic respiration will (normally) have a Krebs cycle. The answer from @Gergana Vandova is incorrect, despite its upvote score.

While aerobic organisms during respiration use oxygen as a terminal electron acceptor, anaerobic organisms use other electron acceptors. These inorganic compounds have a lower reduction potential than oxygen, meaning that respiration is less efficient in these organisms and leads to slower growth rates than aerobes. Many facultative anaerobes can use either oxygen or alternative terminal electron acceptors for respiration depending on the environmental conditions.
Most respiring anaerobes are heterotrophs, although some do live autotrophically. All of the processes described below are dissimilative, meaning that they are used during energy production and not to provide nutrients for the cell (assimilative). Assimilative pathways for many forms of anaerobic respiration are also known:http://en.m.wikipedia.org/wiki/Sulfur_oxidizing_bacteria

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Could an "overactive" brain increase the chances of Alzheimer's Disease?
From  Raichle ME. 2010. Two views of brain function. Trends in cognitive sciences 14: 180–90:

Alzheimer’s disease (AD) is the most common cause of progressive
  cognitive decline and dementia in adults. While the amyloid cascade
  hypothesis of AD posits an initiating role for the β-amyloid (Aβ)
  protein, there is limited understanding of why Aβ is deposited. A
  growing body of evidence based on in vitro, animal studies and human
  imaging work suggests that synaptic activity increases Aβ, which is
  deposited preferentially in multimodal brain regions that show
  continuous levels of heightened activation and plasticity across the
  lifespan. Imaging studies of people with genetic predispositions to AD
  are consistent with these findings, suggesting a mechanism whereby
  neural efficiency or cognitive reserve may diminish Aβ deposition. The
  aggregated findings unify observations from cellular and molecular
  studies with human cognitive neuroscience to reveal potential
  mechanisms of AD development.

High synaptic activity doesn't necessarily mean hyperactivity. You can have an high inhibitory tone, for instance.

I think the article that quoted(1) is different to what the link shows now(2). However, both the article quoted and the one in the link are relevant to the question.
Alzheimer's Disease : In a nutshell, AD is the most common form of dementia. Although the exact cause is still under investigation, several genes have been implicated in the development of AD. One of the things you see in the brain with disease progression is beta amyloid plaque deposition which disrupts brain activity.
Brain Activity : While the brain consumes around 20% of our body's energy at a baseline, an increase in brain activity only increases this consumption by around 5%. Hans Berger, the first to record an EEG stated that "mental work, as I explained elsewhere, adds only a small increment to the cortical work which is going on continuously and not only in the waking state".(2)
However, there are a few 'intrinsic' networks or regions that perform functions such as "information processing for interpreting, responding to and predicting environmental demands". One of the areas active in this state of the brain is referred to as the 'default mode network' (DMN). It's thought that DMN is the main target of the amyloid plaques responsible for Alzheimer's Disease.(2)
However, there are other multimodal regions of the brain that perform processing of various types of information. It's now suggested that "regions vulnerable to Ab deposition do not simply involve the DMN, but rather comprise multimodal brain regions that are highly interconnected, plastic, and capable of rapid ATP generation"(1).
So it's a variation of activity in these particular areas - not all - that are implicated with Alzheimer's Disease. When you are performing a task, activity in these areas diminish.
Why keep the brain intentionally active : The reason for the hypothesis that actively engaging in challenging activity may reduce the risk of AD is that individuals with a high cognitive reserve have been shown to cope with the pathological changes such as beta amyloid deposition better. Cognitive reserve has been linked to a bunch of factors including "education, occupation, socioeconomic status, social networks and lifelong participation in cognitive and physical activity" and reflects "lifelong patterns of behaviors, endogenous factors (including genetics) and exposure to environmental factors"(1).
Moreover, it's suggested that perhaps higher cognitive reserve increases neuronal efficiency which has been shown to reduce plaque deposition.(1).
So InquilineKea's question and jp89's answer aren't really contradictory.

August, et al. Lifespan brain activity, β-amyloid, and Alzheimer's disease.
Trends in Cognitive Sciences. 2011. 15(11):520-526.

Raiche. Two views of the brain.
Trends in Cognitive Sciences. 2010. 14(4):180-190.

Hafkemeijer, et al. Imaging the default mode network in aging and dementia.
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 2012. 1822(3):431-441.

Harrison's Principles of Internal Medicine. 16th Ed. McGraw Hill.

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Do mitochondria simply automatically convert glucose to ATP?
I wonder whether there is any intelligent decision-making in mitochondria in the timing of their operation.
Do they simply begin ATP production as soon as the correct reactants are present?
Or, because they have their own DNA, do they have more complex strategies that vary to benefit the mutual cooperation with the host cell? This assumes that the simple circular DNA is performing higher level decisions in switching.

Mitochondria only have a handful of genes; their regulation is utterly intertwined with their host.  Additionally, only the TCA (Krebs, Citric Acid...) cycle occurs within mitochondria; glycolysis occurs in the cytosol.

@NickT, does that imply that the host 'controls' the activity of mitochondria?

Mitochondria are comprised of ~3000 proteins. However, the mitochondrial genome has only 13-14 protein-encoding genes. The remaining 99.6% of mitochondrial proteins are encoded by genes in the nuclear genome. (Wikipedia) Chloroplast genomes are only slightly larger (~100 genes).
Gene regulation and signaling between the nucleus and mitochondria (and between nucleus & chloroplast in plants/algae) occurs in both directions. Anterograde regulation is the signalling from nucleus to mitochondria and was once thought to be the only method of regulating organelle function. We now also know that Retrograde regulation occurs, in which the mitochondria sends signals to the nucleus.
To answer your question directly (but not thoroughly), both the mitochondria and the nucleus are sensing the environment and needs of the cell and signaling to each other to regulate ATP production.
If you want to learn more about retrograde signaling, googling "retrograde regulation" will bring up lots of papers on this topic in different organisms. This paper also has some diagrams of signalling pathways.

this is very interesting how there is bilateral communication between DNA and mitochondria. Does mitochondria have to work to survive? Eg. if they do not produce ATP, do they die?

Hi @Amy =)  Whilst I know that your block is quite small, we're trying to discourage extended direct quotes from wikipedia (see meta).  It might be a better idea to summarise the article yourself and link to it as a source for your answer =)

@RoryM - edited :)

@Vass That's what I think is the coolest thing about eukaryotic cells. The cell cannot build a mitochondria "from scratch" because the mitochondria have kept just enough genes on their own genome - but mitochondria cannot survive outside the cell because it has lost so many genes. If they don't produce ATP, they die, because the cell dies. Both the cell and the mitochondria have a vested interest in keeping the machinery going. :)

@Amy, why is this symbiosis so much more beneficial than the scenario of all regulation being contained in the nucleus?

@Amy thanks a lot, that really looks a lot better =D

@Vass - The current arrangement is not necessarily the perfect arrangement, it's just the best that has been achieved so far in the accidental history of evolution.  It's quite likely that it would be better if all mitochondrial genes resided in the nucleus since the sexual recombination of genes the nuclear mechanism provides allows better maintenance and improvement of genes (unlike the purely asexual DNA reproduction in the mitochondria).  This is why many genes have migrated from the mitochondrial genome to the nuclear genome, and why 99% of mitochondrial protein genes are nuclear.

@mgkrebbs, which genes migrated from mitochondria to the nuclear genome? Those that it would have needed to survive independently of the host cell?

Mitochondria have very few genes left, many fewer than a free living organism would need.  Almost all the originally present genes have been lost as unneeded, replaced by functional equivalents from the nucleus, or have effectively migrated from the mitochondrion to the nucleus.  The genes left in the mitochondria are mostly the electron transport chain proteins and the ribosome and tRNA genes needed to build those proteins.

The textbook version for the regulation of ATP involves a feedback loop with phosphofructokinase (PFK). The relative concentrations of ADP and ATP are characteristic of the energy state of the cell. If the cell is using energy, then there will be an excess of ADP. If not, then ATP.
ATP is an inhibitor of PFK, which in turn slows glycolysis (thus reducing the production of new ATP). In contrast, ADP is an allosteric activator of PFK, which in turn speeds up glycolysis (thus increasing the production of ATP).

so there is a stable equilibrium concentration between these two compounds? And is it that the use (or lack of use) of ATP ignites the production of more ATP from ADP?


