text:
Adipocyte Density
People who are overweight and wish to lose weight, often do so because they are concerned about looking too big.  Their increased size is attributed to an increased volume of fat.
When people try to lose weight however, they often quantify their goals in terms of weight, not volume.
So my question is, is the volume of an adipocyte cell always directly proportional to the weight of the fat stored within the cell?
If not, what factors would increase/decrease the size of the adipocyte cell for a given mass of stored fat?

Chris asked, "what factors would increase/decrease the size of the adipocyte cell for a given mass of stored fat?"
For an obese person, subcutaneous and visceral fat is composed of 40% immune cells, while that number is ~10% in lean individuals. There is much interplay between adipocytes and immune cells via adipokines and cytokines. Examples include ADIPOQ (adiponectin) and IL1 (interleukin 1). Thus, agents that reduce the inflammation state of the adipose tissue are also likely to have an effect on adipocyte size. This nonetheless is secondary to diet and diet composition as an adipocyte is nearly all lipid droplet and that lipid droplet stores fat - either from the diet directly or converted into fatty acid from simple carbohydrates in the diet.

Is the volume of an adipocyte proportional to the mass of fat that it stores?
The answer is: yes.
Since fat is stored in a lipid droplet within the adipocyte, it is already in the densest form possible. In other words there is no way to make the stored fat more compact, so that a given mass of stored fat takes up less volume.
Response to comment from Chris:
I think you are perhaps being a little pedantic here. Anyway the graph below conveys my view, together with your refinement. So yes, adipocyte volume changes in proportion to mass of fat stored. (The line on my graph should be at 45 degrees, but I drew it by hand so it may be a little out.) There is no way to escape the increase in volume when fat is stored.

Adipocyte volume isn't directly proportional to adipocyte fat content.  Because this would mean 0 fat = 0 volume.  But even with no fat, adipose cells still exist and occupy volume.  Are you however suggesting the change in adipocyte volume is proportional to the change in fat stored within?

Adipocytes (fat cells) change in size quite a bit with nutrient and particularly fat uptake.
Take a look at this paper which is about identifying adipocyte sizes from histological slides.
  In the cross section they are sometimes 10+ times larger.  When you add depth to the equation there is quite a bit of range in the fat cell must be substantial.
On the other hand, white fat cells do multiply and it is thought that when fat cells are engorged, they secrete growth factors that encourage adipocyte division.
So its not just the adipocytes getting larger, but there are also more fat cells over time if there is extra fat storage needed.
Its particularly of note that Insulin like growth factor 1 (IGF-1) is one of the factors identified that signals adipocytes to divide, coupling fat tissue multiplication with metabolic factors just as you might expect, possibly participating in the development of insulin resistance as the tissue expands.

Very interesting!


text:
Why do we still have genetic disorders that show anticipation?
Anticipation whereby symptoms of genetic disorders occur earlier and with more severity as it is passed from one generation to the next.
So wouldn't these inherited diseases over a few hundred generations affect offspring before they can reproduce and thus shouldn't these diseases like Huntington's disease no longer be with us today?
Or are most of these genetic diseases generated through sporadic mutations at a high enough rate to persist?

I can think of 3 explanations (not mutually exclusive) for the maintenance of important genetic disorders that prevent the sick carrier to reproduce.

Following what you said, the frequency of a given allele in a population is influenced by selection, drift, migration and mutation. Some disease present at low frequency can typically spontaneously de novo appear in a population. This is typically the case of cancer and trisomy 21 where new mutations (mutation in the broad sense) likely explain a big part of why such disease do not disappear through time.
Many genetic disease are carried out by recessive alleles. In consequence, only homozygotes for the recessive allele express the disease and the disease can persist through drift. Note the interesting case of hemophilia and Malaria resistant where the heterozygote actually has higher fitness than any homozygote (heterozygote advantage), particularly in regions where there is a high prevalence of malaria. In this case, the disease is not washed out of the population not only due to drift but also due positive selection on the heterozygotes.
Many so-called genetic disease actually have an important environmental component. For the Huntington's disease, the carrier of the autosomal dominant mutation does not necessarily express the disease. From wikipedia:

The disease is caused by an autosomal dominant mutation in either of an individual's two copies of a gene called Huntingtin, which means any child of an affected person typically has a 50% chance of inheriting the disease.

As a result the Huntington's disease can still segregate thanks to drift in the healthy heterozygotes.

I don't see the environmental component in the final part of your answer, the quote doesn't seem to mention an environmental factor, and I won't consider luck to be an environmental factor.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


text:
Can a tree survive if someone cuts all buds?
My thought was to cut all buds of a deciduous tree at spring and see if it can survive a year and develop new buds and leaves next spring. Assuming the tree is already grown and not a sapling.
If the loss of all buds would be to fatal, how many would a tree need to recover?

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
If re-boiling does not curdle the milk, can that be taken as an indicator that the milk hasn't developed the bacteria (and their toxins)?
Usually when left in hot temperature, the milk curdles (which I know when I boil it and it starts separating).
If the re boiling does not curdle the milk, can that be taken as an indicator that the milk hasn't developed the bacteria (and their toxins)?
This is the milk that I use.
http://www.amul.com/products/amul-taaza-info.php

@Jay Yes, I get milk in packets which IS pasteurized. Thanks.

the fact that there are bacteria in the milk (and unless you get sterile milk you WILL have bacteria in it) does not mean there are toxins in it (note that sterile is not the same as pasteurized) 2) yes, bacteria will acidify the medium they grow in, as a result of their metabolism (like any other cell would). 3) the milk should not really separate when you boil it, unless you acidify it at the same time (like when making cheese).


text:
What does static electricity generated by plastic combs do to our hair?
It is said that wooden combs should be preferred to comb hair as compared to plastic combs. Reason is that plastic combs generate static electricity.
Question: What does static electricity do to our hair that it is said that we should use wooden combs to prevent that electricity generation?
Is it bad for hair? Does it get generated always when we comb hair?

The motion of the comb against your hair remove electrons from the hair and deposits them on the comb. The positively charged hair and negatively charge comb now attract each other due to their opposite charges. You can read about this is any introductory Physics text, the topic is "static electricity". I doubt any harm is done to your hair, the issue is that it may be difficult to get your hair lying perfectly flat because of this attraction. This effect is more pronounced in low humidity.
If you want to see an exaggerated example of this, rub an inflated rubber balloon several times, quickly in the same direction, against your hair. Then bring it back near your hair while observing in a mirror.
Edit: I hesitated adding this because folks on this particular SE are sticklers for references. My source for the following is a workshop I attended at Chico State University circa 1990. This workshop was taught by a couple PhD Physics professors to enrich Physics teachers in electircity and magnetism.
When you dry clothes in a drier, static electricity is generated resulting in "static cling". But the cling that persists after a load is done is only part of the story. Constantly, at least once clothes are sufficiently dry, electrons are being stripped from one type of material by another. These electrons snap back from where they accumulate to where they were removed. This results in microscopic "sparking" that causes an ever-so-sight amount of wear on the cloth. So, the professors went on, the use of fabric softening anti-cling tissues minimizes this and prolongs the life of clothes. My take is that this is subtle and is more likely to be evidenced by the quality of appearance of the surface of a garment after many washings than it prematurely falling apart. I don't know for sure how significant this is, especially if you replenish your wardrobe regularly.
So, this may also apply to hair. But, unlike a particular garment, hair is constantly replenishing itself. (Well, not on my head.) So I seriously doubt this static discharge damages hair to any measurable extent. Perhaps if you were to run a comb through your hair for a couple hours every day you might see an effect. Bottom line for me, I use anti-static tissues, fragrance free; typically I get 20 years of use from my washable items and consider the tissues cheep insurance.  But I use plastic combs on what remains of my hair without any worry.


text:
Modelling how much cadmium a cell will be able to chelate with phytochelatins
I am involved in a synthetic biology project where I have to do modelling with ODEs. The biological process I want to model is the chelation of Cd2+ with phytochelatins, to know how much can be chelated. I know the basics of ODEs and I already did other modelling tasks, but I never studied anything related to chelation (I am a computer scientist) so any hint about how these kind of biochemical reactions are modelled would be helpful to get started.

If you know the stoichiometry and dissociation constant of the binding interaction this should a straightforward task. If the aim is to discover the stoichiometry via modelling, it's unclear to me how that could work. I'm probably missing something - maybe you could expand your question, and/or make it more specific?

would this be more suited for the chemistry stack exchange? Chelation is a wide field, and there may be existing models based on EDTA, siderophores, and others that could serve as decent starting points.

One of the best ways that I have found for modeling reaction pathways is to set up a boolean network for that specific pathway. The boolean will give you an idea of the possible different states in that pathway (dependencies) and while not really necessary I find it helps orient you to the system.
The next step once you have yourself oriented is to set up Michaelis-Menten equations which you can then use to run you ODEs. Here is a great primer on how to set up these equations: http://depts.washington.edu/wmatkins/kinetics/michaelis-menten.html
The subsequent modules provided in that link are also helpful in explaining how to set-up quadratic velocity equations and do different sequential models.
Also, I'm sure you know this but, it bears saying: these are all steady-state kinetics. If you are looking for a more accurate model of what is occurring in that reaction you are going to have to set-up stochastic models of your system.
Hopefully, that answers you question. Good luck!
EDIT
I have found a paper that seems to relavent to the process you are trying to model. It goes into a bit more detail than I think you are looking for but the basics seems sound. Mendoza-Cozatl and Moreno-Sanchez, 2006

would michailis-menton really apply here? phytochelatin is a polymer that chelates metal ions and gets transported to the vacoule. I guess you could treat it like 2 enzymatic reactions, with chelation as step 1, and transport to vacoule as step 2. But you might get complex cooperativity as more metal ions bind to the phytochelatin.

