What factors should I consider when selecting a reference genome for mapping?

There are many reasons!

Let's assume you are using the Human reference genome. The latest version is hg38 or GrCh38. This came out roughly three years ago (Dec 2013). Although now these same reasons do not really apply to this particular assembly, but no other assembly comes to mind where these reasons are demonstrable. When dealing with RNA-Seq data you carry out a few common tasks.

Annotations: When a new assembly comes out, all existing annotations are standardised on the previous assembly. Take for example GENCODE, that particular links to the current version of gencode, which is now based on hg38. But, more importantly notice that they still maintain the same release for hg19/GrCh37. From my experience, it takes about 1-3 months for annotation databases to migrate to a new genome assembly after the assembly is released.
Conservation tracks: These are the tracks which take the longest to get updated. I will not post a link to the tracks here. But, here's the UCSC table browser, you can go to the comparative genomics tracks and view the conservation tracks (Phylop, Phastcons) which are available for each assembly. Again from experience, it took more than a year for these tracks to be generated for hg38. So it is just better to work on the previous assembly if you want to this particular information, because generating these tracks by self is a very tedious and computationally intensive task.
Risks associated with unfinished genomes: This does not really deal so much with the human genome as the gain is ever smaller with each consecutive assembly. But considering a assembly which consists of 70% scaffolds, the variation between assemblies tend to be huge. For functional studies as opposed to insilico studies, it makes no sense to redo the entire analysis every time a new assembly comes out, since the insilico part of the study is the predictive pillar on which functional validations are based. Although the same does not apply to insilico studies where the results presented to the public are solely predictive.
Incoherence with existing studies: This is a major obstacle for using a newer assembly, especially applicable towards unfinished genomes, wherein the results may be widely variable and do not align with pre-existing knowledge. Of course, you may be the one who is correct but it is also possible that the variability in your results is the result of human error. Therefore, it is just better to wait for a "landmark" study to introduce the assembly to the public, allowing your study to undergo less stricter perusal and also allowing you to validate the expected variability in your results.
Pitfalls during functional analysis: For RNA-Seq analysis it is common practice to use RT-PCR for a particular gene to establish the expected expression level for that gene, which in turn will validate a successful RNA-Seq experiment bereft of shady PCR duplications and artefacts. For this particular part you would first create a primer, which validates the expected expression level of that gene. But this particular primer originates from a particular assembly. It is also possible that the region which is amplified may have shifted or changed between assemblies. So when you align your data on a different assembly from the one which was used to create the primer, you may get an unexpected expression level for that gene, as the original primer amplified an incorrect region, which got fixed in the newer assembly.

I know there are many more. But, these are the only ones which comes to mind at the moment.


Alas, the great problems with protein formulation. I assume that the labeling chemistry forces you to use the 8.5 pH. (I don't think this is necessarily true since succinimidyl chemistry does work at pH=7.2 and the NHS ester is fairly unstable above pH=8.6)

We usually tackle this problem entirely by brute force ie. testing multiple buffer condition with different bases and different salt concentrations. First attempt would be to try out all of the Good's Buffers notablely HEPES, TRIS, MOPS, Tricine, Maybe you should look at both zwitterionic buffers and non-zwitterionic buffers. In your case, the succinimidyl is vunerable to primary amines so avoid things like Tris/Glycine.

The second thing to test would be various salt concentrations. Since you're already dumping in Sodium Bicarb, NaCl should be great. Unfortunately, this is where things get tricky since it is hard to know if your protein precipitates at low salt or high. A test from 20 mM, 50 mM, 100 mM, 150 mM, 200 mM, 500 mM should cover most of the interesting regimes.

Alternatively the sudden change in the ionic environment around your protein may be causing it to precipitate. You probably should dialyze or purified your protein in PBS to allow it to refold appropriately.


In most eukaryotes, the kinetochore protein complex assembles at a single locus termed the centromere to attach chromosomes to spindle microtubules. Holocentric chromosomes have the unusual property of attaching to spindle microtubules along their entire length.

source


What does chrUn mean in the output from a Bowtie run on human sequences?

I presume chrUn_KI270424v1 refers to a scaffold or sequence that has not yet been assigned to a chromosome. The designation after the Un (unknown or unassigned?) may refer to a particular single sequence or a scaffold. You will be able to determin this by examining the reference sequence and its documentation.

(My assumption is based on the sort of thing one finds in the various versions of Drosophila reference genomes, with which I am familiar. So I can’t help you with the specifics of the human genome.)


Does chicken embryo form the disc called "discoblast" in the cleavage and blastulation of chicken?

It is a mnemonic of two words: discoidal + blastula = discoblastula.
So it suggests that cleavage is partial discoidal in birds.
Embryo forms disc.
Cells called blastodisc are on top of the yolk.
It seems that the formed disc is blastodisc.


Are humans the only mammals that are known to display homosexuality?

Although intuitively it would seem unlikely that there could be an evolutionary advantage to homosexuality (other than some theories regarding population control), homosexual behavior has been clearly observed in a variety of birds, monkeys and apes, lions, dolphins, lizards, insects, and plenty more.

The case of the bonobo is particularly striking in that homosexuality and bisexuality are more common than heterosexuality.  According to this Wikipedia article:

  Bonobos, which have a matriarchal society, unusual among apes, are a fully bisexual species—both males and females engage in heterosexual and homosexual behavior, being noted for female–female homosexuality in particular. Roughly 60% of all bonobo sexual activity occurs between two or more females. While the homosexual bonding system in bonobos represents the highest frequency of homosexuality known in any species, homosexuality has been reported for all great apes (a group which includes humans), as well as a number of other primate species.

Although the complexity of sexuality likely points to the existence of multiple genes playing a role in sexual behavior and preference, at least one study$^1$ points to a single gene playing an important role in the sexual behavior, of female mice:

  In this study, we generated mutant mice specifically lacking the FucM gene that encodes fucose mutarotase. The homo- and heterozygous mutant females exhibited deficits in sexual receptivity as demonstrated by a drop in lordosis score. Moreover, the mutants displayed masculine behaviors and preferences to female urine over male urine.

1) Male-like sexual behavior of female mouse lacking fucose mutarotase, Dongkyu Park, Dongwook Choi, Junghoon Lee, Dae-sik Lim and Chankyu Park, BMC Genetics201011:62, DOI: 10.1186/1471-2156-11-62


Can excessive carbonated drink consumption lead to elevated red blood cell levels?

The main regulatory input into erythrocyte production is hypoxia. The response to elevated CO2 levels in the blood (hypercapnia) is mainly to increase ventilation (i.e. more and/or deeper breaths) so that the excess can be "blown off".

I think that some carbon dioxide could pass into the bloodstream from the stomach since gases tend to be quite good at diffusing across membranes, but this would be easily dealt with by the physiological mechanism described above.


Is it possible to make anaerobic media too reducing?

I notice that you don't specify pH, which might be important.

I don't know if you can put in too much reducing agent (I suspect not), but a large excess is often required as the equilibrium constants for disulfide exchange reactions are typically close to unity (see Cleland, 1963).

I also don't know if any of following has any relevant to your problem (again, I suspect not), but I want to briefly comment on two aspects of using thiols to as reducing agents in general.

Firstly, the oxidized (disulfide) form of thiols may react with a protein sulfhydryl. Using β-mercaptoethanol as an example (Scopes, 1993, p 320), something like the following may occur, where the reducing agent becomes (reversibly) bound to protein. If the reactive sulfhydryl is at an enzyme active site, this may lead to inactivation.

$$\ce{2 HSCH2-CH2OH  +  O2 -> HOCH2CH2-S-S-CH2CH2OH + H2O2\tag{1}}$$

$$\ce{HOCH2CH2-S-S-CH2CH2OH + HS-{Protein} <=>HSCH2-CH2OH + HOCH2CH2-S-S-{Protein}  \tag{2}}$$

As stated, equilibrium constants for thiol exchange reactions are often close to unity (Cleland, 1963).,
 $$\ce{R1-S-S-R2 + R3-SH <=> R1-S-S-R3 + R2-SH \tag{3}}$$
  For this reason, many protein chemists prefer to use dithiol analogs of threitol (dithiothreitol, DTT, or Cleland's reagent) or erythritol as reducing agent, as the oxidized form of these compounds are cyclic disulfides, where the equilibrium constant is displaced to the right  (see Cleland, 1963).

There is also the question of stability.

The half-life of thiols in solution are markedly pH and temperature dependent, as the  table below shows. The half-life of β-mercaptoethanol at pH 6.5 and 20℃ is greater than 100 hours, but at pH 8.5  and 20℃ it is only 4 hours.

The above table was taken from  Stevens, R, Stevens, L & Price, N.C (1983) The stabilities of various thiol compounds used in protein purifications, published in (the now-defunct) Biochemical Education. The full article is freely available as a pdf from the Wiley website


Repeats aren't the problem with CRISPR. They stop you from editing repeats and repeat-like sequences, but in principle they can be worked around through careful design of guide RNA. CRISPR techniques right now do have problems with off target effects, but these problems may yet be solved. The CRISP/Cas approach to gene editing already has a lot of different variants and is under continual improvement, so there's no reason to think it won't get better. There's also no reason to think that the 16% figure there is only influenced by the use of CRISPR/Cas - it's an experiment with lots of other variables.


Yes a range of pain exists. This can be seen probably in your friends who all probably have a completely different threshold for pain. When doctors ask patients to rate their pain it's usually to establish a baseline so after treatment we can see if there's a decrease. The different thresholds have so many factors from general health to receptors to brain activity to emotional state. You name it! Often just focussing on a pain makes it more painful.

It's definitely an unpleasant sensation pain but it's our way of our body saying "hey, you need to pay attention". Usually the response required is rest or to identify what might be there causing the pain. For example pain means we will withdraw very quickly from a hot surface. Doesn't even require the brain as it is a reflex arc which minimises the time we spend burning that part of our body. And as it continues to hurt we use the arm less letting it recover and protecting it from infection by doing so.
As these hazards of being cut, burnt, bit, knocked, fractured are very common there is a survival advantage to be the individual that is alerted to these hazards and take the necessary actions. Particularly in children where pain is necessary as it makes the baby know it needs to eat (or the mother) or that something isn't a good idea (putting hands on something hot).

