Excitability of neurons [The following includes a) two specific questions (at the end), b) an attempt to capture a dispositional concept (excitability) in geometric and physical terms.]

I assume that "excitability of a neuron" is a reasonable concept (and measure) to distinguish neurons: there are (as will be seen) neurons that are more or less excitable (in a quantifiable way).

What does "excitability" mean?

Excitability $E$ may be operationally defined as the sensitivity of a neuron to excitatory synaptical inputs. Mathematically stated: as the (decimal logarithm of the reciprocal of the) proportion of excitatory synapses that must be simultaneously active (i.e. generate an excitatory postsynaptic potential, EPSP) in order to collectively evoke an action potential.

Let $N$ be the number of all excitatory synapses of the neuron, $n$ be the the minimal number of simultaneously active synapses that is needed to evoke an action potential:

$$E = \log \frac{N}{n}$$

If the proportion is 100% (all excitatory synapses must be active), $E =  \log (1) = 0$, if it's only 10%, $E=1$ (higher excitability), if it's 1%, $E = 2$, and so on.

How to determine $E$ for a given neuron? With the operational definition given above:

Count the actual number $N$ of excitatory synapses.
Estimate the minimal number $n$ of simultaneously active synapses that is needed to evoke an action potential (by repeated experiments).

Especially the second number $n$ will be quite hard to achieve experimentally. But there is an alternative way to estimate this number, given a simplified model of the neuron:

All synapses have equal (mean) distance $r$ to the axon hillock
(where the action potential is generated).
The EPSP generated at a synapse is $u$.
The EPSPs travelling from
the synapse to the axon hillock have a constant decay constant
$\alpha$.
The threshold value for action potential generation is $\theta$.

When $m$ synapses simultaneously generate an EPSP of size $u$, these EPSPs will sum up at the axon hillock to

$$ U = m\times u\times 10^{-\alpha r}$$

Only if $U \geq \theta$ an action potential will be generated, that is, the minimal number of simultaneously active synapses to generate an action potential is

$$ n = 10^{\alpha r}\ \frac{\theta}{u}$$

With this we can estimate the excitability $E = \log\frac{N}{n} = \log 10^{-\alpha r}\frac{N\ u}{\theta}$ by

$$E = -\alpha r + \log(N) + \log \frac{u}{\theta} $$

$\alpha$, $u$ and $\theta$ are more physical constants (more or less the same for all types of neurons?), $r$ and $N$ depend heavily on the arbitrary geometry/morphology of the neuron (especially do longer and more strongly branched dendrites have more synapses).

My specific questions are (please feel free to answer only with "yes" or "no"):

  Has the property of excitability (in the operational sense above) been investigated a) for single neurons, b) for morphological types of
  neurons?
  Is there an observed significant correlation between morphological type and excitability? Note that larger dendritic trees have larger
  $r$ (decreasing $E$) but also larger $N$ (increasing $E$).

(Final remark: The relation between $r$ and $N$ of a neuron is partially reflected in the structure – especially the degree of branching – of its dendritic tree.)

Excitability has definitely been tested and measured, but I'm not sure about your exact definition (sort of hard to prove a negative).

For differences in "excitability" across neuron types, I can think of two general approaches.

1) You could simply consider the firing rate and define cells as more "excitable" simply if they fire more or have a lower current threshold (though one must be careful in interpreting the actual "mV" value of threshold, because resting potential and input resistance are crucial and thresholds are dynamic).

These parameters have nothing to do with the number of synapses on them or the number of synapses it takes to fire; if you focus too much on these parameters you risk making a comparison that isn't all that helpful (see the analogy below). This approach is most suited to comparisons across cell types.

2) The second type of excitability concerns the intrinsic properties of a cell: what is it's input resistance, spike threshold, how much current do you need to inject at the soma to evoke a spike, etc. These properties can indeed vary across cell types, but you really have to think about it in the context of (1) to avoid the same problems with the analogy below. A cell might be near threshold but receives very small inputs; should that cell be considered more excitable than another?

Instead, it makes more sense to think about changes of excitability: "how does Manipulation X affect the excitability of Cell K?" If it changes the amount of current you need to inject to the soma to evoke a spike by depolarizing the cell or increasing the input resistance, you would say it increases excitability. This is, in my experience, by far the primary way in which "excitability" is discussed in neuroscience, rather than as a factor that varies across neurons. I did a search on Google Scholar for "neuron excitability": every one of the first 20 results was using it in the context of a change in excitability from one condition or manipulation to another.

A tangential analogy (the problem with your proposed definition of excitability):

Your proposed definition of excitability is a bit like measuring income based on paycheck frequency or number of digits on the check. You could certainly do comparisons between jobs on those merits, and in some cases they might be valid for what you'd normally think of as "income", but as soon as you move between countries (i.e., brain regions or cell types) currency changes, and suddenly the number of digits doesn't help because you don't know if you are talking about British pounds, US dollars, or Brazilian real. And even within a population, if the paychecks come weekly rather than monthly, the same face value of a check means a totally different annual income (i.e., if a cell has synapses that are rarely active, they contribute less to depolarizing it than synapses that are active all the time).

Contributions to excitability

Your question proposes that morphology is a defining characteristic of excitability. In a previous question you asked, I directed you to a review by Magee, J. C. (2000). Dendritic integration of excitatory synaptic input. Nature reviews. Neuroscience, 1(3), 181. - this review is applicable here, too. Active conductances in the dendrites and variation of synaptic properties with distance from the soma (larger, faster EPSPs the further from the soma you go) act to regularize the influence of EPSPs with distance, so you cannot rely only on passive properties. That also means you can't simply assume that a cell with lots of synapses far from the soma is not excitable.

However, there are definitely differences in firing rates and firing thresholds across neuronal subtypes, and you can take these to mean differences in excitability. There are many papers that talk about the diversity of intrinsic properties or firing rates of cells. I'll list a couple here for further reading:

Llinás, R. R. (1988). The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function. Science, 242(4886), 1654-1664.

Izhikevich, E. M., & Edelman, G. M. (2008). Large-scale model of mammalian thalamocortical systems. Proceedings of the national academy of sciences, 105(9), 3593-3598.

It's also important to recognize that excitability is dynamic and cells that are highly excitable in one state may not be as excitable in another state, even though their morphology does not change.


Latency to audition in human beings? On average, in a human being with no neurological deficits, how long does it take for a sound which is sensed in the ear to reach the cortex?

Which brainstem structures are most responsible for the delay?

(I'm interested in things like the effect of the Olivary n.)

There are several ways to infer into the propagation delays of auditory system in vivo that is applicable to humans (i.e. leaves the subjects intact).

One of them is so-called ABR that stands for Auditory Brainstem Response. As it is clear from its name this method allows you to derive the brainstem response to an auditory stimulus (so, you can track the auditory pathway up to its input into thalamus), but its resolution is so fine that you can separate single components ("waves") for the following path segments (from Wikipedia):

Wave I – generated by the peripheral portion of cranial nerve VIII
Wave II – generated by the central portion of cranial nerve VIII
Wave III – generated by the cochlear nucleus
Wave IV – generated by the superior olivary complex/lateral lemniscus
Wave V – generated by the lateral lemniscus/inferior colliculus

So, it takes only 10 ms for the signal to reach the input into thalamus. This correlates well with some auditory signal based activities, like startle reflex, which was also shown to have about 10 ms latency.

I tried to search for some electrophysiological recordings from auditory cortex (temporal lobe) paired with auditory stimuli, but the first paper I came accross that is available for free (and which I can also link from my answer) is this work done on monkeys.

If you look at Figure 1:

This is the results from multiunit recordings and you see that the initial activity in the cortex starts approximately 20 ms after the stimulus onset with a short activity pattern, followed by some short break and then longer period of activity with broader frequences spectrum.

In my opinion the delays in signal propagation are not due to complex signal processing in the olivary nucleus or any other brainstem structures, rather they are due to electro-chemical transformations in CNS synapses.

The initial arrival of the signal into the cortex does not mean the perception of the sound, it definitely takes hundreds of millisecond until the conditioned cortex-mediated response to this stimulus.


Taxonomy for plasmids I liked the question about F' and R plasmids.

What is a good resource that describes what is known about the functions and diversity of plasmids in the wild? Prokaryotes or eukaryotes?

Wikipedia points to five kinds of plasmids (fertility (F), resistance (R), col plasmids (offensive genes that let a bacteria kill other bacteria), degradative function plasmids, and virulence plasmids). There is a brief section on yeast/euk plasmids too. It seems like plasmids could actually convey nearly any gene. Restriction enzymes are found mostly on plasmids and they would seem to be defensive - maybe those are degradative.

Are there references that are more detailed and nuanced?

Not sure if generalized plasmid taxonomy is going to be relevant any longer. A lot of these old names were created before the exact sequence and function of the various DNA sequences were known. This is becoming especially true as synthetic biology allows us to mix and match parts of plasmids at will. If you want to dig through a lot of the old plasmid classification papers, a lot of them are published before 1980.

Back then I'd imagine conversations went more: "oh look, I found an R plasmid conferring ampicillin resistance", instead our more modern understanding: "oh, I have a plasmid conferring ampR via bla "

That being said, I think the more specific / specialized plasmid classifications will stick around for a while as they confer a lot of domain specific meaning.  Check out Ti and Ri plamids which have very specific meanings in plant pathogens and are used in the genetic engineering of them.  You'll notice that the classification for these plasmids comes from a lot more than a single gene.

There have been some modern attempts to classify plasmids, but rely a lot more on the structure / lineage of the plasmid rather than the payload genes (replication origin, size, etc.). Check out [1] for an example.

[1] Wang, et. al. 2009. Plasmid.


Why don't we see turbulence in the aorta even in normal situations? I read about the Windkessel effect. Then I read about pulse pressure waves getting reflected from the periphery. If the pulse pressure wave is reflected during diastole and at the same time blood is being pumped forward by the aorta due to the Windkessel effect, then we have two opposite forces acting which should create turbulence even in a normal aorta. Why doesn't this happen?

Why don't we see turbulance in Aorta even in normal situations?

