Why is some scat in the form of little pellets?

According to this article:

The material that cannot be broken down any further, such as
indigestible fiber, passes directly into the large intestine.  Here
water is reabsorbed and the material is passed, making up the round
droppings you see in your rabbit’s cage.  This indigestible fiber is
important in the diet of the rabbit as it helps to stimulate
intestinal contractions, which keeps the chyme moving through the
gastrointestinal tract.

While this article is specifically about rabbits, all herbivores require high quantities of fiber in their diets. Ruminants such as deer have different stomachs, but it is the large intestine, which is commonplace, that these pellets are formed. Fiber tends to clump together (either because the strands are attached or intertwined), and contractions in the intestine as the material is dehydrated cause these clumps to roll around similarly to pebbles in a rock tumbler, causing them to form round pellets.
Carnivores and omnivores have (and need) less fiber in their diets, so this phenomenon is not present in their feces.


How to determine continental ancestry group (race) with transcriptome data obtained with RNA microarray?

If you can call genomic variants from your data, depending on your coverage of the genome, you should be able to map ancestry. For example, if you have sequencing reads, you can align your reads to a reference genome and then call variants using existing pipelines.

Once you have variant calls, you could use ancestry-informative markers to infer the ancestry of your sample directly.

Or you could use existing software to map the ancestry of your sample in relation to other samples of known ancestry, using a program like ADMIXTURE, STRUCTURE, EIGENSOFT, or just principal components analysis. For reference samples, you could use a publicly available data set like HapMap 3 or the Human Genome Diversity Project.


Short answers:

These insects live near water or marsh areas so that's where you can get them from. This is because many species of this group has larvae that are aquatic or semi-aquatic.  According to wikipedia:

  The adults drink dew and nectar.

And it is their larvae that either prey on or become parasites of gastropods.

In this article the following is stated:

  (...) Sciomyzidae is of interest from practical viewpoints because of their potential as biocontrol agents of aquatic snails carrying diseases (e.g. schistosomiasis and fascioliasis) and terrestrial, pestiferous snails..

So the answer is yes, they might be fit to use as biological pest control, yet they may not be suitable against all species. Details of their life cycle and their biology can be found in the linked article or in this book:
https://books.google.hu/books?id=vqE1AMIj-HUC&pg=PR16&lpg=PR16&dq=Sciomyzidae&source=bl&ots=pCVJJUu2cb&sig=M1F8GhR51VI1Y62htF7eX0kNpfo&hl=hu&sa=X&ei=AF0uVf_tKI3taNLhgIAL&ved=0CFgQ6AEwBzgK#v=onepage&q=Sciomyzidae&f=false


Is there interphase between meiosis I and meiosis II?

The technical name of this brief "interphase" between meiosis I and meiosis II is interkinesis.

Interkinesis is normally short (it may not even happen) and it's not divided in G1, S or G2, mainly because there is no DNA duplication, which defines the S (Synthesis) phase.

Source: A Glossary of Genetics and Cytogenetics: Classical and Molecular


Do death rate and birth rate become equal at replacement fertility rate?

The transition to stationary populations is between stage 4 to stage 5 in all exemples of the DT model that I've seen. Not between stage 3 and 4. This is also what is being implied in the figure that you've included. In your link they also write:

  Countries like India in the third phase of demographic transition have fertility rates that have declined significantly from previously high levels but have not reached the population-stabilizing "replacement level" of 2.1 children per woman.

This is not saying that countries reach the replacement level 2.1 at the end of stage 3.

The same stages are also described at the Wikipedia page on DT and at populationeducation.org.

So you are correct; at replacement levels, populations shouldn't increase and the net growth should be zero.


How to differentiate male and female mosquitoes at pupal stage?

Male and female pupae are consistently slightly different sizes. This isn't particularly obvious to look at them, but allows them to be sorted mechanically by using two sheets of rigid, waterproof material (aluminium, glass or acrylic) fixed at a slight angle to each other, and washing the pupae down between them until they get stuck. The pupal sorter in most common use is described in this paper and you can buy one commercially here:

http://johnwhock.com/products/laboratory-equipment/larval-pupal-separator/

I think I've seen a video of one in use at Virginia Tech somewhere online but I can't find it right now; I'll edit it in later.