However as you say there are times when the pain itself is more crippling than anything else and in that situation we have a problem. Childbirth, backache and in cancer or in tension headaches are just some examples. As being able to feel pain is pretty much required for a long life, the disadvantage of having pains like the above is less and doesn't outweigh the benefits. Pain is always going to be necessary. They also usually don't interfere with reproduction and so genes are passed on.


What is it that creates that wonderful smell after a fresh rain?

That molecule is called Geosmin. It is mainly produced 1 by Actinomycetes such as Streptomyces which are filamentous bacteria that live in soil. Other organisms also produce geosmin:

Cyanobacteria
Certain fungi
An amoeba called Vanella
A liverwort

It is an intracellular metabolite and cell damage is the primary reason attributed to its release. However oxidant exposure and transmembrane pressure also causes geosmin release in cyanobacteria. It seems that the release is triggered by some kind of stress.

I am not quite sure about their advantage to the host species.

1 or perhaps the most well-studied in


Serological assays measuring antibody response

Antibodies used for serological tests are performed in vitro, and are not required to be effective for eliminating the pathogen. For an infected individual, antibodies may play a role in neutralization, opsonization, or activating the complement system (checkout Janeway's Immunobiology for more details). There are a number of reasons why antibodies may be present and not trigger an effective response down these pathways.

For example, E. Coli O157:H7 produces Shiga toxin and there are immunoassays to test for the presence of the toxin in feces (1). Only low amounts of the toxin is needed to cause disease. Antibodies against the toxin have been seen in individuals with the disease, suggesting the toxin is not a strong enough challenge for an immune response Discussion of (2).

You could go case-by-case for each of the immunoassays and see why their targets are difficult to turn into therapeutics.


How would I represent this on a cladogram?

The short answer is that cladograms are not compatible with Linnean taxonomy.

The longer answer explain how and why. First, there aren't enough ranks in Linnean taxonomy to cover all the cladogram nodes. The "kingdom-phylum-class-order-family..." was originally based on similiarity and not on phylogenetic relationship. For example: the class Reptilia is no longer a clade, and the class Aves is a subclade of the order Sauroschia (of the "super"-order Dinosauria, which is a clade of Diapsida which includes modern reptiles and crocodiles). The birds (Aves) are evolution descendants of dinosaurs but they ranked by Linneous as class while dinosaurs, according to Linnean taxonomy were at most super-order.

So you need to choose: a pseudo-Linnean relationship tree or a cladogram phylogenetic tree (and then you should omit the ranks' names "class", "order" etc.

I'll try to sketch the tree you described:

 A
 |
 |-- B
 |-- C
 |
 .
 .
 .


Identify this insect - genus, species (orange, black)

This looks like a Weevil. Specifically it looks like a red/orange-spotted lily weevil

Here is some more information on it:

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

though the information is very limited.


What is Growing on These Tree Leaves? (Image)

This is actually not a gall as other answers have suggested.
This is likely a fungus called Cedar-apple rust (Gymnosporangium juniperi-virginianae).

The fungus only thrives in the presence of both Juniperus virginiana (Eastern red cedar) and apple (Malus spp.) trees.

The leaf in the picture belongs to some species of the apple genus and the growths are aecia of G. juniperi-virginianae. You can read about this interesting fungi through Rutger's Plant & Pest Advisory here.

You can see a picture of the fungi here, and I've included Sabrina Tirpak's (Rutgers PDL) photo of its aecia below:

http://plant-pest-advisory.rutgers.edu/3859/

Below is a visual of the telia of the rust fungus on J. virginiana:

 (Photo source: Ada Hayden Herbarium)


Metrics or operations on genome sequences in human genomic research?

The question of how similar two DNA or protein sequences are, is one of the most important problems in bioinformatics. While there is no definitive answer Bayseian statistics are often used to group sequences. There is a good explanation of the theory on this wikipedia page.

Alternatively one of the most commonly used programs to find similar sequences is BLAST. It is getting a little bit dated but you can find an overview on the statistics used by this program on this page

But there are many other methods out there.


The discovery of peptidoglycan, as present in the bacterium cell wall took many years.
“The terms mucopeptide, glycopeptide, or murein, used by some authors, are all synonymous with peptidoglycan.” [Ghuysen, J.M. (1968) Bacteriol. Rev. 32:425-64] Among those, Weidel and Pelzer previously coined the term murein [Weidel, W. and Pelzer, H. (1964) Adv. Enzymol. Rel. Areas Mol. Biol. 26:193].
Regarding the organized, higher structure of the peptidoglycan as found in the Gram-negative cell envelope, Salton [Salton, M.R.J. (1994) New Compr. Biochem. 27:1-22] mentioned the following:
“The exact nature of comparable ‘wall’ fractions obtained from Gram-negative bacteria remained a matter of uncertainty until the advent of electron microscopy of ultra-thin sections of bacterial cells as demonstrated by Ryter and Kellenberger [Ryter, A. and Kellenberger, E. (1958) J. Biophys. Biochem. Cytol. 4:671-678.]. The response of cells to the Gram stain procedure and the early chemical analysis of ‘cell wall’ preparations clearly pointed to some basic differences in the properties of the envelopes of Gram-positive and Gram-negative bacteria and the greater chemical complexity of the isolated fractions from the latter organisms [Salton, M.R.J. (1953) Biochim. Biophys. Acta 10:512-523.]. The structural complexity of the Gram-negative cell envelope was clearly resolved in the thin sections of Ryter and Kellenberger [Ryter, A. and Kellenberger, E. (1958) J. Biophys. Biochem. Cytol. 4:671-678.] and established the presence of an outer membrane as a characteristic feature of the cell envelope. The mysteries of the structure of the Gram-negative cell envelope were finally solved with the demonstration of the thin layer (peptidoglycan) between the outer and inner (cytoplasmic) membranes by use of lanthanum-stained thin sections by Murray et al. [Murray, R.G.E. et al. (1965) Can. J. Microbiol. 11:547-560.], and the isolation and demonstration of the thin murein sacculus of E. coli by Weidel et al. [Weidel, W. et al. (1960) J. Gen. Microbiol. 22:158-166.]. Thus, the complex cell envelopes of Gram-negative bacteria were resolved as consisting of an outer membrane anchored to the underlying rigid, thin, peptidoglycan layer or sacculus.”


Do the percentage values refer to the percentage of acrylamide in the gel?

Yes. The 8% gel is 8 g acrylamide per 100 mL. The “4-12%” gel is a gradient gel, which are useful for separating proteins over a large range of sizes. Read more about the uses and formulations of gradient gels here.


I am hesitant to provide 'positive' ID without location information, but this bird strongly resembles a Red-vented Bulbul (Pycnonotus cafer). The species is native to the Indian subcontinent, but is a common invasive species in many other parts of the world.

Key identifying features, with features visible in the photo given in bold (description from NZBirdsOnline):

Red-vented bulbuls are slim, starling-sized songbirds with predominantly dark plumage. They are typically bold and conspicuous, with repetitive, monotonous calls. Their slim build and curved bill are reminiscent of a honeyeater (e.g. bellbird or tui), although they are not closely related. The two most distinctive identification features are a small erectile crest on the crown (giving them a square-headed Roman helmet look when the crest is raised) and the diagnostic bright red patch between the base of the legs and the undertail. The head, hindneck and upper breast are glossy black, with a circular brown patch over the ear. This dark hood becomes streaked or scaly on the lower breast and merges into the pale grey belly. The upper wings and mantle are mid-brown with pale margins when in fresh plumage, creating a scaly appearance. The rump is white, and the tail is long and blackish with a prominent white tip. The bill, eyes and legs are dark. The sexes are alike, although males are slightly larger. Juveniles are dull brown with an orange or pinkish (cf. red) vent.

The red feathers around the vent do not have a special name - you can just call them 'the feathers around the vent'.

edited for the addition of location information

As the photo was taken in Northern India, the bird is almost certainly a Red-vented Bulbul. The Red-vented Bulbul is common throughout India, and there are no similar species in the range that could easily be confused with this species.


How the genome assembly be done after k-mer counting?

There are multiple ways of doing genome assembly.
The term you are probably looking for is "De Bruijn-Graph based assembly". Using this you can find a lot more different explanations of how it is done.

Another frequently used method is "Overlap Layout Consensus assembly", which in fact is not based on k-mer counting.


Why isn't there any repulsive force between Na+ and K+ disrupting thier roles in transmembrane voltage/ action potentials

The carriers of the charge are ions and they get repelled from each other well enough. Other than their charge there is only the size in which they differ (for all practical purposes). This means, as long as we are talking about membrane potential, the actors are just a mix of 1+ ions which don't come near each other. When size matters, for example in an ion channel, we are talking about single particles, so there is no action of a repulsive force between K+ and Na+.

From another angle: The charge is a force that emerges from a sea of particles, regardless if they are all of one kind or mixed K+/Na+. If you talk about a force between K+ and Na+ then you would have to separate all 10^15 or so K+ ions from 10^15 or so Na+ ions which is simply impossible, as they are mixed up.

http://en.wikipedia.org/wiki/Brownian_motion

http://en.wikipedia.org/wiki/Ion

http://en.wikipedia.org/wiki/Ion_channel


Those flowers don't come from the same plant as that big leaf in the front do they?  Cant help you with the leaves, but the flower looks like a daylily. source: I know nothing about plants, but happen to have a mom who got a degree in horticulture :)


Why does ant queen keep the eggs out of her hive?

According to various websites and literature I found,

Starting a new colony

During the mating season, Queen Ant grows wings and mate with male (flying) ant. In most of the species the queen will fly away to a new place where, she will loose her wings and dig a tunnel. She may lay eggs inside or outside because of the humidity and temperature, mostly they wait till spring, so that the humidity is high as well as warm temperature.

For laying eggs she will dig a tunnel inside and close the gates. She won't eat or move and completely avoid light, if the eggs are unhatched or some other problem occurs she will eats her own eggs. After around 8-10 weeks eggs will pop and you will get new worker ant babies. They will form the hive and feed the queen ant.

More info: http://antnest.co.uk/colony.html


It is the larva of Harmonia axyridis (Asian lady beetle).

The image posted by timbernasley is more accurate because the larva you have shown is in its late instar ,a stage not an early as this one.