There are different parts of aorta where turbulence is possible and where not.

It is often said that in normal situations, we cannot see turbulence in aorta because aorta is very stiff and its surface is very smooth.
However, this is a simplification and involves an average person (middle aged) which has stiff aortic arch too.

Note that the elasticity of arcus aortae is responsible for 50% of the volume to the peripheral circulation, thus creating a nearly continuous peripheral blood flow as anongoodnurse says, see this publication.
However, not all of this blood travel to the backward direction.
It would be interesting to see how much blood is travelling backward.
This would help to understand what is the likely hood for turbulences.

Those models linked by Anongoodnurse's answer are a few models used to locate places of possible turbulences discretely but they do not seem to consider the amount of blood capable of creating turbulences, just discrete models:

Stalder et al. I do not like the first publication because it is using Reynold's number that is designed originally for laminar flow. Problem with viscosity etc. There are better ways to the same thing and consider explicitly the creation of turbulence. It does much simplifications there. Fitting the equation to the physiological ranges of some set of data is bad procedure.
Fukuda et al. I like the second publication. High velocity and turbulence and nonlinear streamlines in the ascending aorta in normal situation. In other words, high magnitude of the strain rate tensor along aortic curvatures. So we need nonlinear distribution of at least 4D (later 6D) to quantify the amount and degree of nonlinear processes in turbulences.
Lantz et al. Third publication. Linear model for nonlinear situation. I am not convinced by their Mesh selection. Only in Mechanics' journal. Very far from Medical publication or from Mathematical. Not rigorous.

In summary, there are many models and publications to answer the question where are the turbulences. However, they try to answer nonlinear problem by linear models.
I have not seen any models where they do this rigorously.
I think we should narrow this problem even more, like Fukuda et al has done.
They manage to provide some good pieces of information by just considering an intervention with least turbulence in the aorta.

Generally speaking, we can see some turbulence in arcus aortae in the diastole when blood bounces back from the aortic valve.
The walls of arcus aortae can store about 50% of left ventricular volume.
However, I do not know how much of this blood is travelling backward and reflecting back from the atrial valve and causing possibility for turbulences.

  [P]ulse pressure wave getting reflected from periphery.

Pulse pressure is systolic minus diastolic pressure.
Pulse wave is those small waves inside respiratory waves:

where vasomotor waves are controlling the big picture.

  If the pulse pressure wave is reflected during diastole and at the same time blood is being pumped forward by aorta - -.

Wrong! Blood is pumped by heart. Aorta is just a vessel for transportation.
Generally speaking, Some blood is reflected back from arcus aortae which bounches back from the aortic valve.

  [Because] windkessel effect then we have two opposite forces acting which should
  create turbulance even in normal aorta. Why doesn't this happen?

You confuse here different terms and processes.

Generally speaking.
Arcus aortae stretches during systole.
It is coils back in diastole (left atrium relaxing), blood crashing off aortic valve, possibly creating a heart sound and increasing diastolic pressure. Like anongoodnurse says, in this phase, you can see some turbulence in the aorta but little, since the wall of the aorta is very smooth and only small portion of blood is travelling backward from the walls of aorta:

where see the aorta coils part.


Oxygenated hemoglobin in MRI I have read the following sentence:

  Because this oxygenated hemoglobin is unaffected by magnetic fields,
  the response RF signal returned to the fMRI scanner is stronger when
  there is more brain activity and therefore more oxygenated hemoglobin
  in that brain tissue.

Oxygenated hemoglobin does not react to magnetic fields, while deoxygenated hemoglobin does. So in my view, if there is more brain activity and therefore more oxygenated hemoglobin, the signal should be weaker because the oxygenated hemoglobin does not react to the magnetic field? Why is it the other way around?

I think that the type of fMRI you are referring to is blood-oxygenation-level-dependent fMRI or  BOLD fMRI.

The principle behind MRI in general is the detection of proton signals from water molecules. The proton signal is generated by magnetizing the protons in tissue, which causes their spin to change. A subsequent powerful radio wave disrupts this spin and the following relaxation phase of the protons to the original state can be detected by MRI. Water, and hence protons are everywhere in the body, including the brain and the blood.

Deoxygenated hemoglobin (hemoglobin without oxygen) in blood changes the proton signal in its immediate surroundings due to the magnetic properties of deoxyhemoglobin. This is caused by the fact that deoxygenated hemoglobin is paramagnetic and decreases the proton signal. In fact, the paramagnetic influence of deoxyhemoglobin has been regarded as noise in structural MRI scans, before its use in BOLD-fMRI became clear. Oxygenated hemoglobin does not have this property.

Radiopaedia has a nice explanation as to exactly how the BOLD signal is used in BOLD fMRI, and I quote:

  When a specific region of the cortex increases its activity in response to a task, the extraction fraction of oxygen from the local capillaries leads to an initial drop in oxygenated haemoglobin [...]. Following a lag of 2-6 seconds, cerebral blood flow (CBF) increases, delivering a surplus of oxygenated haemoglobin, washing away deoxyhemoglobin and with it the attenuating effect on the MRI signal. It is this large rebound in local tissue oxygenation which is imaged, as it is accompanied by an increase in the MRI signal. The difference is used to generate the BOLD fMRI response.

So brain activity increases the BOLD signal by picking up oxygen-changes after an increased blood flow to that specific part of the brain.

So your statement [...] If there is more brain activity and therefore more oxygenated hemoglobin the signal should be less strong because the oxygenated hemoglobin does not react to the magnetic field is incorrect, because oxyhemoglobin attenuates the proton signal.


How do we know that everybody's DNA fingerprint is unique? How do we know that everybody's DNA fingerprint is unique?

I know, I know, everybody's DNA is unique.

But when we do DNA fingerprinting, we're looking at very specific regions of high variability.

How do we know that just by chance, two people's DNA could be the exact same in the spot(s) we're observing.

With real fingerprints, uniqueness is (almost) guaranteed (I believe it's a 1 in 64 billion chance) because they are developed by physical stresses on the fetus in the womb.

Is there any similar mechanism/affect that acts on these non-coding/highly variable sections of DNA?

Thanks!

evamvid

First, remember that identical twins actually have the same genotype. So its not exactly true that everyone has a unique genome.

But to get at the heart of it, you're asking how I can be sure that I have a different genome than you, or even than say my brother. And moreover you're asking how these differences are obvious enough that they can be detected without whole genome sequencing.

The answer is that there is no mechanism to ensure differences, but that the differences arise from the enormous variability of our genome. Look at the major histocompatibility complex, or MHC, a cluster of genes that affect our immune system.

Just to simplify things, lets focus in on four genes in this cluster: HLA-A, HLA-B, HLA-C and HLA-DRB1. According to this site there are 2579, 3285, 2133 and 1411 alleles for each, respectively. If we make a naive assumption that each of us received a random assortment of these genes, that makes 2579 x 3285 x 2133 x 1411 = 25,549,791,000,000 possible combinations. The chance that we both have the same combination is then about 1 in 25 trillion, just considering 4 genes.

But wait, you say, surely some of these genes are not equally likely and surely they segregate together, making this chance much smaller. You would be right. But this consideration stops mattering very much when you account for the rest of the variable regions. They combine multiplicatively, so considering a fifth gene with only 2 possible alleles brings the possible combinations to 50 trillion.

If you consider just a few more genes, the numbers get unthinkably high. This pretty much ensures that, even considering a small sequence, we can be sure that the genetic fingerprint is unique.


What is the limit of time resolution in fMRI? I was reading about a few studies on estimating functional connectivity between brain areas using fMRI signals. However, as far as I know that fMRI has a very poor time resolution, roughly in the order of 1 second. Individual neurons communicate with delay less than 100 ms, and many brain functions happen within a second, in which case fMRI wouldn't have enough time resolution to determine if things happened simultaneously, or in a sequence at all. This problem would be even greater for causality analysis such as Granger causality framework.

So my question is, what is the theoretical, and practical limit of time resolution in fMRI on human?

The quick and dirty answer is: fMRI doesn't perform well in the temporal domain, but excels in the spatial domain among non-invasive imaging methods. If you need an answer as to where the action is, use fMRI. If you need answers to temporal questions, I recommend using electrophysiology such as EEG, which excels in the temporal domain, or MEG for a combination of good temporal and spatial resolution.

As to what the limit exactly is, I would say a few seconds. fMRI measures blood oxygentaion responses, (See the answer on the question: "What does fMRI measure exactly"), which are inherently slow. Neural processes in local neural networks occur in milliseconds, in larger networks in the order of hundreds of milliseconds. Blood flow differences, in contrast, occur in the order of seconds.


Reference Request: Human visual system takes in $10^7$ bits/sec at the periphery and compresses it down to 50 bits/sec deep inside In Sparse Components of Images and Optimal Atomic Decompositions by Donoho, 1998, the author claims that

  The human visual system is thought to do a tremendous job in achieving sparse representation of image data, taking $10^7$ bits/sec at the periphery of the visual pathway and winnowing it down to about 50 bits/sec deep inside.

Can somebody please point me to the source of that claim, as it is not mentioned in the paper, at least to my knowledge.

How about this:
https://www.springerprofessional.de/data-compression-and-data-selection-in-human-vision/3218014

The original link in the Abstract referenced (https://link.springer.com/content/pdf/10.1007%2F978-3-642-04954-5_7.pdf) above isn't available anymore, but I found a repository:

https://webdav.tuebingen.mpg.de/u/zli/prints/ZhaopingNReview2006.pdf

I don't think the review is peer reviewed, but maybe you find a reference in there (it's not my field, so I guess you know more on where to look ;-)

She's now in Germany:
https://www.researchgate.net/profile/Li_Zhaoping

If you don't find anything, maybe you can ask her on researchgate directly.


How to estimate mRNA counts from Relative Promoter Units (RPU) or RNAP per second (PoPS) in E. coli? I need a rough estimate on how to translate RPU or Polymerases Per Second (PoPS) to mRNA count (or even better protein count) in E. coli.

