How do I know which alleles the parents have? I have the following assignment where I am to look at the "tree" (not sure the english word) and assign whether or not they can be autosomal dominant or recessive as well whether they can be X-linked recessive.

My way to try and complete this assignment is by drawing a punnet's square but I quickly run into some confusion. When I draw my square, I know that is I'm checking for autosomal dominant, then I would draw the mother as A'a, the A' denoting the sick dominant allele. What I'm not sure is this: Can't I also draw her as A'A'? That would also mean she would be autosomal dominant but with 2 sick alleles. What about the father? Do I draw him as Aa, aa or AA? I'm a bit confused here!

Let's go step my step here.

Going by your notation I'll call the square as Male and Circle as female.
So from this information I can confidently say that you disease is not X linked dominant.

Why?

Because Females carry XX, that would mean to be X linked dominant she had to be X'X' for the disease allele to manifest it's phenotype. But if it were X'X, it would lead to a loss in fitness. And since the Male is normal and XY he does not carry the disease which tells us that the disease is definitely not X linked dominant.

Therefore in a cross of X'X' and XY you get individuals X'X and X'Y in the ratio 1:1

Coming to AD Autosomal Dominant may mean A'A' as the disease allele is present in homozygous condition. A heterozygous condition would lead to loss in fitness, not necessarily a disease.

A Father may be AA or AA'

so this cross would give you individuals

AA' for A'A' x AA
A'A A'A' for AA' x A'A'

so in this case you always get the disease in autosomal dominant, what remains is recessive.

AA or AA' Father x A'A' Mother

Products AA' for AA x A'A'
or AA' and A'A' for AA' x A'A'

which tells us that the disease is actually Autosomal recessive on the mother.

The father's genotype for the allele is AA or homozygous dominant

and the disease is autosomal recessive for the disease in the mother.


Oral allergy syndrom, continuation of continuous consumption of allergen Wikipedia states on its page that

  In addition, patients are advised to avoid the triggering foods, particularly nuts.

And same thing goes for webmd.com

  The basic rule: If a food makes you uncomfortable, don’t eat it.

So two very related questions flow from this:

Does continuous consumption cause such an allergic reaction to become stronger?
And if that is the case, by what mechanisms does that happen?

When you ingest an allergen for the first time, your body produces many of an antibody called IgE with specificity toward that allergen. These IgE antibodies bind to mast cells, and basophils. When you encounter more allergen, they bind to these IgE on the surface of the mast cells and basophils, causing them to release a host of chemicals like histamine. Massive amount of histamine are the cause of anaphylaxis, so when more allergen interacts with more and more IgE, the situation worsens. The following figure is a detailed mechanism,

Source

We can also see, though, that histamine released is a function of total allergen, and eventually reaches a maximum regardless of allergen present,

Source
Here they're showing histamine release vs allergen concentration while investigating allergic rhinitis.


Why isn't Fluorine, or Neon, the final electron acceptor in cellular respiration? I'm a Chemistry student learning about periodic trends. I know that in (many organisms') cellular respiration, oxygen serves as the final electron acceptor due to its high electronegativity.

However, applying the periodic trends, fluorine is more electronegative than oxygen, and the noble gas neon even more so than fluorine. Why aren't either of these the final electron acceptor? I know that in some organisms, the final electron acceptor is sulfur. But I've never heard of it being fluorine or neon. Why?

One of the main reasons that modern(!) biology uses oxygen as an electron acceptor is availability.

Around 2.45 billion years ago, oxygen (O$_2$) started being built up in the atmosphere (which actually killed off a lot of the lifeforms/bacteria at that point). Since then, oxygen consuming lifeforms were able to establish themselves. Before that, most organisms probably used mainly (elemental) hydrogen as electron acceptors.

Apart from not really being available in the atmosphere, there are other reasons why fluorine or neon don't make for good biological electron acceptors:

While elemental fluorine (F$_2$) is indeed extremely electronegative, this makes it so reactive that it:
a) could not be controlled by biology [the reactivity of oxygen is why it killed so many bacteria in the first place] and
b) just does not occur (or at least remain in) in the elemental state in nature (there is no measurable F$_2$ in our atmosphere).
Neon (and other noble gases) are in theory also quite electronegative, actually so much so, that they never* occur without their electrons and therefore don't react at all.

*It's somehow possible to form noble-gas compounds, but it requires very specific chemical reaction conditions, that mostly occur under controlled man-made conditions (and are not good for biological life forms).


Is there a way to measure ATP usage in the brain similarly to fMRI? Is there a way to measure ATP usage in the brain (or anywhere else) similarly to how fMRI works (measuring changes in iron resonance in oxygenated/deoxygenated blood)? Is there some sort of similar signal that can be used for ATP?

I'm pretty sure this doesn't exist. If it did, that would be awesome.

The following is 100% pure speculation with nothing to back this up at all (as a disclaimer).

Phosphorus-31 (the stable isotope) is NMR active, which means that you could theoretically use an MRI machine to visualize phosphorus. A quick google search shows scientists attempting to use phosphorus MRI for visualizing bone structure.

I don't really know much about MRI, but I do know some about small molecule NMR, which is based on the same principles. This is a pretty cool paper showing phosphorus-31 NMR used to measure ATP synthesis.

Maybe in the distant future it could be possible to use phosphorus-31 MRI to visualize ATP/ADP ratios in various tissues, including the brain. But that would be some amazing sci-fi stuff.


What are the factors that control the speed of propagation of neuronal signals? If we consider an analogy between a wire and a neuron there may be some resemblance between the factors controlling the data flow rate. For example the increased width of wire leads to decreased resistance etc; similarly increasing or decreasing the thickness of myelin sheath may have an effect on the conductivity or data transfer between neurons.

Are there additional factors that can control the speed of nervous conduction?

The diameter of axons also makes a difference, the thicker the axon, the faster the rate of action potential conduction. This is seen in invertebrates, such as squid. Squid have giant axons (up to 2mm in diameter), which exhibit rapid conduction rates. See Wikipedia 'squid giant axon', in which it says up to 1mm, but I have measured 2mm myself. These are not found in mammals.

Original research on squid giant axon  was by Cole & Curtis (The Journal of general physiology, 1939). For more recent research see Hartline & Colman (Curr Biol. 2007 Jan 9;17(1):R29-35.).

Work by Hodgkin, Huxley and Katz (The Journal of physiology, 1952,  116(4): 424–448) using squid giant axons lead to the elucidation of the mechanism of action potential conduction and a Nobel prize. Academic summary here: http://jp.physoc.org/content/538/1/2.full

Wikipedia: see the Goldman equation (Goldman shared the Nobel Prize with Hodgkins and Katz). This is more frequently known as the Goldman-Hodgkin-Katz  equation in UK publications.


Does the DNA of a tadpole change after it becomes a frog? Does the DNA of a tadpole change after it becomes a frog? In other words what changes take place as a tadpole becomes a frog, and does this metamorphosis affect the DNA in any way?

I would appreciate your help. I am doing research for a book I'm in the process of writing. If you can refer me to research material, I would appreciate that also.

Your germline DNA remains the same no matter what you do in the growth process (The DNA of a child is the same as the DNA of the adult). What does change is the expression of the DNA (transcriptomic profile), other regulatory factors (Epigenetic modifications), alternative forms of the same DNA expressed differently (splice site variations and alternative promoters) things like that.

Your somatic DNA does undergo small changes, caused by (retro) transposons, and in a few cells, like the mature B and T cells, they contain only a small subset of a few essential genes (that give them their specificity to an antigen), and other small changes like that (credit: mdperry, see comments).


What biological systems are affected by Vitamin B6 (or B vitamins in general)? B vitamins and particularly the B6 vitamin appears to the one of the main ingredients in energy drinks.

There has been anecdotal evidence from people interested in dreaming that ingestion of vitamin B6 at night time changes the pattern of dreaming and is likely to produce "lucid" dreams.

From a biological standpoint, what is the effect of the B6 vitamin on the human body and brain? Do other animals require the same vitamin?

Are B vitamins in any way related to the circadian rhythm regulation within some organ systems? Does it speed up metabolism?

I would be grateful for any scholarly papers on the subject or keywords that I may look up myself.

Thank you!

The main effect, of vitamin B6, is neurological, becouse  moderate variations in the intracellular concentration of pyridoxal 5'-phosphate (PLP), the biologically active form of vitamin B6, can have pronounced modulatory effects on steroid-induced gene expression. So you cannot get the effect of stress hormones.

Also neurological damage has been reported on doses from excess of 500 mg/d. Check this papers http://www.ncbi.nlm.nih.gov/pubmed/2661220 and http://www.fasebj.org/content/8/3/343.short


The dominance variance on a single locus I was reading the book "Genetics and Analysis of Quantitative Traits", by Lynch and Walsh. I how the covariance between two individuals with IBD $\Theta$ gets divided into just the additive variance and dominance variance component, even in the simple $1$ locus case.

Here my understanding of the modelling (for the simple one allele case):

Given a genotypic value $G_{i,j}$ of mean $0$, $i,j \in \{0,1\}$ we find numbers $\alpha_0$ and $\alpha_1$ minimising the least squares of the following form $\mathbb{E}(G_{i,j}-\alpha_i-\alpha_j)^2$, where the expectation is over the population.

We next define the error terms in each case as $\delta_{i,j}=G_{i,j}-\alpha_i-\alpha_j$. From the properties, viewed as functions of the population $\alpha_i$ is independent of $\delta_{i,j}$, and both have
mean $0$.

The claim made in the book is that given two individuals, with IBD $\Theta$ and probability that the genotype is equal $\Delta$, the covariance of the genotypes $G_{i,j}$ and $G_{k,l}$ is given by,

$$\text{cov}(G_{i,j},G_{k,l}) = 2\Theta \sigma_A^2 +\Delta \sigma_D^2,$$

where $\sigma_A^2= \text{Var}(\alpha_i)$, and $\sigma_D^2 = \text{Var}(\delta_{i,j})$.

Expanding the LHS of the expression, showing that $\mathbb{E}[(\alpha_i +\alpha_j)(\alpha_k+\alpha_l)] =\Theta \sigma_A^2$ is quite easy. It also seems to follow from the  that the the terms $\mathbb{E}[(\alpha_i +\alpha_j)\delta_{k,l}]=0$ from independence of errors from the $\alpha$.

