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Examples of striking/pedagogic large dataset analysis in biology
This question belongs in "Cross-Validated" as well as "Biology"
I am looking for example datasets that I could use both for teaching and for my personal training, that would be good examples of very successful applications of in silico data analysis tools.
I am interested in tools like: k-means or hierachical clustering, principal component analysis, generalized linear models, or basic machine learning like class discovery & prediction.
Of course, if the data is available, that would be even better, but a simple figure in a paper would work as well.
What I mean by good is "fairly unambiguous and demonstrative", ie. the results could be, for example, a dichotomy of the dataset into two or three groups that make sense from a biological point of view (e.g. different tissues of the same organ, different times in cell development...).
A good example would be, for example, this figure:

(From Handschuh et al, Int J Oncol (2017) Copyright Spandidos Publications)
Rows are genes (microarray expression analysis) and columns are healthy (HV) or cancer patients (AML); clustering makes two large clusters appear.
It is a really good example because we can easily check that the two clusters match the two types of patient samples, which makes this clustering a good, pedagogic case study.
In other words I am looking for striking examples of how the visualized data makes perfect sense, if properly analyzed.


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Are cryovials really better than regular tubes for cryopreservation?
What is the rationale for using cryovials instead of regular, sterile centrifuge tubes for the storage of mammalian cells?
With a good aseptic technique and without touching the cap directly, there should not be a significant risk of contamination in regular microcentrifuge tubes. Is the plastic quality fundamentally different (in terms of leaching chemicals etc)? Both kinds of tubes are usually made of polypropylene so it's not obvious how they would otherwise differ.
There may be a difference when storing things in direct contact with liquid nitrogen (as regular tubes may leak), but many cells can be stored for years in a -80°C freezer, a temperature at which most molecular biology tubes are perfectly stable.

I feel like the best answer here is application-specific ease of use, but I could be wrong!

I do not have data to back this up, but can say that from experience, cryo vials are a much better solution for storing your valuable cells. First, their plastic is thicker, meaning they’re more sturdy and can handle a deep freeze much better. The killer feature is the screw caps, which means that they will never pop open accidentally due to mishandling or temperature changes (which has happened me with samples in microcentrifuge tubes). These screw caps also allow much more efficient storage in expensive cold conditions (liquid nitrogen will be best for cells long term) and easier retrieval from boxes that are freezing cold.
Microcentrifuge tunes may suffice but cryo vials exist for a reason.

Although, thicker plastic is disadvantageous for flash freezing.

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DNA of Different Species and The Fossil Record of Their Common Ancestor
Let me please be clear about something. I believe in evolution. The evidence and data are compelling and conclusive which makes it a very well-established theory.
I'm seeking a certain evidence (if it's existent) for evolution.
Assume we have two species (species A and species B) and we have full information of their genomes. I believe, by using their genomes, we can deduce when their most recent common ancestor lived (let's say X years ago).
Are their any instances in which this X number (which was produced mathematically) matched the age of some fossil (say species C) which has similar attributes to species A and species B? Any data about the ancient DNA of species C which may reinforce the evidence? Do we have something for humans and chimps?
I'm seeking a gourp of, arguably, unrelated quantitative data that point remarkably and decisively to common ancestor/evolution.
Thanks.

Possible duplicate of What could explain discrepancies between dates provided by the fossil record vs. the molecular clock?

One difficulty is that, even if a reliable molecular clock existed to predict when two species diverged, and if a fossil were found that seemed to match the phenotypic profile of a common ancestor, it would not be possible to conclude with certainty that it really is the common ancestor unless the fossil also provided DNA that could be compared to that of the two modern species.  It might be possible to find more modern examples though, for example by comparing the DNA of mummified Egyptian cats to that of modern cats.

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McFarland or O.D of culture what to use and what is the difference?
I am working on gram positive bacteria for which OD was reported and some reported mcfarland value. I am new to microbiology. i want to confirm the only thing that matters is cfu. please reply for what shoul I prefer
thank you.


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When gene editing are both chromosomes in a pair changed?
Sorry for the possibly confused question, my knowledge of genetics is limited to medical training only but I have a question.
Are gene editing techniques such as CRISPR used on both of the chromosomes in a pair or just on one of them?
Some of the general searching I have done suggests that it can hit one or both. Is there a preferred outcome?

Gene editing using CRISPR-Cas9 can result in both heterozygous and homozygous conditions. It is just the event of probability. But even if u get heterozygous line, making it homozygous is not very difficult. You just have to cross two heterozygous line and screen for homozygous line through markers.

Thank you very much for the response. In general is it preferred to gain a homozygous or a hetrozygous change or is it specific to the intended task?

It is specific to the task. If homozygous is not lethal, then i would go for homozygous line, as it will be easy to maintain. In case if you maintain heterozygous, then screening at each generation is necessary.


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Effects of horizontal vs. vertical motion on human body
I want to know if moving along a vertical plane in a circle differs in its effects on the human body from moving horizontally in a circle. Imagine a ferris wheel with a diameter of 50 metres. If a person on it was travelling at 10miles an hours, would they get less dizzy than a person travelling on a roundabout or carousel with a diameter of 50 metres travelling at 10mph?

The inner part of your ear contains fluids that controls how dizzy you feel, with no consideration for direction. I believe astronauts feel dizzy for the initial day or so, before their body adjusts to liquids, if that helps you visualize it. However, on earth, I’d be inclined to say that horizontal would be better due to gravity and the direction the normal force of the fluids is pointing, but I could totally be wrong. Hope that helps.


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Is this a Tabebuia impetiginosa – Pink Trumpet Tree Flower?
Is this a Tabebuia impetiginosa – Pink Trumpet Tree Flower? From Panama.

For tree identification questions please also include: 1) Pictures of the bark and leaves with an estimate of the size, 2) information about the environment within which you found the tree, and 3) an estimate of the size of the tree. All of these can be essential clues for identification. ——— If possible a picture of this plant in its environment could also be helpful. Thanks!

All I have is this photo.

Unfortunate — please edit your post to add whatever information you do have (e.g. ecological/environmental factors) and with luck someone will be able to help ...


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Found this insect in my bedroom. What is it?
I found this bug in my bedroom yesterday. I was afraid that it was a tick so I got rid of it after taking some photos.
The bug was found in Denmark and was about half a nail in size.
 Can somebody recognize it?

Photos with a less cluttered background may help; from what I can see though, I'm thinking a beetle belonging to the superfamily Scarabaeoidea (dung beetles and chafers -- I think we can eliminate stag beetles) but would like a closer view of the front of the animal (that we can't zoom in for any of the photos is a handicap).  Once we get those photos someone else will have a better chance of going deeper (it won't be me; I don't know the Danish fauna of the group I think we see here).

Thank you, @ArthurJFrost. I think that the background gives a perspective on the size of the beetle because it is not much bigger than the paint spatter. Do you still think the the pictures should be cropped?
I can't take more pictures of the beetle so if you don't think that anyone can determine the fauna from these photos, then leave your comment as an answer.


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Peak-calling in CLIP: What is the effect of RNA-concentration?
I hope it's ok to repost my question from 8 months ago from StackExchange:Bioinformatics, that is still in beta.
https://bioinformatics.stackexchange.com/questions/10730/peak-calling-in-clip-what-is-the-effect-of-rna-concentration

Question:
I would like to ask how RNA-concentrations influence the diverse CLIP peak-callers in their evaluation of peaks. The peak-callers I would like to understand are: Piranha, CIMS, Paralyzer and the one used in eCLIP (CLIPper). (After weeks of literature research I still can't find an answer!)

More details:
If the concentration of an RNA is too low it can't be cross-linked to the tested protein and no cross-link-peaks will be found, independent on the peak-caller and independent on whether there would be physicochemical interaction hot-spots (peaks). (obviously)
But what is the consequence of increasing the RNA-concentration from a "sufficient", to a high or extremely high level?
Which of the peak-callers will find more peaks on an RNA, the higher it's concentration and which peak-callers could be considered to be robust? (Robust in a sense that the score of the peaks is independent of the RNA concentration. Also the number of called peaks of a particular RNA-protein interaction depends mainly on the number of "real interaction-hotspots" and would not necessarily increase with concentration. )
Also let's assume the interaction frequency/density is quite uniform (no physical hot-spots): Then which peak-callers would almost necessarily start calling (more) peaks, the higher the concentration of the RNA was in the experiment?

Some considerations:
I know that there are many RNAs that don't interact with any proteins (in the databases) and that there are some RNAs that interact basically everywhere throughout their sequence to almost all tested proteins. (Potentially this is observed due to concentration dependencies!)
CIMS & Paralyzer, to my understanding, take the fitted crosslink-induced mutation rate at the specific sites to evaluate peaks. This ratio (mutated/total), in theory seems robust to me.
Piranha, as I understand, tries to fit the raw data to a sum of many individual binomial-functions, basically assuming the bulk of reads as background noise, only evaluating local peaks in read-counts relative to the background. This seems robust to effects of very high concentrations.
I would be thankful for any comments or references!


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What does $g_0$ mean for a centrifuge?
I'm about to make some Graphene Oxide and in the paper for Tour's Method it uses a centrifuge to isolate the solution. However it requires $319g_0$. What does this mean, and will a centrifuge with 3300rpm suffice?
https://www.researchgate.net/publication/234084399_Graphene_oxide_for_effective_radionuclide_removal

$g_0$ is the standard gravity.
You can look up the rpm-equivalent using a nomogram or calculate it yourself.
On some centrifuges you can switch between both. Some vendors provide conversion tables in their centrifuge's manual.


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What is known about major events of pre-LUCA evolution?
All organisms share many common biochemical features (including 20 amino acid genetic code) and are believed to have a common ancestor (so-called LUCA). According to wikipedia article, this common ancestor was quite complex organism with advanced biochemistry. Are there an knowledge about evolutionary events occurred during pre-LUCA era? Namely, which of biochemical pathways already present in LUCA were evolved earlier than anothers?

There is an awful lot of literature and debate about what happened before LUCA consequently here are some key words to read more about, first on Wikipedia, then on review papers and then on the many papers...