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Looking for a cancer drug target database to guide sequencing of patient tumor DNA
I have a question I would like to pose to the community. I have recently received access to a bench-top ion torrent DNA sequencer. Our idea is to use this machine to sequence the DNA from patient’s tumors in order to guide treatment options. My job is to identify a list of all currently used anti-neoplastic drugs along with their known targets (i.e., specific genes and mutations) and accession numbers. I would like to put these data in a table in which each row corresponds to a different drug.
For example, a row in the table might read (column names are indicated in brackets): [disease] breast cancer, [drug] trastuzumab, [drug target] HER2/neu receptor, [gene] ERBB2, [location] chr17:37844393-37884915, [mutation type] amplification, [accession number] ENSG00000141736. The pathologists would then be able to use this database in order to select appropriate genes for sequencing whenever they receive a tumor specimen. If the patient’s tumor had an amplified ERBB2 gene, they could be given trastuzumab.
Currently our study is in pre-planning stages (i.e., we won’t actually be testing this on patients any time soon). I would appreciate it if anyone could give me on advice on how to go about creating such a database. I am aware of online databases including COSMIC, Sanger's Cancer Gene Census, and the Potential Drug Target Database (PDTD), but they don’t have everything that I’m looking for. I am familiar with R and could use it to combine data from multiple sources if necessary. If anyone else has comments or suggestions for further reading that would also be appreciated. Thanks!
Note: This question has also been posed on a Research Gate forum: http://www.researchgate.net/topic/Cancer_Biology/post/Looking_for_a_cancer_drug_target_database_to_guide_sequencing_of_patient_tumor_DNA

Would this question be better suited to healthcare-it?

Have you tried looking at the NCI-60? Here's a (dated) paper but might serve as a good starting point:
http://discover.nci.nih.gov/nature2000/paper/nature_v26_3_mar_2000.pdf

@RoryM I don't thinkg so, this is either our project or biostart.SE, rather the ours.

This ma be a good start http://www.pharmgkb.org/. I think biostar may be able to give you a good answer.

Is doing whole exome sequencing out of the question for your upcoming project? I feel like it'd crank up the chances of success for your project, and ... actually ... the exome isn't all that big, right?

Thanks for the comments everyone. We have purchased an Ion PGM sequencer, which is not capable of performing whole exome sequencing. The company says that the sequencer is "ideal for sequencing small genomes, sets of genes, or performing gene
expression profiling or ChIP-Seq." Researchers can interrogate "targeted genomic regions using up to 1,536 amplicons in a single tube, in a single day." Their website is www.iontorrent.com. For this reason we would like to design a panel of particular genes to sequence in each tumor type. I will check out the other websites that you all have suggested.

Although, upon further reading their website, it may be possible to upgrade the machine to do this in the future by changing the chip. We are getting the machine delivered to the lab this afternoon, so I haven't actually gotten to play with it yet. If anyone else has more comments or suggestions, please let me know! Thanks.

Am I right in understanding this, you're looking to aggregate data already available from other databases into your own custom database with a custom front end?  Assuming so a simple MySQL database could hold it with a couple BioPython scripts to fetch the data.  A PHP page would allow you to make it easily usable for your pathologists.  This is assuming it's all pretty straight forward, or did I miss the point?

Not sure if the exome sequencing is the way to go for this kind of tasks, especially if you have an idea of the mutations you might be looking for. Current arrays are pretty performant and are much more rapid and cheap.
For the data, you might consider having a look on The Cancer Genome Atlas. Otherwise Biological Networks might provide you the API for you if you aren't afraid of doing a little bit of Java to interface it with R.

There are no perfect resources for this information in the public domain quite yet. However, there are three that are making really good progress. The first is mycancergenome at Vanderbilt. They were one of the first resources to put this type of information on the web. They tend to be pretty stringent in the level of evidence and type of aberrations that go on the Web site. However, I am not sure if you can programmatically access there information. The second resource, is the https://pct.mdanderson.org developed at MD Anderson. This is really good resources however, it is only for a handful of genes, but albeit some of the most frequently mutated. I don't see a programmatic access to the information. The third resource and most promising for the community is the CIVIC database: https://civic.genome.wustl.edu/#/home. This is crowdsourcing resource that is set up to aggregate cancer associated mutation to drugs, phenotypes, and outcomes. I highly recommend this site and encourage not only consumption of data but also to engage in comments.
   As someone that has been doing drug to genome matching a couple pieces of advice. DNA based alterations are the best evidence to use for matching. If you do RNA be a little bit more cautious of matching based on 'is a target' mechanism. So rank DNA based changes above RNA. Additionally, just start with drug targets as place holders but try to acquire information on alteration as it relates to drug response. So alterations in a drug target could be (and often) are passengers and not drivers and in this case will not respond to drug. Frequency in other tumors and mutations in important domains are good guides for triaging variants like this. Also, the information on the disease and the mutations is important. If a drug variant mutation is observed in one disease there maybe mechanisms intrinsic to another tumor type that would preclude acting on drug to variant association in the different tumor type. Lastly, drug mechanism is something to take into account. Certain drugs that hit the same target do so but in different mechanisms that may preclude them being given in the context of particular mutations.
Good luck in your endeavors.


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What is the benefit for cells having the ATP production regulated in mitochondria compared to being from the nucleus?
Mitochondria have their own DNA and appear to be loosely connected to the nucleus and it role.
Why are the functions of mitochondria not in the nucleus? Why doesn't the nucleus control the mitochondria's functions as it controls regulation for other chemical reactions?
Are there evolutionary/competitive benefits for this separation?

For starters, see this thread.
My understanding is that the ancient predecessors of mitochondria were free-living unicellular organisms. Supposedly at one point, these mitochondria-like cells developed an endosymbiotic relationship with a larger cell. This relationship was advantageous for both cells: the smaller cell could focus on energy production, leaving tasks like homeostasis, nutrient collection, etc, to the larger cell. Over evolutionary time, this endosymbiosis caused the smaller cell to lose all functions unrelated to energy production, while the larger cell (as we now know it) came to rely heavily on the mitochondria for energy production.
So it's possible that at one time the nucleus encoded machinery for ATP production, but apparently the modularity and separation of function provided by this ancient symbiosis turned out to be successful.

wouldn't some examples of a mononucleotic system emerged to compete if it was slightly as efficient? Why does this arrangement dominate?

it is a matter of opinion if it dominates. Louis Pasteur would have said: Ce sont les microbes qui ont le dernier mot (the microbes have the last word)

"This relationship was advantageous for both cells: the smaller cell could focus on energy production, leaving tasks like homeostasis, nutrient collection, etc, to the larger cell." --- Indeed, the nucleus even controls the division of mitochondria.


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How do you design a drug to be delivered to the CNS?
I have just started reading up on structure-based methods for drug design (this is completely not my field so apologies for stupid questions that will be coming along!)
Clearly, some drugs are designed to target the central nervous system. However, I understand that the extracellular fluid of the central nervous system is separated from the blood by the "blood-brain barrier" which restricts the passage of large molecules between the two systems.
My question is : how do you design a drug to be delivered to the CNS?

You can read up on the design of opioid drugs (morphine, codeine, etc...). These provide a classic example of rational drug design in relation to the blood brain barrier.

I concur with @jp89. Contrast for instance the effects on the human body of pethidine and loperamide. They are structurally similar, yet only the former is able to execute systemic effects.

In a nutshell: in order to pass through the blood-brain barrier (BBB) the substance has to mimick soee properties of the substances that are allowed to pass through.
There are different types of "transporters" -- integral proteins going through the cell membranes and accounting for the active transport of the substances they can actively bind to. Smaller molecules of drugs can use solute carrier transporter (SLC), whereas bigger molecules (oligo- and polymeres) would use the receptor-mediated transporter (RMT).
There is a nice article on this topic published by ScienceDaily.
Here is the quote:

One technology for enabling active transport of small molecule drugs
  across the BBB involves targeting endogenous nutrient transporters.
  These transporters are members of the solute carrier (SLC) transporter
  superfamily. Transport of small molecules across the BBB by these
  membrane proteins is known as carrier-mediated transport (CMT).
In order to design drugs that utilize CMT to cross the BBB,
  researchers modify their chemical structures so that they resemble
  nutrients that are transported across the BBB by specific SLCs. The
  prototypical drug that uses this strategy (which was developed long
  before mechanisms of CMT were known) is L-DOPA, the major current drug
  for Parkinson's disease. L-DOPA is used to replace dopamine that is
  lost due to degeneration of dopaminergic neurons in the substantia
  nigra of the brain.
Another major system that is used in normal mammalian physiology to
  enable needed molecules to cross the BBB is receptor-mediated
  transport (RMT). The brain uses RMT to transport proteins, peptides,
  and lipoproteins that are needed for brain function across the BBB.
  Examples of biomolecules that are transported into the brain via RMT
  include insulin, insulin-like growth factor (IGF), leptin,
  transferrin, and low-density lipoprotein (LDL).
In RMT, molecules in the circulation may bind to specific receptors on
  the luminal surface of brain capillaries (i.e., the surface that
  interfaces with the bloodstream). Upon binding, the receptor-ligand
  complex is internalized into the endothelial cell by a process called
  receptor-mediated endocytosis. The ligand may then be transported
  across the abluminal membrane of the endothelial cell (i.e., the
  membrane that interfaces with brain tissue) into the brain. This whole
  process is called receptor-mediated transcytosis.


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How does the NAD+/NADH ratio affect lifespan in vertebrates?
Here's the proximate physical implication of the ratio (from the Wikipedia article on NADH).