On analysing $\mathbb{E}[\delta_{i,j}\delta_{k,l}]$, we see that if both genotypes are equal, which occurs with probability $\Delta$, then this reduces to $\sigma_D^2$. This gives us a term $\Theta \sigma_D^2$. Further, if both $i,j$ and $k,l$ are not IBD then the covariance is $0$. However when one of the two alleles are IBD, then it is not clear to me that this the covariance will still be $0$.

The book seems to claim that unless both alleles are IBD,  $\delta_{i,j}$ and $\delta_{k,l}$ are independent. I do not see why this is the case. Am I missing anything here? I'd appreciate any help wrt this.

It looks like I could solve the question. My understanding is as follows.

Let $(X_1,Y_1)$, $(X_2,Y_2)$ (corresponds to $i,j$ and $k,l$ in the question) be the genotypes of two individuals
 at some location. We assume that neither individual
 is in-bred. In this case define,
 \begin{align*}
  \Delta_7&= \text{Pr}(\text{Both alleles $\{X_1,Y_1\}$ and $\{X_2, Y_2\}$ are IBD}),\\
  \Delta_8&= \text{Pr}(\text{Exactly one allele pair of the four pairs is  IBD}),\\
  \Delta_9&= \text{Pr}(\text{ No IBD between the two individuals}).
 \end{align*}
 $\Delta_7$, $\Delta_8$ and $\Delta_9$ are calculated from the pedigrees.
 For example, for non-twin siblings, $\Delta_7 = \frac{1}{4}$, $\Delta_8=\frac{1}{2}$,
 $\Delta_9 =\frac{1}{4}$.

We note that the IBD coefficient (also called kinship coefficient) $\Theta$ is
 \begin{align*}
  \Theta = \frac{1}{2} \Delta_7 + \frac{1}{4} \Delta_8.
 \end{align*}
 Also the fraternity coefficient, $\Delta =\Delta_7$.
Thus we have that the covariance between the genotypic
 value of two individuals is given by
 \begin{align*}
  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)] =& \Delta_7 \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{both IBD}] + \\
  &\Delta_8 \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{one IBD}] + \Delta_9  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{no IBD}].
 \end{align*}

Further note that,
 \begin{align*}
  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{both IBD}] &= \mathbb{E}[G^2(X_1,Y_1)],\\
  &= \sigma_A^2 +\sigma_D^2.
 \end{align*}

\begin{align*}
  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{no IBD}] &= \mathbb{E}[G(X_1,Y_1)] \mathbb{E}[G(X_2,Y_2)],\\
  &=0.
 \end{align*}

\begin{align*}
  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)| \text{one IBD}] &= \mathbb{E}[(\alpha(X)+\alpha(Y_1)+\delta(X,Y_1))(\alpha(X)+\alpha(Y_2)+\delta(X,Y_2))],\\
  &=\mathbb{E}[\alpha^2(X)] + 2 \mathbb{E}(\alpha(X) \delta(X,Y_1)) + \mathbb{E} [\delta(X,Y_1)\delta(X,Y_2)],\\
  &= \frac{1}{2} \sigma_A^2 + 2 \mathbb{E} [ \alpha(X) \mathbb{E}[\delta(X,Y_1) | X] ] +  \mathbb{E} [\mathbb{E}[\delta(X,Y_1)|X]\mathbb{E}[\delta(X,Y_2)|X]],\\
  &= \frac{1}{2} \sigma_A^2.
 \end{align*}

Thus we have that,
 \begin{align*}
  \mathbb{E}[G(X_1,Y_1)G(X_2,Y_2)] =& \left(\frac{1}{2}\Delta_7 + \frac{1}{4}\Delta_8\right) 2 \sigma_A^2 + \Delta_7 \sigma_D^2,\\
  &= 2\Theta \sigma_A^2 + \Delta \sigma_D^2,
 \end{align*}
 which is as claimed.


How do ascending neural pathways filter unimportant information? In school they told us one of the functions of the ascending neural pathways is to filter unimportant information. But the neural signal I know, is only a chemical-electrical chain of neurons. Is this filtering of unimportant information reminiscent of the gradual attenuation of the signal during the travel from the periphery all the way up to the brain? If so, how does that work?

A neuron cannot know the importance of a signal in any applied sense, that is, it can't know the difference between one triggered by a feather or one by a hammer... on an individual basis.

A single neuron can however accumulate information in a number of ways, either by requiring multiple incoming triggers (filtering out localised signals, i.e. from a single connected neuron) or they can require repeated triggers (filtering out weak/freak/accidental signals from a connected neurons). This is called summation:

These filtering events occur at the synapses, so how would a neuron filter a signal as it was passing through it? As far as I know, it doesn't!

NOTE:
As noted by @WSYWYG, LTP and LTD are also important, they stand for Long Term Potentiation and Depression. These are names given to the long term increase or decrease in sensitivity of a synapse, that is a neuron can become more or less likely to pass on a signal over long periods of time due to the pattern or frequency of signals it receives. Googling the terms will lead you to a wealth of vastly more detailed information on these topics.

EDIT:
As an addendum, your body can inhibit neurons selectively, so as a wild stab in the dark, it may be interesting to see if ignoring a sensation from part of your body is the direct result of of external inhibiting (filtering) of signals incoming from ascending neural pathways... but don't trust me on that!


How is the reflectance spectrum of solids measured? I was reading this question about autumn leaf colors. One of the answers refers to an article by Archetti et al. In the article, box 4 (page 5) shows the reflectance spectra of leaves of different color. How is the reflectance spectrum of such solid materials measured? There was a recent question about spectrophotometers but it appears to assume the sample is in a liquid form.

As the name implies, reflectance spectra are measured from light reflected off an object. Any object with reflects light, such as any opaque object) will work for this technique; to me this seems like solids are ideally suited for reflectance spectrphotometry. You might be used to transmission or absorbance spectrophotometry, which measures the amount of light transmitted or lost after passing through a sample. These methods are typically used for liquids which allow passage of light to some extent.

The paper (1) cited by the review you mention says that they used a "RAMSES-ARC hyperspectral radiance sensor," which is probably just as awesome as it sounds. In principle reflection spectrophotometry works very similarly to transmission-based spectrophotometry: generate monochromatic light, shine it at the sample, and measure the intensity of light that comes back at that wavelength (or over a range of wavelengths)$^†$. If you do this for many different wavelengths of light, you have a reflectance spectrum. This link might have some useful information.

$^†$ Edit: Modern-day spectrophotometers use a more efficient method in which broad-band light is passed onto the sample and the response at a single wavelength can later be mathematically reconstructed. If you're interested in these types of details, refer to Fourier Transform spectroscopy.

(1): Doring TF, Anchetti M, Hardie J. (2009). Autumn leaves seen through herbivore eyes. Proc. R. Soc. B 282(1801): 121-127.


Most well studied termite species or a species that I could use to compare termite genes for functional annotation I am working with termites and I have a set of genes that I would like to compare with a species similar to termites so that I could elucidate its function. I am looking for a species that is similar to what Drosophila Melanogaster is to bees where to elucidate the functions of bee genes, it is compared to genes in D. melanogaster. Or how most worm genes is compared to genes in C. elegans. Similarly, if there is a well studied termite species, I could work with that.

The ultimate goal is to create a gene network with termite genes, hopefully on STRING.

Apparently, the most closely related insect to termites is cockroaches. Interesting article I found on the subject. However, that still didn't help because cockroach genes are not included in the STRING database.


What happens to our body when we undergo a sudden temperature change from 40℃ to 20℃? We know that a glass gets cracked when it undergoes sudden change in temperature. But what will happen in the case of a human body if it changes from the maximum(>35℃) to the minimum temperature(<35℃) suddenly?

Disclaimer: the answer is very broad and covers both the situations I am confident about, as well as those I understand only superficially.

The outcome depends on particular temperatures.

Example - cold shock response: "Cold shock response is the physiological response of organisms to sudden cold, especially cold water. In humans, cold shock response is perhaps the most common cause of death from immersion in very cold water, such as by falling through thin ice. The cold water can cause heart attack due to vasoconstriction, the heart has to work harder to pump the same volume of blood throughout the body. For people with heart disease, this additional workload can cause the heart to go into arrest. Inhalation of water (and thus drowning) may result from hyperventilation. Some people, due to body type or mental conditioning, are much better able to survive swimming in very cold water." But: " A person who survives the initial minute of trauma (after falling into icy water), can survive for at least thirty minutes provided they don't drown."

Sudden heat at entering sauna - I am not sure, but probably it also may cause heart attacks. Recent heart attack is a contraindication for sauna visits. Healthy individuals do O.K. due to thermoregulation mechanisms in the body.

As we move to more extreme temperatures, where the thermoregulation of human body simply has no chance at all to keep up, you can percieve the human body as a chunk of meat. The proteins denature, the water in the body gets boiled. The meat gets cooked, turns coal like, burns to ashes... Or by freezing, the water forms crystals, damages and breaks the cells. Eventually the meat freezes to be stone hard and does not change for a long time if kept at such temperature.


Protein folding, extra dimensions and bio-mathematics One metaphor that I have found to explain how proteins fold so quickly to a native shape is that of the blind golfer.

I have made a video to illustrate this metaphor. This shows how the shape of a slope can determine precisely where individual elements will end up.

The video represents many zero-dimensional points each following its own one-dimensional path down a three-dimensional slope to end up in a two-dimensional arrangement. Or almost: the one-dimensional paths are curves in three-dimensional space, the final resting surface is not flat, and one marble sits on top of three others.) The movement takes place through the fourth dimension of time.

Proteins form three-dimensional shapes, so the "slope" that their components slide down must be in an extra dimension.

Atoms have been observed to jump through a crystal lattice, without any indication that, in travelling from their start point to their end point, they pass through the three-dimensional space that we can observe. Is it conceivable that the component parts of a protein move through an extra dimension as the protein "folds"?

There are very simple protein chains whose native folded shape is well known. Is there any data available to suggest what path the different molecules in the protein follow during the folding process? Or do they appear to "jump"?

I imagine that it would be possible to create a mathematical model in n-dimensions to describe the simplest "slope" that the protein molecules could follow as the protein collapses into its native state.

What mathematical work is currently being done in this area?

Short Answer

What mathematical work is currently being done in this area?

