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What is blue light?
What is the "blue light" often discussed in relation to human melatonin production, sleep/wake cycles, etc.?  A Google search seems to define it as light of a particular wavelength, suggesting that it literally means "light that's blue in color," but many articles seem to attribute blue light to the light emitted from computer/TV/etc. screens, which is not inherently blue in color.
What exactly is blue light?  For example, would adjusting the "blueness" of a colored light bulb, as if raising and lowering the "B" slider in an "RGB" color selector (raising "B" in the morning and lowering "B" in the evening), have at least a hypothetical positive impact on human circadian rhythms?

Blue light means wavelengths that appear to the human eye as blue when they are presented alone. This light is important for sleep/wake cycle regulation because this is the wavelength that cells that participate in this regulation respond to.
"White light" is light that covers the full visible spectrum; sunlight, for example, is fairly white. However, that light contains plenty of blue light as well as all the other colors - there is no actual wavelength for "white," it is a collection of all the other wavelengths.
Similarly, TVs and other screens emit red, green, and blue light. Because of our makeup of photoreceptors, this is sufficient to mimic any visible color. When referring to the blue light of televisions, people are referring to that blue component. If you disabled the blue channel somehow you would get a very strange picture but also activate less the cells that sense daylight based on blue light.
The reason screens are so problematic is that people stare directly at them and take in a lot of light. Other sources of bright, whitish light would have the same effect.


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Speed of electric signal vs chemical diffusion
I'm currently reading the book, "An Introduction to Nervous Systems" by Ralph J. Greenspan.
On page 20, there is a sentence that confused me. It was, "Electrical signaling has the advantage of being able to cover large distances very quickly, much more quickly than chemical diffusion". It is in the context of the primitive signaling mechanism in Paramecium.
My doubt was, isn't the electrical signal caused by the movement of ions? Then how is it any different from chemical diffusion? And again, it's not a electrical signal that travels, but a changing potential, right? Then how does it move at a faster pace than diffusion?

Membrane potential is a directed force, while diffusion is a random walk
Your confusion is entirely justified, as you're correct that both diffusion and depolarization rely on the speed of ion travel. Where they differ is that depolarization is a directed force, occuring only in one direction along the membrane, whereas diffusion is subject to the stochastic walk of ions in water.
When membranes depolarize, the whole membrane begins with a certain amount of "pressure" built up behind it. As the signal propagates, a small area of this pressure is released at a time and triggers the next section to trip. That next section is essentially identical to the previous one, with the same amount of pressure behind it initially. In this way, you can imagine membranes "conserving" the initial concentration, so that the signal strength isn't dependent on the distance from the signal itself.
Diffusion, on the other hand, is stronger initially and decays over distance because of its stochastic nature. It's a probabilistic force, and so depends in general on something like the square root of the distance. If you imagine a thousand ions taking a step forward in one moment, in the next it's equally likely that five hundred take a step backward even as an equal amount moves forward. So the signal degrades over time and distance from the source.
If that was confusing, the following metaphor may help. Depolarization acts like a line of dominos, while diffusion acts like a complex dance. Check out this video of the largest human mattress dominos: the speed they're falling over is pretty constant when they're not turning. Compare that to two dancing humans who are equally likely to move forward and backward, and hopefully you can see that the mattress dominos is the faster way to go, even though each one is theoretically limited by how fast a human could move.

Electrons are >100,000 times lighter than the atom nucleus. For chemical diffusion the entire atom moves, it moves >100,000 times times slower.
Molecular diffusion moves at ~500m/s
Electron signals move at ~50,000,000, m/s
In saline, electrons move at 10% speed of light.
In silver, they move at 95% speed of light.
Crowds of electrons drift very slowly, ~1mm per second. It's called electron "drift". Individuals orbiting and free electrons move at nearly the speed of light.
Conductive materials have free electrons that hop between atoms. If you introduce extra electrons at one end of the conductor, it will push free electrons at the speed of light from one atom to another, while the electron drift stays very slow.
Saltatory conduction travels at 10% the speed of light. Like Dubukay sais, the electrons travel like dominos. The dominos don't travel far/fast but the signal does.
Electrical signals are like a sound pressure wave, where the medium/the atoms stays nearly in the same place, but the electron excess propagates very fast with a wave-front, on a conductive line. only a very small number of electrons move, and they don't move very far at all, i.e. one micron each. The electrons travel like a sound pressure wave. The electrons hardly move but the pressure imbalance moves fast. for chemical diffusion I imagine two colors of paint mixing, atoms travel all through the medium, used by the brain to breach micron distances.

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Mating patterns and genetic superiority
In peacocks and peahens, the peahens prefer mating with peacocks having a large and bright tail. But how is having a large tail an indicator of genetic "fitness" (in survival terms) ? If having a large and bright tail is not related with genetic superiority, then what is the point of having the mating ritual?

Darwin thought quite a bit about this. He even said "The sight of a peacock makes me sick". https://www.ncbi.nlm.nih.gov/pubmed/10824193
He added to his ideas about natural selection to include sexual selection. Traits selected by females, even when they are non-adaptive for males, will increase the males fitness (as defined by his number of offspring). There is also the idea that perhaps possessing such an outrageous and non-adaptive tail proves that you a good mate, the same way we would think that a guy who could win a sprint while carrying barbells must be superior.

Evolution of traits under sexual selection is relatively complex subject that isn't easily summarized in a post. In short, these are the most important concepts you will want to read about; Fisherian runaway (aka. runaway selection), the sexy son hypothesis), the good genes hypothesis and Zahavi handicap principle.
All these concepts are somewhat related and the semantics can quickly become a little complicated and has been subject to a number of papers (e.g. Kokko et al. 2003). My understanding of the semantics details is limited. To my understanding, the Fisherian runaway selection and the sexy son hypothesis are very similar and the good genes hypothesis and Zahavi hanicap principle are related. What you will be most interested in is the Fisherian runaway selection.
I will below just cite some popular sources and I will leave to you the pleasure of understanding and misunderstanding the differences between these concepts :)
evo101 > Fisherian runaway

Imagine a bird population in which females choose mates at random. Males with slightly longer tails fly a little more adeptly, avoid predation, and so, survive better than males with slightly shorter tails. In this situation, a gene for female choosiness (longer tail = sexier) will be favored, since by choosing a long-tailed male she will have sons with longer tails. This trait will spread through the population until most males have long tails and most females prefer long-tailed mates. So far so good.
However, once this has happened, the process may run out of control, until the male trait becomes so exaggerated that it is disadvantageous. In other words, female preference, instead of survival advantage, may begin to drive the evolution of ever-longer tails, until males are encumbered by showy plumage that no longer helps them avoid predation.

evo101 > good genes hypothesis

Imagine another bird population in which females choose mates at random. Some males in the population have better genes for survival than others, but it is difficult to tell whether a male has good genes or not. In this scenario, long tails make it more difficult to survive�they are costly to produce and maintain. Because they are so costly, only males with good genes have the extra resources to produce them. In this situation, a long tail is an indicator of good genes. A gene for female choosiness (longer tail = sexier) will be favored, since�by choosing a long-tailed/good gene male�she will have sons with good genes. This trait will spread through the population until most females choose long-tailed mates and males that are able to produce long tails are favored.
If females choose males with “long and costly” tails, they are guaranteed to get good genes! If they choose males with “short and cheap” tails, they may get good or bad genes.

Wikipedia > Sexy sons hypothesis

The sexy son hypothesis in evolutionary biology and sexual selection—proposed by Ronald Fisher in 1930—states that a female's ideal mate choice among potential mates is one whose genes will produce male offspring with the best chance of reproductive success. This also implies that a potential mate's capacity as a parental caregiver or any other direct benefits the father can offer the mother, such as nuptial gifts or good territory, are irrelevant to his value as the potential father of the female's offspring. Fisher's principle means that the sex ratio (except in certain eusocial insects) is always 1:1 between males and females, yet what matters most are her "sexy sons"' future breeding successes, more likely if they have a promiscuous father, in creating large numbers of offspring carrying copies of her genes

Wikipedia > good genes hypothesis

"Good genes" theory proposes that females select males seen to have genetic advantages that increase offspring quality. Increased viability of offspring provides compensation for any lower reproductive success that results from their being "picky". The good-gene hypothesis for polyandry proposes that when females encounter better males than their previous mates, they re-mate in order to fertilize their eggs with the better male's sperm.

Clearly, the good genes theory is not the one you are interested in with the peacock tail example.
Wikipedia > Zahavi handicap prinicple

The handicap principle suggests that reliable signals must be costly to the signaler, costing the signaler something that could not be afforded by an individual with less of a particular trait.

Note that the term "genetic superiority" is never used in evolutionary biology. In fact the term sounds very social science related and make me think of the ugly side of eugenics. We usually talk about "fitness difference", "low fitness" and, "high fitness".

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Genes and proteins with a significantly inbalanced composition
According to Wikipedia, the median size of a protein-coding gene is 26,288 bp which makes it possible (from statistical considerations) that the nucleotides C, G, A, T appear in roughly equal amounts in one strand. But maybe this is wrong so I want to ask:

Are there and which specific protein-coding genes have a significant inbalance
  of amounts of C, G, A, T in one strand?

Related to this is the question if there are larger proteins (containing up to 27,000 amino acids as the titins do) with a significant inbalance of amounts of the 20 different amino acids?
Might it be the case that from an inbalance of the gene an inbalance of the protein may follow?

I don't know about the base usage/(im)balance, but using the transcriptome sequences, that would be relatively easy to check. For amino acid usage, I think there is a bias for evolutionary older proteins (especially mitochondrial ones related to bacteria) to not use certain amino acids as much (mostly the aromatic ones I think)

Tangential to the topic of protein, but related to the "strandedness" mentioned in your question, is the phenomenon of GC skew (not to be confused with GC content).  Differences in strand composition may be explained by asymmetric mutational pressures between the leading and lagging strands during transcription and replication.


