Is there any possible way that hybrids can mate? I'm writing a book, and a a portion of it involves a society of humanzees. Now, is there any plausible way that a hybrid (such as a humanzee) could procreate either with one another, or with their father/mother species? I apologize for my lack of understanding of biology, any help would be much appreciated!

This is a hypothetical scenario which I think could be compared in parallel to hybrids like a mule (offspring of a male donkey and a female horse) or a hinny (offspring of a male horse and a female donkey) or zebroids (reference). In the case of the fertility of mules on wikipedia it is stated that

  A few female mules have produced offspring when mated with a purebred
  horse or donkey.

with examples being given as

  Since 1527 there have been more than 60 documented cases of foals born
  to female mules around the world. There are reports that a mule in
  China produced a foal in 1984. In Morocco, in early 2002, a mare mule
  produced a rare foal. In 2007 a mule named Kate gave birth to a mule
  son in Colorado. Blood and hair samples were tested verifying that the
  mother was a mule and the colt was indeed her offspring (reference).

In the case of a hinny fertility is much more rare but there is a documented case on Wikipedia

  In China in 1981, a hinny mare proved fertile with a donkey stallion.
  When the Chinese hinny was bred to a donkey jack, she produced "Dragon
  Foal," who resembled a donkey with mule-like features (reference).

The wikipedia page on hybrids will also be of interest in your research. In short, hybrids can procreate and give birth in rare cases. However, I wouldn't vouch on the survivability of the offsprings. Since your work is fictional, it is entirely left to your discretion on that topic. Btw, humazee or humzee makes a more intriguing name maybe. Good luck with the book.


Bug Identification: Is this small tubular, black bug a bed bug? So I found this tiny bug on my wall in the bedroom of my apartment. I estimate it is about 3mm long by 1mm wide.

Is it a bed bug?

It does not seem to match any of the pictures I've seen online.

The apartment is very clean by most standards. The only other bug I've seen in here is the odd stink bug.

Northeast coast of USA.

I'm going to suggest it is the larvae of a carpet beetle. Initially I thought possibly the Varied carpet beetle because of the lighter patches near the posterior end similar to this picture from the wiki page on this species:

Having said that the geographical range might not be correct so it could be a similar species so I've dug a bit deeper. There are some 120 species in North America, from this link I'd say that the Buffalo carpet beetle is a contender.

Carpet beetles are classified as a pest species:

  "larvae feed on natural fibers and can damage carpets, furniture, clothing and insect collections"

Not all bad though, the larvae are also known as wooly bears, how nice.


What are the disadvantages of forbidding flights to and from the African Ebola region? After looking through the available Stack Exchange sites, this one seems to come closest to the appropriate place to ask...

Popular opinion, including my own, is that banning flights to and from the Ebola-ridden portion of Africa would protect us overall. I understand it would increase pressure on that region, making it more chaotic and less conducive to tracking people, so that eventually it could "explode uncontrollably" out of that region in a year or whatever time frame. Sanjay Gupta explains this briefly in Jon Stewart's (at points hysterical) report.

The disadvantage of allowing free travel to and from these regions, as I see it, is that the disease spreads much much faster, and to many many more disparate locations. This is because of the variety of places where each passenger comes from. And also the flight crew and plane itself, which affects all future passengers.

I'd appreciate more educated opinions. I'm far from it, regarding these issues, as are many Americans.

I think the disadvantages are mostly economical in that region and so they has nothing to do with epidemiology. Possibly a long term effect can be, that the economy of the region turns from bad to worse, which can affect the healthcare too, but that's just speculation.

The advantages are obvious, ebola is quarantined at some level, so these measures prevent or at least slow down its spread around the world.


Is Chargaff's rule really applicable? Chargaff's rules states that DNA from any cell of all organisms should have a 1:1 ratio (base Pair Rule) of pyrimidine and purine bases and, more specifically, that the amount of guanine is equal to cytosine and the amount of adenine is equal to thymine.

As in the table $A \ne T$ and $C \ne G$.
So I was wondering if Chargaff's rule is really applicable?

In addition to Remi.b's answer, it should be noted that the phage Phi X 174 is the only organism in your list which significantly deviates from Chargaff's Rule (by more than 1-2 percentage points for the A-T pair). While sampling errors are indeed more likely in organisms with small genomes, there is in fact another factor in play here.

This is because Chargaff's Rule only applies to double-stranded DNA, due to the complementary base pairing that occurs between A-T and C-G. Since Phi X 174 is in fact a single-stranded + sense bacteriophage, Chargaff's Rule is inapplicable to it, since it does not obey the standard Watson-Crick base pairing that is the molecular basis of Chargaff's Rule. In fact, the Wikipedia article from which you obtained the chart states this as well:

  The following table is a representative sample of Erwin Chargaff's 1952 data, listing the base composition of DNA from various organisms and support both of Chargaff's rules. An organism such as φX174 with significant variation from A/T and G/C equal to one, is indicative of single stranded DNA.


How do carrier RNAs increase yield in sequencing experiments? I would like to know how carrier RNAs increase yield in RNA/DNA sequencing experiments. Is their main function in the precipitation steps of each protocol (i.e. small quantities are difficult to precipitate and the carrier RNAs add material), or do they have a role at other stages in the process as well?

If you are adding phenol-chloroform extracted tRNA then that is a carrier for the precipitation steps. Some people use linear acrylamide for the same purpose.


How to determine if this blood disorder is recessive or dominant? This question is from "Concepts of Genetics," Klug & Cummings, 10e.

"Thalassemia is an inherited anemic disorder in humans. Affected
individuals exhibit either a minor anemia or a major anemia.
Assuming that only a single gene pair and two alleles are
involved in the inheritance of these conditions, is thalassemia a
dominant or recessive disorder?"

I know from a quick Google search that the disorder is recessive, but how would I come to this conclusion based on the question alone?

Edit: I've spoken to my professor, and he shared his opinion that is essentially the same as canadiener's answer. Thanks to everyone that replied!

Given that this is a text book question about classical genetics, you can safely disregard any reality about the disorder.

I'd argue that the two alleles show incomplete dominance. The mild anemia, which is intermediate between healthy individuals and those with severe anemia, can be attributed to heterozygous individuals. In this case, the expression of the functional allele is not enough to compensate for the nonfunctional allele, producing the mutant phenotype.


Kinesin-5 / cytoplasmic dynein spatial density distribution in neurons Is there some way to experimentally determine the density distribution of Kinesin and Dynein in a Neuron?
Fluorescence labeling would be impossible(?) as GFP markers would probably alter the motor dynamics.
Any ideas? Or do any studies exist which looked into this topic?

It is possible to tag molecular motors with fluorescent proteins. It may impede with its movement but as this paper describes, a variant can be created that doesn't have cargo binding ability.

  Constitutively active kinesin motors can be generated by truncations
  that remove autoinhibitory and cargo-binding regions of the
  polypeptide. For this work, we generated KHC(1-560) (Figure 1A), a
  dimeric motor that has been well characterized in vitro and in vivo
  [16],[18],[19]. KHC(1-560) motors were tagged with three tandem copies
  of monomeric Citrine (mCit), a variant of enhanced yellow fluorescent
  protein (FP) (Figure 1A), and expressed in COS cells (Figure 1B).
  Single Kinesin-1 motors were tracked in live cells using a modified
  TIRF microscope (Figure 1C) in which the angle of illumination was
  varied to enable deeper imaging as described [17]

However, if your objective is just to determine the density distribution of Kinesin and Dynein in a Neuron, you can simply fix the cells and do IHC staining for the motor proteins followed by high resolution imaging.


How does botulinum toxin enter the blood stream from the digestive tract? To my understanding, large polypeptides such as botulinum toxin cannot pass the intestinal lining intact. How, then, can it enter the bloodstream and cause botulism poisoning?

Transcytosis is a process by which large macromolecules are transported across a cell, such as those in the intestinal epithelium. It is used by many toxins and even whole organisms to enter the body. Botulinum toxin also apparently uses this mechanism. I'm not sure how detailed of an answer you want, but the linked to-review is pretty in-depth.


How pronounced is the difference if we would change the running direction for runners? I was jogging when I asked myself this question:

In running contests the standard running direction is counterclockwise; I also believe to remember that the regulation is very old (right back to the Greeks and Romans). I suppose the reason is that most people have a stronger dominant right leg and running counterclockwise feels more natural.

Now there are people who are "left-legged": They have a stronger and dominant left leg. What I ask is: How would the times change overall if we revert the direction and let the runners run clockwise ? Has someone experimented with it ? Is the effect discernible or even decisive ? Would left-legged people get an advantage ?

Been a sprinter for 12 years, so from that perspective, I don't think it would matter. The angle that you take when turning is not drastic enough to have a musculoskeletal difference; step height differs only a few inches. Additionally, turns never account for more than 50% of a race (barring a couple distance events, where turns act much more like straightaways anyway due to the lessened speed), so a bigger imbalance would be disadvantageous for straight sprinting. In practice, I think it would take a little bit to get used to, but not more than a year.


What causes Paresthesia (Pins and Needles) at a cellular level? I've looked it up in plenty of places like the Wikipedia page and such, and it is clear that the most common cause of Paresthesia is either a fair amount of pressure on a specific patch of skin causing lack of blood flow to the specific nerve endings in that limb (not to be confused with a stop in blood flow to the limb altogether) or a much stronger amount of pressure on that patch of skin for a shorter amount of time. This, although the most common cause, is not nearly the only one, which could be anywhere from simply sleeping on the wrong side of the bed to a lethal injection. I'm wondering what happens to the nerve cells that are affected at a cellular level, and what causes it at a cellular level. The level at which pounds per square inch aren't what is being noticed.

Underneath the superficial layers of your skin there are receptors which sense pressure, temperature and pain. These receptors are part of the peripheral nervous system which senses stimuli and they take the message conveying details about the stimulus to the somatosensory cortex of the brain. Here is where the perception of pain, burning, pressure etc is ultimately made. To take the simplest example, if you stop blood flow for a short amount of time in a limb, these receptors are activated, and will send signals to the brain that are interpreted as tingling or numbness. With more severe pain, different receptors are activated which , again, project to the same brain area but a different message is read out. If the pressure from one limb is removed, the receptors will go back to normal function as blood flow is restored.