The balance between the oxidized and reduced forms of nicotinamide
  adenine dinucleotide is called the NAD+/NADH ratio. This ratio is an
  important component of what is called the redox state of a cell, a
  measurement that reflects both the metabolic activities and the health
  of cells. The effects of the NAD+/NADH ratio are complex,
  controlling the activity of several key enzymes, including
  glyceraldehyde 3-phosphate dehydrogenase and pyruvate dehydrogenase.
  In healthy mammalian tissues, estimates of the ratio between free NAD+
  and NADH in the cytoplasm typically lie around 700; the ratio is thus
  favourable for oxidative reactions. The ratio of total
  NAD+/NADH is much lower, with estimates ranging from 0.05 to 4. In
  contrast, the NADP+/NADPH ratio is normally about 0.005, so NADPH is
  the dominant form of this coenzyme. These different ratios are key
  to the different metabolic roles of NADH and NADPH.

So here's my question: how does this manifest in vertebrate aging? Is it something that's simply the resultant of other aging processes, or can the ratio also contribute to aging in a certain way?

What's the source of this quote?

Wikipedia (have added a note for clarification).

This study found a statistically significant decline in NAD+:NADH ratios and in intracellular NAD+ with age in the organs of rats.
They discuss that the activation of  PARP - the  NAD-dependent enzyme Poly(ADP-ribose) polymerase-1 instrumental in DNA repair - increases in aging organs (heart, liver, kidneys). This depletes cellular NAD+ levels via poly(ADP-ribosylation) of proteins. This reduced cellular  NAD+ then reduces the effectiveness of Sirtuins (Sirt1) which can deacetylate tumor-suppressor proteins such as p53.
Here's schematic showing the basic idea from their figure 10:

So, the inference is that oxidative stress in vertebrates increases with age due to lowered cellular NAD+ - i.e.,  consistent with the free-radical theory of aging.  This could mean that lowered cellular NAD+, NAD+/NADH in any given individual may well decrease said individuals lifespan.
The authors of the first study (Braidy et al 2011) suggest that therapies involved in maintaining high NAD+ levels may alleviate age-associated disorders.

Braidy N, Guillemin GJ, Mansour H, Chan-Ling T, Poljak A, et al. (2011) Age Related Changes in NAD+ Metabolism Oxidative Stress and Sirt1 Activity in Wistar Rats. PLoS ONE 6(4)
Smith, J., (2002) Human Sir2 and the 'silencing' of p53 activity, Traneds, Cell Biol. 12, 404


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How does the enzyme ATP Synthase use a proton concentration gradient to make ATP?
I understand what the enzyme ATP synthase does, but I'm not exactly sure how it does it. I've heard that it uses rotary catalysis, but how exactly does this work? How is the energy from the H+ ion harnessed, turned into mechanical energy, and then finally into the chemical energy stored in ATP? Why does the spinning of parts of the enzyme need to occur for this to happen?

Image from wikipedia page on ATP synthase
In brief, the addition and release of protons to the structure cause a conformational change that leads to another conformational change.  This series of conformational changes occurs in such a way that it induces a rotational motion.
The rotation of the central axel that extends through both hemispheres of this large complex is driven by the proton gradient.  Specific residues in the c12 ring are protonated in order to drive this rotation.  A high concentration of protons (in this picture the high concentration is found above the complex) allows each of the subunits in the membrane to be constantly loaded with H+ ammunition, ready to fire when it comes to be their turn.
The function of this axel is to slightly but significantly change the shape of one subunit at at a time in the red part.
Changing the conformation of subunits in the red part is what allows for the three steps in ATP synthesis to occur: binding of ADP and Pi, catalysis of the formation of ATP, and release of ATP.
All of these changes occur at the molecular level.  The proton forms a bond with a single amino acid of the entire protein complex, but this is sufficient to cause a difference in the most stable 3-dimensional structure of the whole.  This could cause either a cascade of changes that result in a net rotation or it could cause a re-stabilization of the structure due to electrostatic forces.
According to Vinit K. Rastogi & Mark E. Girvin in their 1999 Nature paper on the subject, it's more like the former:

Earlier models proposed simple rotational diffusion of a rigid c12 ring, possibly driven by electrostatic forces. The structural data on protonation-linked conformational changes in subunit c indicate that the process may be more mechanical, with local rotations within subunit c driving larger-scale rotations of the c12 oligomer as a whole, in a `wheels within wheels' type of mechanism.

The whole paper's a good read.  But this is as current as I am on the topic, and it's likely that a more detailed mechanism has been determined for the action of ATP synthase since 1999.


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NADH vs. NADPH: Where is each one used and why that instead of the other?
I know NADH is used in cellular respiration and NADPH is used in photosynthesis. What difference does the phosphate group make that the same one isn't or can't be used for both? Is there a greater reason for this separation or is it just coincidental? Why can't the two be interchanged?

NADH provides energy for Catabolic reactions
and as for NADPH it provides energy for anabolic reactions (Synthesis )

The phosphate group in NADPH doesn't affect the redox abilities of the molecule, it is too far away from the part of the molecule involved in the electron transfer. What the phosphate group does is to allow enzymes to discriminate between NADH and NADPH, which allows the cell to regulate both independently.
The ratio of NAD+ to NADH inside the cell is high, while the ratio of NADP+ to NADPH is kept low. The role of NADPH is mostly anabolic reactions, where NADPH is needed as a reducing agent, the role of NADH is mostly in catabolic reactions, where NAD+ is needed as a oxidizing agent.
You'll find some more information about this in chapter 2 of "Molecular Biology of the Cell by Alberts et al.

too bad I only have one upvote to give. A direct link to the section in Alberts that talks about NADH/NADPH was great!

Great use of the link to the chapter - I wish more authors did this.

I personally do not think Alberts et al is a very good reference for this as they do not mention a single anabolic reaction. The supplementary answer by @user9778 does this, and I would suggest the student consult a textbook of biochemistry to find out about biochemistry, not one about cell biology (or biology or molecular biology).

Just to clear out some things:
As stateted above, NADH is produced in catabolic reactions and is later used in the electron transport chain to obtain energy by converting NADH back to NAD+.
NADPH is primarily produced in the oxidative part of the pentose phosphate pathway. NADPH is used in
a) anabolic syntheses to produce cholesterol, fatty acids, transmittor substances and nucleotides.
b) detoxifying processes as an antioxidant. NADPH is for example an essential part of CYP450 in the liver and rereduces gluthatione (one of the most potent antioxidants in nature) in order to make it active once again.

It would be great if you provided some references for your response!

NADPH is found in the cytosol and stroma (chloroplast) of eukaryotes. NADH is more ubiquitous, but mostly found in bacteria and in mitichondria, possibly evidence for the endosymbosis of bacteria in eukaryotes. Neither can pass easily through a membrane.


text:
How do I change bond colors to something besides a different hue in Coot?
I can modify the colors of carbons in Coot under Edit, Bond Colours..., but that only gives me different hues.  Is there a way to change the color to something less-saturated (or perhaps slightly transparent) so I can identify the "active" molecule I'm working on versus a template?
The menus seem no help, I'm wondering if there's some scripting magic that can do this.

@Rory, they're not buttons

You could try other visual differences, like make what you're interested in ball-and-stick, and everything else wireframe, like in this example:
.
.... Because, from: http://www.ysbl.york.ac.uk/~lohkamp/coot/doc/coot-python.html

procedure: hilight_binding_site (imol, centre_residue_spec,
  hilight_colour, radius): hilight-colour is specified in degrees (round
  the colour wheel - starting at yellow (e.g. 230 is purple))

It looks from this like you only get to choose Hue (color_map_rotation) and not Saturation or Lightness, even with the script interface.
However, text can be full RGB

3.28.3 (set-font-colour red green blue)
where:
red is an inexact number green is an inexact number blue is an inexact
  number


text:
What is Peter's rule in neuroscience?
I have heard and read about Peter's rule informally in the past, but never saw a formal definition or description.
Informally I have learned to understand Peter's rule as the assumed correlation between the amount of overlap between axons and dendrites and the post synaptic density in the synapse. Here is a sample of the search results in Google.
Is my interpretation correct? Is there a more rigorous, perhaps quantitative,  definition of Peter's rule?

Your link is not working. Also, it would be nice if you give a short 'informal' description of it yourself.

Thanks @Gergana. I have updated my question and fixed the link. Let me know if there is anything else I can do to improve it.

I think that your interpretation is correct, although Principles of Neural Science (Kandel et al.) doesn't mention Peter's rule (which is where I would have hoped to find a simple explanation).
According to Binzegger et al. (2004), the idea behind Peter's rule dates back to Peters and Feldman (1976) and Peters and Payne (1993), though the Rule per se may have been coined by Braitenberg and Schultz (1991; at which point it was still called Peters' rule). Binzegger et al. describe it as:

They assumed that axons simply connect in direct proportion to the
  occurrence of all synaptic targets in the neuropil. The rule can be
  extended to provide more precise estimates by taking into account the
  detailed morphometrics of the dendritic and axonal trees of the
  different neuronal types.