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Are there "old" neuron types in the neocortex?
"Old" may mean a neuron type that appeared early in the tree of life, and it may mean – going together – that it comes early in the lineage tree of neuronal cells, rooted in the fertilized ovum:
[This is only for Schmidtea mediterranea. Could someone give me a link to a comparingly nice lineage tree for human neurons, please?]
My question is twofold:

Are there neuron types in the adult healthy brain co-present with some of their differentiated descendants?
Are there "old" neuron types in the neocortex, that either appeared early in the tree of life or come early in the lineage tree?


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How and when does the regeneration of cells that have died start?
I assume that the replacement of cells that have died (or been removed by any means) doesn't work on a single cell level but starts only when some critical number of cells have died.
My question is: How is this signaled (to the regenerating cells), and how is the critical number encoded, i.e. the signal threshold at which regeneration starts?

Whatever the answers may be, keep in mind this is a broad question and an answer will not apply to all tissues. Take an epithelium such as the gut lining or the dermis. It may help for you to think rather in a dynamic way ("stem cells in the crypt respond to cues to speed up or slow down the rate of cell replenishment") as opposed to a static way ("of 10 cells, 2 die; this crosses the repair threshold, so 2 cells divide to restore cell count of 10").

@SPr: Thanks for the enlightening comment and the instructive picture you point me to - I wasn't aware of "stem cells in the crypt" (what a great name by the way!) Nevertheless: What are those cues the stem cells respond to?

I'm no expert on this, but it is known that stem cells proliferate in response to a variety of mechanical, biological, and chemical cues/signals. They may respond to signals released by compromised cells, to wound healing cues from platelets for instance, to apoptotic bodies, to stretching or exposure to the atmosphere, to paracrine, immune or endocrine signaling, etc. And it's quite tissue specific. Hope that helps.


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Applying Constraint Programming to sequence alignment/analysis
My Masters program is focused on formal methods such as SAT solving and constraint programming. I am interested in applying such techniques to problems in sequence alignment and sequence analysis, areas that have been dominated by statistical methods.
So can you give me examples of some research problems suitable to be approached as constraints satisfaction problems?
Note: By constraint programming I also include more flexible paradigms like weighted constraint programming, where a solution may violate some of the constraints.

Do you mean optimization? In any case I guess you either have to state your problem clearly and what you want to do. Moreover, this question is not really suitable for this forum. You can ask this in CS-SE.

I mean a problem that can be modeled by specifying a set of constraints and specifying relations between these constraints. Optimization is a special case and is more related to weighted constraints problem (then we are optimizing for a minimum violation weight)

As for asking this on CS-SE: I disagree, my question is not about constraint programming. It is about what problems in bioinformatics (in particular sequence alignment) can be tackled as a constraints problem. The people who would know this best are people working in biology.

First read how local and global alignment differ from each other. Then decide an objective function, i.e. how to measure the similarity between two sequences? Maybe use Hamming distance? Or Levenshtein distance? After this the optimization part probably comes out quite naturally.
Be sure to check the existing softwares. Easy things have been tried out already. (And by the way, for some reason biologists call n-grams as k-mers.)

Well, I am in the middle of project on using HMMs for alignment, and have read the basics. But the problems I have read about (aligning two sequences for functional analysis and allowing for nucleotide insertion/deletion) does not seem to be suitable for modelling with constraints. So I am asking to see if there are other problems that might be better suitable for that.

The closest thing I've seen that may be suitable for constraints approach is the use to transformational grammar for long-distance dependencies. But even there I am not very sure it can be framed as CSP.

Try reading this article: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0018093#pone-0018093-g003 Any help?

Thanks, maybe. One will have to look at the systems/tools mentioned in the article to see if there are any that are constraints-based (rather than statistics based) or at least incorporate constraints in some way.If so then that would be a good candidate for constraints programming project.

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Spectrophotometric Values of Individual Nucleotides
All around the net you will find this list giving 260/280 ratios of individual nucleotides:
Guanine: 1.15
Adenine: 4.50
Cytosine: 1.51
Uracil: 4.00
Thymine: 1.47
Yet I cannot find a reliable source for these values. One source cites a 70s version of Leninger's Biochemistry but even though I got hold of a more recent edition, I cannot find that information in there.
Does anyone happen to know a quotable source for this?

I too was unable to find the data in the 3rd Edition of Lehninger's Biochemistry.
A good source of such information usually is

Data for Biochemical Research, by Rex M. C Dawson, Daphne C. Elliott, William H. Elliott and Kenneth M. Jones (3rd Edition, 1986, Clarendon Press Oxford).

The first thing to note is that the ratios may be significantly
pH-dependent, and the source quoted by the OP does not specify what pH the data refer to.
The data in Column 2 below  been taken from the above source, from which the data in Column 3 were calculated.
(pH 7)-------------A280/A260--A260 /A280
Adenine             0.13        ~ 7.7
Cytosine            0.58        ~ 1.7
Guanine             1.04        ~ 0.96
Uracil              0.17        ~ 5.9
Thymine             0.53        ~ 1.9

These data seem to have been substantially taken from an article by K. Burton in the second edition of DFBR.

K. Burton (1969) Spectral Data and pK values for purines, pyrimidines, nucleosides, and nucleotides in Data for Biochemical Research by Rex M. C Dawson, Daphne C. Elliott, William H. Elliott and Kenneth M. Jones (2rd Edition, Clarendon Press Oxford).

If it's so important to you that you need a quotable source for this, I'd measure it myself with the equipment I use for the real experiment.
Otherwise I'd suggest you look at a chemical database such as NIST:
http://webbook.nist.gov/cgi/cbook.cgi?ID=C58617&Mask=400 and use the spectra that can be found there.

@tomd: Yes, to get the "true" values that would be required, and apparently also in the literature they didn't get the same values twice. I'd say if you need them for your own experiments, it might be better to actually measure the purities you have.

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What is the name/type/species of this spider?
Below are images of it, specimen found in the western region of the Pacific Northwest - North America.

I presume it is Eratigena atrica, commonly called the giant house spider.
It belongs to      Agelenidae family.

E. atrica is found in Europe, Central Asia and Northern Africa. It was unwittingly introduced to the Pacific Northwest of North America circa 1900 due to human activity and has strongly increased in numbers for the last century.

Reference: Wikipedia

This is, indeed, a giant house spider. But the species known to be established in the Pacific Northwest is Eratigena duellica, not E.atrica. (E.duellica is still part of the "E.atrica complex")


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How to interpret dual luciferase assay result (RLU)?
I performed a dual luciferase assay using pGL3 firefly luc as experimental reporter and pRL-TK renilla luc as internal control (Promega assay kit). I used a manual luminometer to analyze my sample. After that, I got following result:
Sample        RLU (LARII)                   RLU (stop & glo)
A               1978                               902
B               1702                               1101
C               1952                               980
As I am doing it for the first time, I cannot understand the result. I want to know, how can I interpret this result? There is no unit. RLU stands for relative luminescence unit; but what it actually means? What is the method to compare the results of different samples? How can I understand expression efficiency? I have read some papers but unfortunately my concept is not being clear.
Where can I find useful information and guidance about it?

Relative luminometer units (RLU) have no unit. They are the result of the luciferase reaction and proportional to the expression of the luciferase gene, meaning the higher the numbers are, the higher the expression is.
To analyze these numbers, you usually use a control, to which your samples are then relative to. So expression from your luciferase vector is 10x higher in the treated sample compared to the control for example.
As the RLU has no unit, it is hard to compare measurements directly. To overcome this problem, you can use a second luciferase reaction (the renilla luciferase) to be able to normalize between samples and to correct for transfection efficiency, but still, your values are only relative.
They are influenced but the kit you use for the measurement, the machine you use (so always use the same machine) and so on.
To normalize the values, you divide each firefly luciferase value by the value for the renilla in the same well. Ideally alls renilla measurements are the same (as you transfected the same amount of plasmid in each well, have the same number of cells etc., but if not, this corrects exactly this problem). You cannot calculate the transfection efficiency from this control.
To calculate the relative expression ratios between your sample B and the respective control A, you set the control to 1 by dividing A/A=1 (for example: A=10, 10/10=1) The relative expression of B is then B/A= relative expression (for example: B=5, relative expression: B/A= 5/10=0.5). In the example the relative expression of sample B would be half the one of the control.

Thank you for your answere. It is helpful; although I am not completely clear. I have used renilla luc here to normalize the expression which is indicated here as RLU (stop & glo) values. And sample A indicates the control. Now, how can I compare my results? Can you give me one example please? Will I have to make a ratio of the two values (firefly RLU: renilla RLU)? And what does the ratio mean? How can I calculate the transfection efficiency? Please help me to know this. @Chris

@MRahman Is this clearer now?


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Is there a fundamental reason that plants cannot fix their own nitrogen?
Plants must have nitrogen to grow. According to the answer to this question, there are no plants that can fix their own nitrogen (without the help of bacteria).
Plants get their nitrogen in the form of nitrates (NO3-) or ammonia (NH4+). Nitrates and ammonia get into the soil through

lightning (causing N2 and O2 to combine to form NO which then reacts with atmospheric water and is brought to earth by rain)
nitrogen-fixing bacteria associated with leguminous plants
fixed nitrogen from dead plants/animals (ammonification), urine, etc.
ammonifying and other bacteria

The answer also states that it seems to be possible to engineer plants to be able to fix nitrogen.
So one could think plants could have evolved to be able to fix nitrogen, but did not.  Maybe it just did not happen based on it's probability to happen.
Is there any other explanation?
Maybe the ability to fix nitrogen would have a harmful effect on plants? Or fixation requires a complex set of related mutations? Are there enough areas with soil depleted of nitrates to exert a selection pressure for nitrogen-fixing plants?