According to the Oparin-Haldane hypothesis life formed from an abiotic primoridal soup.
These abiotic building blocks were formed by lightning, meteorites, UV or other processes (see Miller–Urey experiment and the Murchison meteorite)
Not all metabolites we know today existed and many that do not have a use today existed (non-proteogenic amino acids on Wikipedia is an article/list on the topic).
The genetic code is a frozen accident (Crick), but many believe it went in waves and was rather promiscuous (e.g. 3rd position pairs came later) and may have included ornithine and norleucine, which were "usurped".
Ignoring the temperature/location aspect, from a chemical point of view, life arises from a hypercycle process and requires gradients.
DNA did not form as is. The ribose may have been glycol and the nucleobase glycine: many metabolites in nucleotide metabolism are able to base pair.
The RNA world came first, then DNA with chromosomes came later. This has an odd effect in that early enzymes had to be highly multifunctional.
To have evolution, you need compartmentalisation.
Tar is gloop that forms easily abiotically. Tarrification is a threat to early life, but could have helped with compartmentalisation.
Montmorillonite clay can act as a scaffold for DNA polymerisation.
Ribozymes are RNA enzymes. The most core cellular processes is still RNA operated: the ribosome and tRNAs.
Many cofactors are primordial and are attached to riboses, e.g. NADH, FADH and arguably cobalamins.
Proteins came later, but still today the catalytic power of protein comes from their cofactors or from a single amino acid (e.g. cysteine as a nucleophile).
Once you have potentially RNA-encoded proto-enzymes you can start building more of the useful compounds that were available in the primordial soup but were depleted. Most pathways will therefore form by retrograde pathway evolution.
Enzyme activities can only be evolved if there is a pre-existing activity to select. Luckily accidental activities happen, called promiscuous activities (this term a century ago had no sexual meaning and used mean "being muddled").
Modern enzyme are highly specific and evolved to work at a high turnover (fast) and work at physiological substrate concentrations. But still have promiscuous activities because the substrate chemistry is similar. If the enzyme has never see a given compound the enzyme will not be evolved to not act on it and maybe the activity has no detrimental effect (neutral). When an enzyme evolves into a new activity an intermediate form is seem with higher promiscuity. These are often argued to be primordial-like.
Many pathways have a common origin, for example the Krebs cycle and the branched chain amino acid pathways and actually experiments in E. coli have found that the enzymes can rescue "deficiency" (auxotrophies) in the other pathway albeit slowly. Therefore, as enzymes could act on different similar substrates a set of overlapping pathways arose (patchwork hypothesis).
LUCA is the last common ancestor. It was likely thermophilic and lived in thermal vents as seen in every documentary. If life started there is debated.
Early enzyme were like very unstable, very very slow and may have often broken good metabolites in a futile manner. Given the problem of segregating with a chromosome and the need for high promiscuity, they had to be multifunctional. Not to mention that similar-ish amino acids were used interchangeably —isoleucine and valine say are hard to tell apart to modern tRNA synthases, go figure for the early ones.
Enzymes generally fall under a few families, which share a common ancestor. Rossmann fold enzymes for example bind NADH. TIM barrels are a ubiquitous fold.

So to answer your question, between the RNA world and LUCA, enzymes were slow and were selected upon to remake the more complex metabolites in the soup and then the simpler ones and thanks to their poor selectivity a patchwork of pathways arose. Once simple core pathways started and all metabolites could be made, more complex compounds that cannot arise abiotically such as the amino acids tryptophan and arginine were made. The enzymes became more selective and stuff like straight chain hydrophobic amino acids were selected against and the genetic code was fixed. Then you can make stuff like chromosomes and everything happens fast and efficiently.
Caveat. Early life was messy, really not efficient (it had no competition) and happened a long time ago. As time machines are physically impossible, all this is conjecture (sensu Popper), but the words theory and hypothesis are used happily in the field of origin of life.

Nice and broad answer. Can you provide a reference for review/paper dealing with hypothesis of inclusion of ornithine into early genetic code? Or any recent (scientific) review about the genetic code evolution?

1970s paper asking why no homoserine, ornithine, citrulline etc.
nice paper on early code
re-analysis of Miller experiment with modern tech
norleucine
a very recent review of the different hypotheses.


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"Next generation" brain scanners, can they detect CTE?
I've just read the news that a "new generation" brain scanner is under development. I wonder whether they can detect chronic traumatic encephalopathy. I haven't been able to find the paper about these new brain scanners.
So is it possible to detect CTE (during life of the patient, i.e. non post mortem) with this new device, and if not, is there any chance it will be possible in the future?

I do not know the details of the innovation, but it's based on MEG. MEG is a complementary technique similar to EEG, sesitive to magnetic fields instead of electrical fields (hence the 'M' in place of the 'E'). It is used to read population brain activity in real time, and is less useful as a tool to assess structural changes. MEG is currently mainly used for research purpose, and I don't see this innovation changing that. CTE could manifest in longer conduction delays or disruption of communication, but given that MEG can only access certain areas of the brain, it is probably not going to be very useful in general. I can imagine it being useful for some very specific CTE cases.

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Why isn't suppression of immune system for organ transplant not as dangerous as AIDS?
I've read that when AIDS symptoms show up, life expectancy is about two years if no treatment is applied. On the other hand, I've also read that people having an organ transplant need to take immune system suppressors for the rest of their lives so that their body does not attack the transplanted organ. So, if I understand well, it is a sort of induced AIDS. I do not understand then how it is possible for people with an organ transplant to live more than about two years.
Can someone explain with details the differences between the suppression of the immune system by medicine for organ transplants and the one due to AIDS?

Patients receiving immunosuppressive drugs do fall into the same category as patients with HIV-related acquired immunodeficiency - that is, they are all immunocompromised and face similar risks of infection, cancer, etc. The difference emerges over time: when the immunosuppression is controlled and monitored, a patient can retain some immune function, and a physician can help a patient adjust and rapidly respond to opportunistic infections. Drugs can be given in calculated doses; viral infections which disable the body's ability to stop viral infections typically only get worse. To elaborate:
HIV causes immunodeficiency by killing T cells. Firstly, it preferentially infects CD4+ T cells. This process can trigger an inflammatory response and (1) kill the infected T cell, as well as (2) bystander cells. Once the virus has successfully infected a CD4+ T cell, it can happily produce more viruses without killing the cell, which is how the infection can spread - or it can (3) rupture the cell membrane and kill the T cell. Finally, CD8+ T cells can notice that CD4+ T cells are getting infected by a virus and start (4) killing CD4+ T cells.
Immunosuppression after organ transplant can be more specific. It is typically achieved via a combination of drugs which can (1) reduce immune cell activation, (2) slow down immune cell proliferation, or (3) block the activating receptors on T or B cells. The amount and type of suppressants depend on the phase of treatment: induction of immunosuppression, maintenance, or treatment of transplant rejection.1 These drugs are also often administered alongside preventative antimicrobial drugs.
The immunosuppressants which are administered during the maintenance phase - i.e. for the rest of the patient's life - are often the drugs which dampen immune activation instead of eradicating all T cells, and are given at much lower doses. For example, calcineurin inhibitors block the [calcineurin-NFAT pathway];2 when this pathway is blocked, production of immune activators like IL-2 is reduced, and reduces T cell function.
TL;DR: "induced AIDS" is milder and more controlled than actual AIDS, and doctors work very hard to keep patients within a safe range of immune function/suppression.
PS: Good question! Made me think :) I've written some papers on organ transplantation before so am happy to do some digging to add sources.


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Will dissolved proteins pass through a 0.2 micron filter?
Given that there may be exceptions, can you usually expect protein to pass through?

Many proteins will pass through a 0.2 micron filter. If the proteins aggregate or if they stick to the filter material because it is charged, they may not.
Barring the above, a 0.2 micron filter will allow proteins up to 200kd to pass through.  There are some proteins that are larger.
Editing with some source material.
Nice Presentation on Pore Sizes and Membranes Here
Graphic from that presentation:

Stanford ppt link is broken :(

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What kind of changes "stays" in the neuron after the nervous impulse happened?
I often see in neuroscience textbooks about how the brain controls everything in the body with different tracts and etc, and it seems that information is always being transmitted, like there's no fixed place in which they are stored. So after the depolarization and repolarization what happens to the neuron itself? Does it depend on which neurotransmitter stimulated it? And extending a bit the question, what is exactly the difference between being stimulated by two different neurotransmitters?(supposed that the neuron has receptors for both and the neurotransmitters are the excitatory type).

