text:
Normal cells and the immune system
Normal or healthy cells have a natural ability to avoid being attacked by the immune system.
 So if a cancer cell has all inherited 'strategies' for avoiding the immune system (that are from their earlier pre-cancerous states) does this make them hard to detect or be affected by the immune system.

In short, the major histocompatibility complex.

This is an important question ; how can I make it less 'broad'?

The development of cancer has various reasons. For example in more than 50% of tumors, p53 is mutated. p53 among other things regulates mitosis and forces the cell to arrest in a specific growth state if other systems detected a mutation in the DNA.
But in your special case we have to look at major histocompatibility complexes (MHCs) and NLRC5. There are two types of MHC, namely MHC class I and class II. MHC II presents mostly bacterial peptides to CD4+ T cells causing a immune response. However, MHC I presents viral peptides and peptides from your own body. These peptides are detected by CD8+ T cells which are cytotoxic T cells initializing apoptosis. Without these own peptides natural killer (NK) cells are activated because of a missing-self signal causing apoptosis, too.

Watson et al. (figure 1, Watson et al., Int.J.Cancer, 2006) showed that patients with high MHC I expression or an absent MHC I expression have a higher survival than patients with low MHC I expression. If patients express high levels of MHC I, the chance that these proteins present cancer peptides is higher than patients expressing low levels of MHC I and therefore cancerous cells get killed by cytotoxic T cells probably more often. Without MHC class I, NK cells will initiate apoptosis and cancerous cells will die, too. Patients with low MHC class I expression won´t present so much peptides to cytotoxic T cells and therefore less cancer peptides are presented. But as they have MHC I, NK cells keep inactive. So the cancer finds an escape mechanism in tricking the immune system.
NLRC5 is the biggest member of the NOD-like receptors (NLRs). Expression of NLRC5 can be enhanced by IFN-gamma which activates the JAK/STAT signaling pathway. STAT 1 enhances the expression of NLRC5 and NLRC5 itself can build an enhanceosome with RFX. This enhanceosome raises the expression of MHC class I! NLRC5 is often mutated for example in colorectal cancer. Research now has to focus on how to enhance NLRC5 and therefore MHC class I expression in different cancer types and out of these results to develop an efficient cancer treatment.
I hope that I could help you. Further literature especially on NLRC5 you can find in following paper.
Kobayashi et al., Nat. Rev. Immunology, 2012
Meissner et al., PNAS, 2010
Neerincx et al. (different paper, just google it ;) )
Staehli et al., J. of Immunology, 2015
Yao et al., Protein&Cell, 2012
Of course there are even more, but I think, these paper show a nice overview about this field.

It would be really perfect, if you could add the links for the references.

Watson et al. link,
Kobayashi et al. link
Meissner et al. link
Staehli et al link
Yao et al. link

NLRC5 is only a small part of the picture. The whole topic of immune surveillance and tumor escape is quite broad in scope (much broader than your answer would have us believe), but it is also too broad for this site, which is why I voted to close this question. Nothing you said is incorrect, but I think it's a bit misleading. Otherwise, every drug company on earth would be targeting NLRC5 and we'd have cured cancer by now. I know your own research can seem like the most important topic on Earth, but you need to have some broader perspective and a more nuanced view of how cancer works.

I never said, that NLRC5 is the only responsible protein for these escape mechanisms. I know, that this topic is much greater, but I don´t know every aspect of it, so I wanted to show at least one aspect. If we want to discuss this question in total, we would have to write a book. So NLRC5 and MHC I are two proteins, which show some insights into this broad field and now 201044 has some indications for research also on other involved molecules, if he is interested.

Great information ; I'm just an amateur researcher or like an 'armchair philosopher' I'm an armchair theoretical biologist.  I just wonder if these 'escape mechanisms' as mentioned can be inherited by any daughter cells of a pre-cancerous cell?

Do cancer cells inherit 'survival' strategies from their 'parent' cells?

Either from the parental cells or by mutation.

Do you mean a cancer cell can get a immune system avoidance strategy from only a mutation and not its parent cell? Can some type of radiation cause a mutation that can give a cancer cell some immune avoidance ability??


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Whales and cancer
Do whales get  less cancer than they should considering they have a lot more cells and tissue? If a lot of cancer formation is random because of mutations then shouldn't whales receive  a lot of cancerous growths? Is it partly because there's a lot more systems that can protect against pre-cancerous development and apoptosis degradation in the larger mammal than in a human being?

Short answer: Yes/Maybe
More detailed answer: If the rate of cancer was uniform across cells then you would expect large mammals to more frequently get cancer than small mammals, just like buying 10 lottery tickets is more likely to make you a winner than buying one ticket. However, this correlation between mass and cancer rates does not exist, and it's absence is called Peto's paradox.
Some useful quotes from that paper:

The incidence of cancer in humans stands at one in three [33%], whereas it is only 18% in beluga whales....
There are a number of different hypotheses,” says Carlo Maley, director of the Center for Evolution and Cancer at the University of California, San Francisco. “For example, rather than body mass influencing the number of tumour suppressors and oncogenes, maybe there are less reactive oxygen species in larger organisms due to their lower metabolic rate....
Some biologists question whether there is a paradox at all, saying
that variations in cancer rates across species — which range between
20% and 46% — are more similar than different. “All species get cancer
at about the same rate, typically in the latter part of life span,”
says James DeGregori, a molecular biologist at the University of
Colorado in Denver. “We simply don’t have the data yet to back up the
notion that larger animals have come up with a way to avoid oncogenic
mutations.”

Do eels get cancer, or other fish that have certain properties that use an electromagnetic field , like the eel?

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Similarity between a heart attack and a spasm
When someone is having a heart attack, could it be considered , in some situations, a spasm? Below, I have written how I believe the process may work.
The heart is basically a muscle working constantly to create a sinus rhythm. As I understand it, one can get muscle spasms in any muscle (correct me if I'm wrong). If so, then couldn't someone get a muscle spasm in a part of the heart muscle that disrupts the sinus rhythm and causes chaotic signals? Thus causing a spasm throughout the muscle.
When one is having a heart attack, does the electric shock used cause a dramatic and fast 'stretching' of the heart muscles allowing the heart to get over the spasm and back to normal rhythm? Could something else, like an ElectroMagnetic Pulse be used to 'stretch' the heart muscles away from the spasms?

Do you think you could elaborate a bit here? Are asking what kind of damage could be done by this happening? From what I understand, a dramatically fast stretching of the heart could do serious damage to it; but I'll have to read a little more.

Doesn't the electric shock used to stop a heart attack cause dramatic fast stretching of the heart muscles? I'm basically asking is a heart attack like a muscle spasm in the heart muscles?

Okay. I understand! I'm going to run a couple edits on your question and you can see what you think of them. You can change anything back that you don't like.

You should be able to find either a review button or some such that will let you see my edits before someone else approves them.

I was able to do some reading and research and I found some interesting information that was a). news to me. And b). the answer is yes... And no.
A spasm can be the cause of a heart attack by causing the coronary artery to contract. When that artery contracts, it causes a dramatic decrease in blood flow to the heart. When the heart looses access to oxygenated blood it can cause chest pain (angina) or even an MI (Myocardial Infarction a.k.a. a heart attack). This spasm is can be caused by exposure to extreme cold, smoking and the use of certain recreational drugs.
However, this type of spasm cannot be stopped with defibrillation. Treatment for these involves administering Nitroglycerin and then later treatment involving Statin drugs and such.
In the terms you are speaking of, I don't see that that would be quite accurate. The most common cause of sudden cardiac death is VF (Ventricular Fibrillation) which is essentially an uncontrollable quivering of the heart muscle. I've never heard this described as a spasm though. Google searches of spasm and heart spasm have all lead to definitions of the word spasm and the coronary artery spasm mentioned above.
However, within that, I think you have a valid point and a decent understanding of how things work, just perhaps not fitting under the definition of a spasm.
When a defibrillator is used, it delivers a measured electrical shock to the person's heart and hopefully stops the chaotic electrical rhythm. I'm not sure if this part is correct however, I do not think you should look at that as a stretching of the muscle though. It is an electrical intervention that interrupts the former rhythm and hopefully the heart "forgets" what it was doing and returns to a sinus rhythm.
So, to summarize: A heart attack can be caused by a spasm; however, defibrillation does not help that type of attack. A defibrillator does not 'stretch' the heart but rather interrupts it's former rhythm. Because an irregular heart beat is not considered a spasm, I find it difficult to believe that any form of EMP would help it; however, I would love to hear that it has!
For more information on Ventricular Fibrillation, CAS (Coronary Artery Spasm) and AED's (Automated External Defibrillator(s)). Please see the following:
MedlinePlus - on V-fib
The Mayo Clinic - on CAS
HeartSine - on AED's
I hope this was helpful for you!
Edits:
In the comments, we had discussed a variety of possible causes and treatments for spasms, as well as what - if any - connection there is between how a spasm in perhaps a leg would be caused as compared to how one in your heart could be caused.
From the reading and research I did, I was fairly inconclusive about the safety or desirability of a device to prevent heart attacks using an EMP device implanted in your brain or on your brain stem.
As far as how similar a spasm in your heart is to a spasm in any other muscle, they are not very similar. As seen here, a muscle spasm in most parts of the body can be caused by numerous things, such as dehydration, poor blood circulation, mineral deficiencies etc. Whereas a heart spasm (know as a CAS) can be caused by alcohol withdrawal, stimulant use, extreme cold... As seen here.

Very useful info. I was wondering , when other muscles like a leg muscle has a spasm how are they treated? Could a 'tiny' defibrillator stop a leg muscle spasm?