Edited your question a bit. Please feel free to roll back if you feel the edit detracts from your intent. :-)

That is an interesting question. But rises some line of thought by analogy, e.g. why people won't evolve to produce their own ATP without mitochondria? (I mean of course Eukaryotas in general). I don't see any reason why multicellular organism cannot incorporate bacterial functionality either as happened with mitochondria, or as just separate cell type, that will provide desirable enzymatic reactions.
The answer, no matter how unsatisfactory, might be simple: because it so happened. We definitely can create experimental conditions lacking N-fixing bacteria as well as varying amounts of nitrates, nitrites etc. And then produce and screen line of mutants for ability to fix nitrogen without symbiotic partners.

I don't think it would be an unsatisfactory answer to conclude it could have happened either way, with some probability, and the random outcome was it did not - without any known mechanisms influencing the probability.

i feel that in biology there are many thing that are just are. but such an answer is always insufficient to my taste. for example, why DNA is winded that way and not opposite, or others. in case of nitrogen, maybe, it was easier for two different specialized organisms to live together rather than to one of them acquire some special traits.

DNA is winded in the Type B double helix because it is usually the lowest energy conformation available. There is almost always a good reason why something happens, it may not be known for nitrogen fixation, but the reason probably exists. See http://en.wikipedia.org/wiki/Nucleic_acid_double_helix#Helix_geometries

I meant right- versus -left-handedness of the helix, or chirality of glucose (bacteria eats only D-Glu)

The most obvious answer to your question is that the enzyme responsible for nitrogen fixation is inactivated by oxygen. So photosynthesis, which produces oxygen, rules out nitrogen fixation, and, as you know, plants photosynthesise.
However, they could have evolved specialized cells for nitrogen fixation, which do not photosynthesise. In fact, some colonial cyanobacteria, which photosynthesise, form such specialized cells called heterocysts.
So why haven't plants evolved such specialized cells? I think a fundamental answer to this question would invoke the evolutionary theory of specialization which says that specialization in one thing at the cost of the ability to do something else is selected for when the trade-off is convex, i.e. when you can be really good at only one thing, and being able to do both implies you are actually quite bad at both.
I hope this sets you off to find the fundamental reason you are looking for.

Interesting answer. Can you please add some references to it?

Nitrogen fixation occurs in some species of Cyanobacteria, which would be impossible if your hypothesis is correct.

@MarchHo, doesn't the second sentence of the second paragraph of my answer give an reason why it is possible? I.e they create anaerobic circumstances in specialized cells that do not photosynthesize, where N2 fixation takes place, thus separating the two processes?

@Chris, I was taught at uni about heterocysts and the inhibition of N fixation by O2. I don't have references ready for it. You can read about it at Wikipedia, but I wouldn't refer to Wikipedia to substantiate claims. The evolutionary theory I got from Adaptive Dynamics, see e.g. fig 2.2 of this book. If I have time I will add refs.

I believe that evolution is driven by the needs of the organism to adapt not by the need to adapt for human beings consumption. meaning that some nitrogen gets back to the soil through the effect of nature e.g. fixation of nitrogen during storms  and when fecal matter decomposes in soil and these I assume provide enough nitrogen for normal plant growth and so the plant is not "forced" to adapt to say a deficiency in nitrogen but for humans I assume because of agriculture the land gets "exhausted" and so we need fertilisers but plants have not evolved becuase I assume there was no pressing need for it. That is my own thinking assuming I understood your question


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Is there a difference between "cell line" and "cell strain"?
I'm translating one Russian text where a cell line is transfected to produce a drug. I wonder if I can sometimes use "cell strain" or simply "strain" instead of "cell line" or instead of "producer" (продуцент, meaning "the producer of the drug", i.e. the cells that produce the drug).
I googled and found this answer on Yahoo answers:

Cells in culture can be passaged a finite number of times before reaching a crisis which can be compared with aging. The number of passages, before reaching crisis, has been termed the Hayflick limit and is related to the longevity of the species from which the tissue was originally derived.
Within the Hayflick limit, the cells are referred to as a cell strain.
Cells that survive the crisis and continue to grow are referred to as a cell line. Cell lines can also be derived directly from cancer cells. There are many properties that distinguish cell lines from cell strains, including altered chromosome number, changes at the cell membrane, and reduced requirement for certain growth factors.
Therefore:
A cell strain is defined as an euploid population of cells subcultivated once or twice in vitro, lacking the property of indefinite serial passage. Cell strains ultimately undergo degeration or death (senescence).
A cell line is an aneuploid population of cells that can be grown in cultures indefinitely.

Is this true? Is a cell line always aneuploid and capable of indefinite growth, as opposed to being euploid and incapable of indefinite growth?

"Strain", in general, is usually used for whole organisms (whether they are unicellular or multicellular). For example, there are mouse strains.
"Cell line", on the other hand, is a very specific term that is used to refer cultured cells obtained from a multicellular organism. They need not be necessarily aneuploid.

Is a cell line always aneuploid and capable of indefinite growth, as
  opposed to being euploid and incapable of indefinite growth?

Aneuploidy does not have any causative relationship with indefinite growth. Most cancerous cells evade the cell cycle checkpoints, which allows them to grow out of control. Some of these checkpoints also ensure proper segregation of chromosomes. Bypassing them leads to aneuploidy.

Are cell lines essentially immortal?

Usually primary cell cultures are not referred to as "cell lines" these days. However, originally, any cultured cell that grows in vitro is called cell line. From Freshney (Basic Principles of Cell Culture):

When cells are isolated from donor tissue, they may be maintained in
  a number of different ways. A simple small fragment of tissue that
  adheres to the growth surface, either spontaneously or aided by
  mechanical means, a plasma clot, or an extracellular matrix
  constituent, such as collagen, will usually give rise to an outgrowth
  of cells. This type of culture is known as a primary explant, and the
  cells migrating out are known as the outgrowth (Figs. 1.1, 1.2, See
  Color Plate 1). Cells in the outgrowth are selected, in the first
  instance, by their ability to migrate from the explant and
  subsequently, if subcultured, by their ability to proliferate. When a tissue sample is disaggregated, either mechanically or enzymatically
  (See Fig. 1.1), the suspension of cells and small aggregates that is
  generated will contain a proportion of cells capable of attachment
  to a solid substrate, forming a monolayer. Those cells within the monolayer that are capable of proliferation will then be selected at
  the first subculture and, as with the outgrowth from a primary
  explant, may give rise to a cell line.

Elsewhere, a cell strain is defined as positively selected subpopulation of cells:

A cell strain is a subpopulation of a cell line that has been positively selected from the culture, by cloning or some other method.  A cell strain will often have undergone additional genetic changes since the initiation of the parent line. Individual cell strains may, for example, have become more or less tumorigenic than the established line, or they may be designated as a separate strain following transfection procedures.

This definition does not say anything about what kind of selection was used. You can select for cell that express GFP, for instance. So that strain would be simply designated as GFP+.


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What is "non-immune immunoglobulin"?
From a short introduction to immunohistochemistry controls:

Isotype Control
This control can be utilized when working with monoclonal primary antibodies. The sample is incubated with antibody diluent, supplemented with a non-immune immunoglobulin of the same isotype (for example, IgG1, IgG2A, IgG2B, IgM) and concentration as the primary monoclonal antibody. The sample is then incubated with the secondary antibody and detection reagents. These steps will help ensure that what appears to be specific staining was not caused by non-specific interactions of immunoglobulin molecules with the sample. Background staining should be negligible and not resemble specific staining.

I googled and found out that some pathological agents can bind immunoglobulins in a non-immune fashion, i.e. by binding to their Fc regions. But that still leaves me in the dark on "non-immune IGs".
Maybe it is an IG with which the secondary antibody will not bind?
Or maybe it's an IG that has no activity against the target antigen?

The term "non-immune immunoglobulin" is both confusing and non-standard in the immunology field - "pre-immune" is sometimes used, but not always accurate. A negative control is as they describe - the same diluents and components of the sample incubated with the antibody of interest, only they use a non-specific antibody of the same isotype that is not expected to bind to any targets in an "immune-dependent" manner - the "usual" way you think of an antibody binding to a target antigen. However, antibodies can bind samples in an immune-independent manner, via protein-protein interactions (the sample was insufficiently blocked) or to Fc receptors, for example.
The non-specific antibody can be from several sources - a pre-immunization bleed from the animal that generated a polyclonal primary antibody, an antibody to a target not expected to be present in the sample, such as KLH or GFP, or a monoclonal antibody engineered or screened to not bind to anything.

In theory, "non-immune antibodies" are any kind of antibodies that do not bind the sample using their Fab, specific regions. See for example https://books.google.com/books?id=sFMJAwAAQBAJ&lpg=PA80&ots=O9CqXW9kYt&pg=PA80#v=onepage&f=false Here, a claim is made that they might still bind non-specifically using their Fc regions.
In practice, one ends up using a generic mixture of all immunoglobins from a species' blood (here, all "all immunoglobins of a specific isotype"). It is prohibitively expensive to deplete this mixture of specific antibodies for all the proteins in your sample. You could also imagine some denaturation that renders Fc regions inactive. I couldn't find evidence of either, so generic mixture it is. See http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1162460/pdf/biochemj00424-0223.pdf for an example of "non-immune" preparation - it is simply a precipitation of all IgG. It would be great if you could prove the generic mixture has very little or no specific antibodies to your samples*, but I doubt anyone bothers.
Another option is a monoclonal Ab that works against a completely unrelated protein. Again, one should prove their is no specific reactivity* with the samples.
Pro-tip: searching for "non-immune IgG" will bring way more results than "non-immune immunoglobulin". In general, "immunoglobulin" is less used than the synonymous "antibody".
* This means cleaving the Fc regions, separating them, labeling them with radioactivity or fluorescence, and trying them on a sample. It's tedious and expensive.