TL;DR: There are many ways a neuron can change after a neural impulse happens including calcium influx, long term potentiation and depression, and G-protein coupled receptors. While not an exhaustive list by any means I'll give a brief summary of some mechanisms I know best.
Calcium Entry
There exist calcium channels that open in response to a variety of signals be it voltage depolarization (voltage gated calcium channels), neurotransmitter acetylcholine (Nicotinic-Receptor) or Both depolarization and Neurotransmitter binding (NMDA receptor). There is much more calcium outside the cell than inside the cell. Once inside the cell calcium binds to EF-hands in various calcium-binding enzymes like calmodulin. When calcium binds to the EF-hands of the calmolulin protein it activates and from there can interact with the other enzymes responsible for cell signaling and the effects can be quite diverse depending on what the neuron is responsible for doing and the specific signaling cascade it sets off.
LTP/LTD
I'll focus on the NMDA receptor(excitatory Glutamate/Glycine receptor) in the CA1 region in hippocampus. LTP (or Long Term potentiation) occurs when a synapse (connection between neurons) becomes stronger, meaning the post-synaptic neurons response to the same stimulus from the pre-synaptic neuron is stronger after LTP has occurred. LTD (or long term depression) is the opposite effect where a neuron's response to the same stimulus is weaker after LTD.
The LTP whole process is dependent on calcium entering through the NMDA receptor channel. When both glutamate and glycine are released pre-synaptically they open the channel,  allowing calcium ions to flow into the cell. However, If the voltage in the post-synaptic membrane is too low, Magnesium will get stuck in the channel blocking calcium (and the other ions too!). If the neuron has previously been stimulated and depolarized, by another neurotransmitter/receptor system like AMPA the voltage will be positive enough to pop the magnesium out of place and allow calcium into the cell.
Once calcium is in the cell it is bound to calmodulin which then binds to CaMKII (an enzyme activated by the calcium/calmodulin complex). This will cause a long and complicated signaling cascade which results in AMPA (the other excitatory glutamate receptor in the post-synaptic region) to be phosphorylated causing it to be more active. Furthermore the signaling cascade can cause an increase in AMPA receptor creation and subsequent insertion into the post-synaptic membrane. This of course results in LTP.
Many rules in biology one quickly finds exceptions and caveats to nice rules of thumb (In fact I learned of a few just by preparing this answer!) LTD (long term depression) can occur in the hippocampus as well, and is dependent on the influx of calcium! As paradoxical as that seems, there is a negative feed back loop dependent on the levels of calcium ions inside the neuron, such that strong pre-synaptic stimuli create LTP (potentiation) and weaker (lower frequency) stimuli cause LTD (depression) and rare or intermittent stimuli cause no response. (see this and this for reference).
G-Protein coupled Receptors
G-Protein coupled Receptors are more of a general family of proteins than a specific example. They are metabotropic receptors (meaning they do not allow Ion's to flow through them). Rather when bound they release an G-Protein, which like calmodulin binds to other enzymes and activates them allowing them to do their job. They  can respond to many different neurotransmitters (or more generally ligands) and can do lots of different tasks depending on the  on what type of G-Protein it releases.
I'll give the muscarinic(M2) receptor for acetylcholine as an example. This receptor is found in the heart and responds to acetylcholine release from the Vagus nerve. When the GCPR binds to the acetylcholine it releases its G$\beta$ unit and it binds to potassium ion channels in the heart. This causes the outward flow of potassium ions thus lowering the voltage( hyper-polarizing the heart cell).
Furthermore G-coupled proteins can even induce changes in how many are present in the membrane (i.e. they are self regulating). These are produced by internal signaling cascades and are thought to be the reason for tolerance of drugs. Take for example the $\mu$-opioid receptor (activated by morphine, heroine and other similar compounds). These drugs will induce changes in how well the protein response to the morphine and if enough exposure then the cell will actually take the receptor back into the cell body and thus off the membrane in a process called endocytosis. (source here)
Literature reviews worth reading include (all open access):

Calcium signaling
NMDAR meditated LTP/LTD
GPCR's

Excellent!!! Really liked your approach and all the links provided! I'll look into all of this


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Physiologically, how can stress/anxiety cause neuropathy?
According to the Mayo Clinic, stress/anxiety can cause "pins and needles" (neuropathy) sensations all over the body.
But how can this be? My understanding of the sensory pathway is that sensory receptors (nerves) fire "pins and needles" signals to the brain whenever there is a lack of blood flow to them.
So does stress reduce blood flow to nerves? Is it a chemical reaction, perhaps where stress releases hormones that prevent the nerves from functioning correctly? Something else?
I'm looking for a biological/physiological/scientific explanation of what stress does to make nerves misbehave.

Something related http://biology.stackexchange.com/questions/24492/how-does-anger-relate-to-blood-pressure/24498#24498

Thanks @Jvrek (+1) - thats a pretty darned good answer to that question! So, can you (please) confirm my newfound understanding here: that stress produces various hormones that in turn regulate blood flow/pressure, which can then (under the right circumstances) reduce bloodflow to individual nerves? Am I on track or way off? Thanks again!

pins and needle sensations are not always pointed to lack of blood in nerves. http://biology.stackexchange.com/questions/24555/what-causes-feeling-of-feet-falling-asleep-to-be-delayed/25807#25807

Thanks again @Jvrek (+1) - I understand; however can you at least confirm that stress-induced neuropathy is chiefly a result of hormones which interact with neurons and cause them to malfunction? Thanks again!

There is a big difference between a pins-and-needles sensation and *neuropathy. Are you sure stress can cause neuropathies?

I wouldn't make drastic assumptions about cause-effect relationships or whether it is even neuropathy.  Anxiety may cause neuropathy-like symptoms or the symptoms may be a side effect of another biological process that is causing the anxiety. My personal theory is that there is something electrical going on, because magnesium is known to help mitigate anxiety symptoms.


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How and where do nerves share pathways to the brain?
I am interested in understanding how pain receptors send signals to the somatosensory cortex (the part of the brain that registers various nerve signals such as pain, presure, temperatures, etc).
Specifically, I'm interested in whether or not two distinct nerves/receptors share, or don't share, "channels of communication" to the cortex.
For example, say I touch the very tip of my finger to a hot stove, and, say, only 10 "temperature-sensing nerves" are triggered to transmit pain signals to my brain:

Do each of these 10 nerves send 10 distinct signals to my brain, traveling down 10 completely 10 channels?; or
Do each of these 10 nerves send 10 distinct signals to, say, my spinal cord, where they are then combined into 1 large pain signal and forwarded on to the brain?; or
Something else entirely?

Here's an awful illustration of the question I'm asking:

In Scenario #1, both nerves send 2 distinct signals to the brain, and those signals are kept distinct/isolated throughout the course of their entire journey to the brain.
In Scenario #2, both nerves send 2 distinct signals to the spinal cord, but the spine then combines them and only forwards 1 signal on to the brain.
I''m sure in reality it's neither of these scenarios, and is something much more complex. But I'm curious and want to know!

The first layer of sensory integration from neural interconnection lies in the spinal dorsal horns (for somatosensory stimuli), and the spinal anterolateral system (for painful stimuli). It resembles option #2 much more than option #1.
Addenda: Since you are asking a lot about neuroanatomy and neurophysiology, I suggest those 2 beginner books:

Neuroanatomy Text and Atlas, John Martin
Neuroscience, Dale Purves


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Can signals travel "backwards" in the sensory pathway?
My understanding of the "sensory pathway" is that its a linear, directional pipeline as follows:

Nerves (fire various signals depending on the type of sensors they are)
Fibers (transmit signals from nerves to spinal cord)
Spinal cord (transmits signals from fibers to brainstem)
Brainstem (transmits signals from spinal cord to brain)
Brain (the somatosensory cortex register signals as pain/pressure/temperature/etc.)

So again, my understanding is that sensory nerves are 1-way sensors, and that once they fire a signal, its 1 and only ultimate destination is the brain.
So, as a precursor to my question, if anything I have stated is incorrect, please begin by correcting me!

I read that pinched nerves in the back and neck can cause neuropathy ("pins and needles") all over the body: hands, feet, face, etc.
But how can this be? If my understanding of the sensory pathway is correct, then a pinched nerve in one's neck should only send "pins and needles" signals directly to the brain; it should not at any point forward/relay signals on to any other areas of the body.
To state that a pinched nerve in one's neck could possibly cause neuropathy in their arm, then that insinuates there is some connection between the pinched "neck nerve" and the nerve(s) in the arm that are experiencing the pins and needles sensation.
In fact, unless I completely misunderstand the entire sensory pathway and how pain signals transmit, this implies that a pinched nerve sends signals out to the spinal cord, down the spinal cord and into, say, an arm, and that the sensory receptors in the arm subsequently react to these signals.
How is this possible?!? Is there some kind of feedback mechanism at play where nerves in the neck and back can relay signals on to other areas of the body, instead of just feeding directly into the "spinal cord => brainstem => cortex" pipeline?

Individual nerves are one-way, but there are plenty of nerves running both ways along the "pipeline"

Thanks @Luigi (+1) - however I'm not following you. First you say that individual nerves are 1-way, but then you say nerves run both ways...which is it?!? Are there certain types of nerves that are bidirectional? If so, what are they called? How would they fit in to my scenario of pinched neck nerves causing neuropathy in an arm or other area? Physiologically, how does all this map out? Thanks again!

By "plenty" I mean that there are more than one. Think of a four-lane highway. Four run north, four south. Each individual lane goes in only one direction, but the highway carries cars in both directions.

Thanks again @Luigi (+1 again) - I feel like you're holding back! Don't be afraid to hit me with some science here! I get your highway anology...but does that mean that the 4 lanes going back are for motor nerves? Or can a sensory nerve handle "traffic" going both ways?

So, continuing my metaphor, pinched nerves would be an earthquake destroying a few lanes of the highway. You can see ill effects in either or both directions.

Motor nerves control your movement (brain->muscle) and sensory nerves send info to the brain (extremities->brain). No single nerve handles two-way "traffic"

Right @Luigi (+1) - that's what I figured. So you see, your analogy and reasoning isn't quite adding up (respectfully, of course). You say that sensory nerves can only handle "extremity -> brain" traffic. So if I have a pinched nerve (of any kind; motor or sensory) in my neck, how can that possibly send out signals that sensory nerves in my arm respond to? Thats the root of my question: How do sensory nerves in my arm "read" signals sent to them from my neck?!? It just doesn't make sense!

Let us continue this discussion in chat.

Reverse signals (dendrite -> axon) do occur in neurons, and are called back propagating action potentials (bAPs). However, whatever role bAPs play in the nervous system at large is subtle/small enough that we don't really understand them at all.
In any case, as @luigi points out, pinched nerves don't have anything to do with bAPs. The reason why a pinch in one place (the neck) feels like it has an effect in another place (the arm) is because some neurons trace long (on the order of several feet) pathways through the body. Ultimately, the sensory input of everything below your head passes through neurons in your neck at some point. If there is a pinch in the neuron in your neck that relays sense information from your arm, that neuron in your neck can activate spuriously, even in the absence of any stimulus acting on your arm. In that case your brain will interpret the spurious activation of that neck neuron as being the result of some kind of strange arm stimulus, and so you feel pins and needles.
See here for more information on the sensory cortex in your brain and the "sense image" it maintains of your body.
Edit
To clarify what I mean by a "pathway",

The part marked "proprioceptors or mechanoreceptors" is what's buried in your skin. If you poke a mechanoreceptor, it evokes a signal in the neuron marked "first-order". In some cases, that first-order neuron will reach all the way to brainstem (as in the picture above), and in some cases that first-order neuron will interface with an intermediate neuron in the spine, but the effect is the same in any case. A first-order neuron stimulates a second-order neuron, which in turn stimulates a third-order neuron, etc., all the way until the original signal arising from the mechanoreceptor reaches the somatosensory cortex. A pinch in any of those first, second, etc. order neurons will potentially send spurious signals to the somatosensory cortex.
Second edit:
Rereading your question, I think a lot of the trouble that you're having has to do with your understanding of how the brain assembles sense information. In order to feel pain in your arm, it is not necessary for anything to be happening to the arm itself. Your arm could be perfectly healthy and normal, but as long as your brain is receiving a signal equivalent to the one produced by a damaged arm you will still feel the same sensation of pain.