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

http://www.scholarpedia.org/article/Mammalian_mechanoreception


Calling for Free Online Data for Paediatric ECG? I need free online data about heart murmurs to study these:

  heart murmur frequency , S2 heart sound frequency and its split,
  murmur timing, and duration, murmur intensity, S3 sound presence and
  intensity, S1 presence and intensity, presence of ejection sounds and
  arrhythmias

I will cite your source then if I can use your data freely.

I would really have the same data as used in this paper:

  Heart energy signature spectrogram for cardiovascular diagnosis
  Vladimir Kudriavtsev, Vladimir Polyshchuk and Douglas L Roy

No pediatric ECG data here

beecardio (aggregation of many ECG databases)

Does anyone have simple data for my task?

I remember that some CD of some book has some standardised nicely organised sounds that you can use freely.

I recognize this was asked like 7 months ago, but in case you're still looking for a good resource:

I used a CD of heart sounds that is called something like "Harvey Heart Sounds," which I got with the purchase of my stethoscope.  If you can find a copy of this, I found it an excellent tool when training to recognize the differences.

These are good heart sounds: http://depts.washington.edu/physdx/heart/demo.html

If you were looking for something other than the sounds themselves, then I'm not sure if you're asking about.  There are all sorts of good ECG references, especially Dale Dubin's EKG Interpretation book.  And Kablunde was the cardio textbook I used, which I liked.


Books: DNA replication In what books can I find a detailed literature on the mechanism of function of different enzymes and proteins involved in DNA replication of E. coli ?

Check this online book on NCBI: An Introduction to Genetic Analysis. 7th edition

  Let’s examine each of these components and see how they fit together to produce our current picture of DNA synthesis in E. coli, the best-studied cellular replication system

I used it a bunch while studying E. coli for my master degree, lots of really usefull information.


Acknowledging differentiation of species, in historical times This is at least partly an historical question, and I am not even remotely a biologist of any sort, so apologies beforehand if it's a little obscure.

I often wonder how many distinctions were made in pre-Renaissance times, between species of animals.

For example, though I'm sure there have always been those with enough of an interest in nature to tell subtle differences, how were lemmings or voles, for example, told apart from rats or mice? Or did this recognition of speciation only come later, once more detailed (intrusive) forms of analysis became common?

I've looked up the etymologies for vole, lemming and hamster and all are dated post-Renaissance, so at least in these instances it may be safe to assume that people might simply not have noticed the differences before closer study took place. But I guess there are other animals where the same question applies (particularly smaller, harder-to-scrutinise animals where there are a large number of species similar at a glance).

EDIT: Vole means field (same root as wold), giving rise to the 19th c. term volemouse, meaning that originally, mouse and vole were indeed seen as one and the same -- proof of point.

P.S. Of course, this question need not apply solely to animal species.

The branch of science you are looking for is taxonomy, that is the science of identifying and naming species, and arranging them into a classification.

Modern taxonomy was born from the studies of the Swedish zoologist Carl Linnæus (1707-1778), who first introduced, in his books Systema Naturae (Systems of Nature) and Species Plantarum (Plants Species) the now common binomial nomenclature where each different species is given a Latin name composed by two parts: one identifying the genus and one identifying the species.

For instance, various species of mice are in the genus Mus: the common house mouse is Mus musculus, but in the West Mediterranean you have another type of mouse, called Mus spretus.

Although this rigorous type of classification is quite recent, taxonomy existed much earlier.

Shennong, Emperor of China somewhere around 4000BC apparently tasted hundred of plants to test their curative properties. He wrote his observations in a book called the Shennong Ben Cao Jing.

On a similar note the Ebers Papyrus, dating ~1550 BC contains description of the properties of many plants.

To more "recent" times, around 300BC Aristotle was the first who actually classified animals (e.g. vertebrates and invertebrates) and his student Theophrastus wrote a classification of plants in his Historia Plantarum (Hystory of the Plants).

Some 400 years later Plinius in the Naturalis Historia (Natural History) enumerated many plants and animals and gave some of the first binomial names to certain species.

As to the point of how did they distinguish species: well, with their eyes and ears, of course!
You can distinguish a mouse from a vole because it is skinnier and has a longer tail.
Even more similar species can be easily distinguished without needing special equipment.
A good birdwatcher can distinguish a chiffchaff from a willow warbler by listening to their songs, looking at how they behave how they fly, the subtly different tones of their feathers etc.
We can do that now, without any special equipment, so they could before the Renaissance!


How long does it take for a cricket to die at subzero temperatures? I am on a number of reptile groups and I often hear freezing recommended as a humane way to get rid of surplus feeder insects.

However, they can also revive if you don't leave them in there long enough.

If I had a bag of crickets and put them in the freezer, how long would it take for them to die in this way?

The actual paper that the linked article cites never mentioned about freezing the crickets:

  We examined CCR (Chill Coma Recovery) in G. pennsylvanicus exposed to 0 °C. The time
  required for crickets to recover movement of the abdomen and legs
  increased exponentially with the duration of exposure to 0 °C; after
  more than 12 h of cold exposure, recovery time reached a plateau at
  ca. 15 min

And this is how CCR is performed

  A total of 60 crickets were placed individually into 14-mL plastic
  tubes and cooled from 25 °C at 0.25 °C⋅min−1 and held at 0 °C for 2–42
  h. At 2-h intervals (first 24 h), and every 6 h thereafter, four
  crickets were placed on their dorsum in a Petri dish at room
  temperature. Times of four indices of chill-coma recovery were
  recorded: (i) first foreleg movement, (ii) first hind leg movement,
  (iii) initiation of abdominal contractions (active ventilation), and
  (iv) righting. Foreleg and hind leg movement were identified as a
  coordinated directional movement of the limbs, distinct from twitches
  of the limbs observed during rewarming. If crickets had not righted
  within 3 h of removal from the cold, they were considered to have
  incurred chilling injury that precluded recovery.

So, the crickets were never actually subjected to subzero temperatures or freezing or even cold shocks.

How long it takes to die depends on the freezer temperature; based on personal experience I can say that they die in ~10min @ -20⁰C.

Didn't find much information on crickets but according to this paper Drosophila will die in less than 2 hours at -5⁰C upon transferring them to the cold temperature directly (cold shock). However, if the larvae are "hardened" by keeping at +5⁰C before cold shock, their survival chance increased — the temperature required for killing them in 2h (Lowest Lethal Temperature) reduced. Now cricket is bigger than Drosophila but the surface area is also higher. I cannot do more than speculate at this moment (you can apply complex heat transfer equations and see how the rate changes with the size).


Did Carl Linnaeus ever name a species he never saw? According to this post Carl Linnaeus named more than 13,000 species which is definitely quite impressive. If we consider a 50 years career it makes about 5 species per week! It would feel impressive that he could actually take time to find, observe and describe that many species.

Apparently Linnaeus named species from outside Europe such as the Wild Turkey (Meleagris gallopavo, Linnaeus, 1758). This surprised me a little bit as travelling accross the atlantic wasn't all that common in the middle of the eighteenth century. Also, the wiki article on Carl Linneaus says:

  Boerhaave offered him a journey to South Africa and America, but Linnaeus declined, stating he would not stand the heat.

It made me realize that there are actually many non European species that have been described by Linnaeus such as the Llama (Lama glama, Linnaeus, 1758).

I heard of Linnaeus trip to Lapland and I always pictured Linnaeus as a field naturalist but now I am wondering

Where did he get his specimens from? Did he have an army of graduate students exploring the world for him?
What fraction of the species he named did he really see in the wild?
What fraction of the species he named did he really see alive? (has he ever seen a Llama and a Narwhal?
Did he name species based on other people description but without ever seeing one dead or alive?

During Linnaeus' lifetime there was two ways to get in contact with exotic specimens other than travelling abroad: by visiting museums and collections or by receiving the specimens at your home/laboratory✻. Natural history museums were not that popular at Linnaeus time but only some time later, in the nineteenth century (the first natural history museum, the Muséum National d'Histoire Naturelle, was created in Paris in 1635).

That leaves us (or even better, Linnaeus) with the second option: receiving the specimens. According to the University of California, Berkeley:

  Linnaeus continued to revise his Systema Naturae, which grew from a slim pamphlet to a multivolume work, as his concepts were modified and as more and more plant and animal specimens were sent to him from every corner of the globe. (emphasis mine)

You could argue that a (dead) llama is a big animal, but one can describe an animal using just its bones, or even just some of its bones. Besides that, it's worth mentioning that Owen received a whole mammoth in UK to study and describe! So, sometimes, size is not a problem.

Answering your second and third questions, a good deal of the animals he described he never actually saw in the wild or alive. Estimating the precise fraction is way more complicated. The same may be said regarding plants, but I guess that the fraction here is smaller: live plants are easier to maintain, seeds are easy to be transported and sown etc. Besides that, botany was Linnaeus' area of expertise. The same link above says...

  Linnaeus was also deeply involved with ways to make the Swedish economy more self-sufficient and less dependent on foreign trade, either by acclimatizing valuable plants to grow in Sweden, or by finding native substitutes. Unfortunately, Linnaeus's attempts to grow cacao, coffee, tea, bananas, rice, and mulberries proved unsuccessful in Sweden's cold climate. His attempts to boost the economy (and to prevent the famines that still struck Sweden at the time) by finding native Swedish plants that could be used as tea, coffee, flour, and fodder were also not generally successful.

... which shows us that he dealt with live exotic plants.

Regarding your fourth question ("did he name species based on other people description but without ever seeing one dead or alive?"), the answer is yes, specially for plants and insects: there are several specimens that Linnaeus described based just on drawings or paintings (which may be considered other people's description), without ever seeing the actual organism. Two examples are Dysdercus andreae (an animal) and Porella (a plant).

PS: Not related to this question or to biology, but this is (unfortunately) quite common in sciences: some of Freud's patients, among them his most famous cases (Anna O., little Hans, etc...), he never actually met or even saw at the distance! He "diagnosed" them using just descriptions and hearsay...