Check out my answer, it addresses some of the things you mention here. In practice, it's actually rather easy to make a non-specific negative control antibody.

If the "non-immune antibodies" are 100% not binding the sample, it means that their Fc is also guaranteed not to bind the sample. That makes their use as control in the protocol described in the question rather perfunctory. I am not sure what's worst as a control: a serum which may bind the sample (the way I said it) or a serum whose Fc is guaranteed not to bind (your variant).

I was talking about the Fab region, not the Fc. You definitely don't want to make an isotype control whose Fc doesn't bind to Fc receptors - that would completely defeat the purpose of using a control. What I was talking about was engineering or screening a clone with a Fab that doesn't bind any known antigen, but the rest of the scaffold is identical to your specific antibody of interest. That way, any binding/staining you see with it is truly non-specific (non Fab-mediated).


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Where to find the corrected BLOSUM matrices?
I was looking at this paper which talks about the miscalculations in the BLOSUM matrices and how the "wrong" BLOSUM62 matrix performs better than the corrected version. I was trying to find the corrected version they talk about to experiment with, but the link they list in the paper appears dead.
Does anyone know where I can find the corrected matrix that the authors talk about?  (preferably a version listing frequencies rather than scores)

Either write to them asking for the files or see the images in the supplementary info (fig 4-5). They could have at least made it as a table; unfortunately you have to manually type it out.

Okay, I emailed Dr. Mark Styczynsk (one of the authors) to ask about a link to the matrix. Here are the links he gave me:
http://web.mit.edu/bamel/blosum/revised_blosum.c
http://web.mit.edu/bamel/blosum/original_blosum.c
http://web.mit.edu/bamel/blosum/RBLOSUM64 (isentropic with BLOSUM62)
http://web.mit.edu/bamel/blosum/RBLOSUM62 (not isentropic, but it's 62)
The first link is to the c code to generate the corrected BLOSUM. According to Mark, just replacing the original c file in the original BLOSUM tarball with the revised c file can generate the corrected matrix for any of the BLOSUMs (30, 50, 92). Haven't yet tried that myself.


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What is the difference between "cistron" and "gene"?
I'm asking after reading the cognate wikipedia.en article on "cistron". I am still not sure about the difference between the two terms.
To me it seems valid to picture a "cistron" as the genome wide set of a specific gene's alleles ?
Thus if all copies of a gene bear recessive mutations all generating the same phenotypic trait (not necessarily the same mutation) no complementation is observed in a cis-trans test?

off the top of my head:
cistron and gene are equivalent to each other but cistron is a bit old-fashioned. Consider two phenotypes in different individuals belonging to certain organism; let's say both of them are recessive and you cross these phenotypes with one another. If you see wild type phenotype in the next offspring then it means your phenotypes reside in different regions in the genome and these regions were first defined as cistrons. Of course it then turned out to be much more complicated than that and people started using the term gene more often

A cistron is a gene - here's how the word came about:
It's 1955. The proposed double helical structure of DNA has been published and the race is on to understand the implications of this for genetics. Geneticists have been working with genes for decades, but they don't know what genes are. Sanger has sequenced the two polypeptides of insulin, so the idea of a specific sequence of amino acids is established. The emerging molecular geneticists believe that genes will be explained by a feature of DNA, probably a sequence of nucleotides, but they don't know how. Crick and others are theorising about coding (i.e DNA > protein), but at this stage there is no genetic code, no mRNA or tRNA.
Seymour Benzer, at Purdue, is working on fine structure of a genetic region in bacteriophage and in this year he publishes a key paper with that phrase as the title. Without going into a lot of detail about his experimental set up, he is studying a region of the bacteriophage T4 genome called rII. Wild-type T4 can form plaques on E. coli B or E. coli K12. Mutations in the rII region cause a large plaque phenotype in E. coli B so it is easy to isolate them, but these phage cannot produce plaques on E. coli K12 which sets the scene for a powerful assay for rare recombination events.
Benzer used this system to do very fine mapping of thousands of rII mutations because he was able to use the system to measure recombination frequencies, but what matters in the present context is that he was able to do a kind of complementation test (he called this pseudo-allelism). He was able to assign the rII mutants into two groups according to whether, in a mixed infection, they produced lots of progeny. So if he mixed two phage with different mutations and didn't get many progeny he put these in the same group. On the other hand if he did get a lot of progeny he placed the two in different groups. He called this approach a cis-trans test.

"The application of the phenotype test to pairs of rII mutants leads to the division of the region into two functionally separable segments."

This is as close as he dared to go to claiming to be studying genes. He refers to 'functional units' but never uses the word 'genes' because at this stage that word belonged to classical genetics in higher organisms. In 1957 he proposed the word cistron for the functional unit defined by this type of test, and the word caught on, particularly because of its incorporation into the operon model with the idea of polycistronic mRNA. His other coinings, muton and recon were not adopted.
The two T4 genes/cistrons in the rII region of the phage genome are now called rIIA and rIIB.

Benzer, S (1955) Fine structure of a genetic region in bacteriophage Proc. Natl. Acad. Sci. USA 41:344-354

Really nice answer.


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Plasmid with ITPG and pBR322 ori
I'm looking for suggestions as my internet searches aren't turning up much.
I'm trying to find a plasmid that has the pBR322 origin, as it's low(ish) copy number and can tolerate large inserts. Additionally I need the plasmid to be inducible with a system other than the pBAD setup (e.g. IPTG would be fine, but if there is one that is more tightly repressed that would be preferrable as IPTG is leaky).
Lastly, I could do with it having a potentially obscure resistance cassette, but this is less of a problem.
Any help appreciated.

You might want to check this https://www.embl.de/pepcore/pepcore_services/cloning/choice_vector/ecoli/vectorfeatures/

Gene 1985, Vol.40(2):183–190, doi:10.1016/0378-1119(85)90041-1 ‘ATG vectors’ for regulated high-level expression of cloned genes in Escherichia coli

The pET vectors family is what you are looking for.

Just to add, if you're worried about leaky expression you can select a strain expressing T7 lysozyme from pLysS.


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Depositing/publishing protein structure simulations
Just wondering if anyone has any information on what the general consensus on publishing/depositing online protein structure simulations is?
I've been doing a fair bit of work to characterise the 'quality' of the simulations I have (how well they approximate known homologous structures), but don't know what is generally thought of protein structure simulation methods. They do a lot of work in the CASP programs every couple of years to assess whether they simulate accurately, so a plausible structure simulation should be a valid surrogate for an otherwise unknown protein IMO?
Are the online databases purely for structures resolved experimentally?

The consensus is "not publishing/depositing anything". Reproducability might be an issue throughout biology, but it's sad to see that in the one area that should be perfectly reproducable every time the standards are as low as they are. Please just put it somewhere, supplementary info or any kind of database is better than nothing.

Yeah I fear you're right...read a paper recently about the number of genomes that go unpublished...and my group is as guilty of that as any. They will be included in my thesis certainly, and can be made available through our HPC infrastructure. Really I was just wondering if you tried to publish a paper with simulated rather than experimented structures, whether you'd be opening yourself up to serious criticism...

I published a protein engineering paper based on a model structure. I regret that we didn't publish the structure of the model (although it was just made with YASARA standard settings, nothing special). We had some troubles publishing it where we wanted, but using the model as the basis for protein engineering was never an issue.


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The role of GC content in promoting or hindering transcription
This is quite a specific question, and I'm hoping someone might be able to assist in a literature hunt I've been engaged in for ages.
I study some long bacterial operons, and have noticed that the GC% content at the 3' end drops significantly compared to the beginning of the operon.
I vaguely recall hearing (I can't remember if it was from a paper or a lecture or something), that lower GC (higher AT) content can promote transcription. This sounds plausible to me since it promotes strand separation (this is how replicon origins are often defined), but I've tried several times to find a paper that might demonstrate/attest to this. The hypothesis therefore, is that the distal ends of the operon might have lower GC in order to enhance transcription as the influence of the 5' UTR promotor sequences etc being to wane over a distance.
Has anyone ever come across such a paper or has any information to confirm or deny this? Information to the contrary (e.g. high GC reduces transcription) would also suffice.

Why would you think that transcription would be controlled at the 3' end of an operon? Surely all that it could do there is help termination. I don't understand what you mean in molecular terms about the influence of the promotor sequences begining (?) to wane. The promotor promotes binding of RNA polymerase, that's all. And the promotor sequences are not part of the  5'UTR (untranslated region of the mRNA) as they are not transcribed into mRNA. Have you compared different operons in your bacterium? The problem with GC content is that this varies drastically among bacteria.

What makes you think that bacteria do not modulate transcription along the transcript? The influence of a promoter sequence is essentially strongest nearest to it due to the processivity (or lack of) of the RNA polymerase. Yes I have compared multiple equivalent operant across various related bacteria and this is a consistent trend. I believe it has some significance as bacteria have mechanisms such as transcript elongation to assist in transcribing very long sequences. That is, at least, my conjecture. I am positive I’ve heard of this as a phenomenon before now...

Now you mention it I have heard that there was a problem with reading long sequences, although whether this was transcription or translation I don't remember and can't find it. But I would be wary of the simplistic GC = stronger base pairing therefore more difficult to separate idea. There was expectation that thermophillic bacteria would have higher GC contents, but they don't, and high-GC genomes like those of the herpes simplex virus manage as well as the related low-GC varicella zosta.