Why isn't life expectancy normally distributed?

The histogram you show isn't a distribution of age-at-death for individuals, it's a distribution of life expectancies for different countries.  The post you link takes data from a table on the Wikipedia page List of countries by life expectancy.  Interpreting the histogram you posted, we see average life expectancy seems to hit a wall around 85.  This does not mean that individual human life span is not normally distributed.
Excluding deaths at infancy, the peak of the death rate curve appears to be at about 88 years for women in the United States in 2014, as seen in a blog post by the The Max Planck Institute for Demographic Research:

Lifespans are increasing and becoming more similar: While life expectancy of US women rose by almost 19 years between 1933 and 2014 (from 62.8 to 81.3 years), the variance in the distribution of deaths over age shrank by ten years. Data: Human Mortality Database © MPIDR


Length differences between physically interacting proteins

At least in a human protein interaction network, it appears that proteins indeed mostly bind to proteins of similar sequence length. Consider the figure below, based on analysis of a human protein interaction network from the Protein Interaction Network Analysis (PINA) platform. In the data set, the median relative protein size (the largest amino acid sequence length divided by the smallest in each interacting pair) was 1.9, the maximum value was 293.6 and the 99th percentile, which is the cutoff for the plot, was at 15.2.

Edit: As per stords comment below, you get essentially the same result for a random network:

In this case, the network was generated by picking two proteins at random from the original network, creating an interaction between them, and repeating until the random network has the same number of interactions as the original.

Immediately, it might look like the PINA PIN is dominated by random interactions. I would run some network analysis to determine its characteristics, but seeing as it's a rather large network it would take more time than I have right now. The results are similar for two additional networks with interactions in Saccharomyces cerevisiae and Caenorhabditis elegans respectively downloaded from PINA. Note that all three networks have been constructed from databases with varying levels of curation (See the original publication for PINA:  http://www.nature.com/nmeth/journal/v6/n1/full/nmeth.1282.html). As such, many of the interactions might not be biologically meaningful.

Taking into account the above, you might want to define "interacting proteins" more precisely. One might expect that a better curated network only containing interactions with a known function or effect might give a different picture. However, using a more strigently constructed human "functional interaction" network published by Wu et al. (http://genomebiology.com/content/11/5/R53, FIs_043009.txt in Additional file #3) still gave a similar result.

Method: I made a Python script to calculate the relative amino acid sequence lengths for all interactions in a human protein-protein interaction network (PIN) available from PINA ((http://cbg.garvan.unsw.edu.au/pina/interactome.stat.do). The network file is located at: http://cbg.garvan.unsw.edu.au/pina/download/Homo%20sapiens-20121210.sif. PINs for other organisms are also available at the same site and many other places. The script can be used with any PIN in SIF format using UniProt identifiers.

The script can be downloaded here: https://github.com/jarlemag/misc-bioinformatics/blob/master/ProteinInteractionNetwork.py

The most time-consuming part was downloading the sequence lengths from UniProt. To avoid having to do that, the protein sequence lengths can be saved to and loaded from a text file.  The list of protein sequence lengths is here: https://github.com/jarlemag/misc-bioinformatics/blob/master/protlengths.txt To create the figure, place all three files in the same directory and run the script using Python 2.7.

Keep in mind that the PIN data may not be entirely reliable.


Those are names of alleles involved in the ABO blood group system. The “I” stands for isoagglutinogen which is an antigen that causes agglutination of blood cells when reacting with a specific antibody (an isoagglutinin).


It's an example of SYMBIOSIS

Clownfishes(Amphiprion ocellaris) are never found without an anemone as they have this obligate association with them. Although they can survive without them, but studies show they are much more healthier with than without.