Thanks @tel (+1) - however your answer completely pummels my understanding of this "sensory pathway"! My understanding is that nerves connect to fibers, which connect to the spinal cord. The spinal cord connects to the brainstem and then the brain. When you say "Ultimately, the sensory input of everything below your head passes through neurons in your neck at some point.", this seems to imply that the spinal cord connects back to fibers/nerves and then the brainstem after that... Can you confirm all the major elements of this pipeline/pathway?

...And perhaps elaborate on how a signal sent from a neuron in my hand passes through a neuron in my neck? Again, as I understand the pathway, any neurons in my neck would connect to the spinal cord, then the brainstem, then the brain; and a nerve in my arm would never send signals that pass through a neuron in my neck. Thanks again!

@smeeb tel means that your spinal cord passes through your neck, so you can pinch a nerve in your spinal cord (which happens to be in the part of your spinal cord that passes through your neck) and it could affect the sensation your brain feels in your arm. Please look at this discussion for more

Pinching a nerve in a different part of your neck, i.e. trachea or throat, will not and can not have any effect in an unrelated area (arm)


text:
How many different chains exist within a specific pdb file?
More specifically, if we want to understand the different chains within a protein, is it enough to look at the fourth column of all the lines that start with "ATOM" in a pdb file, and see how many different chain identifiers exist there?

In the PDB format the lines with atoms can start either with ATOM or HETATM.
Chain ID is in column 22, i.e. it is 22nd character of a line that starts with ATOM or HETATM. (Programs that support 2-character chain IDs use columns 21-22 − it's a popular extension of the PDB format).
Yes, the number of different chain IDs is the same as the number of "chains" in the PDB file.
But note that the "chain" from the PDB format is not necessarily a real chain (polymer). It may be a bunch of water molecules or something else.

Thank you for your answer. It’s less confusing now.


text:
How is the rate of transcription influenced by temperature?
How is the rate of transcription influenced by temperature? More precisely, I am looking for an article who quantitatively measured the rate of transcription of an "average gene" and show how this rate is influenced by temperature.
On this question @Chris found this article where such measurement were performed but they were using some arbitrary unit (as it as been pointed out by @shigeta here) that cannot be related to any comprehensive unit such as "mole of amino acid per hours" or something like that.

Also see this answer

If your looking at transcription then your talking about RNA POLYMERASE.
And there are many variants. Here's a good Nature paper that discusses temperature and RNA Pol
http://www.nature.com/ncomms/journal/v1/n6/full/ncomms1076.html
And another:
http://www.ncbi.nlm.nih.gov/m/pubmed/12729734/
I couldn't get full access to this JBC paper but I think the answer would be clearly in here, prob worth a look
M. Chamberlin and J. Ring. Characterization of T7-specific ribonucleic acid polymerase. 1. General properties of the enzymatic reaction and the template specificity of the enzyme. J Biol Chem. 248: 2235-44 (1973)

Very nice. Thanks a lot. I found the answers I needed in the Chamberlin and Ring article. There's a similar question here if you feel you can answer it $\ddot \smile$


text:
Additive genetic variance with $n$ loci
The genetic variance of a quantitative trait (the quantitative trait in question is fitness) can be express as the sum of two components, the dominance and additive variance:
$$\sigma_D^2 + \sigma_A^2  = \sigma^2$$
, where $\sigma$ is the genetic variance, $\sigma_D^2$ is the dominance variance and $\sigma_A^2$ is the additive variance. $\sigma_D^2$  and $\sigma_A^2$ are given by
$$\sigma_D^2 = x^2(1-x)^2(2 \cdot W_{12} - W_{11} - W_{22})^2$$
$$\sigma_A^2 = 2x(1-x)(xW_{11}+(1-2x)W_{12} - (1-x)W_{22})^2$$
, where $W_{11}$, $W_{12}$ and $W_{22}$ are the fitness of the three possible genotypes and $x$ and $1-x$ give the allele frequencies.
Question
The above definition makes sense for one bi-allelic locus only.

How are $\sigma_D^2$, $\sigma_A^2$ and $\sigma^2$ defined for $n$ bi-allelic loci? Is it:

$$\sigma^2 = \sum_{i=1}^n \sigma_i^2$$ $$\sigma_A^2= \sum_{i=1}^n \sigma_{Ai}^2$$ $$\sigma_D^2  = \sum_{i=1}^n \sigma_{Di}^2$$
Here is a related question

Not in general -- there can be linkage disequilibrium among the loci. For instance, say that there are two di-allelic loci, $A/a$ and $B/b$, and that the frequencies of the $A$ and $B$ alleles are both $1/2$ and that they have the same effect on the trait, with no dominance. If all haplotypes in the population are either $Ab$ or $aB$ (with no $AB$ or $ab$ haplotypes), then the genetic variance at each locus is high, but the total genetic variance for the trait is 0!

Thanks for your answer. Yes that totally makes sense. So the formula would be
$$\sum_{i=1}^{n} \left( \sigma_i \frac{\sum_{j=1}^{n} 1-\text{cor}(i,j)}{n} \right)$$
, where $\text{cor}(i,j)$ is the correlation between the two loci... or something like that…?


text:
Biostatistics: Pollen dispersal directionality
What Information am I looking for?
Think about a tree that is sending pollen all over the place. Because of wind, most pollen grain will go toward one direction. Imagine, we split the 2D area around the tree where pollen grains fall into two half disks of equal size. We chose the disks so that the number of pollen grains falling into one half-disk is minimized and the quantity of pollen falling in the other half-disk is maximized.
The information I need is what proportion of pollen grain falls into each disk? Is it $\frac{0.5}{0.5}$ (in which case the wind would have no effect) or is it something like $\frac{0.8}{0.2}$?
Where to get the information from?
I was reading this paper about pollen dispersal directionality and was trying to extract the info I need.
On pages 4 and 5 they explain their analysis under the section statistical procedure. More specifically, in the first paragraph of the 5th page, they seem to describe the meaning of the parameters that are trying to estimate. One of them is the so-called directionality parameter $\delta$. I don't understand how to interpret this parameter $\delta$.  This parameter is part of a logistic regression I think (although the authors do not characterize it as such) of "mating success" $y$ against variables $d$ ("distance") and $h$ ("height") and an angular variable $a = \cos(\alpha_0 - \alpha)$.  ($\alpha_0$ is the "presumed prevailing direction of effective pollen dispersal," which apparently is not estimated from these data.)  The corresponding parameters of the model are $\beta$, $\gamma$, and $\delta$, respectively, hence
$$\phi_j = \Pr(y_j = 1) = \frac{\exp\left(\beta d_j + \gamma h_j + \delta a_j\right)}{\sum_{k=1}^r \exp\left(\beta d_k + \gamma h_k + \delta a_k\right)}$$
where the index $j$ ranges over all $r$ "male(s) in the neighborhood."
Their Results
Using maximum likelihood, they found that the directionality parameter, $\hat\delta = 0.56$ (SE = $ 0.15$; bottom of page 6).
Question
How can I relate their finding to the information I need (even if it is just a rough approximation)?
I think I have to understand the so-called directionality paramter $\delta$ Can you help me to interpret the meaning of this parameter $\delta$?

Reference:
Burczyk, Adams, & Shimizu, Mating patterns and pollen dispersal in a natural knobcone pine ... stand.  Heredity 77 (1996) pp 251-260.

Not receiving any answer on Biology.SE, I asked the same question here on Mathematics.SE but sadly, the question doesn't receive any attention!

You might want to have this migrated to math. There are quite a few people their skilled in probability and stastitcs. Also, if we are minimizing and maximizing the two disk, it would seem strange 50/50 has a chance.

@dustin I would say this question is more related to biology as it is asking about the biological meaning of the δ parameter

@CactusWoman in the information I need section, it is a math question.

@dustin, if it is going to be moved, I think statistics might be more appropriate because it is about experimental design. That being said, the question is probably alright in biology.

@dustin Biology involves math, especially population genetics. This question should not be migrated in my opinion and is perfectly relevant for Biology.SE.

@cagliari2005 pretty much every subject out there has some math component but who offers better help in mathematics? Peoples whose only job is mathematics or people who learn math when they need it?

Even before, opening this question on Biology.SE (and therefore before positing the same on Mathematics.SE), I actually posted my question on CrossValidated.SE but it received little attention and I ended up deleting the post (to avoid cross-posting) to open this post on Biology.SE. Thank you guys for your help!

(This isn't an answer, but hopefully it will help get it past the experimental design into just solving the equation.)
Where did you get that α0 was not determined from their data? On p. 10 (256), they state, "The prevailing direction of effective pollen dispersal within neighbourhoods (a0) that gave the best ﬁt of the model was 91 degrees from north (nearly due east)."
The best-fit δ parameter value of 0.56 (which determines the size of the effect of the angle between the male tree and the wind) is also determined by their model (table 1, model 9) based on their sample set.
This math is too much for me to solve, but here is how I would go about getting through the experimental setup to just solving the math equation:
Since you're only looking for the effect of wind/directionality, you would set the tree height and distance between trees to be equal. So βd and γh would remain constant and cancel out when you solve for a.
Then you want to determine what angles would give you the highest and lowest pollen counts. Set a0 to wind direction and aj to the angle between a0 and the half disk. The highest pollen count would happen at aj = a0. The lowest pollen counts would happen at aj = (a0-180) or (a0-π or whatever unit of angle is appropriate. Stupid trig.).
With those settings, it should be possible to determine the values of ϕ where aj = a0 and where aj = a0-180.
Then you can get the proportion of pollen grain falls into each disk by finding the ratio of ϕj(a0-180) / ϕj(a0).
Assumptions:
1) There's a linear correlation between ϕ, "the mating success (i.e. fertility) of each outcross male in the neighbourhood" and the distribution of pollen grain dispersal.
2) That a0 ("The prevailing direction of effective pollen dispersal within neighbourhoods") is entirely due to wind. Here I could see terrain being a factor, which would make the effect of wind xδ, such that x<1. If this were the case, the calculated ratio of high pollen / low pollen would be higher than actual.