To paraphrase Binzegger et al., in the simplest form of Peter's rule, the number of synapses in a cortical layer are evenly distributed across the potential target neurons. So there would be a direct proportionality between synapses and targets.
The second sentence of the quote above is the meat of the Binzegger paper. They also present a mathematical model of a more complex and realistic variation of Peter's rule which takes into account different types of postsynaptic neurons and the fact that not all cells receive synapses.
Braitenberg V, Schüz A (1991) Peters' Rule and White's Exceptions. In: Anatomy of the Cortex, pp 109–112. Berlin: Springer.
Peters A, Feldman ML (1976) The projection of the lateral geniculate nucleus to area 17 of the rat cerebral cortex. I. General description. J Neurocytol 5:63–84.
Peters A, Payne BR (1993) Numerical relationships between geniculocortical afferents and pyramidal cell modules in cat primary visual cortex. Cereb Cortex 3:69–78.

"taking into account the detailed morphometrics", i.e. looking on an EM image? :P see another exception

So one should cite the papers Braitenberg1991 and Peters1976 at least if one talks about Peters' rule?

Here is a definition taken from a Scholarpedia article on computational neuroanatomy:

The critical underlying question remains: how does the number of synapses between two neurons depend on the overlap between their dendritic and axonal trees? According to "Peters rule", synaptic contacts occur where dendrites and axons happen to be in apposition. These "potential synapses" are required but not sufficient for an actual synapse formation; and the expected number of connections between two neurons is proportional to the product of their dendritic and axonal trees densities (e.g. Peters et al., 91).

This seems to be saying that there are really two pieces to Peter's rule-- first that "synaptic contacts" (potential synapses) actually occur where axons and dendrites share space, and secondly that the proportion of these contacts that are real synapses is proportional to tree density.


text:
Can Naegleria fowleri enter through wounds into the bloodstream?
All the sources I've read said that Naegleria fowleri enters the brain through the nose. But lets say that someone had cuts on their arm or leg and they are swimming in water that is conducive to Naegleria fowleri growth. Could it enter the cut into the bloodstream and then into the brain or cause some other type of damage if it enters the bloodstream?

No, Naegleria fowleri is a free-living excavate form of protist that lives in warm fresh water. Fowleri finds its way into the brain by eating through the olfactory neurons in the nose where it multiplies itself greatly by feeding on nerve tissue.
Once it penetrates the nervous tissue, fowleri's feeding  results in significant necrosis of and hemorrhaging in the olfactory bulbs. The protist then climbs along nerve fibers through the floor of the cranium via the cribriform plate and into the brain.
Since the protist travels by feeding on nervous tissue, fowleri could not enter the brain via bloodstream.
Just some more facts about Naegleria:

Death usually occurs within 14 days of exposure due to destruction the autonomic nerve cells of the medulla oblongata.
Luckily for everyone this disease is rare. There were only 300 cases as of 2008

Maybe the blood-brain barrier would also deter the fowleri from entering the brain. Could the fowleri thrive in the bloodstream?

Is there a drug treatment for this protist?

I know antibiotics would not help. But that is never a concern since it is rarely (if not ever) identified in time to save a life.


text:
Did human hairs actually evolve from scales?
What is the evolution of hairs? Did they evolve from scales?

From a little research I have been able to find some of the hypotheses and speculations but no papers expressly confirming or denying the matter.
One theory displayed in "The evolution of mammalian keratinized structures" (abstract only) is that mammalian hair developed along the following pathway:

Hair follicles develop between reptilian like scales.
A granular layer formed in the pilosebaceous canal (see diagram of modern human skin)
The granular layer extended into the epidermis.  I read this as the point where scales started to more resemble mammalian skin.  It is suggested that this was as a result of a need for increased flexibility and agility.
Hairs began to protrude through the follicles (as seen in rat tails today).  Adaptations to organisms living in cold conditions led to the production of wool to help conserve heat.

So this paper would suggest that hair production evolved separately from but parallel to the movement away from reptilian scales.
"Some Speculations on the Evolution of the Vertebrate Integument" (Paul F. A. Maderson) suggests an entirely different origin of hairs.  He proposes that hairs ultimately evolved from sensory appendages that were involved in the detection of temperature in early synapsids.  The extension of these micro-limbs into hairs was selected towards as a result of their thermally insulating effect by-product rather than for their sensory role, however.

As to the early evolution of mammalian hair, Rowe et al. (2011) hypothesized that the primitive function for hair was not thermoregulatory, but rather for tactile sensation (contra the hypotheses of Spearman and Maderson). Rowe et al. say:

Body hair develops as migrating neural crest cells induce patterns of
  tiny placodes that mature into hair follicles equipped with
  mechanoreceptors. These include lanceolate endings (velocity detectors
  excited by hair deflection), Ruffini receptors (tension receptors
  activated as hair is bent), and Merkel cells (slowly adapting
  sensors). In ontogeny, hair is first sensory, and only later does it
  insulate, as underfur thickens and thermoregulation matures.

So the developmental argument is in favor of tactile sensation.


text:
How are the gene sequences of individual sperm and egg cells "randomized"?
What I mean by "randomized" is, in the place where an egg cell or sperm cell is made, what is the mechanism by which each one is not made identically? Though I am a layman, I'm pretty sure that if the sperm cell that was right next to "me" had made it to the egg instead of the one that did, the resultant human would have a different genomic sequence and different features.

are you familiar with concepts like haploid, homozygos, alleles, chrossing over? I am trying to figure out how high scientific level my answer should be.

Meiosis is the type of cell division responsible for the diversification of genetic material among egg and sperm cells. The diversity comes primarily from crossing over (Prophase I) and the cell divisions (Telophase I & II) later on in the process.

Meiosis begins with one diploid cell containing two copies of each
  chromosome—one from the organism's mother and one from its father—and
  produces four haploid cells containing one copy of each chromosome.
  Each of the resulting chromosomes in the gamete cells is a unique
  mixture of maternal and paternal DNA, ensuring that offspring are
  genetically distinct from either parent. This gives rise to genetic
  diversity in sexually reproducing populations, which provides the
  variation of physical and behavioural attributes (phenotypes) upon
  which natural selection acts.

Further detail of the precise phases can be found in the Wikipeida article.

[picture from wikipedia]

I think we can attribute this to sheer probability. The human genome contains around 3 billion base pairs. When you consider recombination from chromosomal crossover that occurs in germ line cells, there is an astronomically huge number of possible unique combinations that can be made.
Of course, males generate many many sperm, so some of these are bound to be similar. But the number of sperm produced by any individual doesn't come anywhere close to the number of possible unique sperm that he could produce.


text:
What are the constraints when growing an artificial brain?
Are there any experiments on growing artificial brains from brain tissue?
What are the constraints? Will such tissue grown to the mass greater than that of human brain surpass it in intellect or it would need additional conditions?

Please try to clarify your question, it's not entirely clear to me what you are asking. We're also far, far away from anything near growing a functional brain in the lab, so this question might be close to unanswerable.

It is already very difficult to grow neurons in culture, let alone having them form a brain.

You may want to look into the study of embryology.  A jumping off point to get some search terms (as this is a huge area) would be http://en.wikipedia.org/wiki/Neural_development_in_humans.  For a more microscale view, look into http://en.wikipedia.org/wiki/Axon_guidance

A term from counting bacterial colonies comes to mind as an answer to this question: TNTC (too numerous to count).

The comments above are quite relevant -- we are years / decades away from growing functional brains in the lab, so there are probably innumerable constraints that we have likely not even thought of yet.
That being said, you might find this paper interesting: "Adaptive flight control with living neuronal networks on microelectrode arrays" [1]. The authors are able to succesfully culture rat neurons and electrically interface with them in order to control pitch and yaw in the XPlane flight simulation software.  It's a very crude system compared to an actual brain, but it's able to successfully use cells as rudimentary living neural networks. If you consider this to be a successful "artificial brain," then your constraints are all the ones associated with culturing neurons.
[1] DeMarse, et. al 2005


text:
What is meant in biology by the term "evolved"?
A student asked me this the other day and I thought that I would ask it again here. If one organism is said to be "more evolved" than another, what exactly does this mean?

Just to be clear: are you specifically asking what “more evolved” means or what “evolved” (generally) means?

politics, history and humanities uses this sense of the word evolved - as an improcement - more than biology does

Highly related: Are we “more evolved” than present-day bacteria?

"More evolved" is actually meaningless in all contexts. See terdon's answer for a good explanation.
In the strictest sense, an organism can be said to be more divergent than another when comparing both to an outgroup, such that there is an inferred most common ancestor in reference to which to make the comparison. In this case, one organism is more divergent if there are more changes to this organism than the other, relative to the reference point.
However, when speaking, many people get lazy, and use "more evolved" as shorthand, wishing it to mean something like "more divergent". Even "more divergent" is meaningless in the following contexts:

when there is no outgroup understood
when describing increasing complexity (obligate parasites have lost complexity and have had more evolutionary changes than their non-parasitic relatives)
when the outgroup is poorly chosen. Mammal vs reptile comparisons should not, in general, use prokaryotes as the outgroup.

Edited 2013/12/06 to reflect the precision in the answer by terdon.

Can you suggest sources about evolutionary comparative methods?