Was it Galvani who experimented with a frog's leg and a small charge of electricity? Has anyone tried that experiment with an 'appropriate' electro- magnetic charge?

@201044 I did find somethings that discussed the use of an electrical pulse to control bladder spasms. Medicine.net.

The sinus rhythms (if that's what it's called)  that controls the heart pulses ; does this have 'part's' in the brain that regulate this rhythms. If so could electrical pulses effect these rhythms by effecting the associated parts in the brain. So if on had a heart attack maybe the 'relevant' parts in the brain or the spinal chord could be 'zapped' instead of the heart itself.

@201044 Yes, they are indeed called sinus rhythms. I will do some more reading and see what I find.

@201044 I did some additional reading on this and it looks like it may or may not be helpful but isn't necessarily dangerous either. (Although in someone suffering a heart attack it could be dangerous, the heart rate slows and then the person's blood pressure goes up). Here are two links you may find helpful, Johns Hopkins Anatomy of the Brain and PubMed.gov.

But maybe something similar to a pace maker could detect the precursors to a heart attack and if connected to relevant parts of the brain and / or spinal chord it could 'zap' them with tiny electric stimuli to prevent any subsequent attacks.

@201044 I'm afraid this has gone beyond my scope of understanding. I will tell you that not all heart attacks are caused by an abnormal rhythm; some can be caused by lack of oxygen due to a blockage or some such. Also, I think that part of the reason this has not previously been done is that it is much safer and easier to implant an AICD (Automated Internal Cardioverter Defibrillator) or pacemaker. Both of which can be implanted in an outpatient procedure. I hope to edit my answer later today.

Could an implanted device 'attached' to a part of the spinal chord and/or the brain moniter any known precursors to having a heart attack?

@201044 I think perhaps theoretically that could be done. But I'm just not sure how many people would ever be willing to line up to have the back of their head cut open to have a device implanted that could much more safely be implanted in their chest - near  their collar bone.

They might if the device prevented any precursors to any susceptibility to an attack.

@201044 I know at least two people who wouldn't. Myself and my mother... Just sayin' :)

What causes muscular spasms in any other muscle ,other than the muscles in the heart? Are the causes of a non-heart muscle spasm similar to what might cause a heart muscle spasm?

@201044 There are a variety of reasons, from diet to medications. I will share a link in my official answer with a list of common causes. The common causes of most muscle spasms are not at all the same as those causing a CAS (Coronary Artery Spasm).

What can cause a leg muscle spasm?

@201044 The same things that cause other spasms.

What is that, specifically that causes spasms?

@201044 I understand your question now! I'm just having a hard time finding information on it. I'll get back with you if/when I find something!

@201044 Perhaps that would be a good question to ask as a new question.

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Mendelian genetics - How can we infer the number of genes in play in this scenario?
So this is a practice question I got from school but I kinda lost here. So the question is:

In    Drosophila , four new recessive mutations have been found all
  of    which produce purple    eye colour.
Mutations 1, 2 and 3 are all found to be X-linked whereas mutation
  4 segregates with one of  the autosomes.
Crosses   between females heterozygous for either mutation 1 and
  mutation  2, OR mutation 1 and mutation 3, and wild-type males have
  been performed.
1st cross:    no  wild-type   males were  observed in 7500
  male  progeny.
2nd cross: two    wild-type males were recovered among 1510
  male  progeny.
What is   the minimum and maximum number  of  genes   identified  by  these four mutations    given   the above   data? Explain your reasoning.
How   would   you go  about   determining the actual  number  of  genes?

My best guess is either mutation 1 & 2 OR 1 & 3 must be allelic because we didn't observe any WT on the first cross. If it's not allelic, there should be complementation there and we will observe a WT phenotype.
I'm not sure what "OR" means.
I'm not sure why only 2 WT males were recovered among 1510 male progeny. I think it has something to do with recombination, but can't really find out what the gene configuration is to obtain that result.
And the way to determine the actual number of genes is by performing a complementation test, right?
Really appreciate if someone can help me / give me some hints here. I'm really lost!
Thanks in advance :)

I suppose that 2nd cross imply crossing offspring of both sexes with parents (of both sexes). Even then, I can't think of a scenario that would explain this pattern without some level of epistasis or environmental variance. Did you copie-pasted the exact question that has been asked?


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What is mean by the term "an organism's genotype is its specific combination of alleles for a given gene"?

an organism's genotype is its specific combination of alleles for a given gene

What is meant by this? Is it talking about heterozygous and homozygous (like GG or Gg) or is it talking about the nuclear bases?
Thanks

I'm voting to close this question as off-topic because there is no source given for the fragment quoted.

From wikipedia

An Allele is a variant form of a given gene.

Let's consider a simplified example. There is a gene for eye color and there are different alleles at this gene. The allele for blue eye, the allele for brown eye etc...
In a diploid (see ploidy) individual (humans are diploid), we have two copies of each gene (exception of sex chromosomes). Let's imagine, at a givne gene, there are 3 possible alleles called A, B and C. The possible combinations are
AA
AB
AC
BB
BC
CC

The genotype of an individual for a given gene (I should say locus for the sake of generality) is called the genotype of an individual.

Is it talking about heterozygous and homozygous[?]

The terms "homozygous" or "heterozygous" are adjectives to define whether, in a diploid genotype, the same allele is found on both haplotypes or not. In the above examples, 3 genotypes are homozygous (AA, BB and CC) and 3 genotypes are heterozygous (AB,AC and BC).

[I]s it talking about the nuclear bases?

For two alleles to be different, they must differ in their sequence of nuclear bases of course.

Alleles are different versions of the same gene; they have different nucleotide sequences. Which versions of each gene an organism gets defines its genotype.
Zygosity (heterozygous/homozygous) is a related idea. When creatures have more than one copy of a chromosome (e.g. one from each parent) the alleles of each gene on each chromosome may be the same (homozygous) or different (heterozygous).


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Robertsonian translocation on the same chromosome
is there any big difference between Robert-son-i-an translocation between two 13 chromosomes comparing to a translocation between 13 and 14 chromosomes


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Infer gene frequency within a species over time
I was reading Karlsson et al. (2014) and I came into this:

A selected variant that increases rapidly in frequency in the past ~250,000 years can be detected as an unusual reduction in genetic diversity.

I realised that I do not know how to infer a specific allele frequency over time within a given species.
I tried to googled some keyword but was flooded by other concepts. Could you please direct me to some appropriate documentation/kewords?

Welcome to Biology.SE. By tracing over time, I suppose you mean observing the signature of an allele sweeping to high frequency, are you?

I edited your post to include the link and fix the grammatical mistake (among vs within). You might want to add where the sentence comes from exactly (which page, which paragraph).

There's two parts to your post that I want to address, the first is the quote (because I want to make sure you understand it well), and the second is about general inference methods for estimating the genetic composition of ancestral populations.
The Quote: Selective Sweeps

A selected variant that increases rapidly in frequency in the past
  ~250,000 years can be detected as an unusual reduction in genetic
  diversity.

When an allele is selected for it will spread relatively quickly in the population, relative to the spread of neutral alleles for example. If an allele becomes fixed in the population the diversity in that gene is zero; there is no standing genetic variation in the gene. Selection will often reduce genetic variation but see this post too.
However, selection doesn't just reduce genetic diversity at the selected locus, but at loci near to the gene, those that are linked. The loss of genetic diversity at linked loci occurs by a process called a selective sweep. This is defined (somewhat poorly) in the web version of your linked paper:

Selective sweeps; Reductions in genetic variation caused by positive selection at particular loci.

Basically, a selective sweep occurs when strong selection causes one allele, and the loci it is highly linked to, to spread through a population. Genetic diversity will be lost from the linked loci at a rate determined by the strength of selection and the degree of linkage (where tighter linkage and stronger selection increase the rate of loss). This paper (see section 7 for selective sweeps) provides a good discussion of the factors affecting genetic variation in natural populations, and draws on the example of the Y chromosome:

One or more selective sweeps will have left the Y chromosome
  with little or no variability

Inference of ancestral populations
You could sample DNA of the population at the time you are interested in. However, doing so is very tricky. DNA degrades over time therefore it is important to have an understanding of how DNA degrades over time if you want to infer about the population. (I saw a talk a while back by a researcher, can't remember the name, taking samples from graves. I don't know how correctly I remember this, but much of the DNA they collect is bacteria. Just a tiny fraction of the DNA they got from sampling human bones found in graves that were just a few hundred years old was actually human. Another issue of studying old DNA). It's often difficult to find sources of DNA samples which a) of high enough quality and b) with enough individuals to allow good inference of the ancestral population; a small sample will be prone to sampling bias.*
There is another approach, and its commonly used now. If you are interested in finding more you should be searching for coalescent theory and methods. This infers back, based on current (or relatively more recent) genetic composition of populations and using population genetic theory. It's not really an used as an attempt to estimate the specific allele frequency, rather as an attempt to infer population size, migration rates, and recombination rates. It infers when was the most recent common ancestor (MRCA). This paper reviews coalescent methods for phylogenetic trees and this is an introduction lecture on coalescence. Coalescent theory has many considerations that need to be made; Are some mutations more common than others (see Molecular Clock)? How does selection affect genetic variation (e.g. selective sweeps)? Does linkage vary across the genome? Do rates of mutation, drift, and selection vary across the genome? Are different parts of the genome differently affected by migration?
Both approaches raise serious considerations which are at the forefront of evolutionary genetics right now. Research groups all over the world are developing lab methods, statistical methods, and mathematical models in an attempt to make inference more accurate. Right now the only way, in my opinion, to infer the frequency of specific alleles in ancestral populations is to use ancient DNA methods; coalescent can be used to infer population genetic parameters, but regarding specific alleles it just has so many factors to consider which (right now, but certainly less so in the future) we just don't have a thorough understanding of. In other words, the assumptions that need to be made for coalescence to be able to estimate specific ancestral allele frequencies are rarely going to be satisfied. However, as long as this is properly discussed there is no problem with the method being used, and I am certain that the future is bright for such methods.