✻ According to RHA comment below, there is a third way: sending people to collect the specimens for you.


Why AZT is selective towards HIV and doesn't impair human DNA replication? I've found this article, which is a very old one (from the time when nucleoside analogs where researched as a possible way to prevent replication of virus genetic material, before the HIV epidemics).
In the last page, the authors suggest that cellular repair enzymes could remove azidothymidine (AZT, zidovudine) from cellular DNA if it's incorporated, but viruses' polymerases lack this ability.
As it's an old article, I would like to know if this hypothesis was confirmed. As both azidothymidine and thymidine can form normal base pairings, how could human enzymes detect an azidothymidine was incorporated?

If someone is not familiar with AZT mechanism: basically, it's an analog of thymidine which has an azide group instead of 3'-OH

It can be phosphorylated by cell kinases and incorporated to the growing DNA chain; however, this will stop the polymerization because it depends on free 3'-OH. The natural question which follows is: why wouldn't AZT also block the replication of human cells' DNA?

Retroviruses depend on being able to convert their RNA genome into a DNA copy, and have a reverse transcriptase enzyme to do that. This unique activity is not found in human cells, allowing for potential antiviral therapy if a drug can be used to inhibit the reverse transcriptase while not affecting the human enzymes.

AZT is one such drug, by mimicking the nucleotide thymidine, it can it can act as a substrate for nucleotide kinases and become 5' phosphorylated. AZT is phosphorylated by host cell enzymes, specifically thymidine kinase, this means that the levels of AZT phosphates are similar between HIV infected and non-infected cells. Once the 5' triphosphate is formed, the drug is a substrate for the viral reverse transcriptase. If an AZT is incorporated into the DNA backbone, it terminates the DNA because the 3' OH is not available for further polymerization.

However, at high enough doses AZT can be toxic to healthy cells. One mechanism for toxicity is the depletion of thymidine, because AZT competes with thymidine for the kinase enzymes, but is phosphorylated at a slower rate. At high doses, >1mM, AZT can act as a substrate for human DNA polymerases. Thankfully, AZT is about 100 fold more selective for HIV reverse transcriptase than human DNA polymerase.

The mitochondrial DNA polymerase seems to be a little more sensitive to AZT than other human DNA polymerases. This can lead to toxicity in the heart, skeletal muscles, hepatocytes, or other cells that use a lot of mitochondria. This toxicity is generally reversible if doses are reduced.

For more information, read about other nucleotide analogs, such as acyclovir, ganciclovir, and others which work through similar mechanisms.


How well understood are the long-term effects of nuclear radiation? Sometimes, when people are concerned about radiation, it is not because it is precisely quantified how dangerous it is, but because we don't know how dangerous it is.

How well understood are the long-term effects of nuclear radiation, for example on cancer? (As opposed to short-term effects such as acute radiation sickness, which is easy to quantify)

I assume this can be researched from an epidemiological approach (Wikipedia mentions an epidemiological study on the atomic bombing of Hiroshima and Nagasaki, for example), and also from an experimental approach.

Also, is the effects of radiation easy to understand, or difficult? My assumption is that something physical, like radioactivity, would be easier to understand than the effects of more complicated things, like complicated organic chemicals or obesity.

The three major nuclear incidents I can think of are the Japanese atomic bomb attacks, the Chernobyl disaster, and Fukushima disaster. Of course other nuclear incidents have occurred, but usually give much higher doses to far fewer people.

Many studies have been done on the survivors from the atomic bomb attacks, and increased rates of cancer have been the strongest conclusion. This review article looks at those studies for both cancer and non-cancer effects. Leukemia is the most well known cancer to be caused by radiation, and excess leukemia was discovered in bomb survivors within 5 years of the attacks. Rates of most solid tumors had increased by 10 years after the attacks. However "Even 55 years after the
bombings over 40% of the Life Span Study cohort remain alive", indicating that the amount of radiation most people were exposed to wasn't enough to kill them. Here is another article on atomic bomb survivors.

The Chernobyl accident was a very different type of exposure, but many people were exposed to radioactive materials. Immediately after the disaster, the "liquidators" received high doses of radiation while cleaning up the site and building the containment structures, but very few have died from radiation exposure. While the environment around the power plant did suffer in the years after the accident, after the humans moved away the environment has greatly improved. Thyroid cancer rates increased due to Iodine-131 exposure, especially among those exposed as children, but rates were still low.
 Yellow = adults Blue = Adolescents Red = Children.

It is too soon to draw many conclusions about the Fukushima accident, but some studies (7, 8) have tried to predict the number of cancer cases that will be caused by it. In general the rates are expected to be low, with far fewer deaths than were caused by the earthquake and tsunami that caused the accident.

A few instances exposed small numbers of people to very high doses, and are interesting from a radiation safety veiwpoint. The infamous "Demon Core" killed 2 scientists in separate accidents while handling the core. The Goiania incident involved men breaking into an old hospital and stealing a radiation source without realizing what it was. They broke the source open and passed the radioactive material around because it looked cool, resulting in several deaths due to acute radiation sickness.

While radiation can be dangerous, with proper precautions we can avoid accidents and disasters. Remember that Chernobyl was a poorly designed Soviet reactor, and that Fukushima was a 50 year old plant that needed both a magnitude 9 earthquake and a 30 foot wave to disable it. Modern nuclear plants can be built safely and provide clean electricity for many decades, and if they are breeder reactors can recycle the used fuel to reduce both the amount and half-life of the material, making storage easier.


Is there a maximum pain threshold? Is there a maximum threshold of pain a Human can experience, beyond which point there is no noticeable difference?

I ask this question in part to better understand the definition of pain and its different facets, e.g. Is there a quantitative measure of pain? Are there various types of pain, or are they all part of the same fundamental experience?

It would also be interesting to know since I could perhaps be allowed to claim:

  "well at least I know I cannot feel more pain than X"

Thank you for your opinions.

When the pain receptors are fully loaded then it's not possible to excite these receptor greater. However the perception of pain has a large psychological component and is not well understood. Your brain could modulate your perception of pain naturally or due to illness.


Diffusion of Hypotonic solution into solution with glucose and starch Cell walls are selectively permeable to ions and organic molecules. Sometimes the selectivity is passive and a reflection of the physical laws governing diffusion. We can do simple experiments that strengthen intuition about transport across biological membranes. The following homework question concerns a situation which tests understanding of the basic ideas of osmosis and diffusion generally.

  A bag made of a flexible semipermeable membrane is filled with a 10% glucose and 5% starch solution. This bag is permeable to water and glucose but NOT to starch. The bag is suspended in a a beaker containing a 10% glucose solution. In 30 minutes the bag can be expected to

(A) swell
(B) shrink slightly
(C) collapse entirely
(D) become impermeable to glucose
(E) remain the same

Since the bag is impermeable to starch, I know that the solution in the bag isn't going to diffuse outside so it won't shrink, but would water from outside flood into the bag to try to dilute the starch concentration to the point that it's isotonic? Or am I not understanding some fundamental principle of diffusion?

The bag will swell.

Diffusion results in molecules moving down their concentration gradient.

In the set-up described only glucose and water are able to diffuse. Glucose is at the same concentration inside and out so there will be no changes in glucose concentration. Water will move into the bag because it is effectively at a lower concentration (more correctly  - chemical potential) inside due to the presence of the starch. As water moves into the bag, increasing the volume, glucose will also move so that the glucose concentration remains equal on both sides. Thus there will be net movement of water and glucose into the bag.

@WYSIWYG has raised the spectre of colloids in the comments. I don't understand colloids so cannot comment, but I think that in the context of problems like this we are usually dealing with "soluble" starch. Here is an example of a calculation in which starch is treated as an osmolyte.


Are pseudogene counted as a subtype of long non-coding RNA genes? Are pseudogenes regarded as a subtype of the genes for long non-coding RNAs?

I could not find the answer to this question in an internet search.

A note on nomenclature in modern biology

As it stands, this question seems to assume there is some legal commission, Académie française, or the like that is devoted to continually determining scientific nomenclature, and that those in the field obediently follow it. While organizations like IUPAC — The International Union of Pure and Applied Chemistry — do exist for standardization, they move very slowly, and only come out when the dust has settled (so to speak). So if I write an article about genes I can classify them as suits my purpose. I may wish to distinguish just between coding or non-coding; or between structural, informational, regulatory and junk etc. etc. Nobody is going to throw me in gaol if they disagree.

Is it scientific to classify pseudogenes in this way?

By this, I mean do the genes (for that is what we can compare) for long non-coding RNAs (ncRNAs or lncRNAs) have enough general features shared by pseudogenes that it would be useful to sub-type pseudogenes in this way. In my opinion, No. Pseudogenes are generally regarded as non-functional — remnants of unsuccessful or uncompleted gene duplication, or of reverse transcription of mature mRNAs into the germ-line DNA. In many cases they are not even transcribed.  There may not be a single function for those gene-products termed lncRNAs but in general they are transcribed and thought to have functions concerned with gene regulation. There are no structural similarities with pseudogenes, so that all the genes have in common is that they are, well, long, so to that idea I would say “So long!”

How do the genome annotators regard this?

The people that make the rules, de facto — and revise them as science advances — are the ones with the job of annotating sequenced genomes. I haven’t made a general survey of genomes, and am restricting myself to the genome of the fruit fly, Drosophila melanogaster, with which I am familiar. The distinct Biotypes for genes in the data at FlyBase are currently (2019) as follows:

ncRNA (aka lncRNA)
protein coding
pseudogene
snRNA
tRNA
rRNA
snoRNA
pre miRNA

I suspect that this is standard among the large genome databases, and it can be seen that pseudogene and ncRNA are regarded as distinct categories.

Of course, one can argue with this classification — where are the SINES and LINES and Drosophila-specific mobile elements, for example? But that just illustrates what I have written above.


How much do urban pigeons move around cities? Do they tend to live their lives in one area of the city or do they move around? For example, do pigeons born on London's Trafalgar Square live their whole lives centered around Trafalgar Square or can they move and become Marble Arch based pigeons?

What is the typical range of a city pigeon? Have Trafalgar Square pigeons ever made the trip to Buckingham palace just down the road from them, or do they hang out in the square all the time?