I disagree, your definition refers to more diverged evolved is not qualitative. You cannot be more or less evolved unless you are actually comparing generation numbers.

Strongly agree/like this statement. Would also like to add: please emphasize teaching your students that evolution is not something that is worked towards, so much as naturally selected. I think heavy, heavy emphasis on natural selection is what you should explain, until your students demonstrate that they understand things "evolve" simply because they survive, and they survive if they are fit.

I cannot improve on Thomas Ingalls' description of when "more evolved" is appropriately used, but the inappropriate/lazy use of the phrase is so prevalent that it deserves further comment. In my experience, the most common use of the phrase "more evolved" is when describing the increased complexity of one organism versus another. This usage is not just meaningless, but wrong and harmful, and springs from a misunderstanding of what evolution implies. Evolution is emphatically not the same as increased complexity.
I try to avoid saying "more evolved" and tend to favor "more complex", "less simple" or "less primitive." "Primitive" has its own problems, since it sometimes brings with it the connotation of evolution (a "primitive eye" or "primitive nervous system" are common phrases), but it at least avoids an explicit misuse of "evolved."

“more complex” unfortunately suffers from similar problems.

@KonradRudolph Do you mean that "more complex" has the same problems as "more evolved"? Or rather that it has the same problems as "more primitive"? Can you expand? What phrase do you prefer? I think "more complex" is very near to what people actually want to say when they use the term "more evolved." It does come with a bit of a value judgment about what complexity means, but I have a hard time thinking of a phrase that has much less baggage. If one is careful to specify the dimension, I think it can be reasonable to discuss the relative complexity of different systems.

Well, the first question is: what is complex? Genome? Phenotype? Specifically, behaviour? And how do you measure complexity? Once you have agreed on that (but people don’t) – what does this actually tell us? In reality, not much. People just use it as they would “more evolved”. In reality, it makes much more sense to speak about specific features, not about an ill-defined, poorly-understood and not comparable whole.

@KonradRudolph I agree with you in general, and I was not advocating using "more complex" when comparing whole organisms. But I stand by using "more complex" when discussing specific features. It's true that complexity is a flexible ill-defined concept, but at least a speaker can specify how they are using the phrase. I think it's important to have some way to express the concept of relative complexity, which is meaningful if defined for a particular domain/feature.

There is no such thing as more or less evolved. At least not outside popular media. The only reasonable comparison one can make is comparing generation numbers. You could say that a species that has undergone X generations is less evolved than one that has undergone X*2 generations. It just doesn't mean much.
Evolved is not a quantitative term, you cannot really be more or less evolved than something else.

It is a phrase in common parlance without scientific meaning, fitting in the same category as devolved or devolution. It is as @terdon said:

There is no such thing as more or less evolved.

In a scientific context you should always find the evolutionary measure in question and the methods for quantifying that measure.
In a biological context the phrase would fail to find meaning, when evolution is a function of fitness. In such context fitness is inevitably tied to environmental parameters. The more complex these parameters, the more niches may be available for potential species, with temperature being one of the strongest factors (See: Effective evolutionary time Hypothesis ). Take this assertion with the necessary caution, as it is far outside my expertise.
Mostly I have come across the phrase more evolved in reference to large, tangible species, and also in science fiction.
Tell your student, to always be aware that in the end the unicellular species make life for us on this planet viable - we coevolved. But they also eventually consume/recycle us in one way or another, and surely will outlast us. It takes extreme effort and finesse for a large, energetic multicellular host to obtain, maintain and retain its niche on this planet. In all of the field of molecular biology there is nothing quite like Immunology.
For a mind experiment, let the student imagine soil with different pH, of the same plant species which equal seeding-times.
The outcome may be something as shown below. The phrase "more evolved" clearly fails to describe such a scenario of one generation of plant species, and hence is not suitable in an objective description of evolution.
Sidenote: Al3+-ions are toxic to plants, stuning root growth and phosphate intake. With increased pH, more aluminum dissolves.

I have mostly seen it used to mean "possessing features that appeared most recently in the historical evolutionary record". Thus a human is considered more evolved than a chimp because our bipedality, hairlessness and large brain appeared more recently than the features of chimps, and a chimp is more evolved than a fish because fish very similar to ones alive today appear in the record before anything resembling an ape, and so on.
I think it's pretty poor use of language, frankly, since it suggests linearity and ordering to evolution that is simply not there, conflates gross morphological change with change in general and incorrectly implies that stabilising selection is not evolution.


text:
Is there a correlation between muscle fibers and body types?
I have been told the number of muscle fibers a particular muscle has varies from person to person. Unfortunately, the person who told me this did not know much more than this. Initial searching on the web did not reveal much detail on this; some random sources suggested there was a correlation but they weren't referenced.
Is there a general correlation between the number of muscle fibers and body type (mesomorph, endomorph, ectomorph)?
What about a correlation between muscle fiber type (Type I/Type IIa/Type IIx/Type IIb) and body type?

Don't know about fibre numbers, but there is a correlation between fibre types and athletic ability, in that the ratio of type I to II (slow-twitch vs fast-twitch) determines whether a person would be naturally good at sprinting vs endurance activities. If you google for something like "striated muscle fibre twitch endurance" you should find quite a bit on that. I would imagine that your somatotypes would be quite influenced by fibre type ratio...

Body type is something about your constitution. I would probably formulate the question differently to ask for correlation between muscle types and physical strength/endurance, for there is some known correlations here (as @Amanda mentioned in her comment).

A recent paper called 'Genetic Influences in Sport and Physical Performance'[1] states:

"Muscle fibre type determination is complex. Whilst initial composition is likely to be strongly influenced by genetic factors, training has significant effects on fibre shifts."

They also go onto say that:

"However, the role of genetic variation in determining psychological state and responses remains poorly understood; only recently have specific genes been implicated in motivational behaviour and maintenance of exercise."

Finally:

"With the current state of knowledge, the field of genetic influences on sports performance remains in its infancy, despite over a decade of research."

An older paper which also examined fiber types stated that:

"These results reveal the existence of large interindividual variability and gender differences in the most common characteristics of the human skeletal muscle."[4].

Another study hypothesises that there may be racial differences in muscle fibre types.[2]. It's also said that a large variation in fiber composition of skeletal muscle within subgroups of athletic ability. This suggests that factors other than fiber-type composition contribute to performance.[3].
A small study carried out in the Croatian Navy found that ectomorphs had a better ability to sprint than endomorphs.[5]. They also found a positive correlation between calf girth and sprinting ability.
The information is a bit disjointed and sparse. However, to finally come around to the question at hand, it seems that although there may be differences according to body type initially (which obviously also has a genetic basis), training and physical activity contributes significantly to what number and types of fibres individuals possess.
There are lots of sport-specific research papers examining individuals' performance and suitability on body types.
A note on somatotyping: I guess it might also be handy note that somatotyping (endomorph, ectomorph and mesomorph) is just one theory on measuring an individual and it does have critics. The theory was initially developed in an attempt to link body type to behaviour.
It's been suggested that measurements like BMI are much more objective and useful.[6]. Another point made was that bodies change according to a number of environmental variables, nutrition etc.[7]. For example, one study suggested that intense labour during adolescence may affect somatotype (there are a few similar studies).[8]. So perhaps while using somatotypes to identify a person at one point in time is useful, it has limits in use as a long term classification.
This point probably has more relevance to the question at hand since with training and physical activity, a person can potentially change their somatotype at least to some extent; and also the number and types of muscle fibers (which evidence supports).

Puthucheary Z, et al. Genetic influences in sport and physical performance. Sports Med. 2011. 41:845-59.
Nielsen J. Glucose intolerance in the West African Diaspora: a skeletal muscle fibre type distribution hypothesis. Acta Physiol. 2011. 202(4):605-16.
DeLee: DeLee and Drez's Orthopaedic Sports Medicine. 3rd ed. Saunders.
Simoneau, et al. Human variation in skeletal muscle fiber-type proportion and enzyme activities. AJP - Endo. 1989. 257(4):567-572.
Sporis G. Impact of body composition on performance in fitness tests among personnel of the Croatian navy. Coll Antropol. 2011. 35(2):335-9.
Maddan, et al. The BMI as a somatotypic measure of physique: A rejoinder to Jeremy E.C. Genovese. The Social Science Journal. 2009. 46:394–401.
Parnell. Simplified somatotypes Original Research Article. Journal of Psychosomatic Research. 1964. 8(3):311-315.
Ozener, et al. The effect of labour on somatotype of males during the adolescent growth period. Homo. 2008. 59(2):161-72.