This paper suggests the opposite in mammalian cells. Obviously, gene regulation is quite different in prokaryotes, so don't know how much confidence you want to put into that one.
This paper suggests more of the same, but includes some caveats related to prokaryotes that may pique your interest. They do a pretty in-depth dive of GC content near genes from many different species, but I haven't read it closely enough to give a good breakdown.


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from an ageing reproductive stem cell's DNA to baby's "brand new" somatic cells' DNA
On the one hand, somatic cells's DNA age as life goes on, mitosis after mitosis, and that is reflected into reduced telomeres.
On the other hand, during life, reproductive stem cells must age too. However one half of the DNA of some random old reproductive stem cell is eventually transferred through reproduction, and the ageing cycle begins again, with new somatic cells with long telomeres.
What mechanisms can explain reproductive stem cells DNA do not age as somatic cells' DNA ? Or do we know how telomeres are growing back from old reproductive stem cells to gamete during meiosis ? Put another way, how is it possible that we are born with long telomeres ?
I am sorry for the formulation of my question. I think it is understandable but not really well written. However I don't know how to formulate it another way yet. Do not hesitate to reformulate it if you feel like it.
Thanks.

Some cell types have an active telomerase, stem cells are among these cells. Additionally sperm cells/eggs do not divide any further once they are haploid.

I was not aware of the "active telomerase". It seems to me like some great advantage for a cell. Why would some have it and others not ?

One advantage of somatic cells not having active telomerase enzymes is that they die when become too old / damaged / used etc. and new  somatic cells can take their place. These new somatic cells from progenitor cells aka "adult stem cells". This way we can renew our skin, relplace old red blood cells (although they don't even have nucleus) etc.

Then is'nt damage to stem cells' DNA, reproduction event after reproduction event, increasing as well ?

We have to be careful about how much we mix telomere length and aging. Yes diseases that cause artificial telomere shortening accelerate aging, but exercise causes widespread telomere shortening but not accelerated aging. And constitutive telomerase expression does not mean that cells are immortal, for example mice have constitutive telomerase expression in every cell. I believe the more plausible advantage to somatic cells not expressing telomerase is reduced transformative capacity because pre-cancers must first find a way to express telomerase.

I am still a little unclear about your question though, if it is how to we increase telomeres between generations, I guess that is explained, or is it  how we don't age as a population (a great question) due to constant mutations accumulation in germline cells?

Yes ! the second question is exactly what I tried to ask. Should I open a new question, asking "how we don't age as a population, due to constant mutations accumulation in germline cells ?"

Possible duplicate of How are new people created from the DNA of an aged person. i.e. Why are we young?


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What is the difference between an alpha subunit and a non-alpha subunit in ACh receptors?
When reading about ACh receptors, it is frequently the case that a protein is described as (alpha) or (non-alpha).  However, I haven't really been able to find out what that means.  What is the difference, and why would it matter if a subunit is alpha or not?


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When consuming carbohydrates and fats together, why are the fats caloric?
If I understand things, and I most likely don't: mammals primarily use carbohydrates to produce metabolic energy when there are sufficient carbohydrates to do so.  The use of fats for fuel requires the organism to break down the fat into constituent parts and from there produce either glucose (right?) or ketone bodies.  Presuming that the organism is not in ketosis, it seems that its body would preferentially use carbohydrates for fuel.
This is where my confusion comes in: why would the mammal's body use fats for fuel if its diet contain sufficient carbohydrates?  The real underlying layman's question is: why is that when I eat fat, I have to count those calories, if my body preferentially uses carbohydrates for fuel?

The only way you wouldn't have to count calories from fat is if your digestive system wouldn't absorb them. Fat might not be used immediately as metabolic fuel but it will still be stored as adipose tissue in your body.

So you're saying that the fats are presumably broken into their constituent parts and will be stored as fat tissue if I'm in a caloric surplus, yes?  If so, then to change the question slightly, when I consume a deficit of carbohydrates compared to my base metabolic requirements, and consume the rest as fat (for simplicity), does the fat get turned into adipose tissue and then to fuel, or is it converted directly?

Yes, fat is not turned directly into energy and it is stored first before its usage. If you undergo a carbohydrate deficit you would first make use of your glycogen stored in the liver and muscles before proceeding to use fat for fuel via beta oxidation. I can try to provide a more detailed answer once I get off work later.

@MikeKatz45, it seems that now the question is getting clear and you seem to be able to make an answer. If not an excessive effort for you, I'd love to read a simple explanation about how carbs and fats are consumed at the same time are used for current metabolic needs. Mainly how fats are converted into energy.

To expand on my comments:
Just like you mentioned in your question, carbohydrates (mostly glucose) is used as the primary source of energy when available to satisfy metabolic needs in human cells, however lipids and even proteins will be used if required, in order to produce energy. Since all these biomolecules (carbs, lipids and proteins) can actually be used to sustain the metabolic activity of cells, that means all of them store energy to a greater or lesser extent (which we can quantify in a practical way as food calories). Other things that we eat or drink such as vitamins, cofactors, water, etc. are not accounted for in the calorie count because they can't be broken down to produce energy for metabolism.
Dietary carbohydrates are easily digested into smaller blocks (mostly glucose) and absorbed directly into the bloodstream, afterwards glucose is taken rapidly from the bloodstream by human cells and processed via glycolysis and lactic acid fermentation or the citric acid cycle (all these are metabolic pathways for glucose in humans). Each gram consumed of carbs yields approximately 4 calories of energy.
Lipids on the other hand undergo a more complex process of usage after their slower digestion compared to carbs since after their absorption they have to be transported in special molecules across the lymph, then into the bloodstream and then they can be taken by various kinds of cells. Considering just this, we can start seeing why lipids aren't a fast source of energy (they take long to be available as potential energy sources). Furthermore, the main destination of dietary lipids is the adipose tissue which constitutes a special tissue in which fatty acids can be stored for latter usage. Fatty acids not being used immediately to provide metabolic energy doesn't mean they lose their stored energy (doesn't mean they have no caloric intake value), its just "quiescent" for when its needed (when exercising or when fasting for example).
Each gram of consumed fat yields approximately 9 calories of energy, this quantity is higher compared to that of glucose because the metabolic pathway that breaks down fatty acids (beta-oxidation) in combination with the citric acid cycle produces more metabolic energy (ATP) compared to glycolysis in combination with the same citric acid cycle. However such amounts of energy are not usually required in rest.
It is important to mention that glucose can also be stored in the form of glycogen or even fat since it will be converted to these molecules if there is more glucose available compared to what the cell needs in a given moment. This glucose converted to glycogen or fat also has to be accounted for in the calorie count because its still a potential energy source (just not used right now).
References:
Dietary Carbohydrates - National Agricultural Library
Dietary Lipids - National Agricultural Library
Insights into digestion and absorption of major nutrients in humans - Goodman, B. E.
Food calories per gram of biomolecule - National Agricultural Library

I'm tempted to suggest you to copy-paste the first two paragraphs from p. 430 from your 2nd link https://www.nap.edu/read/10490/chapter/10#430 , which clearly explain how fats are metabolized and why are metabolized after carbs.


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What does C. Elegans sense when touched?
I'm reading up on C. Elegans' touch responses.  Once touched, what is it that the neurons are sensing, specifically?  Presumably, touch deforms the body cells, and that deformation is sensed by the sensory neurons. Is that correct?  Alternately, are the neurons themselves directly stimulated due to the organism's small size? (Or am I way off?)

In short, you are correct. You touch the skin, and that compresses mechanoreceptors, which then generate a cascading neuronal response.
As far as the actual neurons, it really depends on the type of touch. For example, a well characterized type is gentle mechanical stimuli, which can involve ALM, AVM, PLMs, and PVM, depending on the response (Will Schafer's review doi:  10.1007/s00424-014-1574-3).
Those gentle touch receptors (TRNs) are in the hypodermis, and they have specialized mechanotransduction (MeT) channels along their neurites. It's the altering of those channels that causes receptor activation and the whole downstream behavioral response (summarized from the scientific reports paper below).
So, in summary: mechanoreceptor neurons are activated, and those produce a response. By "response" I mean that those mechanoreceptor neurons activate some interneuron pathways, which in turn activate motor neurons, which make the worm do stuff.

There are many other mechanosensation mechanisms, and WormBook is the place to see a ~comprehensive review of those.

The actual mechanical mechanism/way that MeT channels are activated is a great enough question that a recent paper was published in Scientific Reports to address it. That paper is DOI:10.1038/s41598-017-12190-0 (Elmi et al. Determining the biomechanics of touch sensation in C elegans).
They introduce the paper reiterating what I summarized above.

[...] touch sensation can be considered as a chain of events initiated
  by the spatiotemporal distribution of mechanical loads applied to the
  skin, which result in stresses that deform the skin’s surface,
  sub-layers and underlying mechanoreceptors. In response to the
  transmitted mechanical energy, the mechanoreceptors activate a
  neuronal signaling network that encodes the physical contact as
  information which we perceive as ‘touch’.

Elmi et al. set up a clever assay to look at how the worm's body changes. The body is pretty elastic (up to 16 micrometers) and there's some imperfect skin displacement because the body isn't perfectly cylindrical.
They used that data to build a preliminary model of the different layers of a worm body, and then they validated and tuned the model. It's a cool paper (with some math/physics, which from your profile it looks like you might appreciate).


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Fauna in deep great lakes
A significant amount of research has gone into the fauna of the deep oceans, but not so much that I can find on the deep great lakes (specifically the North American Great Lakes).  I'm interested in seeing pictures and learning more about the types of fauna in these lakes.  Can anyone provide a reference to get me going?