Michaelis-Menton is only relevant to a simplified system that only has explicitly two variables. It seems from the original posting that this is the case. The original poster appears to be only trying to observe chelation and not transport to vacoule which makes this method a valid option. You are correct that you can treat the pathway as individual reactions but those reactions you mention must be considered independently for the Michaelis-Menton approximation to work. Additionally, cooperativity can be identified by a sigmoidal curve as in the classic case of hemoglobin.


text:
Gliotoxin ingestion and actions needed
what are the "next day" actions that one has to take, when accidentally ingests contaminated drink/food from Aspergillus or Penicillium or Candida fungus?
Is it feasible to take N-acetyl-L-cysteine supplements? What other measures minimize the damage from the mycotoxins?
What kind of supplements and/or treatments reduce the superoxides produced as effect of the mycotoxins?


text:
Help to identify larva found in sink?
I need some help in identifying this critter. It was found in southeast Georgia in a home I am renovating. There were several around the sink and toilet bowl.
Approximately 5 millimeters long. Stripes black/dark gray. Tapered end seems to be moving as though it was the head. Bulbous end has two extrusions like antennae?
Thanks in advance.

Found it!
Seems to actually be the pupae phase of the common drain fly - psychoda spp.
Looks like I'm going to be routing or replacing the pipes in that house.
Thanks.

Welcome to Biology.SE! You are more likely to get a positive response to your answer if you explain why your identification is correct. Specifically, please edit your answer to add discussion of key features that led you to this conclusion and supporting references or at least validated images. Without this your answer is indistinguishable from opinion. ——— You may also wish to take the [tour] and then consult the help pages for additional advice on [Answer] effectively on this site. Thank you!

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


text:
Pathway where carbon dioxide captured by phosphoenolpyruvate is not re-released?
I have been reading about C4 carbon fixation in which CO2 is captured by phosphoenolpyruvate (PEP) to make oxaloacetate.
Are there known pathways in plants that use substantial amounts of this oxaloacetate for anabolism, i.e. without decarboxylation and subsequent use of the CO2 by RuBisCO?
My searches keep getting absorbed by the huge amount of info on conventional photosynthesis.

I assume you are aware of the position of OAA in the TCA cycle and the glyoxylate pathway. Anything TCA cycle intermediates can do, additional OAA can do. But it wouldn’t because the whole point in C4 plants is to build up carbon dioxide. I don’t see what you’re getting at.

I see that any oxaloacetate produced  in excess of other requirements can go on to be used for CO2 transport for C4  photosynthesis. I’m trying to wrap my mind around the fact that CO2 capture by Rubisco seems inefficient, but there must be a reason (unknown to me) why CO2 captured earlier as oxaloacetate is not used for anabolic reactions.

I have posted an answer which I hope addresses your question. I haven't actually discussed the inefficiency of Rubisco. It is topic that most of us find strange when first encountered — "Surely Nature could have evolved the enzyme to get round the problem". It may be chemically unsurmountable, or evolution does not require perfection, just something that works. Be that as it may, the phenomenon is undisputable, but the explanation is the subject of a different, speculative question (which may already have been asked).

Q. Are there known pathways in plants that use substantial amounts of this oxaloacetate for anabolism?
A. No on two counts:

“This oxaloacetate” is used in C4 plants for the specific purpose of creating a high concentration of carbon dioxide in the environment of RuBisCO after conversion to malate and aspartate and transport of the latter to the bundle-sheath cells — cells that have evolved in C4 plants for the purpose.
Oxaloacetate is not involved in any any anabolic pathways specific to plants, although aspartate (that may be derived from it) may be an early intermediate in certain pathways.

One can check this for oneself using the KEGG facility, starting with the page for oxaloacetate. At first sight the list of pathways involving oxaloacetate would appear promising in this respect, including:

Map
Description

map00999
Biosynthesis of various plant secondary metabolites

map01060
Biosynthesis of plant secondary metabolites

map01061
Biosynthesis of phenylpropanoids

map01062
Biosynthesis of terpenoids and steroids

map01063
Biosynthesis of alkaloids derived from shikimate pathway

map01064
Biosynthesis of alkaloids derived from ornithine, lysine and nicotinic acid

map01065
Biosynthesis of alkaloids derived from histidine and purine

map01066
Biosynthesis of alkaloids derived from terpenoid and polyketide

map01070
Biosynthesis of plant hormones

However, when one goes to the respective map one finds that oxaloacetate appears either as an incidental component of the tricarboxylic acid cycle, or as a precursor to aspartate (by transamination) e.g.in map01064:

This is supported by the lack of any such mention in the introduction of a recent (2020) paper in Nature Scientific Reports regarding phosphoenolpyruvate carboxylase, the enzyme that catalyses the conversion of phosphoenolpyruvate to oxaloacetate. (Such introductions commonly emphasise the ‘importance’ of the subject of a study.)

Phosphoenolpyruvate carboxylase (PEPc) is a carbon dioxide fixing enzyme that in an irreversible manner and in the presence of Mg2+, converts phosphoenolpyruvate and bicarbonate into oxaloacetate and inorganic phosphorus. It is present in bacteria (including cyanobacteria), algae, fungi and plants. PEPc has been demonstrated to be involved in atmospheric CO2 fixation and storing carbon in cell vacuoles, play an anapleurotic role, supply energy for symbiotic bacteria, produce energy, abiotic stress acclimation, seed formation, and in the development and cell expansion.

Why not?
In general, all most organisms draw off intermediates of the the tricarboxylic acid cycle as synthetic intermediates. It is true that these have to be replenished if the cycle is to continue turning (oxaloacetate condensing with acetyl-CoA, above), but this can be done at several points:

Furthermore, this use of simple intermediates for more complex ones had evolved long before C4 plants came on the scene — indeed the problem had already been solved in C3 plants.
Oxalate Production?
Although it is arguable whether this would be anabolism, @Ryan raised the interesting question of whether oxaloacetate produced in this way might be used for the production of oxalate, which accumulates as crystals in the leaves of certain plants.

The general question of the production of oxalate is discussed in the following review: Annu. Rev. Plant Biol. 2005. 56:41–71, from which it appears that this is not the case. The actual pathway of production appears to be subject to some disagreement, with most reports tending to the view that ascorbic acid is the precursor but others suggesting that the glycolate pathway operates in certain species.
I do not think this is too surprising if one considers that PEP carboxylase and oxalate formation each occur in (quite different) specialized cells. (And this is a general consideration regarding C4 plant metabolism: it has evolved in a specialized structures for a specific purpose, and is regulated according to the diurnal requirements of the plant.)

@davidjun what about malic acid in fruit

@Harrychink — Thanks. You are correct regarding the synthesis of malate from oxaloacetate. Of course this is not specific for C4 plants, but it falsifies my generalization. I shall edit my answer when I have a moment.

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


text:
Why is exonuclease action an important proofreading mechanism?
My copy of the Molecular Biology of the Cell (the 5th edition, so not entirely up to date) seems to claim that exonuclease action is an important part of DNA proofreading, and that dysfunction in  this leads to an increased rate of mutation (pp 276-277).
But at the same time it specifies that exonuclease action is only useful in removing incorrect bases from DNA-primers (p. 270). That means that only the base pairs in the one primer on the leading strand would be proofread, and only a minority of the base pairs in the lagging strand (The primers are vastly more numerous, but still only a minority of base pairs will be found inside primers).
In addition, these primers are made out of RNA and are only temporary, so I can’t see why mutations in these sequences would be considered important. They are replaced with DNA-segments at the end anyway and it’s these final DNA-segments that ought to be proofread.
So how can exonuclease action be considered an important (or even vaguely relevant) proofreading mechanism?

If you could find and provide links to the corresponding sections in the fourth edition available to all at NCBI Bookshelf on line, we could check whether you are misinterpreting the text. Few of us will have a physical copy to relate to your page numbers. Otherwise decent sized quotations might help.

@David
Updated text with exerpts, this was somewhat labour intensive ^^

@David .....and those changes just disappeared somehow (different versions open in different tabs?)

You have my sympathies. Sometimes I pause in the middle of an answer or edit and... I'll have a look myself when I have a moment.

I have edited your question to change "exonucleases" to "exonuclease action". DNA polymerase has both polymerization and exonuclease action, and it is this that the section you mention is referring to. This is evident in the diagram in my answer, which is therefore confined to your main problem — confusion about the usage of the term "primer".

Without access to the 5th edition of The Molecular Biology of the Cell I am relying on the section in the 4th edition which describes proofreading, and specifically Figure 5.9, which I have reworked in a linear manner so as not to occupy too much space on the page:

If this is, indeed, the section to which the poster refers, the problem is one of misunderstanding the term primer.
The poster appears to be thinking of the priming of DNA synthesis at the replication fork by RNA — Okazaki pieces to initiate copying of the template strand. However this specific usage of primer is not that which is meant in the diagram shown. Long before Okazaki discovered RNA priming of DNA synthesis, analysis of the reaction of DNA polymerase in vitro had shown that the process required 1. A template and 2. A primer with a 3′-OH end, with which the 5′-dNTP phosphate could react. And I for one (for I am very old) taught that to students.
So what the authors are referring to is the continual extension of the DNA strand, not its initiation. And the primer is the 3′-OH end of the growing complementary strand, hydrogen bonded to the template strand.
Appendix: Historical Perspective of the usage of ‘primer’
The double-stranded structure of DNA in 1953 suggested a ‘inverse copying’ mechanism to maintain the genetic information of an organism on cell division. A DNA template was obviously assumed, but it was not anticipated that the enzymes responsible for this (DNA polymerases) would have any further requirements. It was therefore unanticipated that the DNA polymerase described by Arthur Kornberg in 1959 could only ‘copy’ a DNA template if there was already a base-paired portion of DNA on the a complementary strand with a 3′-OH end with which the dNTPs reacted. The same was true of every other DNA polymerase subsequently isolated, and contrasted with the DNA-dependant RNA polymerases, which did not have this restriction. This pre-existing DNA on the complementary strand was termed a ‘primer’, with no prejudice of length implied. For the next twenty years students were taught that the three salient features of DNA polymerase were that it required a template, a primer with a 3′-OH end, and used dNTPs. And nobody could explain how initiation occured, and more saliently, how synthesis on one of the strands occured in the 3′ to 5′ direction.
It was only in the early 1980s that the repeated generation of small stretches of complementary RNA at the replication fork provided the 3′-OH ends that DNA polymerase could extend from. The term ‘primer’ was naturally applied to these complementary RNA stretches, but (especially as the RNA was later removed) with time became associated with the fragments (Okazaki fragments) being of small size. This association was further reinforced with the advent of the polymerase chain reaction which uses small synthetic oligonucleotide primers, as do other molecular genetic techniques.
The first edition of The Molecular Biology of the Cell was published in 1983, and its authors had worked in the scientific environment of the 60s and 70s, and naturally used the terminology of that era. Perhaps writing today, they might have used a term such as “elongating strand”, rather than “primer strand”, to avoid confusing a different generation of young scientists.