*On sampling bias: Imagine you want to work out the frequency of the number two on a six-sided die (we know the true frequency is 0.167). You roll the die four times and the die shows the side with two dots once. You population frequency estimate is 0.25. Your friend rolls the same die 4000 times. They see the two dots 652 times, which is 0.163, much more representative of the true population frequency. The moral of the story, small samples can give misleading estimates of the truth.

Your answer has been very useful as I did not understand the selective sweeps at first, where the linkage explanation makes it clear. The first aim was to understand how to read the history of a gene frequency and @Resonating explained it well.

I was just updating my answer to cover more of the approaches to inference @zakrapovic

There are really two ways to infer past genetics.

Sample the past.

Only really works if you have well-preserved uncontaminated archaeological samples, but works surprisingly well, considering. The accuracy and completeness goes down fairly quickly as you go back in time but thousands of years to hundreds of thousands of years is roughly possible. You won't have many samples so it's hard to say anything about population genetics. Don't do this. It doesn't work very well and it's very hard.

Molecular clocks.

Same-sense mutations that affect nothing accumulate in genes over time as they're passed down. Genes that have a distant common ancestor are more different than genes that are just a generation or two apart. This is essentially how phylogenetics works as a whole, but you can use age differences between nearby genes to detect selection in this way. If gene A is nearly identical in every individual in a population, but gene B has thousands of pretty distinct variations, it's clear gene A does something important and has been powerfully selected for. Don't just count the number of kinds of alleles for gene A, calculate the average relatedness between all the alleles you find. If the relatedness for gene A is much lower than for other genes, gene A is being selected on. This is what the text means by 'reduction in genetic diversity', bringing down the average relatedness.
You can't work out allele frequencies at arbitrary times in the past without a time machine(even ancient sampling, you can't really be sure you're getting an accurate sample of the historical population), but phylogenetics can hint at what happened by detecting the signatures of evolution.

I did not know that we could sample the past and this is awesome. Then same-sens mutation explanation is clear. Many thanks

I would guess, the article the OP is referring talks about genetic signature of selection (such as a selective sweep). Shouldn't this be a third big category? It is also unclear to me what inference on change in allele frequency through time you would like to do by comparing number of fixed difference in a single population.

Your guess is right

@Remi.b Sorry, I think this needs an edit to be a little clearer. Measuring the number of fixed differences in a population isn't particularly robust, especially if the selection happened in the past. Something like 'mean relatedness' between many sampled alleles is much better and also lets you detect selection in subpopulations by looking at the distribution of scores.


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Does anyone know the explanation for branches with different flower colors (see picture)?
As you can see in the below picture, there's a branch with white-colored flowers, while the rest of the tree has pink flowers.

I googled a number of questions but it is a bit complicated to formulate in a search. Plus I have no background in botany or even biology.

I edited your post. Feel free to roll back if you don't like my edits

Many ornamental cherries are grown on a hardier root stock, that is, they are propagated by grafting onto hardy wild cherry saplings. This is because the ornamental variety will not produce offspring that are true to the parents, if they produce offspring at all.

All are grafted plants and mainly on wild cherry (gean) rootstock.  Such trees should be planted with the graft union above ground level.  Seed, rarely produced, will give rise to new hybrids.

This is a picture of an ornamental cherry of the pompom variety:

My guess is that the tree in your picture sent a shoot off the main trunk under the graft site, resulting in a branch of native cherry, which is mostly white and a much simpler flower than the ornamental variety that was grafter onto it. Another possibility is that two different specimens were grafted onto the same stock (but since the white blossoms are very simple - like a wild cherry - I would guess the former occurred.)
This is a picture of a wild cherry (gean):

So you have the grafted ornamental cherry blooming alongside of the rootstock cherry it was grafted to.
The rootstock (although usually wild cherry) can vary, so... can't identify with certainty the rootstock, but can explain what you're seeing.
It's not rare, but it's not usually desirable. Some newer growers are grafting several varietues of cherries onto the same rootstock to intentionally produce a tree with different kinds and colors of flowers. See, for example, this artist's work.
The Hamada Cherries

Wow! That's so intriguing. I suspected it to be a rootstock but I thought maybe there could be some other reason because that was on a small street where I live. Thanks!

There is a bougainvillea variety called 'Surprise', which puts out bracts either white or magenta in color, though I believe all of the actual flowers are white.

So, how does this point answer the question, even without a reference?


text:
Protein Conformation Modeling
I'm interested in learning about computational modeling in biophysics. I have heard some amount about people modeling proteins as a network of ideal springs to examine things like conformation switching. I was thinking it would be cool to try to make a very simple model of a small motif undergoing denaturation at certain temperatures while being stable at others.
Does anyone know of a good reference about protein modeling that would be understandable to someone who is decent with math/physics/programming but is in no way a mathematician/physicist/computer scientist?
Also, if you have a better idea of a simple project for me to practice computational modeling in biophysics (or even just any biology) I would appreciate hearing it.
Thanks

Well I sometimes use PDB files from proteins whose structure has been identified and study them. I use swiss PDB viewer software to do this and its pretty neat! I haven't looked at the biophysical data associated with a PDB file but I'm pretty sure they are there since you wouldn't be able to make the calculations and resolve the protein structure and confirmation without that kind of data. All you need is to download the software, go to Uniprot database and use the accession number of a protein you are interested in, see if its structure is resolved and either download the PDB file or use the accession number to download the file inside the software.


text:
Gloves for Cell Culture?
I always wear gloves when I'm doing cell culture. Moreover, I always spray my gloves with ethanol to disinfect, so that I don't contaminate everything.
However, I recently heard the argument that EtOH could impair the integrity of the glove, making it an unsuitible barrier between your hand and the culture. According to this argument, the best idea is to not wear gloves during cell culture, but instead thoroughly spray your hands with EtOH to ensure decontamination.
I don't believe it, but I'm wondering if anyone else has heard a similar argument and if there is any truth to the claim.

In my opinion wearing gloves during cell culture is a good idea. It works both ways as a protection: For your cells since you are not loosing small danders from your hand and for you since you are not getting media or chemicals used in cell culture on your skin when you are uncautious.
I usually prefer nitrile gloves over latex, since nitrile gloves are ways more stable and pose no risk for allergies (I am not allergic, but minimizing risks is always a good idea). The downside of nitrile is, that they are a bit more expensive (thats the point where you need to argue with some coordinators about what to buy).
I never had problems with desinfectants and gloves, but this is my personal experience and probably not more than an anecdote. I desinfect my gloves, since I touch different things with them, but I usually don't spray everything which comes around with alcohol since this is usually pointless. To be useful, it needs to reach all points of a surface and also needs to stay there for a while. What I make sure is that all the stuff, which goes into the hood is either very clean or packaged sterile anyway.
After my experiences some data, this PDF has quite a lot of information. The list below is taken from the PDF:
Nitrile gloves:

Acetone - fair
Ethanol - excellent
Isobutyl - alcohol excellent
Isopropyl - alcohol excellent
Methanol - fair

Latex gloves:

Acetone - good
Ethanol - excellent
Isobutyl - alcohol poor
Isopropyl - alcohol excellent
Methanol - fair

I second that.. Nitrile gloves are also good against many acids. Only chloroform destroys it. plus, even if alcohol did affect the gloves it wont do it immediately and in any case you wont use the same pair for more than a few days..

Chloroform (and other halogenated solvents as well) also break Latex gloves very fast. So if these are used, different security measures are needed. Or you have to work very clean (which is always good :-) ).

Assuming you use latex or nitrile, you're probably good.  Nitrile does hold up better than latex in many situations, so if you're worried about it, switch to nitrile.  This is a good quick guide to glove materials and their resistance.  For some of the applications we do in our clinic/lab, we use thick >6mm nitrile gloves.
Your needs all really depend on your application.


text:
Phylogenetic tree
I want to find the conventional phylogenetic tree of human, mouse, C elegans and drosophila, without all the other organisms.
Do you know where can I get it?
thanks,
Noga

Are you looking to make one, or find one that someone else already made?  I have a feeling that you wouldn't find one pre-made and that at best you'd have to do some deleting.  You might also expand on what your end goal is, as I have a feeling a graph-kernel diagram might actually show what you want better.

I made some trees based on few enzymes and i want to compare them to the conventional tree.

If you just want to check something, use the whole tree, you have all the information there. Just ignore the species you don't care about.

Every tree is an hypothesis of relationships.

You can go to Wikispecies and find the species page for each organism, e.g. the Mouse page.  On there you can click on the Taxonavigation box Expand button and see the group names for the organism.  Comparing the names for each organism will give the closest common ones, which gives you the tree.
However, for the tree between the mammals and the other two, you might want to have a look at the Tree of Life Web page for Bilateria.  Your three groups fall into Deuterostomia, Arthropoda, and Nematoda; for these you'll find a tree for these three groups.  (Actually two trees, but for your groups they amount to the same thing.)

I would not recommend Wikispecies as a reference for phylogeny: taxonomic system is not identical to (our current understanding of) phylogenetic relationships. I'd not recommend Wikispecies at all, since it is currently occupied by a single moderator.