I understand that any number we come up with will be a very rough estimate of it, but for now, I need a placeholder value to do some modeling on genetic circuits in E. coli until a more verifiable number comes about.

I could not find any paper that discusses these issues. So this answer is just based on my guess.

From the this page:

  Transcription rate is generally a parameter associated with a
  particular transcript and has units of transcripts per unit time. In
  contrast, PoPS is essentially transcription rate at a particular
  location on the DNA. The value of PoPS just downstream of a coding
  region should be equal to the coding region's transcription rate.
  However, there are certain positions at which a transcription rate
  doesn't necessarily make sense yet PoPS does. For instance, as
  biological engineers, we care about the rate at which RNA polymerase
  moves through a terminator (or the PoPS downstream of a terminator)
  but yet most people don't talk about the transcription rate of a
  terminator.

What we want is the transcription rate for every gene. You can estimate it using PoPS corresponding to that terminator.

Now, at steady state the mRNA concentration would be the rate of formation divided by the rate of degradation (removal): rf / rd.

Since the study that you are referring to, calculates PoPs, I would guess that it is based on some standard BioBricks parts. You are likely to have have mRNA degradation rates associated with these transcripts (even protein formation and degradation rates, possibly). If you don't have the mRNA degradation rate then at least for long lived mRNAs, you can assume the rate of removal to be same as the dilution rate (loge2 / doubling time). Substitute this in the equation for steady state and you should get mRNA concentration.

Steady state protein counts would be: mRNA counts × protein formation rate / protein removal rate.


Genotype result of double fertilization So, clearly, the endosperm would be a fusion of the polar nuclei and one male gamete. Does this mean that each male gamete would have a T allele on it?

I can't seem to figure out a way to predict the allele distribution between the 2 polar nuclei since the flower has a Tt genotype.

Along the same lines, how can I predict what alleles the haploid egg would have? T or t? So, in that case, there would be a 50% chance of the embryo being TT and 50% chance of it being Tt (I didn't understand what the plus sign signifies).

The correct option is D, but I can't figure out how to get to that answer with absolute certainty.

IMO, the question is unclear

The question is unclear to me. I understand we expect a triploid nucleus plus a diploid zygote (double fertilization) but I don't understand what (TTT + TTt), TT means.

Which book did the question come from?
Is there any preamble to this question?

Double fertilization

I am not so used to thinking about double fertilization in plants. In short, two pollens are involved. One fertilize a haploid gamete from the mother and the other fuse with two haploid gamete (polar nuclei) from the mother (triple fusion) resulting in a triploid "individual".

In my below answer, I am assuming that any two polar nuclei can fuse with the pollen. I am not sure this is true. If it is systematically polar nuclei resulting from the same meiosis II (that is they have the same parent cell after meiosis I), then t story is a little different.

How I understand the question

In my understanding, we are talking about a single locus with two alleles T and t. Both pollens are T. The mother is Tt.

Answer

There are two possible gametes from the female side T and t. Only one possible gamete from the male side T. Therefore, the diploid zygote is either

$\frac{1}{2}$ TT
$\frac{1}{2}$ Tt

, where the numbers indicate probabilities

Now, for the triploid nucleus resulting from the fertilisation of two polar nucleus from the mother and one pollen grain can be either

$\frac{1}{4}$ TTT
$\frac{1}{2}$ TtT or tTT
$\frac{1}{4}$ ttT

Now, I have no idea how that matches to the possible answers as I don't understand the notation.


How does the creative process of Biological Evolution work? In order for nature to go from microbes to man, there needs to be new information. Where does this new information come from?

It is understood that Evolution basically involves three elements. Natural selection, genetic mutation, and time. The problem for Evolution, is that none of those three elements are creative. Natural selection is basically just a pruning process. It selects from what is there and advantageous, and prunes off what is deleterious to the organism as far as its fitness.

Genetic mutation is just errors in replication. So it creates nothing. It simply degrades. We have no new information, just an erroneous replication, and degradation of what was there before.

That is still true of gene duplication. We have an error that repeats the same information/genes. So we have two copies of something but there is still no new information.

This brings us to the second problem. What mechanism or process of nature/Evolution, carries out the instructions. What I mean by this, is that it essentially has to work like a computer. If I want my computer to have a more advanced program, I need to input new information, and its often codified in the form of say a disk, or installation file.

What is the equivalent of this installation file for Evolution?

For example. Say I'm a cephalopod. And I'm getting environmental pressure from predators and I want, or need, to advance my defenses, so I want to built some spikes on a hard outer shell. Where does the cephalopod get the new information, or rather, instructions, to know how to do this new feature?

Your basic problem is indeed a fundamental misunderstanding of how DNA and by extension its evolution works. First of all, there is no such thing as "correct" or "error", there are only changes, some of them are better for the individual and some are worse. You also have a basic misunderstanding of the concept of information. An error does not decrease the amount of information, it just alters that information. For example, consider this sentence:

  The book is read

Say I make a simple error when I transcribe it:

  The book is red

The two statements contain the same amount of information. Nothing has been lost, only changed. But that change created new information. Now what if I try a different change:

  The book is rled

Now, this one is nonsensical, indeed, but how does that translate into DNA?

The computer analogy is a bad one. Programming languages have a very specific set of rules and anything outside those rules results in an error. For example, while this is a perfectly valid statement in many scripting languages:

print "Hello World"

This one is not:

priint "Hello World"

That, however, is not the way that DNA works. DNA is read in words of three characters, the codons. Every single possible
combination of those characters actually has a meaning. Therefore, a mutation like that above which would decrease the information content of the sentence (here, the gene) is not possible. Let's quantify. The DNA sequence consists of a long series of chemicals, commonly known as A, C, T and G. Since these are read in "words" of three "letters", this means you have:

$$4^{3} = 64$$

64 possible combinations. Of these 64, 61 are words with a specific meaning and 3, the STOP codons, are punctuation marks, full stops if you will. In other words, all possible combinations of letters have meaning in DNA.

Because all possible 3-letter combinations have meaning, no change will affect the information content of the "sentence". All it can do is change it. Now, changing the information can indeed result in "sentences" that make no sense. In the DNA world, this most often results in what are known as deleterious mutations. These happen all the time, but the result is usually a dead individual. Those with such mutations are not even born (speaking of mammals).

However, other mutations, such as the change from read to red that I mentioned before, can give rise to a change of meaning, this change, if it turns out that it makes the individual carrying it more likely to reproduce, will spread across the population and will be selected for. That is how new traits can arise.

In closing, another point that you have misunderstood is that evolution is not a path from the least to the most complex. In many ways it is the inverse. In fact, by any measure that counts, bacteria are far more "evolved" than humans for the very simple reason that the only way you can measure evolution is in terms of numbers of generations. Think of evolution as happening every time a species reproduces, this means that bacteria have had orders of magnitude more time to evolve than mammals have. Still, this is a useless comparison which is why nobody compares species by how "evolved" they are. For a discussion on that, have a look here.


Are there any viruses or bacteria which have evolved to withstand higher temperatures due to fever My question was raised after receiving this information:

  The primary reason the body raises its temperature (via the Hypothalamus in this case) is that bacteria and viruses tend to optimally thrive at 98.6F, which is also your body's optimal operating temperature.

I am just wondering if there are any viruses or bacteria that have gained the ability to prosper under fever temperatures through evolution? If not, why not?  Is there any biological restriction stopping such viral evolution?

Update:

I will try to explain my question.  As far as I know, evolution helps species to adapt to their environment.  For example, when people started using antibiotics we got new bacteria resistant to those antibiotics.

If fever is part of the innate immune reaction to viruses and bacteria, why hasn't this resulted in selection for fever-resistant variants? Why has evolution apparently stopped in this case?

Fever is just one of the many ways of the body's defense mechanism work. Under infection, human body can raise body temperature, release cytokins and activate white blood cells etc. Sometimes the bacteria can evade immune suppression or immune complement fixation so that they can stay inside a "fever-ish" body like they just don't care. Example: Pseudomonas aeruginosa. They can grow in 42 degree Celsius which surpass the normal fever temperature.

My answer may not be the best for your question. All I'm trying to say is that fever acts as a supportive role during an infection. Human body relies on heavy artilleries such as white blood cells and cytokin to clear the infection. That's why it will be more beneficial for the bacteria to evolve abilities to evade immune suppression and immune complement fixation. And bacteria know how to do those.


Hamilton's Rule in practice I came across this question in USABO 2013 open exam:

A mother antelope and its child are galloping along the plains, when they encounter a group of hungry lions. If the two antelopes try to escape the lions together, there is a 75% chance that both will be consumed and eaten, and a 25% chance that both will escape alive. If, however, the mother sacrifices herself to the lions, she may be able to buy her baby additional time to escape.
What is the minimum chance that the baby can have to escape from the lions following such a sacrifice such that the mother’s action will be evolutionarily favored?
You may assume that the baby antelope, once escaped, will be guaranteed to survive into a reproducing adult, and that the mother antelope is at the beginning of reproductive age.

I suppose one should use Hamilton's Rule ($r \cdot B > C$) to solve this issue. I'm not familiar with the working of this rule to put it into the question's context. To my understanding $r=0.5$ but this is pretty much how far I managed to go.

It doesn't have to be that complicated.

The evolutionary value of the offspring to the mother is half that of herself (0.5). Then the relative value of both mother and offspring is 1 + 0.5 = 1.5. So the value of preserving both lives is about 3 times the value of preserving the offspring alone, given the simplistic assumptions from the question. Therefore, to choose to make this sacrifice, the probability of survival of the offspring alone must be at least 3 times the probability of both surviving otherwise. 3 times 25% = 75%.

Edit:

In terms of B and C as requested (though I think it's simpler to step away from this):

B is the benefit to the relative. This is not the probability of survival given the action of sacrifice, but the increased probability of survival. The baby already had a 25% chance of survival, but this action will increase that chance to some p, which we are looking for. B is the improvement in the situation:
B = p - 0.25

C is the cost to only the individual (the mother). This is not 1 (loss of survival), but the difference between the situation without making the sacrifice and the situation when she makes the sacrifice. She's only giving up a 25% chance of survival. So:

C = 0.25.

r is the relation between mother and offspring.

r = 0.5.