A... lot?
Longer Answer
The "n-dimensional slope" thing that you're talking about shows up in the modern theory of protein dynamics as the "landscapes" concept. There's no truly standardized form for the theory, so it goes by many names. Try googling folding funnel, energy landscape, probability landscape, free energy surface, etc.
adendum
Oh, and also the current consensus is that the "quantum leap"-style effects that you were talking a little bit about don't play a large role in folding, at least in the initial stages. The current thinking is that most (not all!) of the dynamics of protein folding can be modeled using classical physics. Quantum effects can't come into play until the atoms of a protein are closely smooshed together (ie after the initial "collapse" phase of protein folding has finished).


Why only honey bee collects & store honey? In Insects, most of flying insects like butterfly etc, diet is sucking honey from flowers. none of them store honey except honey bee. Why so ?

Many different bees also make honey, not just honey bees (Apis species). There are carpenter bees, bumblebees and as Geraldo said, there's honey pot ants.

Only honey bees make any great quantity of honey. The other species make far less and it's a different consistency. Honey bees live in large colonies and honey is stored to feed developing larvae as well as feeding workers and the queen through winter. Other bees are solitary except for a few bumblebee species but their colonies are much smaller - usually less than 50. Bumblebees make far less honey. There's no need to store honey for winter as the queen and workers die in late fall. Only a newly hatched and fertilized queen will survive, hibernating through winter underground. Hence, storing more than the immediate needs of queen, larvae and workers would be pointless.

You mentioned butterflies sipping nectar. A butterfly's lifespan is very brief and only sips nectar to provide energy for fertilization and egg laying. Then, generally, they die. Larvae have been provided for already since the eggs hatch on the appropriate plant leaves as their food.


What is the role of CRISPR-dCas9 in gRNA-dCas9 transcription regulator complexes? In this paper1, I read that mutant versions of Cas proteins such as a deactivated Cas9 (dCas9) are used alongside a guide-RNA (gRNA) to form variants of CRISPR tool that can function as transcription regulators.

Since the mutant Cas9 has lost its nuclease functionality, the mutant gRNA-dCas9 complex can "block" transcription factors such as RNA polymerase from binding a certain gene, hence repressing transcription or elongation.

Another way that dCas9 can regulate transcription is by "carrying" another transcription factor - be it an activator or repressor - and this can be done by engineering a dCas9 fused to the other transcription factor of choice.

I understand how the dCas9 can block the binding of another transcription factor to repress transcription initiation or elongation, but what is the point of fusing another transcription factor with the dCas9? It seems to me that in this scenario, the dCas9 is just a passive carrier of the transcription factor that is actually doing the job, so why can't the transcription factor be fused with the gRNA instead, so that it can directly affect transcription when the gRNA forms complimentary base pairs with the target gene, instead of it being on a passive dCas9?

 1. Jusiak, B., Cleto, S., Perez-Pinera, P. and Lu, T.K., 2016. Engineering synthetic gene circuits in living cells with CRISPR technology. Trends in biotechnology, 34(7), pp.535-547.

so why can't the transcription factor be fused with the gRNA instead,
  so that it can directly affect transcription when the gRNA forms
  complimentary base pairs with the target gene, instead of it being on
  a passive dCas9?

The main reason for that is that both the gRNA and the dCas9-TF (transcription factor) combination can (each) be encoded genetically, while a combination of a gRNA with a transcription factor could only be generated chemically.

The possibility to genetically encode the dCas9-TF + gRNA unit allows one to:
a) use established methods for transferring DNA into cells,so that the cells make the Cas9 and the gRNA by themselves and
b) generate cells that will stably express the whole unit (dCas9-TF + gRNA) forever.

Neither of these options would be possible with a chemically linked gRNA-TF (which is also much harder to make for molecular biology labs that don't have the proper chemistry equipment).


How can CI repressor both activate and repress $P_{RM}$ promoter found in $\lambda$ phage? I'm reading a paper where the authors constructed a toggle switch that uses bidirectional $P_R/P_{RM}$ promoter found in the $\lambda$ phage. There are 3 binding sites - $O_{R1}$, $O_{R2}$, $O_{R3}$ - located between the two promoters. CI is expressed by $P_{RM}$ and CI dimers bind to these binding sites:

What I don't get is that CI seems to function as both an activator and a repressor of $P_{RM}$.
First, my understanding was that $P_{RM}$ is an inducible promoter activated by CI which also represses a constitutive promoter $P_R$:

CI is a transcriptional activator of $P_{RM}$, thus producing positive feedback.
CI preferentially binds to $O_{R1}$ and $O_{R2}$, repressing the constitutive promoter, $P_R$.

However, it is also stated:

In high concentrations, CI binds to $O_{R3}$ and acts as a repressor to $P_{RM}$.

This seems to suggest that the CI can function either as an activator or as a repressor depending on the binding site bound; specifically, CI dimer binding to $O_{R1}$ and $O_{R2}$ will repress $P_R$ and at the same time activate $P_{RM}$, while CI dimer binding to $O_{R3}$ will repress $P_{RM}$. Is this correct?
I (a computer scientist by training) was always given the impression that a transcription factor is either inherently a repressor or an activator of a promoter, but this doesn't seem to be the case here. I would expect that e.g. CI would act as a repressor to $P_R$ and an activator to $P_{RM}$ regardless of the binding site. So why does CI binding to $O_{R2}$ (and $O_{R1}$ as well?) activate $P_{RM}$, while binding to $O_{R3}$ represses it - why the inconsistency? Note that I'm primarily interested in this from the modeling perspective.
What I also don't understand is whether or not $P_{RM}$ promoter is inducible or constitutive (e.g. in the absence of bound transcription factors, how leaky is it)?

There's no rule that says a transcription factor must be either a repressor or an activator. The lambda repressor (CI) is in fact a repressor and activator of transcription, depending on where it is bound and to what promoter you are referring to. I know your question isn't directly about lambda phage, but I think this mechanism may be best explained in the context of where it was first invented: nature. So, I will try to briefly explain how the lambda repressor's dual role allows regulation of its own expression and controls lysogenic induction.

The cI gene is under the control of the PRM promoter. The PRM promoter is weak because the sigma factor of RNA polymerase (RNAP) holoenzyme has low affinity for it. Binding of RNAP to PRM, and thus transcription from there, at a reasonable level requires an activator. There is another protein involved in this process as well, called Cro, that can also bind the OR operators. The cro gene is under the control of the PR promoter. PRM is not a constitutive promoter because it requires an activator. I have heard PR called constitutive because it is a strong promoter and can bind RNAP without an activator. But, at the same time, it is under the control of the lambda repressor. I suppose it depends on which definition of 'constitutive promoter' you use.

The OR operators are not identical and thus CI and Cro bind them with different affinities: CI has the highest affinity for OR1, followed distantly by OR2 and OR3, while Cro binds OR3 with highest affinity. Binding (of any two molecules) is dependent on both their affinity to each other as well as their effective concentration. At lower concentrations, CI can only bind OR1 and OR2 cooperatively. That is, each lambda repressor dimer binds to another, forming a tetramer, with one half binding OR1 and the other binding OR2. Binding both operators as tetramer allows for a stronger interaction. At higher concentrations, CI can bind OR3. Furthermore, OR1 and OR2 are located in the PR promoter, while OR3 is located in the PRM promoter.*

Most lambda genes are under the control, directly or indirectly, of the PR and PL promoters (PL is similar to PR, but the promoter itself is not directly involved in cI regulation). When lambda exists as a prophage, its DNA is integrated into the host genome and most of its gene expression is repressed. This requires CI repression of PL and PR. When the viral DNA is first integrated, there is no CI in the cell (because it is a phage gene). Expression of cI is initially dependent on a different promoter (PRE), but I won't get into this here. Once CI concentration is high enough, it can bind to OR1 and OR2 as a tetramer. Binding here physically blocks the PR promoter and prevents expression of cro (CI acts as a repressor of PR here). It also interacts with RNAP (actually the sigma factor) and facilitates is binding to the PRM promoter, which leads to further cI expression. This process is commonly called recruitment: since CI is bound tightly to the DNA and has some affinity for RNAP, it can create a stronger interaction between the DNA and the RNAP-CI complex. Simply put, it induces the PRM promoter and is thus functioning as an activator of cI transcription. As CI concentration increases, it will bind OR3 more (which is located in the PRM promoter) and repress the PRM promoter by physically blocking RNAP from binding. In these ways, cI can autoregulate its expression level, both positively and negatively.

When the lysogen is in some kind of stressful condition, normal host processes will result in proteolysis of CI and its DNA/sigma binding domain is cleaved from the dimer- and tetramerization domains. This means that CI can no longer oligomerize and is no longer able to bind cooperatively to OR1 and OR2. The result is loss of PRM activation (leading to vastly reduced cI expression) and also a loss of PR repression (leading to cro expression). Cro can then bind OR3 and represses PRM. Lack of PR repression also allows expression of early phage genes (which are under the control of PR).

Note that a similar situation occurs at the PL promoter region, and binding of CI to both OR and OL as well as CI octomerization is important in prophage regulation, but that seems even further out of the scope of your question. Hopefully you can see how he lambda "repressor" actually functions as both a repressor and activator of transcription. If this kind of stuff interests you, I highly recommend a textbook called Molecular Biology of the Gene by Watson et al.

*See comments. Upon further research, the PRM and PR promoters both overlap OR2 (Autoregulation and Function of a Repressor in Bacteriophage Lambda, Ptashne et al.), as the diagram in the OP shows. It appears that the -35 region of both PRM and PR overlap OR2 by 2 and 3 base pairs, respectively. That led me to wonder that if CI binds to OR2, which is in PRM, wouldn't it physically inhibit RNAP binding and thus repress transcription? Well it appears that CI interacts with the same region of sigma that is responsible for binding the -35 region of PRM (Amino acid substitutions in the -35 recognition motif of sigma 70 that result in defects in phage lambda repressor-stimulated transcription, Kuldell and Hochschild). So instead of blocking sigma binding here, it enhances it.


Dataset of microscopic images before and after staining? I am looking for a freely distributed dataset of microscopic images. I am hoping to find a dataset that would feature histological images before and after staining (e.g. H&E or some other standard one, preferably). I have been searching through various databases, but I cannot find a proper set. I hope the sample size to be at least about 100. Suggestions?

Virtual fly brain (http://www.virtualflybrain.org/site/stacks/index.htm) is an excellent database of fly (Drosophila) brain sections, which can be electronically processed/annotated/highlighted on the fly to show different areas of the fly brain as an overlay on top of the original images.

