text:
Weighing 2 vertical halves of the human body
I had this thought while bathing:
Assume a perfectly developed physical human body and anatomy in terms of size, dimensions and proportions. In theory, if I cut the body vertically into two exact halves from the center of the head downwards, would the two halves weigh the same?
I tend to think that the 2 halves would weigh differently, and if so, I find this quite interesting because it is strange to me that our body would - perhaps unecessarily - evolve in such a manner that requires it to balance itself on a symmetrical skeleton.
Are there any topics that touches on this... phenomenon?

My gut reaction is no as the body isn't symmetrical.  In most individuals the heart will be on the left, just as an obvious example.

I think it would also be quite impressive that given the asymmetry, the 2 halves weighs almost the same for balance.

The two halves likely do weigh approximately the same. Since the density of most tissues that are not filled with air is basically equal, it doesn't matter that, e.g., heart, spleen, and stomach are on the left and liver is (mostly) on the right. In the left/right axis, it evens out.
As for the location of the center of mass of a human: it's located about 10 cm below the navel, at the level of the S2 vertebra approximately midway between dorsal and ventral surfaces of the body (assuming that the person in question is neither pregnant nor obese).

Afterthought: CG of human body is well known, could have inferred that both halves weigh the same. Still interesting that this could happen.

Humans, like all vertebrates, belong in subregnum bilateria, a broad class of animals whose characteristic trait is having a bilaterally symmetric body plan at least in some of their life stages.
The common ancestor of all bilaterians was presumably something like a small marine worm.  For a primitive animal living in water, an obvious advantage of bilateral symmetry is that it makes directed swimming easier.  If the animal were completely asymmetric, it would have to continually exert active control over its heading to be able to swim straight.   On the other hand, an even more symmetrical animal (such as one with 90° rotational symmetry) might have trouble controlling its vertical and lateral heading separately, which could be a problem in aquatic habitats where staying at a certain depth is often useful.
(Indeed, in many ways these reasons are the same as why pretty much all aircraft are bilaterally symmetric: in the absence of active steering, we want them to fly straight and level.  That requires at least rough left–right symmetry and generally also some degree of top–down symmetry, although some breaking of the latter is usually needed both for landing and to account for the effects of gravity on flight dynamics.  We could build completely asymmetric aircraft if we wanted, they just would be harder to fly.)
As for why this ancestral bilateral symmetry has survived so well throughout the course of evolution, that's presumably both because it's so deeply embedded in the genes that control our ontogeny, but also because the basic reasons why such symmetry is useful still remain, even though our size, shape, habitat and locomotion are very different from those of the first "urbilaterian".  Even though we mostly move by walking instead of swimming, it's still useful for us to be able to walk straight without having to pay constant attention to it.  Furthermore, once we've first learned to walk (or crawl) straight, it's useful that we can also learn to run, swim and jump (and ride a bike or drive a car) straight without having to always re-learn the exact amount of control needed to maintain a given heading with each of these modes of locomotion.

Ps. To answer your actual question, I'd guess, like Rory M, that the two halves of a human body probably won't weigh exactly the same, both due to the asymmetrical distribution of the internal organs and also due to uneven muscle development.
However, the difference is quite small compared to the total mass of the human body, so that the center of mass is presumably still quite close to the body's centerline.  As I noted above, any significant deviation from that would cause issues with gait and balance.  Although such issues can certainly be adapted to and overcome with active control — after all, even people who've lost a whole leg manage to get around one way or another — they're presumably still significant enough to be selected against over evolutionary timescales, which is why our body shape remains so nearly symmetrical.

I also had this thought about the bilateral symmetry of the body and the weight distribution. I'm sure if we were to Q & A a kinesiologist about this particular query we would find that the arrangement of the organs left and right and the difference in weight muscular development left to right is off set by our arms which move in and out from our body to maintain balance. When we eat, we gain weight in the form of fat. A full belly makes us front heavy, but by leaning back we maintain the balance. I would wager that the two halves of our body are no more than ten pounds off from each other and the arms used as ballast keep us upright. Hope this helps.


text:
Negative association between habitat quality and reproductive success in birds
I'm looking for bird studies that have found either a negative correlation or no correlation between habitat quality and reproductive success.
Or in other words, bird studies that have found that reproductive success was lower in lower quality habitats. Or, that have found there was no difference in reproductive success between habitat classified as high quality and low quality.
Can anyone help?

Do you mean studies where the habitat quality was assigned before gathering data on reproductive success (i.e. based on other data sources)? Habitats where the reproductive success is low is often considered to be "poor" habitat post-hoc.

Yes where habitat was classified as low quality before high reproductive success was found

I've been part of one paper that estimates habitat-specific survival rates and population growth rate (to evaluate quality), with habitats relating to field-layer height, where there was a rather clear idea of what should correspond to "good" and "bad" habitats, see Arlt et al (2008). Habitat-Specific Population Growth of a Farmland Bird. PlosOne. Does this seem like a suitable study to your question?

Google Scholar pulls up some useful looking options

source: Stack Exchange

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

sort: votes


text:
Optimization of annealing temperature
I am trying to optimize annealing temperature for some primer pairs. I have tried optimization using cDNA, genomic DNA, Taq polymerase, phusion polymerase etc., but every time I am either getting non-specific amplification, a band of larger size than expected or no amplification. Every time I am getting a primer-dimer. Can anybody help me optimize the annealing temperature?

Posting the primer sequences and what genome they are designed against would be helpful.  Furthermore, have you double checked that your primers are in the correct orientation?

I've heard of people using single stand binding protein to reduce primer dimers.

Most PCR enzymes come with a manual (which can also be found online) that has a troubleshooting section, often dealing exactly with you problem. It may be more fruitful to first follow these steps, and include the outcome in your question.

I'm going to give this question a blind attempt, assuming you are talking about PCR (since you are talking about genomic DNA and cDNA) and not RT-PCR or qPCR, since I know very little about them. This answer is not necessarily optimisation for annealing but checking some basics and potential solutions. In my work I had to do a lot of site directed mutagenesis and genotyping and there are some important rules you have to follow in your primer design. First try to keep your primer length between 25-30 for sequencing (at least thats what I do) and for site-directed mutagenesis between 25-45 since anything above 45 bases increases the likelihood of secondary structure formation. Primer melting temperature (Tm) should be >=78 oC (Tm= 81.5 + 0.41(%GC)-675/N [with N being primer length in bases]). Also primers should have a minimum CG content of 40% and should ideally start and end with a C or G. So check your primer CG% since if its too high then it will make a few problems including increased Tm and possibility of primer-dimer formation due to CG triple hydrogen binding. This document has some nice information (http://www.genomics.agilent.com/files/Manual/210518.pdf)
In my opinion if all else fails and you are still struggling with your primers, then re-design a new primer set, if possible. Now getting back to the annealing temperature issue, in my experience for cDNA, annealing temp of 50 oC works best and for genomic DNA, annealing temp of 55 oC works best, which is about the range most people work with and I have so far had no problems. I'm more than happy to share my genomic DNA PCR cycle information with you if you wish through an edit.
Hope this helps!

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


text:
Where is the cartilage plate in this electron microscope image of the trachea?
Also how could you tell? Assuming you were shown a photo of the cartilage only, how would you identify it?

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


text:
Cartilage regeneration
Why can we not regenerate cartilage in our ear and nose, while bones and flesh can heal?
What makes it so resistant to regeneration. Can we artificially create it in the lab?

The reason that cartilage rarely is able to regenerate is that it is poorly vascularized and innervated. It doesn't have its own blood supply to deliver signaling molecules that promote regeneration and repair after injury.
There has been some recent progress on getting the body to repair and replace cartilage with lab created biogels detailed here.


text:
Why are different mesenchymal stem cells used for articular, auricular, septal nasal and costal chondrocytes?

Why do stem cell researchers use the mesenchymal stem cells shown in the table above for these specific types of chrondrocytes? Can you only use bone marrow to make articular cartilage, or are there other types of cartilage that can be made using bone marrow, if so which other types of cartilage?