So the equation is:
0.5(p - 0.25) = 0.25
0.5 p - 0.125 = 0.25
0.5 p         = 0.375
p = 0.75

Someone feel free to format if you want...


What percentage of people today would likely be descendants a man born 4,000 years ago? Assuming a particular man was born in  southern Mesopotamia, around 4,000 years ago, and was significant involved in a major religion.

To what degree (if any) of accuracy could his descendants be traced?
What percentage of the global population is likely a descendant of the man?

This question comes from a comment on sister site.

  I don't think most people are really able to trace their entire family tree that far back. But Avraham is so many generations ago, I would expect that either nobody in the world is his descendant or nearly everybody in the world is

To what degree (if any) of accuracy could his descendants be traced?

I don't really understand this question. To what degree can we trace its descendants given we know what from this man? Do we have a blood sample?

  What percentage of the global population is likely a descendant of the man?

If $N_0$ was the population size 4,000 years ago and $N$ is the population today, then the expected number of descendent of any given person is simply $\frac{N}{N_0}$. However, there is a huge variance and this is where things get more complicated.

As coalescent processes are geometrically distributed (well approximated by an exponential distribution if we assume that the population is large; more info in this answer), then the variance in coalescent times is equal to the expected coalescent time.

The expected coalescent time in a diploid population of constant size $N$ is $2N$. Of course, the assumption of constant population size doesn't hold for humans due to the recent demographic explosion. When the population size is increasing the genealogy looks like a star as coalescent events are rarer and therefore, it is more likely for a given individual living in the past to live descendant today (Excoffier et al. 2009). However, I don't know how to calculate coalescent time in expanding populations.


In males, why it is difficult to control orgasm? Why it is difficult to control orgasm in male humans? How are orgasms controlled and what is different between males and females?

We can control urine for few minutes, but we can't control orgasm for more than a few seconds, but both are discharging though same organ (penis).

The sphincter of the bladder is under voluntary control (that's what toilet training is about). That's why you can hold your urine even when the stretched bladder is sending messages to your brain that you really have to go. That's not to say there aren't involuntary effects on the bladder during orgasm.

Orgasm is a separate entity. It is a complex neurological response with four stages. Orgasm is controlled by the autonomic nervous system and is a response that can be controlled as easily as pupillary dilation/contraction in response to light (that is, not at all). However, there is some measure of voluntary control over the plateau phase of orgasm.

In a bit more detail,

  expulsion is a spinal cord reflex that occurs as the ejaculatory process reaches a ‘point of no return’. During expulsion, the smooth muscle fibers of the bladder neck contract to prevent the backward flow of semen into the bladder; the pelvic floor muscles, along with the bulbospongiosus and ischiocavernosus muscles, have primary roles in this function, and display stereotypical rhythmic contractions to propel semen distally throughout the bulbar and penile urethra. During this process, the external urinary sphincter is normally relaxed. The bladder neck and proximal portion of the urethra, which both contain abundant smooth muscle fibers, receive dual sympathetic and parasympathetic innervation. Besides the cholinergic and noradrenergic components, the principal mediators found in these nerve terminals are NPY, VIP, and NO. The external urethral sphincter and pelvic floor striated muscles are solely regulated by the somatic nervous system, but there is no definitive evidence that a voluntary control of the expulsion phase exists in humans.[1]

Human sexual response cycle
Physiology of male sexual function
[1] Ejaculatory Disorders: Pathophysiology and Management: Physiology of Ejaculation


How does a neuron change as you learn? I am currently taking a course called "Introduction to Machine Learning with ENCOG 3", and I have a question about how well the Artificial Intelligence (AI) algorithm for a "neural network" corresponds with how an actual neuron works.

In the course, they model a neuron like this:

x1, x2, etc. are voltage inputs, the wij are weights.  The inputs are multiplied by these weights and summed up by the neuron.  The neuron then has an "activation function" which then takes the sum of weighted inputs and calculates an output, typically a value between 0 and 1 (or between -1 and 1). You can think of the wij as representing dendrites (a higher weight means a more dense and thus conductive dendrite), and the output of the activation function as the voltage that gets sent down an axon.

The AI neural network algorithm creates a kind of intelligence by modifying the weights (wij shown in the picture).

My first questions is: Is this a good approximation as to how neurons actually work?  That is, do our neurons "learn" by changing the weights (dendrite density, conductivity)?  Or, is there some other mechanism that is more important (e.g. do neurons learn by changing their activation or summation functions?)

My second question is: If neurons really do learn by changing the density of dendrites, then how fast does this happen?  Is this a fast process like DNA replication?  Does the neuron quickly generate (or decrease) dendrite density when it receives some kind of biochemical signal that it needs to learn now?

I understand that much of this might not yet be known, but would like to know how well the AI algorithm corresponds with current theories on biological neural networks.

With respect to your first question, that model isn't intended to take time into account, but is based on Hebbian learning with the goal of computability. It's generally used in simple pattern recognition situations where each case has no bearing on the next. The learning portion is performed ahead of time during the training phase. For example, a deterministic perceptron isn't permitted to change after training. In contrast, the Biological Neuron Model is much more complex, and uses a variety of ordinary differential equations to integrate the cumulative behavior of neurons over time. As such, those models are non-deterministic and don't see as much practical use outside of experimentation.

To address your second question, neurons themselves don't "learn." A single neuron is essentially meaningless. Learning is an emergent process created by the interaction of several systems at once. While one influencing factor is connectivity (zero for no connection, non-zero for the inhibitory or excitatory connection which emulates both synaptic and non-synaptic), what you might call short term learning can also be performed by existing clusters of neurons, without any change in connectivity. Biologically, this is what must occur before any of the comparably slow process of tissue remodelling can take place, and the computationally equivalent process is only possible in time-aware models like the aforementioned Biological Neuron Model.

Take, for example, someone who wishes to learn to play guitar. When they begin playing, existing clusters emulate the desired behavior as best as they can. These neurons act as the functional scaffold that initiates and drives the neuroplastic process. Playing becomes easier because this scaffold becomes more efficient as new connections (shortcuts) are created, existing connections are strengthened, and irrelevant connections are inhibited. The improved scaffold in turn allows further improvements. Newborn neurons may also migrate to the area, though the how, why, and when of that process is unclear to me. This "behavior emulation" or "short term learning" process used in practicing the guitar, or whenever a novel situation is encountered, must be primarily governed by excitatory and inhibitory neurons' influence. Otherwise the whole process cannot even begin.

Further reading

Parameter estimation of a spiking silicon neuron.
Synaptic plasticity, memory and the hippocampus: a neural network approach to causality
Signaling mechanisms in cortical axon growth, guidance, and branching


Insect identification: Fly with eye strip Location details:
Country - India,

State - Tamil Nadu,

District- Chennai.

Found this fly in my backyard keen to know its exact name. Thanks for the help

Definitely Stratiomyidae, probably genus Odontomyia. Very widespread and species-rich genus.
Here is an example of Odontomyia - not the same species - https://www.flickr.com/photos/63075200@N07/sets/72157632905103705/.


What is the smallest touch sensation that a human can feel? What is smallest touch (pressure) sensation that a normal, healthy person (not hypersensitive nor insensitive) can feel on the palm of the hand?

Short answer
The detection threshold of static indentation stimuli on the palm of the hand is approximately 10 to 40 micrometers, dependent on the exact location under investigation.

Background
The sensitivity of a sensory system can be expressed as the detection threshold. This threshold is in psychophysics generally defined as that stimulus level where, on average, 50% of the stimuli are felt.

There are several types of touch receptors that can be investigated, each with specific types of stimuli that are associated with them (Fig. 1)

  Fig. 1. Skin receptors and their response properties (Delmas et al. (2011)

The question specifically targets detection thresholds of indentation stimuli. These stimuli are typically expressed as distance units (meters) or pressure units (Newtons). The skin indentation under constant force is dependent on the area of contact, skin type and other parameters of lesser importance. Hence, indentation units using distance metrics may be the most appropriate way of expressing static detection thresholds. Johansson & Valbo (1970) investigated static detection thresholds on the palm of the hand (Fig. 1) and found average thresholds of 10 to 40 micrometers indentation. This variation was due to geographical differences; towards the fingers sensitivity is higher and thresholds are hence lower (Fig. 2).

Fig. 2. Detection thresholds of static stimuli on the palm of the hand. source:  Johansson & Valbo (1970)

References
- Delmas et al. Nature Rev Neurosci (2011); 12: 139-53


Schiff Base in Enzyme Mechanisms Can a schiff base stabilize the transition state and form an intermediate as in covalent catalysis with a substrate in the same reaction? Basically I'm wondering if a schiff base creates a ping pong reaction.

I think the answer to this one is a most definite 'yes'.  Almost all aminotransferases proceed via a ping-pong mechanism where a schiff base involving pyridoxal phosphate is an obligate intermediate, and where  the 'half-reation' modified enzyme form has often been isolated. An example is aspartate aminotransferase.

Let's also remind ourselves that a transition state is not an intermediate on the reaction pathway (in the TS bonds are in the process of being broken and formed), but may resemble one.


Does the existence of one species imply the existence of many other? Reading one of Sir Arthur Clarke's scifi stories, I came across a statement something to the effect of, existence of a single species automatically implies the existence of many other species. So considering multi-cellular organisms, something more complex than a virus/bacteria, if we know for a fact that there is one species (plant/animal whatever) then without directly observing any other species or any obvious evidence, can we deduce that there must be other species? Assume we are in a completely new environment like a brand new planet discovered with life on it. Does the existence of a  species imply existence of many other species?

Thanks.

I am not sure I'm providing the kind of answer you would expect.

Your question is very conceptual. For such question it is important to very well define the concepts you're using. For example, the concept of species is not well defined (and will certainly never be well defined as it does not represent a natural category to my point of view). Also, the separation you do between complex and non-complex species might not be obvious. For example, you create two categories which are bacteria/virus and multicellular. But you kind of forget the many of the eukaryotes which belong to non of these two categories. Or some bacteria that might almost be considered as multicellular.