This association is more of a survival necessity. These anemones are actually toxic and the fish is resistance to it. If being attacked they will get inside these and the attacker might be stung with this actinotoxin.

Also,

  The presence of an anemone is also essential to reproduction of the
  fishes: their eggs are laid beneath the oral disc overhang of the
  anemone, where they are tended by the male.

Source:

Wikipedia on Sea anemone
INTERACTIONS BETWEEN FISH AND SEA ANEMONES
Clownfish and its mutualism relationship with anemones


What concentration of table salt is needed to kill bacteria in sweaty gym clothes?

Short answer
Toxicity of salt depends on contact time. 50 g NaCl per liter kills nearly all bacteria in 2 days. 100 g NaCl/L may do a quite thorough job in 30 minutes.

Background
Body odor is caused by bacteria that feed on the fluids produced by the apocrine glands, mainly present under the arm pits and other areas with abundant hair follicles. Bacteria in the skin feed on the products of the apocrine glands and convert it into odorous compounds. Skin microfauna includes Staphylococcus, Micrococcus, Corynebacterium, Dermabacter and others. As pointed out by others in the comments, treating your cloths against bacterial growth may not be the most efficient approach, as the bacteria are residents of the skin. Nonetheless, the following studies addressed the antimicrobial effects of salt.

A study using the gut bacterium E.coli showed that survival in 5% NaCl (50 g NaCl per liter H2O) was <0.01%. In 2% NaCl survival survival was 8%. The contact time was 48 hours (Carlucci and Pramer, 1958).

Another study examined the effects of salinity on E. coli using a shorter contact time of 30 minutes, and concluded that 10% salinity killed 80% of organisms (Somani et al., 2011).

Sea water, which has a salinity of about 3.5% contains low numbers of bacteria (Carlucci and Pramer, 1958), suggestive of toxic concentrations of NaCl, the major salty constituent in sea water.

Although E. coli has been associated with skin fauna and body odor, I must note that Gram negative gut bacteria as used in the two studies above may not be representative of the mainly Gram positive microfauna found on the skin (Strauss & Kligman, 1956).

References
- Carlucci and Pramer, Am Soc Microbiol (1958)
- Somani et al., J Eng Res Studies (2011): 40-43
- Strauss & Kligman, J Invest Dermatol (1956); 27: 67–71


What is a good set of notes to study human's eye mathematically?

Mathematical models of the human eye

Fluid mechanics

Mathematics of Eye

Physics of blinking
Thin layer approximation (lubrication theory)
Aqueous flow in eye chambers
Tonometry

Those two links provide quite a sufficient description of how to mathematically describe/analyze the human eye. It seems that you need to be fairly familiar with (at least) differential, integral and vector calculus in order to competently study the eye, mathematically. If you can get through (and understand) the fluid mechanics then you'll be well off.

And as for practice problems, aside from the examples in those links, I'm not sure you'll so easily be able to find sets of mathematical practice problems that specifically describe the eye. Or at least, I wasn't able to find any such  repository.


Gel electrophoresis after RNAse treatment

The question is a bit vague in some important parts, so I'll have to make a few assumptions about what the authors likely meant.

RNAses are enzymes that degrade RNA. There are a few different ones that lead to different kinds of degradation. The type that you would use in an experiment like this is an RNAse that completely degrades RNA. The purpose of this is to be able to distinguish RNA from DNA. So whatever is left after the RNAse treatment is DNA, and the bands that vanished are RNA.

If you isolate nucleic acids from liver, the major DNA part would be genomic DNA. The major RNA components would be mRNA and rRNA. Genomic DNA is huge compared to mRNA and rRNA. In gel electrophoresis of nucleic acids, the bands that move further are smaller nucleic acids, and the bands that move less far are larger nucleic acids. So the band on the left in your example is likely genomic DNA, and the band to the right is mRNA or rRNA. After RNAse digestion only the left band should remain, which is answer A.


Why do many DNA solutions contain additional compounds?