Alternatively, you can use BrainTrap (http://fruitfly.inf.ed.ac.uk/braintrap/) for the expression of proteins in the fly (Drosophila) brain using brain sections. Another database which has silver stains of Drosophila brain sections is the flybrain (http://flybrain.neurobio.arizona.edu/Flybrain/html/atlas/) database. This database also contains 3D models of different fly brain structures and much more!

I'm sure there are many many similar databases, but these are the ones I knew of, which are widely used in the Drosophila community.


Why would you plate cells at different densities in a colormetric assay? The aim of my experiment is to see if a kinase inhibitor reduces cancer cell viability. I am using 2 different cell densities 50,000 cells/well and 100,000 cells/well and different doses of the kinase inhibitor.

The comments you have given are some reasons, although they also depend on the confluency of the cells. Your teacher/professor/advisor is also making sure that you can see an effect at low levels of drug, as well as making sure that changes in the signal are visible - for example, does a 50% reduction in viability due to drug activity give the same drop in signal as reducing the number of cells by 50%? You don't say what kind of assay you're running, but a fairly common and inexpensive one is the MTT assay, with some kits nowadays switching to XTT for greater sensitivity and a reduction in the number of steps in the assay (example kit from Cell Signaling compared to an MTT assay kit from ThermoFisher), as the final colorimetric product does not require solubilization before reading. Finally, depending on the lab you're in, the conditions for the assay may not have been optimized yet, so your instructor wants you to test a couple of different densities to see what works best.


Is the technology "identitas v1 forensics chip" related to microarray technology? Available resource but difficult for me to make scence

Relation about crime scene and identitas v1 forensics chip

Is the technology "identitas v1 forensics chip" related to microarray technology?

if true ,as I know, different combination of genes are expressed in different parts of our body which means a certain tissue only makes particular types of mRNA.

Then my question raised: How can a CSI crew reconstruct a person's virtual appearance (for example skin color, face structure) by a piece of microarray with limited tissue (for example cells from saliva) and mRNA?
I mean saliva cells don't make pigment of our body, so how can the eye color or skin color be presumed, for example?

Otherwise, what is the technique "identitas v1 forensics chip "which allow us  to detect several phenotype  simultaneously?

According to the information I Know,"identitas v1 forensics chip" it contains hundreds of thousands of short sequences of DNA that binds to SNPs,where the DNA from the crime scene binds to this chip can allow software to reconstruct the appearance of the person of interest.

the chip is the first to provide data on all these traits simultaneously. Other devices can determine at most two at a time – usually eye and hair colour.

Interesting question. The answer lies encoded in our DNA. If you take eye color for example, the genes important here are well known. The most important are OCA2, HERC2, SLC24A4 and TYR.

These are involved in different parts of the pigmentation process, any mutations in these genes lead to changes in pigmentation. Since also the variants, which lead to a altered pigmentation are known, you only need to analyze some cells containing genomic DNA from your suspect to check for these mutations (or SNP, single nucleotide polymorphisms).

The same is true for hair and skin color. So if you identify one or several mutations in the MC1R gene, you can be pretty sure, that your suspect is red haired, has pretty light skin and a high chance for green eyes.

This technique doesn't need to know the exact expression of a certain gene, but needs information on the cause for a phenotype (like skin, hair or eye color) and the causative gene.

The "Identitas v1 forensics chip" is a microarray chip, unfortunately, the company website is not really a source for information. You can find some in the New Scientist article you linked. This is basically a microarray (or chip) where all the forensically interesting and known SNPs about how a person looks like are analyzed.
It gives basic information (or at least a chance) how a persons looks like, what CSI does in the series is usually widely exagerated.


Did the hyoid bone of Australipetichus afarensis have a hyoid bulla? The hyoid bulla is present in Chimpanzee hyoid bones, and not in Humans. Does A. afarensis have a hyoid bulla?

Short answer:

Yes.

Longer but still short answer:

H. heidelbergensis and H. neanderthalensis have a modern human-like hyoid bone. A. afarensis has a hyoid bulla similar to modern chimpanzees.

The hyoid bone is thought by some to be important in human evolution because of its position in the throat and the possibility that morphological changes in the hyoid were important for the development of speech. However, this view is not without controversy, and it is probably not sufficient to use hyoid bone morphology as a definitive marker for development of speech similar to modern humans, though it may be suggestive.

Some quotes from two references on the morphology of the hyoid of A. afarensis:

Alemseged, et al. 2006:

  [the hyoid of A. afarensis] "...is
  most similar to that of juvenile African apes, and unlike that of
  modern humans11,12. The exposed greater horn is slender, and the
  body is expanded anteriorly, forming a bulla that is deep relative to its
  breadth and height..."

Steele, et al. 2013:

  "...the Dikika juvenile australopith hyoid is deep for its height (Figure 9) and width and is morphologically chimpanzee-like. This similarity applies both when comparing only subadults from the three extant species (Figure 9A), and when comparing across all observed age classes (Figure 9B..."

References:

Alemseged, Z., Spoor, F., Kimbel, W. H., Bobe, R., Geraads, D., Reed, D., & Wynn, J. G. (2006). A juvenile early hominin skeleton from Dikika, Ethiopia. Nature, 443(7109), 296-301.

Steele, J., Clegg, M., & Martelli, S. (2013). Comparative morphology of the hominin and african ape hyoid bone, a possible marker of the evolution of speech. Human biology, 85(5), 639-672.


Is there logic in this sentence? "Authors discovered a gene as one of the genes evolved through natural selection" From a news report:

  PhD candidate Daiki Sato and Professor Masakado Kawata have discovered SLC18A1 (VMAT1), which encodes vesicular monoamine transporter 1, as one of the genes evolved through natural selection in the human lineage.

Didn't all genes evolve through natural selection?

I'm self-training myself in translation into Russian, and this sentence stumped me. How do I translate it and avoid an absurdity? I thought that all genes have evolved. That's what genetics is about, isn't it?

Yes, the statement in the news article is not correct; however, it (probably accidentally) isn't quite as nonsensical as it sounds.

The actual paper that the news article is trying to describe is unsurprisingly more accurate.

  Here, we found a gene, SLC18A1 (VMAT1: Vesicular monoamine transporter 1), as a positively selected gene in the human lineage. This gene has a human‐unique variant (Thr136Ile; different from other mammals (136Asn)) whose association with several psychotic symptoms has been repeatedly indicated. Moreover, our analysis showed that this variant has been maintained in non‐African populations by balancing selection and had originated around 100,000 years ago, typically regarded as the timing of Out‐of‐Africa migration.

--Positive and balancing selection on SLC18A1 gene associated with psychiatric disorders and human‐unique personality traits

Here instead of talking about "natural selection", the authors refer to "positive selection" and "balancing selection", two sub-categories of natural selection. Since much of the genome is under negative selection, it's worth noting alleles that are not.

  Didn't all genes evolve through natural selection?

The reason the news article is not nonsensical is that natural selection is not the only force that acts on genomes.  We've known for 50 years that drift is an important factor that influences genetic evolution (wikipedia: Neutral theory of molecular evolution, Nearly neutral theory of molecular evolution).  However, it's pretty clear from the article that the author is unaware of these concepts and probably doesn't understand the significance of the paper.


Is it hydrogen atoms or electrons that are passed along an electron transport chain? I am so confused because my book says it is electrons which are passed along the electron transport chain but all we are considering is hydrogen ions (H+) and hydride ions (H-). Can someone clear that up for me ?

As explained on the Wikipedia page of the electron transport chain:

  An electron transport chain (ETC) is a series of complexes that transfer electrons from electron donors to electron acceptors via redox (both reduction and oxidation occurring simultaneously) reactions, and couples this electron transfer with the transfer of protons (H+ ions) across a membrane.

Electron are thus transfered from the electron donor (NADH, H$^+$ produced by the TCA) to the electron acceptor (O$_2$) through the successive enzymatic complexes of the electron transport chain.

Complexes I, III and IV are proton (H$^+$) pumps: they use the energy gained thank to the electron transport in order to translocate protons across the membrane.


What would be a reason for a tree to have flowers of different colors? The spring is here and the cherry trees along my street are blooming again!  Some trees have white flowers, some dark pink. But then... there're these trees which are all white yet just a few flowers are pink, just like that:

Is there a layman explanation for this phenomenon?

There are a couple of possibilities for what's going on here:

The most likely explanation is Position Effect Variegation (PEV). Genes are, at the most basic level, organized linearly on chromosomes (very long strings of DNA). Some parts of chromosomes contain stretches of genes that are actively silenced, or turned off, by cells (large silenced regions like this are called heterochromatin). The boundaries of where this silencing starts and ends are sometimes fuzzy. If a gene necessary to produce pigment happens to be next to a silenced region, the silencing can randomly creep in and shut off that gene as well, or creep back to its normal boundary. (This is why it's called 'position' effect variegation: it depends on the physical position of a gene, in this case the pigment gene, on the chromosome, and how close it happens to be to a normally 'silenced' region.) This process is (probably) effectively random, so it won't happen in every cell, which means some cells will produce pigment whereas others won't. A famous example of this happens in fly eyes, as in the image on the left. Importantly, the difference here isn't 'genetic' (the actual content of the DNA), but 'epigenetic' - essentially, the way cells modify and read their own DNA.
Another possibility is an active jumping gene, or transposon: unlike most genes, transposons can move around in the DNA, and can sometimes carry with them a piece of DNA that tells nearby genes to be turned on or off (or are simply silenced by the cell, like in the PEV case above). If a transposon sits right near a pigment gene, it can cause that gene to be silenced. However, if the transposon up and jumps somewhere else at a random time (which active transposons do!), the gene nearby is no longer silenced, and can now cause pigment to be produced again. There's an example of this happening in snapdragons (see middle image). In this case, there is an actual genetic difference between the pink and white cells: one group has a jumping gene sitting next to the pigment gene, and the other doesn't.

Importantly, PEV silencing--like the transposon jumping--is inherited when cells divide, so if a stem cell that eventually makes a whole flower silences the pigment gene (or transposon jumps out), the whole flower will be white. If the silencing happens later in development, maybe when the early divisions forming the flower have happened, then a single petal, or just a sector of a petal, could be white, and the rest pink. Such sectoring is a telltale sign of PEV or transposon-related effects.

In your photo and description, the tree is mostly white, and individual sectors are pink, not vice versa. If the cause of the color switch is PEV, then the pigment gene's 'default' in this tree being silenced, with the silencing randomly moving away from the pigment gene in some cells. Or there could be a particularly active transposon that tends to bring gene silencing along with it at play here.