I think it would help answering your question if we had the arguments of Sir Arthur Clark for saying such things. Below are two arguments I could use to defend your statement.

Speciation:

If you consider than one population rarely (or virtually never) go under sufficiently major changes before undergoing speciation, then you would never have only one species which is very different from the others.

Ecology:

One might consider that one species cannot by itself be responsible of a whole cycle of elements. Therefore, if the species we observe can theoretically live forever (equilibrium), then, it implies that other species must exist to recycle their wastes. But this hypothesis has nothing to do with the separation of species per complexity that you do.

Update:

Following your comment: So what you had in mind seem roughly the same than my "Ecology" argument. The difference is that I emphasized on the fact that one species alone cannot live for ever because they degrade their resources through time. I did not want to say that one individual of one species cannot live without the presence of another individual of another species. This individual would need the presence of the other species not for himself but rather but its great-great-grand-children when one resource would have been totally consumed by the ancestors.

For your curiosity, here is base of the tree of life. What is eukarotic but not plants, animals or fungi are called protista and are all (or almost all?!) unicellular. You'll notice that viruses/viroid and prions does not belong to this tree. It would be a bit long to explain why they are no represented and it would have nothing to do with your question :D


How to measure GnRH in menstrual cycle? I am interested in pulse frequencies of GnRH (gonadotropin-releasing hormone) in the menstrual cycle (MC) i.e. 28 +/- 7 days.
I would like to study its pulsatile nature i.e. within one MC, not same as cyclic nature within many MCs; but possible cyclic dynamics could be found in one MC too but not focus there.

GnRH releases human chorionic gonadotropin (hCG) which can be monitored by beta hCG but also by (source DynaMed Plus on Chorionic gonadotropin)

serum progesterone, Luteinizing hormone (LH)
estradiol levels
ovarian US 7-14 MCD i.e. in late follicular phase
onset of ovulation at 14 MCD
pelvic exam
cryptorchidism: signs of precocious puberty

Two articles on GnRH monitoring:

Monitoring gonadotropin-releasing hormone administration by measurement of urinary steroid conjugates in the morning urine samples.
some gene studies: Episodic gonadotropin-releasing hormone gene expression revealed by dynamic monitoring of luciferase reporter activity in single, living neurons

Possible cases to study

Amenorrhea: Kallmann syndrome where congenitally deficiency of GnRH but how low?

However, I did not find any publication describing direct/indirect continuous measurement of GnRH.

How can GnRH be measured continuously during the menstrual cycle?

GnRH is found in very low concentrations (2-10 pg/mL)

Options:

  A highly sensitive analytical method (e.g. radioimmunoassay)
  To sample directly from the hypophyseal-portal system
  A surrogate measure

This abstract: http://www.ncbi.nlm.nih.gov/pubmed/9749566 describes direct measurement.
Direct sampling could only be done under general anaesthesia and in a short window, so I'd avoid that altogether unless you're talking about using an animal model and can surgically impact a cannula.
This abstract: http://www.ncbi.nlm.nih.gov/pubmed/21646369 describes use of the $\alpha$-subunit as a surrogate of GnRH (the $\alpha$-subunit is the same for FSH, LH, and TSH and is released under the control of GnRH).

By the way, GnRH does not promote secretion of hCG so much as it does LH and FSH (LH is fairly homologous to hCG).  For the most part hCG is secreted by trophoblasts (in the placenta) and is quite low except in pregnancy or the presence of certain germ cell tumors, so wouldn't be worth measuring in non-pregnant women or males anyway.

The bigger point is why do you want to measure GnRH pulsatility?  This has been done and the you know that it is pulsatile is because it has been done.


When did our ancestors switch to a menstrual cycle instead of the estrous cycle? The Wikipedia page on the Estrous cycle says:

  Humans have menstrual cycles instead of estrous cycles. They shed their endometrium instead of reabsorbing it. Unlike animals with estrous cycles, human females are sexually receptive throughout their cycles.

The page on the menstrual cycles says:

  The cycle occurs only in fertile female humans and other female primates

Do we know how many million years ago that switch happened and our female ancestors got sexually receptive throughout their cycles?

Menstruation occurs only in most of the primates, and a handful of other mammals. It is tempting to speculate that place the switch to menstrual cycles evolved right after the split between non-menstruating primates (tarsiers and their relatives) and menstruating relatives (almost all others), which is about 63 million years ago.

There are other menstruating animals, so I am not sure if nature reinvented menstruation whenever social conditions required unproductive sex, or menses are in fact a more archaic trait.

I doubt we have material evidence about all these speculations.


Do the effect of inbreeding depression disappear after the first generation of outbreeding? An animal that is the result of generations of inbreeding tends to have lower fitness. (More diseases etc.) This is usually explained by harmful but recessive mutations that exist in all populations, but in inbred animals end up occuring on both copies of a gene in a chromosome-pair.

If the problem of inbreeding is that the two sets of genes in the chromosome pairs are too alike, does that imply that the offspring of an inbred animal will revert to "normal" fitness as long as the inbred parent was mated with an unrelated animal? Seeing as the inbred parent can only transmit one copy.
Or is the situation more subtle?

This depends on if you are talking about animals in the wild, such as isolated populations, or humans, or whether you mean research animals. Inbreeding tends to breed homozygosity, so as you said, if you have a recessive disease causing allele within a bloodline, then even if only one of the founders was a heterozygous carrier, then inbreeding can give rise to afflicted homozygotes. However, for lab strains, it is actually desirable to use completely inbred lines where all animals are as near to 100% identical (from a DNA sequence perspective) as you can get. This makes genetic mutational analysis far easier (possible).

It also depends on the alleles in question. Not every mutation is purely dominant or purely recessive. You can have situations, such as with some tumor suppressor genes, that diversifying the population by outbreeding to someone with a functional tumor suppressor, will still cause the offspring to have only a single working allele, and therefore an increased probability that they can sustain a random mutation that will knock the working gene out. You can also have cases where having one functional copy of the gene isn't enough, so the offspring are haploinsufficient. You need two doses of both working copies of an allele to display the non-afflicted phenotype, though the afflicted heterozygote has a better time of it that the afflicted homozygote, who has none of the working allele.

You also have X-Linked conditions. If the maternal lineage is inbred, then all of the males will be afflicted and females will be carriers.

Another possibility is that the outside breeder is a carrier of the mutant allele so the offspring remain homozygous or the outside breeder has an allele of the gene that comes with its own defect. They may not be afflicted, as they could be heterozygous for a working copy, but their offspring with the inbred line could be heterozygous afflicted because neither of the alleles they inherit are functional, it is just that they are not functional in different ways.

Sexual reproductions main advantage is that it is supposed to increase diversity in the population and increase survivability of the species. When you have isolated populations or inbreeding by choice, then this can circumvents the benefits. Not all inbreeding, as seen with laboratory strains and selective breeding of domesticated animals, is deleterious. It is just that the breeder needs to be careful of the choices made and cognizant of how the genetics can work. Animals displaying a diseased phenotype should not be allowed to produce offspring, and you need to evaluate the siblings of that animal as well as the parents to insure that you do not have problems in that lineage.


Human Bones classification and anatomy quiz I'm a junior Biology Student and I came across this Human Anatomy Question:

In respect to the bone characteristics, mark the correct answer:

A) Even bones: Palatine, Inferior jaw, Parietal.

B) Examples of Long Bones: Sternum and Radius-clavicle.

C) Some Mixed Bones are (I couldn't find a better translation for "ossos mistos" in portuguese): vertebrae, ribs, hip bones.

D)Plane Bones protect organs and form cavities, for instance we have: Ribs and Sternum.

E)Odd and Plane Bones: Occipital, Frontal and Sternum.

I am almost sure that options A through C are incorrect. I'm between options D and E, but in option E I am really sure only that the Sternum Bone is correct. I couldn't find a reliable source that said explicitly that the Occipital and Frontal Bone are Plane and Odd.
And I think option D has a flaw mainly because the Sternum Bone does not form any cavities.

@KMM's comment above appears to be on the right rack.

"plane" = "flat"
"mixed" = "irregular"
"even" & "odd" = "paired" & "unpaired"

That being said:

A = FALSE because jaw bones are not paired
B = FALSE because sternum is not a long bone (it's a flat bone)
C = FALSE because ribs are not irregular bones (they're flat bones)
D = TRUE because both are flat bones and protect organs
E = FALSE but ONLY under the assumption of the persistence of a metopic suture (frontal suture) causing the frontal bone to be split (and therefore "paired").


How does one maintain balance sleepwalking? Anectodal. Feel free to shoot it down.

Walking is an acquired skill; As far as I'm concerned exhaustion causes disorientation. Even after waking up it sometimes takes a second or so to get balanced.

How is it sleepwalkers don't stumble around when walking?

Balance is mediated by 3 things: the cerebellum, vision and the ear via the semicircular canal + vestibular nerve (i.e. the ear).

Sleepwalkers lack the visual feedback, but they have a functional cerebellum and semicircular system which is sufficient.

As for waking up and feeling disorientated, if that's when you get up fast that's because your semicircular system hasn't yet reset (as well as your blood pressure has just dipped).


Exact meaning of the term "clutch" When reading a Wikipedia article to do with chickens, I have come across the term "clutch", but I was not able to entirely figure out what this word means. I was wondering whether the term clutch can be used to refer to any set of eggs by birds, reptiles, and amphibians, or whether a clutch must consist of a set eggs all by the same bird, reptile, or amphibian. In general, if a typical clutch by a well fed chicken amounts to a dozen of eggs, that seems like a lot of eggs for a chicken to hold within its body prior to laying them, hence my question about clarification and about what number would actually fit (I have seen as high as fifteen). It is this simply the number of eggs expected to live concurrently in a typical nest where more than one chicken would breed?

A clutch usually refers to all the eggs for a single reproductive event or laying or location. It can mean either all those laid by one organisms in one event or all those laid in a population in a single time and place. Which is usually clear in context.

Even just for an individual it is a bit vague however and can refer to one laying or multiple layings if they happen close together in time.