DNA in pure water.
The only time that nucleic acids would encounter pure water would be in a laboratory setting--for example after an oligonucleotide is synthesized in vitro, the protecting groups are removed from the reactive atoms in the finished sequence and the final product is cleaved from the supporting matrix.  At that point you can lyophilize (freeze dry) the ammonium hydroxide solution, and resuspend the single-stranded oligo in pure water.
Additional compounds enhance heavy oligomer solubility.
However, as noted in the comments, nucleic acid solubility, particularly high molecular weight DNA, like genomic DNA,  is enhanced in solutions with dilute monovalent cations. 10 mM TrisHCl, pH 8.0, 1 mM EDTA suffices for almost every application. The EDTA inhibits any errant DNAses, and also slightly inhibits microbial growth.
Compounds act as pH buffers.
Tris is not the best biological buffer but has high solubility and is relatively cheap and stable. If the solution becomes too basic the DNA strands will melt, and if the solution becomes too acidic the purines will start to deaminate.
DNA never experiences pure water in biology.
From the moment that DNA is synthesized in a cell until that cell dies and its DNA is ultimately degraded, it does not encounter a pure water environment.


Unless you're specifically targeting genes involved in the physical morphology of the cell, I doubt you would find any differences with CRISPRed vs non-CRISPRed cells that is measurable via AFM.

Perhaps you should instead target genes known to contribute to the structure of the cell wall, which I would expect to be the dominant material contributing to the Young's modulus. Since you mentioned GFP as a tool for selecting for "successful" cuts, it might be worthwhile looking into generating a multiplex plasmid that allows you to target several loci with a single construct. Such kits are available on Addgene and contain associated publications and manuals on how they can be used.

So to summarize, no, I don't think there is anything physically different about cells that have been CRISPR treated compared to a control group. If you did want to use CRISPR to effect a knockout of the fluorescence in the competent cells you described and alter the cell mechanics, you would likely have to generate a multiplex CRISPR plasmid with multiple gRNA cassettes for both GFP and perhaps some gene involved in cell wall formation. Keep in mind that your efficiency percentage is compounded with each new target in the same multiplex – instead of a single cut being deemed successful, you will have raised the bar to 2 cuts being deemed successful without doing anything to improve the efficiency of a single cutting event.

Hope this helps, and I'd be happy to discuss this more.


Negative value on linear gene expression in microarrays

I'm not personally familiar with Illumina arrays, but I can give some notes here.  This link is a paper which describes the array quality controls specifically. This presentation describes the calculation of the intensities in bioconductor.

The answer is yes: you will find negative numbers sometimes.  They should be rare.  The Intensities numbers from a scanner which essentially takes an image of the bead fluorescence on the glass slide and tries to subtract a background signal.

The background is the typical level of signal you see on a bead with no sample DNA bound to it.  You will get some pixels lighting up a bit even there.

In expression microarrays, this is not a perfect system as each bead has a different nucleotide sequence on it.  Each bead has a specific DNA sequence has non-specific binding which is pretty much unique on the slide.  That is to say, the oligomer on the bead might bind strongly to DNA from your sample which is not its reverse complement to varying degrees.

I think what happened is that there will be a handful of cases you can find a bead which has less fluorescence than the background controls on the slide.  It's possible that the probe has a design flaw but I would generally assume that the negative number means that there is no detectable target cDNA in the sample for that oligo.

I probably wouldn't convert the number to a zero, but you could probably justify it to yourself in some cases.  Most difference experiments are the logarithm of the ratio so zero is not a great number in those cases.

@Luke 's comments are well said.

I think that negative values can still represent signal because of the variance of sequence-dependent effects for the purposes of scaling, and difference experiments.  But I'd tend to think of them as zero signal in any case.  There are probably genes which express at or below detection threshold all the time, which is not zero information, so the number has some value.


Epistasis: Why should a recessive allele be a hypostatic gene?

In the context of this textbook, m is simply an allele that codes for a non-functional protein product. The protein product of m is incapable of converting magenta pigment into blue pigment.


What is "irrational" drug/molecule design?