Thank you for your time and effort!

Not at all. I have added a historical appendix, which puts your confusion in perspective (and makes me feel very old).


text:
Biological Calculations
(a) At the moment of fertilization a female egg is about 100μm in diameter. Assuming that each lipid molecule in the plasma membrane has a surface area of 10-14 cm2 , how many lipid molecules are there in the egg plasma membrane if 25% of the surface is protein?
(b) Each fertilized egg cell (zygote) divides 30 times to produce all the eggs that a female child will need in her lifetime. One of these eggs will be fertilized giving rise to a new generation. If lipid molecules are never degraded, how many lipid molecules have you inherited that were synthesized in your grandmother? Assume for calculation purposes that the lipid molecules synthesized by your grandmother is equally divided between the daughter cells at each cell division.
My answer:
 (a)  Given, a female egg is about 100μm in diameter.  Radius = 50μm
           Each lipid molecule in the plasma membrane has a surface area of 10-14 cm2.
           25% of the egg surface is protein and 75% of the surface is lipids.
           Therefore, Surface area of egg is = 4π(radius)2
                                                                                =  4*3.14*2500*10-12
                                                                      =  3.14*10-8 m2
                                Area for the presence of lipid molecules = 3.14*10-8 *3 / 4
                                                                                = 2.355*10-8 m2 = 2.355*10-8 * 104 cm2
        Number of lipid molecules in egg plasma membrane = 2.355*10-4/10-14 = 2.355*1010 molecules
(b) Each fertilized egg cell divides 30 times into 2,4,8……230 cells. Assuming that the lipid molecules     synthesized by our grandmother is equally divided between daughter cells at each cell division.
•   After 30 divisions we have 230  cells synthesized in grandmother
                      Initially the zygote has 2.355*1010 lipid molecules from above calculations.
                      Therefore, each cell has 2.355*1010/230 = 21.93 molecules.
•   After mother takes birth, she inherits lipid molecules present in zygote, that is a single cell
Number of lipid molecules that is inherited from grandmother by mother is 21.93 molecules.
This zygote undergoes division for 30 times.
Thus, each cell inherits = 21.93/230
                                          = 2.0424*10-8 lipid molecules from zygote
•   Finally, a single cell in mother undergoes the zygote formation that leads to our birth.
Hence, we have 2.0424*10-8  lipid molecules inherited from our grandmother.
Can anyone please confirm it?

Welcome to Biology.SE! Please take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. For "homework" questions, you are required to use the "homework" tag. (Note that "homework" can apply to questions even if they are not assigned as homework.) In addition, this site is for asking and answering biological questions that may be of interest to multiple people, but checking your math is probably only of interest to you. Thanks!

I think almost everything is correct except for the last part.
The reason one may easily overlook that part is that we inherit the complete 22 molecules from our mother who inherited the whole 2.35 * 10^10 molecules from her grandmother zygote. Grandma gave the whole thing to her daughter and that that number was distributed in all the cells in mom's body, which is 22 per cell. These 22 lipid molecules would be inherited by us from our mom, so the answer seems to be 22 logically.
This can be understood easily as given below:
2.35*10^10 -> From granny to mommy
22 -> From mommy to us
Hope this made sense... Thanks!


text:
Mutation Rate in Multicellular Eukaryotes
I always hear people saying that the mutation rate is around $10^{-6}$ or $10^{-7}$. I don't even know if this number is the mutation rate of genes or of a single nucleotides and I actually (almost) never seen a referenced estimation of the mutation rate.
I know there is an impressive variance in mutation rate depending on the species we look at and depending on the genomic region we look at. Various other factors also influence the mutation rate such as ecological factors (thermal stress for example).
In multicellular eukaryotes, what is a good estimate of the mutation rate per nucleotide, per gene and per genome? How does real values vary around these estimates?

Actually depends on the environment also you see: Mutagens etc. BTW did you see Bert Volgenstein's paper in science last week on cancer prevalence and replication error. You would find it interesting

@WYSIWYG Thanks for the reference. No I haven't read that paper yet. Yes, I actually edited my post right before your comment to add "ecological factors" in the list of things influencing the mutation rate.

The real mutation rate of any organism depends by too many factors both external, like the environment, and internal, like the error rate of the DNA polymerases and DNA-repair enzymes and even from different region in the same genome (the mutation rate of non-coding DNA tend to be higher than the one of actively used DNA).
In general however it is possible to determine an average mutation rate for a given organism and usually it is expressed in mutation per base pair (or single nucleotide) per generation.
If you want to know roughly the mutation rate per gene or per genome you just need to multiply the mutation rate by the number of bases of the gene or genome.
Good papers on the topic are:

Drake JW, Charlesworth B, Charlesworth D, Crow JF (April 1998). "Rates
  of spontaneous mutation". Genetics 148 (4): 1667–86.
Ossowski S, Schneeberger K, Lucas-Lledó JI, et al. (January 2010).
  "The rate and molecular spectrum of spontaneous mutations in
  Arabidopsis thaliana". Science 327 (5961): 92–4.
Nachman MW, Crowell SL (September 2000). "Estimate of the mutation
  rate per nucleotide in humans". Genetics 156 (1): 297–304.

If you want to know about some specific organism you have to dig into the literature...

Hello. Welcome to bioSE. I guess the OP is aware of what mutation rates are. OP is asking information on Multicellular Eukaryotes. I understand it is a broad category. So can you, from the articles that you have listed, paste some excerpt or provide information otherwise about the estimated figures of mutation rates for the respective organisms?

Hello! Indeed, as WYSIWYG said, I am looking for estimates of mutation rate in multicellular eukaryotes and estimates of how the mutation rate varies (variations being caused by a whole bunch of factors as you said). Thanks for the references.

The point is that "Multicellular Eukaryotes" is a huge category... Here are some numbers from the papers cited before http://www.genetics.org/content/148/4/1667/T5.expansion.html the paper "Rates of Spontaneous Mutation" report all the details...

@alec_djinn I understand that it is a broad category. Can you please look more carefully at my previous comment. I'll upvote your answer if you do that :)

Ok...Then, summarizing the data I got from the publications above, the mutation rate per genome per replication span from 0.01 (in C.elegans) to 0.5 (in Mouse).
Mutation rate per base pair per replication (that probably is a more convenient unit to use) ranges from is 1.8 × 10^−10 (Mouse) to 5.0 × 10^−11 (Human) and around 3 x 10^-10 in insects and worms...
So, roughly, the average mutation rate (per base pair per replication) is 10^-11 and it can vary of +- one order of magnitude.
These values seems to be valid for most of the eukaryotes but not for plants.


text:
Mutation-Selection-Drift Equilibrium
mutation-selection-drift equilibrium is one of the most important concept of population genetics. I could easily find the calculations for mutation-secltion equilibrium and for mutation-drift equilibrium but not for mutation-selection-drift equilibrium.

mutation-selection equilibrium
At mutation-selection equilibrium the expected frequency $p$ of a given allele is
$$p ≈ \frac{\mu}{s\cdot h}$$
, where $\mu$ is the mutation rate, $s$ is the selection coefficient and $h$ is the coefficient of dominance.
mutation-drift equilibrium
At mutation-drift equilibrium the expected frequency $p$ of a given allele is
$$p ≈ \frac{1}{4N\mu+1} $$
, where $N$ is the population size.
What is the allelic frequency at mutation-selection-drift equilibrium?

I think this paper might be relevant. From what I can see they derive an analytical approx for deleterious allele frequency in MSD equilibrium.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1894624/

Drift doesn't change the expected frequency of alleles. In your equation for the mutation-drift equilibrium, I don't think that $f$ is an allele frequency -- it's the homozygosity.

"expected frequency f of a given locus is" are you sure this is correct? do you mean frequency of an allele rather than locus? According to Charlesworth & Charlesworth it should be $q^*$ which is the equilibrium frequency of $A_2$ the mutant allele

(I'm concerned with the definition not the notation - I've seen $f$ used elsewhere)

Oh I missed your comment for some reason. You are right "frequency of a locus" makes no sense. I corrected it. Also I replaced $f$ by $p$ as $p$ (or $x$) are more often used to represent allele frequency. Thanks

Maybe I wasn't clear in my previous comment -- I also was talking about the definition, not the notation. Your mutation-drift equilibrium equation is for the homozygosity at a locus, not the frequency of an allele. Drift does not change the expected frequency of alleles. So your first equation is valid for mut-sel-drift equilibrium... with one caveat: the actual equation you wrote down is just the strong selection limit of the exact equation, so if drift is too strong it won't be valid.