How different are these behaviors from their wild behaviors and how effected by humans actions in the city are they? For example, do pigeons learn that a particular city square will become busy with tourists in the summer and travel there at these times of the year seeking food?

I'm only aware of two studies that have looked at Rock Pigeon home range size. Note that this isolated research and may not be representative of Rock Pigeons everywhere nor of other pigeon species.

Rose and Nagel (2006) tracked 80 feral pigeons using GPS receivers and found 32% remained within 0.3 km of their roost location. Only 7.5% traveled over 2km from their roost location. Individuals of this species typically have 1-2 primary feeding locations within their home range which ranged from 3 - 151 ha in size (Rose et al. 2006).

Rose, E., D. Haag-Wackernagel, and P. Nagel. 2006. Practical use of GPS-localization of Feral Pigeons Columba livia in the urban environment. Ibis 148(2):231-239.

Rose, E. and P. Nagel. 2006. Spatio-temporal use of the urban habitat by Feral Pigeons (Columba livia) Behavioral Ecology and Sociobiology 60(2):242-254.


Why do neurons have long axons but short dendrites? Cian O'Donnell, a British neuroscientist, originally asked this question on Twitter: https://twitter.com/cian_neuro/status/1075432086692089857. I am not a biophysicist by training but I wonder whether there might be existing publications that have shed light on this question.

My primitive back-of-the-envelope analysis involves the following:

If we suppose that most neurons are limited to a volume V, give or take epsilon volume, and the function of axons is to carry a signal over a large distance whereas the function of dendrites is to integrate information from different sources then a semi-spherical radiation of dendrites should be the norm.
This becomes an extremal optimisation problem where there are specific constraints on the minimal axon thickness, the minimal dendrite thickness and an upper-bound on the average number of dendrites that fan out of a given axon.
This becomes an extremal optimisation problem where there are specific constraints on the minimal axon thickness, the minimal dendrite thickness and an upper-bound on the average number of dendrites that fan out of a given axon.

This is a very sloppy analysis which ignores biophysical constraints but I think that we have an extremal optimisation problem here.

Axons are used to transfer electrical signals from Point A to Point B.
Dendrites are for receiving electrical signals from different neuron cells via their respective Axons.

There are mainly two different types of Axons, insulated and non-insulated.

Insulated Axons allows extremely high velocity of electrical signals to propagate from Point A to Point B. Please note that insulated axons are not entirely insulated, the axons are only insulated at every given interval for a certain length (in measurement of distance). This forces the electrical signal to jump from one gap to another gap between insulation and result in extreme speed of electrical signal propagation down the axon.

Non-insulated axons still allow high velocity of electrical signal propagation but it is very much slower as compared to insulated axons. This is why when you have a stomach ache, its a slow and dull pain due to non-insulated axons which gives you prolonged pain signal. However, if you accidentally knock into a sharp object, you receive an instant sharp pain for a split second for you to react at that instant (Its a biological life saving function) due to insulated axons that gives you extreme speed of pain signal propagation.

On the other hand, dendrites are not built for signal transmitting but for signal receiving. Dendrites comes in different configurations, one such examples are your color sensory cells in your retina.

This is why dendrites are short while axons are long. They are configured for different purpose. Just a bit more information, electrical signal in biofluid are actually ionic current. Ionic current are different from electron current, the charge carrier are different. Lastly, electrical signal are generated due to electrochemical gradient on cellular level. When a certain membrane potential threshold is reached, action potential will be triggered and they resulted in the firing of electrical signal down the axons.

I hope you find these useful.

Best Regards

Price


Is an athlete's heart rate after exercise greater than a non-athlete I was just wondering
And if it is greater or lower how does this benefit an athlete
Also what is the averaged number of heart beats per minute

Whilst exercising, the heartbeat of a non-athletic individual is faster than that of an athletic individual. The untrained heart beats faster, but less efficiently than that of an athlete. Both the maximum, and the resting heart rate of an athletic individual are lower than the average heartbeat. In a non-athletic individual, the heart rate when resting is about 60 to 90 beats per minute, whilst in athletes it can drop below 40 beats per minute.

When you exercise, the heart works harder when other muscles in the body pump more blood back to the heart. The major muscles of the legs have large veins that will fill during the relaxation stage of the movement, and the muscle contraction in the active movement pushes the blood back into the circulatory system. Increasing blood flow triggers a faster heartbeat. Because the heart muscle of conditioned athletes enlarges and strengthens, the hearts of athletes pump more blood per beat. 1


Evolution of leukemia pluripotent short-term cells I have a problem in understanding the introduction of this paper entitled  "Stability and bifurcation in a model for the dynamics of stem-like cells in leukemia under treatment". As I have no background in biology, it's difficult for me to get the meaning of some terms like:

Short-term cells
Multipotent progenitor cells
Goldie-Coldman Law

On the other hand, the second paragraph is completely confusing to me:

  Let $Q$ denote the density of stem-cells population. A percentage $\eta_1$ of these ones are supposed to undergo asymmetric division with one daughter cell identical to the mother cell and the other one committed to differentiation. A percentage $\eta_2$ of the stem-like population differentiate symmetrically and go to the line of mature cells. The rest of them, a percentage $(1- \eta_1 - \eta_2)$ is supposed to self-renew: both cells that result from mitosis are identical to the cell that entred to the cell cycle. The same duration $\tau$ of the cell cycle is supposed for all types of division.

Is there a charitable soul to indicate some web page or youtube video on the subject?

Some background: leukemia is an immune cancer so it comes from the hematopoietic system. Thus, it would be useful to look into Hematopoietic stem cells (HSCs). Note that, in general, the (semantic) hierarchy of stem cells goes: totipotent, pluripotent, and multipotent, in order of less generality (i.e. more differentiated, or more mature as a cell in other words). Maybe reading about stem cells in general would be useful too.

HSCs have two subtypes: one which can indefinitely renew itself, and one which has a timed lifespan (i.e. it stops being capable of generating new cells of different types after awhile).  It is interesting to note that leukemias have  an analog of these, which is what is being referenced, presumably, in the paper.
See Normal and leukemic hematopoiesis: Are leukemias a stem cell disorder or a reacquisition of stem cell characteristics? for a bit more on this.
Multipotent progenitor cells (MPCs) are also capable of generating new cells, but are capable of less variety than plutipotent stem cells.
They can "choose" to become a more differentiated cell (i.e. choose a lineage).
They also cannot self-replicate (i.e. to divide and create new multipotent progenitors) indefinitely, though they can do it for some number of steps usually.
In other words, an MPC will generate a finite number of cells, whereas a true stem cell can divide indefinitely, given the resources.
The Goldie-Coldman Law (also called hypothesis) can be summarized via:

  This hypothesis predicts that the tumor cells develop resistant phenotypic variations towards chemotherapeutic agents. This resistance is independent of the chemotherapeutic agent and dependent on the number of cell divisions that occur after treatment begins. The larger the tumor size or the longer delay in initiating chemotherapy, the more resistant cells. The implication is that a regimen of alternating cycles of two different non–cross-resistant chemotherapy medicines yields a better chance of tumor eradication.
    (From here).

       In other words, it is a model for how cancers become resistant to drugs. See also Improving       Cancer Treatment via Mathematical Modeling: Surmounting the Challenges is Worth the Effort.

Ok, onto the second paragraph. I will be very informal here :)

  Let $Q$ denote the density of stem-cells population.

Within a cell population (cancer or otherwise), often there is a small subpopulation of stem cells (the rest of the cells are differentiated cells). So if there are $N$ cells in total, roughly $S=QN$ will be the number of stem cells present.

  A percentage $\eta_1$ of these ones are supposed to undergo asymmetric division with one daughter cell identical to the mother cell and the other one committed to differentiation.

Within the population of stem cells (which are a subpopulation of cells), there will be further subcategories with different reproductive behaviours.
Notice there are really only 3 options: a stem cell becomes (a) two stem cells, (b) two differentiated cells, and (c) one stem and one differentiated cell.
This sentence means that roughly $s_1 = \eta_1 S$ cells will divide in the asymmetric pattern given above.

  A percentage $\eta_2$ of the stem-like population differentiate symmetrically and go to the line of mature cells.

This means the number of symmetric divider cells is roughly $s_2 = \eta_2 S$ (both outputs will be differentiated.

  The rest of them, a percentage $p = 1−\eta_1−\eta_2$ is supposed to self-renew: both cells that result from mitosis are identical to the cell that entered to the cell cycle.

Finally, around $s_3=pS$ cells become stem cells again, i.e. division type (a).

  The same duration $\tau$ of the cell cycle is supposed for all types of division.

In order to divide, every cell has to undergo a complex process called the cell cycle. This takes time; in other words, it upper-bounds/limits the rate at which cells can divide. Presumably, different cells take different lengths of times to divide. This assumption above ignores this issue.

Edit (062018): let's take a look at the equation
$$
\tilde{r}(P) = r_1(P)\frac{x_0 - R_0}{x_0^{-p+1}} \;\text{  with  }\;
r_1(P) = \frac{P^m}{P^m + P^m_0}
$$
where $Q$ is the density of the stem cell population, $P$ is the amount of plasmatic drug, $P_0$ is the half-maximum activity concentration, $m$ is the Hill coefficient, $x_0$ is the number of infected cells, $R_0$ is the number of resistant cells, $p$ is the probability of mutation, and $q=-p\in (-1,0]$.

From a high level perspective, we need to account for three effects of treatment:
(1) the building of the cancer's resistance to that treatment,
(2) the increase in drug effect as it gets absorbed and decrease as it is excreted, and
(3) the effect of the drug on the target cells.

First, notice in the differential equations:
\begin{align}
\dot{Q} = f(Q,t) - \tilde{r}(P)Q^{q+1} \\
\dot{D} = -\lambda_0 D + K \\
\dot{P} = -vP + \lambda_0 D
\end{align}
that (2) is being handled in the equations for $D$ and $P$.
Drugs start in some compartment (like the intestines when you swallow a pill) where they are not so useful against leukemia. Here they start with some concentration $K$, and the amount of drug decreases with first-order kinetics, i.e. the first order linear differential equation that shows $D$ decreasing. See an article on pharmacokinetics for more info on this.