The looks great. I'll have to reread that tomorrow morning with a fresher mind! +1 in the meantime. Let me know if you can come up with an actual number for the proportions in the half disks. Thank you so much for your help.


text:
What is meant by increased vagal tone?
Smiling ,for example,can stimulate vagus nerve as written in the following quote:

Whether it’s through mindfulness, paced breathing, sports, sex or
simply smiling, increased vagal tone is important for good health and
wellbeing. There is a lot of hype online and some of it may be over
the top. But reduced stress and greater relaxation are safe for
everyone and have positive effects for our body and brain.

In above quote vagus nerve is stimulated by increased vagal tone.
My question is - What is meant by increased vagal tone ? Can pain also stimulate vagus nerve and increase vagal tone ?

Welcome Dheeraj. I'm not sure that this site is the best fit for this question. We have a [psychology.se] sister-site as well as a [medical.se] one. You might want to check them out, but before posting, ensure to take their tour and read their help centres to ensure that your post is on-topic.

@JiminyCricket ok.

Hi, that was supposed to read: [medicalsciences.se] in my previous comment.


text:
How does an antisense RNA molecule restore protein function in CF patients?
I am researching a treatment for cystic fibrosis (CF) called Eluforsen and I am trying to understand the mechanism by which an RNA molecule can restore proper protein function. In many research articles I come across the same sentence:
"Eluforsen, is an antisense RNA oligonucleotide designed to bind specifically to the mRNA region around the F508-encoding deletion and to restore CFTR protein function."
But I cant find any literature explaining how an antisense RNA molecule can restore function of a protein on its own. When I think of antisense RNA I think of  RNA interference not restoring protein function.

Please [edit] your question to include information for at least one of the references for the quote. This is expected on this site, is generally considered good practice in scientific communication, and will help other users understand the context for the quote. ——— In general, it might be beneficial for you to take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site and [edit] your question accordingly. Thanks!

https://www.nature.com/articles/nbt0102-47

The root of the problem for a majority of cystic fibrosis patients is that they have two defective genes for a particular protein and at least one of these genes is defective because it is missing a 3-base codon for the amino acid at position 508 of the protein.
Eluforsen, also known as QR-010, is a somewhat modified 33-base RNA molecule.  The bases in it are complementary to an area centered on the codon for amino acid 508 of the normal mRNA (messenger RNA) for the protein. Since the defective mRNA is missing 3 bases in the middle of this sequence, eluforsen binds to only 30 bases of the mRNA and has an unbound loop of three bases in the middle, as suggested by the wiggle in this diagram:

[image from SEC]
Such a double-stranded stretch of mRNA is abnormal, of course, but the effect of its presence at least some of the time is to cause the mRNA to undergo repair in the duplex area in a manner which makes a break in the main strand opposite the loop and inserts RNA bases that are complementary to the three "excess" bases present in the eluforsen loop.  Since these three bases are complementary to the normal mRNA bases at that point, the effect is to transform the defective mRNA into a normal mRNA.  When the repaired mRNA is translated by a ribosome, a normal protein is produced, and some of the symptoms of the CF condition are reduced because of the presence of normal protein.
The mechanism which causes the mRNA to be repaired in this manner is not yet well understood(1).  The condition improvement from a complementary mRNA fragment was noted back in 2004.(2)  One hypothesis is that RNAse H is involved in the repair.(1)  Some further information about QR‐010 effects can be found towards the end of reference (3).
(1) Matos & Matos, 2018
(2) Zamecnik et al., 2004
(3) Alton et al., 2016


text:
Are Hsp70 proteins only activated in response to heat shock?
Hsp70 proteins are chaperones that assist in protein folding in my plant physiology textbook it says the Hsp70 proteins were discovered by inducing heat shock. But do they only work in response to heat shock stress?
I know these types of proteins are found in many organisms but I am interested in how they assist on protein folding or stress response in plants specifically.

The wikipedia Hsp70 article answers the headline question.

They get upregulated under stress, but will be expressed normally. In effect the name is deceptive...


text:
Ideas for microbiology lab. Antimicrobial properties of cutting boards
I am an undergraduate student in Biology and I am trying to design a microbiology lab that will takes 3 weeks to carry out (1-2 day each week). I am going to examine the antimicrobial properties of cutting boards. So far I have determined that I will use bamboo vs plastic and dish-soap vs disinfectants. I will be using two bacterial strains E.coli and S.epidermis.
Week 1: MIC (Minimal Inhibitory Concentration) assay of disinfectants and soap and prepared LBA (lysogenic Broth Agar) plates for viable counts during week 2.
Week 2: Inoculated cutting boards wait 30, 60, and 120 mins wash with various products then swab cutting boards with sterile swab, place swab in test tube with saline vortex and plate the resulting liquid on LBA. Count CFU (colony forming units) during the week.
Week 3: This is where I'm stuck the experiment has to last three weeks but I'm not sure what other tests I could carry out on the third week.
Any advice would be greatly appreciated thank you.

Did you plan on doing statistics to compare your treatments?  Statistical analysis could be your "Week 3"

I do plan on doing statistical analysis but that will be done outside the lab I was looking for another type of assay or different types of treatments I could do in lab. Thanks, @Dirigible

In my experience in biology, usually if everything goes as well as possible then Week 3 is for repeating the thing that went wrong in weeks 1 or 2. If everything goes normally, then Week 3 is for repeating Week 1 and Week 4 is for repeating Week 2.

I am afraid that however much one sympathizes with the problems of setting up laboratory classes for students, that is not included in the remit of this site, which is to answer questions about biology itself.


text:
Amino acid substitutions near the receptor binding site HA protein in type A H3N2 influenza strains?
I have read the scientific paper, "Substitutions Near the Receptor Binding Site Determine Major Antigenic Change During Influenza Virus Evolution" by Björn F. Koel et al (http://science.sciencemag.org/content/342/6161/976).
In the paper, important positions to influenza antigenic drift include positions 109-301, with special emphasis on sites 133, 144, 145, 155, 156, 158, 159, 189, 193.
However, nowhere in the paper does it specifically mention which positions are part of the receptor binding site and which are close to it.
The range (109-301) is a bit broad since it includes amino acid positions that are unimportant to antigenicity. I would like a list of all very important AA substitutions (that are near the receptor binding site) to involve in a bioinformatics project. The special emphasis amino acid sites list does not include all amino acids that are near the binding site.
To convey a sense of the problem, if position 155 is important, does that mean position 156 is also important?
I don't know if position 156 is considered "near" the receptor binding site.
Any help is appreciated.

I may provide a more substantial answer after reading the paper but right now I just want to point out that an amino acid substitution can affect sites that are far from it (on the sequence) because it can affect the folding. There are no general rules but some approximations can be made if we know the protein structure.

@wysiwyg that's a fair point in general but less of an issue with influenza hemagglutinin. HA is incredibly tolerant of amino variants and can include a shocking number of substitutions without drastically affecting its folding. The result is that it's usually fairly safe to consider mainly local effects of substitutions without worrying too much about major structural changes

Short answer: Yes, 156 is generally considered "near" the RBS, e.g. in this paper you can see it mapped onto the structure.
For a more general answer, you'll need to sit down and stare at 3D models of hemagglutinins (there are hundreds in the PDB), just like the rest of us. Antibody binding sites are not black and white, and interactions between influenza and antibodies are wildly complicated. What's "near" in some contexts might be "far" in others.
You might find the Influenza Research Database's Identify Sequence Features in Segments tool useful, particularly its annotation of hemagglutinin H3.
Be aware that numbering of amino acids can be confusing, since different groups may be using different starting points. There's a vague agreement on the "correct" numbering, but quite a few groups pay it lip service and then number their version however they like.


text:
Choosing viruses for influenza vaccine
When scientists choose viruses for the influenza vaccine based on biological and clinical data, what indicates that a certain strain will circulate and likely be dominant in a certain season?
Does a low HI titer (meaning antigenic novelty) for a virus antigen relative to an antiserum of a virus that is currently prevalent mean that the new virus will likely dominate in the next season? OR is a high HI titer a better choice for the vaccine since it means the virus in question is very similar to currently circulating viruses?

Again, the full answer is too complex to answer here. The CDC has a broad explanation (Selecting Viruses for the Seasonal Influenza Vaccine) and the WHO has a presentation summarizing the process (The WHO Vaccine Strain Selection Process: Review of the Evidence).
The major factor for choosing a new vaccine virus is based on surveillance from the preceding season and from the opposite hemisphere's season. The surveillance data shows which virus groups are expanding or shrinking. Antigenic variation (high or low HI titers) is also a part of the decision, but every season has a number of viruses that have low HI titers to the current vaccine and the real question is whether those occasional outliers are just sporadic, or whether they're showing signs of becoming increasingly common.
Interpreting whether particular virus families are increasing or not requires a lot of familiarity with influenza behavior, genetics, and antigenicity. You can look at some of the data used in strain selection on the WHO site, e.g. Recommended composition of influenza virus vaccines for use in the 2018- 2019 northern hemisphere influenza season.

Thank you @iayork. Can you tell me how one can gain familiarity with influenza behavior, genetics, and antigenicity in order to understand as much as possible? What book(s) should I read to understand this better?