Oh I got the point. Can you develop your comment into an answer by clearly stating what are the expected homozygosity and allele frequency under the different scenarios of mutation-selection balance and mutation-selection-drift balance? Thanks a lot.


text:
Understanding the meaning of $s$ and $t$ in a population genetics equation
Sewall Wright in this article (1937) at the end of page 313 gives the equation:
$$\Delta q = (s+tq)q(1-q) \space\space\space\space\space\space\space\space\space(1)$$
This equation is an approximation who holds only when $t$ and $s$ are small. $q$ is the frequency of allele A. $s$ and $t$ define the fitness of the three possible genotypes AA, AB and BB. I am not sure which genotype has fitness equal to 1 and I don't how $t$ and $s$ define the genotype fitnesses.
Let's assume for example that the genotype BB has fitness of 1. Then, the fitness of the genotypes AB and AA might be given by $1-t$ and $1-s$ respectively or $1-s$ and $1-t$ respectively or eventually by $1-t$ and $1-(s+t)$ (or variants) or even $s$ and $t$ (and opposite) or $st$ and $s$ (and variants). The genotypes fitness might as well be given by $1-st$ and $1-s$ but it would not be make much sense given the assumptions used for the approximation.
My question is: do you know how is the fitness of the three genotypes defined in equation (1)?


text:
Is $F_{ST}$ a probability and a correlation coefficient?
$F_{ST}$ is one of the most famous and most important statistics of all of evolutionary biology. Yet, many people misunderstand it or misuse the classical results from the literature on $F_{ST}$ (Whitlock and McCaughley,1999).
Fixation Index in infinite islands model
In a panmictic population, the probability of identity by descent $F(t)$ in generation $t$ is the probability of sampling the same allele twice plus the probability of not sampling the same allele multiplied by the probability of identity by descent in the previous generation
$$F(t) = \frac{1}{2N} + \left(1-\frac{1}{2N}\right) F(t-1)$$
, where $N$ is the population size. Here I am assuming diploid population and no mutation. In an infinite allele model, these probabilities must be weighted by the probability that none of the parent migrated in the previous generation.
$$F(t) = (1-m)^2\left(\frac{1}{2N} + \left(1-\frac{1}{2N}\right) F(t-1)\right)$$
, where $m$ is the migration rate between any two demes. Setting $F(t) = F(t-1) = \hat F = F_{ST}$, assuming that $m$ is low and solving for $F_{ST}$ yield to the classic result from Sewall Wright
$$F_{ST} = \frac{1}{1+4Nm}$$
Definitions of $F_{ST}$
$F_{ST}$ was defined by S. Wright as
$$F_{ST} = \frac{var(p)}{\bar p(1-\bar p)}$$
, where $var(p)$ is the variance of allele frequency among population and $\bar p$ is the overall average allele frequency.
From Nei (1973)

Wright showed that the variation in gene frequency among subpopulations may be analyzed by the fixation indices or F-statistics. He derived the formula
  $$1 - F_{IT}= (1 - F_{IS}) (l-F_{ST})$$
  where FIT and F1s are the correlations between two uniting gametes to produce the individuals relative to the total population and relative to the subpopulations, respectively, while $F_{ST}$ is the correlation between two gametes drawn at random from each subpopulation. $F_{IT}$ and $F_{IS}$ may become negative, but $F_{ST}$ is nonnegative.

Question
In the derivation of the fixation index in infinite island model, $F_{ST}$ is a probability of identity. In the quotation from Nei (1973) (and other sources), $F_{ST}$ is presented as a correlation coefficient. In Wright's and Nei's definition, I don't see the relation from the equations to either a probability or a correlation coefficient. Can you help to clarify this for me?
For example, I would expect that $E\left[\frac{var(p)}{\bar p (1-\bar p)}\right] ≈ \frac{1}{4Nm+1}$, where $E[X]$ is the expected value of the variable $X$. Can you demonstrate that this is true?


text:
Population size and genetic drift - What are the evidences?
Wright-Fisher model
From the Wright-Fisher model of genetic drift, the random sampling of allele from one generation to the next is taken from a binomial distribution with parameters $2N$ and $p$, where $N$ is the population size and $p$ the frequency of an allele of interest.
Strength of Genetic drift
The strength of genetic drift can be measured in terms of two different statistics:

variance in allele frequency from one generation to the next
loss of heterozygosity per generation

Variance in allele frequency from one generation to the next
From the above, it is relatelively straight forward to show that the variance in allele frequency in the successive generation is
$$\text{var}\left(p'\right) = \frac{p(1-p)}{2N}$$
, where $N$ is the population size.
Loss of heterozygosity
Heterozygosity decays by $1-\frac{1}{2N}$ every generation
$$H_t = H_{t-1}\left(1-\frac{1}{2N}\right)$$
, where $H_t$, is the expected heterozygosity at time $t$.
Source
See Gillespie: Population Genetics - A concise guide chapter 2 for more info on these predictions.
Question
Do we have empirical evidence that the decay rate in heterozygosity and/or the variance in allele frequency due to genetic drift follows these predictions?

I suppose it's quite complex, would need large amounts of replication and have to neutralise/standardise selection and mutation across replicates - maybe mutation accumulation experiments would be worth investigating

This paper looks interesting https://www.researchgate.net/publication/11126342_Microsatellite_DNA_evidence_for_genetic_drift_and_philopatry_in_Svalbard_reindeer but it's not quite what you are looking for I think

In natural populations? No. This is why people generally talk about "effective population size". (I'm not a fan of this term though -- if we mean "the diffusion parameter of allele frequencies" or "the rate of decay of heterozygosity", we should just say so!)

Not necessarily in natural population. I was rather thinking about experimental evolution. Someone may have produced an experimental evolution where the population is as close as possible to a wright-fisher population (random mating, constant population, no selection, non-overlapping generation; so that $N=Ne$) and test whether the model offers good predictions.


text:
History: Do evolutionary and ecological processes occur at the same timescales?
Classically, it was thought that evolutionary processes occurred at a much slower pace than demographic/ecological processes. Nobody, ever thought about incorporating both processes into the same model as they were assumed to occur at different time scales. We slowly came to realize that this way of thinking is quite wrong and many demographic/ecological changes (demographic expansion for example) directly affect evolutionary processes and even more important that evolutionary processes can directly influence demographic/ecological processes. I take for example Kirkpatrick and Barton (1996) who investigated how dispersal load (fitness decrease due to maladaptive alleles brought to local populations by dispersal) affect the "evolution" of the species range limits.
Who (what) are the main authors (articles) that allowed for this switch in our viewpoint about the interrelations between evolution and demographic/ecological processes?

Dennis Chitty might have been an important author to establish the viewpoint that evolutionary processes can influence the probability of survival of a population. However, I know a little bit about his work only because he was professor at my department (way before I even arrived in the department) and he might therefore not be the most important author of all.

This doesn't directly answer your question but my current research is on building models that combine ecological and evolutionary processes. Thompson (1998) is one of the earliest papers to talk about rapid evolution on ecological time-scales. And also a recent paper highlighting the interactions was Schoener (2011).
Perhaps reading through these two papers and looking at their references will give you a better idea of when the shift in thought started.

Thanks a lot Sanalphatau (and welcome to Biology.SE). The Thompson (1998) paper will probably help indeed. +1


text:
Effective population size of a metapopulation structured on a grid
Scenario
Consider a rectangular metapopulation consisting of $x \cdot y$ demes, where $x$ is the number of deme horizontally and $y$ is the number of demes vertically. The population size per deme is $N$ and the migration rate between any two adjacent demes is $m$.
Assumptions
I welcome any kind of assumptions for the purpose of this post.
Question
Can you help me to calculate an expectation of the effective population size $Ne$ of the whole metapopulation?

I am not an expert in this area but if the initial population in all the demes is homogeneous then you can consider the entire metapopulation as one unit with x × y × N individuals. If the sex-ratios are skewed then you may expect different dynamics.

Mating is not random in the total metapopulation, the $Ne > x \cdot y \cdot N$ even if (as I assumed in the question) all demes have the same size $N$.


text:
How do plants 'tell time' for circadian rhythms based on a ~24 cycle?
I've read that many plants have some sort of circadian rhythm where they perform a certain action on a cycle of about 24 hours, like the mimosa plant opening and closing its leaves. Obviously, this is done in order to synchronize with the sun, but many such plants continue to perform these actions even when left in constant darkness or light. It follows that this is the result of some sort of biochemical pathway, but whatever internal 'clock' is used is also independent of temperature.
How can these plants perform certain actions every 24 hours at different temperatures when the chemical reactions most biochemical pathways use are temperature dependent?
It would seem like the length of the cycle should vary widely according to the temperature as it affected the reactions involved, but instead it stays at a very constant length very close to 24 hours. How can this be?
(This is in my textbook, but unfortunately the book doesn't cite any studies. I would greatly appreciate it if anyone could help me find one to link to so I can improve the  question. :)


text:
How exactly are game theoretical evolutionary models described during implementation for computer simulations?
When a biologist or a layman tries to reason the evolutionary explanation for something, they would simply use English with some math thrown in (for a random example, pick any explanation out of "The Selfish Gene" -- for example, the reasoning why "discriminate in favor of one's own eggs" strategy is employed by Guillemots, in "Genesmanship" chapter, page 103. I won't quote it in full since it's a page worth of text).
Another example of such a wall of English is (Dawkins-inspired) Bio.SE question: " Why is 'Grudger' an evolutionary stable strategy? "
When a biologist tries to actually model evolutionary development to see which traits would win, they would need to somehow teach the computer to implement that model: what the environmental factors are, what the genotype involved is, how exactly it's expressed in different phenotypal and extended phenotypal traits, and how environment would affect an individual with that phenotype.
My question is: is there some sort of standard way to build such a model? A domain specific language (in computer science terminology) that is used by many different biologists or some standard modeling packages/software? E.g. some sort of special XML format, etc...
Or is it always just hand-built custom implementation by individual researchers for their current model?

Just to clarify:

I'm NOT asking what the models look like theoretically. I'm asking what language/format (if any standard one exists) is used to encode them to run simulations.
If there are discrepancies between the type/purposes of models, the ones I'm most interested in are game theoretical ones.

The impetus of this question is, if I'm curious to see how a specific model would behave, would I have to code the entire thing - mode, language, and simulator - from scratch (likely incorrectly, being a layman); or there are some standard packages that do it for you as long as you use some proper language to describe your model.

Unfortunately the guillemot example is a bad one - Dawkins was wrong about it (and very obviously so). He forgets to account for the fact that if a bird lays twice as many eggs as any other in the colony, his eggs are twice as likely to be excluded from care.

@RichardSmith - Seems counterintuitive to me. If the only eggs being excluded are the ones that no bird claims; you lay 2x eggs, and there's 5% of you with that specific strategy, then (assuming you have a colony of 100, with 1 egg clutch for normals), you have 105 eggs total, so 5 will be excluded. Each egg has ~1% chance of being excluded, so for BOTH of your eggs to be excluded, the chances are 1%x1%=0.01%. Nearly 100 times better than a single-egg bird.