What risk to DNA does long-term exposure to low-dose radiation pose? A new study from MIT scientists suggests that long-term exposure to low-radiation poses no risk of DNA damage for mice (it is also important to note that mice are unusually susceptible to cancer). So apparently there may be a threshold for radiation damage to DNA.

But is this study conclusive? What are some other studies that show the biological effects of long-term low-dose radiation on DNA?

There are some studies that do show increased rates of cancer in frequent flyers. So are are we going to reconcile this finding with the finding above?

I agree with @Kevin - there are no ultimate statements in science. The answer is 'its all relative'.

With radiation and risk, more radiation means more risk of cancer or any number of other types of damage that can result.  The question is is this significant?  And this is a somewhat subjective question.

When someone says:

'there is no health risk from XYZ'

what they mean is..

"to the extent that we can determine, we can't see any more chance of adverse health if you are exposed to XYZ conditions than if you weren't"

DNA damage happens all the time.  The frequent flier study you cite is trying to see if the additional exposure to cosmic radiation while flying, which is largely blocked by the atmosphere, causes a change in the rate of some cancers.

Radiation and cancer is like a lottery.  If you buy just one ticket you might win.  If you step outside, the thousands of extra gamma rays you get outside might start a cancer that will eventually take your life.  If you buy 20 million tickets you will very likely win.  If you hang out next to high levels of radiation, even for a short while, you will get so much damage you will not live long.

Its difficult to study the effect of low levels of radiation. The lower the levels of radiation we are asking about, the longer you will have to wait to see if there is an effect.  If 10% more people get cancer, you have a very real concern that some of these folks might have done something else, like sunbathe or live in a poorly ventilated basement for too long.

The real question is, what is significant?  I once saw a 60 minutes segment where a dermatologist said that she simply never directly exposes her skin to direct sunlight.  I'm betting she never got a melanoma.  She carried a parasol and wore light gloves outdoors.  (sorry I can't find the link)  She was at least in her 50s and she had the skin of a teenager.  I still go out in the sun.  I assume my risk of melanoma is 5-10 times more than hers was (this was a pretty old broadcast).  (mine is 0.03% in the next 5 years btw).  Its just not worth it to me.


What is the highest pressure at which plants can survive? Inspired by this awesome question, I'm looking for the corresponding maximum: what is the highest air pressure at which plant life can survive?

For example, Venus's atmosphere is about 90x as dense as Earth's.  Aside from the other obvious factors, like sulphuric air and boiling temperatures and otherwise resembling hell in every possible way, can plant life survive in such a condition?

Additionally, are some types of plant life more adaptable to high pressure environments than others?  (I'm assuming an air environment, and excluding deep-sea life, etc.)

See Effect of very high pressure on life of plants and animals (2012).

Judging from the fact that all the living creatures we have examined, both animals (tardigrades and Artemia) and plants (Ptychomitrium, Venturiella and white clover) were alive after exposure to 7.5 GPa, it was suggested that most of the proteins of those creatures which unfolded at the early stage of the compression remain principally unchanged after exposure to the very high pressure of 7.5 GPa. It was also suggested that the unfolding of proteins was completely reversible up to 7.5 GPa.
The maximum hydrostatic pressure applied to all the living specimens investigated in the present experiments corresponds to that in the upper mantle, at the depth of 180 km from the surface of the earth.

So survival of plants at 75,000 times atmospheric pressure is possible. In this experiment the exposure times were 30 minutes and 1 hour for the plants and 13 hours for the animals.


Is there a reason for the lack of full RTK structures? Bocharov et al. (2013) write that

  As there are no structures of full-length RTKs [receptor tyrosine kinases], we do not fully understand how different domains function together to mediate signal transduction inside the cell.

True to the above quote, I've so far only found isolated domains of some RTKs in the PDB, but no complete structures (neither X-ray nor NMR). I am a chemist by training, so am hardly an expert in this area, but it does seem counterintuitive given the general importance of RTKs in cell signalling. Is there a fundamental reason for the lack of RTK structures?

In contrast, there are examples of full-length GPCRs, e.g. rhodopsin (Palczewski et al. 2000). As tsttst brought up in the comments, this seems to be an issue with RTKs being single-pass membrane proteins, whereas GPCRs are multi-pass. How does this affect the ability to obtain a structure?

Bocharov EV, Lesovoy DM, Goncharuk SA, Goncharuk MV, Hristova K, Arseniev AS. 2013. Structure of FGFR3 transmembrane domain dimer: implications for signaling and human pathologies. Structure 21(11):2087–2093. doi: 10.1016/j.str.2013.08.026.

Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA, Le Trong I,  Teller DC, Okada T, Stenkamp RE, et al. 2000. Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289(5480):739–745. doi: 10.1126/science.289.5480.739.

Large proteins are challenging for NMR: the more amino acids, the more peaks one has to assign. Peak overlap is also more likely the more amino acids you have, making assignment difficult. Some NMR strategies work well for studying dynamics of large proteins, but as far as structure determination is concerned, there definitely is a critical size past which NMR is simply not the tool for the job.

Flexible proteins are challenging for crystallography: too much flexibility can simply prevent crystallization, you can spend years only trying to get crystals, and once you do manage to grow crystals they might diffract poorly or not at all. But crystallography is often very useful to solve high-resolution structures of individual, isolated domains; this is of great help down the road to interpret a lower-resolution cryoEM map of the full-length protein.

Membrane proteins are challenging for biochemistry: purifying them and getting them to remain stable in solution is difficult.

Receptor Tyrosine Kinases (RTKs) are all of that at the same time! Large, flexible membrane proteins.

Now, with tremendous technological progress of cryo-electron microscopy (cryoEM) recently, such challenging structures become more tractable. Conformational flexibility is still an issue, but unlike with crystallography it can be dealt with to some extent (i.e. it won't prevent you from collecting initial data and getting preliminary results that can guide your next attempt).


Basic Local Alignment Search Tool (BLAST) Why would BLASTP (Basic Local Alignment Search Tool) be a poor tool to search for motifs in protein sequences?

Because it has a poor statistical model. It's basically a local alignment tool aided by a fixed-length k-mer index. It estimates homology in terms of sequence identity and while this is often enough to find homology in relatively conservative sequences, the heuristic scoring model doesn't really allow to search motifs. A motif in terms of bioinformatics can be seen as a series of state-switch events, hence you need a model that estimates similarity in terms of likelihood of observing such a sequence of state switches under  your prior state-switch matrix (inferred from a training sample). These models are known as Markov models and people usually utilize Hidden Markov Models to find motifs. There are good popular tools, such as HMMER

EDIT as per OP's comment

  As motifs are locally conserved regions & BLAST also performs local
  alignment then why it should not be able to search for motifs?

A motif is not just a "locally conserved region", it's a specific sequence profile. BLAST doesn't extract any sequence profiles, it wasn't created for that. Given a pair of sequences it simply shows you similar patches. Hence BLAST is simply not the right tool for the task. They made PSI-BLAST for that very sake.
Moreover, many motifs comprise amino acids or nucleotides that can be quite separated in a primary sequence and only get close in a folded (secondary or tertiary) structure. Here your definition of "locally conserved region" fails as does BLAST.
As I've already mentioned, BLAST performs a heuristic local alignment, that is it assumes that two related sequences must contain at least one common k-mer (word) of specific length. This, given a precomputed word index, significantly increases performance in terms of speed and RAM consumption. But similar motifs can be present in non-homologous sequences or in highly divergent sequences that hardly evince any homology, and BLAST won't find anything at all.


How do you average Ki values? It's embarrassing for me to ask this but well such is life. NIMH Psychoactive Drug Screening Program (PDSP) Ki Database is mentioned as the source of the average binding affinity (Ki) values given in Goodman and Gilman but whenever I try to, in some way, confirm that these values are averages obtained from PDSP I get values that are way (up to 10,000 fold) off the values given in Goodman and Gilman. (ps. I am a mathematician too so I know how to take an average, $\bar{x} = \frac{\sum_i^n x_i}{n}$ so you don't need to hold my hand through the calculation with something as simple as the conventional definition of averages) Therefore I have reached the conclusion that I must be doing the calculations wrong. Please show me how to do them correctly. Here's a screenshot of exactly what Goodman and Gilman says that's confusing me:

Oh and yes I am using just the cloned human transporter values not just all the stuff that comes up.

Since I asked this question I found out what I was doing wrong in searching for Ki (i.e. I thought the Ki ID was the test ligand and hence I was searching for drugs the wrong way) values but also how, I think Goodman and Gilman got its Ki values.

I think what they did was they searched for the hot ligand that gave the most consistent and numerous Ki values and took the average of the consistent Ki values (with an relative tolerance of ~100% between results). Additionally since I knew the data, as is stated in the page displayed above, was taken 30 June 2009 I was able to eliminate some sources that were probably not available on PDSP at the time. Using this I was able to get consistent averaged Ki values in the vast majority of cases (with like, at most a small handful of exceptions).


How extensive is CD47? CD47 aka the "don't eat me" signal has recently been claimed to be expressed on all tumor cells. This doesn't seem to corroborate with other cell-biology experiments. On what other cells is CD47 expressed?

I don't know how extensive. Let's run a simple data query and find out: Go to GEO at NCBI. In the "Gene profiles" window, type CD47, and hit enter to launch the query. At the top of the resulting page, use the link labeled "Limits" to restrict the 7000+ results to human by entering the term "human" in the "DataSet organism" window. So, there are 3700+ results. Look through them to get an idea of which cell types and under which conditions CD47 is expressed.

Let's try a second method. Go to the BioGPS portal. Enter CD47 in the appropriate window and run the query. From the results, select the row with ID # 961 as this represents the human gene CD47. The resulting gene expression/activity chart for Hs (human) will show you in more general terms where CD47 is expressed.


Why don't we build up an immunity to sore throat? We often get sore throats once or twice a year, and it clears in a few days sometimes without any antibiotics. I was wondering why doesn't our body become immune after clearing a sore throat?

Short Answer

It should be noted that there are many non-pathogenic causes of sore throat, and I would suspect that you are not always distinguishing these causes from actual illness.

In most cases, it would not be possible to build a response (immunological or otherwise) to avoid reacting to these stressors.

Bacteria and viruses mutate frequently in ways that make your immune system unable to properly recognize them to ward off initial infection.

Your immune system recognizes specific pathogens based on structural characteristics. If those characteristics change when pathogens mutate (which happens fairly frequently), your immune system will not recognize it as readily (or initially at all).