Here's the link: Wikipedia


Why do most animals never seem to evolve over millenia?

How come most animals never seem to evolve over millennia?

The word "seem" in your question should not be disregarded. You seem to assume that cockroaches (or most animals as you say) did not change much the last tens or hundreds of thousands of years. But what do you know about that (no offence here)? Have you actually reviewed many kinds of research that estimate the rate of evolution of different randomly chosen lineages in the past 500,000 years? I think you assume that other species evolved slower than humans rather than know it. And you will certainly put much more importance to the evolution of the gene FoxP2 (involved in language) than to a gene allowing cockroaches to have a better sense of smell. This is a biased view of what is a rate of evolution. It would be much wiser to consider a rate of evolution as something like the number of newly arising mutations that succeeded to get fixed in the population. See Haldane's rate of evolution and the Darwin unit. Please don't make the mistake to think that being smart (or complex) is some kind of the goal of evolution and those that are not smart (or complex) are "less evolved" or that they evolved more slowly.

You also seem to want to point on the evolution of DNA and evolution of habits. I guess you might be appreciative of the evolution of human knowledge and culture. But this is obviously something that does not have to do with genetic evolution but is rather a matter of cognitive capacity. You cannot compare the change of culture and traditions of insects and humans as insects have mostly no traditions.

Now, this is obviously true that different lineages evolve at different rates. Many things influence this rates such as the population size, the mutation rate, the generation time, the selection pressure (which itself might depend on social structure or the rate of environmental change for example). In these terms, I would rather believe of Homo sapiens as a lineage that should have a rather slow evolutionary rate.

Homo sapiens is quite a recent species. And speciation is often linked with phenotypic divergence, with niche competition and niche complementarity and therefore with a high rate of evolution. In these terms, I would believe that humans are a lineage with high evolutionary rate.


Why do cockroaches flip over when they die?

It is a result from the insecticide you are using.  From this excerpt from the 10th Edition of the Mallis Handbook on Pest Control:

  Neurotoxic insecticides cause tremors and muscle spasms, flipping the cockroach on its back. A healthy cockroach can easily right itself, but without muscle coordination, the cockroach dies on its back. Cockroaches exposed to slow-acting insecticides that target respiration (energy production) also can die “face-down,” as they run out of energy without experiencing muscle spasms.

Here's also a website from UMass describing it in more detail:

  Most of these insecticides are organophosphate nerve poisons.  The nerve poison often inhibits cholinesterase, an enzyme that breaks down acetyl choline (ACh), a neurotransmitter.  With extra ACh in the nervous system, the cockroach has muscular spasms which often result in the cockroach flipping on its back.  Without muscular coordination the cockroach cannot right itself and eventually dies in its upside down-position.

And an entomology professor even answered this for Maxim:

  Most insecticides are poisons that target a bug’s nervous system. When you spray a roach, those neurotoxins cause tremors and muscle spasms, which flip
  it onto its back, and without muscle coordination, that’s the position it dies in


Implications of what the discovery of Naia means

The discovery strengthens the bering strait land bridge hypothesis because if I remember right they did genetic analysis and her ancestors were almost certainly east asian. As for opposing migration models, they involve boats. Some evidence exists for polynesians reaching the west coast of south america, but probably in small numbers and not before humans walked in from the north. There is more information here: https://en.wikipedia.org/wiki/Models_of_migration_to_the_New_World


From the general appearance, and from the opposite leaves (seen if you look carefully in the enlarged photo) I think this is Euoynmous europaeus (Wikipedia entry).  Specimens I've seen can grow like a ground cover, similar to your picture, but they also get shrubby/woody.  It is not native to the US.  We'd need more details/pictures to be sure, but I'm guessing from how you worded the question these might not be available.


Does an organism have only certain antibodies for life?

Are these the only B-cell types you will ever have? Or can the body generate new types of B cells, with new antibodies to deal with newly encountered threats?

New B cells are constantly formed throughout one's life; the B cells that are present in the newborn are constantly supplemented by newly formed B cells.

  ... there is no statistical difference in the rate of production of new immature B cells in the marrow of young and old animals. In total, our results confirm previous work showing that mature B cells in old mice have a slower turnover, but more importantly suggest that the defect in mature B cell turnover is not due to a decline in B lymphopoiesis, but rather an inability of the newly made cells to replenish the peripheral compartments.

--Aging and developmental transitions in the B cell lineage.

But the second part of your question seems to have a misconception.  The newly-formed B cells have no relationship to newly-encountered threats.  No matter what new pathogens you encounter, your newly-formed B cells don't reflect them; they are formed randomly, and it is only by chance that any particular B cell might be able to react with a new threat.  Fortunately, there are so many B cells that the chance of at least a few reacting is very high, even though only a tiny fraction of the whole B cell population can do so.

Although new threats (mainly) require new B cells, repeated threats don't -- once a B cell is stimulated the first time, it undergoes a pathway that functionally makes it longer lived and more effective, so that on repeat exposure these optimized B cells are called in and there's much less need for the new naive B cells.


Similarity between the human genome and archea genome in deep sea hydrothermal vents?

To achieve whole genome alignment between a genome as large as a human, and as small as an archea organism, is possible, but in the end, you'll have to strain your eyes to see patterns. The archea genome is about 1-5 million bp long, whereas the human genome is about 3.3 billion bp long (that's a thousand times too large).

In practice what this means is that you may or may not have small islands of similarity, in vast regions of emptiness.

Nevertheless, you can align whole genomes using the MUMer tool (http://mummer.sourceforge.net/). The white paper is here
Delcher, Arthur L., et al. "Alignment of whole genomes." Nucleic acids research 27.11 (1999): 2369-2376.

You might also be interested in reading this:

Wei, Liping, et al. "Comparative genomics approaches to study organism similarities and differences." Journal of biomedical informatics 35.2 (2002): 142-150.


Is there a negative correlation between the mRNA produced by the cell and the time of extraction?

$\gamma$-irradiation produces single- and double-strand DNA breaks, depending on the dosage, and activates DNA damage repair pathways like p53. During this time, the cell cycle arrests and most if not all mRNA production ceases. For sub-lethal doses of $\gamma$ rays, I would expect to see newly-produced mRNA levels drop off fairly quickly with time following the initial dose, then possibly begin to ramp up again later as the damage is repaired and the cell cycle arrest checkpoints released.


What are the main differences between lab-grown tissues and natural tissues from living animals?

Immortalized cell lines are often cancerous, which has large effects on their gene expression profiles. They also adapt to cell culture conditions after several hundred passages in culture. I've cultured both HepG2 cells and primary mouse hepatocytes. The HepG2 are a hepatocellular carcinoma line and grow fine in culture, while the primary hepatocytes don't really grow in culture and only live for a few days after you extract them from a mouse. We were doing gene transfer assays with both sets of cells. The quickly dividing HepG2 cells were easy to transform using PEI, and while primary hepatocytes could be transformed with PEI, they worked better with calcium phosphate, probably because it was less toxic. I noticed that HepG2 cells were smaller than primary hepatocytes, and the primaries were far more fragile, we could run HepG2 through a peristaltic pump with no problems, but had to handle all the primary cells by hand.

As far as cost goes, tissue culture is almost always cheaper. You can make a bottle of media for a few dollars worth of material and use it for several passages. The cost of running an incubator and biosafety cabinet are also minimal. So unless you're doing something unusual, cell culture is affordable. However, it's an incomplete model at best. Trying to create whole tissues in the lab counts as unusual.

Doing work with animals is far more accurate than cell culture, but much more expensive. Our mice are cheap, but still cost about a dollar each, and about 20 cents a day for housing. A typical biodistribution experiment will use 3 mice per time point and 8 - 10 time points, so 24 to 30 mice assuming no mistakes during dosing. On top of that, doing animal work has a lot more bureaucracy involved, with animal use protocols and approvals and inspections.

The question about whether to use animal models vs cell culture comes down to what you're trying to accomplish. If you're studying gene regulation or protein interactions, cell culture usually works better because it's more amenable to gene transfer and allows you to use techniques like fluorescent fusion proteins and bioconjugation. If you're studying drug metabolism and toxicity you should use whole animals because the interactions between metabolites and specific tissues are hard to reproduce in cell culture. In some far off future we may be able to totally replace animal models with cell culture or even computer models, but we're not even close.


Any species returning to the land twice throughout their evolution?

Woodlouse

Life emerged in the water. Ancestors of insects, spiders, myriapods and crustaceans were probably terrestrial (please correct me if that is wrong) but then, crustaceans evolved to living in the water again. Finally, woodlice went back onto land!


Is "A" inhibiting "B" and vice-versa, a positive feedback loop?

The situation that you presented in which an entity A inhibits the production of another entity B which in turn inhibits A, is a positive feedback.

In a network path or a loop the overall sign of the loop/path is the product of the signs of individual edges (interactions). In this case it is negative times negative which gives a positive sign to the loop.

In simple words, a positive feedback should lead to an entity promoting its own production, directly or indirectly; it can auto-activate itself, activate an activator or inhibit an inhibitor. In this case A inhibits its inhibitor. Sometimes you can have large loops like this:

This is still a positive feedback.

Moreover, your case would exhibit (with the right parameters) the dynamic properties of positive feedbacks (such as bistability and hysteresis).

Sometimes people also refer to this type of positive feedback as double-negative feedback (which I personally do not like because it is misleading).

  Positive and negative feedback loops may consist of a single component
  that activates and represses directly its own activity, respectively
  (Fig. 1B,C); or they may include several components and involve
  indirect interactions (Fig. 1D–G). The overall sign of a complex
  feedback loop (i.e. positive or negative) depends on the constituting
  elementary interactions (Fig. 1D–G).(1) For example, two mutually
  repressing components form a positive feedback loop (PFL, also termed
  “double-negative feedback loop”).

  Mitrophanov & Groisman, 2008

However, not all positive feedbacks lead to runaway amplification. That is a property of an unstable system. The degradation of the molecules (or death) ensures a finite (and stable) steady state. Sometimes (with certain parameter combinations, as previously mentioned) positive feedbacks can have two stable steady states. Depending on the initial condition, the system can settle to either of the states. In your example the two states can be — High-A Low-B and Low-A High-B.