It's not the chance of both eggs being excluded that Dawkins talks about, he talks about the chance of having an egg excluded. It's still true that it would be worth cheating for the first few birds. The wider point about the trait not being an ESS might be true, but his specific explanation is not. In your specific example, if there are 105 eggs and 5 are excluded, each egg has a ~5% (more precisely, 4.76%), not ~1%, chance of being excluded. In any case, your question was interesting so I'm writing a model of the Guillemot situation. I'll report back when done :)

The field most closely associated with game theoretic models in biology is evolutionary game theory. If modeling is required, then the typical paradigm is agent-based modeling, and a good introductory book is:

Yoav Shoham and Kevin Leyton-Brown
  [2009], "Multiagent systems:
  algorithmic, game-theoretic, and
  logical foundations", Cambridge
  University press.

As for actually building the model, and what to describe/how, I will take you through my usual procedure since this is a field I specialize in:

Define what type of strategies you think are relevant to the interactions you are modeling. Select what you expect the payoff of those strategies to be. For instance, if you are studying the evolution of cooperation, you might select 'Cooperate' and 'Defect' as your strategies and the Prisoner's dilemma as your pay-off matrix, but maybe you will pick something more general. Unfortunately, in most of EGT a clear distinction between genotype and phenotype is not drawn, and they are usually equated. At the end of this step you have a game matrix G. Sometimes when mutation or innovation are explicitly necessary even in the inviscid model, further analytic approaches are taken at this stage. I recommend Hofbauer & Sigmund (2003) for a broad treatment of step 1.
Now you need a basic intuition of what the 'default' behavior in this interaction is, so solve the replicator dynamics of G.
The main interest in EGT right now is structured populations. This is where computational modeling is typically used. However, before I turn to simulation, I first try the best analytic approach I know. I use the Ohtsuki-Nowak transform on G to analytically solve the interaction for random graphs (Ohtsuki & Nowak, 2006).
If I am still interested in the question, and steps 2 and 3 didn't capture all the subtlety of the system I want to study, then I start building a multi-agent computational model. I make sure that my model has some way to scale to the completely inviscid case of replicatory dynamics, and the simply-structured case of ON-transform. If my computational model disagrees with the analytic approach in these regimes, then I become worried. Otherwise, I continue with standard agent-based modeling techniques. Personally, I code in Matlab. I have never seen a modern EGT simulation that required the performance of C/Fortran. As suggested in another answer, if you don't have a programming background then you can use NetLogo. However, my experience is that the models are typically simple enough to implement from scratch, and NetLogo models typically hide from you some very important subtleties (like which reproduction rule to use: death-birth, birth-death, immitation?) and usually lead to weaker papers.

Note the broad theme. These models are typically described as differential equations, and this approach is preferred to agent-based models. However, if a clean differential equations approach does not capture all the subtleties of what you are studying, then an ABM paradigm is adopted.

The particular language a bioligist uses depends on the trade-offs between speed and ease of programming.  Many models are written in C or Fortran if speed is paramount.  On the other hand people will write models in higher level languages if speed is less important.  These would be Python, R, MatLab, etc...  In my models, which are written mostly in Python, I write all the classes from scratch and then all the simulation components by hand as well.  Since almost all models are mathematical in nature, the language is inconsequential.  Algorithms should behave similarly across platforms.  If you're looking for examples of easy ways to code up game theoretic models, consider NetLogo, they have some nice examples using game theory.

This. I would say most people use the language they know best, so for non-programmer scientists that's python or perl, for mathematicians it's matlab, mathematica, or berkeley madonna, and for programmers it's c or some descendant.

No generally used DSLs? Is that because it's too hard to develop, or just nobody needs it?

Probably both. Berkeley Madonna is specifically for modelling, but it's horrible, so it's not that widely used.

I'd say that as far as DSLs go, Logo is a DSL for individual based models, but most biologists can program in another language that's more flexible.  Also both python (in scipy) and R have ODE solving capabilities so you don't have to use Madonna.

There is no single way to build such a model.  They can vary from a simple mathematical statement like Hamilton's rule (rB>C) to the chemical diffusion models used to describe the patterns in animal skin coloring (like zebra stripes, leopard spots and the like).
There are efforts to build molecular models of entire cells like this model of mycobacterium genitalium dividing, which integrates nearly 30 different mathematical models to describe different aspects of the organism.  There are efforts to build such a model of an entire brain as well.
Another common sort of model for evolutionary biology is the use of game theory, where different strategies can be posed one against another as in the prisoner's dilemma competition Dawkins describes in the Selfish Gene.
It goes on and on.  Basically biological modeling is driven by the sorts of mathematical models that we know.   New models will reveal new paradigms of how biology works.  They can be highly mathematical, but their relative importance and when they apply and what they mean are more analogy than proof.
For instance in the prisoner's dilemma, the first contests showed that Tit for Tat was the strongest model - generally assisting others, but betraying when there is a history of betrayal.  The ideas at the time moved towards general cooperation in populations.  More recent replays have shown that if there is a team of entrants that make extraordinary gifts to each other (allow betrayal without retribution), then they can compete against other models quite well.
One can never prove that a selfish model for the prisoner's dilemma will not show up, though biological systems to seem to be highly cooperative.  That is a model, not a proof.

My question was mostly aimed at game theoretical ones

Please see updates to the question. I'm not asking how the models are tested. I'm asking what language (if a standard one exists) is used to communicate the model parameters to the simulation.

I think the answer would be no - R could be a standard in the coming years, but i've seen several languages touted in various courses including Excel.

Let's hope R doesn't become standard for anything other than stats - it's the ugliest programming language since J.


text:
Why do restriction enzymes tend to have an even number of bases in their recognition site?
When reading my textbook I noticed that in all examples but one from eight the recognition site was an even number of bases.
I wondered if this was just a co-incidence, so I took the data from this site for over a thousand known recognition sites and put it into a spreadsheet (XLS uploaded here).  The results are probably best summarised graphically:

Stats Test: Chi Squared Goodness of Fit.
Null Hypothesis:
There is no significant difference between the number of restriction sequences
that are an odd or even length.

|---------|----------|----------|-----|-------|----------|
|  Trait  | Observed | Expected | O-E |(O-E)^2|(O-E)^2 /E|
|---------|----------|----------|-----|-------|----------|
|  Odd    |    172   |  231.5   |-59.5|3540.25|  15.293  |
|  Even   |    291   |  231.5   | 59.5|3540.25|  15.293  |
|---------|----------|----------|-----|-------|----------|

Chi Squared Value = 30.586

P=0.05, 1 Degree of Freedom: Critical Value of 3.841

H0 rejected with 95% confidence (indeed with 99.9%+ confidence)

Can anyone explain or suggest why it is more common that restriction enzymes recognition sites have an even number of bases?
Updates

Expanded dataset to include new recognition sites from the resource that 96well linked to.
Removed all duplicate recognition sites leaving 465 distinct recognition sequences (my fault for not removing them in the first instance)
Ran stats test on the data
See Previous Version

I congratulate for your reflex: from the textbook to the database search. Nicely done! Your data is from a sample of some 1100 restriction enzymes. Rebase.neb.com reports some 6800 restriction enzymes. Are your conclusions still valid?

I think this is due to the over-representation of recognition sites with length 6:
data<-c(16, 16, 12, 12, 6, 6, 6, 6, 4, 16, 6, 6, 6, 6, 15, 15, 6, 6, 6, 6, 11, 11, 6, 6, 4, 4, 6, 6, 11, 12, 6, 6, 23, 23, 6, 6, 6, 6, 9, 12, 4, 4, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 10, 10, 6, 4, 6, 6, 11, 11, 9, 9, 6, 6, 6, 6, 5, 5, 8, 8, 6, 6, 8, 8, 6, 9, 10, 10, 6, 6, 6, 5, 5, 6, 4, 6, 6, 5, 5, 14, 14, 6, 6, 6, 16, 6, 6, 6, 6, 15, 15, 6, 6, 6, 6, 6, 18, 18, 7, 7, 11, 11, 20, 20, 6, 13, 4, 4, 6, 6, 6, 6, 6, 6, 6, 11, 6, 6, 7, 7, 6, 6, 6, 6, 6, 12, 6, 6, 10, 10, 23, 23, 7, 7, 23, 23, 12, 12, 6, 6, 6, 6, 10, 10, 6, 6, 8, 8, 6, 6, 35, 35, 11, 11, 7, 7, 6, 6, 9, 9, 8, 8, 16, 16, 6, 6, 17, 17, 6, 6, 6, 6, 23, 23, 6, 6, 4, 4, 21, 21, 12, 12, 20, 20, 6, 6, 6, 6, 6, 7, 7, 6, 6, 6, 6, 5, 5, 11, 11, 6, 11, 11, 6, 6, 5, 5, 7, 7, 11, 11, 11, 11, 6, 6, 12, 12, 6, 6, 6, 21, 21, 9, 9, 8, 8, 7, 7, 16, 16, 4, 4, 6, 6, 6, 6, 7, 7, 18, 18, 6, 6, 6, 6, 6, 23, 23, 7, 34, 34, 39, 39, 6, 6, 12, 12, 5, 5, 19, 19, 8, 8, 8, 8, 4, 6, 6, 6, 6, 6, 5, 5, 6, 6, 6, 6, 7, 7, 4, 4, 15, 15, 7, 7, 7, 7, 14, 14, 11, 11, 27, 27, 12, 12, 4, 4, 10, 10, 6, 6, 8, 8, 7, 7, 8, 8, 7, 7, 5, 5, 7, 7, 6, 7, 7, 6, 6, 8, 8, 39, 39, 6, 6, 12, 12, 8, 8, 7, 13, 13, 8, 8, 8, 8, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 7, 17, 17, 17, 17, 11, 11, 15, 15, 6, 6, 6, 5, 5, 5, 6, 6, 5, 7, 7, 12, 6, 12, 6, 6, 6, 5, 6, 6, 7, 2, 5, 11, 5, 6, 4, 5, 7, 5, 4, 4, 6, 4, 5, 6, 7, 12, 6, 7, 7, 7, 6, 4, 4, 7, 5, 6, 6, 6, 7, 5, 12, 13, 5, 6, 6, 6, 5, 11, 11, 5, 6, 10, 5, 5, 11, 6, 5, 5, 6, 5, 6, 5, 6, 6, 7, 7, 6, 5, 5, 7, 6, 5, 6, 5, 6, 5, 5, 7, 6, 6, 6, 3, 5)
h<-hist(data, breaks=0.5:40.5)
df<-data.frame(counts=h$counts, mids=h$mids)
df$even <- (df$mids%%2 == 0)
ggplot(df, aes(x=mids, y=counts, fill=even))+geom_bar(stat="identity")

If you look at the histogram of lengths, there is no bias towards even recognition site lengths except for length 6.