Awesome, I will look into all those papers for sure :)

I have been studying somatotypes on my own since 1994 and yes, I have been observing the total correlation between biotypes and the predominance of one type of muscle fiber in relation to others.
Since 1985 I have been developing a training system that is exactly above the differentiation of biotypes.
I was able to develop a fiber differentiation system through a localized stress test. This test allows me to leave through a result obtained the qualification of fibers predominant in a certain muscle group. Through these observations I can safely affirm that YES, there is a pattern that repeats and shows that there is a very close correlation.Although this test has a great margin of subjectivity, it has been helping me and proving very effective

Welcome. Can you add sources to your answer? If you are an expert as you claim, adding some relevant references to allow other users to background read on your topic shouldn't be much of an issue. Thanks.


text:
DNA synthesis companies: cost per base, turn-around time, codon-optimization algorithms
I would like to synthesize a 3.4kb gene (originally isolated from soil bacteria) and transform it into E. coli. There are several companies (DNA2.0, GeneScript, BlueHeron) which will synthesize the gene for you. I would like to know how these companies (or others) compare with each other in terms of:

Codon optimization - most of the companies are going to codon optimize the sequence and thus increase the protein expression in the desired host. Recently I learned that there are different algorithms that can be applied. I am mostly interested in how the codon-optimization is performed in the different companies and whether there are some direct comparisons of protein expression between them.
cost per base - I would like to find the cheapest one. In general, the cost of gene synthesis usually depends on the size of the fragment, as well as the complexity of the sequence. But on the other hand, DNA2.0 can synthesize 1kb fragment and 5kb fragment for the same price.
Turn-around time - which company will synthesize the fragment the fastest? I think that this mainly depends on size. Of course I have an option of ordering 3 x 1.1kb fragments and joining them myself, but then I have to sequence-verify the final product. So, I need to find the trade-off.

Please, keep in mind that I am not asking about your favorite company, but about specific characteristics of the companies.

The question about price is probably too localized, it changes too fast and those questions are discouraged across the SE network. For the turn-around time you'll only get anecdotes here, which probably won't help much. I'd focus the question on the codon optimization, though I fear the answer will be that the algorithms are prorietary and they won't tell you how they work exactly.

These are good points. I would thing that the information about cost will be valid once you match it with the date on which the answers are posted. As for turn-around time, I came across a blog, where there was a plot of turn-around time vs length of DNA construct for several companies, so average values can be definitely taken into account. But mostly, I really would love to know about their codon-optimization algorithms but perhaps you are right and they are proprietary. Hopefully, the main ideas are not.

Are you working in academia? It might be worthwhile to call the companies directly and see if there is a discounted rate for your institution (another lab or department may have already set something up).
You won't be able to get information on the different algorithms if they are proprietary.  However considering that codon usage data is public and shared knowledge, I can't imagine that the different algorithms are that much different. I think there are some tricks for choosing certain codons near the transcription start site in some organisms? From what I hear, the algorithms are constantly changing. I could tell you how my E. coli optimized gene from GenScript worked two years ago, but they'd probably design it differently now.
Okay - GenScript calls their algorithm "proprietary", so they are not sharing the details. DNA2.0 says their algorithm is patented, so it's out there for inspection. They published a PLOS paper on their E. coli algorithm: Welch et al..
Although, maybe all they do these days is spit out codon sequence randomly:

The results obtained in this study indicate that the codon
  randomization method is a superior strategy for codon optimization. A
  significant improvement in protein expression was obtained for the
  largely established process of chymosin production, showing the power
  of this strategy to reduce production costs of industrial enzymes in
  microbial hosts. (Menzella 2011)

Stitching smaller synthesized fragments works well if you're pressed for time, but it's usually more expensive. However, sometimes these companies do special pricing on synthesis for <1kb, which makes stitching a great choice. Turnaround is generally faster for three 1kb fragments than one 3kb fragment.

Thanks for your answer @Amy. So, you have experience with GenScript. I would like to ask you some specific questions. Would you mind emailing me so that I don't extend my comment into long discussion? My email is gvandova@stanford.edu

Here is a blog post from Ginkgo BioWorks that graphs the turn-times from 3 major suppliers:
http://blog.ginkgobioworks.com/2012/01/14/commercial-gene-synthesis/

Thanks, I already looked at it, but yeah, it is really useful.

And here is a blog post from Reportergene that compares actual prices, even do I agree with Mad Scientist that the question about prize is probably too localized.
http://www.reportergene.com/2011/08/gene-synthesis-review.html


text:
Why would taking antibiotics increase stamina and energy?
I often hear that people who are taking antibiotics experience wild fluctuations between feeling full of energy and completely alert but soon after feeling impossibly fatigued and sick.
Does this have anything to do with the antibiotics being used by the body as anything? For example as a hormone or as a source of nutrition?  Is this this a reported side effect when used for other infections?

Mono is caused by the Epstein-Barr virus.  The antibiotics won't do anything to fight against that, anyway.  Sometimes antibiotics are given to fight the strep throat infection that can accompany mono.

ah didn't know that. Well, they tell me its mono... haha

can't really answer this, but I wanted to mention that there are some stimuli that can make you feel full of energy. There are anecdotes that drinking some radioactive isotopes also make some people feel great.  See "The Great Radium Scandal" by Roger Macklis in the August 1993 issue of Scientific American.

I have never heard about this phenomenon from my patients or professors at the Medical School, but this is a possible mechanism that comes to my mind.
One of the classification for antibiotics takes consideration the effect on bacteria. Two possible effects are either stopping the proliferation (and letting the immune system to kill those that are currently present in the body) or killing bacteria directly.
The second approach is obviously more effective but has one big disadvantage: massive death of bacteria leads to the massive release of their toxins that are normally trapped within they bodies (so-called endotoxins). The symptoms you describe as "impossible fatigue" match exactly the symptoms of bacterial intoxication -- and this can increase upon the antibiotics intake.
Depending upon the bioavailability and pharmacokinetics some antibiotics might not kill all bacteria "on the first run" and the symptoms of intoxication recur several times with decreasing severity of manifestations.

Over the years since this question was posted, gut flora research has become mainstream. Could the elimination of gut flora cause a statistically significant increase of nutrients in the blood stream? Could that be a source of the proposed effect?

"There are antibiotics which contain carbohydrates, such as Gentamycin and Streptomycin (the aminoglycosides). These must be the antibiotics that could account for this phenomenon."
My conjecture that the carbohydrate moities contained within aminoglycosides account for the high energy is incorrect. Aminoglycosides are NEVER metabolized by the body, they are excreted out into the urine UNCHANGED. See here: http://www.ebmedicine.net/topics.php?paction=showTopicSeg&topic_id=43&seg_id=839
And even if it were possible to metabolize the carbohydrate molecules within them, the energy released would be far less than the energy consumed to break their linkages in the first place, thus placing a negative energy balance on the body, and thus, not providing the burst of energy that is apparently observed after taking antibiotics.


text:
How does the brain's energy consumption depend on mental activity?
What is the impact of mental activity on the energy consumption of the human brain?
I am most interested in intellectually demanding tasks (e.g., chess matches, solving a puzzle, taking a difficult exam) versus tasks with a similar posture but less demanding (e.g., reading a newspaper, watching TV).
I heard that energy consumption stays remarkably constant regardless of the mental activity (and energy consumption can be explained by elevated heart rate due to stress). However, it seems to contradict techniques such as fMRI, where the change in metabolism is measured (unless the relative change is really small).

The energy consumption doesn't vary that much between resting and performing tasks, as discussed in a review by Marcus Raichle and Mark A. Mintun:

In the average adult human, the brain represents approximately 2% of
the total body weight but approximately 20% of the energy consumed
(Clark & Sokoloff 1999), 10 times that predicted by its weight alone.
Relative to this high rate of ongoing or “basal” metabolism (usually
measured while resting quietly awake with eyes closed), the amount
dedicated to task-evoked regional imaging signals is remarkably small.
The regional increases in absolute blood flow associated with imaging
signals as measured with PET are rarely more than 5%–10% of the
resting blood flow of the brain. These are modest modulations in
ongoing circulatory activity that rarely affect the overall rate of
brain blood flow during even the most arousing perceptual and vigorous
motor activity (Fox et al. 1987, Friston et al. 1990, Lennox 1931,
Madsen et al. 1995, Roland et al. 1987, Sokoloff et al. 1955).
[...]
From knowledge of these relationships, one can estimate that if blood flow and glucose utilization increase by 10%, but oxygen consumption does not, the local energy consumption increase owing to a typical task-related response could be as little as 1%. It becomes clear, then, that the brain continuously expends a considerable amount of energy even in the absence of a particular task (i.e., when a subject is awake and at rest).

Techniques like fMRI measure relatively small differences, their existence does not contradict the claim that the energy consumption of the brain doesn't change a lot between the resting state and performing an activity.

1. Raichle ME, Mintun MA. BRAIN WORK AND BRAIN IMAGING. Annual Review of Neuroscience 2006 Jul;29(1):449-476.

well there seems to be evidence that there is a lower and upper limit of energy concumption for doing cognitive CONSCIOUS/AWARE tasks my linked papers contain http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2855379/bin/ukmss-29376-f0001.jpg So we have some evidence that energy consumption can not raise on and on, as we loose awareness then. It looks more like we need a distinct frame of energetic activity to allow consciousness at all. That fMRI is a pretty inaccurate method mainly useful for visualizing neuronal correlates is no big news.

I found Does Thinking Really Hard Burn More Calories? - Scientific American going in the same way - "Unlike physical exercise, mental workouts probably do not demand significantly more energy than usual. Believing we have drained our brains, however, may be enough to induce weariness".