Further reading:
Mitrophanov, Alexander Y., and Eduardo A. Groisman. "Positive feedback in cellular control systems." Bioessays 30.6 (2008): 542-555.


Examples of references for mathematical approaches in bioinformatics that are applicable to linguistics?

There are a number of more recent papers dealing with phylogenetic methods in reconstructing language history as well, including work by Colin Renfrew and Quentin Atkinson.

Here are two recent high-profile papers. Unfortunately, both are still behind paywalls, but even reading the list of papers they cite / that cite them would be a great way to answer your question.

 Bouchard-Côté A, Hall D, Griffiths TL, Klein D. 2013. Automated reconstruction of ancient languages using probabilistic models of sound change. Proceedings of the National Academy of Sciences 110: 4224–4229.
 Gray RD, Drummond AJ, Greenhill SJ. 2009. Language phylogenies reveal expansion pulses and pauses in Pacific settlement. Science 323: 479–483.

Maybe not quite as high-profile, but available online, one of my classmates did his (superb) undergraduate thesis as a Biology/Linguistics double major in exactly this topic. I think it could be a very useful place to start, although there have certainly been developments in the field in the last six years:

 Saunders, A. 2006. Linguistic Phylogenetics of the Austronesian Family: a performance review of methods adapted from biology.

See also the wikipedia page Quantitative Comparative Linguistics, this Stanford how-to, and this interesting article Linguistic Phylogenies Are Not the Same as Biological Phylogenies.


What is the optimal frame size for protein secondary structure prediction methods?

By frame size, do you mean sliding window?

I know that if you want to predict a secondary structure of a transmembrane protein, then your window size should be 20 amino acids (this is the average length of 1 transmembrane alpha helix spanning through the membrane).

I found this paper by Chen, Kurgan, and Ruan[1].

It basically says that the window size depends on what kind of pattern you are looking for, but in general, 19 residues should be optimal.

Also, secondary structure predictors rely on many features like hydrophobicity, missing coordinates in X-ray structures, B-factors, motifs, etc.

Chen K, Kurgan L, Ruan J. 2006. Optimization of the Sliding Window Size for Protein Structure Prediction. CIBCB '06: 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, pp.1-7, 28-29, doi:10.1109/CIBCB.2006.330959.


What does 5' and 3' mean in DNA and RNA strands?

The 5' and 3' mean "five prime" and "three prime", which indicate the carbon numbers in the DNA's sugar backbone. The 5' carbon has a phosphate group attached to it and the 3' carbon a hydroxyl (-OH) group. This asymmetry gives a DNA strand a "direction". For example, DNA polymerase works in a 5' -> 3' direction, that is, it adds nucleotides to the 3' end of the molecule (the -OH group is not shown in diagram), thus advancing to that direction (downwards).


When does protein folding begin?

With reference to time you have asked, it can be after the translation has occurred (called Translational protein folding) or while translation is still occuring (called Co-Translational protein folding). Here is the link to an article for basic understanding of co-translational protein folding.

There is a lot of debate on the true time. Experimentalists have amassed extensive evidence over the past four decades that proteins appear to fold during production by the ribosome. Protein structure prediction methods, however, do not incorporate this property of folding (reference).

If you are looking at particularly some organisms it is advised to refer to the research articles related to them.The primary mechanism is the interplay between several non-covalent interactions such as hydrophobic effect and hydrogen bonding in a cooperative manner (they also follow basic rules of thermodynamics) which leads to a marginally stable tertiary structure.

When do secondary and tertiary structures begin forming?

Ofcourse, after Primary structure forms.The alpha helices/beta sheets then fold in a cooperative manner to form a tertiary structure.

One point to note is that, slight variations in these cooperative act causes misfoldingng of proteins which may cause certain diseases.


The smaller the cell the greater its surface-to-volume ratio?

This is a basic property of geometry: for any given shape, area will be generally proportional to the square of the length, and volume will be proportional to its cube. (this isn't true for all shapes by any means; the "generally" refers to the principle that length, area and volume are 1, 2 and 3-dimensional properties respectively, not that all or even most shapes behave this way... although a lot of the shapes that happen to be common in the Universe do. See end of the answer).

For example, if a sphere has a radius of R, its surface will have an area of 4*Pi*R², and its interior will have a volume of 4/3*Pi*R³. This means its surface-to-volume ratio will be 3/R, which is inversely proportional to R, meaning when R increases it will decrease and vice-versa.

Like so:

\begin{array} {|l|l|}
\hline
R~(\sim length) & R^2~(\sim surface~area) & R^3~(\sim volume) &  1/R~(\sim surface~area / volume) \\
\hline
1 &   1 &   1 & 1~(= 1/1) \\
\hline
2 &   4 &   8 & 1/2~(= 4/8)\\
\hline
3 &   9 &  27 & 1/3~(=9/27)\\
\hline
4 &  16 &  64 & 1/4~(=16/64)\\
\hline
5 &  25 & 125 & 1/5~(=25/125) \\
\hline
\end{array}

Put another way, if your shape is growing in 3D then whenever you add a bit of length you'll tend to add much more area (because area is increasing along two directions of length) but you'll be adding even more volume (because volume is increasing along three directions of length), and more volume than area means the area-to-volume ratio becomes smaller.

It helps that cells are convex and can often be approximated as spheres, so the rule absolutely applies to them. It's different with squiggly shapes, or cases where you aren't growing along every axis (for example this principle is true if you increase a cylinder's radius and length, but not if you just increase its length; at that point length, surface area and volume are all increasing along a single dimension and thus all at the same rate; check the equations to see this). You often do find such squiggly, long or thin shapes in nature, and this is often an adaptation to get around the surface-to-volume decrease issue. Examples include your intestines, or the interface between the placenta and the uterus.


Are unilaterally deaf people able to determine where sound comes from?

From what I could gather, there is a decent amount of variability in the ability to detect which direction sound is coming from in unilateral hearing impaired people. It would appear that some people have severely impaired localization skills, akin to someone with an earplug in one ear, but others can use their monaural hearing cues to better locate sound.

Monaural cues seem to be based on the structure of the outer ear as well as how the sound bounces off of the head and shoulders.

http://www.sciencedirect.com/science/article/pii/0378595594900531

http://en.wikipedia.org/wiki/Sound_localization#Monaural_cues


Have scientists ever produce a new species in laboratory by means of natural selection?

There are a few issues your question brings up.  First, the idea that species evolve from simple to complex is actually not a prediction or inevitable consequence of evolution by natural selection.  The terms "simple" and "complex" themselves are ill-defined.  For instance, if you defined "complex" to be size of the genome, the most complex organism found to date is probably a flowering plant from Japan.  This idea of arranging organisms from simple to complex hearkens back to a pre-Darwinian idea of the Great Chain of Being.

You may be thinking that since multicellular life, for example, evolved from single-celled organisms, mutlticellular life is more complex than single celled life.  The fallacy is that modern single celled organisms also evolved from the same single-celled ancestor.  In no evolutionary sense is modern multicellular life more evolved than modern single celled organisms. You can, of course, defined notions of complexity to make multicellular life more complex than single celled life, but such definitions have no evolutionary significance.

We can, of course, say that organisms evolved from earlier organisms.  So the second issue your question brings up is have scientists seen large evolutionary changes in a laboratory setting.  The example you bring up is whether we could observe the evolution of photosynthesis in a lab.

The short answer is no.  We would not expect traits which took millions of years to evolve to evolve in a lab in a shorter amount of time.  In the case of photosynthesis, we may not even have a good idea what selective pressures were involved early in the evolution of cyanobacteria.  Such traits do not usually evolve in their totality in one step.  Instead there are many steps along the way, each of which may be selected for in particular environments for different reasons.  Even if we had millions of years and a very large lab, we may not know of these early selective pressures to successfully recreate the evolution of a particular trait. (There's actually a bit more depth here which I am glossing over. Since the variation in the population is different, the same series of selective pressures won't necessarily yield the same outcome.  When traits evolve through convergent evolution, which is what you are suggesting, they virtually always have different genetic bases and underlying biochemistry.  But a digression into this is probably a distraction from the central point.)

So, you may reasonably ask, if we can not directly observe the evolution of these major traits in a lab, how do we know that they evolved?  There are multiple lines of evidence:

We can see smaller changes occur in shorter periods of time, so it seems likely that the same process creates larger changes in longer periods of time.
For many large traits, we see evidence of common ancestry and the same underlying biology being used for different purposes.
For some traits, we have the evolutionary history of that trait and can identify the sequence of events which brought that trait about (the best evidence generally comes from skeletal traits, where there's preservation).
More speculative evolutionary histories can still be examined through genetic techniques such as molecular clocks, which can indicate when species diverged from a common ancestor.


Are there free electrons in muscles, hair, or skin?

Our body contains a lot of salt and which act as electroyte,so when we comes in contact of electric source then the electrolyte helps in the conduction of electric current through out body,


The mitochondrial genome is highly reduced; many mitochondrial genes have been transferred to the nuclear genome (see endosymbiotic gene transfer) and therefore the mitochondria are fully dependent on the nucleus to function.

Bacteria need not necessarily have a plasmid. Usually, all the important genes are present in the chromosomal DNA. Since the mitochondria have lost most of their genes and retain only a few genes that are highly essential for their function, the likelihood of retention of any plasmid DNA is very low. However, there are some reports of plasmid-like DNA in mitochondria (mostly in plants).

Handa (2008): in Brassica
Robison et al., (2005): in carrots
Collins et al., (1981): in Neurospora (a fungus)

Likewise, chloroplasts also harbour plasmid-like DNA (google-scholar hits).


For mouse gene names and other details you should refer to the mouse genome informatics database (it is a standard organism-specific database like flybase [Drosophila], SGD [yeast], etc).

However, it is much better to work with RefSeq IDs. Moreover, miRNAs are seldom referred to, using their gene names. Always stick to the miRNA naming convention that is described in miRbase.

I am not sure what you are actually interested in. If you intend to map miRNAs to their targets then you can use one of the standard gene names along with the RefSeq ID. If you are using miRanda or TargetScan to predict the targets then these programs return different identifiers for the target gene including its official gene name.

In general, for ID conversion, I would prefer BioMart.