I would guess that the followup question is why is this the case?

Interesting. Is there any motif in the length 6 sites?

Surprising that there seems to be at least one restriction enzyme with a recognition sequence of length just 2!

Most restriction enzymes recognize palindromes, hence the recognition site of an even number of residues. Why palindromes? This allows for a vast increase in complexity (or rarity) from a DNA sequence standpoint, while requiring very little added complexity from the protein. In other words, if a protein domain recognizes 2 or 3 or 4 bp of DNA, simply adding a second copy of that domain to the peptide chain (via duplication of the DNA encoding that domain) does the trick. It is much easier to duplicate a module than to build a new or second (perhaps complimentary) module.

How does being even or odd affect a palindrome? What would be the probability difference between CATATG (6) and CATGATG (7) i.e. why are even palindromes more likely?

-1 for justifying your answer by defining palindromes as sequences with even number of bases. EcoRII recognizes the palindrome CCWGG (W being A or T).

@RoryM CAT TAC is not a palindrome. CAT ATG is a palindrome.

@GerganaVandova sorry I was thinking of palindrome in the common sense rather than the DNA sense, I'll make the edit!

The misuse of the word palindrome for these sequences is a real pet hate of mine - they're rotationally symmetrical not palindromic!

@RoryM: I have no idea why you're intepreting Larry's answer as suggesting that rotationally symmetrical - ;) - recognition sequences have to be even what he is saying is that the duplication of a single recognition module can produce a rotationally symmetrical recognition sequence and that this will lead to an even length recognition sequence.

Are odd numbered overhangs actually palindromes?  Somebody gave an example saying the following is a palindrome:
5'-CATGATG-3'
However, the opposite strand will have a C in the center position, that is, it will have the sequence:
5'-CATCATG-3'
In this example, the two center-most bases (G and C) are complimentary, but the two sequences are not strictly palindromic.  This should be the case whenever there is an odd number of bases in the overhang.
Another example, a 3-base overhang.
5'-GTC-3'
The complement will be:
5'-GAC-3'
Which is not a palindrome of the upper sequence.
This means that half of the time overhangs with odd number of bases cut by the same restriction enzyme from random fragments will not be complimentary (the 5'-GTC-3' overhangs can't anneal to other 5'-GTC-3' overhangs, only to the 5'-GAC-3' ones), and unless careful attention is paid to their sequences, odd-numbered overhangs in cloning projects can cause problems.
Even numbered overhang example:
5'-AATT-3'
In this case the opposite strand will have an identical overhang:
5'-AATT-3'
and will always have homology with other 5'-AATT-3' overhangs.
I suspect that the reason there are more even numbered restriction enzyme overhangs is to avoid this problem.

This is possibly better suited to be a follow-up question than an answer.

@MaximilinPress the last sentence does seem to address the problem, somewhat. To OP: I have added the 'add citation' banner, because the answer seems more like a long comment, or an educated guess at best. It's best to pen up science-based answers, including references to credible sources.


text:
What is the mass of carbon dioxide absorbed by an oak tree in one year?
I want to understand the environmental impact of oak trees due to absorption carbon dioxide. So my question is, what is the mass of carbon dioxide absorbed by an oak tree in one year?

What's the difference between '$CO2$' and '$\ce{CO2}$' ? I'm new to SE.

Oh ok, thank you. I have now proposed an edit using that format. Will that be for an equilibrium reaction with k1 and K2 as forward and backward rate constants?

Sometimes, the simple solutions work well: CO2.

It's uncommon (and probably not that useful) to consider this sort of question from a "per tree" perspective. "Per tree" depends greatly on the surrounding environment. Instead, people typically approach carbon fixation from a "per area" perspective.

I upvoted @RodrigodeAzevedo  comment, but neither work in titles on the phone and the Math thingy is unreadable. In any case one has always to ask oneself why not just writing carbon dioxide? It’s not as if there’s any equation involved. So it’s not justified. So I’ll edit it.

@trinitrotoluene: The difference is that some people (and I'm one of them) haven't memorized the keyboard combinations or other gymnastics needed to get subscripts :-)  Just about everyone will recognize what you mean if you write "CO2", though.

This question is unanswerable as it stands.  How big an oak tree, a year-old seedling or the centuries-old oaks of English forests?  What species?   Quercus robur (the English oak again) or the often shrubby Quercus wislizeni found in interior California?  Just to pick two of many species of oak.

@David I have posted a question regarding formatting on meta. Please let me know of the accepted formatting on Biology.SE

Re: Bryan Krause's comment, measurements per hectare are common. However, if you can just estimate average trees per hectare, then it works out. But it still likely depends on the local climate, ecology etc. It also varies across the life term of the tree.
Some estimates have been made, such as in this paper (see Table 4), for Quercus rubra and 2 other hardwood species. They estimate that for the most mature trees, Q. rubra stores ~20 Mg/hectare total biomass, of which approximately half is carbon.
This is a little more than twice the biomass of the 8-year-old tree, so if we just linearly interpolate we could say that a hectare of oak stores ~1 Mg C per year. There are some problems with this- for example, older trees are likely to store much more than that, but it is not clear exactly how much variation there is over the course of an oak's life, and also there is likely variation between the sites in the study.
It is also clear that the other species measured, e.g. American chestnut, are more effective carbon sinks than oaks as young trees.
See the paper or this pop science article on the subject for more information. THere are also a number of papers citing that paper that may be interesting, such as this, this, and this.


text:
Recombination Data Set
I was looking over some genetics question and came across this data set.

In the fruit fly Drosophila melanogaster there is a dominant gene b+ for grey body color and another dominant gene c+ for normal wings. The recessive alleles (b,c) of these two genes result in black body color and curved wings respectively.

The question asked about calculation of the recombination frequency.
To me Ada's data set makes sense as the parental type offspring numbers are higher than the recombinant offspring. However, Donald's data set doesn't. Is there any way a recombinant offspring could be in a higher proportion than the parental type offspring?

can you give more info? which is the parental type? what is the experimental design? are these derived from the same background? what generation, e.g. F2? not enough info to answer as it is. This looks to me like a homework question, if so please add the "homework" tag.

This isn't a homework question. In fact, this is a question from IBO. I'll actually post the whole information.

b+/c+
b/c
b+/c
b/c+

Ada
~0.39
~0.42
~0.08
~0.1

Donald
~0.09
~0.09
~0.4
~0.41

The other chromosome beeing b/c (I assume each one got an heterozygote fly and than they did a testcross)
There are a two possibilities for an heterozygote fly:
(b+/c+, b/c), (b+/c, b/c+)
If there was no genetic linkage we would except 0.25 for each fly group, but we didn't which means that fly groups with a higher probability are showing the original parental chromosomes phenotyping.
Since they didn't get the same results (by far) I assume (there are statistical tests for this) each scientist got a differently genetic fly
Donald got (b+/c+, b/c) since in his experiment the predominant flies are those showing a dominant phenotype and recessive phenotype and Ada got the mixed fly.
With this in mind we can see that the recombination frequency is 0.18 or 18cM
Yes, the recombinant can appear more than the parental (for example, if the parental is lethal or by pure chance) but in this case I belive it is simply a different organization on the chromosomes


text:
Why do mammals have two testes?
Why do mammals generally have two testes?

My guess would be symmetry and redundancy. :-)

I guess the same could be asked of ovaries

And, you could probably ask the same about: ears, eyes, nipples, etc.

Two eyes and ears is to do with stereo receptivity, having two sensors of the same type in different places helps to gather much more information about distance and position (triangulation) of the source. One cool example of this is the hammerhead shark. It's believed that it has smell sensory organs in either end of its head. The further apart they are the better the sharks are at finding prey. It is also why predators have the eyes on the front of their head - so they work in tandem.
http://news.bbc.co.uk/earth/hi/earth_news/newsid_8376000/8376740.stm

Mammals inherited them, testes are paired way back in fish.

Else they'd all be like Hitler... Here's trivia: monotremes, oppossums, ferrets, some fish and birds have one main testis.

EvoDevo is not my field, but I will try to give you some pointers.
Mammals as vertebrates, start out as fertilized oocytes, transform into a rapidly dividing lump of cells with eventual polarity through numerous gradients of numerous chemical messengers, and form a neural tube.
The forming body is ever more segmented through the use of gradients and thresholds (see french flag model) and (dorsoventral) axial symmetry is maintained throughout development, and as such two testes represent the default development.
Therefore, it may be more interesting to ask for singular organs which require more information, and thus maintenance throughout evolution of this information. But when considering the energy requirements, the need for synchronization, the need for a separate blood supply and thus the introduction of additional faults, it is easy to see why we only have one heart.

Wikipedia; author: Zephyris, title: "The first few weeks of embryogenesis in humans", DOR: 25/09/2012
See:

Inversion
Evolutionary developmental biology

I hope this helps as a starting point.

I might further speculate that the female reproductive system has strong axial symmetry and the testes are probably following the conservative development pattern of the female reproductive system.

Short answer, they didn't. It evolved long before mammals and we just inherited it.
Becasue the testes form from the mesoderm, all mesoderm organs are bilaterally symetric or start so developmentally in chordates. Since they do not form on the midline like the spleen, they are paired by default. The testes NOT being paird would requires further explination and some evolutionary function to develop. Since testes is essential to chordate reproduction, a reduction in their function and redundancy would need a very strong evolutionary pressure to happen.

Because mammals are bilaterians, which have bilateral symmetry (as opposed to cnidarians' radial symmetry).
Bilateral symmetry means your left side should be symmetrical to the right side - two eyes, two ears, two hands, two feet, two testes.
Edit: also adding @John's comments below:

Those develop from the endoderm, which does not form paired organs, everything from the mesoderm and ectoderm, testes included is paired or starts paired. – John

The heart is a paired organ, they are just joined, the gut is part of the endoderm which is not paired. Why do we have two kidneys but one liver? – John

By your logic, why then are there not two (or one symmetric) stomachs, livers or hearts?