Once the drug is absorbed (i.e. contributes to $P$ instead of $D$), it enters the plasma and starts to have an effect on the leukemia cells. (Notice that (2) is being handled here as well, in the $-vP$ term of the differential formula for $P$, which measures how fast your body is destroying the drug.)

Naturally, only the drug concentration $P$ in the blood plasma can affect the cancer cells; hence, the term for $\tilde{r}$ only depends on $P$!

Next, we can see how the model accounts for (3) in the differential equation for $Q$. Again, we have first-order kinetics of $Q$ (by the first-order linear differential relation), modulated by $r$ and $q$. Since $q + 1 > 0$ and $\tilde{r} \geq 0$, we know that as $\tilde{r}$ increases, we are causing $Q$ to decrease faster, i.e. we are hurting the cancer more (good!). Thus we expect that as $P$ (the drug concentration) increases, $\tilde{r}$ should also increase.

Ok, so now for (1). Notice that the equation for $\tilde{r}$ breaks into 2 terms. The second term is $R_T=(x_0- R_0)/x_0^{-p+1}$. This captures the effect of resistance, as the cancer evolves via mutation to gain resistance to the drug. Notice there is no dependence on the drug itself (just as described in the Goldie-Coldman hypothesis). (Note that this may not be realistic, since the drug will induce an (un)natural selection pressure on the cells and encourage the ones that resist the drug to proliferate more easily; however it does simplify the model).
Notice that $R_T$ decreases as $R_0$ increases, meaning that as the number of resistant cells increases, the efficacy of the treatment decreases.

The first term, i.e. $r_1(P)$, describes the effectiveness of the drug as a function of its concentration via the classical Hill equation.
Simplistically speaking, drugs often act via receptor molecules on the surfaces of cells; once all these receptors are saturated, the drug cannot affect the cell anymore! Hence, the effect of a drug "levels off": as its concentration increases, it will bind more and more receptors (and thus have more and more effect, albeit at a diminishing rate), until saturation occurs and adding more drug (i.e. increasing $P$ no longer does anything). You can see this in the equation for $r_1$ since $\lim_{P\rightarrow\infty} r_1(P) = 1$ (though of course $\partial_P r_1 > 0$ still). The $m$ and the $P_0$ simply control this relationship: the Hill coefficient $m$ describes the "cooperative binding" properties of the drug (see the link above for details), i.e. whether binding accelerates further binding or not, while $P_0$ (usually denoted $K_A$, or called the dissociation constant) describes the ligand concentration at which half the target sites are occupied.
Higher $P_0$ means that occupying half the receptor sites requires a higher concentration, which means you need more drug for the same effect, i.e. the efficacy of the drug is poorer; this is why $P_0$ appears on the denominator: as it increases, the effect of the drug on the cells (given by $\tilde{r}$) will decrease.
Essentially, $m$ controls how fast the drug reaches peak efficacy (how steep the curve is), while $P_0$ controls the physical properties of molecular binding (the translation component of the curve).


Would intravenous insulin + glucose significantly accelerate glycogen synthesis? Would an intravenous injection of insulin + glucose result in significantly quicker replenishment of exhausted glycogen stores than an injection of glucose alone?

This is a strictly theoretical question and I'm aware of serious dangers of intravenous insulin (Diabetes Spectrum). It is to help with writing a story in which a quick recovery from exhaustion is needed.

After heavy exercise, during which the glycogen stores are depleted, the glycogen can be replenished fully in about a day by consuming high-carbohydrate meals (PubMed).

According to one study, intravenous glucose stimulates glycogen synthesis, but there is no timing mentioned.

Would adding insulin into glucose injection further accelerate glycogen synthesis and for how much? Is there any minimal time needed for glycogen synthesis regardless of the amount of glucose and insulin available?

The added insulin would probably inhibit the natural secretion of insulin from the pancreas, so does intravenous insulin injection even make sense?

Concluding from this 1991 PubMed article, intravenous (or subcutaneous) insulin may not stimulate glycogen synthesis more than naturally secreted insulin.

  Experiments carried out in man have suggested that insulin may play
  only a permissive role in the determination of splanchnic glucose
  uptake. In a study by DeFronzo et al. (5), in which the plasma glucose
  and insulin levels were raised via peripheral intravenous infusion to
  223 mg/dl and 55 μU/ml, respectively, net splanchnic glucose
  uptake was 1.0 mg/kg per min. The rate of glucose uptake did not
  change appreciably when the arterial insulin level was raised further
  to 191 μU/ml.

So, at insulin level 191 μU/ml, there was no greater hepatic glucose uptake than at 55 μU/ml and hence no further stimulation of glycogen synthesis.

According to Emedicine, insulin levels can increase to 276 μU/ml 1 hour after glucose administration.

Which means that even naturally secreted insulin can reach levels that no longer stimulate glycogen synthesis and there is no point to give insulin by injection to stimulate it.


Does arterial blood always flow away from the heart? Is there a negative net flow of blood in human arteries at any point of the cardiac cycle? I realise that blood flow can be turbulent, e.g. in the aorta or around stenotic arteries, but then the average is still flowing away from the heart.

The question was provoked by this graph, which admittedly I haven't seen in its context:

A similar graph showed negative velocities in the aorta and innominate artery of humans.

Simple answer, yes.

It really is a matter of how technical you wish to be. By defintion, all arterial flow conveys blood away from the heart. The largest arteries exhibit the Windkessel effect which allows for the compression-based effects that bobthejoe inferred. Explicity, as blood is pumped out of the left ventricle, it stretches te aorta, and this tension in turn causes compression on the artery and pushes blood forward. On the flip side, venous vessels (except the pulmonary vein) return blood to the heart, but here you are likely to encounter local areas of reverse flow. This is counteracted to a degree by one-way valves present in the large veins to keep the net movement of blood in the body always toward the heart.


What are the limiting factors of pathogen population size in human populations? I understand that one limiting factor in non-human animal populations is that increased pathogen populations decrease animal populations from killing them, which decreases the density of the animals, which makes it harder for pathogens to infect other animals. However, pathogens, at least in developed nations, don't seem to kill a large enough number of people for this to be the main limiting factor. So what else are the limiting factors?

One of the limiting factors is how many uninfected hosts exist. As a pathogen becomes more widespread, the probability of someone infected with it infecting someone else decreases, as it's more likely that the person will spread the disease to someone who already has it instead of someone who doesn't have it, preventing the virus's population size from increasing. See this for more information.

Also the more common a pathogen is, the more likely it is that people will take actions against it, for example by being more sanitary or getting vaccinated against it.


What is internal symmetry in membrane proteins? I have come across the term "internal symmetry" in the context of membrane proteins, but have never found a satisfactory definition.

I'm struggling to figure out exactly what this term means... What plane is this symmetry seen on? Is it dimers that are symmetrical or can a monomer also be internally symmetrical?

Internal symmetry in this case refers to cases where a part of the protein structure can be superimposed (approximately) on another. It's not a strict mathematical symmetry, more a 'resemblance'

For instance in the 12 transmembrane helix transporters, the first six helices are arranged similarly to the second six, such that if one were to cut the protein in half one would see that the two halves (approximately) superimposed.

Fig 3 of this Nature Micro shows it clearly. http://www.nature.com/articles/nmicrobiol20159 Where the blue helices in 3a could be rotated 180 degrees and then look very similar in arrangment to the yellow helices.


DNA of cellular organelle Why do some cellular organelles like mitochondria and plastids have their own DNA. And what is the basic difference between the DNA of the nucleus and these organelles?

Mitochondria and plastids are the result of two ancient mergers. A kind of symbiotic relationship where one cell phogocytized another. Rather than being digested, the phagocytized cell, complete with its own DNA cooperated with the cell that "ate" it. This was part of the evolution of eukaryotes. This idea is called endosymbiosis, and was championed by Lynn Margulis in the late 1960s. Mitochondria and plastids come from Bacteria, and carry the traces of their original DNA. However, a complete genome was no longer required for the new function, so mitochondria lost many redundant genes. Mitochondrial genomes are much smaller. Plastid genomes are larger than mitochondrial genomes, but smaller than the genomes from which they originated.


Are intracortical axon branches myelinated? I found the following pictures of axon trees:

source

source (axons are red)

but didn't find a concise answer to the following question:

  Is it possibly true that the intracortical axon branches (i.e. those that don't leave the gray matter) are not
  myelinated?  (The first picture seems to indicate that they have at
  least a smaller diameter, making them slower?)

A great reference for this question is Tomassy et al. 2014. Axons of cells from all layers lack a myelin sheath at their proximal segment, often called the axon initial segment. This stretch of unmyelinated axon is longer for more superficial pyramidal neurons (~150 $\mu m$) and shorter for those located in deeper layers (~25 $\mu m$), something which does not depend on axonal caliber. These authors observed that some of the superficial neurons didn't have any myelin for the length of axon observed (> 200 $\mu m$). They speculated that these are neurons that send their axons through the corpus callosum.

What is interesting is that superficial pyramidal neurons often displayed intermittent myelination away from that initial segment, with long stretches of axons (up to ~55 $\mu m$) being unmyelinated. Note that these myelin gaps are more than an order of magnitude longer than Ranvier's nodes.

What are these gaps in myelin good for? If these axons target other intracortical neurons, it is unlikely that the predicted transmission delay will have an important impact given the short distances in the cortex (~1 mm). For those neurons targeting other brain areas it may be somewhat more important. It is interesting, however, that these patches of unmyelinated axons both made and received synapses, suggesting that they may have a functional role.

The neurons in the OP's images are corticothalamic cells residing in (lower) layer 2/3 of the visual cortex (upper half) and thalamorecipient cells in layer 4 of the motor cortex (bottom half). Thus it is likely that their axon initial segment is unmyelinated. Although not yet conclusive, the results of the cited paper support the view that the axons of those superficial neurons that project to deeper layers or other brain areas are completely unmyelinated.

modified from wikipedia, CC BY-SA 3.0


Energy consumption of a resting synapse What is the energy penalty of maintaining rarely used synapse?