Contrary to oceans, deep lakes are always isolated from other deep lakes by land. Therefore, one might expect different fauna in every lake, with possibly a lot of endemic species. So it may be hard to study deep lakes in general.
The ancient and deep lake Ohrid, in the former yugoslav republic of Macedonia, has been researched relatively well. Here's a reference which will get you started. Or search "lake ohrid fauna".


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Where can I get my exomes sequenced?
I am a private individual and I want my exomes sequenced, I don't know of any place that will keep my data confidential as I read reports of companies sharing this data with insurance companies. I tried looking into a number of university research centers but none of them sequence DNA of private individuals. Does anybody know of any university that does WES of individuals or a place which can keep my information confidential? Many thanks in advance for your replies!

There are private companies that sequence DNA; you have to pay for it. They would have legal documents in place to maintain the confidentiality of the data. Or go to your nearest university/research institute and offer to provide samples in exchange for some information (that you'll not disclose until they allow you to). That said, your question is off-topic because it is not about a biological concept.

Most companies will genotype a number of SNPs but won't do full exome sequencing. Is there any reason you'd want your exome sequenced? With SNP association studies we have, one can already tell quite a bit about health related questions. 23andMe for example does a good job on this matter.

May I ask why you want your exome sequenced? Depending on what information you'd like that may or may not be the best approach.

I will be doing my own whole genome sequencing soon. The best reputable company I've found is Veritas. For 999 dollars and at a pretty decent depth (30+ reads).  They will produce a canned report of diseases and traits similar to cheaper alternatives, but also for another $100 will provide you a complete Variant File.
My understanding is that they will only use your data after anonymization for scientific endeavors, but I still need to finish reading the fine print. See here under privacy.  Good luck!
p.s. I also would skip exome and go with WGS since the price has come down. More and more diseases and traits are being linked to variation in intergenic regions of DNA.

The two companies you are most likely looking for that perform DTC whole exome sequencing are Genos Research and Full Genomes Corporation. Both companies make a Promethease compatible file format and provide a BAM file.
Full Genomes Corporation provides full genome sequencing at various depths, exome sequencing, genome depth ancestry service, and BAM file interpretation. They don't have the most user friendly service, but I'm told they aren't too hard to work with either. I didn't see anything in their privacy policy to suggest they are sharing your data to research.
https://www.fullgenomes.com/
Genos Research is a small company that sends out your sample to be sequenced. After 9 weeks they provide a variant report, BAM file, a VCF file, and a file formatted specifically for Promethease. They don't share your information. Instead they present to you a list of research projects they hope you will volunteer your data in exchange for money. https://genos.co/
Another option you have is the Personal Genome Project. Their goal is to establish a public database of genomes and medical records. This is one were if you don't mind the privacy risk they will sequence your genome as they have funding to do so. It might take them some time to get around to your samples. They also want your medical records and other information.
Personal Genome Project is deidentified. So a person can't just google to see if someone is a member of the PGP. But it is possible to take the genetics and demographics information and search for an owner name in public databases. It is not hard to prevent such searches by making small alterations to your date of birth, broaden your area of residence, and keep your data out of DNA ancestry databases. On the other hand some people are proud to release their identity and information to the public.
http://personalgenomes.org/
Veritas Genetics. They only provide full genomes, and clinical products. My understanding is you will need your own doctor to approve the test, whereas Genos Research provides it on staff. For 999 dollars they will provide the same information that Full Genomes Corporation if you buy their full genome product. Their VCF file isn't fully compatible to Promethease, so it is of limited use on third party tools. You could hire Full Genomes Corporation to generate such a file if you wish. You have the option of volunteering your data for research. I guess they donate your information to the Personal Genome Project if you agree. They can also for an extra fee perform a clinical evaluation of specific genes.
https://www.veritasgenetics.com/mygenome
These is also Gene By Gene. They do mostly clinical evaluation and research. But they are user friendly to the person that wants to spend, in my opinion, too much to get their exome or genome sequenced. They are the company behind FamilyTreeDNA. https://www.genebygene.com/pages/research
For those whom don't know, Promethease (https://www.promethease.com/) is a third party tool for generating a health report using a genetics test and the SNPedia wiki. It was meant to be free, but since it involves heavy amounts of server usage they charge a small fee to cover the cost of service.


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Why does cell differentiation start with the morula?
I suppose that cell differentation has to start by some external symmetry breaking. The first time there are two different types of cells is the morula with roughly 16 cells: there are some 12-15 cells forming the surface of the morula and some 1-4 cells in the interior of the morula. These are exposed to physically/chemically different local environments which might be the initial triggers of cell differentiation.

(source)
Questions:

Is this kind of argument/picture correct?
What are the significant differences in the environments of the outer and the inner blastomeres of the morula that trigger cell differentiation - and how do they do?

(Partial response) You're actually correct that inner vs. outer position is a differentiator, but there's still controversy whether position is a cause or whether differentiation actually happens sooner.

For a long time it has been believed that cells are identical within this ball at least until they take up distinct inside and outside positions, but is this true? A number of studies [2, 3, 6, 7, 8, 9] over the last 10 years involving a variety of markers such as oil-drops, dyes, fluorescent beads and proteins, together has challenged this view. These studies indicated that cells start to develop their identity earlier than expected, before taking inside or outside positions and, importantly, that these differences between cells are significant, as they bias cell fate [2, 3, 6, 7, 8, 9]. This view has not been universally held, however, because differences between the cells were not detected by other groups and so the view that cell fate choice is random was maintained [10, 11, 12]. It was also proposed that the bias in cell fate might simply result from the shape of the zona pellucida surrounding the embryo until implantation [13], an interpretation that has itself been questioned [14]. The random (stochastic) view of development became popular as it seemed to fit more comfortably with the experiments showing that early embryo cells are plastic and can adopt different fates upon transplantation.
The new contribution from Kevin Eggan’s group [1] now further challenges the view that early mouse development is stochastic.

And from a slightly more recent paper:

Drosophila has been found to have a pre-pattern in oocytes and zygotes. Several molecules that act as maternal determinants of the future body axis (for example, bicoid mRNA) are thus localized asymmetrically in both oocytes and fertilized embryos of Drosophila [6]. No such molecule has been identified in the mouse oocyte or embryo, although certain molecular and structural asymmetries have been described in unfertilized mouse oocytes. For example, Par4 protein is asymmetrically localized in mouse oocytes [7], but whether this protein is unevenly distributed among blastomeres after fertilization remains unknown. In addition, transcriptome asymmetry in terms of mRNA regionalization within mouse oocytes and zygotes has been identified, but no such asymmetry was detected between blastomeres within 2- or 3-cell-stage embryos [8]. However, several recent studies suggest molecular differences exist between blastomeres of the mouse embryo as early as the 4-cell stage. These molecular heterogeneities include the level of H3R17me2 and H3R26me2 (dimethylation of histone H3 at arginines 17 and 26, respectively) [9] and the level of Cdx2 expression [10].

Wikipedia also mentions this fact about Drosophila, so for insects at least it seems uncontroversial.

But isn't it received opinion that the first approx. 16 blastomeres are identical? What would "sooner" mean?

@HansStricker: I've added a quote from the paper.

Does this make my question pointless? I guess not, at least not necessarily. It might be the case that "differentiation by inner/outer position" still takes place (maybe modulated by some "pre-differentiation" before)?

One interesting question might be: If the 16 cells of the morula are already of slightly different types: Is there a correlation between inner/outer position and type, i.e. do the cells of the one type tend to be "inner", and the cells of the other type tend to be "outer" blastomeres. Has this been investigated, or doesn't it matter?

Finally: Isn't it a matter of fact, that the outer cells of the morula specialize into trophoblasts while the inner cells specialize into the embryoblasts? And that they do it for "positional reasons"? Internally, the embryoblasts may already be pre-specialized, triggered by random asymmetries of inner structure/distribution of proteins.


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Do hairs in the ear respond to things like shampoo?
Shampoo and conditioning products make claims to be the end all be all in hair care. I doubt that they are so advanced "growth formula/anti-breakage/oily treatment". Have any of the claims been shown to be valid? Assuming a positive response do they have application for restoring the hairs used for hearing?

You are mixing up hair cells and hair. Hair cells in the cochlea (wiki) have tiny stereocilia (subcellular organelles) that sense vibrations approaching the atomic scale. These are then translated in hyperpolarizing or depolarizing currents that drive the spiral ganglion cells of the auditory nerve. The 'hairs' on the hair cells will not readily benefit from shampoo I'm afraid. If you should want to test it, the shampoo should be intracochlearly administered in the scala media of the cochlea - so even if shampoo is beneficial it would be hard to utilize it without surgical intervention.

thanks for clearing up my misunderstanding i have had that for a while now


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Shannon diversity index: Pi relates to all found species, or number of species by site?
I am trying to dig into Shannon's species diversity index to compare the species diversity between different sites. For this, I need to calculate the 'relative abundance of species within the community'[details here][1]. What I do not understand is if this relative abundance relates to all species in a sample, or all found species?
In my example, I have in site1 6 species: a, b, c, d, e, f and in site2 two species: g, h. Should I calculate the proportion by species by site relative to 6 and 2, or to 8 (6+2, as species do not overlap between the sites? This is dummy example, likely species will reoccur).

If calculated by total number of species (8): Shannon H = 1.11 and 0.820,
if calculated by total number of species by site (6 & 2): Shannon H = 1.29 and 1.26.