Who is "they"? Why are certain cells in the body of different lineages than other, somewhat similar cells? Because that's how the body evolved. "Why" questions about evolution are rarely informative or helpful.

@MattDMo: I was referring to stem cell researchers. For example: Can you only use bone marrow to make articular cartilage, or are there other types of cartilage that can be made using bone marrow, if so which other types of cartilage?

OK, I see. Thanks for clarifying. You might want to add the ideas of your entire comment to the question so everyone understands.


text:
What are the units of enzyme activity?
I was looking at this graph of turnip peroxidase activity and I saw that they use units of 1/sec for enzyme activity. What does this unit intuitively represent and how is it calculated?

The Wikipedia "Enzyme Assay" page looks pretty good.

This refers to the turnover number (a.k.a kcat or k2) of an enzyme and is usually calculated using Michaelis-Menten kinetics. Jump to the summary at the end if you want a simple answer. If you want a more thorough answer, consider the following chemical equation:

[E] + [S] ⇌ [ES] → [E] + [P]

This says that a certain concentration of enzyme mixed with a certain concentration of substrate will first combine and form a complex depending on the enzyme's affinity for the substrate. Then the enzyme complex will generate a product depending on the enzyme's ability to convert the transition state into product. The k1 constant is the arrow moving from [E] + [S] → [ES] and the k-1 is the arrow moving from [ES] → [E] + [S] (they oppose each other). The k2 constant is the arrow moving from [ES] → [E] + [P].

Vo = [ES]k2

Vo - this is the rate that product is being formed, which can be measured.
[ES] - this is the concentration of enzyme-substrate complexes.
k2 - this is a constant value comparing the two.

This can also be expressed in terms of maximum rate:

Vmax = [E]Tk2

Vmax - Vmax is catalytic rate when [E]T = [ES] (when all of the enzyme present is bound to substrate/saturated).
[E]T - [E]T is the total enzyme concentration. [E]T = [E] + [ES].
k2 - the kcat is the catalytic constant. It is a constant indicating how quickly an enzyme can convert substrates into products. It is easily observed by this equation.

Summary
So k2 is basically an indicator of how efficiently or quickly an enzyme operates. Not all enzymes follow standard Michaelis-Menten kinetics. For example, the allosteric properties of some enzymes cause a non-linear saturation curve. Because of this, the turnover number is commonly referred to. The turnover number's units of s-1 indicate one product molecule per second, so a turnover rate of 3000 means you can create 3000 products in 1 second at Vmax.


text:
Genetic Models for Natural Selection?
My question is simple:
Given that evolution is described by random genetic mutations allowing certain members of a species to gain a reproductive advantage over others that coexist in the particular environment- I am curious- single genetic mutations do not seem to really explain complex morphic changes such as the length of a giraffes neck. Instead it appears it must be a compilation of many such mutations. So what are the statistics for mutations? How long does it really take for so many to favorably compile? How does this compare with the reproductive time of the species?

This is a good question but I’d remove / rephrase the last paragraph since it’s unnecessarily inflammatory and not actually accurate: most arguments for natural selection entirely take this into account (but it’s usually implied in mutation rates, rather than explicit).

just to clarify, evolution by natural selection is based on heritable variation that produces a reproductive advantage.  Evolution is simply a change in the allele frequency of a population over time and does not require natural selection.

The rate of mutation has been studied since the early 1900s, which is when your question was put to rest in a prescient paper by JBS Haldane (1949). Essentially the answer is that it varies a lot between organisms and environmental conditions, but for any given gene a mutation occurs once in about 50,000 sexual replications. That is equivalent to, in a human, several hundred new mutations in each person born. Impressively, Haldane's calculations have since been confirmed by a variety of other methods (e.g. Nachman & Crowell, 2000; Xue et al., 2009).
Faster rates of evolution have been recorded in other organisms, and there have been many, many studies looking at the rate of increase in sizes of the whole body or of particular organs of a wide variety of animals and plants.
For example, Azevedo et al. (2002) look at the rate of mutations affecting size (trying to select for decrease in body size) in C. elegans, and found mutations affecting size occured at a rate of ~0.0025 per haploid genome per generation.
In another example, with a result more definite regarding your question, Keightley (1998) investigated the rate of change in average body weight under conditions of selection for increased body size, over 50 generations in mice. They recorded an average increase of 0.23-0.57% body weight per generation from new mutations. That's pretty huge, and demonstrates how rapidly a complex trait can change by mutation under selection.
I wrote a small piece of python code to calculate the increase after x generations at the same rate (the formula is very simple)...
initial = 1
rate = 0.35
generations = 1000
result = initial * (1.0 + rate) ** generations
print result
>>>20.10655586861808

Thus if we assume that approximately the average rate found in the mouse study (0.35%) could be the rate at which giraffes' necks might increase under strong selection, after 1000 generations the mean neck length would be over 20 times the original length. A low estimate for wild giraffe longevity is around 20 years, thus for giraffe necks to increase around 20x might take 20,000 years. Of course this basic estimate is making a whole lot of assumptions, but the point is that rates of mutation are actually very high, easily enough to explain the diversity of traits we see in the world.
References

 Azevedo RBR, Keightley PD, Laurén-Määttä C, Vassilieva LL, Lynch M, Leroi AM. 2002. Spontaneous Mutational Variation for Body Size in Caenorhabditis Elegans. Genetics 162: 755–765.
 Haldane JBS. 1949. THE RATE OF MUTATION OF HUMAN GENES. Hereditas 35: 267–273.
 Keightley PD. 1998. Genetic Basis of Response to 50 Generations of Selection on Body Weight in Inbred Mice. Genetics 148: 1931–1939.
 Nachman MW, Crowell SL. 2000. Estimate of the Mutation Rate Per Nucleotide in Humans. Genetics 156: 297–304.
 Xue Y, Wang Q, Long Q, Ng BL, Swerdlow H, Burton J, Skuce C, Taylor R, Abdellah Z, Zhao Y, et al.. 2009. Human Y Chromosome Base-Substitution Mutation Rate Measured by Direct Sequencing in a Deep-Rooting Pedigree. Current Biology 19: 1453–1457.

wow- that's a really good answer. So these rates of mutation that are studied- in particular the Haldane paper- they represent mutations in the genome that are passed on to the offspring or just random mutations that occur in individual cells throughout the collective body?

okay i reread- nevamind the above..

Yes, they represent mutations that are passed on to the offspring.

You might have a look at the E. coli long-term evolution experiment lead by Lenski.  They've traced over 50 thousand generations of E. Coli and measured how they evolved when growing in a minimal growth medium.  Since these E. Coli reproduce asexually and do not trade genes via bacterial conjugations, the only genetic changes over time come from mutations.  Since they keep frozen samples of earlier generations, it's possible to test exactly what changed and when (and even to go back in time and rerun the experiment again).  The experimenters estimate that there were hundreds of millions of mutations during the first 20K generations.  Of those 20K, approximately 100 reached fixation (that is, where everything without those mutations died), and of those there were between 10 and 20 beneficial mutations.  During those 20K generations the fitness (measured by how quickly the population grew when introduced to a new media) grew by 70%.  Later studies have looked directly at the DNA and identified the precise mutations which lead to important increases in fitness.

Here's a paper on that experiment which includes a summary of the project and also a particularly stunning example of a trait that evolved due to a combination of more than one point mutation: http://www.pnas.org/content/105/23/7899.full

This is such a fantastic experiment. It must have been a hard slog for so many doctoral candidates endlessly curating E. coli cultures, reminiscent of Morgan's fly boys.


text:
Why are brightly coloured marine animals thought not to display aposematism?
There are many brightly coloured marine animals, such as fish, corals, sea stars, and octopodes. And yet Wikipaedia says it is thought that those colours don't serve to deter predators, while they do serve that purpose in insects and frogs. Why should bright colours not deter marine predators? And what, then, is their purpose?