 Long Answer

Sore throat is most commonly attributed to pharyngitis, or the inflammation of the back of the throat called the pharynx.

Causes

Sore throats can be caused by many things. (e.g., see here, summarized below):

First off, a sore throat can be the result of many things unrelated to illness:

Allergies
Dryness
Irritants
Excessive talking,singing,shouting,etc.
Muscle Strain
Gastroesophageal reflux disease (GERD)

As a result, at least 30+% (higher in adults) of reported sore throat cases (and supposedly many more unreported cases) are not due to any type of illness.

Further, a number of pathogens can cause a sore throat:

Viruses

Rhinovirus, coronavirus, influenza, parainfluenza, adenoviruses, Epstein–Barr, etc.
(see here for one estimate of relative etiologies).

Bacteria

A number of bacterial infections can cause a sore throat. The most common is Streptococcus pyogenes (aka "Strep A").

It turns out that pathogen-caused pharyngitis is fairly common. Supposedly 10% of adults with sore throats have strep, and around 70% of children pharyngitis cases seen by doctors are either virally or bacterially caused.

However, it should be noted that only 20-30% of children and just 5-10% of adults have bacteria to blame for their sore throat, with viral infections being much more common. (source: IDSA).

Sore Throat Frequency

It turns out that sore throats are fairly common; Jones (2004) determined that about 7.5% of people have a sore throat in any three-month period. Further, on average, adults get a sore throat two to three times a year and children about five times a year (Tamparo 2011 and Rutter & Newby 2015), so your personal experience is fairly average.

Because viral causes and non-pathogenic causes make up an overwhelming percentage of overall sore throat cases, it shouldn't be surprising that most sore throats clear up without the use of any antibiotics.

As for those that are caused by pathogens:

Why no Immunity?

Bacteria and viruses both mutate fairly quickly (see Antigenic Variation, Antigenic Drift and Antigenic Shift), so it shouldn't be surprising that you're capable of having an immune response to pathogens throughout life.

If we consider just strep alone, it mutates/reemerges with improved fitness frequently (e.g., see Bao et al 2016 and their citations)
And see Sanjuán et al. (2010) for a reviewof viral mutation rates.

So not only are there a number of pathogens that can cause sore throat, but each of these pathogens can mutate. That leaves you with a fairly sizable number of potential invaders that can illicit a sore throat.

Let's See How Your Immune System Responds:

Your immune system contains cells that can be split into two broad groups: cells that belong to the adaptive immune system, and cells which belong to the innate immune system. [See here for a simple explanation].

Innate Immune system: consists of cells responsible for initial detection of pathogens, recruitment of other immune cells, activation of the complement system, engulfment and (more immediate) destruction of pathogens.
Adaptive immune system: consists of cells which coordinate to develop a memory of the infections they've seen previously in order to mount a faster, more pronounced immune response to repeat pathogens.

Depending on the kind of foreign invasion, two different immune responses can occur in either of these 2 broader "systems": either a humoral response involving antibodies or a cell-mediated repsponse.

A general feature of the immune system is that these mechanisms rely on detecting structural features of the pathogen or toxin that mark it as distinct from host cells (see Chaplin 2010 for a review). The mechanisms permitting recognition of pathogenic/toxic foreign structures can be broken down into two general categories:

hard-wired responses encoded by genes that recognize molecular patterns shared both by many microbes and toxins that are not present in the mammalian host. This is the innate system described above.
responses that are encoded by gene elements that somatically rearrange to assemble antigen-binding molecules with extreme specificity for individual unique foreign structures. This is the adaptive system described above.

Antibodies recognizes a unique/specific molecule of the harmful agent, called an antigen, and binds to it to tag it for immune attack.

  Because the adaptive system is composed of small numbers of cells with specificity for any individual pathogen the responding cells must proliferate after encountering the antigen in order to attain sufficient numbers to mount an effective response against the microbe or the toxin. [Source: Chaplin 2010].

This means that you can still experience some mild symptoms due to the invading pathogen.

The important take-away from all this, though, is that your immune response relies on structural "markers" on pathogens in order to recognize them. This is true for both innate and adaptive immune responses. If the physical/structural properties of a pathogen change (due to antigenic processes and mutations as mentioned above) your immune system will be slower (and possibly ineffective) in responding to an attack.

The result, then, could be another one of those sore throats...

Citations

Bao, Yun-Juan et al. “Phenotypic Differentiation of Streptococcus Pyogenes Populations Is Induced by Recombination-Driven Gene-Specific Sweeps.” Scientific Reports 6 (2016): 36644. PMC. Web. 17 Mar. 2017.
Chaplin, D. D. (2010). Overview of the immune response. Journal of Allergy and Clinical Immunology, 125(2), S3-S23.
Jones, Roger (2004). Oxford Textbook of Primary Medical Care. Oxford University Press. p. 674. ISBN 9780198567820. Retrieved 4 August 2016.
Rutter, Paul Professor; Newby, David (2015). Community Pharmacy ANZ: Symptoms, Diagnosis and Treatment. Elsevier Health Sciences. p. 19. ISBN 9780729583459.
Sanjuan, R., Nebot, M. R., Chirico, N., Mansky, L. M., & Belshaw, R. (2010). Viral mutation rates. Journal of virology, 84(19), 9733-9748.
Tamparo, Carol (2011). Fifth Edition: Diseases of the Human Body. Philadelphia, PA: F.A. Davis Company. p. 356. ISBN 978-0-8036-2505-1.


Are there foods which not only prevent but help fighting cancer? I was reading a probably not to serious webpage and I found this quote

  " Certain types of vegetables, such as the cruciferous variety, are
  not only nutrient-dense but contain compounds that may fight cancer,
  according to the National Cancer Institute."

Then I looked more information about this, but I can only find references to foods helping prevent cancer but they dont seem to say they help fight cancer when it's already present.

This page says the following foods help prevent cancer, but later make an ambiguos statement that you could think they imply those foods help fighting cancer when it's presented

  The following is a list of foods that have been shown to have
  cancer-fighting properties. While some are well-known super foods,
  others may surprise you. You won’t find a burger or fries on this list
  – when it comes to cancer prevention, clean eating prevails:

http://www.cancercenter.com/community/newsletter/article/Foods-that-have-cancer-fighting-properties/

So, my question is, are there foods which not only prevent but help fighting cancer when it already exists?

The short answer is, no.  There really isn't any good evidence that a person can eat enough of any chemical to have a clinically detectable effect on cancer.

Note that any study that shows an effect on cancer cells in a petri dish doesn't count as demonstrating that it would do anything in a person with cancer.  It might be that the chemical would not work the same in the body, or would not work the same on real cancer cells growing in a person (not cells cultivated to grow in a petri dish for 30 years).  And even if they did kill cancers like in a petri dish, that doesn't mean that you can actually eat enough of the chemical to get a high enough concentration to have that effect.

That link is pretty much click-bait, and nothing more.


Fermentation of bananas I may have access to huge quantities of freshly picked bananas. Searching the web, I have found that the sugar content of the average banana is 14g of fructose (could stand to be corrected on this) which should in principle allow for fermentation. The bananas are in no way processed. My questions now are:

(1) How suitable are bananas for ethanol or methanol fermentation?

(2) How exactly is the fermentation workflow? I presume the bananas would be chopped?

(3) considering point (2) what effect would the banana skin have on the fermentation process? Would it be better to ferment the whole fruit including skins or remove the skin before fermentation?

Hope someone can help

Fruit Moonshine is quite desirable :)

Peel the bananas. Good workflow here:

http://www.moonshiners.club/banana-moonshine-recipe/

It takes considerable work especially in large quantities. Furthermore, check legality and read up on methanol poisoning.  Don't poison yourself!


Barr bodies in males? This source states that there are Barr bodies in 0-4% of males.

Why isn't it complete 0%? why some males loose their only X chromosome? How does then their body compensates for those genes which are inactivated?

To understand how the X inactivation can occur in, it requires a bit of understanding of how Barr bodies come about.

The main key players to keep in mind are (From 1):

Xist: Xist   Required for initiation of X-inactivation
Tsix: Tsix (It's Xist spelled backwards!) Represses Xist expression by silencing the Xist promoter, also required for X-chromosome pairing, counting the number of XICs (X-inactivated chromosomes)

From 2, Here is a general diagram of how X-inactivation occurs.

X-inactivation requires first, count how many X chromosomes are present (n). Then, the (n-1) number of X chromosomes are inactivated. The choice for which gets inactivated is largely random.

Therefore, if a male has multiple X-chromosomes (as in the case of Klinefelter syndrome) then X-inactivation would occur in males. However, there is also the case that erroneous counting may lead to the inactivation of the only X chromosome in males early in a developing embryo. But this is lethal, and the embryo would die.

More about Kleinfelter Syndrome can be found here: Klinefelter syndrome

Guided by RNAs: X-inactivation as a model for lncRNA function.
Lessons from X-chromosome ina ctivation: long ncRNA as guides and tethers to the epigenome


About lack of selective pressure In [1] it is stated that:

  the frequency of comutations in FGFR3 and KRAS or PIK3CA and KRAS was lower than predicted by chance, suggesting ... a lack of selective pressure for both mutations to occur

It is not clear to me how lack of selective pressure may produce a frequency of comutations that is lower than predicted by chance. I'd expect the frequency to be the one predicted by chance, if no selective pressure is applied. What am I missing?

[1]   S. E. Woodman and G. B. Mills, “Are oncogenes sufficient to cause human cancer?,” Proc. Natl. Acad. Sci. U.S.A., vol. 107, no. 48, pp. 20599–20600, Nov. 2010.

Often the phenotype caused by a given allele depends on the alleles present in other genes; this is termed epistasis. In the context of tumors, selective pressure is primarily associated with the ability of cells to grow and divide (without dying). It could be possible for two mutations which each confer some tumorigenic properties to conflict with each other, such that when both mutations are present they interact to either kill the cell or otherwise block the effect of the other mutation. The expected result would be that few tumor cells would exist with that combination of mutations because they would proliferate less than those cells with just one.