This isn't a complete answer, but to get things rolling.
I think I see what you want; a comprehensive "correct" tree you can compare your single alignment tree to?
I can think of a couple of responses to this.  Firstly there is no perfect way to make a phylogenetic tree. Aside from all the different distance metrics you could use and algorithms to sort large trees, the data you use can also vary depending on what you want to do.  You can compare some conserved genes for long distance comparisons or highly mutable sequences for close distances, but which are subject to noise.
That being said a tree comparing ribosomal RNA is a phylogenetic standard.  As are trees derived from multiple genes. If you want to see if your genes are unusual you can run a few other genes through the same comparison and see if the trees vary substantially for your gene. Because the animals you compare are so far apart on the tree the relative comparison will be pretty close to the tree you've made.
If you are trying to compare the tree quantitatively to some master tree, that will be a demanding task.

If you accept the nowadays prevailing Ecdysozoa-hypothesis the relationships are as follows:
               ____ Drosophila
              |
        ______|
       |      |____ C. elegans
       |
  -----|       ____ Human
       |      |
       |______|
              |____ Mouse

According to the more traditional views (the Coelomata-hypothesis):
         _______________ C. elegans
        |
    ----|     __________ Drosophila
        |    |
        |____|       ____ Human
             |      |
             |______|
                    |____ Mouse

(Note that these trees have the same unrooted topologies)


text:
How does the brain know where a signal came from? What is the addressing system
I am an electronic engineer so I am thinking about this from an electronics outlook.
How does the addressing system work, As I see it, the nervous system is small parallel branches attached to larger "serial" lines (spinal cord).
The serial line is then attached to the brain, but how does it then figure out where the message came from and then get the message back to the place it came from.
If I were to build a robot I would have an addressing system with each message and maybe some kind of error checking to make sure the messages don't become corrupted, but as it's not an electronic system I don't see how the brain could possibly do this. unless it is a fully parallel system and there is a single wire going from every sensor back to the CPU..

The brain knows where a sensory signal came from by what neuron is doing the signalling.  The incoming neuron is dedicated to signals from one source and, since it is not shared by other sources, does not need to have an encoding as to what the source was. When your toe touches something, the sensation causes a pulse which, amazingly, travels along a single nerve cell (neuron) up to the brain stem.  That neuron has its nucleus at a dorsal root ganglion located by the spinal cord, and has a fiber (axon) that extends to the source (toe) and another extending up to the brain stem.  This pathway is called the PCML pathway and the Wikipedia article has some readable details.  This page has a schematic and tabular summary, while this site has a good descriptive overview.
If a robot were built along the same sort of design, to determine what was happening at 1000 places in its body, it would have 1000 wires running to its central computer.  You probably wouldn't choose to use such a design, but then you probably wouldn't be designing a robot that has to build itself from raw materials.

That is exactly the answer I was looking for, thank you so much. So it is literally a fully parallel system. So extending what I said below, does every sensation reach the brain or are some so, meaningless that they don't need much processing. E.g. Hair, stuff like that. Beacuase if so does that mean there's millions of axons and neurons

If you perceive a sensation, it had a path; the signaling is indeed massively parallel.  Some sensations are processed in the periphery and a derived signal sent on to the brain; The density also varies (the hands have many nerves, the back, few). There is also peripheral processing like the knee reflex.  Also there are nerves that have little or no flow to the brain; see autonomic nervous system.  If this answer is what you wanted, you can accept it by clicking the checkmark to the left.

Is it precisely 1-to-1? The number of somatosensory neurons < axons in spinal cord to brain? I don't think this is absolutely true, but not sure. For example on your back, you have a very coarse sensation, but there's no missing area of sensation. To save bandwidth, it is plausible that there were some converging signals in the spinal cord level.

Isn't this simply a circular reasoning? The essential question must be: How does the brain know 'which neuron is doing the signalling'? The answer must be of meta-sensation, something like self-recognition. Though I think no one in the world can really answer it..

your question is a little bit difficult to answer in the current forum format, however I'd suggest you reading about Reflex arc  - from this you can understand consequence of the events in simple reflex on the level of spinal cord (i.e. monosinaptic pathway) and very complex reflexes managed by multiple neural cells (neurons).
A classic example of the reflex -

If you want to dive into the very complex explanations you should read some textbook and probably not forums.
Probably, you'd like to know what the potential of action is....

Thanks for the answer but as I see it these are all just connections and how the conduction works, but somehow the tip of my little toe can send a variety of messages to the brain and it knows exactly which toe and which sensation, there must be some kind of addressing. Biology is so complex

I have just noticed this similar post http://biology.stackexchange.com/questions/550/how-does-a-brain-distinguish-stimuli where the top comment says the way the brain distinguishes is largely unknown.

the messages come from specific receptors and along any pathway there are interconnections for different regions. Your question is complex, so we cannot answer before you'll be more specific...

Well okay a specific sensation, is the brain processing the movement of hairs and does it know the location of every single hair. Well obviously it does because if you touch it lightly I know exactly where I was touched.. Or do you mean something else by specifics?

considering hairs you're a little bit wrong - the brain join skin regions in quadrants and each quadrant has about 1cm sides, thus you cannot differentiate 2 touches inside the same quadrant


text:
Does the size or mass of a body affect the time it takes for rigor mortis to sets in?
Does the size or mass of a body affect the time it takes for rigor mortis to sets in? For example: compare a 300 pound man to 100 pound girl to 5 pound animal.

My work with mice suggests it can happen in less than 10 minutes, but I haven't had to euthanize any other types of animals.

One of the main factors that impacts rigor mortis is temperature. Basically, a smaller body would slow down the metabolic processes behind rigor more substantially. Also, one of the first things that happens in rigor is the stiffening of muscles. An increase in muscle mass would increase the time for rigor as well.
Refer to these links: wikipedia and another that talks about rigor mortis within the scope of forensic pathology.
Hope that helps!
n.i.

I think that a larger body mass with a corresponding smaller surface area to volume ratio would decrease the time for rigor mortis to set it since the body stays warmer for longer.

Yes I saw that but previously you said that a larger body mass increases the time for rigor mortis to set in.

@canadianer - thanks for catching that! I edited my answer.


text:
What Causes the White Layer on These Leaves?
I recently noticed that a Malabar Java plum (Jamun) tree in our garden has most of its leaves covered in a strange white layer, like in the picture I've attached.

I'm curious to understand why this is occurring and whether it could potentially lead to allergies such as allergic rhinitis. What's causing this, and what can be done about it? Any help understanding this would be great. Thanks!

Please read about powdery mildew to see if that fits what's going on with your plum. Without handling the leaf, I can't be sure, but it's the most common cause of white, grey or brown spots on plants.

You also have scale insects on there (along the mid-rib are the most obvious adults, but lots of life stages all over in patches) - these are sucking insects, often covered in white waxy or powdery substance.

@bob1 - Wow, I need new glasses; I completely missed that. Scale insects also exude a sweet substance that promotes fungal growth, but I think the primary problem there is scale.

@anongoodnurse Yep, scale looks like the problem - you can even see where a couple of adults have come off mid-leaf, leaving the rings behind. Feel free to write it up.

Thanks, but I missed it, you caught it. :)

The major problem your plant has here is a very heavy scale insect (Coccomorpha) infestation. These are sucking insects that bite into the veins of plants and suck the sap. They are related to aphids, and feed in a similar manner. The females attach themselves to the plant and are covered by a shield and/or a waxy layer for protection from the environment and from predators. Like aphids, when feeding they exude some sap residue from their gut and this can result in growth of fungal species on the plant. The fungal species are often black sooty molds, but I would hazard a guess that not always.
You can see adults clustered along the main mid-rib of the leaf and smaller instars clustered along the lines of leaf veins. The adults look like ovals with a darker line running down the middle. The instars are particularly obvious about mid-leaf, near the two ovals outlined in white, where you can see 3 approximately regularly spaced veins with lines of them feeding. The two ovals outlined are where adults have fallen off and left behind some of the waxy coating they coat themselves with.
I don't know which of the many many species of scale insect within the grouping you have here, but one common and well known grouping within the scale insects is the mealybug (not what you have here, mealybugs are all unarmoured, yours is armoured). You should be able to treat your plant with a product that is designed to kill mealybugs. These products usually contain an oil delivery system to counteract the waxy water repellent layer the scale insects coat themselves in, and an insecticide to kill the insects.
The white residue you are seeing on you plant is probably not mold and is the waxy substance you can see on the insects. I can't find any reports in the scientific literature of allergy to scale insects, so these are unlikely to be causing a problem. Molds from the secreted sap might cause a problem as fungi from many types are known to cause allergies.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Species Identification : Worm like insect but broad at back
Can anyone help me identify this insect
Location: Southern India
Size: About 2cm
It looks like a worm but has a broad back, it seems like (not very sure) it tucks it's thin head inside the broad shell like body to ward off.
Here is the picture,

Please always include your location and the approximate size of your specimen

Related: Identifying a creature that appears to be a worm wrapped in a cocoon, What is this black and white worm in a white case?,  Help in identifying an unknown arthropod, What insect is this? (India), Identify this smooth-cocoon worm from Southern India, Small worm living in some kind of cocoon......

Related:  What is this animal that hides in dustlike structure?, What in the world is this critter?, What is this hard shelled insect in my house?, What is this insect found commonly in coastal India?, Insect identification - pantry moth vs clothes moth

That actually looks like some sort of caddisfly larvae in its case to me.

Are you sure that's it's 'body' & not a case?
Did you find it in water?
Or a Case Bearing Clothes Moth (Caddisfly are closely related to moths).
This one (a clothes moth larvae) looks very similar to your image.