What I wanna know, since the brain's energy consumption is a) constant and b) high for an organ its size, is: How can we INCREASE its energy consumption and get thin without needing to work out ?!

I answered on the facts of this question already on skeptics.SE, here and here. You should read both papers very carefully, I highlighted the most important facts but this is a very tricky question, esp. when it comes to defining what mental activitiy is. The papers also give an explanation of how fMRI signal is linked to NEURONAL activity, as far as I remember there is no strong direct link.
You assume in your question that a mathematician solving a differential equation needs higher mental activity than a child reading a book. Is this legitimate? It seems intuitive but also very subjective. In the paper they mention that for the highest and lowest energy consumption we lose consciousness. I will not draw conclusions from this. However, you are talking about conscious mental activities so this may answer your question. To me it means more that the understanding of the human brain in neurobiololgy is on the level of the Rutherford Atomic Model in Physics at the beginning of the 20th century. We have not really got a clue how information is processed and how it's constrained by physical laws and principles of entropy and energy. By reading the 2 papers it looks more like the human brain is not raising energy consumption as a computer would (the computer analogy pretty much fails when compared to the human brain). Most of the energy is used for unconscious processes in "standby mode".
As in physics, extreme cases such as savants and the mentally disabled are probably the best starting point to exclude possible models of human brain and physical boundary conditions as we cannot approach the questions of human brain in a reductionistic way. How can savants like Kim Peek process such huge amounts of information AND save it. He is able to scan books pages just once and know them by heart thereafter. His brain does not, however, consume more energy than an average human brain. So mental activity is probably not a very good term, quantity, or even really suited to be scientifically used. Does neuronal activity mean mental activity (in the sense of your definition?) Reading the papers, the problem is the separation of mental and neuronal activities. At first you have to know what are the basic brain functions and processes that are consuming most of the energy. However the brain is not built in modular way like a computer (most energy is used here for constantly refreshing RAM). So there is not really a objective way to analyse and separate this modular energy consumption, if it even is modular.
In my opinion, most models about information processing in human brain are intuitive guessing (again Rutherford). We need much more detailed experiments and data (Blue Brain Project). fMRi is like analysing a atom with a magnifying glass. Also, the more prosperous approach from a biophysical perspective is probably not the level of "mental activity" but the hard-based amount of information processed by human brains and linked energy consumption (Kim Peek). But therefore we need a model of how this information is saved in human brain. Do normal humans save the same information as Kim Peek scanning a page or are we just unable to recall it consciouscly? When solving a differential equation, how much energy do you consume when recalling facts and is that experience not similar to reading a book? How much is mental logical tasks and is there really a difference at all?
I will stop here, hope you gained some insight that the question is of course important but too early to be definitively answered. I think we will learn a lot more from projects like Blue Brain as we have from fMRI experiments.

Thanks, though I am far from making analogy with computer, especially when it comes to the information processed. Actually, the energy usage (at least - in principle) can be measured by heat generation, even if nothing is known about the process. "You assume in your question that a mathematician solving a differential equation needs higher mental activity than a child reading a book. Is this legitimated?" - hard to say; better to compare a mathematician during a few hour competition vs control.

@PiotrMigdal so what answer are you looking for? Any correlation between "mental activity" and energy, although you do not really define what the difference between neuronal and mental activitiy is? I'm a bit confused now. Measuring generated heat is far more inaccurate than oxygen consumption by fMRI. Even more unknown factors. Also in these papers they actually did compare cognitive tasks vs. resting brain afair. I'm not sure where I should point you to. Maybe you should ask first on cognisci.SE wether reading a book and solving a puzzle is really of very different kind. I tried to point

to some neurobiological facts. But lets wait for other answers it's for sure a tricky question, but imho currently too much terminological flaws for a clearcut answer.

@WernerSchmitt you may want to participate in this meta discussion =)

This sounds wishy-washy. In fact, we do have a pretty solid understanding of “how information is processed and how it's constrained by physical laws and principles of entropy and energy.” We might lack the computational power to build good predictive models but the physical, chemical and molecular biological basis is well understood. The whole “we don’t understand the brain” discussion is really a red herring. We do. It’s just that the brain models a very complex network with certain emergent properties, remodelling of which is extremely expensive.

@Konrad: If you don't now about the emergent properties then you don't understand the brain in a meaningful sense. More importantly if you don't think that predictive models are the standard for what it means to know something in science, than what's your standard?

@Christian I disagree. Most of classical science is simple enough to be grasped by us but this is a paradigm of the past. Models of biological systems, be it the brain, a single cell, an ecosystem or sociology, are simply too complex to be looked at in total, down to the smallest detail. You have to zoom in and out. As long as we have understanding on a given level and know how the levels interconnect, we understand the system. If you demand that we can look at all levels at once then I predict that modern science will fail. In all the examples listed.

@KonradRudolph Yes, modern science is a failure. Drug discovery is still mostly a matter of bruteforcering componends through huge screening libraries and then hoping that a few componends that hit go through clinical trials. Nearly all drugs fail. The number that succeeds is statistically insignificant (p<0.05). We don't even make process at getting better but discovery of new drugs. As each year goes by  exponentially more expensive to discover new drugs through Eroom's law. Then we don't even really know how those drugs that do work, work.

@Christian Note I talked about the principle. If you don’t think science can ever understand these subjects, why do you study bioinformatics, then? Drug discovery is a completely different thing: we simply don’t have any good models here (but note that this is changing – will change).

@Konrad: (1) When I choose to study bioinformatics I had a bit more faith in it. I don't think the the molecular biology field produces the return it promises. My personal bets are on QS/Health2.0. (2) I'm not saying that science will never understand the subject. I'm agnostic about whether it will. If you however want to claim that you understand something in a scientific sense than you got to make predictions with your model. Redefining success is silly.

This answer relates closely to the classic myth

We only us 10% of our brain power

As with many truisms it holds a grain of truth.  Large areas of the brain are specialized for tasks like the visual and motor cortices.  Other areas are known to be responsible for spatial memory (hippocampus) and emotional learning (amygdala).  Higher order functions like you're describing are classically assigned to the prefrontal cortex, but that means little.
Because there is some level of functional specificity throughout the brain, the fMRI studies you mention generally look at many places in the brain (nearly) simultaneously.  They then compare relative activation in different areas under different conditions, and are clever about how they frame their experiments to determine which areas are associated with which responses.
The most common method of measuring activity is through the BOLD response, which measures haemoglobin's oxygenation state as a proxy for the amount of blood flowing into the area under the presumption that there is high metabolic demand there.  For the purposes of this discussion, this is fairly useful since glucose delivery should be a reasonable proxy for metabolic demand even if it has limitations when it comes to predicting neural activity.
So which areas are metabolically more active while doing a cognitive activity?  In this study they test exactly that.  Their basic finding is that chess does increase mental activity in certain areas of the brain, particularly the parietal and occipital lobes in real game conditions, and that the activation was relatively bilteral between the left and right hemispheres.  I just glanced through it, but it looks like the authors were surprised that the activation was less pre-frontal and more visuospatial.
I believe this supports the logical conclusion: thinking takes energy.  But your brain is used for many things, so the change in activation is best understood in a relative sense.  Watching TV also takes energy, preferentially in the visual cortex.  As does playing ultimate frisbee, in the motor cortex.
References:

Logothetis, Nikos K., 2008. What we can do and what we cannot do with fMRI, Nature 453, 869-878
Atherton M, Zhuang J, Bart WM, Hu X, He S, 2003. A functional MRI study of high-level cognition. I. The game of chess, Cognitive Brain Research 16.


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Does the genetic expression of specific physical traits ever correlate to behaviour?
Over at skeptics, there were a couple questions asked as to the correlation of specific physical traits in relation to personality/behaviour.  For instance, the simian line as well as red hair.  Now, I did my best to answer these questions, with what I understand as there being a long history of people attempting to correlate external physical characteristics with behaviour (see the disgraced "art" of phrenology for instance).
However, in answering the simian line question, I did come across some weak correlations.  It got me to wondering if this is an area of exploration in terms of perhaps one gene sequence for a physical trait somehow being tied with another gene sequence for behaviour.
So, do any physical characteristics being expressed through genes correlate to behaviour?

cognitivesciences.SE has started, imho this question belongs there as a biologist has no scientific definition of what "personality" is. There are so many methodical flaws to this question that I dont where to start... Surely you can measure any correlations you want with the "right" measurment setup and self-chossen definitions. Instead of pointing ot "possible" correlations I would rather ignore/close such questions, but thats why I left prejudices(skeptics).SE. Best you can do is to ask if behaviour is manifested in genes. Then its is more a interaction of distinct enviromment and subject

@WernerSchmitt does the edit refine the question more to your liking?

no need to edit immediately, just my view. The problem to me is that behaviour originates from social evolution. "Behaviour" like Autism or Asperger are clearly caused by genes. But then the judgement of such behaviour as unnormal by normal people is kind of chicken or the egg problem. You probably know of epigenetics and that this also affects sexual orientation. So the question to me is more where does behaviour start and personality end...I dont have any clue :) But thats imho a psychological question. I know of experiemts with mice with electrode implantation in their brain to trigger fear

is less/more fear already different behaviour? Not sure.