Wikipaedia gives a few arguments, but some don't seem terribly strong, while others I don't quite understand:

It has been proposed that aposematism and mimicry is less evident in marine invertebrates than terrestrial insects because predation is a more intense selective force for many insects, which also disperse as adults rather than as larvae and have much shorter generation times.[24] Further, there is evidence that fish predators such as blueheads may adapt to visual cues more rapidly than do birds, making aposematism less effective.[30]

I read what may be four different arguments, or perhaps some together constitute one argument:

predation is a more intense selective force for many insects

Is this really true? If so, what causes this stronger pressure on insects?

insects disperse as adults

By this I presume they compare insects, whose eggs are often found clumped together in large numbers, with marine animals whose eggs are fertilised while floating around dispersed; but why does that make aposematism less useful for those marine animals? And aren't there also many marine animals whose eggs are laid in clumps on solid sea floors? Is this related to the supposedly lower pressure of predation from 1?

insects have much shorter generation times

That's very interesting: do they really have much shorter times between generations? At least a reference is made, but it is inaccessible. But how does that make aposematism more beneficial? Is this, too, related to 1?

fish predators such as blueheads may adapt to visual cues more rapidly

This, too, refers to a scientific source. The experiment showed that fish can quickly overcome instinctive aversion from certain colours (mainly red) in food. At least I understand this argument (although I'm not sure I think it provides nearly enough evidence).

Some thoughts: marine animals often do exhibit camouflage and mimicry successfully, cf. angler fish and harmful parasitic fish that mimic cleaner fish; could it be that there is something different about the metabolism of marine animals?; or could it be that the three-dimensional environment makes other strategies more effective, such as flight—but then how about all the floor-bound animals, and the unmoving ones?


text:
Could a fetus properly develop in micro/zero-gravity?
I suppose another way of looking at the question is: how important is gravity for the development of mammal fetuses?
And if things would go wrong, what sort of things would they be, and what would be the result?

Let me just say, it would be awesome to be the first scientist to breed mice in space. Just sayin...

There is some evidence that fetal development under zero gravity conditions might be problematic.

Wakayama S, Kawahara Y, Li C, Yamagata K, Yuge L, et al. (2009) Detrimental Effects of Microgravity on Mouse Preimplantation Development In Vitro. PLoS ONE 4(8): e6753. doi:10.1371/journal.pone.0006753

The paper is here.
These authors studied aspects of reproduction of mice in a clinostat under 10-3G. They found that fertilisation was unaffected, but that preimplantation development of the embryo was affected by the mG environment.
The introduction to the paper gives a good brief review of this area of research. Perhaps of particular relevance is this section:

In the STS-80 space shuttle mission, mouse 2-cell embryos were collected on the ground, launched into space and cultured for four days in µG. The control embryos on Earth developed to normal blastocysts, but in the space flight group, none of the embryos showed any sign of development, and all degenerated (Schenker & Forkheim, 1998) . A more reliable experiment was done on the Cosmos 1129 mission in 1979, when mature male and female rats were sent into orbit and then allowed to intermingle in a common breeding chamber (Serova & Denisova, 1982). However, none of the females gave birth, although postflight examinations revealed that ovulation had occurred. Two of the females were reported to have achieved pregnancy, but the embryos appear to have been resorbed.

Schenker E, Forkheim K (1998) Mammalian mice embryo early development in weightlessness environment on STS 80 space flight. Israel Aerospace Medicine Institute Report.
Serova LV, Denisova LA (1982) The effect of weightlessness on the reproductive function of mammals. Physiologist 25: S9–12.


text:
Terminology question: the scope of an allele in an organism
Let us consider a gene FOO with novel type foo.
If I were discussing an organism that has inherited foo in every cell during classical zygote formation, then I would ordinarily just say that the organism has foo.
If I were discussing a SNP of FOO that gives rise to foo in a tumor cell of an organism, I wouldn't say that the organism has foo, but I might say that the tumor has it.
If I were discussing a chimeric or mosaic organism in which some fraction of the chimera had foo and the other fraction had FOO, I would have to say something like "in foo-containing cells ..."
But what if I wanted to particularly draw attention to the scope of applicability of the allele in question? That is, I want to talk about the scope explicitly, rather than implicitly. How could I directly refer to the scope of applicability of an allele? Is there a single adjective that captures the concept of "This organism has foo in every cell except in rare ones where a point mutation may have occurred; it's probably been inherited during normal meiosis" and is there a contrasting term for "The organism only has foo in a particular subset of its cells and there is some other genetic process necessary to explain that."?

I have never seen a term applied to that - although there was a question on here a few weeks ago about something similar. Can't find it now though!

I've also never heard of it.  Perhaps it's best to refer to it in the context of the chronology of development (e.g., "the foo mutation happened early in development and is thus prevalent in most cell lineages in the organism")?

If I were discussing a SNP of FOO that gives rise to foo in a tumor
  cell of an organism, I wouldn't say that the organism has foo, but I
  might say that the tumor has it.

You can call it a somatic mutation. See this paper. They report such mutations in cancer.
You can use the term like this:

Carcinoma tissue had a somatic mutation in XYZ oncogene, thereby making it constitutively active.

If I were discussing a chimeric or mosaic organism in which some
  fraction of the chimera had foo and the other fraction had FOO

In this case you can say:

The organism is chimeric for gene-X, expressing variants X1 and X2

From this article:

Effects of AngII-Infusion Into LDL Receptor−/− Mice That Were Chimeric
  for AT1a Receptors


text:
Do teeth have the capacity to heal?
Could a cavity in a human tooth "heal over" or possibly fill back in?

The answer is a simple no. Cavities in the teeth caused by dental decay cannot heal. Enamel which is affected by dental decay cannot heal as they are fully formed at the time of eruption and then on only deteriorates. The deeper part of the tooth which has dentin cannot heal the cavity formation, however it can produce a protective barrier between the advancing cavity front and the pulp inside. The cementum the third mineralised tissue of the tooth cannot heal a decay cavity. Its main function is to attach the tooth to the bony socket through the periodontal fibres.

I see you're an oral pathologist, so your answer has merit. However, can we improve the answer with some explanation or reason to believe the things you say are true, other than just your testimony? I'm not suggesting what you're saying is false, I just want to be 100% convinced. I do appreciate your answer and hope you're not offended by my request. How do we know enamel cannot heal because it was formed at the time of eruption? Why can't dentin heal cavity formation? How does dentin produce a protective barrier? Thank you!

Enamel is not formed at the time of eruption, it is formed before eruption. Enamel is secreted as an organic matrix which subsequently gets mineralised by cells called ameloblasts from inside out. Enamel formation is completed before tooth eruption. After enamel formation the ameloblasts regress and are completely lost after eruption. So no further enamel formation is possible if there are no ameloblasts. Hence once a cavity is formed in the enamel it cannot get filled up with enamel.

Where as dentin forming cells are retained live on the pulpal side. So reparative dentin can form on the pulpal side and not on the cavity side to fill it up. These are well established facts which can be found in any standard book on Oral and dental histology and Oral Pathology. Feel free to ask further clarification if required.

That makes sense. Thanks so much!  I've seen reports of decayed enamel before eruption. Is there truth to this?  If so, how does enamel decay before exposed to food acids?

Teeth completely embeded in tissue cannot undergo decay as they are not exposed to plaque. However they can undergo a process called resorption under some circumstances. Rosorption of teeth are by cells called odontoclasts. In xrays these partially resorbed teeth may appear as decayed in xrays. If you can link the reports you have seen I can look at them and comment on it.

I am unable to find the text I had read before, which was making the claim that diets deficient in calcium resulted in children's teeth decaying before eruption. All I can find on the matter is this http://cyberdentist.blogspot.com/2006/11/can-tooth-get-cavity-before-it-erupts.html which backs what you've already said. I am curious how calcium in our diets affects how resistant our teeth are to decay. And how phosphoric acid in soft drinks may remove calcium from the body and promote decay.