Are these fruit flies really coming back to life after being frozen?

Short answer
Short-term freezing kills fruit flies. Long-term cryo-preservation of D. melanogaster is also not possible.

Background
Per a publication of Koštál et al. (2016), long term preservation of insects is only possible for embryos, or larvae in diapause. Indeed, freezing is an effective way to kill adult fruit flies (source: Phys.org)

However, D. melanogaster adults show very weak capacity to enter reproductive diapause, and larvae possess absolutely no capacity for diapause Koštál et al., 2016).

Reference
Koštál et al., Scientific Reports (2026); 6: 32346


Goodness of fit: How to decide which ratio to deal with?

To solve this question you need to have a basic understanding of Mendelian genetics. Contrary to peoples' comments, this problem does provide enough information.

Genes are inherited from two parents. That is, the offspring will inherit one allele from each parent. Genes also interact with each other in a dominant/recessive nature. A dominant trait will be expressed, no matter what if this is carried by an organism. A recessive trait will only be expressed if the organism is carrying two copies of the same allele - the organism must receive the recessive gene from both parents.

In the first question, there are four genes. One gene encoding large seeds. One gene encoding small seeds. On gene encoding red seeds. One gene encoding white seeds.

The dominant genes are those that code for: large & red
The recessive genes are those that code for: small & white

For this question, you assume that both parents are carrying a single copy of each gene. This means, each parent has one copy of a gene coding for large seeds, one copy of a gene coding for small seeds, one copy of a gene coding for red seeds, and one copy of a gene coding for white seeds.

As a side note, this would mean that each parent came from a large red seed. There is also a chance for any of the four genes to be passed to the offspring.

Each parent could pass the genes for: Large red seeds, Large white seeds, small red seeds or small white seeds.

This means that the following gene-combinations are possible:

-large red, large red

-large red, large white

-large red, small red

-large red, small white

-large white, large red

-large white, large white

...etc...

And, I'm sorry, I've been trying for twenty minutes to upload a picture to show you what I mean. But, you can do this yourself also to see what I mean:

Draw a 4x4 grid, and in each box fill in each possible combination of genes that can be inherited by an offspring. They call this a Punnett square, and it is used to predict the phenotype of an offspring bred by two parents. If you search Punett square you will understand how this works.

But the thing to remember is this: If the offspring carries one copy of a dominate gene (large seed, red seed) then these phenotypes will be expressed. In order for a recessive trait to be expressed, the offspring must carry two copies of the genes (small seed, white seed), ie. it must have received the same recesssive allele from both parents.

Now, to solve the problem statistically, you will use the ratio 9:3:3:1. The null hypothesis is that there is no difference between the observation and this ratio. The alternative hypothesis is that there is a statistically significant difference observed from the sample in comparison to the test-ratio.

This means, a p-value < 0.05 indicates that the 9:3:3:1 ratio is false. And the gene-interaction must be explained by another means - not by Mendelian inheritance. Or, I suppose it could also indicate that the parents did not in fact carry one copy of each allele and some other combination, that maybe you need to find. Eg. One parent could have had two copies of each recessive trait, while the other parent could have had in had one copy of each trait. (Play with the Punnett square, and maybe you can figure out if this is true)


Are there any flowers that look like snakes?

There are quite a few examples of plants which look like snakes. I'll tell about them one at a time.

Darlingtonia californica: or Cobra Lily, is a type of pitcher plant which looks much like a snake. It is native to Northern California and Oregon, growing in bogs and seeps with cold running water. See this image:

Arisaema triphyllum: commonly called Jack-in-the-Pulpit, it is a type of corm which resembles cobra. It is native to eastern North America, occurring in moist woodlands and thickets from Nova Scotia west to Minnesota, and south to southern Florida and Texas. See this:

A similar and closely related plant, Arisaema griffithii, called Griffith's Cobra Lily, resembles even more. See this:

Pogonia ophioglossoides: also called Snakemouth Orchid, whose flowers resemble the face of a snake, pretty much like your image. It is a species of orchid occurring from central Canada to the east-central and eastern United States. See this:

Isotria medeoloides: named Little Five Leaves, its flower also resembles a snake's face. It is a threatened species of terrestrial orchid found in temperate eastern North America. See this:


Terminology question about the correct term for areas of biological research

I think your suggestions are fine - there are a few ways you could write this.

I might use some variant of;

  The techniques used may be specific to the research question, and particular considerations may also be required depending on the accepted norms within the academic field


What kind of bird is this and what does it eat?

Based on the photo, it looks like you have a fledgling American Goldfinch (Spinus tristis). Here's a photo of an adult female feeding a young goldfinch. This link has dietary information.

I would suggest contacting your local Wildlife Rehabilitation Centre or leaving the young guy where he was found. He could of jumped the nest a bit early, but typically the parents are always nearby.


"Cytoplasmic localization" is a very general term and it means that something is present in the cytoplasm. For instance (hypothetical but there are known examples), you can say protein-X is localized to cytoplasm or the cytoplasmic localization of protein-Y is reduced upon phosphorylation. Similarly, there are terms like "nuclear localization", "ER localization", "mitochondrial localization" etc.

The usage mentioned in your excerpt is actually unclear and misleading. There is no process called cytoplasmic localization. What it actually means is that there are proteins/RNA inside the cytoplasm of the embryo that are asymmetrically distributed. When the cell divides, these molecules are therefore asymmetrically sorted to the daughter cells. Depending on what (and how much of) molecules the daughter cells receive, different cells adopt different phenotypes. Also note that the axis of division also plays a role; if lets say the distribution of a given molecule is asymmetric only about the anteroposterior axis and the division happens along that axis then both daughter cells receive the same amount of molecule and both the cells would be similar (w.r.t that molecule). This won't be the case if the division is along left-right axis. See the figure below.

  From: Berika et al., 2014

I am not sure which book you are following but Developmental Biology by Scott F Gilbert is a good book and explains these processes nicely.


Why are men more susceptible to severe COVID-19?

Update -- In the time since this question was asked, two relevant articles have been published, one in Nature Reviews Immunology and one in medRxiv (note: medRxiv is a preprint server and is therefore not peer reiewed).
Scully, E.P., Haverfield, J., Ursin, R.L. et al. Considering how biological sex impacts immune responses and COVID-19 outcomes. Nat Rev Immunol (2020).
Takahashi, T., Wong, P., Ellingson, M., et al. Sex differences in immune responses to SARS-CoV-2 that underlie disease outcomes. medRxiv (2020).
Besides the genetic factors related to viral entry that I've explained below, these papers explain the immunological factors that may determine the higher susceptibility of males to severe SARS-CoV-2 infection, including sex-specific differences in early antiviral response, innate immune repsonse, and adaptive immune response.  Figure 2 of Scully et al. provides a graphic summary.

Genetic factors
SARS-CoV-2 entry into human cells is thought to depend on two human proteins:

ACE2 -- a transmembrane protein important for blood pressure control.1  The viral spike protein binds the enzymatic domain of ACE2, facilitating translocation of the virus into the cell.2
TMPRSS2 -- a serine protease with a transmembrane domain.  The proteolytic activity of this enzyme is thought to play a role in "priming" the viral spike protein.3

So, a place to start would be to ask if there are sex-specific differences in the expression or localization of these proteins.
ACE2
No significant differences in lung ACE2 activity have been found between male and female mice.4  In rats, however, lung ACE2 levels are reduced with aging in both males and females, with significantly higher ACE2 expression in old female rats compared to old males.5 Assuming that rats are a good model for sex-specific human lung protein expression, this observation counters the simple explanation that men are more likely to have severe COVID-19 due to higher ACE2 expression.
A recent preprint 6 presents an interesting hypothesis -- that ACE2 mosaicism due to X inactivation may be protective against SARS-CoV-2 in women.
From the abstract:

The fact that the human ACE2 protein is encoded on the X chromosome means that males who carry rare ACE2 coding variants will express those variants in all ACE2-expressing cells, whereas females will typically express those variants in a mosaic distribution determined by early X-inactivation events.

So, since males are hemizygous for the X-chromosome, males that have an ACE2 variant that binds strongly to the SARS-CoV-2 spike protein will only express that variant in their lungs.  Females have two X-chromosomes, though only one is expressed in any given cell due to X-inactivation.  If a female is heterozygous at the ACE2 locus, with one allele that encodes a protein that strongly binds SARS-CoV-2 spike protein and one allele that encodes a protein that weakly binds SARS-CoV-2 spike protein, mosaic expression of the maternal and paternal alleles may give partial protection from infection.
The authors found that ACE2 is generally intolerant of loss-of-function variants, though many missense variants occur at and near residues predicted to bind SARS-CoV-2.  Such variants were detected at a rate of 3.9 males per 1000 and 8.5 females per 1000.  However, the most popular missense variant, rs41303171, does not lie in a domain of ACE2 that is predicted to interact with SARS-CoV-2.  Additionally, this SNP is only observed in 1.7% of male and 3.1% of female samples, so it is not obvious that this explanation can account for the sex-specific discrepancy in severe COVID-19 at the population level.
TMPRSS2
Currently, evidence suggests that there are no sex-specific differences in TMPRSS2 expression in the lungs of humans or mice.7  Note, however, that only transcript levels have been evaluated in this context, and that TMPRSS2 activity would need to be evaluated to determine that proteolytic action is not different between sexes.

Non-genetic factors
Worldwide, men smoke five times as much as women.8
Smoking is co-morbid with severe COVID-19 9, likely due to decreased lung capacity, though possibly through a mechanism involving increased TMPRSS2 expression.7  From the same TMPRSS2 paper cited above:

regardless of sex, smoking significantly increases the expression of TMPRSS2, which reverts back to never-smoker levels in former smokers

Indeed, one recent study of more than 1,000 COVID-19 patients reported greater than two-fold increased risk for intensive care unit admission and death in smokers as compared with non-smokers.10
There may be cultural factors affecting disease progression, as well.  If men are less likely to wear masks or follow other guidelines to reduce the risk of infection, then infected men may be exposed to a higher infectious dose than women. Initial infectious dose may be positively correlated with viral load 11, and higher viral load is associated with a more severe prognosis for SARS infections.12
It could simply be the case that symptomatic men are less likely to be tested (a "tough it out" mentality), and therefore would be less likely to receive treatment that prevents a mild infection from becoming severe.