@FIREREED I don't have a simple answer. You might find some of the chapters in The Immunological Basis
for Immunization: Influenza Vaccines interesting, and Trevor Bedford's web site and his NextStrain site may be useful.


text:
Transcript without a start codon in mouse genome?
I am looking at the mouse reference genome in combination with ensemble annotation and am finding many transcripts that have no start codon.
For example, the transcript ENSMUST00000193149 at position 165503943-165567747. The first CDS has a frame number 1. In the UCSC genome browser, I see that in one of the tracks ADCY10 gene starts at this location, but in the protein sequence, there is an X under the first base, followed by a T under the next three (which indeed correspond to T).
I am puzzled: why does the transcript start at something other than the start codon? Why does the annotation indicate its start position as 165503943 instead of 165503944 where the actual codon starts?

The entry in ensembl has a "CDS 5' incomplete" tag
http://uswest.ensembl.org/Mus_musculus/Transcript/Exons?db=core;g=ENSMUSG00000026567;r=1:165331512-165395316;t=ENSMUST00000193149


text:
How did we do the COVID PCR after its first appear?
I recently learned about the PCR testing and its idea of using primers to replicate the DNA or RNA. By this I assume that we need to know the sequencing of the DNA to make our primers. If that is true; then how did we do the COVID PCR in the early days of the pandemic? Is it possible to do the sequencing on a sample without amplifying it first with PCR?

Indeed, one can sequence genome directly without prior amplification - this is usually referred to as shotgun sequencing. Obviously, this is a time-consuming and costly approach. Therefore, once the biomarker of interest is identified, one focuses on amplifying and detecting only this biomarker.
Note also, that there exist generic sequencing primers, which could, with high probability, initiate DNA synthesis for preferred type of organism/virus.
Remark
@bob1 has pointed in the comment that what we call time consuming and costly is relative: e.g., sequencing human genome costs <\$1000 per sample, and takes a couple of hours to run - in this sense it is not too costly to be done in a research lab, but it is still quite costly in terms of everyday testing of millions of people. The cost of commerically available PCR tests for covid-19 is about \$50-\$100.

These days people just do whole genome sequencing for something like this. It's not particularly costly (<USD$1000/sample), and sequence agnostic - a bunch of blunt-end ligations to get the library prep done, then put it on the machine. ~2h-3d later you get the results, 1h analysis.

@bob1 I added a clarification, taking into account your comment.

I was more meaning in the context of the OP's question which boils down to "how did we get the initial sequence to design the primers" The answer is: it was done by whole genome sequencing. I've just had a look at the cost of a miSeq run, and it's about $2000 - you can get 96 samples on that, so about $20/sample, but not as simple as quick or as automated as PCR can be.

@bob1 I understood the question as asking whether we could sequence without amplification. But to identify the specific sequences corresponding to the virus one probably had to sequence everything that was in the sample - this is probably what you mean.

You can't sequence 96 full human genomes on a MiSeq.  I don't think you can do one.

As an extension of Roger Vadim's answer and bob1's comment, note that preparation of DNA libraries for shotgun sequencing often does involve PCR, but the PCR does not use primers that are specific to the sequence of interest. Rather, the primers are either random or specific to so-called adapter sequences that are appended to the ends of genomic DNA fragments in a mostly random fashion. An example of such a workflow would be...

Obtain genomic material from a pure culture of your organism / virus of interest
For genomic DNA, fragment genomic material to a desired insert size. For RNA genomes, use random primers to carry out reverse transcription.
Treat your DNA/cDNA libraries with a pool of enzymes that makes the fragment ends amenable to ligation of adapters. This process is often called "blunting and A-tailing".
Ligate adapters to the ends of treated fragments.
PCR amplify your DNA libraries using primers that recognize the specific sequence of the adapters. This creates DNA fragments that contain genomic DNA flanked by the sequences of your choosing. Often, this appended DNA will include sequences needed by your sequencing platform (read up on bridge amplification in context of Illumina sequencing) as well as short "barcodes" that identify your DNA library as being associated with a specific biological sample.

Once you've got your "reads" from the DNA sequencer, you can use those reads to construct a complete genome in a process known as de novo assembly. If everything goes right, you now have a genome against which you design primers for faster, targeted PCR detection.


text:
What does "novel, predicted deleterious, within autozygome" mean in genetics?
I am a medical student and just got involved with a genetic lab and research. I read a lot phrases like: "Although no mutations have been reported in this gene, we think this variant is interesting because the nature of the variant (novel, predicted deleterious, within autozygome).
Can anyone explain it to me?

Welcome to Biology.SE. Could you please give a direct quote and link to the original paper?

For a genetic variant:

novel - Not previously reported in the scientific literature.
predicted deleterious - There are reasons to suspect the variant could cause abnormal effects in a person.  This may be in part from where the variant is located (e.g. what gene), what problems were observed in persons having the variant, and many other considerations.  See the "Variant interpretation" section of this paper for more detail.
in autozygome - "Autozygous" refers to parts of the genome which are identical on both maternal and paternal chromosomes because of common ancestry of the two parents.  The autozygome is the collection of all such segments for a person, and is larger in cases of inbreeding, as when the parents are first cousins.  Autozygous segments are (usually) entirely homozygous, that is, all alleles are the same since they come from the common ancestor. (In normal segments, there will be a mix of matching and mismatching alleles.) The importance of homozygous alleles, of course, is that a recessive allele will be expressed in the person when both alleles are the same.  (Related papers: "Autozygosity mapping with exome sequence data", "Autozygome-guided exome sequencing in retinal dystrophy patients reveals pathogenetic mutations and novel candidate disease genes".)


text:
Does the brain process sound in "clips" or "frames"?
I've always been under the impression that our brains process images (relayed to it via the eyes) at a particular frequency or "framerate"; this is supported by lots of sources, such as this one.
I'm wondering how close this compares to the way our brains process sounds:

Do we sample "snippets"/clips of sound? If so, is there any evidence as to how long (duration-wise) these "clips" are? Do we "sample" at the millisecond level? Microsecond?; or...
Do we actually sample "sound frames" (much like we do with visual images)? If so, how does our brain process a "frame" that contains multiple noises occurring at the same time (say a dog is barking at the same time the television is on)? After all, a frame is all the input for an instantaneous point in time, versus a clip, which is all the input over a period of time.

Any ideas?

In your question, you ask about processing and sampling. I'd like to make a distinction between sampling, which in my view does not have a framerate, and perception which there is some evidence that there is sort of a framerate (though not as concrete as the framerate of a video display, for example). Processing is everything in between, and as such, whether it shows "framerate-like" behavior depends on the stage of processing.
Does vision really have a framerate?
The "framerate" depicted in those sources for vision is sort of a special case, talking about perception of a particular stimulus. There are no real "frames" in your vision, only temporal averaging (because phototransduction is quite slow on the timescale of neural processing in general). The article you link makes a mistake in logic in concluding that humans have a frame rate: the research they cite is about discriminating between separate flashes, which is an issue of temporal averaging rather than framerate. There is a separate issue, which is whether perception correlates with particular oscillatory frequencies; I'll get to this later in my answer.
If you flash a very bright 1 ms light, and record it with a video camera, you will often miss the light entirely (or it may appear only in part of the image, depending on the scanning pattern of the camera). With vision, though, you will always see the light, and for very brief flashes you will perceive changes in duration as changes in intensity.
The other contributor is the "magic" of perception: effectively, what you perceive is not directly the signals that come in through your eyes but rather the model your brain makes for the world based on that information. This process is the origin of all perceptual illusions; the appearance of "backward" images like with a spinning wheel is one example.
Our current model for how processing of sensory stimuli works in the brain is that there is a functional hierarchy with significant abstraction at higher levels of the hierarchy. As you get to higher order levels of processing, you will cease to see the "pixel information" and simple edge/feature detection, and begin to see more abstract representations like detection of particular visual objects or encoding of object velocity.
Okay but the question is about auditory stuff..
It's easiest to start with vision simply because, for better or worse, it is best studied historically. For auditory processing, there are a lot of similarities with vision even though the input stimuli start very different. At low levels of processing, auditory neurons are well described by spectro-temporal receptive fields. At higher levels of processing, you will instead see representations of whole features in sounds, such as phonemes.
Object segmentation is a very difficult problem in both vision and hearing (and a difficult task for computer/AI-based versions of those senses, as well). This is definitely an active field of research, but there is good evidence that some segmentation is present throughout the cortical hierarchy (for example, see here). There are no concrete answers for 'how' exactly segmentation works, just that it does, some evidence for where it might be happening, and some understanding of factors that make it harder to segment different sources. Sound localization is certainly one of the key factors, though segmentation can occur even when there are no localization cues. For example, if you have multiple speakers on the radio, or multiple musical instruments playing, there are some shared spectral characteristics of the speakers or instruments
Discrete signals in cortex
All that said, this does not mean that the brain is free from any discrete elements of processing (like "frames"), although it probably doesn't make sense to think of a frame rate but rather a type of "threading". There is recent strong evidence that activity in the neocortex can be organized into packets of activity that contain sensory or other information. So even though the auditory stream is sampled continuously, that continuous sample is most likely distilled into discrete auditory objects that reflect both the content and source of those stimuli.

Question about visual higher order. Do we have schemata for visuals? That's what I think of when you say "...more abstract representations like detection of particular visual objects or encoding of object velocity." but I'm not sure.

I would really love an explanation for the downvote...though I know how unlikely those requests are to actually produce an explanation.

@anongoodnurse, schemata looks like a psych term, haven't seen it used in (my area of) neuroscience. I'm not quite comfortable saying "yes" without understanding clearly what baggage that term might convey, but I'll say "probably" :). By abstract representations I mean to be a bit non-specific, I'm basically including anything that is not a pixel/edge representation. It could be a code for "dog" versus "cat" or simpler features like "triangular" versus "square" - those are things that all seem discrete in vision, the Necker cube being a great example.

A schema in learning theory is a concept (of information) we know in a matrix of such concepts (say it's a room among many millions of rooms). If the room has a label (e.g. "organelles"), we expend far less energy on learning new things about organelle-related subjects. If the room "organelle" is missing, we need to devote a lot of working memory in order to remember a new fact. Does that make sense? So, if I have a schema for "cat", it's easy to place new incoming info immediately where it belongs, cutting down on processing (or the use of working memory.)