Yes, it can be done to a certain degree.
Cementum is capable of repairing itself to a limited degree and is not resorbed under normal conditions. Some root resorption of the apical portion of the root may occur, however, if orthodontic pressures are excessive and movement is too fast. Some experts also agree on a third type of cementum, afibrillar cementum, which sometimes extends onto the enamel of the tooth.
Cementum is produced by cells called cementoblasts.
more here:
http://en.wikipedia.org/wiki/Cementum

The answer is not relevant as the question is on healing of a cavity. Root caries affect the cementum first which is only few microns thick and does not heal by itself since the cells capable of formation is no longer in relation to the caries cavity. The reference quouted does not substantiate the healing of a cavity involving cementum. Healing of a resorption site of cementum is totally diffierent and is not applicable here.


text:
Genetics: pedigree following a rare trait autosomal recessive

I have two questions pertaining to this pedigree
I believe it to be an  autosomal recessive trait.

The probability that individuals IV-1 and IV-2 would give rise to an affected individual would be:
A. 1/4 b. 1/2 c. 1/8 d. 1/12 e. 1/24
Suppose individual IV-2 was unaffected. The probability of his marriage giving rise to an affected child would be:
A. 1/4 b. 1/2 c. 1/8 d. 1/12 e. 1/24

I worked on this problem for the last hour or so and figured up question 1 to be 1/2 and question two to be 1/4. I don't feel this is correct. I feel like I am missing something. If you don't mind showing the calculations for how you came about an answer that would be greatly appreciated.

Question 1
Okay, so I'll go through my own process for you here step by step, moving down the tree.  Here's an annotated version of your diagram with my own thoughts (it's been a while since I've done this but should hopefully be accurate):

Generation 2:  As you realised, the trait is autosomal recessive so the female (II:2) has the genotype aa.  The male is considered wild type unless informed otherwise, giving him a genotype of AA.  I think you had worked all this out, but they are shown in red on the diagram.
Generation 3: Using the two genotypes of the parents from II (red), we know that all the progeny in generation III are carriers - i.e. Aa genotypes.  This is indicated for III:6 in orangey-brown.  I think you also worked this out successfully.  However in your original chart, III:7 is noted as Aa.  III:7 is from outside of the affected family and would therefore again be considered to have be wild type and therefore instead have the genotype AA - shown in purple.
Generation 4: In order to work out the potential genotypes of IV:1 we have to do a cross between the two parents III:6 and III:7 - which works out as follows:
        |          Male          |
        |     A            a     |
        |------------------------|
F       |                        |
e     A |    AA            Aa    |
m       |                        |
a       |                        |
l     A |    AA            Aa    |
e       |                        |

As you can see, there is a 50% chance of IV:1 being healthy AA and a 50% chance of being a carrier Aa - shown in green.  As IV:2 is affected, we know his genotype is aa (pink).
Generation V:  Now for answer to your first question.  If IV:1 had the AA genotype then the child could never be affected, reducing the odds to 50% immediately. Of this remaining 50%:
        |          Male          |
        |     a            a     |
        |------------------------|
F       |                        |
e     A |    Aa            Aa    |
m       |                        |
a       |                        |
l     a |    aa            aa    |
e       |                        |

50% of the offspring would be affected.
Therefore the probability of V:I being affected is $\frac{1}{2} \times \frac{1}{2} = \frac{1}{4}$

Question 2
The second question seems very odd to me.  If IV:2 was unaffected in the literal sense of the word they would be wild-type AA.  This would make the probability of them having an affected child as 0.
As this isn't one of your options, I assume they mean that IV:2 is a carrier (Aa).  We are this time therefore crossing either AA or Aa (IV:1) with Aa (IV:2).  Again, if IV:1 is heterozygous dominant (AA) none of her children will be affected.  This means the odds are again reduced by a half.  In the case that she is heterozygous Aa then the cross becomes:
        |          Male          |
        |     A            a     |
        |------------------------|
F       |                        |
e     A |    AA            Aa    |
m       |                        |
a       |                        |
l     a |    Aa            aa    |
e       |                        |

Giving 25% healthy, 50% carrier and 25% affected.
As you're looking for affected children: $\frac{1}{2} \times \frac{1}{4} = \frac{1}{8}$

If "affected" means "aa", then "unaffected" should mean "not aa", i.e. "AA or Aa". If neither IV-1 not IV-2 are affected, the offspring could only be affected if both are carriers. The chance of IV-1 being a carrier is 50% whereas the chance of IV-2 being a carrier is 66% (because IV-2 had 1/4 chance to be AA, 1/2 chance Aa and 1/4 chance aa, but we know the genotype isn't aa, thus leaving 1/3 chance AA and 2/3 chance Aa). If they both are Aa, there is a 25% chance of offspring being affected (aa). 1/2 * 2/3 * 1/4 = 1/12 = (D). Edit: Haha excuse my necromancy, was prompted by a flag.

Rory gave a good answer to part 1.  Your main problem is that you have written Aa for III-7, and that's not the right call.  III-7 is not in the family (maybe you missed that detail in the tree), so their odds of carrying a bad allele in the same gene that this family carries a broken gene in is very very small.  So III-7 is AA.
So the III-6,7 mating is AA x Aa.  That means the odds of their kid also being a carrier is 50/50, the odds of the kid passing on the bad allele to her kid is also 50/50, so the odds of V being affected are .25.  (when you have a probability question in the form of "What are the odds of this, then that happening", you multiple the probabilities to get the answer)
In Part 2, if IV-2 is unaffected, then the odds are 2/3 that their genotype is Aa, and 1/3rd that their genotype is AA.  (See the Punnett Square, and notice that you disregard the box that leads to an affected phenotype)
So for V to be affected, we need
1) III-6 to have passed on the bad allele to IV 1(50%)
2) IV-1 to have passed on the bad allele (50%)
3) IV-2 to be heterozygous (66.6%)
4) IV-2 to have passed on the bad allele (50%)
The odds of all of that happening is 1/12

From my own point of view, I think the answer to no. 1 is a 50% chance i.e. 2 out of 4. My reason is because, IV-1 could be a carrier of the trait and since the IV-2 is affected that means 2 will be affected.
No 2. For the second question, the answer is 1 out of 4, because it's obvious both (IV-1 and IV-2) would be carriers of the trait from their family pedigree, and have 1 in a 4 chance of developing an offspring with the trait.

This is rather a comment than an answer. Can you elaborate this?


text:
Why does a housecat (or other predator) play with it's food before killing and eating it? Does it make the food taste better?
I've read a couple people theorize that a cat playing with a mouse causes the mouse's body to be flushed with adrenaline before the final kill and that this adrenaline makes the meat more tender/easier to digest/more nutritious etc.
Is there any evidence to support the idea that by playing with it's prey the cat is making it taste better or easier to eat?

Animal Planet is quoting researcher Dennis C. Turner who claims this is an instinct which is supposed to tire the prey:

Cats, rather, wear down prey to avoid sustaining injuries. They're motivated by self-preservation, just like most other animals, and they know what could happen if they aren't careful. Mice and rats, for example, can deliver nasty bites that can cause injury or spread disease. Birds, for their part, are able to scratch and peck. So, what's a cat to do? Rather than playing with their prey for amusement, cats tire out their victims to the point where they're too worn down to fight back. And after that, the cats will feel better, and safer, about finishing them off, according to researcher Dennis C. Turner. So while it might look like a display of cruelty, a cat playing with its prey is just an (admittedly harsh) example of animal instinct in action [1].

Karen B. London (animal behaviorist) agrees:

Actually, the way that cats let go of and then recapture their prey is not a way for them to have fun, but rather a way for the cats to protect themselves from serious injury. Cats kill their prey by breaking the spinal cord with a strong bite to the neck. If a cat must let go of the animal in order to grab it on the neck, that cat is risking escape or retaliation by their prey [2].

Playing (not only with prey) also gives cats experience and improves their ability to make judgments [3].