This is not a caddisfly. Caddisflies are only found in water. Also note the bulging shape of the case -- such non-hydrodynamic shape would be quite challenging for the caddisfly to stay in place. The OP's specimen does in fact look like a case-bearing moth
(similar to the many linked posts I added in the comments above). In the future, please make sure that images and sources you use are reputable. Alamy stock photos are VERY often mislabeled and wrong, so using them as a form of evidence should be avoided or at least corroborated by better info. Also note that your link does not work.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Expected time for a neutral allele to reach a frequency of $p_1$ when starting at frequency $p_0$
Kimura and Ohta (1968) showed that the expected time for a neutral allele to reach fixation (given that it will reach fixation) is
$$\bar t(p_0)=-4N\left(\frac{1-p_0}{p_0}\right)\ln(1-p_0),$$
where $p_0$ is the initial frequency and $N$ is the population size.
From their work, can we generalize this result to calculate the expected time to reach a frequency of $p_1$ (given that this frequency will be reached at some point), where $p_1$ is not necessarily equal to $1$?

In the above paper, a key quantity is u(p,t), the prob. that an allele fixes at time t given starting freq. p. They cite a previous paper showing that u(p,t) satisfies a certain PDE. In your case, you want to modify u(p,t) to be a sort of first-passage-time probability (i.e. the prob. that the allele freq. reaches p1 for the 1st time at time t given initial freq. p). In this case, u(p,t) may no longer satisfy the same PDE as before (check that other paper). In order to proceed, you need to find the PDE that your new u(p,t) satisfies. Look up first passage time problems, it may help.

Plain English Answer:
I have written a computer function which simulates neutral evolution to solve this problem. It's not an exact mathematical answer, but it is basically the same approach as Kimura and Ohta took in (the second half of) their paper, except that my computer is more powerful than their one, so I could get far more precise estimates by simulating more populations than they did.
Figure One is a lattice plot of the relationship between P0 and the expected time to reach P1, for different values of P1 (by column) and different population sizes (by row). It is clear that the same relationships between P0, P1 and expected time to get from P0 to P1 are seen in every population size, but with larger populations, you should expect a longer time to get from P0 to P1.
When P0 and P1 are close together, you generally expect a smaller time to get from P0 to P1 than when P0 and P1 are far apart. You might think of this as a rule like 'it takes a longer time to travel further'. Expected time taken to get from P0 to P1 is smaller when P0 and P1 are on the same side of 0.5 as each other and P1 is further from 0.5 than P0 is, than when P0 is further from 0.5 than P1 is. You might think of this as a rule like 'it is quicker to travel when you're closer to fixation or extinction, than when you're in the middle frequencies'.

Figure One: Expected time for a neutral allele to go from frequency P0 to frequency P1, given differences in P0, sub-plotted by P1 and population size. Modelled frequencies of P0 and P1 are 0.1, 0.3, 0.5, 0.7, and 0.9. Modelled population sizes are N = 10, N = 50, and N = 100. Each sub-plot represents one combination of P1 and population size, with P1 increasing from left to right, and population size increasing from bottom to top. All expectations are estimated from 10,000 simulated populations.
Some populations take longer than others to go from P0 to P1. Generally, most populations take a small number of generations to reach P1, and a smaller number take a long time – but a very few can take a very very long time.
I've attached my code, so if you know how to use R you can use it to estimate the expected time to get from P0 to P1 for any combination of P0, P1, and population size.
Additional details and assumptions for the technically inclined:
Relevant theory:
In a diploid, sexually-reproducing population of size $N$, there are $2N$ copies of a given locus. Each locus is occupied by some allele. All variation at our locus of interest is selectively neutral. For our purposes, we can consider that each locus is occupied either by our allele of interest ($A$), or another variant ($a$), ignoring variation in the 'other' alleles. The number of copies of $A$ in the population at the start of the process, $A | t=0$, is given by  $2N*P0$.
Let us assume that population size is constant ($Nt+1 = Nt$ for all $t$), and that mating is random. Let us further assume that generations are distinct. Let $t = 1$ be the first generation born, and so on.
The expected number of copies of $A$ at time $t+1$ then follows a binomial distribution:
$At+1$ is distributed $Binom(2N, At/(2N))$
Since we have a transition rule for $At → At+1$, it is a fairly simple matter to simulate populations undergoing this form of evolution. I have written the R function neutralFPT to carry out this simulation and estimate the proportion of all populations which reach $P1$ at some point in their history, the expected time for a neutral allele to reach $P1$ from $P0$, given that it will reach $P1$, and the distribution of lengths of time taken to reach $P1$, given that a population will reach $P1$. The script is given in the final section of this answer.
Probability densities of first-passage times:
Probability densities of first-passage times over plausible values of $P0$, $P1$, and $N$ follow a similar structure – unimodal near the left margin, with a long right-tail of longer first-passage times (Figure 2).

Figure 2: probabiltiy-densities of first-passage times from P0 to P1 under different values of P0, P1, and N. A: P0 = 0.5, P1 = 0.9, N = 50; B: P0 = 0.9, P1 = 0.5, N = 50; C: P0 = 0.5, P1 = 0.9, N = 500.
Function: neutralFPT, with examples of use.
 ## this function simulates the number of generations taken for a
 # neutral allele to go from a starting proportion, P0, to a final
 # proportion, P1, in a random population, given that it will at some
 # point reach P1. Allele frequencies are not modelled after the point
 # when P1 is reached.
## neutralFPT was generated in response to Stack Exchange user Remi.b, at
 # http://biology.stackexchange.com/questions/30812/expected-time-for-a-neutral-allele-to-reach-a-frequency-of-p-1-when-starting-a
## neutralFPT was written by Shane Baylis, 2015
 # for R version 3.2.2

neutralFPT <- function(P0, P1, N, niter) {

tOut <- c(rep(NaN, niter))
 # create a vector of blank t-values
statOut <- c(rep(NaN, niter))
 # create a vector of population status values (reached P1, or didn't)

if(P0 == P1) stop("P0 and P1 are set to the same value!")
if(P0 == 0 | P0 == 1) stop("P0 is set to zero or one, so its frequency
                           cannot change!")
if(P0 < 0 | P0 > 1) stop("P0 must be between zero and one")
if(P1 < 0 | P1 > 1) stop("P1 must be between zero and one")
## work out whether you're heading upwards or downwards
if(P1 > P0) { # i.e., our target is above us
    for (i in 1:niter) {
        NAllele <- round(2*(P0*N))
        Target <- round(2*(P1*N))
        t <- 0
        while (NAllele < Target && NAllele != 0 && NAllele != 2*N) {
            t <- t+1
            NAllele <- rbinom(1, 2*N, (NAllele/(2*N)))
        }
        if(NAllele >= Target) {
            statOut[i] <- 1 ## 1 indicates that P1 occurred
            tOut[i] <- t
        }else{
            statOut[i] <- 0
            tOut[i] <- Inf
        }
    }
}else{ ## i.e., our target is below us
    for (i in 1:niter) {
       NAllele <- round(2*(P0*N))
       Target <- round(2*(P1*N))
       t <- 0
       while (NAllele > Target && NAllele != 0 && NAllele != 2*N) {
           t <- t+1
           NAllele <- rbinom(1, 2*N, (NAllele/(2*N)))
       }
       if(NAllele <= Target) {
           statOut[i] <- 1 ## 1 indicates that P1 occurred
           tOut[i] <- t
       }else{
           statOut[i] <- 0
           tOut[i] <- Inf
       }
   }
}
successes <- sum(statOut) # the number of populations in which
                          # P1 was reached
propSuccesses <- successes / niter # the proportion of populations
                                   # in which P1 was reached
successTimes <- subset(tOut, statOut == 1)
expectedFPT <- mean(successTimes)
medianFPT <- median(successTimes)
outs <- list(successes=successes, propSuccesses=propSuccesses,
             successTimes=successTimes,expectedFPT=expectedFPT,
             medianFPT=medianFPT, trials=niter)
return(outs)
} # function close

## neutralFPT examples #################################################

sim <- neutralFPT(0.5, 0.9, 500, 10000)
sim$expectedFPT # Numeric. shows the expected (i.e., mean) first-passage
                # time from P0 to P1, in generations, given that a
                # population reached P1.
sim$medianFPT # Integer. Shows the median first-passage time from P0 to P1,
              # in generations, given that a population reached P1.
sim$propSuccesses # Integer. The proportion of simulated populations which
                  # reached P1. Other populations reached fixation
                  # or extinction of A without reaching P1.
sim$successTimes # Vector. The number of generations taken to reach P1,
                 # for all populations which reached P1.
hist(sim$successTimes, xlab="First passage time (generations)",
     main=paste(sim$successes, "successes from", sim$trials,
         "populations"))  ## histogram of first-passage times

PZero <- c(rep(c(0.1, 0.3, 0.5, 0.7, 0.9), 15))
POne <- c(rep(c(rep(0.1,5),rep(0.3,5),rep(0.5,5),rep(0.7,5),rep(0.9,5)),3))
PopSize <- c(rep(10,25),rep(50,25),rep(100,25))
FPTs <- c(rep(NaN, length(starts)))
testFrame <- data.frame(PZero, POne, PopSize, FPTs)
testFrame <- subset(testFrame, starts != ends)
for(s in 1:nrow(testFrame)) {
    sim <- with(testFrame, neutralFPT(PZero[s],POne[s],PopSize[s],10000))
    testFrame$FPTs[s] <- sim$expectedFPT
}  ## estimates expected first passage times from P0 to P1 for a variety
    # of values of P0, P1, and population size. Outputs the estimates to
    # a table called testFrame.

require(lattice)
with(testFrame, dotplot(FPTs~PZero|POne*PopSize,
   main="Expected First-Passage Time by P0, P1, and Population Size",
   xlab="starting frequency (P0)")) ## generates the lattice plot used as
                                     # Figure One.


text:
Simplest Biological Organism?
What is the simplest biological organism from which a DNA sample has been or could be obtained?  Could the resulting DNA be processed and examined in such a way that the resulting information would give biologists a rudimentary understanding of life's minimal requirements?