DV not mine, but I had to read your answer twice. Maybe someone doesn't understand it and therefore thinks it's not useful?? Just a guess. I certainly disagree.

Yeah, I think I understand, I'm glad I didn't jump to say yes to schemas then, just because of all the additional implications. I would say that hierarchical representations are definitely a way to reduce complexity, and they are certainly related to schemas as you describe them. Where I want to distance them, though, is that having a representation of "cat" doesn't necessarily make all things easy to classify, it depends on the task: sometimes you have to group things, sometimes differentiate them.

For what it's worth, I've received a relatively high number of unexplained downvotes over the past week that didn't seem particularly warranted, so maybe there's someone with an axe to grind.


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What is the purpose of segments in citrus fruit?
What is the purpose of segments in citrus fruit? In my experience, each segment usually contains from zero to two seeds. I may have seen more but only rarely, if I remember correctly. What is the significance of having more than one seed in a section (twinning, perhaps)?

The citrus fruits belongs to the type hesperidium, which is a highly specialised form of berry specific to citrus fruit.The hesperidium is derived entirely from the ovary, other features of hesperidium includes leathery exocarp, spongy mesocarp and juice filled endocarp.

A hesperidium has an aromatic, leathery exocarp (the "rind") and mesocarp and endocarp compartmentalized into sections (each representing a carpel), each of which contains one to several seeds. This type of berry is unique to the genus Citrus, which produces fruits such as oranges, grapefruit, lemons, limes and tangerines.
Reference

The edible flesh of a mature citrus fruit is divided into segments, each derived from an ovary locule.The number of segments varies widely but is typically between 10-15.Each segment is surrounded by tough endocarp membrane and filled with tightly packed juice sacks or vesticles.
Reference

There are several major ways that plants have evolved for constructing
fleshy fruits.  Oranges etc. belong to the family Rutaceae, which is
unique in filling its "locules" (the spaces in which seeds are produced)
with "juice sacs" that are attached to the outer walls.  Each of the
locules probably represents a structure, known as a "carpel" that was
at one time distinct, but now has fused together with its neighbors.
The outer skin of most citrus fruits shows no sign that the interior
is sectioned, but this is a result of the fusion occurring early in
the development of each individual fruit (rather than early in the
evolution of the Rutaceae).
Reference

Segmentation inside the citric fruits are due to its development from the ovary, as each of the segment is evolved from the ovary locule, the number of segments varies according to species(also there are variations in single species). The evolutionary advantage of segmentation inside the fruit is a debated topic.A digestible theory is that, each segment of the fruit contains 1-3(in the case of orange) seeds, due to the evolution by mammalian resources, keeping segments inside the fruits helps in the dispersal of seeds by different agents. When a ripe fruit falls down, its individual segments are broken apart and eaten by different animals/birds, this in turn helps in dispersal of seeds to geographically distinct(distant) locations. With each segments featuring seeds inside them, its a good adaptation to produce a single fruit which can be distributed by different agents.

My issue with segmentation as a distribution strategy is that the segments are often stuck to each other. However, I've never observed citrus in the wild so I have no idea what goes on there. Thanks for the very well done answer.

The selectionist part of the answer lacks refs. I personally doubt, it has any scientific basis.

@har-wradim: Is it so much difficult to believe "With each segments featuring seeds inside them, its a good adaptation to produce a single fruit which can be distributed by different agents."

@Jay That's exactly my point: science is not about believing.

@har-wradim: Some times we have to believe something in order to get a conclusion !


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What causes biennial epidemics?
I read the Wikipedia article on acute flaccid myelitis which contains a graph showing confirmed US cases peaking biennially in 2014, 2016 and 2018.
That got me wondering because I found that pattern to seem unusual compared to an annual one tied to seasons or a constant or increasing one. So I did a quick Google search on "biennial patterns in rates of infection" and turned up this paper: Regular biennial cycles in epidemics caused by parametric resonance which discusses, mathematically, the biennial patterns sometimes found in the incidence of measles.
What I'd like to know, in layman's terms, is the causes of biennial patterns such as these in terms of the way these infections spread among victims and develop within them.


text:
Textbook on molecular basis of memory
Looking at the rules in the meta, it seems book-recs are a little on the iffy side for on-topic so I hope this is okay.
I am looking for a (graduate-level) textbook that has a thorough treatment of the molecular basis of learning and memory. The issue I am having is that a lot of textbooks seem to cover bits and pieces or just focus on one area. Usually, they just have a few small sections on the molecular events and the rest of the textbook covers channel properties, pharmacology, systems neuro, and behavior.

Synapses - This one comes close but is now quite dated (2003)
The Neurobiology of Learning and Memory - A significant section on the molecular aspect but is not particularly detailed. Very basic idea.

Review articles tend to be difficult because they are more specialized for specific kinases (mTOR, CaMKII etc), events, or channels.
I am trying to get a sense of the broader picture of the just the molecular side of all of this. Specifically the molecular and cell biology that underlies:

Early-phase LTP (receptor trafficking, signaling pathways)
Proteins expressed from local translation in dendritic spines, signaling pathways that control this
Details on synaptic tagging hypothesis
Late-phase LTP events, pathways, proteins, and regulation
Downstream effects of activation of different channels, how they control pathways below, how they all intersect and how this differs by brain area and cell type
LTD events
Events at the post-synaptic density (receptors, ion-channels, protein composition, scaffolding, actin network)
Synaptogenesis, plasticity, maintenance during long-term memory
Kinases in learning and memory
Transcriptional control
Post-translational modifications and consequences for learning and memory
Scaffolding proteins and their contribution to signal stability
Pre-synaptic events
Contributions of glia/auxiliary neuronal cells
Bonus: Disease focus - what pathways and proteins underlie various well-studied genetic diseases?
etc.

I know this is a tall order but with 1000+ page textbooks out there on other neuroscience topics, surely someone has written something? Review article are great too, perhaps I just haven't found the right one yet.

From what I am aware of, most of the molecular basis of memory research is relatively new, and thus will likely only be in primary literature at this point, there is usually a 5 to 10 year lag for the most recent research to make it into the textbooks. There is the Cognitive Sciences Stack, where you might have a more focused audience for your question. @AliceD may have some advice on this topic though, or at least where to start looking for good reviews. The journal Neuron comes to mind, but I am not sure if there would be more specialized journals.


text:
What percentage of introns are spliced in polyadenylated mRNAs?
I am asking a variation of a previously asked question: What percentage of RNA splicing happens during transcription?
I am planning mRNA purification using poly(A) antisense-oligo pull-down and, for subsequent purposes, would need to have an educated guess on what percentage of introns I should expect to be spliced out. An easier alternative question, mitigating the complication of mRNA turnover, would be the percentage of introns that are spliced until completion of polyadenylation.
Maybe someone knows more recent papers on this?

I mean the an answer for an average mRNA independent of concentrations. I will self-answer once I find a good estimate.

Might depend somewhat on the organism, whether the retained introns are part of "mature" alternative mRNAs vs. incompletely spliced mRNAs, whether cell compartment matter, etc. For example, Arabidopsis has lots of unspliced introns in polyadenylated nuclear transcripts that are absent from cytoplasm, with a report of >50% of introns being removed post-transcriptionally (apparently some of these are spliced before polyadenylation).

Introns are usually very huge compared to exons. If unspliced introns are worrying you, you could use size exclusion columns or PAGE to purify your RNA, if that helps.


text:
Leaf pictures: Which disease?
I had several plants that with same symptoms, which all eventually died within some weeks: Formation of blisters along stem (no picture) and leaf veins, that seem to pop up (assumption) and make everything around sticky. The disease started with citrus plants (diverse limes) that I bought.
I thought it must be a some microorganism, but strangely close-up pictures resemble some flea-like morphology of the blisters, which makes me so curious that I ask this question. The plant leafs are Kaffir limes, approximately 6 cm long.
Also, would you have any idea how to save my plants?

I forgot to say, you can scrub them off with a toothbrush, but that won't kill the eggs. Needs to be repeated several times. Good luck!

Great, I will try that!

It looks like a scale insect to me, similar to Citricola scale but lighter in color. It might be a Soft Brown Scale, but they usually appear multiple generations at a time, so you'd see all sizes from tiny to full grown, whereas citricola scale usually appears as a single generation (all approximately the same size.) Either way, they suck the life out of plant leaves and will reduce their vigor and setting of fruit, while secreting a sweet liquid that promotes fungal growth.
When I see a scale insect, it gets scraped off the plant with my fingernail or a knife (and smooshed), and the leaf gets cleaned. If the leaf has been injured, I either get rid of it or rub a tiny bit of a mixture of beeswax and olive oil on the spot. Clearly this won't work for you. As I don't use any insecticides (unless you count my fingernails, etc.), I can't give you any advice about control, but it should be easy to search online.

Photograph from the United States National Collection of Scale Insects Photographs

It is only necessary to scrape them off with a nail ; they will not reattach.

That's true, but I don't like plant pests... If insects in my garden are unsightly but basically harmless, I leave them alone. If they are harmful, they are no more.


text:
What experiment for first time showed DNA is anti-parallel?
Scientists how to prove DNA is anti-parallel?

Hello and welcome to Bio.SE! Take the tour to learn about the site and earn yourself your first badge. Also, we require questions to show the previous efforts looking for an answer. What did you already do in order to find experiments for anti-parallel DNA?

@LinuxBlanket i still think thats only homowork. :)

@L.Diago I know, but let's know them the site policy :)

The definitive proof came with the crystal structure of B-DNA (see Watson & Crick, 1953). Anti-parallel strands is the configuration that best explained the diffraction data while not violating chemistry (bond lengths and angles, no steric clashes, etc.).
The relevant sentence from the article is:

the sequences of the atoms in the two chains run in opposite directions

I underlined this sentence in the following screenshot of the article:

Why are you answering homework questions that clearly do not satisfy SE Biology criteria as two comments make clear. Doing so encourages cheats and people too idle to do any research of their own.