References:

Animal Planet. Why do cats play with their prey? Available from http://curiosity.discovery.com/question/why-cats-play-with-prey (accessed 27.07.2014)
Karen B. London, Ph.D.. London Zoo: Why do cats play with their food? Available from http://azdailysun.com/lifestyles/pets/london-zoo-why-do-cats-play-with-their-food/article_46a97775-232d-5e56-b0ea-dd1c8782b062.html (acessed 27.07.2014)
Perfect Paws. Predatory Behavior of Cats. Available from http://www.perfectpaws.com/help3.html#.U9TLpON_tJk (accessed 27.07.2014)


text:
Effect of testosterone hormone on cell signalling and behaviour?
A steroid, testosterone was injected in female body which led to development of secondary sexual characters but these characters were not developed over night (Response was very slow). What could be possible explanation of this phenomenon

a Steroid hormones produce a slow response because they do not have secondary messenger
Slow response is due to lack of cell membrane receptors and amplification enzymes
Movement of this hormone is very slow in blood
None of the above

I think option 3 is correct because steroid hormones are hydrophobic in nature and cant be transported in the blood without the help of any carrier protein so this may be the reason but I am not sure about this..

Read the title - it is completely valid. Answer to it. Then, lastly read the body. This should be reopened because I think we know too little about testosterone hormone and its effects in cell signalling and embryology.

Steroid hormones produce a slow response because they do not have secondary messenger
It's true that steroids don't have secondary messengers because they don't need them - they can go directly into a cells nucleus and affect transcription there.  This wouldn't slow down the response by much, however.
Slow response is due to lack of cell membrane receptors and amplification enzymes
This is just the inverse of the first option, which again isn't really a cause of slowing down the response.  Steroids are amplified in that they act directly on DNA at the very first step of the synthesis pathways so don't need much amplification.
Movement of this hormone is very slow in blood
 Again I don't think there is much to this option, the difference in speed of distribution of steroid and peptide hormones is likely to be minimal

This leaves us with:
 4. None of the above
I would personally have gone with this answer.  Steroids have a long time of action because they require the new transcription of genes that they activate.  This process takes time and consistent doses are needed to maintain the effect.

It may be important to consider the developmental stage of the "female body" as well. For instance, organizational vs. activational hypothesis--injecting testosterone during a critical period during development (it can be pre-natal, or during puberty) could produce permanent changes in secondary sexual characteristics and sex-specific behaviors; however, injecting testosterone after the organized system has "crystallized" (e.g. receptors are expressed in sex-specific regions, external genitalia is fully developed) may only induce temporary changes that may not be sex-specific.
As for a "female body" to develop secondary sex characteristics with testosterone injections--if these characteristics are "female" secondary sex characteristics (e.g. increased subcutaneous fat deposition in breasts in humans), it is likely that the machinery has already been organized (e.g. more "aromatase" converts testosterone to estrogen, or the location/density of androgen receptors affects sensitivity, or there is less androgen-binding protein to transport circulating testosterone), while if the secondary sex characteristics were "male" (e.g. laryngeal prominence) the testosterone injections happened during a critical development stage and/or were chronically administered (e.g. continuous administration, daily injections...).
Phoenix et al (a review cited above) did a cool experiment that might interest you.


text:
How fallible are DNA paternity tests?
Is it possible to get either a false positive or a false negative from a DNA paternity test and what would be the likely mechanisms behind this?  For example, is it possible that a father's DNA could have changed during his lifetime enough to be unrecognisable to that of his children?

Only when the lab made a mistake and exchanged samples. Otherwise not.

Try to make the test again, in different place..

Thanks I we did take one mouth swap from one company then we did a blood test with another just to be sure. Both test came back negative.  Just confused with the similarities.

@lou It would be nice if you refrain from bringing your personal issues in the post. Just ask a neutral question.

I know. Just didn't know how to explain the situation for someone with knowledge about dna ect to help me with my question.

@lou hopefully that edit helps a bit

Discounting lab error and other kinds of human incompetence, there aren't very many things that can confound a paternity test. Normal DNA damage cannot, but there are kinds of genetic chimeras that get strange results.
Normal human DNA damage can't add up fast enough to change the results without killing you several times over, but there are a surprisingly large number of people who are chimeras.
The relevant particular flavor of chimerism is tetragametic chimerism, where essentially parts of your body are sibling-related to the rest. This occasionally is discovered during paternity testing, in one vivid instance when a woman was provably not the mother of the newborn that she had just given birth to. Technically I suppose the baby was her skin's niece.
The incidence of this was thought to be very low, but it's almost impossible to detect without DNA testing. We know the incidence is much higher than we thought, but we don't know how high.


text:
Are common eye defects inherited?
If one parent is nearsighted and the other is farsighted.
One parent developed nearsightedness later in life, while the other was born farsighted and they are both the first ones in their family to have any sort of eye problems.
Is there a possibility of their children having a perfect vision since both their conditions are the result of a recessive gene and can the probability of inheriting one over the other be assessed?

Both Nearsightedness and farsightedness are inheritable.
According to Citizen Scientists Look into Nearsightedness, 23andme blog:

Nearsightedness, a condition in which far-away objects look blurry, is
  a problem of endemic proportions — approximately 30-40 percent of
  adults in the United States are nearsighted.  And, as computers and
  cellphones (which train our eyes to focus on short distances) play an
  ever-increasing role in our lives, we can only expect that this number
  will grow. One study in the United States highlights the rising rates
  of nearsightedness. These researchers found that in the early 1970’s,
  approximately 25 percent of Americans between the ages of 12 and 54
  were nearsighted, but thirty years later that number had skyrocketed
  to 42 percent. While it’s been clear that genetics play an important
  role in nearsightedness, until this month relatively little was known
  about which genes are involved. Two large studies on nearsightedness,
  however, have recently shed light on the subject. One of these studies
  was conducted by the 23andMe research team under the leadership of Amy
  Kiefer and Nick Eriksson.
Read more at
  http://blog.23andme.com/23andme-research/citizen-scientists-look-into-nearsightedness/#ijOHfuvePBSFOm4A.99

Which types of eye disease are inherited?
Genetic factors play a role in many kinds of eye disease, including those diseases that are the leading cause of blindness among infants, children and adults.
More than 60 percent of cases of blindness among infants are caused by inherited eye diseases such as congenital (present at birth) cataracts, congenital glaucoma, retinal degeneration, optic atrophy and eye malformations. Up to 40% of patients with certain types of strabismus (ocular misalignment) have a family history of the disease and efforts are currently under way to identify the responsible genes.
In adults, glaucoma and age-related macular degeneration are two of the leading causes of blindness, and both appear to be inherited in a large portion of cases. Researchers have mapped several genes for glaucoma and are starting to identify genes involved in macular degeneration. They also are making very significant progress in identifying the genes that cause retinitis pigmentosa, a degenerative disease of the retina that causes night blindness and gradual vision loss.
Can common vision problems be inherited?
Genetics also play a role in vision problems that occur in otherwise healthy eyes. Genetic ophthalmologic researchers now have evidence that the most common vision problems among children and adults are genetically determined. The list includes strabismus (cross-eyes), amblyopia (lazy eye) and refraction errors such as myopia (nearsightedness), hyperopia (farsightedness) and astigmatism.
Can inherited eye diseases be corrected if an early diagnosis is made?
YES
Source: http://my.clevelandclinic.org/disorders/inherited_eye_disease/default.aspx
This Table gives a better insight on Causes of Myopia:

So in conclusion there isn't a chance of our children having perfect vision, they will inherit one or the other. Whether they are going to be farsighted or nearsighted is completely unpredictable but if diagnosed early there is a chance to keep the severity in check. Am I correct?

No, actually there are chances of your children having perfect vision. Otherwise you are correct.

How? Both conditions are the result of a recessive gene.

There are SNPs and Environmental factors involved too.

@Giota B: Hope this solved your question, if so, mark this as answer?


text:
Is there a program that simulates biology on a molecular level?
Is there a computer program that simulates biology on a molecular level? Software that has rules that simulates the rules of molecular-biology?

What do you mean by "simulates biology on a molecular level"? There are definitely 3D molecule viewers, as well as programs for organic chemistry mechanisms, but not something that encompasses every detail of all living processes ever.

I am currently working on a numerical model that simulates an evolving population by simulating the molecular interaction regulating gene expression.