Vertebrates have a generally bilaterally symmetrical body-plan, but this symmetry is broken by the consistently asymmetric placement of various internal organs such as the heart, liver, spleen, and gut, or the asymmetric development of paired organs (such as brain hemispheres and lungs). - link - generally bilateral symmetry is the ancestral state, while left-right assymetries are derived features that evolved subsequently

@Domen because those develope from the endoderm, which dos not form paired organs, everything fromed from the mesoderm and ecoderm, testes included is paired or starts paired.

@sashoalm the heart is a paired organs, they are just joined, the gut is part of the endoderm which is not paired. https://biology.stackexchange.com/questions/100928/why-do-we-have-two-kidneys-but-one-liver/100935#100935

@John, I don't need an explanation – it should be provided in the answer, that's why I made the comment and downvoted this answer.

@Domen why?  paired is the default for all mesoderm organs, the stomach and liver are not mesoderm organs.

Thank you, I added @John's comments in the answer since they clarify things.


text:
Why did abiogenesis only happen once?
If the "primordial soup" theory of abiogenesis is to be believed, self-reproducing organisms spontaneously arose on Earth at least 3.5 billion years ago, surprisingly soon after the Earth cooled down enough to potentially harbor life.
It may never have happened again, however, since all lifeforms on Earth today are similar on a molecular level (DNA), suggesting a common origin.
This appears to imply at least one of the following:

Immediately after the first spontaneous abiogenesis, environmental conditions on Earth changed dramatically, making a repeat impossible.
The first organisms that arose consumed any subsequent organisms that came into being. This was suggested by Alexander Oparin, but I find it very difficult to believe since it would have to happen everywhere on Earth. Also, most single-celled organisms found today do not consume other organisms, and even where they do that does not usually lead to their complete extinction.
The common origin theory is in fact false, despite the similarities between organisms, and abiogenesis did occur multiple times in the same way.
Abiogenesis happened more than once, but only the descendants of one occurrence survived till today.
Spontaneous abiogenesis never occurred on Earth after all because the conditions never allowed it; instead, a proto-organism arrived on Earth from a planet where the conditions do (Panspermia).
The standard theory of geological history is wrong (i.e. the Earth was in a "fertile" state for much longer before the eventual origin of life than commonly thought, due to some unknown mechanism causing radiometric dating to give wrong results).

None of these seem likely to me, yet even less likely I find the idea that life arose spontaneously almost immediately (within a few hundred million years, possibly even faster) after the Earth's crust solidified, and never again afterwards.
What are the currently held theories on that matter? Can poeple provide references to relevant publications.

Are we sure that all life on Earth shares a common origin/ancestor? Even if all multi-celled life does, there may be single-celled organisms which are not related to any of these related species. Plus, we have not witnessed every location on Earth, like the bottoms of some oceans...

This question shows how any new life would have to compete for resources with existing life:  https://biology.stackexchange.com/questions/59892/is-abiogenesis-possible-today

It is so strange to hear human say "few hundred million years" are "almost immediate". Sure, it is short compared to age of earth but it is also almost incomprehensibly long time compared to anything else. Seventy years is an eon to microorganisms. What is "few hundred million years" to microorganisms?

@trysis yes, we are sure, because all organisms have the same DNA code and chirality.

As @BagIM has correctly noted, quantitative qualifiers in science are meaninful only in comparison to something else: e.g., a million years is a long/huge time compared to human lifetime, but it is of the same order as the existence of humans as species, and it is a very small time period compared to the existence of life or Earth.

It may never have happened again, however, since all lifeforms on Earth today are similar on a molecular level (DNA), suggesting a common origin.

An important distinction to make here is that all extant life on Earth has a common origin.
It's completely possible that abiogenesis occurred many times, but whatever organisms emerged as a result became extinct early on or are not preserved in the fossil record.

Immediately after the first spontaneous abiogenesis, environmental conditions on Earth changed dramatically, making a repeat impossible.

Nope. The red bands and subsequent dating techniques suggest it took a very long time for a change to occur.

The first organisms that arose consumed any subsequent organisms...

Possible, but we have solid data suggesting the first functional organisms were autotrophs. That is, they made their own food from whatever they were exposed to, and the predator/prey relationship had yet to play a major role.

The common origin theory is in fact false, despite the similarities between organisms, and abiogenesis did occur multiple times in the same way.

The Common Origin Theory - as you've defined it - is almost certainly true. DNA is a constant, as is RNA, mitochondria, etc.
That, however, doesn't mean abiogenesis couldn't have happened more than once. As I said above, the Common Origin Theory applies to extant (living) species, not necessarily all organisms that have ever existed. Species go extinct all the time.

Spontaneous abiogenesis never occurred on Earth after all because the conditions never allowed it; instead, a proto-organism arrived on Earth from a planet where the conditions do (Panspermia).

That merely pushes the question of abiogensis back a bit. Why did it evolve on another world and not Earth, then? How did it survive in space? Why was it so well suited to Earth's environment if Earth-like planets are (relatively speaking) rare?

The standard theory of geological history is wrong (i.e. the Earth was in a "fertile" state for much longer before the eventual origin of life than commonly thought, due to some unknown mechanism causing radiometric dating to give wrong results).

Estimations and conclusions have come from more than radiometric dating. We have fossil records, geological records spanning continents, and even ice-core records from the poles that both confirm radiometric dating and establish themselves as independent evidence.

None of these seem likely to me, yet even less likely I find the idea that life arose spontaneously almost immediately (within a few hundred million years, possibly even faster) after the Earth's crust solidified, and never again afterwards.

Why?

What are the currently held theories on that matter? Both random speculations and references to relevant publications are welcome.

This SE is not the place for random speculations. I don't have publications handy, so I may return and edit my answer when I have the impetus.
The most widely held theory is that all extant life, with a few possible exceptions, has evolved from a single organism that existed billions of years ago. That organism may or may not have been the only one to arise. If it was one among many variations of progenitors, we have yet to find the progenitors in the fossil or biological records. Given the extremely long time span between now and the beginnings of life, we don't expect fossil records to exist of all the organisms that existed some 3 B.Y.A. so the best we can do is speculate on what might have existed to account for what we see today.

Great answer, but what "few possible exceptions" are you talking about? I'm genuinely interested.

@ChinmayKanchi - I remember a few years back that some researchers found some (assumed) Archae members that had some surprisingly different inheritable material. Not completely new genetic material, but odd nucleotides IIRC. I haven't heard about it since, so I don't know if it was ever verified.

Right. I seem to remember that vaguely as well. Wasn't it something like a tetrose sugar instead of a pentose?

The narrative that life arose once a few hundred million years after the crust solidified and then never again doesn't add up from a probabilistic perspective. If it took a relatively short time for abiogenesis to happen once, it means it isn't an extremely rare event. But if that is the case, why have we never seen it happen again in billions of years?

@RohitPandey -- A brief of the theory of "why doesn't life arise these days" is that early Earth presented a completely different environment to what exists now. Conditions some 4 BYA were extremely different, and so different chemistry was taking place. Another possibility: New variations of life exist, but the populations are very small or well hidden and we haven't found them.

For the extraterrestrial abiogenesis question, although I agree on the first statement, we shouldn't ignore the fact that our observation methods currently favour detection of big, heavy planets quickly and closely spinning around their star, for several reasons (including access to telescope time), so it's still too soon to catalogue the Earth as a rare planet type.

It may never have happened again, however, since all lifeforms on
  Earth today are similar on a molecular level

Actually, the similarity is at the chemical level where the chirality of all known-life's amino acids are "left-handed" (see http://en.wikipedia.org/wiki/Hypothetical_types_of_biochemistry#Alternative-chirality_biomolecules). Since there is no advantage to having left-handed proteins over right handed, we would expect the chemistry in a spontaneously organism to randomly chose one or the other. So, it's 99% likely that life didn't arise more then 7 times: (1/2)^7 < .01.
Or, all the descendants of the right-handed protein life could have died-off, but this seems unlikely if there is no inherent efficiency difference.

The first organisms that arose consumed any subsequent organisms that
  came into being. This was suggested by Alexander Oparin, but I find it
  very difficult to believe since it would have to happen everywhere on
  Earth

This is where your missing a big point:

It's not necessarily eating them, or even outcompeting them once they arise, it's about cutting the legs out of the environment - eating the primordial soup of any loose complex organic matter. The places where the minimal materials for self replication machinery would have been available (since crystal-based origin of life was rejected in the 60's) would be very rare, and only on very specfic parts of the Earth...
Two of the current theories for this location, were in seafloor thermal vents, or on beaches with radioactive sand. Once life arise once in one of these niches, it will gain a strong foothold in these exact locations, crowding out those places orginal "ideal conditions" that led to the generation of life in the first place.

Ultimately, we'll probably be better able to answer this question by looking out to other planets than by un-earthing any satisfying evidence that could be found intact from 3 billion years ago.

Some people think that abiogenesis did occur more than once, and that the results of those occurrences are still with us. Paul Davies, for instance, is a proponent of what he calls 'the shadow biosphere' (here's a link to a popular article on his views: http://www.theguardian.com/science/2013/apr/14/shadow-biosphere-alien-life-on-earth).
I've seen him talk about it, and while he has pretty much zero evidence for the idea, it's an intriguing thought. His argument is basically that we're not finding the organisms in the shadow biosphere because we're just not looking in the right places or in the right way;  our discovery techniques are all biased towards our particular RNA/DNA-based life.
Note that this doesn't really put common origin in the ground, it would just mean that there's more than one common origin for each 'type' of life.
Also, it isn't necessary for early organisms to consume each other in order for there to have been multiple origins that subsequently went extinct. Our brand of life could simply have out-replicated the competition.

There are essentially two ways this can be interpreted:

Why did only one type of life evolve at the beginning, as opposed to multiple types coexisting?
Why have no other forms of life evolved much later than the one we know about (i.e. when relatively "modern" cells already existed?