There is also a usage difference by specialization, agricultural scientists tend to favor a boarder usage for instance.


classical conditioning paradigm for hippocampal learning I wanted to know what a suitable classical conditioning experiment would be to analyze learning and memory capabilities in rodent models with respect to hippocampal long-term potentiation.

For example, I want to subject the animal to conditioning and test the behavioral readout at a certain time point after conditioning. Many , like fear conditioning experiments, are mostly attributed to amygdala processes.

I wish to know some classical conditioning task where I can understand primarily hippocampal processes.

Also is there a way to monitor hippocampal CA1-CA3 firing pattern after the training period or during the training ?

That is, I want to check if LTP will sustain after the training period or is there is any increased sustenance of LTP post training.

But if I am to do this electrophysiological experiment in hippocampal brain slices, how will I incorporate the conditioned and unconditioned aspect to this ?

First of all, your first sentence assumes something which may not be true and is still controversial in the literature. Learning and memory are thought to be related to the phenomenon of LTP but it appears you are taking this as a given.

There is a huge swath of literature on hippocampal-dependent behavioural tests like the Morris-water maze etc so I assume you are already aware of these. If you wish to monitor the HPC firing pattern:
1) during training --- you can set-up an in-vivo electrophysiology platform coupled to a virtual navigation interface and record from cells while the animals are performing a spatial navigation task.
2) after training- you can take slices from the animals as is classically done and try to induce LTP and see if your spatial learning task has influenced the amount of LTP you can get. The condidtioned and unconditioned animals will simply be the two groups which you can compare to see if the behavioural readout(spatial memory task) corresponds to changes in what is though as the cellular basis for memory(LTP)

  Whitlock, J.R., Heynen, A.J., Shuler, M.G., and Bear, M.F. (2006). Learning Induces Long-Term Potentiation in the Hippocampus. Science 313, 1093–1097.

  Goh, J.J., and Manahan-Vaughan, D. (2013). Synaptic depression in the CA1 region of freely behaving mice is highly dependent on afferent stimulation parameters. Front Integr Neurosci 7.

  Heynen, A.J., and Bear, M.F. (2001). Long-Term Potentiation of Thalamocortical Transmission in the Adult Visual Cortex In Vivo. J. Neurosci. 21, 9801–9813.


Do omnivore mammals vary food preferences based on dietary needs? I'm wandering if mammals that can eat many different kinds of food (omnivores) vary their preference for food not only based on the availability, but also based on dietary needs?

I'm looking at this site Food nutritional content and see that "not all foods are created equal" - the vitamin/mineral and amino acid contents can vary dramatically. Is there some part of an omnivore brain/digestive system that "monitors" the micronutrient density of digested food and adjusts food preferences towards foods that make the diet more complete?

For what concerns amino acids, mice rapidly reject meals that are not balanced in essential amino acids and continue to look for other kind of foods. This behavior is called aversion response and it is an adaptive phenomena that can be observed already 20 minutes after exposure to the unbalanced food. The mechanism involves brain sensing of uncharged tRNAs. The significance of the aversion response is to minimize depletion of essential amino acids that can not be directly synthethized but are required for protein synthesis. You can find good reviews in PubMed, for instance Gietzen et al. 2007, Annual Review of Nutrition, and Gietzen and Aya 2012, Molecular Neurobiology.


Why we aren't making Darwin's theory a Law I was wandering about darwin's theory which is controversial theory and there are no enough evidence to prove it right or falsify it, since I'm a biology student so i studied basic way of a hypothesis going to be a law ,the last thing to be a law is theory...am i right?
Hmmm if yes then it's been about more than 130 years since darwin died and there is still no response to his theory?why this taking so long? Are we supporting Darwin because if we don't then we gonna recreate our basic embryology and evolution? If no then why we aren't making it a scientific law?

Scientific Laws differ from Scientific Theories in that Laws do not posit a mechanism or explanation of phenomena. Scientific Laws are merely distillations of the results of repeated observation. As such, a law is limited in applicability to circumstances resembling those already observed, and may be found false when extrapolated.

Examples are like
Ohm's law only applies to linear networks, Newton's law of universal gravitation only applies in weak gravitational fields, the early laws of aerodynamics such as Bernoulli's principle do not apply in case of compressible flow such as occurs in transonic and supersonic flight, Hooke's law only applies to strain below the elastic limit, etc. These laws remain useful, but only under the conditions where they apply. Such laws do not explain how and why they work.

https://en.wikipedia.org/wiki/Scientific_law

Darwin's Theory of Evolution in contrast contains both observation, and a proposes an explanation of the phenomena of species formation.


spinal cord lesion and result in somatic sensation Jimbo suffers a lesion to the entire right half of the spinal cord at the T6 level. A few weeks after his injury, his doctor tests his right and left legs for somatic sensation and tone.  fill out her chart concerning the absence or presence of different sensations and muscle tone in the lower limbs.
Mark a for absent, P for present

Right leg: Light touch, Pain, Proprioception, Temperature, Hypertonicity, Hypotonicity
Left Leg: Light touch, Pain, Proprioception, Temperature, Hypertonicity, Hypotonicity

what about if the lesion is in C1 or L5? where would it affect (leg/hand..) and fill out the above chart?

This is a classic Brown-Sequard syndrome well- studied in the field of neurology. To answer your question, you would need to know what tracts are being severed and what sensations each tract is responsible for. A clean R hemi-section of the spinal cord at the level of T6 would affect the 1) R lateral corticospinal tract, 2) R spinothalamic tract, and 3) R dorsal columns.

The R lateral corticopsinal tract is an upper motor neuron (UMN) pathway, which relays messages from your brain to the periphery. If severed, it would lead to paralysis of muscles below the lesion on the ipsilateral side. This would result in UMN signs such as increased reflexes, increased spasticity, and muscle weakness.
The spinothalamic tract is a sensory pathway connecting peripheral sensations and bringing them up to the brain. Specifically, it communicates sensations of pain, temperature, and gross touch. If severed on the R side, these sensations would be lost on the contralateral side a few levels below the site of the lesion. The reason for this is due to the decussation, or crossing over, of the tract at or slightly above the level of entry of the nerve fibers into the spinal cord from the periphery.
The dorsal columns are similar to the spinothalamic tract, except the sensations communicated are vibration, fine touch, and proprioception. If severed, this would cause loss of these sensations below the level of the lesion but on the same side. A patient would not be able to balance himself/herself without support.

Regarding what areas of the body would be affected based on a lesion in T6, C1, or L5, just as mentioned by jonsca, one would need a dermatome to understand what areas of skin sensation would be affected, and know the nerve root origins of different nerves of muscles. A great book to read to locate these answers in a table format is Neurology BluePrints.

Otherwise, feel free to open any Neurology textbook for a reference, and look for Brown-Sequard Syndrome to read in more detail.


Is it possible to graft plants from different families? For example, I have some Eastern Hemlock rootstock (Pinaceae), and want to graft a scion from Dawn Redwood (Cupressaceae) onto it. Is this possible? Is anything like this possible?

No. Exceptions are always possible, but it would be a noteworthy.
I just find this notes in: https://courses.cit.cornell.edu/hort494/mg/specific.grafting/compatibility.html

Interfamilial
Although there are a few reports of short-term graft union formation between distantly related (interfamilial) herbaceous species, there are no confirmed reports of interfamilial grafts between woody perennials.
One extremely curious report of natural interfamilial graft compatibility which must be considered unconfirmed, and even unlikely, was the observation of La Rue (1934) [...]


Why does a cell produce a lot of p53 protein only to later degrade it? It is known that the half life of p53 is short and so does that play a role in the amount of energy the cell would need to expend to degrade all the p53? By that does the fact that the half life of p53 is so short does that just allow for the cell to not have to expend very much energy to degrade the p53 so in a way the cell doesn't "mind" having to degrade the p53 since it wouldn't take a lot of effort?

This answer is not reserved for the example you cite but for all proteins/RNAs which have high turnover. So your question generalizes to

What is the advantage of having high turnover? or in other words, What is the advantage of regulation via degradation?

Fast responsiveness. If your protein/RNA has a low turnover then it would take a lot of time for it to clear up from the cytoplasm even after the activating signal is gone. Enhancing the degradation will make the response fast. Cell cycle proteins such as p53 have to clear up as soon as the cell progresses to the next phase.
In certain cases an additional degradation control makes the regulation more efficient. If the "regulated" gene happens to be in turn an activator of many downstream genes, then efficient control actually helps in saving the cellular resources. I can't cite any literature for it but I have observed this in one of my unpublished research work using mathematical models.


Spider Identification Michigan This was taken in Ann Arbor, MI.  It looks a bit different from the wolf and grass spiders I'm used to seeing.  Anyone know  what this might be?

edit: Per request, I've uploaded a better picture.  Actually, it's the same picture, but I postprocessed the first image quite a bit to ease identification.  The second one is not post processed but (hopefully) clearer.

Processed image:

Unprocessed image:

I can't tell how big your spider is. :( But I agree, it's probably not a wolf spider. (The fourth pair of legs is the longest in the wolf spider

I think it might be a fishing spider (Dolomedes tenebrosus). They do hang out in man made structures and are the most common fishing spiders found.

  Fishing spiders are similar to the larger wolf spiders in size, shape, and coloration. Species in the genus Dolomedes are called fishing spiders because most live near water and have been reported to catch small fishes and aquatic insects from the water as they walk on the surface. The species Dolomedes tenebrosus is more frequently associated with wooded areas (it would be more accurately classified as a tree-dwelling spider) and is a common household invader in these locations. It occurs from New England and Canada south to Florida and Texas.

The stripes on the legs are characteristic, the shape and size ratio of the thorax and abdomen are right, and they are smaller than their giant cousins that catch minnows (!). The coloration on the abdomen can vary. The females are 1.5 to 2.6 cm *about an inch) in length; males are smaller. The legs of both male and female are banded with alternating brown/black, scalloped rings on the femurs and reddish-brown/black rings on the tibia. Seeing an eye pattern and/or a good side view would help.