However, I suspect they are just addressing an non-significant difference from chance that they felt was too big to ignore entirely in discussion. You left out the rest of the sentence including a key word 'either' which I think is entirely misleading here and I wish you would not have done that (emphasis mine):

  frequency of comutations in FGFR3 and KRAS or PIK3CA and KRAS was lower than predicted by chance, suggesting either a lack of selective pressure for both mutations to occur or a negative interaction between the consequences of each mutation

Essentially they are hedging the statement that there could be a negative interaction (i.e., selective pressure against) having both mutations with the possibility that there is just no meaningful positive interaction and the observation of a less than chance co-occurrence is not a true result. Note that they have a very small population because these are clinical tumors, and KRAS analysis was only in 59 patients (with only 12 mutants), making the statistical power for interactions very low.

I agree that this wording is imprecise and a bit unclear, so your confusion is understandable, but I think there are two reasons why it is worded this way. First, I believe they are trying to emphasize a possible future research direction and are trying to do so without making a criticism of the paper they are reviewing, because I don't think they view it as a criticism. Had they said "This study doesn't have enough statistical power to determine if there is a negative interaction between these mutations," that would sound overly critical given they are discussing something that wasn't really the intent of the original study. Second, I think the simplest prior expectation (which they do not state but is implied) is that two mutations that contribute to tumor production individually will be even more tumorigenic when present together. By stating the other outcomes: no selective pressure for the two mutations to cooccur or a negative interaction, they are implicitly stating that the simpler outcome, a positive interaction, does not seem to be occurring.

There is also a definite issue of selection bias here (statistically, not evolutionarily). That is, they are investigating a certain type of tumor. If those tumors can be caused by either a mutation in one gene or a mutation in another, then the chance association of those mutations would be the chance in the general population/other types of tumors/noncancerous tissue, which would be low (because most have neither), rather than the chance in patients.

The article you refer to is just a commentary on another article; you should really read Hafner et al instead (and note the original paper doesn't talk much if at all about these co-occurrences).


What would the RBCs of someone heterozygous for sickle cell anemia look like? Would half of the RBCs look normal, and the other half sickled?
Or would all of the RBCs have slight deformation/sickling?

Thanks!

The peripheral smear in a patient with sickle cell trait typically appears normal (see Cecil Medicine Ch. 166). Each cell has only 30-40% HbS, and so the polymer that causes the sickling doesn't usually occur.  You can find some examples online of smears with target cells and maybe one sickled cell, but these are the exceptions to the rule. This is one of the reasons a smear is not a good screening tool for sickle cell trait.

To clarify, RBCs in the blood of a patient with sickle cell disease aren't all abnormal either. See this smear from this case published on the NEJM blog:

Again, this is sickle cell disease, not trait, and you see many normal RBCs, even from this patient (honestly, it's not clear whether this is that patient's smear, but this would be typical). In sickle cell trait, the smear would likely be normal (image from webpath tutorial at the university of utah):


What confuses me about "homologous gene" When I first encountered homologous genes I thought those genes are identical because the text book said so, and "homologous" meant the same knowledge.

But as I studied along, it comes out that diploid is a two sets of haploid, each from mom and dad.

This means they are not identical, doesn't it? How could they be "identical" since they are from mom and dad seperately?

If they were identical, crossing over during meiosis loses a point(mixing chromatids is meaningless if they are "same").

Then, when the text book says homologous genes are identical, what identical trait is the text book referring to?

Can you please directly cite your textbook. Either your textbook is wrong or you massively misinterpret it.

The concept of homology refers to the concept of shared ancestry. From wikipedia

  In biology, homology is the existence of shared ancestry between a pair of structures, or genes, in different taxa. A common example of homologous structures is the forelimbs of vertebrates, where the wings of bats, the arms of primates, the front flippers of whales and the forelegs of dogs and horses are all derived from the same ancestral tetrapod structure.

I would add that a common counter example are bats wings and bird wings (which is an analogy).

Two genes are homologous if they both derive from the same ancestral gene. Of course, as ultimately, all genes are related, the concept only make sense by comparison to other structures that are more distantly related or relative to a time point in time.

For more information, just have a look at any good introductory course or textbook to evolutionary biology (for example evo101 > homology)


In scuba diving, are nitrogen narcosis and high pressure nervous syndrome the same thing? In training for scuba diving, they tell you that when you're bellow 100 ft or so you have to watch out for changes in mental state that resemble drunkenness. The cause of these mental disturbances is called nitrogen narcosis, and it has something to do with the increased pressure on the nitrogen component of the gas that you're breathing out of your tank. I just read this article from the what-if section of XKCD (halfway down the page, under the header about Michael Phelps) that mentioned a very similar sounding disorder called high pressure nervous syndrome. Are nitrogen narcosis and high pressure nervous syndrome related, or are the effects of high pressure nitrogen and high pressure by itself separable?

These are different things.

Nitrogen Narcosis or more commonly Gas Narcosis is the narcotic effect of gasses like Oxygen and Nitrogen under pressure. The effects are most prominent under 30m and commercial/technical dives doing dives to 40/50m on air tend to experience the effects most. (Narcosis is managed by adding an inert gas - in most gases Helium - to air to form a mixture referred to as Trimix (Helium/Oxygen/Nitrogen) this then produces an effect as if the diver is diving to a shallower depth and is referred to as Equivalent Narcotic Depth, in some cases Heliox (Helium & Oxygen) was also used)

High Pressure Nervous Syndrome is an interesting aspect of deep diving and used to be called Helium Jitters/Tremors as the accepted standard was that it was caused by breathing Helium mixtures under 150m. Some people hold this to be true and others claim that it has nothing to do with Helium but rather the pressure disrupting the flow of electric signals thru the nervous system.

What is interesting is that they found that if you used Trimix (Helium/Nitrogen/Oxygen) rather than Heliox (Helium/Oxygen) the onset happened later or not as severe. And the slower your descent is the slower the onset of the symptoms.

Some Docs to Read:

Narcosis - Relatively simple document on Narcosis

Narcosis - "Narcosis is not unique to nitrogen; however, it can occur with many of the so-called “noble” or inert gases, with the exception of helium. Add to this the fact that other inert gases each have their own brand of narcotic effects at depth, and you have a complicated picture for technical and commercial divers. One of these rare gases, argon, for example, has about twice the narcotic potency of nitrogen, but helium has very weak narcotic properties and is less soluble than nitrogen in body tissues."

HPNS - Relatively Simple doc on HPNS

HPNS - Very technical discussion on gasses, from a HPNS and Narcosis view point.

References:

Bennett, P.B. 1982b. The high pressure nervous syndrome in man. In: The Physiology and Medicine of Diving and Compressed Air Work. (P.B. Bennett and D.H. Elliot, eds), Balliere-Tindall, London. pp. 262-296.

Bennett, P.B. 1990. Inert gas narcosis and HPNS. In: Diving Medicine, Second Edition (A.A. Bove and J.C. Davis, eds.).W.B. Saunders Company, Philadelphia. pp. 69-81.

Bennett, P.B, R. Coggin, and J. Roby. 1981. Control of HPNS in humans during rapid compression with trimix to 650 m (2132 ft). Undersea Biomed. Res., 8(2): 85-100.


A program for cell motility assessment with a batch process function? Cell motility assessment is a branch of experimental biology or medical science. One example could be an assessment of treatment effects on sperm motility of an animal. The standard procedure involves taking film clips of sperm (or any other moving objects) through a microscope and measuring average linear velocity of particles on these film clips. The program used for measuring these linear velocities is important, and there are not too many choices to my knowledge. However, my knowledge might be limited.

I have previously used CellTrak for measuring sperm swimming speeds. The program works well, but lacks a batch processing function. As the assessment bases on a considerable number of replicates, I end up with 1000-2000 film clips to be analyzed and clicking my way through CellTrak is a tedious and irritating process. Also CellTrak licence costs a lot of money for such a poorly written program.

Therefore, my question is: Is someone aware of a similar program to CellTrak, which includes batch processing option, or even better, which works through command line and can be looped? Are there open source options or extensions to widely used open source programs (ImageJ, Bioconductor, etc.)? Please give a short tutorial/personal experience to the usage of the suggested program (if any).

ImageJ has several tracking plugins, a good one being TrackMate. Most of it's functions can be scripted in various languages and the Fiji distribution can also run in headless mode. It's open source and won't cost you any mony for a much lager feture set.

I personally have used ImageJ in headless mode scripted with its own macro language because it is relatively easy to learn.
TrackMate also should output average speeds for the tracks, if I remember correctly. Otherwise you would have to write a script to measure those from the tracking data. You can use the IJ macro language, Python, Java or one of the other supported languages.

In combination with a bash script wrapper for its headless mode I even use it in Makefiles to convert my tiff stacks to avi and put scale bars and time stamps on everything.

Hope this helps.


Are glands in human made up of muscles? I came across this idea while reading an excerpt of my textbook $-$

  Muscles move eye lid , tongue, beat the heart, popel food through gut, discharge wastes, squeeze out secretion from the glands etc.

But I don't understand how this happen ? Does glands really squeeze out hormones?

No they are not made of muscles. Glands are modified epithelial tissues. Glands are basically of two types Endocrine and Exocrine glands.

Endocrine gland

It is a gland that lacks a duct system. The secretions are directly
   poured into the bloodstream. They secrete hormones through exocytosis mostly.

Exocrine gland

It is a gland with a duct system. The secretions(sweat, sebum,saliva
   etc) are transported onto a surface of the body (e.g skin or lumen of GI tract) by
   ducts.Exocrine glands may be controlled by muscles at the duct level.

There are three types of exocrine glands based on the process of secretion of chemical substance at a cellular level$-$

Apocrine gland

It is a gland in which the apical portion of the secretory cells are distintegrated to release the chemical. e.g- Apocrine sweat gland

Holocrine gland

It is a gland in which the secretory cells are completely disintegrated to release the chemical.e.g.- Sebaceous gland

Merocrine gland

It is a gland in which the secretory cells remain intact and the chemical is
released through exocytosis.e.g.- salivary gland

Reference:

Wikipedia
ncbi


What is the appropriate method to send a strain? We are planning to send an ecoli strain to another lab. What is the appropriate way to do so. No MTA is required but the options seem to be using filter paper or sending a glycerol stock on dry ice.

I believe Addgene send strains as bacterial stabs.

This is the protocol from Qiagen.

  E. coli strains can also be stored for up to 1 year as stabs in soft
  agar. Stab cultures are used to transport or send bacterial strains to
  other labs. Prepare stab cultures as follows:

  Prepare and autoclave LB agar (standard LB medium containing 0.7% agar) as described in the last issue of QIAGEN News (1).
  Cool the LB agar to below 50°C (when you can hold it comfortably) and add the appropriate antibiotic(s). While the agar is still liquid,
  add 1 ml agar to a 2-ml screw-cap vial under sterile conditions, then
  leave to solidify.