"Irrational" design in these papers refers to combinatorial mutagenesis, which is put forward as the alternative to "rational" protein design.

Rational design involves using existing information about a protein to choose residues to mutate.

From Nixon et al.:

  Alteration of function by rational approaches can be achieved through single-point mutation, exchange of elements of secondary structure, exchange of whole domains, or generation of fusion proteins

Whereas irrational design uses random mutations to gain insight into the functional capacity of specific residues or domains, which may then be further manipulated by rational approaches.

From Tobin et al.:

  ‘Irrational’ protein design using directed evolution methods relying on entirely random mutagenesis techniques has also had its successes, particularly in cases in which sequential rounds of mutagenesis have been pursued.


Microarray gene expression matrix format

The RAW signal values from each microarray are transformed and processed to give you normalized signal values for each microarray. The transformation and processing steps are standard but different for each manufacture. Each manufacture uses a different method/technology to obtain signal values. Thus, signal values are not directly comparable between different microarray technologies.

Experiments using different technologies might get similar RANK of results but the normalized signal values will be different. You can have a look at GEO for a list of datasets and commonly used technologies. I have no clue what you mean by applying classification (are you looking to cluster the results from different microarray technologies run on the same experiment? I'm pretty sure a comparison of microarray technologies has been done before/already)


The effect on the efficacy and potency of a non-competetive antagonist binding to the active site of the receptor (dose-response curve)

This is a tough question. I was reading this paper Patrono, C., et al. "Clinical pharmacology of platelet cyclooxygenase inhibition." Circulation 72.6 (1985): 1177-1184. and they seemed t mention this paragraph in the introduction.

  Platelet Cycloxygenase or prostaglandin (PG) H synthase (i.e., the
  enzyme that converts arachidonate released from membrane phospholipids
  into PG endoperoxides) is the target of several antiplatelet agents
  that can reversibly or irreversibly block the activity of the enzyme
  by competing with the substrate or permanently altering the active
  site, respectively.Such drugs belong to the class of so-called
  nonsteroidal anti-inflammatory agents (e.g., indomethacin, aspirin),
  but also include a uricosuric agent, i.e., sulfinpyrazone.

So we have to look for  DRC of a NSAID to say COX. Now I was unable to find a good DRC for aspirin (If you find it, let me know in the comments below. I would love to take a look at it). But I did find DRC for other drugs that inhibit COX.

It led me to this paper Walker, M., et al. "A three-step kinetic mechanism for selective inhibition of cyclo-oxygenase-2 by diarylheterocyclic inhibitors." Biochem. J 357 (2001): 709-718. which described the inhibiton of COX2 by a NSAID called celecoxib.

  The inhibition of COX isoenzymes by NSAIDs generally conforms to one of three inhibitory mechanisms: simple reversible inhibition, as demonstrated by ibuprofen ; time-dependent reversible inhibition, which includes both weaker binding inhibitors, such as naproxen , and tight binding inhibitors, such as indomethacin and meclofenamic acid ; and irreversible covalent inhibition, as demonstrated by aspirin  and o-(acetoxy-phenyl)hept-2-ynyl sulphide ('APHS') . Most of the traditional NSAIDs display similar inhibitory mechanisms against both COX-1 and COX-2 , and are relatively non-selective. However, COX-2-selective diarylheterocyclic inhibitors demonstrate distinct inhibitory mechanisms for the two isoforms . For example, celecoxib  has been reported to be a reversible competitive inhibitor of COX-1 while demonstrating time-dependent irreversible inhibition of COX-2.

Considering the highlighted statement, I think you can consider the COX1 curve as a standard competitive inhibition and COX2 as non competitive inhibition. The resulting change is essentially the curve shape itself (being shifted to the right).

The DRCs were reported here: Tacconelli, Stefania, et al. "The biochemical selectivity of novel COX-2 inhibitors in whole blood assays of COX-isozyme activity." Current Medical Research and Opinion® 18.8 (2002): 503-511.

Interestingly the second paper (By Walker) also described how (the authors proposed) the binding occurs. A very interesting read.