I wonder which one is correct? The general trend is the same (site1 is more diverse then site2) but differences between indices seems quite large.
Dummy example to calculate Shannon's H step by step with dplyr. The commented out mutate allows to change if distinct number of species and their sum will by calculated by site or by total.
# Create dataframe with two sites and 6 and 2 different species. Area indicate abundance of species.
d<- data.frame(site = c(rep("s1",6),  rep("s2", 4)),
               species = c(letters[1:6], letters[5:8]),
               area = c(59,12,11,10,5,3,
                        10,5,21,20))

# Calculate sum of the area
# calculate distinct number of species, vary if the distinct area calculates by sum or by total??
d %>%
  mutate(species_n   = n_distinct(species)) %>%   # !! should 'mutate' by placed before the grouping variable or after?
  mutate(species_sum = sum(area)) %>%
  group_by(site) %>%
 #mutate(species_n   = n_distinct(species)) %>%
 #mutate(species_sum = sum(area)) %>%
  mutate(spec_pi     = area/species_sum) %>%
  mutate(pi_ln       = abs(log(spec_pi))) %>%
  mutate(sp_shannon  = spec_pi*pi_ln ) %>%
  mutate(shannon_comun = sum(sp_shannon))

I am trying to dig into Shannon's species diversity index to compare the species diversity between different sites

Shannon's diversity index is a measure of alpha diversity, or diversity within a community. If you are considering each site a different community (which is sounds like you are), then you would calculate Shannon diversity for each site separately, without consideration of the other sites.

What I do not understand is if this relative abundance relates to all species in a sample, or all found species?

Relative abundance is not a function of the number of species found, but the total number of observations collected (similar to sampling effort) at a given site. So, if you made 100 total observations at a site and 10 of those belonged to Species X, the relative (proportional) abundance of Species X is (10 / 100) or 0.1, regardless of the total number of different species present, and regardless of any observations from other sites.
I can't comment on your code, because I don't do tidy-verse. I guess I'm (apparently) old school and still use Vegan and LabDSV for community analysis (I may be biased since I learned community ecology from the author of the LabDSV package). But in general, for any measure of alpha-diversity, each community gets it's own value, and you would not consider any observations from other sites in that calculation, regardless of whether there is species overlap between communities.
For a more direct comparison of diversity between sites, you would use a beta-diversity index like Bray-Curtis dissimilarity, which compares each community to every other community in your analysis.


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Which Darwin book (and today edition) is illustrated by his own drawings?
I am interested in buying Charles Darwin books and mostly drawings (nowadays editions, I am not a collector). Please, can you advise in which book and which edition I can find the most of his drawings? I found some books as On the Origin of Species ad the Geology of The Voyage of The Beagle but I am not sure if there are his drawings too. I am a student so I couldn't spend too much money on it, but I was interested in his texts and drawings, supporting each other in one book/journal/publication. Thank you !

I believe that there is only one drawing in the first edition of On the Origin of Species, and it is Darwin's.  Any good edition such as the fascimile edition with an introduction by Ernst Mayr, will include this drawing.  I'm not sure about other editions of the Origin or other books of Darwin's.  However, maybe you don't need to buy anything.  Darwin Online is a wonderful collection that includes many (all?) of Darwin's writings over the years, including images of many of them; the drawings are no doubt included.
It's possible that the History of Science and Mathematics StackExchange site would be a better place for this question.

Very good answer +1. I did not know about History_of_Science_and_Math.SE. Darwin Online is a nice resource as well.

Thank you @Mars, I neither didn't know about History of Science... thanks for the book link and  Darwin online, I also found this resource later. Thank you again ! :)


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What is the most recent well-attested common ancestor of chimpanzees and humans?
Humans and chimpanzees are related and thus have a most recent common ancestor. Of course pinning down this precise point is essentially impossible, so I'm interested in close ancestors of this most recent common ancestor. Also, I'd like to know things about it -- how it compares to common chimpanzees, bonobos, and humans in various ways -- so species known only from fragmentary evidence are less interesting to me. Ideally I'd ask for something with at least one near-complete skeleton and a separate (perhaps less complete) find, but as a non-expert I'd be happy to settle for whatever is considered to be well-attested.
So, what is the most recent well-attested common ancestor of chimpanzees and humans?

Two reasonably close relatives of the most recent chimpanzee-human ancestor (CHA) are Sahelanthropus tchadensis and Orrorin tugenensis, but both are poorly attested.
One better candidate is Ardipithecus ramidus, which has a fairly-complete skeleton ("Ardi") among other fossils. It's a bit young (4.4 Ma), perhaps, to be a CHA but should be a close relative.
Another reasonable candidate is Oreopithecus bambolii. It is very well-attested. The trouble is that no one seems to know how it's related to humans; 'best guess' is that it's not actually an ancestor but a sister taxon.
(I'm not an evolutionary biologist, nor even a scientist, but I thought I'd leave what information I collected here as there is no better answer at this time.)

Welcome to Biology.SE. I know absolutely nothing about CHA! Can you please include your references. There is no problem if you collected these informations in none peer-reviewed articles, but still it would be good to show your references.


text:
How were (many) dinosaurs' brains so small?
Brain size (or its proxy, encephalization quotient) usually varies allometrically with mass -- larger creatures need larger brains to control their larger bodies, apparently.
Dinosaurs are popularly known as small-brained. While this certainly doesn't hold in general -- theropods and especially birds were particularly intelligent -- but sauropods and thyreophorans (ankylosaurs and stegosaurs) seem to have preposterously small brains. How were they able to control their large bodies with such small brains? Are there modern animals with similar proportional brain size, and if so does that give any clues as to how these dinosaurs functioned?

I would like to know why a small brain cannot control a big body, if that is the case. A small brain would be so much less metabolically expensive. You'd think that there would be a strong selection pressure to have the smallest brain that could do the job. So a lion should have the same size brain as a house cat, and so on.

I don't think there is a concrete answer, because we don't really know the minimum size of a vertebrate brain in relation to body size. Many vertebrates, including many fish, get along fine with tiny brains in large bodies.
For many decades, scientists speculated for this very reason of small brain size, that dinosaurs seemed to have an extra brain, or ganglion, at the hip. Especially sauropods and thyreophorans appear to have had a widening of the spinal cord cavity around the sacral area suggesting this possibility. This pelvic ganglion or "hip brain" was then presumed to be responsible for running the hind legs and tails. However, this idea has not gained any further evidence or traction in the scientific community and is generally dismissed.

Interesting theory. Can you please add some references to your answer?

FWIW I've heard the plausible conjecture that the lower limit of brain mass is roughly the mass of the spinal cord (i.e., the brain + cord is at least roughly twice the cord).

A good modern point of comparison in modern animals is the koala. The giant pandas are likely headed in the same direction, too. It seems that the lack of a need to process complex sensory information to acquire food or avoid predators, the nutritional inefficiency of the diet, and the fact that the number of systems isn't increasing, just their size, is also relevant. Do we have coprolites from these dinos to see how well digested their food was?

Well, as I said, there is not really any scientific traction for the "pelvic ganglion" theory anymore, so there is not much documentation to find other than some speculative papers. Dinosaurs are now generally presumed to be simply small-brained vertebrates for the most part.


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Effect of flask position in shaking incubator affects growth kinetics
During some cultivation experiments for my bachelor thesis I noticed that in liquid culture my bacteria (E. coli) grew differently, according to the position in the shaking incubator.
Because the goal was just to induce protein expression at a given OD, I altered the position of the flasks in the shaker, so the cultures were at a similar OD and I could add the IPTG to all of them at the same time.
Now I wonder if someone else noticed this phenomenon (Literature to cite would be great, I couldn't find anything until now) or if I did something wrong. Maybe it's also known and ignored for longer times?
The cultures more in the back of the incubator grew faster, so I think it's because of temperature alterations when opening the incubator to draw samples for growth kinetics, but I'm not sure about this at the moment.
Thank you for helping me :-)

Is it possible, that there are different amounts of shear stress involved in different flasks? Cells can die due to shear stress, and E. coli is possibly more sensitive to shear stress than a gram positive bacteria.

No offense, but how reliably are your OD measurements? I noticed that there can be some difference, depending on where in the fask you take a sample. Also when you stop the incubator to take samples, cells start to sediment. This can influence the measurement for the later flasks from which you took samples.


text:
Limits of phase-locking
In Rieke et al, Spikes, p. 31, I found this instructive picture showing and explaining phase-locking.

I take it for granted, that phase-locking is possible only upto a maximal stimulus frequency (well below the maximal firing rate of the neuron). Beyond this, phase-locking must break down: the neuron cannot follow the stimulus anymore.
My questions are:

Does this maximal frequency count as a characteristic of a neuron (type of neuron), and what is its name?
Are there typical values of this frequency, e.g. as a fraction of the maximal firing rate of the neuron?
Does the breakdown of phase-locking typically occur suddenly (as a phase transition) or gradually?
What happens beyond? Does the neuron follow a virtual stimulus of 1/n of the original frequency (which would be in phase with the original stimulus)? Or does chaotic firing take over?

see https://biology.stackexchange.com/a/67843/460

My question was about single neurons, not assemblies. Phase locking of assemblies is a different case. (Maybe the question about single neurons is not so interesting, because it's only assemblies that count - but nevertheless I dare to ask it.)

Phase-locking can occur at very high frequencies at the early stages of a sensory system. In addition to the answer provided in your previous question, let me offer an illustrative example from single neurons in the somatosensory system.
Deschênes, Timofeeva and Lavallée (2003), have stimulated the whiskers of an anesthetized rat with a sinusoidal stimulus while recording extracellularly in the main feed-forward brainstem nucleus of this system (Pr5). Practically all neurons responded with at least one action potential to all cycles of a stimulus up to a stimulation frequency of $300Hz$. Neurons always fired an action potential at first cycle up to the maximum frequency tested, $400Hz$, and ~$30\%$ fewer spikes upon subsequent stimulation (questions 2 and 3). The extend of coupling to the stimulation frequency depended on the amplitude, velocity, and direction of the stimulation.