Aldridge et al. (2011) show a correlation between facial phenotypes and autism spectrum disorders (ASD) in a sample of 8-12 year old boys.
They studied two groups of boys, 65 that had been diagnosed with ASD and 41 who had not. They collected 3D images of the faces and looked for similar patterns among the two groups. They found a significant association between some phenotypes and ASD. But, as with most studies, the results are complex; there a distinct sub-groups within the ASD group.
Keep in mind that this is an association study -- no causation is shown.

I don't think there's any serious possibility that different facial phenotypes cause autistic traits or behaviors. In keeping with the OP's question, the authors seem to assume that biological factors leading to autism also affect facial morphology.


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How do you knockout an E. coli gene without disrupting the rest of the gene cluster?
I'm familiar with the method to build Keio collection using single-gene deletion with an antibiotic cassette. However, what happens when there are gene clusters or overlapping ORFs and you still only wish to knockout a single gene?

Let's say that we have gene A, followed by gene B so that they overlap with 100 bases. If you want to knock out only gene A, you can do the following:

PCR gene A and clone it into a vector
PCR gene B and clone it into another vector
Insert a antibiotic resistance marker at the overlapping region of gene A and B

now you don't have functional gene A and gene B

Transform your cells only with the vector that contains gene B

Now you have disrupted only gene A but you have a functional gene B.


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How does an inhibitory synapse communicate to the cell body of a neuron?
I picture a neuron as having multiple trees of dendrites attached to the cell body with a single axon leaving the cell body.  I believe the cell body near the axon root makes the decision to fire or not fire an action potential.

If the neuron has both excitatory and inhibitory synapses in the dendrite trees, how do these communicate to the cell body?
Does something like an action potential get transmitted down the dendritic trees to the cell body?
What is the difference between the excitatory and inhibitory signals that are transmitted?

From your comment to nico's good answer, it seems that your question is really about how synaptic potentials propagate through dendrites.
Canonically, synaptic potentials travel passively along membranes and is described by cable theory. The cable equation describes how the voltage will change over time and space along a cable. The theory was originally developed for signal decay in trans-Atlantic telegraph cables, but the principle holds for a voltage-independent length of membrane like a dendrite.
A key point is that the potential change "seen" by the cell body is different from the potential change seen locally at the site of the synapse itself. In fact, the voltage decays exponentially with increasing distance from the synapse. The extent of the signal decay is governed by the axial resistance (influenced by dendritic diameter), the membrane resistance, and membrane capacitance, and the branching pattern. A common neuron modeling environment called NEURON is basically a fancy solver for the cable equation.
You'll note that a consequence of this signal decay is that synaptic location matters a lot. Given an identical synaptic potential, a very distal synapse will have much less of an effect on the soma than a more proximal dendrite. Sometimes, the synaptic strengths are scaled to compensate for this location issue (a distal synapse will have a much larger local potential change). Many inhibitory synapses capitalize on this location dependence and are located close to the soma to act as shunts for all signals coming from the dendritic tree. When activated, an inhibitory synapse will decrease the local membrane resistance thereby decreasing cell excitability.
Finally, I'll note that although we often talk about dendrites as being passive conductors, dendrites are actually quite active and have many voltage-dependent channels. The voltage-dependent phenomena in the dendrite complicates the use of pure cable theory to understand the dynamics of synaptic potentials. However, cable theory is still the essential foundation upon which our growing understanding of the active dendrite is built.

An inhibitory synapse works just like an excitatory one!
When a presynaptic neuron fires it will release a neurotransmitter at its terminal(s). This neurotransmitter can be excitatory or inhibitory, the main excitatory one in the central nervous system being glutamate and the main inhibitory one GABA.*
GABA and Glu are far from being the only neurotransmitters in the brain, they're just a classic example, so we'll stick with them. When the neurotransmitter is released it binds to receptors on the postsynaptic neuron (provided, of course, that the postsynaptic neuron expresses these receptors).
Various GABA and Glu receptors exist, both ionotropic (i.e. channel-receptors that let ions flow through the membrane upon binding of the ligand) and metabotropic (i.e. receptors which activate an intracellular pathway that does not per se start the flow of ions, but that can induce it or prevent it indirectly).
For simplicity we'll stick to ionotropic receptors.
Glu binds to three types of ionotropic receptors: AMPA, NMDA and kainate receptors. These have different kinetics/properties, but the bottom line is that they let cations (positively charged ions, such as Na+ and Ca++) into the cell. When this happens a postsynaptic depolarization happens, which is named EPSP (excitatory post-synaptic potential).
So, if the resting membrane potential was, say, -57mV, it will become, for instance -52mV.
This means that, if the threshold potential for firing an action potential were -43mV the cell, which first needed a 14mV depolarization to fire now will need a 9mV depolarization.
If subsequent EPSP sum they can depolarize the cell sufficiently to reach threshold and let the cell fire.
This image from Wikipedia is quite self-explicatory: in this case 3 synaptic events generated 3 EPSPs that summed, making the cell depolarize enough to reach threshold potential, and generate an action potential, that will then propagate to the cell body.

GABA, on the other hand, binds to the GABA-A receptor, which is a chloride channel. In most cases, upon binding of GABA, GABA-A lets Cl- in the cell, effectively hypopolarizing it and generating an IPSP (inhibitory post-synaptic potential). The situation is the same (but opposite) to Glu, this time, though, the potential becomes more negative.
EPSP and IPSP can and do happen at the same time: as they can vary in frequency and intensity depending on the firing frequency and firing pattern of the presynaptic neuron, a pretty much continuous range of voltages can be achieved in the postsynaptic neuron.
Other controls over this process come from metabotropic receptors that can, for instance [de]phosphorylate (add or remove a phosphate group) ion channels modulating their permeability to ions or from the different kinetics of the different channels (for instance certain channels stay open for longer or open in a delayed manner etc), allowing for fine-tuning of the system.

*I am making a gross generalization here. A neurotransmitter is not excitatory or inhibitory per se, it depends on the context. For instance excitatory GABA synapses do exist.

I had read about EPSPs and IPSPs before and I now see that the main difference is the sign of the delta voltage change - thanks. My question still remains about how these travel down to the cell body down the dendrite tree.  These are not action potentials and I thought action potentials were required for signals to travel unchanged over any distance. Do these EPSPs and IPSPs travel unchanged down the dendrite tree to the cell body to get "summed"? The membrane potential near the synapse changes but how does that change travel down the dendrite?  The dendrite is not an electrical conductor.

I think the answer provided by @yamad answers your concern very well

I wish I could "accept" both your answer and yamad's answer ;-).  Thanks again for a great answer...

A small linguistic side-note: the term "stimulatory synapse" is not used in neuroscience. A search in Google scholar gave me 183 results and they were almost all, if not all, from immunology studies. Perhaps @Nico you meant "excitatory"? I replaced the occurrences in this answer and my edits got accepted, but they were now reverted back.

@vkehayas I reverted the edit, since I have definitely heard "stimulatory synapse" and "excitatory synapse" used in an exchangeable manner. To be fair, I did not check Google Scholar, but if you feel strongly about that please change it back and I will not revert it.


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How would one calculate the availability of nucleotides to an enzyme?
How would one calculate the availability of nucleotides to an enzyme like a polymerase ?
I imagine an answer in units like nucleotides per second per enzyme, but I'm also imagining an answer that is not a simple rate of reaction. k_on calculations and k_off do not offer mechanistic explanation.
I'd like to know, specifically, if there is a theoretical approach to this question:  how does a polymerase reject an incorrect nucleotide?

All nucleotides or a specific nucleotide?

All nucleotides. I will revise the question to reflect better my intention.

The second question on DNA proofreading is probably worth an entire question by itself. You might as well ask it and get more reputation ;)

Wouldn't this be a mass-transport related question? I think that transport rate/flux of nucleotides can be described entirely by the diffusion coefficient given the cellular environment.

@bobthejoe things like temp, pH, salts, etc. should also make a difference to nucleotide incorporation by a polymerase. I think a thorough answer would cover it all, and will be really impressed if we get something that comprehensive.

I could read this question more than one way.  Are you talking about an enzyme in a cell or in a reaction in vitro?  Kinetics and mechanical explanations can overlap, but are not entirely the same and are usually dealt with separately - kinetics with watching the rate of reactions in a tube and mechanism in a crystal structure or possibly Nuclear Magnetic Resonance.
Protein structures are usually static- you only get a time lapse snapshot of the reaction in most cases. kinetics allows you to see how fast these things go and can help you understand the order of binding when more than one component is needed for the reaction, etc.
The polymerase has a binding pocket where the template strand and the growing strand are used to build a double helix together.  if the base being introduced does not form Watson Crick base pair bonds, the geometry of the reaction will not allow the base to be added to the growing strand.
Hope this helps? If I can make this clearer, can you drop me a comment and I'll revise...