Which side of the DNA helix is used for describing SNPs?

It is described with respect to the reference sequence. See the VCF format description.


How can human infants express chymosin with only a pseudogene at their disposal?

TL;DR: Chymosin is similar to pepsin and I couldn't find any evidence of functional/expressed chymosin gene in human genome.

It seems like a common misconception that chymosin is functional in humans. Already in 1940s it has been shown that rennin (aka chymosin) is absent from "gastric juice" in adult humans.

Genetically there is only pseudo-gene for chymosin, as wiki and other sources state. At the same link that leads to chymosin gene page you can find some literature on cloning and structural analysis of chymosin pseudo-gene.

If you use BLAST for finding homologous proteins to chymosin from, say Bos  mutus (aka yak), you can find that in humans closes sequence can be attributed to pepsinogen and similar proteins. Which very much might mean that what is called chymosin in other animals is pepsin in humans, or there is some convergence/divergence which eliminated chymosin in humans. But this is only a speculation.

You can try to scan Google scholar for more sources.

NB link to BLAST search will expire in ~24 hrs.


Do human neurons in a petri dish do different things from chimpanzee neurons

I have came across several studies indicating large similarities between chimpanzee and humans. A study by Bianchi et al., 2013 used immunohistochemistry, electron microscopy, and Golgi staining to characterise synaptic density and dendritic morphology of pyramidal neurons in primary somatosensory (area 3b), primary motor (area 4), prestriate visual (area 18), and prefrontal (area 10) cortices of developing chimpanzees (Pan troglodytes). They found that synaptogenesis occurs synchronously across cortical areas, with a peak of synapse density during the juvenile period (3–5 y). Moreover, similar to findings in humans, dendrites of prefrontal pyramidal neurons developed later than sensorimotor areas. These results suggest that evolutionary changes to neocortical development promoting greater neuronal plasticity early in postnatal life preceded the divergence of the human and chimpanzee lineages. This study however does note that

  Despite sharing these neurodevelopmental similarities, it is important to note that cognitive ontogeny in chimpanzees differs from humans in several respects. Behavioral studies suggest that the different social and environmental contexts in which humans and chimpanzee develop may have also been important in the evolution of human-specific socio-cognitive abilities. For example, whereas young chimpanzees do not fully wean until 4–5 y of age and remain closely attached to their mothers during the early years of development, human infants often interact with multiple caregivers and engage in joint attention.

In another study by Bianchi et al., also published in 2013 regional variation in the morphology of pyramidal neurons in the cerebral cortex of great apes, humans' closest living relatives were investigated. The study used the rapid Golgi stain to quantify the dendritic structure of layer III pyramidal neurons in 4 areas of the chimpanzee cerebral cortex: Primary somatosensory (area 3b), primary motor (area 4), prestriate visual (area 18), and prefrontal (area 10) cortex. The study showed that

  Consistent with previous studies in humans and macaque monkeys, pyramidal neurons in the prefrontal cortex of chimpanzees exhibit greater dendritic complexity than those in other cortical regions, suggesting that prefrontal cortical evolution in primates is characterized by increased potential for integrative connectivity.

However

  Compared with chimpanzees, the pyramidal neurons of humans had significantly longer and more branched dendritic arbors in all cortical regions.

These studies show that despite significant morphological and developmental similarities between human and chimpanzee neurons, there are still notable observable differences.


How do memory cells(B-cells) encounter pathogens?

Great Question.

Location:
Memory B cells are highly abundant in the human spleen, and they make up 45% of the total B cell population in this organ. There is evidence to indicate that human memory B cells might mostly reside in the spleen, and some memory B cells recirculate in the blood [1].

Activation:

Memory B cells circulate throughout the body in a quiescent state until specific antigen is re-encountered and triggers a potent secondary immune response [2].T cell help is a strict requirement for the reactivation of memory B cells that are specific for monomeric protein antigens [3].