I'm wondering if forgetting is cheaper than remembering unnecessary details.

Short answer is yes, of course. Maintaining a healthy synapse is very energy-consuming process.

Let me first note that forgetting as we know it is more complicated than just pruning of synapses. It might involve rearrangement of proteins in pre/post-synaptic membrane and near it, local de-regulation of local protein synthesis, decrease in synaptic mRNA content and epigenetic change of transcription.

Secondly, average energy spending on a synapse, if it is not being used too often, includes mainly maintaining of membrane potential at resting -80mV level. Cellular membrane is a leaky barrier, so that without ion pumps, such as $K^+/Na^+$-ATPase, potential will quickly go to zero. Maintaining and recycling neurotransmitter pool also require energy.

Action potentials itself are passive processes, its generating does not require energy. ATPase will have to maintain potential at rest and keep it from fluctuating.

You can read this review for more: Synaptic Energy Use and Supply (Neuron, 2012). It generally describes where energy comes from and how it is being used.


Cloning DNA fragment - at least trying to I`ve been trying to clone a fragment (about 1.6 kb) using pGEM system, unfortunately it was not succesful. Then, I moved to pJET, and guess what? Again, very low transformation efficiency. Now I am moving to pENTR. However, I am think about why I am struggling to clone this fragment.
I have tried to increase insert:vector proportion; plate a higher # of e. coli cells; left my ligation reaction overnight, but nothing is very helpful. Does anyone have any guess or suggestion about it? Does anyone think that the fragment is too long?
Thanks :)

The fragment size itself shouldn't be a problem in principle.

Cloning has many steps, so anything you didn't specifically test could be causing problems. If different vectors are also not the problem, you should probably look at your experimental steps:

One problem can often be residual EtOH from cleanup steps, which will make your ligation and transformation very inefficient.
You should also test your competent cells with another plasmid to be sure, that they are still viable
Have you checked that all fragments run at the correct size on a gel? You might have star-digestion or bound enzymes that cause problems. Additionally you could also check the ligation product on a gel (though you won't be able to use that for transformation), to see if the reaction works correctly


Can Oxaloacetate cross the outer mitochondrial membrane? I am aware of the Malate–Aspartate Shuttle, but something is not clear to me and different sources seem to contradict each other. Some show oxaloacetate (OAA) being reduced to malate in the mitochondrial inter-membrane space (IMS), whereas others show the reduction happening in the cytosol.

Where does the OAA → malate reduction happen? i.e., can OAA cross the outer mitochondrial membrane (from the cytosol into the IMS) so that it can be reduced in the IMS, or must it be reduced in the cytosol before crossing either of the two mitochondrial membranes?

In general the outer mitochondrial membrane is thought to be basically permeable (through porins) to small molecules such as OAA. As is typical in biology, the situation may actually be more complex -- see for example this paper. But I think the default assumption is that metabolites freely cross the mitochondrial outer membrane.

You might also ask whether either the mitochondrial MDH or the cytoplasmic MDH enzyme is likely to be found or be active inside the intermembrane space.


Why aren't there more Ash-Red pigeons? My favorite color pigeon is Ash-Red, but I don't see a lot of them.  I figured it must be a recessive phenotype, but when I googled it, I found out it's dominant.  So why aren't there more Ash-Red pigeons around?

Edit: I'm in North America.

Edit 2: This website from the University of Utah is where I learned that Ash-Red is the dominant phenotype.

Welcome to Biology.SE

Assumption

I will assume it is true that the allele causing a ash-red plumage is dominant over all other alleles. Note however that you should cite your reference when making such claim in your post.

Dominance and allele frequency

Phenotypes associated to a dominant allele A aren't necessarily more common than the phenotype of the recessive allele a. It all depends on the allele frequency. If the dominant allele is at low frequency then both AA and Aa (both displaying the dominant phenotype) are at low frequency (esp. AA individuals) and most individuals are aa and show the recessive phenotype.

Learn more

You might want to read about Hardy-Weinberg rule with this post for example.


Generating custom human DNA sequences based on traits such as eye colour? I'm wondering if it would be possible to create software (unless some already exists, but I couldn't find any) to generate human DNA (the base pairs on the double helix) containing genes representing specific permutations (eye colour, hair colour, etc.)?

Basically, something like the "character builder" from those "Saints Row"-style video games, except with actual human chromosomes, enabling you to essentially create a 'custom' human.

Of course, that is assuming that all human DNA has a common structure, and that the entire sequence can either be assembled from individual chromosomes, or by using a reference genome and modifying specific genes/chromosomes according to user input. Is this the case?

One setback here, of course, could be the number of bases in each chromosome, which ranges between 100 million and 250 million, and the (approximately) 23000 human genes - a lot of data to manipulate.

A major limiting factor in such an exercise is the complexity of the biological process under question (eye colour etc.,) and thus, our nascent understanding of these. What I mean is that there is not a single gene that determines a given characteristic, rather it is the complex interaction of a set of genes in different conditions responding to environmental cues and such. We are barely at the level of scratching the surface when it comes to understanding the mechanisms that underlie such outputs. And so, we are long ways off (maybe hundreds of years?) before we can even start thinking about coming up with feasible approaches to such objectives.


Can anyone identify this bug/insect? !Saw this bug/insect/spider? on a ranch in Santa Ynez, CA. Pretty fast moving-this was the only photo I could get. The creature is the thing in the photo that looks like two puff balls on a very black body. (The smaller puff is the front of the body.) Maybe a bumble bee? Did not appear to have wings.

Perhaps it was a species of velvet ant (a type of wasp from the genus Dasymutilla). The females lack wings, and it appears like what you describe and vaguely see in your image.

Here are some photos:

Photo 1 Source

Photo 2/Information Source


Glycogen vs cellulose-curvature of glycogen molecule? I was wondering if anyone knows what the degree of curvature is or bond angle between the $\alpha$ glucose molecules in glycogen is. I know that glycogen/amylose/amylopectin have a general curved backbone (as well as branches in glycogen and amylopectin). This is a consequence of the 1,4-glycosidic bond between $\alpha$ glucose molecules. On the other hand cellulose has straight molceules, which is a consequnce of the 1,4-glycosiodic bond between $\beta$ molecules with alternating orientation. However I cannot find anywhere what the degree of this curvature is in glycogen backbone, or the bond angle between molecules in $\alpha$ 1,4-glycosidic bond?

Interesting question. Here, the question actually comes down to how the bond actually looks vs how we depict the bond. In detail, see this image of maltose from here:

Pay attention to the geometry of the glycosidic bond. From how it is depicted, one would conclude that it is straight in geometry. But how it actually looks is like this:

Now, the obvious conclusion is that the glycosidic bond does have an angle.
Now, with introduction over, lets come to the main point. After searching a lot, I found the value of this angle. It is 109°, much closer to the general tetrahedral angle (109.5°) of sp3 hybridized oxygen atom (deviation could be due to steric hindrance). See this article:

300 alpha-glucose units, bonded by $\alpha$-1,4 glycosidic linkages, making a 109 degree angle between 2 C-O bonds
causing the polymer to twist into a helix. -OH group of C2 projects out into the middle and form H bonds with each other, stabilising the shape.

Yes, the glucose molecules in amylose form intermolecular hydrogen bonds which stabilize the molecule. See this article and in the diagram, notice that the hydrogen bond is formed between adjacent glucose units (to the left and right of the glycosidic oxygen atom):

Although the $\alpha$-(1$\rightarrow$4) links are capable of relatively free rotation around the ($\Phi$) phi and ($\Psi$) psi torsions, hydrogen bonding between the O3' and O2 oxygen atoms of sequential residues tends to encourage a helical conformation. These helical structures are relatively stiff and may present contiguous hydrophobic surfaces.


Is there a possibility that medicine will affect the efficiency of natural selection? I mean, saving sick people means that they possibly can propagate something that nature does not allow. I know that there is already something that operate at genetical level producing alteration, i.e. genetical mutation. And i am well aware that natural selection and genetical mutations take place really slowly.

p.s. i really want medicine to work!!

Summary:  Yes it can, but not the way you might think.

Humans aren't under a lot of selective pressure on a large scale right now.  We have a lot of control over our environment, and you're accurate that disease (or I'd add massive, fatal natural disasters) are the biggest ways we would see a large genetic shift.  (Or genocide, which is an extremely unnatural, artificial selection, but some of our species have historically been horrific enough to try to do this.)

Small local natural selection has happened in areas where Malaria is endemic: many people die from malaria. some people die early from homozygous sickle cell anemia, but those who are heterozygous have "sickle cell trait" (because of incomplete dominance) and have deformed enough RBC that malaria isn't able to infect them well.  So the survival advantage is enough that the prevalence of sickle cell alleles in these areas is higher.  There's a similar story with Glucose-6-phosphate dehydrogenase deficiency.

But on a scale you might be thinking of, the primary mechanism would be a global pandemic infection that targets people with a specific trait.  For example, if suddenly an incurable contagious, virulent, highly pathogenic, and fatal virus/bacteria that was only fatal to those with an allele for blood type A were to emerge.  Theoretically it would cause a genetic shift to eliminate type A blood from the gene pool, and reduce prevalence of type B (by eliminating AB due to the A).  Or if it attacked only one location of the world, but that's highly unlikely due to global travel.

Medicine could theoretically catch it in time - mitigate impact and prevent a large shift by creating a vaccine or cure that is effective and easily mass-produced.  The most likely to succeed would be a vaccine (yay for public health!).

Variations on this have happened to reduce or eliminate pathogens (such as polio and smallpox because of the vaccine) and their effect on mankind, but those have little to do with selection for human traits that would cause genetic shift.


How to calculate apparent diffusion coefficient (ADC) with example? Can someone give an example calculation for the apparent diffusion coefficient (ADC)?