There is a recent paper that introduced the first molecular-level whole-cell simulation.
Karr, J.R., Sanghvi, J.C., Macklin, D.N., Gutschow, M.V., Jacobs, J.M., Bolival, B., Assad-Garcia, N., Glass, J.I., & Covert, M.W. (2012). A whole-cell computational model predicts phenotype from genotype. Cell 150:389-401 DOI: 10.1016/j.cell.2012.05.044
The authors combined 28 different sub-modules of various biological processes from the literature. Each one operates at the level of macromolecules, although models them in different ways: some by ODEs, some by logic; some by agent-based approaches. If you want to fool around their code is available online and I wrote a basic introduction/summary of the paper.
Here are some related bio.SE questions motivated by that model:

Short-term Lamarckism in asexual single cell organisms
Computational/mathematical models for predicting phenotype from genotype
Macromolecule levels in daughter cells after fission

Just a very important note, seen what the OP is asking. Simulating one cell is great, but it does not in any way mean that we can currently simulate an entire organism with that same level of detail.

You might want to check out agent based modeling if you're up to programming your own model. NetLog  might be able to help you.

@RichardErickson I am not sure who your comment is directed at, but I think people would struggle to implement models like Karr, Sanghvi et al. in NetLogo. I think it is also a bit misleading to suggest that a completely novice modeler (of the sort that will be just starting with NetLogo) will be in a position to program their own model at the level of detail of Karr & Sanghvi.

NAMD is a molecular simulation software system with an extensive, active community of researchers
https://www-s.ks.uiuc.edu/Research/namd/
it has a slick visualization package called VMD
https://www-s.ks.uiuc.edu/Research/vmd/

I think this is a good answer, more useful than mine. But could you make it a bit more self-contained by saying a bit more about NAMD and maybe including an example reference where it is used in the literature? And why you think it's visualization package is particularly slick.


text:
Are there natural selection experiments that quantitatively agree with theoretical modeling?
Has anyone ever conducted an evolution experiment and quantitatively compared it to theory?  For example, has anyone ever put bacteria in a million petri dishes filled with antibiotics and calculated the number of petri dishes that should develop drug-resistant bacteria, and then compared that calculation with the experiment?
I imagine that both the experiment and theoretical modeling would be very difficult, but maybe someone has been ambitious enough to try it.

If this is possible, I'd be particularly interested in finding out what variables they took into account in their calculations.

I'm not really sure what the theoretical model would be. But really, I just wanted to say that you might enjoy reading about the Luria-Delbruck fluctuation experiment, which is tangentially relevant - see http://en.wikipedia.org/wiki/Luria%E2%80%93Delbr%C3%BCck_

The question is definitely unclear. There are tons of theoretical predictions. The vast majority of them have been tested (sometimes through experimental evolution ans sometimes through observation) but not all.

I think the closest example to this is Greg Lang's work at Princeton. His work will take a population of yeast and let it grow for 1000 generations. At each generation a sample will be kept allowing sequencing of the population at each generation.
His website is available here: http://www.genomics.princeton.edu/glang/
And some of his work has already been published here: http://www.genomics.princeton.edu/glang/papers.htm

Unless I am not getting the example you give, it seems to me that there is a classic experiment that does just what you said:  the fluctuation test or the luria-delbruck experiment
Also, this recent paper from R. Lenski's lab is a good example too.
but I am sure there must be others.


text:
Recent and good quality articles on systems biology
I'm a biotechnology student and I have to write a sort of non-experimental thesis (30 pages long) within the end of a three years study.
I'm very interested in the "systems biology" field and I'm searching good (innovative) and recent (max 3-4 years old) articles about this subject, but unfortunately I've found my research more difficult than I expected.
I'd like to focus on not immediate/easy articles and possibly containing new and promising approaches.
Does anybody have suggestions?
PS: it all started from Uri Alon's great lessons on YouTube.

Welcome to Biology SE.  Unfortunately, your question is very broad - there are many topics (not even getting to papers) that fit your criteria.  Are there particular types of techniques (or objectives) that you are interested in?

Maybe we could start with asking for a list of the most interesting problems currently being worked on in systems biology... what do you think Mattia?

Thank you for your answers. I have been broad because i'm not interested in nothing in particular, moreover I don't want to miss something (I'm ignorant in the field, mainly fascinated) that you may think very interesting. I need however that the subject has already been studied in an article. I'm willing to eventually study hard on it for fill my gaps.

I'll have a go at a short list.  This is more of a highlight and primer sort of response to a somewhat subjective question so pardon if this isn't what you wanted. I don't have paper references for all this, but I'll try to come back and add some later - I usually only have half an hour or so to write an answer so bear with me.
Synthetic biology as defined as the use of genes and promoters to engineer cells or even multicellular organisms like devices is a major category.  I like browsing the projects from the iGem Competitions.  A couple of outstanding efforts in this field are the use of photoreceptors to program E coli gene expression and the general effort to create logic and computational circuits in the cell.
A major application in systems biology is engineering cells to produce new chemical compounds or to overproduce compounds.  A classic example (sort of old, but still pretty outstanding) is the engineering of E coli to produce the antimalarial drug artemisinin at levels which would enable world wide release of the drug.  This has inspired efforts to produce fuel from algae and bacteria as well.
If you define Systems biology as being often concerned with modeling some or even all the biological processes of the cell, there are probably too many major efforts to cite, but this is just a list of some favorites.
There are lots of papers focused on flux balance analysis which models how the metabolic machinery processes and synthesizes all the scores of chemical compounds that make up a cell.
Another category of synbio tries to take the genes found in a genome and model the actions of all the genes.  One of the most exciting papers to come out in this sort of systems biology is the whole cell model of Mycobacterium genetalium.  Using data from a massive effort to characterize every gene in this very small genome, the model consists of over 20 specific models which have combined to make a very impressive simulation of the entire cell dividing.
Then there is metagenomics, which looks at the different populations of microorganisms and tries to look at how they vary with different environmental conditions. A recent paper that's exciting is the review of how different bacteria dominate in the gut of obese mice and people (several references in the link).  A tour de force in metagenomics was the global sea survey.

Thank you for your list, the whole cell model is very exciting! And pardon me for the broad question, I'll keep it in mind in the future.

I personally wish more sorts of questions like this were around more - having a good conversation about ongoing science is kinda hard to find on the internet...

I agree with you, but maybe this is not the right place to discuss of it since my answer has been closed. I'm trying to figure out what is my favourite subject, so I will ask again but with more precision.  For now I am focusing on flux balance analysis and on the cell simulation article (that has an exhaustive 100 pages long supplemental document).

This question is extremely vague, and can't have any real answer without you specifying a question or at least focus. Keep in mind, there is no high-road to research, you will have to dig in and start reading papers to gain understanding of your field. If you want help from others, you should at least take time to list the papers that you have already read and why you liked them to give readers a flavor of your interests.
To start you off, consider this Google Scholar query for systems biology since 2009. If you've read specific older papers that you've liked, for example this popular 2002 minu-survey:
Kitano, H. (2002). Systems biology: a brief overview. Science, 295(5560), 1662-1664.
Then you can learn how the field has advanced since by doing a forward search in Scholar (and restricted to 2009+). Hopefully this will provide you will some ideas so that you can ask a more precise question!


text:
Systems identification in small neural network
When analyzing data from cortex, we often try to understand what each neuron does in terms of its inputs from other neurons - a specific kind of a systems identification strategy. Most current approaches use generalized linear models for that purpose (Review article).
For very small systems like the worm c.elegans it must be possible to record from all neurons at the same time, at least optically. How well can we understand the output of each neuron based on its inputs in such simple systems? What are the best databases to ask such questions?
The reason I am asking this question now is because the human brain project that just got roughly a billion dollars in funding basically needs such data for every cell in the whole brain.

Hi Konrad. I'm also very interested in the same question. I do not know of any such data available though.

Hi Memming - Nice to see you here. I posted it here to clarify a question I sent to @OpenWorm - who may know best.

For very small systems like the worm c.elegans it must be possible to record from all neurons at the same time, at least optically.