Citations

A Novel Angiotensin-Converting Enzyme–Related Carboxypeptidase (ACE2) Converts Angiotensin I to Angiotensin 1-9
SARS coronavirus entry into host cells through a novel clathrin- and caveolae-independent endocytic pathway
Activation of the SARS coronavirus spike protein via sequential proteolytic cleavage at two distinct sites
Sex differences in renal angiotensin converting enzyme 2 (ACE2) activity are 17β-oestradiol-dependent and sex chromosome-independent
Age- and gender-related difference of ACE2 expression in rat lung
ACE 2 Coding Variants: A Potential X-linked Risk Factor for COVID-19 Disease
No evidence that androgen regulation of pulmonary TMPRSS2 explains sex-discordant COVID-19 outcomes
Gender empowerment and female-to-male smoking prevalence ratios
COVID-19 and smoking: A systematic review of the evidence
Clinical Characteristics of Coronavirus Disease 2019 in China
SARS-CoV-2 viral load and the severity of COVID-19
Initial viral load and the outcomes of SARS


Hodgin-Huxley model for a single neuron - continuation

Actually there is a way to determine the initial conditions for this problem.

We assume that the gating variables $r$ and $s$ are at a steady state before the membrane potential jump from$u_0$ to $u'$.

If we look at the first graph(the steady state relation versus membrane potential) we can see that at the membrane potential $u_0$ that $r(t=0)\approx 0$ and $s(t=0)\approx 1$.

Then we make our jump in voltage from$u_0$ to $u'$ and now our $r(t)$ and $s(t)$ will change towards their new steady values $r'=1$ $s'=0$ with time constants given by the second graph.

Your equations $r(t) =C_1 e^{-t}+1$ and $s(t)=0+C_2 e^{-t/15}$ are correct, but using the information from the graphs we can se that $C_1= -1$ and $C_2= 1$.

From these equations we can see that $r(3)=1-e^{-3}\approx .9502$ and $s(3)= e^{\frac{-1}{5}}\approx .81$ (note that .81 is close enough to 1 for this particular problem). This means that the channel is mostly open as statement 4 asserts.

Now for statement 7 we have $t= 100$ and while $r(100)= 1-e^{-100}\approx1$, and $s(100)=e^{\frac{-100}{15}}\approx 0$. This means the product $r(100)^2* s(100)\approx 1^2 * 0 \approx 0$ thus the channel is mostly closed.

Hope this helps.


So the CDC has a list of total leading causes of death

https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm

  Number of deaths for leading causes of death
  • Heart disease: 614,348
  • Cancer: 591,699
  • Chronic lower respiratory diseases: 147,101
  • Accidents (unintentional injuries): 136,053
  • Stroke (cerebrovascular diseases): 133,103
  • Alzheimer's disease: 93,541
  • Diabetes: 76,488
  • Influenza and pneumonia: 55,227
  • Nephritis, nephrotic syndrome, and nephrosis: 48,146
  • Intentional self-harm (suicide): 42,773

Cancers can be further subdivided into types which may or may not be related to lifestyle. There are lung cancers and skin cancers that are not linked to smoking or skin damage respectively. Cancer is very complicated.

Most of the causes on this list have lifestyle or environmental components to them. Influenza and pneumonia have less to do with lifestyle and more to do with the immune system either being too robust or not robust enough but the immune system is influenced by lifestyle as well.

To get a list of diseases that are the leading causes of death and not influenced by lifestyle or environmental, you'd probably be looking at genetic diseases like cystic fibrosis for example.

The WHO has a list of these monogenetic diseases. These are diseases that are caused by a single gene (either one or two copies of the gene depending on the disease) and are independent of lifestyle and environment.

  Thalassaemia
  Sickle cell anemia
  Haemophilia
  Cystic Fibrosis
  Tay sachs disease
  Fragile X syndrome
  Huntington's disease

You can read more about these diseases here: http://www.who.int/genomics/public/geneticdiseases/en/index2.html


Why does a wound itch while it's healing?

While healing your wound the cells in and around it are enhancing their communication via messenger substances to quicken and coordinate the healing process. These messengers irritate the sore nerves which we feel as itching.

Skin tension is another factor to itching.

Scratching is bad for the healing process in any way.


Could a human become infected with rabies in such a way that even prior vaccination wouldn't stop the infection?

Reframing your question as:

  Are rabies exposures at specific sites on the body riskier than other sites, even for a vaccinated individual?

Possibly for post exposure prophylaxis, but probably not for pre exposure vaccination.

Rabies transmitted by a bite or scratch (almost all cases) involves a period of slow replication in muscle tissue at the site of the bite or scratch (see Murray Medical Microbiology Ch. 60 for a general discussion). This is called the incubation phase, and it is highly variable. The incubation phase is followed by a prodrome phase (virus binds receptors of sensory neurons at the site of exposure, and travels to the CNS) and neurological phase (infection of the brain).

An effective immune response is believed to be the result of both an antibody response and cell mediated immunity during the prodrome phase. Post exposure vaccination is effective because the incubation period provides enough time for a naive immune system to mount a protective response (same reference). Regardless, rabies post exposure prophylaxis (PEP) includes both active and passive immunization, i.e., vaccine and human rabies immune globulin.

Both post and pre-exposure prophylaxis failures have been reported. As discussed here cases with pre-exposure vaccination failure involve immunocompromised individuals. Cases with post-exposure prophylaxis tend to involve failure to fully follow guidelines (some are summarized here), but there is a recent case where guidelines were followed. These cases tend to involve bites or scratches to the head and face, which tend to involve a more rapid progression from incubation through prodrome to the neurological phase.

So, since reports of post exposure prophylaxis failure tend to involve specific locations of exposure (head and face), it's reasonable to assume that an exposure there has a higher risk. There is no data supporting this risk for cases with pre-exposure vaccination.


Different level of toxicity between smoke

I am not sure, if any comparisions have been made with other plant leaves, but unless these contain some pharmacologic active substances, I doubt that they are smoked widely.
There are comparisions between normal smoking and the smoking of marijuana and the short version is: Both are harmful. It depends on the temperature at which they are burned, how they where grown and so on. For smoking marijuana it also depends if you mix it with tobacco...
This fact sheet from the University of Washington lists a number of points on marijuana together with proper references.
Then there are some articles about smoking and marijuana in comparision:

A Comparison of Mainstream and Sidestream Marijuana and Tobacco
Cigarette Smoke Produced under Two Machine Smoking Conditions
On the Carcinogenicity of Marijuana Smoke
A possible chemical basis for the higher mutagenicity of marijuana
smoke as compared to tobacco smoke
Is frequent marijuana smoking harmful to health?


Search engine for biological/medical/epidemiological science literature

Yes, this exists. The portal is called "Pubmed" and looks like this:

This portal allows you to search (have a look into the search-Faq) in various ways as well as getting email alerts, download your searches in different formats and so on. It indexes most (but not all) scientific literature for medicine, biosciences and all related topics and is probably the biggest database in this field. And its free.

Another possibility would be Google Scholar, which is focussed on scientific literature and can also be adapted to your personal needs. However, I usually prefer using Pubmed, but sometimes it is useful as well to use Google Scholar.


How to remove duplicate results from BLAST?

BLAST against a non-redundant database (for e.g. nr and UniProt). nr contains all non-redundant sequences collected from different primary databases but nonetheless there is some redundancy. You can also specify (or filter out) the species if you are not interested in all species.

Finally, you can also choose the best hit (post-BLAST, using simple scripts).


The curve you are talking about is JVPJuglar Venous Pressure Curve.
You are talking avoit x-decent after c pulse.
The downward deflections of x decent is produced by the atrium relaxation and the downward movement tricuspid valve.
This causes decrease in atrial pressure.
A new fascinating question could be why x-decent is greater than y-decent.
Good luck.


Why aren't there any transitional animals today?

Every species on the planet is "transitional" - this is because there is no ultimate or final species. Species branch out from one another, sometimes species go extinct, leaving gaps between the extant branches. But it also comes down to how you look at it; if you were comparing blue whales and humans, then chimpanzees (and many other species) would be "transitional", so some "transitional" species are extant, others are extinct. In fact, it is estimated that 1% of species that have ever existed are extant, the remaining 99% are extinct.

It's very hard to say why the "transitional" species of chimpanzees and humans went extinct. There's a lot of (sub-)species that would fall in that bracket, thus to answer that specifically would be too broad and speculative for this site.

Some concepts and key points

Speciation is a gradual process with species forming over time out of one in to two (or more).
Species is a hard concept to pin down because it applies binary/categorical classification to a very much continuous distribution
Evolution is a process of change, and in all likelihood it will be an unceasing process because at least one of the mechanisms will likely be affecting every species in some way. This means that every species is "transitional" because no species represents an end point.


Evolution is not the type of theory that is mainly directed towards technological applications, as opposed to many physical theories. It is a principle to understand living systems, from the simplest to the most complex. So it mainly gives understanding, not 'solutions' to particular problems.

That being said, evolutionary principles can be applied to many 'practical' problems.

For one, all of the technologies that rely on sequence alignment and phylogenetic inference use models of substitution based on evolutionary principles, in which you have hypotheses based on the probability that some evolutionary changes occur (these changes can be at the nucleotide level or at the organismal level), and then you infer which hypotheses are the most plausible given the evolutionary and ecological context of the problem. A 'practical' side of this, for instance, would be to infer the evolutionary trajectory of the COVID-19 epidemic, or the study of the geographic spread of the virus given the sequences of the virus at different locations/time. A lot of modern molecular biology is based on a comparison of sequences.

Another 'application' is that of designing enzymes or other molecules, that have a desired function or feature. In fact, a recent Nobel prize was awarded to Frances Arnold for harnessing the power of evolution in her research on molecular design.

Some other applications besides the ones people have mentioned in the comments above are medical applications. It is well known that cancer lineages evolve, so the principles from evolution can be used to better treat cancer progression, for instance by adjusting the evolutionary outcomes of a particular treatment (you can read a fascinating example here). In fact, the understanding of cancer itself, besides therapeutic interventions, has used evolutionary principles for some years now (see a nice example of evolutionary dynamics in metastases here).