There appears to be multiple ways that this can be calculated, e.g. as discussed here: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166577/

Do you like R ? if so, look at this package "dcemriS4"  and its example http://www.inside-r.org/packages/cran/dcemriS4/docs/adc.lm

install.packages("dcemriS4")
install.packages("minpack.lm")
library(dcemriS4)
library(dcemriS4)

S0 <- 10
b <- c(0, 50, 400, 800)  # units?
D <- 0.7e-3              # mm^2 / sec (normal white matter)

## Signal intensities based on the (simplified) Bloch-Torry equation
dwi <- function(S0, b, D) {
  S0 * exp(-b*D)
}

set.seed(1234) # this is just to make the example reproducible
signal <- array(dwi(S0, b, D) + rnorm(length(b), sd=0.15),
                c(rep(1,3), length(b)))
ADC <- ADC.fast(signal, b, array(TRUE, rep(1,3)))
unlist(ADC) # text output
par(mfrow=c(1,1)) # graphical output
plot(b, signal, xlab="b-value", ylab="Signal intensity")
lines(seq(0,800,10), dwi(S0, seq(0,800,10), D), lwd=2, col=1)
lines(seq(0,800,10), dwi(ADC$S0, seq(0,800,10), ADC$D), lwd=2, col=2)
legend("topright", c("True","Estimated"), lwd=2, col=1:2)

Here you can see an example of the steps used for mir http://rsl.stanford.edu/moseley/tensorcalc/tensorcalc/Steps/ADCmaps/adc.html

here is to understand the math behind of its calculation
http://www.ajronline.org/doi/full/10.2214/AJR.12.9231

if you don't like R but you like Matlab, here you can use this code to calculate it in Matlab http://www.mathworks.com/matlabcentral/fileexchange/21130-dti-and-fiber-tracking/content/DTI.m one of the output is ADC for mir data


How can Giant squid have $20,000 mm^{-2}$ photoreceptor cells, but no cones? According to this post, Cephalopods have about $20,000 mm^{-2}$ photoreceptors in there eyes. However, Cephalopods (in my case, the Giant Squid) aren't born with cones (cells that dictate which colours you see). So are they born with about 20,000 rods (cells that help detect movement), or is there another type of cell involved?

First squid lack both cones and rods, they evolved their eyes independently, the cells they use most closely resemble rods but they are by no means identical.

In vertebrates there are two types of cells rods and cones both of which can be used to see movement (movement is just detecting changes in the visual field). rods are better at it becasue they are smaller so they can be packed tighter, thus they can detect smaller changes, but that is by no means their primary function. Rods detect luminosity, that is the intensity of light, but react to light from all parts of the visual spectrum.

There is a lot of debate about how much color squid and octopi can see. behaviorally they appear to recognize color, but they don't have differentiated cells or opsins to detect them.

I appears they have stumbled on a completely different way to achieve color vision, they appear to use weird shaped pupils and chromatic aberration.
I suggest reading the linked paper as you have to dive pretty deep into the physics of optics to understand. Basically different colors of light are bend by slightly different amounts by a lens, and they are using the multiple images of their U shaped pupils to gain color information.


How can biologists rule out multiple early organisms that went through conjugation? The current idea is that all life evolved from a single cell. Analysis indicates the probability of two different origins being very unlikely, given shared DNA. However, why couldn't numerous organisms have evolved and then conjugated, with a few lineages surviving? It would vastly increase the odds of modern organisms sharing the DNA that they do.

Because they would not use the same DNA codons. Codons are extremely conserved across life, with only minor variations, there is no reason this should be the case unless those codons are inherited from a common ancestor. This is contingent on what you mean by organism, prior to the incorporation of ribosomes it would be more possible.

If what you suggest had occurred it would drastically DECREASE the odds modern organism would share the same DNA.


Is there an optimal composition and length for protein linkers in FRET? I'm designing a protein that I'd like to use in FRET reporting.  General idea on the shape is:
FRETprotein1--Linker--CleavageSite--Linker--FRETprotein2.  I would like to know what AA are best for the linker, or does it matter?  I have heard SSG is a good choice, but when I started a lit review I become unconvinced.  If it doesn't matter, I may try and put more convenient restriction sites there.

Is there a good way to theoretically determine optimal length?  I realize that may change depending on which FRET protein pair is chosen.  The cleavage sites are between 15-18 AA long.  Unfortunately, I don't think I can give any more detail than that on the cleavage sites.

Response to answer:
So far there have been no FRET systems or tests published with the cleavage sites I want to study.  In fact, I haven't even heard of anyone else trying.  If I'm forced into a positive FRET probe, which I'm worried that I am, does anyone have any FRET pairings that don't interfere with Texas-Red on the spectrum?  My first choices were Venus and Cerulean, but if I have to make a positive probe then I don't think they are a good choice.

I am also about to undertake some FRET studies (this week in fact). FRET linkers are a thing of tinkering, unfortunately. Förster resonance energy transfer, or FRET, is a phenomena that decays with $ 1/{r^6} $, the radius between the donor and acceptor. When constructing FRET reporters, there are a few things to keep in mind:

Length of linker. The length of the linker (including any cleavage sites), follows an concave optimization curve. A linker too long (> 18 amino acids) or too short (< 5 amino acids) and the FRET signal rapidly diminishes. When considering a FRET reporter in which no cleavage site is introduced, I've seen reporter an optimal linker length of 7-8 amino acids. When including a cleavage site, I've seen optimal liker lengths reporter of 18 amino acids. TO my knowledge, there is no theoretical way to predict the FRET efficiency based on linker sequence, and from scientists I've talked to, they conduct a trial-and-error approach using purified protein products to screen for an optimal length if it appears necessary to do so.
Type of FRET reporter. Cleavable FRET reporters fall into two classes. Positive reporters, in which signal appears after cleavage, must use longer linkers to separate fluorophores enough to reduce the FRET phenomenon. Negative reporter, in which FRET signal is lost after cleavage, must necessarily employ both short cleavage sites and linkers, to maximize the FRET phenomenon prior to cleavage. Since you mention the cleavage site itself is 15-18 AA, I would certainly expect very little FRET when uncleaved, assuming that the linker and cleavage site are unstructured, as the distance between the two fluorophores is quite large for the FRET phenomenon. Alternatively, intramolecular FRET reporters are usually designed as positive FRET controls, using short linkers to maximize the FRET phenomenon. When tagging two proteins seperately for FRET, short linkers are also chosen, relying on some external interaction to bring them together, however, this requires a lot of optimization of linker length for both fluorophores for maximum efficiency.
Choice of linker amino acids. This part here is somewhat subjective. The choice I often see in the literature are the tiny and small amino acids (especially Ser, Ala and Gly). The choice of these is mostly because they will likely have the least interaction among the linker structure and adjoining proteins and will be the most flexible. The linker should be chosen to avoid use of putative sites for modification (e.g., phosphorylation, glycosylation), rigid geometry (Pro, or bulky aromatics) and excessive charged amino acids.

I should note that I have found no comprehensive review of these three parameters for FRET construct design, and I have gleaned them from the literature. In my opinion, linker length is more critical to optimize than its amino acid sequence, provided that the linker does not lend itself to stable/rigid geometry and modification.

I would also suggest seeing if FRET constructs have been made using your cleavage site of interest already, and perhaps use the same linking sequences. From this, you could construct a slightly shorter and longer construct to see if one is more optimal over the other.


If the average resting potential of a neuron is -70 mV, why is there such a high ratio of potassium ions inside relative to out? My bio teacher was discussing the ratios of different ions inside versus outside the cell.

$$\text{OUT:IN}$$

$$\text{K}^+ (1:20)$$
$$\text{Cl}^- (11.5:1)$$
$$\text{Ca}^{2+} (10000:1)$$
$$\text{Na}^+ (10:1)$$

Can someone provide specific details as to the relative quantities of these different ions relative to each other? In other words, given these ion ratios, provide me with how much of each type of ion there are and show why this adds to to -70 mV. I just want to make sure I have a realistic picture of the concentrations.

I think I am mixing up concentration with the ratio between inside and out. Although for every potassium ion outside there are 20 inside, the charge from the total number of potassium ions must be less than that of chloride or it would not be negative inside, right?

Representative ion concentrations are shown in Fig. 1:

The membrane is mainly permeable to K+. Because the Na+,K+-ATPase pumps K+ inside of the cell, it tends to diffuse outward again, thereby taking positive charge outside the cell and making it negative inside (extracellular space is pretty much devoid of charge due to its vastness). Because the membrane is mainly permeable to K+, the membrane potential can be estimated using the Nernst equation by taking into account only [K+]:

This delivers about -90 mV, using the values in Fig. 1, which is quite close to the cell membrane resting potential.

However, other ions have some limited permeability too and especially Cl- also has quite a large leak current. To add the permeability p of the various ions (for K+ p=1, for Na+ p=0.04 and Cl- p=0.45) into the equation and take multiple ions into account, the Goldman equation is needed:

This equation yields closer estimates of the membrane potential than the Nernst equation taking only K+ into consideration. However, other factors such as buffer effects (Cl- is often buffered) as well as active transport mechanisms may alter the outcome of the Goldman equation slightly.


Was site-directed mutagenesis used to study the effects of sickle-cell anemia? The title says it all. I am inquiring whether or not site-directed mutagenesis was used to study the effects of sickle-cell anemia/figuring out that specific amino acid mutation was the problem.

The cause of sickle-cell anemia to be a molecular defect was discovered in 1949 by Linus Pauling. In his experiment hemoglobin molecules were broken down to smaller fragments, which were then subjected to electrophoresis and chromatography. The results of these measurements were compared between healthy and affected samples, allowing the identification of a mutated fragment.
The amino acids in the mutated fragment were analyzed in 1956 by Vernon Ingram, identifying the single mutation. The process in a bit more detail is described on this webpage.

Site-directed mutagenesis is used primarily in research aimed at finding a gene therapy based treatment for sickle-cell disease, such an attempt is described in this publication.

Also, the technique was used on recombinant hemoglobin to create and study some properties of naturally not occurring mutations. [Link]


Flow Cytometry Channels I did a flow cytometry experiment for the first time. I had three conditions: (1) unstained healthy monocytes (2) healthy monocytes stained with green/red (488/570) from the Live/Dead thermofisher kit (3) dead monocytes stained with the same green/red dyes.

I did those condition to know what graphs to expects, and learn the FACs process and analysis. Would appreciate it if someone can answer the following questions:

So I have two dyes in my samples and a control. Which flow cytometry channel should I use in my plots (FL1, FL2, FL3, or FL4)?
How to know the percentage of live and dead cells in each condition?
Anyone knows a free analysis software?
How practical is R to do flow cytometry analysis?