While it is true that whole organism optical recording is technically possible in C. elegans, I'm not aware of any published work  where all neurons were identified and recorded from simultaneously and then combined with connectivity data in a systematic way.
I should note, that this isn't limited to C. elegans. Florian Engert's lab has published whole-organism recordings from zebrafish as well. At the moment, though, there are still technical challenges to work out before we get the input-output relationships you desire on a whole organism level. First off, the recordings aren't truly simultaneous, in the sense that it still takes time to build up 3D images from z-stacks. Second, the image processing to label neurons is not yet robust.  And finally, the most popular optical indicators  are based on calcium levels and thus provide only a proxy for membrane potential and furthermore they have limitations in time resolution, range and accuracy.
The field, however, is progressing rapidly and I suspect that these challenges will be overcome in the next few years.

What are the best databases to ask such questions?

There are no database yet for C. elegans neural activity,  likely because the number of groups publishing optical recordings in C. elegans is still fairly small. But as more labs pick up the technique, I think the value of a database will become more obvious to the community and the OpenWorm project is providing some well-needed leadership in this area.
Finally, I should point out that in the end we may find that neural activity and connectivity provide only one part of the story. It is likely that in C. elegans neuromodulators and other "unwired" connections between neurons could play very important roles as well.


text:
Difference between various evolutionary terms
Could someone kindly explain me the difference between Phylogeny, Phylogenetic Tree, Evolutionary Trees, Phylotype, Clusters, OTU (Open Taxonomic Units). Or if possible please do suggest me a beginner's book on that said topics.

Any evolutionary biology textbook should cover this, e.g. Futuyma's Evolution. To me, your question is too open-ended and broad, and it reads as unresearched homework.

Source of information
Understanding Evolution is a free online introductory course of evolutionary biology that will probably answer these questions.
Wikipedia will also make a decent job at answering your questions.
Any introductory book to evolutionary biology would do it.
To answer your question

phylogeny = phylogenetic tree = evolutionary tree: evolutionary relationship between lineages
phylotype: An observed morphological similarity that is used to classify a group of organisms.
OTU: An observed genetic similarity that is used to classify a group of organisms.

Both OTU and phylotype are often used for asexual lineages where the concept of species poorly apply. See more info on the concept of species here.


text:
Does a theory exist for the formation of thylakoid structure?
I'm interested in how the structure of the thylakoid forms into its characteristic highly rugose stacks of grana. What causes the thylakoid to invaginate and self-associate, albeit with what appear to be fairly large gaps in between folds?

I think I found a reference.  Most of these papers are behind paywalls - its a pretty obscure topic in biology, though not because it isn't interesting...
For those not familiar with the question, the thylakoid membranes are an organelle structure in the chloroplast, which contains all the photosynthetic machinery in the plant cell.  The chloroplast is though to be a symbiotic cyanobacterium captured to make eukaryotic plants.  Like mitochondria, the chloroplast maintains its own chromosome and some ribosomal machinery.
The stack (grana) and extended (stromal lamallae) structures of the thylakoid no doubt help optimize light/energy capture by distributing the light gathering proteins in an advantageous way.  It was previously believed that the electrostatic charge of the thylakoid membrane helped make the stacks, but this Trends in Plant Science review article (Allen and Forsberg, 2001) discusses how the distribution of photosystem (PS) I and II are more concentrated in the stroma and grana respectively.
They put forth that Light Harvesting complex II (LHC II), which gathers photons for PSII tends to cluster in a trans fashion - forming contacts with LHCII in membranes above it, specifically forming the grana stacks enriched in PSII.


text:
Does finite rate of increase depend on mortality of individuals in a population?
As written in my lecture handouts, there two main factors in the Geometric Growth Model of populations:
$R_{0}$ is the expected lifetime reproductive output. This way, for unicellulars, for example, when time between division represents life time, if there is no mortality, $R_{0}$ is calculated as $R_{0}=1*2$, where 1 is 100% and 2 is the amount of daughter cells expected to be produced as a result of the mother cell split. We also define that for this isolated incident, $B$, the amount of births is 2, while the mother cell "dies", which leads to $D=1$.
The second factor is $\lambda$, which is the finite rate of increase, which in other words means that this is average per-capita multiplication factor per one time-step.
When we measure population growth in time-steps of 1 lifetime, we can conclude that $\lambda=R_0$. We actually look at $\lambda$ as at $\frac{N_{t+1}}{N_{t}}$, where $N_{t+1}=N_{t}+B-D$(1) and $N_t$ is the amount of individuals in the populations at time-step $t$. This way we define $\lambda$ using $b=\frac{B}{N_{t}}$ and $d=\frac{D}{N_{t}}$: $\lambda=\frac{N_{t+1}}{N_{t}}=\frac{N_{t}}{N_{t}}+\frac{B}{N_{t}}-\frac{D}{N_{t}}=1+b-d$.
All fine when we deal with ideal conditions, where all mother cells divide and there are no mortalities or mutations.
But suppose we're told that only 80% of the mother cells will divide, and the remaining 20% will die without division. In this case: $R_{0}=0.20*0+0.80*2$.
What I'm trying to understand, how will $\lambda$ be affected by this? Does $\lambda$ refers to ideal conditions only, or it depends on the natural situation?
(1) We ignore Immigration and the Emigration at this point.

*It's been several years since I've worked with similar equations. The following reply is based on memory, and if anyone has a firmer grasp of the materials, please modify or answer as you see fit.
I would assume λ is under ideal conditions or as an average of whatever species you're working with. Your modified lifetime reproductive output still leaves out many variables which can affect λ. By your own words it leaves out mutations and daughter cells that are dead-on-arrival. There could also be predation or conditions where the Mother-cell produces more than one Daughter-cell, resulting in R = 3 instead of 2 and your subsequent λ also being 3. UCLA Bioengineers have actually observed up to 5 daughter cells in cancer lines.
I'm not sure what you mean by "... or it depends on the natural situation?", but ultimately reality is always more complicated than basic equations usually describe. Either B or D can increase or decrease, depending on the species, environment, and how you define t.
Your equation still produces a population increase, just at a slower rate than your ideal conditions. If you're asking if there's a specific definition for "λ" referenced in your equation, I'm not aware of any specific definition for "λ" - it's not a Constant.
Your title question - does the rate of increase depend on mortality - is ultimately "Yes." If mortality is higher than the birth rate, then you will see a decrease of the population until extinction is reached if there isn't an equilibrium or rebound.
However, most populations change at an Exponential rate - NOT Geometric. To that end, you might be interested in the r/K Selection Theory and how they operate within Exponential equations (which are similar to your Geometric equations). In short, r-Selection is the reproductive strategy of producing extraordinary amounts of offspring with a very, very low survival rate. However, because so many are produced you only need a small overall percentage of survival to maintain or increase populations. The tapeworm I mentioned above is one of the stereotypical examples. K-Selection represents species that invest additional resources into raising a few offspring, usually just a handful that are carefully watched over and raised by the parent(s) until they are capable of reproducing themselves. Humans, elephants, most birds, and larger animals in general are K-selected.
For r-Selection your B and D will both be very high, and for K-Selection both B and D will be low. However, both will result in a positive λ simply because it's all about the ratios.

Thanks for your answer. I will look into r/K Selection Theory.

r/K selection is just as relevant for populations with discrete growth. However, the whole concept of r/K selection has also been challenged - for an overview see Reznick D, et al. 2002. r-and K-selection revisited: the role of population regulation in life-history evolution. Ecology, 83 (6): 1509–1520 and this nice blogpost Oikos blog: Zombie ideas in ecology: r and K selection.

The same relationship still holds, and $\lambda$ just describes the finite population growth rate under a particular set of conditions. 'Ideal' conditions (whatever that means) are not implied. Generally you can write: $\lambda = e^r = R_0^{1/G}$, where $G$ is the (average) generation time. However, $r$ (the instantaneous/intrinsic rate of increase) is not really relevant for an organism with discrete reproductive events (i.e. geometric growth)
So for your second example where $R_0$=1.6, assuming that $G$=3 timesteps, $\lambda$= 1.169. However, as hinted above an exponential model is generally a better fit for unicellular organisms.


text:
Online repositories of scanning electron microscope photographs?
I have looked at every single Wikimedia commons photo in the category 'scanning electron microscope'. Unfortunately, I could not find any other repositories of such photos, but I would readily look at every single photograph there as well. It strikes me that such repositories are also bound to be useful to biologists and biology students. A simple Google search did not yield much. Can anyone help out?