I think scientists already have an good understanding of "life's minimal requirements". What you need to do is define life for yourself.

You should also look at Synthetic biology and Mycoplasma laboratorium, which deals with minimum requirements of life.

Could not fit in a comment...
This post (and the excellent answer from Richard Smith-Unna) lists the species that have the smallest genome that we are aware of in different clades.
Yes we can/could sequence these tiny genomes and try to understand what each sequence does. I think that to understand the minimum requirements for life you will mostly be interested in theoretical cytology and synthetic biology than in sequencing simple genomes.
Note that the basic requirement really depends on how you define life. Is a virus alive although it has no metabolism? Would a self-replicating RNA be a living thing? Because we were able to artificially synthesize self-replicating RNA. While the subject is interesting, the main issue is a purely philosophical one: How do you define life?

Consider prions...

Yes, prions is another example of limit case


text:
How do butterflies defend themselves from other creatures when they don't have the ability to sting or some other offensive/defensive mechanism?
How do butterflies defend themselves from other creatures when they don't have the ability to sting or some other offensive/defensive mechanism?

Butterflies are part of the class of Insects in the order Lepidoptera. Adult butterflies have large, often brightly coloured wings, and conspicuous, fluttering flight.

Hi there, I downvoted your question because its important to include an attempt at an answer in your question. Hopefully @fileunderwater gave you the answer you were looking for :)

It might come across harsh @ShyamRadhakrishnan especially as a new user, but you'll get used to it and eventually understand why!

Butterflies have a number of defence mechanisms, even if they don't have the ability to sting (as adults - see spines in larvae below). Here is a non-comprehensive list of some defensive mechanisms:

Toxins or repellents, which can be present in both adults and larvae.
Aposematism (warning coloration)
Mimicry, both in the form of resembling other poisonous species and using features such as eyespots.
Spines, bristles or long hairs, often in larvae (see google images), to make ingestion highly unpleasent or dangerous. See the Pine processionary moth (Thaumetopoea pityocampa) for an nice example of defensive larval hairs.
Camouflage/hiding
Sound clicks used to startle or disorient predators. This is most often known from moths to prevent bat attacks (see e.g. Cycnia tenera and Fullard et al, 1994).
Conspicuous features at the edge of wings to make them targets of attack, e.g. eyespots or appendages, which are used to lure predators to attack non-essential body parts (see Olofsson et al, 2013 for an example).

Nice answer! I removed my comment from the question as this says it all. +1


text:
Distance to source populations and/or environmental gradients?
How do you disentangle the effects of distance to source populations and environmental gradients when the environmental gradient occurs in the same direction as the source population?

For example, if I have a regression model with species richness as the independent variable and distance to source population and pH as significant dependent variables, how do I know which is the driving factor?

Welcome to Biology.SE. Where does the figure come from? The article who made this figure might help you to answer your question. What have you found so far?

The effects of distance to source populations and environmental gradients on WHAT? Species Richness? Pairwise $F_{ST}$?

pH? Are you referring to scale to measure acidity and basicity? Is this just one example of possible environmental variable that you are giving?

I made the figure in powerpoint to ask the question. lol

This question would be just as suitable (if not more) at SE-CrossValidated

First of all, species richness is most likely the dependent variable (the one you want to explain), while distance to the source pool and pH are the independent variables (the ones you assume to have an effect on species richness).
The problem you are describing is termed multicollinearity and a common problem in regression analyses. The good news is that it does not affect the prediction of your model as a whole. The bad news is that the estimates for you individual predictors become increasingly erratic the higher their correlation is. You can estimate the severeness of multicollinearity in your model with the Variance inflation factor (VIF). Wikipedia explains nicely how to interpret the VIF:

The square root of the variance inflation factor tells you how much larger the standard error is, compared with what it would be if that variable were uncorrelated with the other predictor variables in the model.
Example
If the variance inflation factor of a predictor variable were 5.27 (√5.27 = 2.3) this means that the standard error for the coefficient of that predictor variable is 2.3 times as large as it would be if that predictor variable were uncorrelated with the other predictor variables.

You should calculate the VIF for your model. Many sources state that a VIF < 10 is still acceptable, but since there is no rule of thumb, I suggest to do some further reading on the topic if you get some critical value (just google "dealing with collinearity" and you'll find tons of material).

Thanks for the response. My VIFs for all the variables are less than 2.  So thats good. Regression between my distance to source and pH returns a r2 of .2. And the distance contributes ~.18 to the variance of richness. I'm just worried that explanatory power of distance is actually just pH. meh. EDIT: richness is dependent, space and environment are independent. ha.

Could some type of null model work here?

To partition the R² you can start out with a single-predictor model and add predictors while keeping track of the increment in R². However, since your predictors are not completely uncorrelated, the partial R² will differ depending on the order of variable entrance. Another way to compare effect sizes would be to standardize each variable (i.e. compute z-values) and look at the estimated coefficients.


text:
Structure of an Ecosystem

Changes in WHICH of the following factors will result in a change of an ecosystem's structure and composition?

A: nutrient availability
B: temperature
C: number of trees
D: light intensity

I got this question from an online "fun" quiz.
I understand that nutrient availability would affect the carrying capacity of an ecosystem. Temperature, if there was a big shift, could cause a change because some organisms would thrive and others would not. Light intensity affects the autotroph population.
But why would the number of trees not change it? I would think that if the number of trees changes, then the structure of the ecosystem would also have changed.

Yeah, I thought about it some more. The number of trees is not a factor, it IS part of the structure that might change if one or more factors is changed.

Well IMO, that's a bad question coming from your online quizz! As you said, C is not so much a causal agent than a change in itself. All the other agents are likely to affect the ecosystem by its structure and composition (whatever the definitions of structure and composition in this context).

Structure of an ecosystem deals mainly with species decomposition (Ref: On the Origin of Ecological Structure: https://web.stanford.edu/~fukamit/stokstad-2009.pdf). But I remember from one of old lectures, that species structure includes vertical stratification also (have no reference for it).

Maybe the assumption is that if you remove some trees they will just grow back to whatever they were before due to factors like nutrient availability and temperature that dictate the ecosystem's composition, but that is ignoring that trees do have causal influence on ecosystem structure in addition to being part of it. Depending on the environment the trees may be part of a positive feedback loop that maintains certain conditions, and once you get rid of them those conditions will change.

I'd vote for E: all of the above.


text:
What is considered incorrect for a cladogram's time axis?
I am looking for help (and possibly references) regarding the correct mapping of time in a cladogram. As far as I know, it is considered incorrect to draw a time axis diagonally in a cladogram as shown below:

This setting would lead to conclusions like: Species B and ancestor b lived at the same time, because they would both fall upon the same place on the time axis. But we know this is incorrect. Or is this an acceptable positioning for a time axis?
The image below correctly represents the time axis, if I'm not wrong, using a vertical axis.

This positioning makes it clear that species B and b are not living at the same time. In this case, species B is alive and b is an extinct ancestor.

I think it really depends what you're trying to show. The folks in our lab that do these sort of diagrams make scaled cladograms for time (calculated by rates of mutation).

@James does your comment imply that the first diagram could make sense in some circumstance? Following, the OP's description I don't understand how the first diagram could make any sense.

Why did the question receive two close votes?

@James I am sorry, but I don't really understand your comment. I don't think it makes any difference what one is trying to show with the cladogram. A correct time axis shouldn't depend on the information being presented. The branch lenghts would matter in a phylogram, but that's not the case here.

@Remi.b I voted to close because OP introduced a cladogram I have never seen before that is wrong and tells us why it's wrong. My comment was trying to explain that even the figure 2 axis has problems. For example is  A as genetically distinct from a as D is from a, or is it just reflecting time passed? I'm not entirely sure what the question is... Figure 2 is better than Figure 1, but it's still arguably incorrect depending on what you want to show.

@James The quantitative diagrams made in your lab are certainly more precise and more useful to evolutionary biologists. But qualitative ones such as the OP seems interested in are very useful in the classroom and are commonly found in textbooks. In this capacity they generally refer to higher groupings than species. Example, in reference to OPs diagram: A = bryophytes, B = ferns, C = gymnosperms, D = angiosperms.

In your first example, each species becomes "frozen in time" once it evolves implying there is no further change. A slightly more complex cladogram will help.

Imagine the species A ancestor, after branching off the remote ancestor, serves as the ancestor to species E. You need to draw that line in some direction other than along A. Most popularily, that line would extend upward to the right. With the temporal axis as you first show, how did species E even evolve since A is frozen in time? Furthermore, the advantage of a vertical time axis allows us to see that species E appeared after species B and a bit before species C (horizontal dashed line).

Thanks for your answer. That's precisely my line of thought as to why the first setting is wrong. I guess the person I'm trying to convince is connecting the nodes and ancestors to the time axis horizontally, instead of using a line perpendicular/normal to the axis. That's why this person said the first option is not wrong.


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Mixed-mating plants: is the number of mixed mating plants supposed to be trivial?
I am referring to Winn et al. 2011
Last sentence of the first paragraph is

Although sampling bias against both selfing and highly outcrossing species may inflate the frequency of mixed-mating populations, the number of species reported to show mixed mating is not trivial, and calls into question the status of mixed-mating populations as transitional, and therefore the sufficiency of the theory to explain the observed distribution of mating systems in hermaphroditic species.

I do not really understand what is the logic behind the highlighted part and what is its purpose.

Is the number of mixed mating species supposed to be trivial in a case where the number is inflated (So there is a need to clarify it is non trivial)?
How does the fact that it is not trivial bring up the question below the highlighted part?