  Vials of agar can be prepared in batches and stored at room
  temperature until required.

  Using a sterile straight wire, pick a single colony from a freshly streaked plate and stab it deep down into the soft agar several times
  (Figure 1).

  ￼￼￼￼￼￼￼￼￼4. Incubate the vial at 37°C for 8–12 h leaving the cap
  slightly loose.

  Seal the vial tightly and store in the dark, preferably at 4°C.

  When recovering a stored strain, it is advisable to check the
  antibiotic markers by streaking the strain onto a selective plate.

I believe if the shipping is <24hrs you could send a stab in ice.

Hope that helps

Ben


Is the poly(A) tail added while transcription is still underway? I read in Campbell that

  ....splicing and poly A tail addition may also occur while transcription is still under way.

How can the poly(A) tail be added while transcription is still going on?

It's slightly more complicated than the comments above indicate.

  Glover-Cutter, K et al. (2007) RNA polymerase II pauses and associates with pre-mRNA processing factors at both ends of genes. Nature Structural & Molecular Biology 15: 71-78

The authors present evidence that RNA polII pauses 0.5 - 1.5 kb downstream of the poly(A) site where processing factors are recruited (cleavage stimulation factor, or CstF, and cleavage polyadenylation specificity factor, CPSF). So the polymerase is still engaged with the template and the premRNA when processing is initiated, although it may not be actively elongating the transcript.

  "Localisation of the active polII-3' end processing complex well downstream of the poly(A) consensus sequence agrees well with the cleavage of Chironomus BR1 transcripts after 600 bases of downstream sequence has been transcribed. This model is also supported by the fact that efficient poly(A) site cleavage requires an intact RNA tether linking the poly(A) site with the downstream polymerase." (references are cited in the original).

It is a semantic question as to whether you call this cotranscriptional processing.

[Incidentally this is yet another example which contradicts the commonly-stated idea that evolution acts to optimise everything to conserve ATP - here we have the transcription process discarding the energy from approximately 1000 phosphodiester bonds per transcript.]

UPDATE
@WYSIWYG The polymerase goes past the site where the poly(A) will eventually be added, and makes another 1000 bases of RNA before pausing to recruit factors that are needed for the subsequent cleavage at the pol(A) site which now lies "behind it". After that the poly (A) tail is added at the newly created 3' end. So the initiation of poly(A) addition (in the sense that the cleavage is an obligatory first step in the process) is accomplished while the polymerase is still engaged. I agree that the actual addition of the poly(A) cannot in any way be considered to be cotranscriptional.

I was trying to make the point out that it isn't simply a case of the polymerase encountering the cleavage site and dropping off to allow a second unlinked process to take place.


Why can hair grow without limit while eyebrow cannot? I cut my eyebrow and it grows until reach a certain length. Hair can grow without limit.
Why can hair grow without limit while eyebrow cannot?

Hair actually does have a limit to its growth. All hair cycles between periods where it grows, and when a new stand appears, which pushes the older, long hair out. Hairs that are generally shorter, like eyebrows or arm hairs, have a shorter growth period before a new hair pushes the old one out. The hair on your head actually grows much faster than many other hairs as well, so with the longer cycle and the faster growth, it can grow to be much longer before being replaced.

I remember hearing that for many women (the cycle does vary from individual to individual, which explains why some men can't grow beards while others look like ZZ Top) the growth cycle ends between the waist and butt.

My speculation would be that hair on the head could grow for longer because there are more capillaries in the scalp, which might lead to more nutrients, higher cell turnover (like you see in dandruff), and hence more hair. That's just a guess, mind you.


Can a hydra get cancer? Because hydras have immune systems, telomerase activity, and Piwi-piRNA like cancer cells I wonder if they can get cancer?

Yes.

  Research in cnidarians shows that even pre‐bilaterian animals can develop neoplasia (Domazet‐Lošo et al., 2014). Two different species of Hydra have presented with tumour‐bearing polyps. The cells in these tumours were invasive, which suggests that metastatic capacity has ancient roots. Additionally, the tumours had several orthologues to tumour‐related genes in mammals and displayed parallels to the hallmarks of cancer in vertebrates. The proposed mechanism for tumourigenesis in Hydra is the accumulation of stem cells if they are not appropriately removed by programmed cell death (Domazet‐Lošo et al., 2014). Scientists have also identified several cancer‐like lesions in corals (Aktipis et al., 2015).

--From humans to hydra: patterns of cancer across the tree of life


Why does a "cascade" of events happen during signal transduction? I've been watching some videos on signal transduction and it says that because there are enzymes being activated by the signal, then there is a "cascade" which happens afterwards...I don't understand why?

Thanks.

There is one main reason: Amplification of the signal. You can start a signal downwards the cascade with relatively few receptors which need to be activated which allows even for weak signals to be translated into the nucleus.

This figure shows this for G protein coupled receptors (from here):

For example one molecule of cAMP can activate many molecules of pKA until it's hydrolysed which in turn can phosphorylate many other protein molecules.

For more information you can read the references articles (at least the introduction) and follow the references in them.

References:

Ultrasensitivity in the mitogen-activated protein kinase cascade
Noisy signal amplification in ultrasensitive signal transduction


Modeling inclusive fitness Consider a population of two altruist with coefficient of relatedness
$r$. The average inclusive fitness of this population will be
$w_{0} + br -c$. Like in this example, assignment of inclusive fitness
I've seen in books and articles follow the rule that you should
not count changes in inclusive fitness that result from the
action of your neighbor. For instance, in our example, the calculation
of average inclusive fitness include the increase in indirect fitness
to the actor (i.e., $br$), the costs (i.e., $c$), but do not include
the effects of the altruist behavior of the neighbor (i.e., $b$). That
is, the average inclusive fitness is not $(w_{0} + br -c) + b$.

My question is: why is it that, in inclusive fitness models, you do
not count changes in inclusive fitness that result from the
action of your neighbor? Wouldn't it make the model more accurate to
take into account the effects of your neighbor's behavior? In other
words, in our example, why isn't $(w_{0} + br -c) + b$ a better value
for the average inclusive fitness than simply $(w_{0} + br -c)$?

Note:

As @Corvus pointed out, if we include changes in inclusive fitness that result from the action of your neighbor, we will double-count benefits. Consider the example mentioned above once again of a population of two altruists with a coefficient of relatedness $r$:

If we write $w_1 = w_2= (w_{0} + br -c) + b$, the help of 1 on 2 appears as $rb$ in $w_1$ and as $b$ in $w_2$. If we write the fitness in the right way, $w_1 = w_2= (w_{0} + br -c)$, the help of 1 on 2 is only counted once (i.e., $br$ in $w_1$). However, I cannot help but ask "Why not count the help of 1 on 2 twice?" We are counting the help of 1 on 2 twice, but each time we are assigning it to different individuals, 1 and 2.

Generalities

There are plenty of ways at looking at phenotypes that affect the fitness of the carrier and of other individuals. One of them is group selection and another one is kin selection. Those two concepts are just two different ways of looking at the same processes. Now let's consider only the kin selection way of looking at these processes.

You can either consider the impact of the phenotype of a focus individual to neighbour individuals or the impact of neighbour individuals to the focus individual. Looking at it both ways, would yield to count the effect of your phenotype on twice. It doesn't make much sense to talk about the mean inclusive fitness of a population. You can only talk about the mean fitness of a population.

The confusion

The reason for all these confusion boils down to what $B$ and $C$ really mean. One of the issue is that you confuse $B$ and $b$, $C$ and $c$. The formulation $rB>C$ is a oversimplification of the reality. Hamilton did not use this formulation at first and interpreting $b$ as the benefit for the carrier might be misleading. It is important to understand Hamilton's rule in its original formulation and it is important to understand the evolutionary game theory that underlies the evolution of social traits.

What is Hamilton's rule

One cannot study the evolution of social traits under the kin selection framework if (s)he doesn't understand the underlying game theory. $rB>C$ assumes that the game we're playing is the Prisoner's dilemna. You can learn more about game theory. You can learn more about evolutionary game theory on wiki or in this book. Here is a Khan academy video on Prisoner's dilemna

Let's assume we are playing prisoner's dilemna. The fitness of an individual which cooperate is by definition $w_o + b - c$ (note the letters are not capitalized). If you cooperate and the other don't, your fitness is $w_o - c$. If you don't cooperate and the other does cooperate, you fitness is $w_o + b$. If nobody cooperates, your fitness if $w_o$. And by definition , $b>c$. Knowing the frequency of people that cooperate in the population $y$ and knowing and your probability of cooperating is $x$. Then, the level of altruism (frequency of cooperations) increases in the population if and only if

$$R\cdot\frac{dw(x,y)}{dx}>\frac{dw(x,y)}{dy}$$, where $R$ is the coefficient of relatedness which can itself be expressed as a correlation between the variables $x$ and $y$. $w(x,y)$ is the fitness of the the individual being altruistic with probability $x$ in a population where individuals cooperate with probability $y$ and $\frac{dw(x,y)}{dx}$ is the partial derivative of the fitness function with respect to $x$. By definition, $\frac{dw(x,y)}{dx} = B$ and $\frac{dw(x,y)}{dy}=C$ (capital letters).

The mean fitness of the population therefore depends on the frequency of cooperation $y$. Let's assume for simplicity that $y=1$ (equilibrium), then the mean fitness of the population is $w_o + b - c$ (note that the letters, $b$ and $c$ are not capital letter), and the variance in fitness is null. All individuals has a fitness of $w_o + b -c$ as all individuals are altruistic and perform action that has a negative impact on the fitness $-c$ and a positive impact on their fitness $b$.

In short

$b$ and $c$ in your question, correspond to $b$ and $c$ in my answer and not to $B$ and $C$. If you're playing prisoner's dilemna, then by definition, if everybody cooperate (no variance in the population), then everybody has a fitness of $w_o + b - c$ and the mean fitness is $w_0 + b - c$ (as there is no variance). Now the question of whether everybody ends up cooperating depends on $B$, $C$ and $R$.

In your edit, you write $rb$ and $c$ but you get confused about the meaning of $b$ and $c$. If you are playing prisoner's dilemna, when you cooperate with someone that is also cooperating, you inclusive fitness is $b-c + r(b-c)$ and if you cooperate with someone that is not cooperating, your inclusive fitness is $b-c + r(b)$.