Are you looking for images for your personal use, CC or similar licensed images or commercial photos? =)

@Rory i'm looking for anything and everything. what people have posted so far is great.

micrographs, not photographs. Photons are not involved in the generation of SEM micrographs (well, they CAN be for some techniques, but those are afaik mostly used to study certain mineral deposits etc.).

First off I'd like to reccomend the University of Dartmouth's publicly available collection located here.  They have both SEM and TEM images of a wide range of organisms and cells from algae to see urchins through everything from cholera to mammalian cells.  Images are high quality, fully captioned and properly attributed.
I'm a little confused as to the problem you're having with google - see my original comment on your question.  However I have looked at the photos of Wikimedia Commons in the SEM category and see that they are either images taken with, images of SEM Microscopes or technical drawings regarding their function.  I assume that you're looking for the images taken with SEM.
I was able to find a great number of similar images to those in the commons with a Google Image search - I read above that you were having problems with this approach so perhaps try the search term "SEM images" in image search (or this search to avoid duplications from images you have already seen on Wiki Commons)?
Examples found on just the first page:

thanks for those recommendations. the trouble with google image search is that it doesn't search everything, doesn't know about everything -- and how can it? not everything has top-down categorically descriptive text attached. there's just no way to find out about repositories of images like the ones linked to here without asking people.

I know exactly where you're coming from, hope Dartmouth helped though =)

David Orloff's The Cell – an Image Library has thousands of SEM images.

very nice. i have a hard time deciding whether or not i like the dartmouth images better or i like the cell images better, and that's an excellent predicament to be in.

Have a look at:

XTALENT Image Gallery, more than 600 images, last updated in 2006, though.
Dennis Kunkel Microscopy, Inc., "scientific stock photography library of light microscope pictures and electron microscopy images featuring science and biomedical microscopy photos".
Iowa State University SEM library, includes pictures submitted by students from around the state of Iowa.

Take a look at my website which has a section called Images.  http://www.hssemgroup.com/
There are more than 13 sites listed which have hundreds of SEM images posted

Specifically http://www.hssemgroup.com/students-enjoying-their-sems/resource-urls - looks like a very helpful resource.

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


text:
From inflammation to sickness and depression: when the immune system subjugates the brain
Recently, some research, for example this article has proposed that inflammation can cause innate immune cells to produce pro-inflammatory cytokines that act on the brain to cause sickness behaviour.
My questions are:
(1) What medication would potentially help to reduce the inflammation? I am not a biology expert so I do get a little confused reading the research articles.
(2) What are cytokines in laymen's terms? Are they the same as histamines which cause allergies?

Cytokines are essentially signalling molecules of the immune system. Broadly speaking these can be classed as pro- or anti-inflammatory. Pro-inflammatory cytokines promote inflammation, and anti-inflammatory cytokines inhibit inflammation.
Inflammation (again, broadly speaking) is associated with the 'innate' immune response - this is the immediate response by neutrophils and macrophages (among others), and these cells release a variety of molecules designed to damage cells around them. This is great if those cells are bacterial, or damaged host cells that need removing, but not so great if that is 'normally' functioning tissue.
Aging is associated with increased systemic inflammation - i.e. a greater proportion of pro- to anti-inflammatory cytokines. The causes of this aren't entirely certain, but it could be that the adaptive immune response (i.e. the memory T-/B- cells) is not as effective in older ages so the innate response is more important, or that it is just simply left 'unchecked'. Either way, the result this that the pro-inflammatory response can end up damaging host tissues, including the brain, without the corresponding repair instigated by anti-inflammatory cells/cytokines.
Any anti-inflammatory medication (e.g. aspirin, ibuprofen, or glucocorticoids) will, in theory, reduce inflammation, but by suppressing the immune system the risk of infection naturally rises, and there may be unforeseen consequences to prolonged use (the immune system does a lot more than just fend of bacteria - e.g. it is essential for tissue maintenance and regeneration), so I am by no means suggesting the use of anti-inflammatories to protect brain function!


text:
Regarding TIMP and MMP enzymes
Are there substances that can promote TIMP enzyme production, or MMP enzyme production or supression in tendons?
Are there medical tests that measure quantities of MMP and TIMP enzymes in tendons?

For your first question
Both enzymes, are components of Epidermal growth factor receptor (EGFR) signalling pathway.
MMP is a matrix metalloproteinase, that triggers EGFR signalling, this can be done by a mechanism called transactivation

So, A signal from G-coupled receptor, or cytokine receptor could activate the cleavage of MMP,  then MMP converts to a ligand for EGFR activation
For example Angiotensin II type 1 receptor (AT1R) and type 2 receptor (AT2R) which are GPCR, there are evidence for crosstalk with EGFR, look for this paper. This could be linked with hypertension or inflamation. Also cancer, could trigger EGFR receptors by NMP's.
And finally tissue inhibitors of metalloproteinases (TIMPs) are the negative regulator of MMP's
This are only an overview of the whole biological process involving MMP, so I think there is no single answer to your question, but you can delimit the topic for a specific disease, and look for papers at google scholar.

Did you mean to make this community wiki?

Yes, because I do not have, the complete answer, and if someone could help to complete that or have more examples, can enhance the reply, I think this is a very interesting field to research. I'm finishing my MSc thesis in signal transduction, for a model like this.


text:
Why is rabies incurable?
I'm still not sure about the mechanics that lead to rabies being incurable. I know that it can be treated before any symptoms show up, but why is it that once symptoms show the person is a dead man walking?

I understand what you are asking, but I think the wording is a bit odd. There is not a mechanism that renders rabies uncurable. We simply have not managed to create a cure yet.

This is because rabies is a viral infection of nervous tissue that propagates through peripheral nerves into the brain and causes brain tissue inflammation (encephalitis).
As long as the virus is in the brain there is no way to get rid of it. The main trade-off here is that everything that would kill the virus will be as (or even more) aggressive against the brain tissue, and impairment of the latter will lead to really heavy deficits in vital functions like breathing and thermoregulation.
The first manifestations of rabies are those due to brain damage. This means, the virus is already there and the brain is already fatally damaged.

Ok, so the virus is already in the brain tissue if treatment isn't started. Thank you.

It may actually be curable, as shown by success stories involving the Milwaukee protocol in which the brain is effectively shut down to allow for the immune system to eradicate the virus.  In most cases, however, it is fatal once symptomatic.  Note that the Milwaukee protocol boasts an imporessive (sarcastic) survival rate of under 15%

Interesting! But I can't see it being adopted with <15% survival (although this is better than 0% if no treatment is administered)! But work will undoubtedly continue.

Also, even if you survive, you'll likely still have suffered permanent brain damage.

It's a small price to pay, in most cases.

The consensus among doctors and researchers is now that the Milwaukee Protocol not only only useless, it's worse than useless. E.g (one example of many)  "The recommendations made by the Milwaukee protocol warrant serious reconsideration before any future use of this failed protocol." --Critical Appraisal of the Milwaukee Protocol for Rabies: This Failed Approach Should Be Abandoned

I couldn't get that article through the paywall, so I wanted to add this non-academic article which explains some of the problems with the Milwaukee Protocol.


text:
Recommendation of a comprehensive book on the history of medicine
I was wondering if somebody could recommend a book on the history of medicine, be it comprehensive or an introduction to the history of medicine. I know there are a lot of medical books that cover this subject, but given that I have a limited amount of time for reading I was wondering which book would make the best use of my time.

While it's not meant to be a history of all of medicine, I thought the The Emperor of All Maladies touched on a good deal of the history as the author took us through how cancers were diagnosed and treated since long ago.
Great book, that was.

I enjoyed "Doctors: the biography of Medicine" by Sherwin Nuland
It is not comprehensive, but covers the major eras of medicine.
Im sure there are many others.