I edited your post. Feel free to roll back if you don't like the edit

I think the main message of the quote is
"Many would have expected that mixed mating can only exist as a transitional state and thought that stable equilibriums are either pure selfing or pure mixing (or both). The observation of a non-trivial number of mixed mating populations suggest that our expectations were wrong."
The first sentence of the quote is a statistical detail of their paper and not a premise for the conclusion that there is a non-trivial number of populations that show mixed mating.
The evolution of selfing is a large topic in evolutionary biology and cannot really be summarized in a single post (even more so that many question are still open to debate). Goodwillie et al. 2005 is a review on the subject that will help you understand the work that has been done on the evolution of selfing. Very related is the evolution of hermaphrodism, dioecy and other mating systems in plants. Pannell 2002 is a very good paper on the evolution of androdioecy and the maintenance of these unexpected mating systems.

If the first sentence is only a detail, then why does it use "although" to begin the sentence? I would assume the first sentence is somehow supportive of the opinion that the number of mixed mating species should be trivial. That is exactly where I do not understand why (the relationship that "inflation" implies "trivial").

As I understand the section, it could be rephrased as:

Even though the frequency of mixed-mating populations might be artificially inflated due to sampling bias against both selfing and highly outcrossing species, this is only a partial explanation. Also when taking the sampling induced bias into account (i.e. controlling for sampling bias), the number of mixed-mating species is still not insignificantly small. This observation challenges the notion that mixed-mating populations are supposed to be transitional, and therefore also the current theory used to explain the observed distribution of mating systems in hermaphroditic species.

So, for you questions, I would say:

The number of mixed mating species is non-trivial (i.e. not small and insignificant), even after removing the inflated numbers caused by sampling bias.
The fact that the number is non-trivial, and not only caused by a sampling artifact, fits poorly (according to the authors) with the idea that mixed-mating populations are supposed to be transitional. Therefore, by extension, the observation of a non-trivial frequency of mixed-mating populations also challenges the theory used to explain mating systems in hermaphroditic species.

As a final sidenote, this question could just as well be posed at English-SE (or SE-English language learners), since it is mostly a question about the english language.


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What is the interchange of nutrients between plants called?
I've heard about how fungi is the nutrient super highway of the plant web. What is this interchange between plants and the fungi called?

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

Since all the exchange takes place at a molecular level, it can be called  Bidirectional transportation/ Bidirectional transfer of minerals, carbon, and other nutrients.
During the symbiotic association, the fungus grows either inter- or intra-cellularly in the host plant's root system to create certain interfaces between both symbionts. These interfaces are often termed as symbiotic interfaces, which are simply membranes of both the symbionts' cells separated by an interface space.
Like a normal bio-membrane, these membranes/symbiotic interfaces also have different types of transporter proteins, channels, ion-gates which have their regular role in the transportation of molecules across the membrane. The compositions of these symbiotic interfaces differ from species to species.

The process of interchange of nutrients is similar to what takes place between two cells. It depends on the concentration of molecules, charge, size etc.
For more info- http://www.davidmoore.org.uk/21st_Century_Guidebook_to_Fungi_PLATINUM/REPRINT_collection/Ferrol_etal_nutrient_transport.pdf

Mycorrhizal associations. These are mutualistic associations between the roots of plants and the mycelium of fungi. The plants and fungi both benefit. The plants gets improved access to nutrients deep in the soil and the fungi get access to the photosynthetic carbohydrates made by the plants.
Here is a good source: https://www.pnas.org/content/116/46/23163

what 1 or two words is the specific interchange between 2 plants, or fungi and plant called, since the whole system is the mycorrhizal network?


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What kind of yellow flower is this?
Shot in a garden in Haliburton, Ontario, Canada on August 6th, 2020. Flowerhead size approx. 3" diameter across.

It would be helpful to show the flower-head from a bee's eye view, perhaps the leaves too if you can.

Can unequivocally say Asteraceae from the picture. Beyond that, without more information, very hard to say. Likely a garden (cultivated) plant rather than  a wild species.

We serious gardeners call that a DYC: a damned yellow composite, because there are so damned many of them. Head on photo required, but I'd guess it was a single heliopsis. Leaves would help, too.

It's definitely heliopsis, probably Heliopsis helianthoides.


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Same 185th million grandfather?
I was watching a lecture by Richard Dawkins earlier today and he mentioned that “Your 185th million grandfather was a fish.” I started wondering about the following question,
Is it true that my 185th million grandfather is the same as your 185th million grandfather?
Now, I fully recognize that there are more generations in my family tree than in yours or vice-versa so the 185 million may not match up exactly. This is not the point of the question. Do Humans share a common ancestor substantially after the origin of life?

Yes, all currently living humans stem from one ancestor which was also hominid. Much further back, all life probably shares one ancestor.

All currently existent forms of life (and all their ancestors) are thought to be descended from a single life form known as LUCA (Last Universal Common Ancestor). Within those organisms, all organisms that share a common ancestor more recent than LUCA are said to be phylogenetically related. These organisms are (ideally - see note) grouped together by scientists into monophyletic taxa.
Therefore, ideally, each taxon represents a group of organisms that have descended from a single common ancestor, not shared by any other taxon. Taxa are defined at various levels including, but not limited to, Kingdom, Phylum, Class, Order, Family, Genus and Species, with organisms at each level having a more recent common ancestor than the ones preceding it. For example, for humans, a superficial phylogenetic classification would look somewhat like this:

Kingdom: Animalia (shares a common ancestor with all multicellular, eukaryotic, heterotrphic, motile organisms)
Phylum: Chordata (shares a common ancestor with all animals that possess a spinal cord)
Class: Mammalia (shares a common ancestor with all chordates that produce milk and are warm-blooded)
Order: Primates (shares a common ancestor with all monkey-like mammals)
Family: Hominidae (shares a common ancestor with all the great apes)
Genus: Homo (shares a common ancestor with relatively recent humanoid species)
Species: sapiens (shares a common ancestor with all humans)

As you can see, this means that all humans share a common ancestor with all other humans, but going further back, they also share a common ancestor with all primates, all mammmals and all vertebrates. Eventually, all animals share a common ancestor, and if you go as far back as LUCA, so does all life.
Note on taxonomy and phylogenetics: Many modern taxa are (to the best of our knowledge) monophyletic, meaning all organisms in a given taxon share a unique common ancestor. However, there remain several taxa that are paraphyletic, because they were described before modern genetic methods became available, or because no one has got down to reclassifying them or (in at least one case, reptiles and birds), because they are so widely used that changing the classification could (and probably would) cause a lot of confusion. So, when using taxonomic classifications to deduce phylogenetic relationships, a bit of caution must be exercised to ensure that the taxon one is talking about is indeed monophyletic.


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Action of Ebola Viruses
This video suggests that the first cell to be the victim of viral infection of ebola is the dendritic cell which acts as the leader of immune system cells.But I am unable to understand how the dendritic cells get infected if they are the leaders?

Ebola is not something you should worry about... http://www.pbs.org/wgbh/pages/frontline/hunting-the-nightmare-bacteria/

This is a good question. The other question is how does it deactivate the dendritic cell.

Viruses can infect any cell:

a virus must have a host cell (bacteria, plant or animal) in which to live and make more viruses. Outside of a host cell, viruses cannot function.

Source
This includes the dendritic cells:

Dendritic cells are antigen-presenting cells of the immune system. Their main function is to process antigen material and present it on the cell surface to the T cells of the immune system. They act as messengers. They don't actually release any antibodies.

Source
Quite simply, at the beginning of an infection, the viruses / bacteria will be destroyed by macrophages.

The dendritic cell will "pick up" some of the leftover pieces.

When it finds a T-Cell that has the same configuration, it orders lots of identical T-Cells to be made. These T cells have multiple jobs, one of which is activating the B cells. It is the B cells that release the antibodies.

So Ebola.
If the dendritic cells are "invaded", then the only line of defence is the macrophages. This is often not enough to stop an attack, and it multiplies out of control.
The reason the Dendritic cells can be invaded is because they are just as vulnerable as other cells. They haven't activated the T cells, and they haven't activated the B cells, so there is nothing protecting them.
Images Source (YouTube video)


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Preventing Diabetes by preventing stress?
I have came to know that taking a lot of stress increases the risk of Diabetes, and patients of Diabetes are adviced not to take too much stress, am i correct? if yes then I am unable to understand that how stress affects the level of glucose in our blood?

Prolonged stress leads to elevated levels of cortisol. Cortisol interacts with insulin action and blood glucose levels in various ways, essentially promoting hyperglycaemia.


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Does fasting improves immunity?
I have heard that fasting causes regeneration of memory cells(B- and T-lymphocytes) thereby improving immunity.Is this true? If yes, how?

For those interested, i have found a study examining memory cell depletion in deer mice due to food restriction. The author considers energy cost of memory immune response and examines it in animal trials. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2727600/#!po=65.9091 Perhaps not counterproductive in autoimmunity issues.

Interestingly this effect seems to be true - there is one paper which claims that fasting for three days leads to the depletion of unused (and especially damaged) immune cells to save energy. When food is back at normal rates, the body starts to renew these cells which have been depleted before. This process also seems to enhance the self-renewal process of stem cells which start to replicate and further differentiate.
This works like in the figure below (from the paper below):

Although this renews a part of the immune cells, I wouldn't say that this improves the immune system. I think that here mostly naive cells (which haven't) come in contact with an antigen are shut off. If you deplete memory cells (which had this contact) this would be counterproductive, since these cells are important for a fast immune response.