Is secondary follicle or Graafian follicle arrested in the second metaphase of oogenesis? My note about which I am not sure:

  Secondary oocyte is arrested in the metaphase II monthly after puberty until fertilization with sperm.

The following picture also satisfies my sentence: .

So you can see that the secondary oocyte that is arrested seems to be Graafian.

I know that Graafian develops during the second week.
I know that the secondary follicle is developing two days before ovulation.
It seems that the development of the secondary follicle ends and the formation of Graafian follicle occurs just before ovulation.
My lecture material suggests that Graafian follicle is arrested in metaphase II, since Graafian follicle is ovulated once in a month and waits sperm in tuba uterina infundibulum:

The answer to my question is not also clear from my previous thread:

  An oocyte completes meiosis I as its follicle matures (during ovulation) resulting in a secondary oocyte and the FIRST polar body. After ovulation, each oocyte continues to metaphase of meiosis II.

Which follicle is arrested in the metaphase II of oogenesis?

Graafian follicle.

The secondary oocyte and thus Graafian follicle are arrested in the second metaphase of oogenesis.
After this the corpus luteum develops from the follicle during the luteal phase of the menstrual cycle.


Common mistakes when sequencing? I've sequenced two genes of 15 dogs for SNP analysis. the chromatograms of one gene looked perfect but the ones of the second gene didn't look as good. To be precise, the chromatograms of one exon looked relatively good with only a few spots where the bases seemed unreadable. But the chromatograms of the second exon were full of that. So there must have been an error somewhere and my question is where this could have happened.
My hypothesis is that I simply made a mistake during the mixing of the chemicals at some point.

Further useful information: The error must have happened befor the first pcr since i checked the pcr product with a fragment analyzer and the bands were only barely or not visible. Additionally, I noticed that many imprecisions seen in the chromatograms were only found at either the forward or backward strand.

Here is an image of several of the chromatograms of the exon that didn't work:

Looks like a dye blob.  A better job of clean up might help.

https://www.nucleics.com/DNA_sequencing_support/DNA-sequencing-dye-blobs.html


Is there a name for the behavioral phenomena of when animals like ants sacrifice themselves? Title says everything about the first question.

The second question is: does the special case when ants apparently explode, https://www.washingtonpost.com/news/morning-mix/wp/2018/04/20/meet-the-exploding-ant-which-sacrifices-itself-for-its-colony/?noredirect=on&utm_term=.b56b0100a88b have its own name or does it fall under the same previous term?

The term you're looking for is altruism. According to Wikipedia, altruistic behaviour "allows an individual to increase the success of its genes by helping relatives that share those genes." Someone correct me if I am wrong but this means that this behaviour evolved by natural selection because it ensures the survival of a species in most cases. The link about exploding ants is probably a nifty example of altruism.


What's the determinant of the male-biased birth sex ratio in humans? Will the baby be male or female? If it was a random biological switch then, with a huge sample number, the sex ratio at birth would be exactly 50-50. But it isn't; the ratio is about 51-49 in favour of males. So how does this inequality arise?

Further to @Remib's comments. I was specifically thinking of the sex ratio in humans. Would it be true to say that the genetic determinant of the sex ratio would be exactly 50:50 M/F? If the disparity is environmental, then how does it work, and wouldn't an environmental effect be more variable than the 51:49% that we see?

There are a number of ways in which the true sex-ratio at birth (let's assume the 51:49 is well estimated and is the true ratio) could deviate from 50:50. This list is just an brief overview.

Sex, in humans, is determined by the sex chromosome present in the haploid sperm cell which fertilises the egg. If males produced more or less Y-bearing sperm than X-bearing sperm, then the birth sex ratio would be expected to deviate from 50:50. However, studies suggest that sperm production is not biased towards X or Y bearing in humans.
The probability of fertilisation may differ between X- and Y-bearing sperm. If Y-bearing sperm were more likely to succeed in fertilising the egg then there would be a male-bias in the birth sex ratio. I've seen it suggested that the small Y chromosome makes the sperm slightly smaller and therefore faster, but can't find those claims right now. Regardless, it appears that sex ratio at fertilisation is not sex-biased.
Bias in the birth sex ratio can come through sex-biases in the failure rate in fetuses. If female fetuses are more likely to miscarry than male fetuses, over the course of the gestation, then the sex ratio at birth will be male-biased. It appears that there is sex-bias in the failure rate of fetuses which can be male or female-biased throughout gestation, but the tendency is for female-biased failure rate during the second trimester to generate an overall male-bias birth sex ratio.


What are some useful physical information of a protein? Beside energy and heat, I don't know any useful physical information of a protein. Can you help me list some of it. Somethings like Fourier-transform infrared spectroscopy to provide protein structure aren't what I'm looking for.

All the information about a protein, biochemical or functional is encoded in its structure, which are primary (Amino Acid (AA) sequence), secondary (alpha helix or beta pleated sheet), tertiary (overall 3D structure of a single peptide) and quaternary (overall 3D-structure of a protein composed of multiple peptides which are attached together through various different bonds) structures (http://en.wikipedia.org/wiki/Protein_structure).

Obviously, the key determinants for all these structures is the AA sequence of a protein, since that determines the biochemical property of a protein as well as its function (e.g. enzymatic residues and active sites, functional domains, motifs, whether it is post-translationally modified or not by phosphorylation and whether that causes its activation or inactivation through conformational changes or its interaction with other proteins etc).


Why do we die of old age? Not sure where to ask this question and thought this would the best place.
I am not after any opinion or theological, philosophical answers.
I am after the science or biology research, experiments or facts.
I would like the answer to be focused on the following:
Why do we die? With the condition that there are no diseases or any outside factors contributing to death.

In a simpler way, what makes us die biologically, physiologically. Is there a trigger? Is it cellular?.... and so on

As per suggested comment, I have researched genetics such as cell regeneration dynamics, Organ's lives studies.
Yet I find very little on the brains involvement, nervous system, chemical or anything else on the multitude of systems we have including triggers or irreversible messages from any or these systems

We die of old age because the biological cost of making us live forever does not improve our chances of passing on our genes. In nature something else would kill us eventually so there was never a reason to evolve the ability to live indefinitely. There are multicellular organism  that are biologically immortal(all unicellular are), they live slow low activity lives. A lot of the evolution of more "advanced" life is trading regeneration or longevity for higher activity. Literally live fast die young, leave more offspring.


What is the easiest way to measure a human body surface area? Looking for accuracy, cost-efficiency, and speed: this could provide useful information for determining individual bioinformatic calculations, pertaining to, for example cell type estimation, for personalized medicine regimens. I'm not sure why this question was marked as off-topic and closed.  The biological implications are grandioso.

How cost efficient does it has to be? Do you want these data to be comparable to another study?
Fundamental issues
What do you call surface area?
The interior of the guts (interior of the mouth, stomach, intestins, ...) are typically considered as exterior to the body. I would assume you don't want to consider these things in your measurements, right?
Coastline paradox
By aware of the coastline paradox

The coastline paradox is the counterintuitive observation that the coastline of a landmass does not have a well-defined length. This results from the fractal-like properties of coastlines.

Similarly, for the surface of the human body, the results will be drastically different depending upon the scale of measurement you want to consider. If you want to measure the small bumps of each atom or if you're happy to consider the the skin is a perfectly flat surface, the answer will vary a lot (numerous order of magnitudes)!
So, if you want to make your results comparable to those of another study, then you should definitely copy their methodology. If all that matters is that you can compare the different individual you measure, then you can pick a methodology that works well for you.
Methods
Those are in no way an exhaustive list.
3D scanner
3D scanner is probably the way to go for accuracy.
Approximation of body shape into cylinder and spheres
If you want cheap and inaccurate, you can assume each body part is a cylinder. Consider for example reducing the human body to 4 limbs (which you could further split in two separated by the knee and the elbow), a torso and a head. Just measure the perimeter of each body part and and approximate the surface area.
It might sound like a silly technic but it might well be good enough for your purpose (esp. if you're not comparing your results with another study).
Polyethylene film
Following Walsberg & King (1978) (thanks to @bshane for pointing this paper out), you can wrap people in a polyethylene film and then measure the area of the film. When measuring the area of the polyethylene film, you are going to have to make some approximation into some simplified (or series of simplified) shapes just like I suggested above. Walsberg & King (1978), when measuring birds, assumed the overall shaped was a prolate spheroid with a hemispherical head. You're going to have to try to find what simplified shape ressembles most to the polyethylene film.
Of cours, you might want to eventually consider other fabrics than polyethylene film and you might want to consider different number of fabrics.
You could prepare pre-measured rectangles and triangles of a given fabrics with colors matching a known size. Then you can just stick those fabrics on the individual body and simply add up the size of the shape you add on the body. This sounds like a difficult solution as you will have a hard time to correctly place the fabrics to avoid wrinkles, overlaps and gaps.
Test reliability of your measure
Reliability of your measure
Do not forget to repeat measurement on a few individuals to measure the accuracy of your measure.
inter-raters reliability
If several people are going to work on this project, you should also make sure to test the inter-raters reliability


Lethal gene and population genetics In the European population, about 1 in 2500 people suffers from Cystic Fibrosis, a genetically determined (descared), autosomal disease. Healthy parents have a child suffering from Cystic Fibrosis. The woman remarries a healthy man. What is the chance of a child from this second marriage suffering from Cystic Fibrosis ?

My attempt

http://i.imgur.com/4mhU3Qh.jpg

But the answer given is 1/100

Genetics of Cystic fibrosis

Cystic fibrosis is caused by an autosomal recessive allele. We therefore know that the frequency of the homozygote recessive allele is $P_{aa} = \frac{1}{2500}$, where $a$ denotes the recessive allele and $A$ will denote the dominant allele.

Solving the problem

The probability of the second child (from a second husband) has cystic fibrosis is the probability that a second husband is heterozygous ($P_{aA}$) times the probability that this father will transmit the recessive allele $a$ ($\frac{1}{2}$) times the probability that the mother transits the recessive allele $a$ ($\frac{1}{2}$, note that we know the mother is heterozygous as she is healthy but already had a child that suffers from cystic fibrosis).