I also want to mention an important example from microbiology. It is a pressing issue of public health the fact that no novel antibiotics have been developed in the last few years, and that the existing ones are less and less effective given to the evolution of antibiotic resistance. What if we could make "evolution-proof" antibiotics? That's a fascinating question that some people are starting to explore, for instance by combining classical antibiotic treatments with phage therapy or molecules different than the traditional antibiotics (a cool paper here).

Finally, I want to mention that these applications of evolutionary principles do not "rely" on evolution being "fundamentally correct". Evolution is a process for which we have a lot of evidence, so at this point (and for a long time) evolution is an uncontroversial fact to the scientific community. This is similar, for instance, to the fact that we have lots of evidence for the phenomenon of gravity; so what scientists are doing at the moment is figuring out the mechanisms by which evolutionary processes occur (just as physicists are looking for gravitons). Another addendum is that evolution seems to be an open-ended process. This means that many of the mechanisms we can find in evolution will be, to a high degree, statistical in nature, because there are just so many possibilities that we cannot account for all possible outcomes. This is a fundamental difference to many theories in, say, physics, where there are clear "solutions" to a problem (in the form of an equation, for instance). I say this because people keep coming up with examples that "disprove" evolution, but they just don't consider that evolution is a statistical process, which allows for "outliers". In fact, the outliers are quite informative for evolutionary theory, not at all undesirable (consider for instance the origins of life, or the emergence of consciousness, these are unique 'events' for which we have no mechanism to explain why did they emerge).


Can we measure the rate of mutation in (say) E. coli without gel electrophoresis or genome sequencing?

This is pretty broad question so I'm not really sure what the end goal is here, but here goes.

The answer is both: "yes" and "it depends what you mean exactly". I'll explain what I mean.

Firstly, you should clarify in your question whether what you actually mean is the substitution rate, or not. The mutation rate, which is how often a given base pair position changes, cannot be observed with any current technique, even Next Generation Sequencing. This is for 2 reasons (that spring to mind, there may be more).

If you make an observation at time $t$, and another at time $t +1$, but a base mutates (say A $\rightarrow$ C) and then mutates back again between your observations, you would not be able to tell that this had ever happened. Thus there would be 2 mutation events which you would not count in your 'rate'. This is one of the reasons molecular clocks based on SNPs tend to underestimate ancestral distances.
If a mutation occurs that is deleterious (has a negative effect on the organism), the mutation won't be observed because the lineage of the organism won't survive to be sampled. By the way, the chances of a mutation being deleterious are considerably higher than it being advantageous, but lower than it being neutral.

The substitution rate is how many mutations have occurred that persist in the lineage. Now if we assume that when you say mutation rate, you mean substitution rate...

Yes, you can study mutation rate without 'molecular techniques'.

Throughout the history of classical genetics we've studied mutation rate without access to these tools.

My favourite example is basically the one I used in this question, where you can study the emergence of antibiotic resistance in bacteria (since you provided the example of E. coli, this is rather apt).

In the papers I linked however, they will almost certainly have used some molecular techniques to validate their answers.

But, if we set that aside for the moment, the very first indication of antibiotic resistance one might observe in the lab is seeing colonies of a bacteria growing on a petri dish in the presence of an antibiotic they are supposedly susceptible to.

Now, if we consider the 'mutation rate' to be the time taken (perhaps counted in the number of generations), for a spontaneous mutation to appear as a phenotype (observed characteristic), you can assess this purely visually without any molecular techniques. If you repeated this experiment however, you would most likely not be able to verify that resistance arose in exactly the same way twice without use of various molecular technqiues.

As a molecular biologist though, I would not really consider this a very good approach/definition of mutation rate, which leads me on to...

'It depends what you mean exactly'

If you were to stick to what is probably the stricter but more widely accepted definition of mutation rate (.i.e substitution rate), you'd need molecular techniques to determine this, as you'd need to know precisely which bases are changing.

Hand-wavy list of pros and cons:

Phenotyping (pros and cons):

Quick
Cheap
Easy
Low resolution
Possibly not reproducible

Genotyping (pros and cons):

Massive resolution
Can be quick in some circumstances
Functional information
Generally expensive
Requires specialist equipment

Not an exhaustive list by any means.


Why don't antibiotics affect mitochondria?

The short answer is, as you found, that mitochondria are wrapped in a double membrane and are thus harder to penetrate with antibiotics.

The long answer is some of them do.  Good antibiotics target structures widely found on and conserved in bacteria that are not found in human bodies.  Some antibiotics are a little less specific and can indeed interact with other molecules.  The allergy to penicillin, for example, is caused by the immune system reacting to a "novel" protein formed when penicillin binds to the surface of red blood cells.  Some antibiotics can indeed harm mitochondria, but we tend not to use those and in fact wouldn't even call most of them antibiotics since we wouldn't use them because of their harmful effects.  Here is a very recent report looking at some of the anti-mitochondrial effects of some antibiotics.  To quote from the abstract:

  We show that clinically relevant doses of bactericidal antibiotics—quinolones, aminoglycosides, and β-lactams—cause mitochondrial dysfunction and ROS [reactive oxygen species] overproduction in mammalian cells. We demonstrate that these bactericidal antibiotic–induced effects lead to oxidative damage to DNA, proteins, and membrane lipids.


Can you approximate Cardiac Output by Ohm's law?

I don't get the first sentence either, since PR and CO in your notation are in fundamentally different units. It's like saying '4 Celsius < 5 meters.' You will have to think about what you are implicitly holding constant and ignoring in that relationship to make it meaningful. I suspect the first sentence is just emphasizing the inverse relationship between CO and PR (PR goes up, CO goes down, etc).

As for Ohm's law, absolutely! You have it written right there. I assume Cardiac output is the flow rate of fluid in a blood vessel, and AP is arterial pressure, and PR is peripheral resistance. Stated another way,

$\textrm{Flow} = \frac{\textrm{Pressure}}{\textrm{Resistance}}$,

which is exactly Ohm's law. Frequently electrical current is described with a Hydraulic analogy, with pressure$\rightarrow$voltage, fluid flow$\rightarrow$current, and flow resistance$\rightarrow$electrical resistance. It makes a lot of sense, since electric current is literally flow of electrons. Poiseuille's Law that makes this analogy rigorous, deriving an Ohmic relationship between those variables. Interestingly enough, Poiseuille derived the law in the context of blood flow, making it particularly applicable.


Does direction relative to origin of replication matter on small plasmids?

I like this question, and I had a similar thought when reading that "Forward or Reverse Strand" post. I've since found a 2005 publication by Mirkin and Mirkin1, which investigates the interaction between the replication fork and transcription machinery in context of an E. coli plasmid.
An excerpt from the abstract:

Studying Escherichia coli plasmids, which carry constitutive or inducible promoters in different orientations relative to the replication origin, we show that the mutual orientation of the two processes determines their mode of interaction. Replication elongation appears not to be affected by transcription proceeding in the codirectional orientation. Head-on transcription, by contrast, leads to severe inhibition of the replication fork progression.

To break this down, replication in E. coli proceeds at approximately 20 times the rate of transcription.2,3 From this, there are two kinds of collisions possible: (1) a "head-on" collision where replication and transcription complexes proceeding in different directions meet, or (2) a "co-directional" collision where the faster replication complex catches up to the slower transcription complex proceeding in the same direction.  Mirkin and Mirkin find that co-directional collisions have little effect on the procession of the DNA polymerase III holoenzyme, whereas head-on collisions
cause replication to stall.

One can clearly see that when transcription from the P7 promoter is codirectional with replication, replication was not affected (Fig.3A). Head-on transcription, in contrast, imposed severe constraints on the replication fork progression (Fig.3B).

Altogether, it is a gem of a paper, and I suggest reading the full discussion to best understand the limitations of their experiments and their caveats in interpreting the results. (e.g. the different rates of procession of DNA Pol I and III, and the frequency of polymerase switching.)

References

Mirkin EV, Mirkin SM. Mechanisms of transcription-replication collisions in bacteria. Mol Cell Biol. 2005 Feb;25(3):888-95.
Gotta SL, Miller OL Jr, French SL. rRNA transcription rate in Escherichia coli. J Bacteriol. 1991 Oct;173(20):6647-9.
Hirose S, Hiraga S, Okazaki T. Initiation site of deoxyribonucleotide polymerization at the replication origin of the Escherichia coli chromosome. Mol Gen Genet. 1983;189(3):422-31.


What is the focus distance of a 3D screen?

There are a number of aspects to the perception of a 3D world. While looking into how cinema and TV 3D systems work recently, I found the following Wikipedia articles useful on how the illusion of a 3D world is generated:

Stereoscopy
Depth perception

The articles on 3D Television, 3D film and Head-mounted displays have some coverage of the issues with 3D display systems, since they do not work the same for all individuals.

Generally 3D display systems ignore convergence and accommodation as a mechanism for generating depth and instead depend on parallax and the brain being able to assemble an approximation of the 3D scene without the information from those cues.

In head-mounted display systems such as the Oculus Rift the image focus is usually at infinity.


https://www.rosaceae.org/species/malus/malus_x_domestica/genome_v1.0

You can see the data in the URL above. The details are described in this article.

As others said, NCBI seems useful.
Go to this site.
Chose chromosome you want to see and click genebank or refsequence corresponding to the chromosome in the table (Assembly Unit: Primary Assembly).
You can see overview of the sequence.
Find FASTA in the page showing the overview and click FASTA. Then the sequence data will be downloaded.


How Does Green Tea Increase Metabolic Rate?

Interesting question! Green tea increases metabolic rate of body because it contains antioxidants known as catechins1. Catechins are actually polyphenol flavonoids, and have been shown by Wang et al and team to affect body composition and decrease body fat in intra-abdominal area. Also, as per Khalesi et al, catechins improve blood pressure, especially when systolic pressure exceeds 130 mmHg, while some studies, such as Ellinger et al, have indicated that catechins may have effect on endothelium-dependent vasodilation which might lead to normal blood flow regulation. Another study, by Weinreb et al, shows that catechins can also reduce the risk of Parkinson's and Alzheimer's. However, their exact mode of action is unknown because of their extensive metabolism during digestion6.