Prolonged Fasting Reduces IGF-1/PKA to Promote
Hematopoietic-Stem-Cell-Based Regeneration and Reverse
Immunosuppression

There is as well an article in Science Daily, which summarizes the original paper. It can be found here.


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Is there any evolutionary significance of downward facing nostrils in human beings?
The nostrils in apes and monkeys are almost at the front, but in humans nostrils (external nares) face downwards. Also a lot of non-primate mammals like goats have nostrils at the front.
Is it the increased cranial capacity in humans which pushed the nostrils downwards?
Is having a pair of downward facing nostrils, an advanced feature? If yes, then why?

I think you're right, there's a lot of articles here: https://www.google.fr/search?q=evolution+of+human+nose&oq=evolution+of+human+nose&aqs=chrome..69i57j69i60.3832j0j7&sourceid=chrome&ie=UTF-8 Some people do have quite upturned nostrils, it seems that dust, aridity, cold, long distance running, checking food, swimming, diving, and talking to people who have caught a cold are good reasons to have discreet nostrils and longer nares.


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How does inbreeding depression cause infertility?
My textbook states that repetitive self-pollination in the plants cause inbreeding depression which causes infertility thus plants develop techniques called outbreeding devices to encourage outcrossing. My question is how does inbreeding depression cause infertility?

One of the main contributors to inbreeding depression are recessive lethal alleles. Suppose you have an individual who has the genotype Aa, where A is the dominant, non-lethal allele and a is the recessive lethal allele. This recessive lethal allele is likely very rare in the population (selection would decrease the frequency of a recessive lethal allele), so our Aa individual can breed with almost any individual without consequence because most other individuals are AA, so the offspring of this individual will be either Aa or AA.
However, if the Aa individual breeds with itself or with a close relative who has the Aa genotype, its offspring will have a chance of inheriting the two aa alleles, which is lethal, decreasing the fitness of the Aa individual that bred with itself (or a close relative). This decrease of fitness resulting from self-breeding will cause selective pressure to outcross instead of self.
It is important to note that the recessive allele doesn't need to be strictly lethal for this effect to happen - if the recessive allele causes infertility (for isntance, failure to produce gametes or something similar) the same effect will happen.
In short, inbreeding can cause detrimental recessive alleles to become paired, causing lethality or infertility.


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Why does hypergranulation prevent the epithelialization of a wound?
I recently read about how does a wound heals. I read that when the granulation tissue protrudes out of the wound bed (proud flesh), the epithelialization cannot occur because the protruding proud flesh is in the way.
But I don't really understand why. Keratinocytes migrate on the surface of the granulation tissue. Even if it bulges out they should follow the geometry of it, shouldn't they? Otherwise I think none of our wounds would heal...


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How to gather life-history traits data on bird species?
I am looking for a data base of life history traits for bird species. Is there such data base? If not, what are your advice on how to collect those data? Is there a handy website that list characteristics of birds around the world? I started to gather those data using wikipedia (and the references anytime wikipedia actually have reference) but it is very cumbersome.
The kind of data I am looking for are:

Reproductive age
Average lifespan
Average gestation time
Number of eggs per reproduction event

Welcome to Biology.SE. When reading your question without reading the example, I was rather thinking you were looking for population data (dynamic of population size through time and things like that). But it seems that you are actually interested in life-history measures of different species, is that right? If yes, you might want to change your post to say that you're looking for life-history data (and not population data).

@Remi.b Life-history is the term I was looking for

I rewrote your post. If you don't like it,please feel free to rollback. In its current form, I am voting to reopen the post.

I started looking at wikipedia and I even started collecting the life history traits into a spread sheet, but I wanted to see if there was something like this already available, becuase it seemed to be very cumbersome

Yes indeed. And the question seems legit. This is why I cared about improving the format and defining the scope more accurately hoping it would get reopen. I added that you started with wiki to the post.

Have you tried the Ecological Data Wiki? It's an NSF-funded repository of links to ecological databases and datasets:
Main page:
http://ecologicaldata.org
Find data tab, refined to Taxon=Birds, Ecological level=Species:
https://ecologicaldata.org/search?f[0]=taxonomy_vocabulary_2%253Aname%3ABirds&f[1]=taxonomy_vocabulary_6%253Aname%3ASpecies
The 'Avian body size and life history' dataset on the above page looks relevant to your search.

Up until recently, my answer would have been: Find your library's copies of standard reference-works like the Handbook of Australian New Zealand, and Antarctic Birds, Birds of the Western Palearctic, and the Handbook of North American Birds, and prepare to spend a couple of weeks transcribing the details of interest for each species. You still may need to take that approach for some regions.
For Australian birds, most of the key details are now available in digitised form in Garnett et al. (2015). Similar datasets may be available for other regions.


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Why would worker bias sex-ratio toward workers?
This question prompts for explanation on a topic, an interpretation of this topic is given. A simplified question statement is also given at the end for those who do not wish to read.
Topic
In the Self Gene by Richard Dawkins, it was suggested that genes are the fundamental units of evolution.
In one of the chapters of this book, animals such as the ants are discussed. These animals are specified to have the following properties:

They live in colonies consisting of sterile workers and reproductive queens.
Worker ants possess half of the genes from its queen and half its genes from the king, which is not living in the colony because it died after fertilizing the queen.
The queen produces male "drones"--potential kings for future colonies. Drones are genetically identical to the queen.

The following interaction is suggested: worker ants, being less related to the drones than they are to each other, will manipulate the colony to increase the number of workers and reduce the number of drones present. They may do this by eating some drones before they hatch.
The reason why the workers do this is explained and interpreted as such:
The workers wish to produce more individuals that are more closely related to themselves; other workers are more closely related to a worker than a drone is to that worker; therefore, the worker prefers another worker over a drone.
Question
The Selfish Gene suggest that genes are the fundamental units of evolution, therefore a successful gene must be able to displace its alleles by being better at propagating itself.
Suppose gene-A incentivizes workers' drone-eating behavior, this gene in the short term and within one colony can produce a larger number of its own copy, but all of these copies are inside sterile workers, none of which can propagate gene-A.
When the colony containing gene-A spawns drones and potential queens, there are two cases to consider:

Gene-A is present in drones: If this is true, then by incentivizing the occasional drone-killing by the workers, gene-A has reduced the number of gene-A carrying drones, this is deleterious to gene-A. When workers of the new colony is born, gene-A reduces the number of possibly non-gene-A-carrier drones and decreases the fertility of the new colony in general.
Gene-A is present in female offspring: gene-A decreases the fertility of new queen, making her produce less gene-A carrying drones, this is again deleterious.

So far, gene-A has proven to be often deleterious to itself by restricting the number of reproductive individuals that may carry it. In terms of competition, gene-A may harm its alleles when the queen carries the allele and the king carries gene-A, but this will stop being beneficial when the number of gene-A and the number of its Alleles reach a 1:1 ratio, since after that point, the probability of harm is equal for both.
So, why is the drone-killing behavior still exhibited in animals such as ants?
Simplified question
Worker ants sometimes kill male ants in its colony because they are less related to the worker ants than the latter is to each other. Since worker ants can't reproduce, why do they bother about the number of close relatives who also cannot reproduce?

+1. The question is a little long though :) This question has bugged me already in the past. I don't fully remember how I ended up accepting it. There are good evidence for the existence of different sex-ratio depending on the number of fathers though.

Note btw, that there are a few sentences that make no sense in the post such as gene-A has proven to be often deleterious to itself. A gene cannot be deleterious, only an allele can. Also, "deleterious to itself" is either senseless or terribly redundant. Similar issue with gene-A may harm its alleles.

Is there any rephrasing that you suggest?

I'd suggest rephrasing the title - it's currently quite uninformative / nonsensical.. also is this purely hypothetical or has this behaviour been demonstrated? Could you point me to where in the book it talks about it?

@rg255 ha ha the title is the only thing that I edited.

@user289661 I have to confess that I am too lazy to read the whole post entirely so I upvoted hoping somebody else would make the corrections. If it is unclear to you why sentences like gene-A may harm its alleles make no sense, then you might want to follow a quick introductory course to evolutionary biology such as Understanding Evolution for example


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Seed head Identification. July in Toronto, Ontario, Canada
What flower has this type of seed head? (this was shot on July 17th, 2020)
This was in a residential garden in Toronto. Going from memory, i believe the size was approx. 2 1/2" to 3" in diamater.

Looks like an allium to me, but I doubt anyone is going to be able to identify it more specifically from only this part of the plant - there are hundreds of alliums, both cultivated and wild. Do you have other photos of the rest?

Thank-you Bryan, that's really helpful. This is the only photo i have.

Alright; I'll post it as an answer. Possibly someone else will be able to narrow it down a bit more for you.

Looks to me like an allium, but you'll find many of these look quite similar at this stage, I doubt you can get much further than that. See for example a Google image search for allium+flower+seeds (added 'seeds' to the search to get later stages like the one you've got).
Alliums include onions and garlic (both cultivated versions you'd commonly find in a grocery store and wild varieties; for onions this includes green onions and scallions as well as bulb onions), numerous other plants grown primarily for decorative purposes commonly called "allium", and lots of other wild plants.

I agree with @BryanKrause that this is an Allium seed head. The seed pod and seed on the end give it away
For another partial match from a commonly cultivated plant in domestic gardens, Agapanthus seed heads look similar, though the seed pod and seeds are elongated and winged. When these dehisce at the end of seeding you can be left with a head that superficially looks like OP's photo, but without the small black seeds. Agapanthus tend to be much larger, up to about 6 inches (15 cm) across, though there are many cultivars, some of which have smaller inflorescences.
Head with seed pods (from gardeningknowhow.com, photo by eldadcarin):

Without pods (from seenobjects.org, photo by Martin Kenny):