So the answer is $p_{Aa} \frac{1}{2} \frac{1}{2} = p_{Aa} \frac{1}{4}$, we only need to calculate $p_{Aa}$. Let $x$ denote the frequency of the recessive $a$ allele, then $P_{Aa} = 2 x (1-x)$ at Hardy Weinberg equilibrium. As we know $p_{aa}=\frac{1}{2500}=x^2$, it results that $x=\sqrt{\frac{1}{2500}} = \frac{1}{50}=0.02$. Therefore, $p_{Aa}=2 x (1-x) = 0.0392$. The final answer is  $p_{Aa} \frac{1}{4} = \frac{0.0392}{4} = 0.0098 ≈ \frac{1}{100}$.

What you did wrong

You were pretty close to the right answer. In your calculations you multiplied the frequency of the recessive allele $a$ (which I called $x$) by $\frac{1}{4}$ but you should have multiplied the frequency of heterozygote genotypes (which I called $p_{Aa}=2 x (1-x)$) by $\frac{1}{4}$.


Hair becoming white in one night after tremendous stress You have surely heard about soldiers during the war whose hair became white in one night due to the tremendous stress.

I was wondering how is this possible biologically ?

The physiological condition you are looking for is commonly called Marie Antoinette Syndrome.

Under extreme psychological stress, the hair of the person does turn white but not in a single night (takes place slowly over successive days; in a matter of weeks) and cases of this has been reported worldwide generally in warzones.

Contrary to what you suggest, this phenomenon is extremely rare and I doubt many soldiers experience it.

Source- http://archderm.jamanetwork.com/mobile/article.aspx?articleid=712060

Another interesting tidbit the author mentions is whether Marie Antoinette herself suffered from it or not. The author goes in depth on the topic; regardless the syndrome is definitely real with documented cases. It is also known as canities subita.

Most in the scientific field now refer to it as an acute episode of diffuse alopecia areata. Alopecia areata is patchy hair-loss. This syndrome is referred to as such because the white hair eventually fall off.


Has the most recent common ancestor of all living birds lived after dinosaur mass extinction? I wonder if one or more phylogenetic threads of dinosaurs survived the mass extinction.

In other words, are all living birds equally related to any given ancient dinosaur, or do some birds relate more to some ancient dinosaurs while other birds are more related to other ancient dinosaurs?

I suppose that by the mass extinction, you are referring to the Cretaceous–Paleogene extinction event that happened 66 mya. The Most Recent Common Ancestor (MRCA) of all birds lived about 113.3 mya (early Cretaceous, according to this in oneZoom.org).

So yes, the MRCA of all birds is definitely older than the Cretaceous–Paleogene extinction event. As you said, this also mean that some ancient dinosaurs are/were more related to some extant birds than some extant birds are related.

You (the OP) might not need it but some other readers might need clarification about phylogeny with the post If dinosaurs could have feathers, would they still be reptiles?


Does a full tear of the gluteus minimus tendon result in a long-lasting inflammatory response? Does a full tear of the gluteus minimus tendon result in a long-lasting inflammatory response?

This answer mentions:

  An isolated gluteus minimus tear still causes functional problems because of the associated inflammatory response

But I read on {1}:

  “signs of either acute or chronic inflammation have not been found in any surgical pathologic specimens in patients with clinically diagnosed lateral tennis elbow syndrome,”

Note that tendon tears are present in a tennis elbow (a.k.a. lateral epicondylopathy). From {2}:

  Review of MRI findings from 24 patients with epicondylitis reported increased intratendon signal on both T1 and T2 pulse sequences58 with occasional bone marrow edema pattern in the epicondyle. Other studies have shown thickening, edema, and tears of the common extensor tendon.

References:

{1} Bass, Evelyn. "Tendinopathy: why the difference between tendinitis and tendinosis matters." International journal of therapeutic massage & bodywork 5, no. 1 (2012): 14. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3312643/
{2} Taylor, Samuel A., and Jo A. Hannafin. "Evaluation and management of elbow tendinopathy." Sports Health 4, no. 5 (2012): 384-393.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3435941/

The article you linked is interesting, but as @Charles E. Grant mentioned in the comments, it’s not particularly reasonable to compare a non-tear repetitive stress injury (like epicondylitis) to a full muscle tear. Non-tear repetitive stress injuries persist because the offending frequent motion doesn’t stop. A muscle tear, however, will recruit an inflammatory response that will eventually be resolved by anti-inflammatory factors (Th2 cells directing the cellular microenvironment towards healing / scarring).

This healing process might not result in an optimal resolution of the initial injury, and it’s not unique to any particular body system. Rather, pretty much anything in your body that can be injured will first respond with a period of innate inflammation followed by fibrosis and resolution (whether or not that restores function / alleviates pain depends on a number of factors including injury severity, therapeutic management, and healing conditions e.g. if there were repeated injuries during the healing process).

With regard to gluteus minimus tears — it depends on the injury. If a patient persistently aggravates an already-torn muscle, they will have more inflammatory cells recruited to the injury. If they do a good job allowing the injury to heal (not re-aggravating the injury, receiving surgery if structural correction is required), the inflammatory process will resolve relatively quickly.


Does recombination slow mutation accumulation in sexual populations? Is there any evidence? Mullers Ratchet is the process by which asexual organisms would accumulate mutations without bound. It is claimed that sexual organisms would slow this mutation accumulation through recombination. Is there any evidence that recombination achieves this? Preferably experimental evidence.

It's a good question and one without a wholly satisfactory answer.  Here's a nice review from 2012 outlining the theoretical questions regarding Mueller's ratchet and recombination.

There also is "unequivocal evidence that deleterious mutations accumulate in low recombining regions of the genome, due to the reduced efficacy of purifying selection. " So if you accept this correlation between recombination and removal of deleterious mutations, then studies such as these are compelling evidence of what's happening in real populations .

One other thing to keep in mind that in terms of experimental evidence, it is non-trivial to translate theoretical measures of fitness (e.g. "selection coefficients") to something that we can directly measure in real populations.  So even determining if there is an increase/decrease in deleterious alleles is going to dependent on having useful data in the first place. The assignment of "true" measures of selection on individual genotypes is the mainstay of experimental evolution (nice review here) and is very labor intensive. Moreover, the vast majority of this work has been carried out in bacteria (due to their short generation times) so effects of recombination are not addressed. Nevertheless there are some cool comparative studies in yeast showing how recombination can make selection more efficient.


Gender and age-specific mutation rate in plants Background

General concept

According to Cochran and Harpending (2013), mothers transmits on average a number $x$ of new mutations to their offspring. This number $x$ is independent of the age of the Mother. Fathers, however transmit a number of new mutations to their offsprings that is very much dependent on the age of the father for developmental reasons. In short (and probably poorly stated due to my lack of knowledge in physiology), spermatogenesis is a continuous process that occurs during the lifetime of the individual while the creation of ovules occurs once and are then stocked.

Human example

According to Kong et al.(2012), in humans the mother transmit on average $15$ new mutations and the father transmit on average $25 + 2(g-20)\space\space$ new mutations, where $g$ is the age of the father. For example, a 30-year-old father transmits $25 + 2(30-20) = 45\space\space$ new mutations. (This approximation holds only for men older than 20 years).

Question: How about plants?

Do you think that in plants too, male and female organs (or individuals for (gyno/andro)diocious species and eventually sequential hermophroditic species) transmit a different number of new mutations for similar developmental reasons?
Do you think that in plants the number of new mutations is age-dependent in males but not in females alike in humans?
Do we have any estimate of the sex and age-specific number of new mutations transmitted in plants?

From Whittle and Johnston (2006):

  Specifically, human epidemiological data and/or nucleotide substitution rates of selectively neutral DNA (which equals the mutation rate, Kimura, 1983; Miyata et al., 1987) have shown that more mutations occur in the male than in the female germ line for numerous animal taxa (e.g. humans, mice, chickens, and sheep) and in older rather than younger human males, patterns that each agree with the cell-division hypothesis (i.e. more DNA replications in males and in particular older males; Penrose, 1955; Risch et al., 1987; Becker et al., 1996; Moloney et al., 1996; Li, 1997; Green et al., 1999; Crow, 2000; Li et al., 2002; Makova and Li, 2002). Other data, however, have indicated that the mutation bias reported relative to gender and male age are not generally well correlated with the number of germ cell divisions and that other factors could explain these trends, such as methylation patterns, differential repair, metabolic rates, and preferential transmission of mutations to pro- geny from older males (Risch et al., 1987; Martin and Palumbi, 1993; Drost and Lee, 1995; Bromham et al., 1996; Hurst and Ellegren, 1998; Martin, 1999; Crow, 2000; Huttley et al., 2000; McVean, 2000; Sommer et al., 2001;Hebert et al., 2002; Hurst and Ellegren, 2002; Kumar and Subramanian, 2002; Li et al., 2002; Bartosch-Harlid et al., 2003).

…so basically we don't really know whether difference in gametogenesis between males and females lead to more sex and age-specific mutation rate!

However, Whittle and Johnston (2006) in reviewing many articles also show that old seeds are more likely to carry chromosomal aberration and that old individuals are more likely because of the instability of their metabolism to transmit more mutations but that would be sex independent and would not result in different gametogenesis as I was expecting in asking this question. Also the kind of mutations that become more frequent with all parents are chromosomal abnormalities or important deletion but not so much substitutions (which was also what I was interested in when asking).

Thanks @DevashishDas for finding this article. This other one was interesting as well.


Prostate, seminal vesicles or testis which one is bigger(by volume and size)? I can't understand this by looking at these photos, especially the last picture makes me more doubtful.

Do you know which of them is the biggest one by volume?

Another question is, what is the biggest organ in the male reproductive system? (Note that the bladder is not a part of it.)

The average seminal vesicle length was 31±10.3mm and its average volume 7.1±5.2cc. That is verified by another source which states 6-10mm in controls.

The average prostate volume ranges from 20 to 40cc from ages 30  to 80, 3-2-3cm for younger males 5-4-5 for older ones.