Because I am not convinced it's a homework question. Assuming it is a homework question, it's a poorly formulated one anyway because the article containing the answer is behind a paywall, even on campus at a US university (I just checked where I work), which means no student would realistically find the answer on their own easily.

Whether or not you think the question was homework, @LinuxBLanket had explained the deficiency of the question. It is reasonable to expect the OP to respond this (and the comment about home work), and to wait until he has done so before answering. As for the unavailability of the original Watson and Crick paper, this is described in every book on biology, and is available on line in a far more comprehensible form to the student. I would wait until there is a request for access to original sources before posting, and then do so in a form that does not discriminate against the partially sighted.

You're right about accessibility: I should have retyped the sentence instead of posting a screenshot (the PDF is a scan from which I couldn't copy text, and I was lazy, hence the screenshot). Will edit the answer accordingly. Now, I disagree with the rest of your comment: answers on SE are public and therefore potentially useful to anybody (not only the OP), who would never find the information because it's behind a paywall.

Agreed about "at this point", but now their interpretation has been confirmed experimentally more than 5000 times: https://www.rcsb.org/pdb/results/results.do?tabtoshow=Current&qrid=B94C6458


text:
Small flying insects gathering around the pot flowers
Recently I spotted relatively small flying insects gathering around the pots inside my flat.
There are smaller than fruit flies, probably around 1mm - 2mm long, blackish, and fly somewhat erratically. As far as I can tell the insects are active mostly during the day.
I didn't spot any obvious damage to the plants so far, but I might have miss something.
The location is relatively warm (southern window, above heating sink), and excluding the soil in the pots, rather dry.

Geographical location: Central Europe
Time of observation: Late summer, early autumn.

I'd be grateful if someone could help me identify this species.

Hello and welcome to Bio.SE! Take the tour to learn about the site and earn yourself your first badge. Your description is rather accurate, nice first question!

Looks like some sort of fungus gnat though I won't make any attempt to ID a particular species. Note that fungus gnat describes a very wide range of species over 6 families, though yours looks most like the flies from the family Sciaridae (Wikipedia notes there are ~600 species in Europe).
Fungus gnats feed on organisms decomposing soil, which are most present when the soil is moist, especially if overwatered. The damage you will experience, if any, would be to the roots, rather than visible on the leaves, though you will see wilting if the damage becomes significant.
You say things are dry, however, the important place is the soil. You will deter, though probably not completely eliminate, the fungus gnats if you let the soil dry between waterings (in my personal experience with fungus gnats this approach was sufficient). Some specific parasitic nematodes are also used for pest control of fungus gnats, if they are available in your area.

Agreeing with @Bryan Krause even as far as family; if we're both right in that respect, species-level identification requires a compound microscope and at least some dissection (look for "Sciaridae 'sp. nov.'" in your favorite search engine; the open access results will give you some idea what specialists seek in preparing their descriptions).


text:
How to set the phenotype in GWAS analysis?
In the GWAS analysis, my animal sample phenotype is whether an individual dies or survives. And I have every sample death time. How do I set the phenotype in GWAS analysis?

Simply, First of all, you can group samples as survived animals and dead samples and you have a binary phenotype.
In a different approach, you can use survival time (time to death) as an ordinal variable phenotype. If you want you can utilize survived sample by assign a large death time value to them.
In the third approach, you can cluster the survival time (time to death) into the desired $n$ groups by the simple procedure like $k$-means. and you have coarse grain ordinal variable you can add survived sample group at the end of The Spectrum.


text:
Genotype -/- vs delta/delta
In https://doi.org/10.1016/j.neuron.2018.07.033, Pan et al. use the designation TMC1^delta/delta to describe a mouse strain lacking a functional TMC1 gene.  What if any is the different between the delta/delta superscript and a -/- superscript in this context?

The delta refers to a mutant allele, in this case a cysteine point mutant. The -/- refers to a homozygous null allele, in this case a knockout.


text:
How would inserting a nonfunctional protein impact fitness of an organism?
Producing proteins costs energy, and producing longer proteins costs more energy than shorter proteins. Producing proteins which have no function, would therefore presumably negatively impact the fitness of a bacteria in culture. So my question is this:
Is there a way of modeling how much a nonfunctional protein would impact fitness relative to the wild-type which doesn't produce this protein? In other words, what is the cost — in terms of fitness — of just producing a protein, if you ignore all the other effects of the protein inside the cell?
How much would the length of the protein effect it? would the impact on fitness vary linearly with the length of the protein?
This would probably depend on many different parameters, I'm just not sure what all of them are and how each of them would factor into the final result. For instance, it would probably depend on the level of expression of the gene (which sigma factor would impact this especially).
I posted a similar question a while ago, but I've reworded it based on feedback from last time. If it helps you to think of a specific organism to answer the question, by all means, do so. Let me know if there is any literature already on a question related to this one!

I expect any empirical investigation would show there would be more to this than the lost energy spent producing the nonfunctional protein. You could transform a bacterial cell so that it produced this "nonfunctional protein", but it's going to take up space, interact with other macromolecules and cellular components, possibly agglomerate... Cells are crowded. Are you more interested in a theoretical model that ignores these possible effects?

Yes, my main question was more how one would even begin to create a theoretical model. But the point you raised is a good one.

Every transgenic cell we ever made to express some fluorescent protein (FP) is doing this. At least we hope that besides fluorescing, the protein is non-functional (which isn't always the case). It's usually the method of insertion that's more harmful than wasting energy on expressing the protein. Reasoning from the fact that my transgenic fruit flies do horribly compared to wild ones (and it's common knowledge that more insertions = sicker flies), but within one tissue, FP-expressing cells don't get displaced by non-FP-expressing cells of the same type.


text:
Difference between clonal and subclonal mutations
I'm a physicist writing a proposal that has to do with cancer as a disease driven by evolutionary selection. As far as I understand, all tumors start with a single precursor (single cell or group of cells), and the other cells derive from this precursor by cycles of alterations and selection processes.
Reading recent articles, such as this, I learned that the derived cells include both clones and subclones. Since I'm not sure I understood things correctly, I have a few questions on the difference between the two words:

Is it OK to call clones the cells derived from the precursors?
When should I use subclones?
In the case of heterogeneity, is it fine to call clonal population a group of clones with the same characteristics?

clones means when a cell has the same DNA characteristics as his predecessor so in that case of yours you could say that those cells are clones while for sub-clones I am not that sure, the difference of clone and sub-clone is that a sub-clone is basically a clone who is then remade with a different characteristic(an upgrade if you will) , since cancer are mutated cells you could call them like that but only if you study its DNA, meaning you have to study deep to find out if there are sub-clones in there. AS for the 3 question I didn't quite understood what you meant cuz you just used 2 words with opposite meaning because heterogeneity means a group of organismes with different characteristics and clonal population means organismes with same DNA ( much like a colony of bacteria).


text:
Looking for hard cell segmentation problem
I am a physicist working on a new image segmentation technique, and I would like to test it by segmenting some images with low-refined cells on a noisy background... Do you know where I could find such images? Thanks!

What type of microscopy? We have tons of phase contrast images of adherent human cells in our lab, and I have always wanted to try segmentation for automatic cell counting ... If interested, email me at roland.nilsson@ki.se !

Hi Roland, thanks for the reply! I'm gonna send you an email ;-)


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Why can't proteins make copies of themselves?
Why is it impossible for proteins to make copies of themselves?

Because they have no "blueprint" to work off of. DNA is the "set of directions" used to make new proteins.

I mean you could argue that proteins do make copies of themselves, just not de novo.

It is not impossible. It simply didn't evolve that way.

I really don't think questions of the type "why is the world like this" are either answerable or useful. If you can offer a biological alternative and argue that it was equally feasible, that is a different matter.

If the question was "Are there proteins that are able to self-replicate?" everyone would be happy I suppose. @tesgoe you should rephrase your post. You could say that DNA is able to self-replicate to make a tiny bit of content to your post.

It is not theoretically impossible for protein to self-replicate. It just did not evolve to be a common mechanism. Lee et al. 1996 reports finding of a protein that can catalyze its own synthesis.

It is possible indirectly in case of prion.See this link

It would be helpful if you summarized the link in your answer, in case it is not available in the future


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Is DNA of all animals made of the A,T,C,G blocks?
Is it true that DNA of all animals is made of the A,T,C,G blocks?

DNA is not made of these blocks only. But the genetic information is conveyed through the series of these four block.
All animals, all plants, all fungi, all other eukaryotes, all bacteria, all archea and plenty of viruses use these four blocks. Some viruses use RNA instead of DNA, in which case the T is replaced by a U (Uracile).
You will find more information on wikipedia > DNA.


text:
To what group does coconut plant belong?
I've tried looking it up but I couldn't find an answer. Could someone please tell me to what group of plants do coconuts belong depending upon the natural availability of water?

what do you mean by "group" (https://en.wikipedia.org/wiki/Taxonomic_rank) and what relevance is the availability of water?

I mean it's neither in halophytes nor in hydrophytes. Does it have a separate classification on the basis of availability of water in its natural habitat?

In terms of taxonomy and morphology:

Although coconut trees display considerable morphological diversity,
  they are considered taxonomically a single species (and the only
  species) within the genus Cocos. Based on stature and breeding,
  coconut cultivars can be divided into two groups: tall and dwarf.
  The former typically grows up to 35 to 40 meters and is mainly
  outcrossing, whereas the latter can only grow up to 25 to 30 meters
  and usually is selfing. Dwarf coconuts, which are less common than the
  tall variety, are usually found growing close to humans and have
  traits that likely result from human selection.

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0074736
I've found little information about whether or not they are halophytes, hydrophytes, xerophytes,or mesophytes - but according to a Google Book, a number of crops are widely cultivated in non-saline soils, including Cocos nucifera (coconuts). Another Google book with a lot of information about coconuts states this: Some experiments show that a small quantity of salt added to the tree roots is beneficial.
Cocos nucifera also love sunlight, so they can be considered heliophytes.