Green tea also contains a little amount of caffeine. Now, as we all know, caffeine is known for its stimulating effects on the body. Caffeine, as stated by Nehlig et al, blocks the formation of adenosine in brain, thus increasing concentration of dopamine and norepinephrine in the brain which, in turn, allow quicker firing of neurons. Along with caffeine, another compound with similar effects is L-theanine, which increases the activity of GABA and leads to anti-anxiety effects, as reported by Nathan et al. Caffeine and L-theanine can together have synergistic effects on the brain and give much more pronounced effects together than individually.

A yet another, and probably less spoken of, effect of green tea, as concluded by Lee et al, is that it can even kill some bacteria and viruses (obviously, killing means preventing growth here) and thus reduces chances of bacterial and viral infections.

Obviously, there might be even more benefits of green tea than I've put here. To the precise point you were asking, we don't yet know how green tea helps in burning calories and fat oxidation. The proposed mechanisms of action are10:

catechins act on catechol-o-methyltransferase (COMT), an enzyme which degrades norepinephrine. Norepinephrine is known for regulating thermogenesis and fat oxidation. Thus inhibition of COMT by catechins may lead to prolonged effects of norepinephrine on fat metabolism.
caffeine can also affect thermogenesis, but by inhibiting phosphodiesterases & thus prolonging effects of cAMP in the cell. As a result, cAMP stimulates hormone - sensitive lipase and promote lipolysis.
catechins and caffeine can also work together and increase thermogenesis in body by 35-43% by increasing fat oxidation.

However, these are just the proposed mechanisms and more detailed studies are required to reach a conclusion.

References:

 1. Beneficial Effects of Green Tea—A Review; Carmen Cabrera, Reyes Artacho, and Rafael Giménez; Journal Of The American College Of Nutrition Vol. 25 , Iss. 2,2006

 2. Wang, H., Wen, Y., Du, Y., Yan, X., Guo, H., Rycroft, J. A., Boon, N., Kovacs, E. M.R. and Mela, D. J. (2010), Effects of Catechin Enriched Green Tea on Body Composition. Obesity, 18: 773–779. doi:10.1038/oby.2009.256

 3. Khalesi, S., Sun, J., Buys, N. et al. Eur J Nutr (2014) Green tea catechins and blood pressure: a systematic review and meta-analysis of randomised controlled trials, 53: 1299. doi:10.1007/s00394-014-0720-1

 4. Epicatechin ingested via cocoa products reduces blood pressure in humans: a nonlinear regression model with a Bayesian approach; Sabine Ellinger, Andreas Reusch, Peter Stehle, and Hans-Peter Helfrich

 5. Neurological mechanisms of green tea polyphenols in Alzheimer's and Parkinson's diseases; Orly Weinreb, Silvia Mandel, Tamar Amit, Moussa B.H. Youdim

 6. "Flavonoids". Linus Pauling Institute Micronutrient Information Center, Oregon State University

 7. Caffeine and the central nervous system: mechanisms of action, biochemical, metabolic and psychostimulant effects.; Nehlig A, Daval JL, Debry G.

 8. Nathan PJ, Lu K, Gray M, Oliver C.. The neuropharmacology of L-theanine (N-ethyl-L-glutamine) a possible neuroprotective and cognitive enhancing agent. J Herb Pharmacother (2006) 6(2):21–30.10.1080/J157v06n02_02

 9. Lee H.J., Lee Y.N., Youn H.N., Lee D.H., Kwak J.H., Seong B.L., Lee J.B., Park S.Y., Choi I.S., Song C.S. Anti-influenza virus activity of green tea by-products in vitro and efficacy against influenza virus infection in chickens. Poult. Sci. 2012;91:66–73. doi: 10.3382/ps.2011-01645.

 10. Jówko E. Green Tea Catechins and Sport Performance. In: Lamprecht M, editor. Antioxidants in Sport Nutrition. Boca Raton (FL): CRC Press/Taylor & Francis; 2015. Chapter 8. Available from: https://www.ncbi.nlm.nih.gov/books/NBK299060/


How is single nucleotide polymorphism denoted?

C228T is a mutation from Citosin to Thymin at the 228th basepair.

Maybe this website helps? Nomenclature for the description of mutations and other sequence variations
I see they write the mutation different (following their format it would be 228C>T), but the general idea is the same.


Why doesn't Manipulated Virus for Cancer Cure Work

This is not an idea I'm trying to make, obviously, I just couldn't get it off my mind and wanted to see what is wrong and if it is fixable.

Since everybody else is giving you a bad attitude in the comments...

While it might work for some cancers, it is completely impractical for the majority of cancers.

SOME cancers do occur because of a specific mutation or specific set of mutations. Some genes predispose people to greater risk for certain cancers. These have a much greater chance of being treatable via viral therapy, but there are still barriers:

The length of coding material (DNA or RNA) a retrovirus can hold and propagate is limited. The mutated gene or stretch of DNA may be much larger than the length a retrovirus could potentially replace.
The retroviral material is not guaranteed to "rewrite" or "overwrite" any bad DNA. Retroviral DNA is inserted fairly randomly into the host genome with little regard for where since it is generally an entire gene meant to be read in its entirety to eventually produce proteins. You'd expect BOTH gene versions to exist simultaneously. This wouldn't end in a cure, but some middleground between cured and affected.
There are tissues where cancers develop that wouldn't be infected. Any sort of brain tumor would remain completely untouched by retroviral therapy, for example.
Targeting specific cancerous tissues while leaving surrounding or other tissues alone is a big problem, even for non-retroviral therapies. Replacing bad genes in a cancerous cell is good, but replacing good genes in a healthy cell could lead to that cell's death or -- ironically -- possibly turn it into a cancerous cell as well.

The majority of cancers are not specific mutations and do not have known genes that predispose their bearers. The majority are an accumulation of mutations across sections of the genome. As MattDMo said in the comments (paraphrased): For these cancers, viral therapy is nearly impossible. Every mutated gene would required its own retrovirus. At that point, the time and financial investments start to rise exponentially.

While I'm not one to say it's impossible (I'm not involved in the research, so if anybody who is can correct me on anything in this post, I'd appreciate it) -- it is certainly very improbable with current knowledge and methods. Every bullet point above (which isn't an exhaustive list) represents a mountain to climb on hands and knees before an "inject-and-forget" end product could be developed.

Kudos for the critical thinking and forming a working theory from the knowledge you had, but unfortunately it does break down with some more specialized information.


How does HIV mutate into other strains while keeping their virulent phenotype?

Others have already touched the important points. Consider this as a summary.

  What gives HIV the ability to mutate?

All organisms mutate by two mechanisms:

Replication errors
Mutagenesis by physical/chemical agents that cause a chemical change
(lesion) on DNA

The main enzyme responsible for HIV replication is reverse transcriptase which makes a DNA copy of its RNA genome. All RNA and DNA polymerases make some amount of error but the error rate of reverse transcriptase is much higher than usual DNA-dependent DNA polymerases because it does not have a proofreading mechanism.

  How does a virus like HIV mutate into so many strains, and yet all of
  them are harmful to our immune system?

As indicated in previous answers, the mutations will produce a virions with a spectrum of infectivity/pathogenicity (some can even be non-infective).
However, the immune system acts as a selective barrier which selects only those mutants that can survive (similar to what happens in evolutionary process of natural selection). The selected strains expand their population and that is how these strains get established.


From the Wiki page for Dengue fever, I believe the text you're referring to is:

  ... those who have previously been infected with other serotypes of dengue virus ("secondary infection") are at an increased risk.

Notice that the text says, "...infected with other serotypes of dengue fever ...". That being said, your focus should be on the effects of reoccurring infections brought about by different forms of dengue fever.

In 2011, the School of Public Health at University of Berekeley published a study that addressed this very situation. According to the article:

  In two clinical studies of dengue in Managua, Nicaragua, we observed an abrupt increase in disease severity across several epidemic seasons of dengue virus serotype 2 (DENV-2) transmission. Waning DENV-1 immunity appeared to increase the risk of severe disease in subsequent DENV-2 infections after a period of cross-protection. The increase in severity coincided with replacement of the Asian/American DENV-2 NI-1 clade with a new virus clade, NI-2B.

And to quote lead author Molly OhAinle, which I believe answers your question:

  With the second infection, the antibodies sort of recognize the new type of viruses, but not well enough to clear them from the system ...  Instead of neutralizing the viruses, the antibodies bind to them in a way that actually helps them invade the immune system’s other cells and spread.

So, given that the immune system represents all behaviors within our body that defend against foreign bodies considered to be a threat, if the immune system itself is helping the virus, then no, there is no other line of defense against  the infection (excluding treatment intervention).

Lastly, here's an image from that publication, showing the seasonal patterns of dengue fever with respect to the various serotypes:

For finer details, you can access (and download) the publication for free; you just need to create an account on this site.


Welcome to Biology.SE Wendy.

Issue in your post

There are a few issues in your post.

You made a personal observation that males tend to more often be diagnosed with a handicap than females (in frequency). You probably did not keep track of the numbers and you probably did not make any statistical analysis. So there is really no reason to trust this observation. The idea that males are more often classified as handicapped than females is opinion-based for the moment and you will need a reference for this before asking why it is true.
You also claim that most birth defects occur in males and not in females. You should also include a reference.
You are talking about gender difference in "handicap frequency" and "birth defect frequency". It is a little unclear what the question (your last sentence Why) refers to. Maybe both. In such case, why would you expect that a common mechanism explains both observations? You should probably restrict your question to one or the other only.

For these above reasons, the question cannot be correctly answered in its above form. But below is something that may already help you.

Birth defects

It is true that birth defects is more prevalent among males than among females (in humans). According to Lary and Paulozzi 2001:

  The overall prevalence of major defects at birth was 3.9% among males and 2.8% among females.

Reading their abstract only, one can see that they go on saying

  Defects of the sex organs were eight and one-half times more prevalent among males and accounted for about half of the increased risk of birth defects among males relative to females. Urinary tract defects were 62% more prevalent among males, and gastrointestinal tract defects were 55% more prevalent among males.

In consequence, it seems at first sight that the difference in birth defects frequency is very much related to the development of sex organs. In their abstract they announce that they discuss the mechanisms that account for such difference.

I currently don't have access to the paper (I am not on campus) to report more details of their findings.