I'll amend this answer as I get details from you.

What is your cytometer, and how are the optics set up? You typically have 1-5 lasers: UV (355nm), violet (405nm), blue (488nm), green/yellow (~561nm) and red (~633nm) lasers. Your FL number, FL1-4, typically refer to a particular PMT (photomultiplier tube) and filter combination. For example, a typical FACSCantoII has a 4-2-2 setup with 4 PMT on the blue laser, 2 on the violet laser and 2 on the red laser (if you bought the device that way, there are other configurations). These fluorescence channels are set up to detect a particular fluorophore or equivalent with a bandpass filter. The base filters on FACSCanto II red laser are 660/20 and 780/60. These filter light emitted by the stained cells at a particular range of wavelengths, and you read them as 600nm +/- 10nm and 780nm +/- 30nm, for example.

You can set your software up to be FL numbers or fluorophores, but what you need to know is what filter is FL1 and so forth? Typical cytometers like FACSAria, these are FL1 = FITC, FL2 = PE, FL3 = 7AAD, PerCP/Cy5.5, etc., FL4 = APC.

So you used a live/dead thermofisher kit, please provide us also the catalog numbers.

What we want to do is take the information about your dyes and about your cytometer and reconcile them to determine what channel they should fluoresce in. 488nm looks like FITC or FL1 and 570nm looks like PE or FL2, but these look like lasers, whereas you want to tell me the dye emission to match it to a channel, using the information about your device configuration!

As for software, there are a number of good, expensive options like FCS Express and FlowJo but they're costly. See if your core or what have you has these available for you to use on-site. Otherwise, the on-board cytometer software like FACSDiva may need to suffice, and often does. I've used some of the "free" ones but they're very clunky and/or terrible to use.

R has some usefulness for high-dimensional analysis, but you need to be able to use R fluently, and you can't draw manual gates. There do exist helpful packages with good documentation like X-cyt (broad institute), though. And for visualization like PCA and t-SNE, R has a lot of documentation for flow data. Also consider R loads everything into RAM so on a slower 2-4GB computer it might have lackluster performance.

To start with your analysis, I'll ask why did you use two dyes? The LIVE/DEAD product line are reactive with free amines which present inside and outside the cell. Dying cells have more permeable membranes and take up more dye. So when you analyze the cells, everything is positive, but the dead and dying cells are 1-2 logs higher intensity of staining compared to the live population.

So the first thing any flow experiment needs are controls. You have unstained controls, FMO controls and compensation controls. The unstained just gives you an idea your morphology by light scatter, but for low-dimensional experiements can act as an FMO. The FMO or fluorescence minus-one is a cell stained with everything in your antibody/dye panel except one marker, so that you can compare against the fully-stained sample and see where to draw your gate. Compensation controls help the cytometer correct for the fact that filters pick up emission from other fluorophores than the target. You also have a biological control, which is good, because for analysis you always want to see where a clear positive and negative population lay on your dotplots or histograms. Live cells help you see where the positive and negatives are but may have a weak positive signals, and unstained cells will have a negative population that is shifted down 1/2 log or so because they dont have any dye at all. The dead stained cells will show you a strong positive signal and potentially a weak negative signal. Use these to draw your gates.

So then compensate the data electronically with your software (follow the manual), and create a dotplot with FSC-A and SSC-A on the axes. Only experience will tell how your cells look on this plot, but for reference, a blood or leukocyte sample would like like this:

You want to draw a gate around your monocytes and then create a plot based on your monocyte gate (at least gate out debris). It's also useful for further experiments to stain with a monocyte marker so you can dump everything but your target cells, so use CD14, for example, which is specific to monocytes.

On the next dotplot, make the axes FSC-A and FSC-H. This is a doublet discimination step where laser area scaling done before a cytometer run helps a lot (see your core expert). The principle here is to gate out (get rid of) cells that are stuck together:

Then you would want to look for your target cells. If they're both live/dead dyes you're going to have the same signal on two different channels, so you can probably just pick one, like live/dead green.

You can do a histogram of FL1 based on the cells kept in the doublet plot. You should see two discrete peaks on a log or bi-exponential transformed intensity axis (width basis -10 is good to use, but FACSDiva does it automatically). Width basis is a co-factor that compresses the data around 0, so negative populations get smaller and you get better resolution among the positive populations.

You would draw a bifur gate between the positive and negative peak or a range gate around the positive, and select tell the software to generate statistics to get your percentages. And you can repeat for the FL2/red dye to get those percentages, too, but both markers are looking at the same thing.

Then, apply those gates to all your samples and adjust the gates based on what the data looks like.

Please try this presentation: https://www.slideshare.net/richardhastings589/kumc-introduction-to-flow-cytometry


What is meant by "opposing plasma membrane" with respect to cell adhesion molecules? I am reading the Handbook of Neurochemistry and Molecular Neurobiology and I am learning about cell adhesion molecules (CAMs) and I have come across the following:

CAMs are involved in homo‐ or heterophilic interactions with molecules
positioned on opposing plasma membranes, and such interactions are
referred to as trans‐interactions. In addition, CAMs are often
involved in homo‐ or heterophilic interactions with other
membrane‐associated molecules positioned in the same plasma membrane.
Such membrane‐lateral interactions are referred to as
cis‐interactions.

I know that cell adhesion molecules are proteins mediation cell-cell or cell-extracellular matrix interactions. However, in the above excerpt from the book in the following statement: CAMs are involved in homo‐ or heterophilic interactions with molecules positioned on opposing plasma membranes, I am not sure what exactly is meant by "opposing plasma membranes". I think that this refers to the plasma membrane of a neighbouring cell the CAM is interacting with, however I am not fully certain.
Any insights are appreciated.

Opposing means facing each other, so the two outer surfaces can interact. Like two opposing armies.
I found an article:
"Pharmacology of cell adhesion molecules of the nervous system"
at
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2644493/
doi: 10.2174/157015907782793658
"...CAM-induced intracellular signalling is triggered via homophilic (CAM-CAM) and heterophilic (CAM - other counter-receptors) interactions..."


Why are some viruses not communicable person-to-person? Below are two quotes from the CDC about Hantavirus:

  "Researchers believe that people may be able to get the virus if they
  touch something that has been contaminated with rodent urine,
  droppings, or saliva, and then touch their nose or mouth."

and:

  "You cannot get the virus from touching or kissing a person who has HPS."

This is hard to believe.  So, since human saliva is not a problem, can you be contaminated
by human urine or human droppings?  The only way for me to interpret this logically is to
say that this virus lives at the end of the digestive tract (for both rodents and humans)
and people can be kissed because they have much better hygiene than rodents.  Is there a
better interpretation?

Also, is there a simple reason why Hantavirus leaves the mouth (moving to the end of the
digestive tract) of an infected animal, but influenza does not?

Viruses can have many different conditions necessary for transmission.  Viruses which have membrane surface coats (like HIV ) need to be in water all the time to survive.  Cold and flu viruses are more resilient and can survive on a surface such as a doorknob with a halflife of 18 hours(!).  Fortunately we are also have a reasonable intrinsic resistance to cold and flu and I think most infections do not result in symptoms.

Viruses often only infect some parts of the body.  Venerial diseases are a classic example of this where only contact of genitalia might cause transmission. Its probable that Hantavirus is not excreted through the sweat glands or in saliva.  If it did it would certainly be a more devastating disease.   It may also only be serious when the virus is introduced into the lungs, which may make transmission difficult.

For Hantavirus human to human transmission looks possible as observed by these folks. Even so, transmission is still so rare that there is no accounting for it in public health policy.  (they might also have been mistaken!).   Its possible that the virus requires transmission from a mouse to be virulent in humans. Its possible that the human transmission mechanism is so improbable (ingestion of faeces of infected human for instance) that you just dont' see it happening with the few cases of Hantavirus infection we have on the books.


What does sympathetic and parasympathetic 'tone' mean? My professor's lecture notes say that " The basal rate of firing is called “sympathetic tone” and 'parasympathetic tone"  , but a table I found on the internet  says that the parasympthetic system has no tonic activity.

Does saying the ANS has tonic activity mean that it sends impulses continuously and at a low rate to effectors? How is the ANS considered rapid then?

On Euroform Healthcare
It is written that without the sympathetic and parasympathetic tones, we would not be able to regulate the activity of organs or bring it up and down, I don't understand why that's the case ?

I'm very new to this whole topic (ANS) so please go lightly on me.

Short answer
Parasympathetic tone is not necessarily mediated by tonic firing.

Background
Nice question! I think part of the confusion stems from terminology. Let's start with some definitions first.

'Tone' in sympathetic tone can be translated as mean activity level (Hayano & Yuda, 2019).
'Tonic' firing by neurons may be translated as a sustained response, which activates during the course of the stimulus (Wang et al., 2014), although some neurons have intrinsic tonic activity as well, like thalamocortical neurons. This opposes to phasic firing neurons.
'Phasic firing' refers to a transient response with one or few action potentials at the onset of stimulus followed by accommodation (Wang et al., 2014).

In your post you seem to assume that parasympathetic tone equals tonic firing activity. I'm not so sure about this. For example, I found a catching paper on the parasympathetic regulation of lung function in guinea pigs (which lacks sympathetic innervation altogether). The paper nicely illustrates (Fig. 1) that parasympathetic regulation of the bronchi in guinea pigs is mediated by both tonic and phasic (burst) stimulation (Myers, 2000):

  [P]hasic neurons in guinea pig bronchial parasympathetic ganglia
  respond to a prolonged suprathreshold stimulation with a
  high‐frequency burst of action potentials ..., whereas tonic neurons are nonaccommodating and will respond with relatively lower
  frequency action potentials...

Fig. 1. Phasic and tonic neurons in guinea pig bronchial parasympathetic ganglia. source: (Myers, 2000)

References
- Hayano & Yuda, J Physiol Anthropol (2019); 38(3) (2019)
- Myers, JCN (2000); 419(417): 439-50
- Wang et al., Channels (2014); 8(4): 298–307