 Encoding of high-frequency whisker deflections by primary afferent axons
(Figure 6 from Deschênes, Timofeeva and Lavallée (2003))
Given the physical limitations of the stimulation device (piezoelectric element) it was not possible to directly stimulate at higher frequencies. However, the authors took advantage of the harmonic oscillations of the stimulator to look at the phase-coupling of spiking to higher frequencies of stimulations. Remarkably, units that were sensitive to small displacements of the whisker were able to follow the harmonic oscillations of the stimulator up to at least $1kHz$ (see Figure above).

What happens beyond? Does the neuron follow a virtual stimulus of 1/n of the original frequency (which would be in phase with the original stimulus)? Or does chaotic firing take over?

It is important to note that $1kHz$ is very close to the refractory period of most neurons, thus I would predict that this could be the only limiting factor in these cells. Of course, different types of cells will show different responses to high-frequency stimulation based on their intrinsic properties, the degree of short-term synaptic plasticity of the activated synapses, and/or the filtering of the incoming inputs by upstream circuits.

Does this maximal frequency count as a characteristic of a neuron (type of neuron), and what is its name?

I am not aware of something like this. Stimulation at such high frequencies is not typically used to classify neurons as it is rather non-physiological for neurons beyond those receiving direct inputs from the sensory receptors. Most often researchers apply a DC pulse and observe the degree of spiking adaptation.

Reference
Deschênes, M., Timofeeva, E., & Lavallée, P. (2003). The relay of high-frequency sensory signals in the Whisker-to-barreloid pathway. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 23(17), 6778–87. https://doi.org/23/17/6778


text:
Are there axon branches that go up to cortex layer 1 and spread there?
I found the following pictures of axon trees:

source

source (axons are red)
but didn't find a concise answer to the following question:

Are there axon branches that go up to cortex layer 1 and spread there?
  (This is not indicated in the pictures above, maybe because there are no.)

Short answer: It depends on the layer.
Axons of some neurons in deep layers will project back to L1 (Brecht et al. 2003a, Oberlaender et al. 2011), but neurons of superficial layers extend their axons laterally (Brecht et al. 2003b).
Besides focusing on specific pyramidal cell sub-classes it's worth considering what proportion of inputs to L1 comes from intracolumnar or extracolumnar inputs. From the wikipedia article on the cerebral cortex:

Layer I, the molecular layer, contains few scattered neurons and consists mainly of extensions of apical dendritic tufts of pyramidal neurons and horizontally oriented axons, as well as glial cells. [...] Inputs to the apical tufts are thought to be crucial for the ‘‘feedback interactions in the cerebral cortex involved in associative learning and attention. While it was once thought that the input to layer I came from the cortex itself, it is now realized that layer I across the cerebral cortex mantle receives substantial input from ‘‘matrix or M-type thalamus cells (in contrast to ‘‘core or C-type that go to layer IV).

Most of the inputs to layer 1 (L1) are indeed thought to come from the "non-specific" thalamus and other cortical areas, such as the primary motor cortex in the case of primary sensory areas.[citation needed] I am only aware of circumstantial evidence for the relative prevalence of thalamic inputs in L1. According to staining for different vesicular transporters of glutamate (type I is thought to label mostly cortical neurons in adult animals, type II subcortical), about half of the input to L1 is subcortical (Kubota et al. 2007). It's worth noting that the slender-tufted neurons described by Oberlaender et al. (2011) to project heavily in L1 are considered to be the main targets of the "non-specific" thalamus in the cortex (Brecht et al. 2003a). The extracolumnar origin of cortical inputs to L1 matches with the overall trend observed accross layers for the majority of inputs to come outside the cortical column (Stepanyants et al. 2009).

Depends on the layer the pyramidal cell lives in?

Anyway a great and concise answer!

@HansStricker Correct.

Having learned that there are such axons resp. branches of axons, and assuming that they play a functional role (and are not just outliers): How far do you think do they spread in layer 1 (typically, roughly, on average)?

I didn't mean to imply that they are outliers, but rather a sub-class of cellls. I've updated the text to reflect that. If I understand you correctly, the answer is in Figure 3 from Oberlaender et al.

Figure 3 is hard to grok for me (at first sight). What does it tell me?

And no, I didn't want to suggest that you implied them being outliers. It was just for the case.

The average slender-tufted L5 pyramidal cell projects ~50 mm of axon in the superficial layers (L1-3) outside its principal column, in comparison with ~10 mm inside the column.

Just to add, cortico-cortical inputs to layer 1 originate from many areas (not just motor cortex), usually in a 'feed-back' pattern from 'higher' to lower-order cortex, and many of them travel quite some distance once there.


text:
How many synapses are there in the different target regions of a typical cortical pyramidal cell?
I found the following pictures of axon trees:

source

source (axons are red)
but didn't find a concise answer to the following question:

How many (in relative terms) branches terminate and how many axon
  terminals (synapses) are there in the different target regions of a
  typical cortical pyramidal cell, i.e.

same cortical layer
other cortical layers
same cortical column
other cortical columns
more distant cortical regions (e.g. in the same gyrus)
subcortical regions

I take it that you mean how many synapses are formed with a pyramidal neuron and $X$. Talking about branches doesn't make too much sense. You should know that there are 4-7 different types of cortical pyramidal cells, depending on how you count (e.g. Oberlaender et al. 2012 for the higher estimate). Every single presynaptic source you are asking about is going to have a different estimate for every different type of pyramidal neuron, and some of them are unknown. I'd say this is too broad.

You "just" say there is no typical pyramidal neuron? I know that

... but 4-7 is not such a big number one couldn't give a partial answer: for type X it is so-and-so, ... Should I rephrase my question? To which of the 4-7 types would you recommend to restrict my question?

I'd say we only have numbers for the number of synapses or the volume of axon that comes or goes inside or outside the column, with no estimates about specific neurons, but I really do hope that someone will prove me wrong.


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Species of this White Dove
I visited a bird enclosure close to where I live in Australia. The enclosure had several different species. The birds that stood out most were these doves sitting right along the fence railing, making a deep "Wo-wo-wo-woo" sound. That and also I thought they looked and sounded similar to Spotted Doves.

Does anyone know what the species of this birds may be?

if you still have any doubts or need any sort of clarification feel free to comment

I think this is a Barbary dove (or Ringneck dove). See this image (from the here):

More information can be found here and here. The second pages shows also images of different color variations.

I accepted @agha rehan abbas before, but only because I didn't see your answer. The Barbary Dove seems to have a white and brown wing tip, while the Collared Dove has solid colour for it's wingtip. The one I saw has the same type of pattern on it's wingtip.

it is symi bird and more over it is commonly called as collared dove its a resident of symi and would have brought to australia by other means

you can find a list off all the symi birds here


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Cross section of actin network in neurites
for a simulation I am developing I would like to know how the actin network in neurites is distributed.
Is actin confined to the periphery or is the whole neurite shaft containing actin with a rather constant density?
If you have any papers backing up the one or the other view don't hesitate to pass the link.
Thanks for answering.

does this help? (http://www.neuraldevelopment.com/content/pdf/1749-8104-6-27.pdf)

on first sight this paper only gives a 2D distribution of actin over the whole neuron or? I would like to know what you would see if you cut a neurite and subsequently look "into" the cross section. Is the actin only found on the outer part of the cross section or evenly distributed across the circle?

Just look at papers doing confocal microscopy/imaging of actin with z-stacking (z refers to the axis) since thats the main approach people use for 3D imaging and people also use delta vision microscope with z-stacking and deconvolution.

Actin is required for the neurite architecture and is present throughout the shaft (along the direction of the neurite process)
See these images.

                                        [Source]

                                             [Source]
These are not from research papers but the sources are trustworthy.

From those images I would not deduce that the neurite shaft has a substantial actin skeleton but rather a small amount of "misguided" filaments. Is that right?

Why would you assume some misguided filaments? The region indicated as meshwork is essential for the structure.

In the second picture actin and tubulin are labeled. I cannot see any actin along the shaft except of growth cone areas. So there is no substantial amount of actin concentrated along the shaft. Or?

OK I didnt understand what you meant by shaft. I thought you were referring to the filopodial region. Yes actin is not abundant in the axonal regions


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Typical firing patterns of neurons in the default mode network in resting state
Inspired by the Wikipedia article on the default mode network where I read:

Hans Berger, the inventor of the electroencephalogram, was the first
  to propose the idea that the brain is constantly busy. In a series of
  papers published in 1929 he showed that the electrical oscillations
  detected by his device do not cease even when the subject is at rest.

I came up with the following question:

Are there data available for typical firing patterns of single neurons
  (of a given type, in a given region or functional unit) in the
  default mode network in resting state  over some significant
  period of time, say a minute?

By "typical firing pattern" I mean:

the overall number of spikes (per minute)
the number of isolated spikes
the number and duration of tonic bursts
the number and duration of other firing patterns as proposed e.g. by Eugene Izhikevich
and the mean distances between them

Or are such data not available, maybe because they are too hard to gather or cannot be summarized in a sensible way.
I ask just to get an idea, and because I would like to know if - for example - the maximal, mean, or median number of spikes per minute has an order of magnitude of 10, 100, 1,000 or 10,000 - or even more?

The DMN is composed of many different cortical brain areas each containing many cell types; I think it would be difficult to define anything as 'typical' among them. There are also no hard borders to the DMN; you could define some for a given purpose, but it would be hard to find agreement.

Both classifying neurons into proper subtypes and recording firing patterns of neurons (in their natural environment) are not very easy tasks. This review (not sure if freely available) is mostly about the classification but also contains a good introduction & some examples on different electro-physiology.

@Nicolai, thanks for the link, unfortunately not freely available. (What to do?)