I think the answer to 1) is "we don't actually know if it didn't". During the "RNA world" and earlier, it's quite possible that many self-replicating molecular machines evolved totally independently from each other and coexisted much like separate species today. However, once whole cells came along, any "free agent" self-replicating molecules that hadn't joined forces with others to make cells (or didn't evolve to exploit cells, like viruses) were likely left in the dust.
As for the answer to 2), similarly to the last comment above, once the familiar type of life was on a solid footing, it would have probably eaten or starved any competing form of life before it could get off to any kind of start. A crude new self-replicating molecule could never outgrow a highly evolved cell containing multiple already highly evolved self-replicating molecules within it.

The OP mentioned this possibility: "Abiogenesis happened more than once, but only the descendants of one occurrence survived till today."
This seems to be a viable hypothesis. Suppose that around 4 billion years ago life did arise at multiple locations on the Earth. Most theories invoke very small localized environments where very complex organic chemistry would lead to life via an intermediary RNA-World scenario. The origin of life could not have been a global phenomenon, it would take place in some miniscule pore in a rock, perhaps in a hot-spring environment. It's then hard to see why this happening at one location on the Earth would preclude the same sort of thing happening on the other side of the Earth.
So, if we assume that life originated here on Earth, then given that it started so fast after the environmental conditions would allow for it, instead of billions of years later, it follows that it must have started at many different locations on the Earth.
So, the fact that all life that exists today descends from one common ancestor, would then suggest that all the other lifeforms went extinct. But this does not have to have happened soon after the origin of life. As pointed out in Winawar's answer, Paul Davies has suggested that alternative lifeforms could exist even today and have escaped detection because we haven't been looking for them using the right methods. While that's a rather far-out hypothesis, the possibility that multiple lifeforms existed until, say, 2.8 billion years ago is a lot less far-out hypothesis, and certainly shouldn't be dismissed out of hand.
Assuming that Paul Davies is wrong about different types of life still existing today, the question is then why they would eventually have died out. After all, lifeforms compete mostly with their closest related versions, life today is very diverse and the more unrelated living organisms are the less they compete over resources.
The answer could be mass extinctions, particularly those caused by living organisms. Take e.g. the great oxygenation event. Oxygen is a rather basic chemical compound that could reasonably have been toxic to most lifeforms that would all have evolved under hypoxic conditions. So, it's entirely possible that until the great oxygenation event there existed multiple weakly interacting parallel biospheres. One of these biospheres started to produce large amounts of oxygen, destroying all other  biospheres, only narrowly escaping killing itself.

None of these seem likely to me, yet even less likely I find the idea that life arose spontaneously almost immediately (within a few hundred million years, possibly even faster) after the Earth's crust solidified, and never again afterwards.

I think that's exactly what happened and it isn't even surprising.
All the answers here assume a-priori that the rate of abiogenesis is high (since we saw life start early here). However, this isn't consistent with two facts:

We haven't observed abiogenesis again, either here or anywhere else in the universe. Granted, it would be hard to observe it if the resulting life didn't progress to a certain extent, but if one doesn't find fairies one must seriously consider at least the possibility that there are no fairies (or they're exceedingly rare).
We tried to replicate abiogenesis in the lab and to date haven't succeeded. Unlikely we will anytime soon. So, it can't be that easy.

The observations made by the OP can also be explained in the context of a very low rate of abiogenesis by invoking survivorship bias and the anthropic principal. Here, one doesn't have to assume a wildly fluctuating rate of abiogenesis or extreme extinction events (the argument still works even with those assumptions, but doesn't need them).
Note that we really are in a sweet spot where we've evolved intelligence and started thinking about expanding beyond our planet when a relatively short time is left (a few hundred million years; according to [2], all life might be wiped out in a billion years, and conditions for intelligent life will be gone sooner; also see [3]). So, if the whole process had started a few hundred million years later (not such a long time compared to the total span of time the planet has been suitable for life), no one would be around asking such questions.
Essentially, this argument is invoking survivorship bias and the Anthropic principal [1]. The idea is that abiogenesis is indeed very rare, but if it doesn't happen soon enough, intelligent life doesn't get a chance to evolve. We have one sample where intelligent life did evolve (or at least, intelligent enough  to ask such questions) and are making observations on this one sample. So we have to condition on the fact that intelligence did evolve in that sample. When we do that, the probability of life evolving "early" becomes much higher (whereas it would be close to uniform over the time-line of the planet being "fertile" for life without the conditioning and a low rate of abiogenesis). The question merely isn't taking this conditioning into account.
Another thing to note - intelligence took about 4 billion years from abiogenesis to evolve here. In reality, there will be some random distribution for the "time till intelligence". Did we get a typical sample from this "time till intelligence" distribution or did we draw a short straw? Conditioning on the fact that intelligence evolved here before it was wiped out by an expanding Sun tells us its likely we did draw a shorter straw. The typical timeline from Abiogenesis -> Intelligence is likely longer than what we saw here.

This argument addresses the Fermi paradox as well, as a bonus. And it paints an optimistic view of the future since the "great filter" becomes life starting soon enough for intelligence to evolve and would therefore be behind us.
Unless there are multiple filters. Such as self-destruction.

References:
[1] https://en.wikipedia.org/wiki/Anthropic_principle
[2] https://theconversation.com/a-billion-years-from-now-a-lack-of-oxygen-will-wipe-out-life-on-earth-156241
[3] https://image.gsfc.nasa.gov/poetry/venus/q79.html

The poster may welcome speculation, but this list does not. It is specifically a question and answer list about biology. I have edited his question.

In my view, the best we can do with questions we don't know the answer to is speculate (probably why he solicited it in the first place). Indeed, that is a very good (only?) way to find the answer. So banning speculation in all contexts might be unwise, even for a question and answer forum.

I don't see BTW why invoking selection bias is any more speculative than the other arguments here. To me, its the most likely explanation, frankly. It's a very old argument applied to other questions like "why is the universe so fine tuned for life".

@David Every reply to this is speculation, I don't see how this is any different

@0x777C — You may be right. Or not. But as I recall, at the time I edited the question it already had too many answers for there to be a hope of closing it. My aim was not to encourage speculation that was  not based, at least in part, on scientific arguments. But, whereas I have contributed answers to speculative questions on the relative times of origin of RNA, DNA and protein, I had nothing other than the obvious to contribute to this, and was only involved in site hygiene.


text:
What hydrolyses aspirin within the digestive tract and blood stream?
I have had some further thoughts after my previous question regarding the buccal delivery of medication.  The active compound in aspirin (acetylsalicylic acid or systematically 2-Acetoxybenzoic acid)  is salicylic acid (2-hydroxybenzoic acid).
I understand that the hydrolysis reaction occurs as follows within the stomach - therefore in the body it is an acid hydrolysis:

N.B. The H2O is not shown in the diagram.
However having done this experimentally I know that in the lab to ensure a decent yield of salicylic acid I had to reflux the solution for several hours.  Yet the onset of action of aspirin tablets is much faster than this.  To me this suggests some enzymatic activity, but I have no idea which enzyme this is likely to be.
To follow on directly from my previous question, if the aspirin is absorbed directly into the bloodstream bypassing the stomach then what causes the hydrolysis in the blood stream and is it the same factor that increases the rate of hydrolysis in the stomach if the medication were to be taken orally?

As a side question, how are you doing all this lab work as an A-level student? V. impressive!

@RichardSmith I'm lucky enough to be on a really obscure chemistry exam board - OCR Salters.  It's the most practically based since Nuffield bit the dust. We have to do an extended lab project over a few months, which is a great opportunity for us!

Acetylsalicylate deacetylase is the enzyme responsible for this reaction.

Precisely, the present investigation reveals that the hydrolysis of aspirin in liver, kidney and probably other tissues of
  rats is catalyzed by two highly substrate specific microsomal
  esterases, ASA esterase I and II active at acidic and slightly
  alkaline pH, respectively. The findings that ASA esterases have
  distinct organ distribution pattern and display responses to
  various inhibitors/activators that are different in many respects
  from those exhibited by cholinesterase and nonspecific carboxylesterase suggest that the latter esterases probably do not play
  a significant role in the hydrolysis of aspirin.
From:
  Ali B, Kaur S (1983) Mammalian tissue acetylsalicylic acid esterase(s): identification, distribution and discrimination from other esterases. J Pharmacol Exp Ther,226,589-594

That's an interesting one - according to the handbook of enzymes notably page 357, the enzyme doesn't seem adapted for use in the human stomach.  This suggests that it is active elsewhere - a website suggested the liver. Does anyone know if this is the case (as it would prove an answer to how the hydrolysis happens in the bloodstream)?

@RoryM See my update with a quote from the article.  Much of the drug metabolism that the body does happens in the liver anyway, after all these are just safe dosages of "toxins" that we take for our health!

However in Alexander's Answer to the linked question he states one advantage of buccal delivery as the bypassing of the liver.  As this method supposedly gives faster delivery of the medication there must be another factor at play somewhere =)

See http://en.wikipedia.org/wiki/First_pass_effect.  First pass effect is just that, the reduction in the amount of absorption when the drug is first metabolized.  One's blood volume makes many more subsequent passes through your liver.  The article also notes the kidney as a location of the enzyme, which is just as likely to revisit the same blood volume.

Perhaps I'm misinterpreting, but the 1st pass effect is one that reduces the potency of drugs.  The enzyme you mentioned above that hydrolyses aspirin into salicylic acid would be increasing potency as salicylic acid is the active ingredient, therefore the first-pass effect does not apply?

I don't want to go too far out on a limb here, because I don't know for sure, but there are probably non-specific enzymes that metabolize the ASA directly in first-pass, either by oxidation (e.g., the p450s) or conjugation (the various transferases) which render it inert.  The liver is a complicated machine, and I regret that I don't remember more about first pass metabolism.

You may want to see if Alexander wants to take a peek at this question, too.

@TomD I think you misunderstood, Rory was not referring to the pharmacodynamics of aspirin itself, but the pharmacokinetics of the removal of aspirin from the system.

@RoryM See the answer to my latest question I think it finally clears this one up.  The sublingual drugs will in fact be carried to the liver via the hepatic artery, just not initially.