Sources:

Hauser, Anja E., and Uta E. Höpken. "B cell localization and migration in health and disease." Molecular Biology of B Cells (Second Edition). 2015. 187-214.
Firestein, Gary S., et al. Kelley's Textbook of Rheumatology E-Book. Elsevier Health Sciences, 2012.
Janeway, Charles A., et al. "Immunobiology: the immune system in health and disease." (2005).


A major cause of squirrel death is predation:

Survival and mortality of the Arizona gray squirrel (Sciurus arizonensis)
Causes of red squirrel (Sciurus vulgaris) mortality in England

You won't see those bodies, for obvious reasons.

Disease, starvation, and harsh weather are other major causes of death. Squirrels dying in these ways are probably likely to die in their nests or otherwise hidden places. Again, no visible bodies.

So that leaves being hit by cars as the major cause of mortality where you'd have a chance of seeing bodies. You've already noted that you do in fact see these bodies, so there's no contradiction there. I'll add that depending on where you live, roadkill can be cleaned up by scavengers more or less quickly -- in areas where buzzards, coyotes, crows, etc are common, they can be cleaned up quickly, but in more urban and/or colder areas they may last longer.


Why do apples taste sweeter at the bottom?

For whether or not your assumption is correct, I have found the following (here), which states that sweetness indeed differs, as well as pH level:

  The bottom sections of ‘McIntosh’ apples were sweeter; whereas the bottom sections of ‘Jonagold’ were less crisp and more fruity.
  The bottom sections of both the ‘McIntosh’ and ‘Jonagold’ apples had significantly lower pH than the top.

Fruits consist of two main parts, the pericarp and the seeds. The pericarp can be further divided into the followings: exocarp, mesocarp and endocarp. In the case of apples, the one responsible for composing most part of the fruit flesh is the mesocarp, so I would like to disregard the other two. The mesocarp consists of ground tissue almost exclusively[1] and no vascular system, thus the only way for sugars to travel inside the flesh of fruit is diffusion, which is mostly determined by gravitation, hence the result.


Can 'hardware' thermalization explain memory decay?

Interesting point, but I think there is a simpler and possibly more widespread reason for the decay of memories. Namely, as new memories need to be stored in the same neural networks, the weights, timings and other properties of the network links are constantly changed. In other words, there is competition for the limited amount of memory. This re-use of the same networks for multiple functions and memories is the same reason we have redundancy in our brain - it's also largely why they are as fuzzy in remembering as they are. And since memories are recalled associatively, the more connected two networks that encode different memories, the more likely it is that activations of one will activate the other. But that also blurs the boundaries between specific bits of information stored. It's a trade-off between fidelity of the memory stored and recalled and generality of the recall and associations possible.


This phenomenon is called Ototoxicity, which literally means "toxic for the ear". Mostly the cochlea or the auditory nerve are affected and almost all these cases are connected to medications as gentamicin or cisplatin.

The reasons for this are that the cells are either driven into apoptosis or necrosis. This is caused by destroying mitochondria and releasing calcium and cytochrome c which triggers apoptosis or by deregulating the the JNK-signal transduction pathway and causing necrosis. This image gives a nice overview:

For further reading you can start with the Wikipedia page on ototoxicity and then also read these two papers which are both freely available (the figure above is from the first):

Intracellular mechanisms of aminoglycoside-induced cytotoxicity.
Gentamicin rapidly inhibits mitochondrial metabolism in
high-frequency cochlear outer hair cells.

To answer the question why this occurs in the ear, it seems that there is some genetic predisposition for this, see this paper: "Aminoglycoside-induced ototoxicity." Mitochondrial damages leading to hearing loss is also not uncommin, see here. Noise seems to play an additional role here and is probably the "last drop" to cause hearing loss.


What do the haploinsufficiency scores in the clinVar database represent?

Okay, I finally found an official source outlining what the dosage sensitivity scores represent.
0 represents no evidence of dosage sensitivity: clinical interpretation is that dosage differences is "likely benign."
1 represents little evidence of dosage sensitivity: This can be marked if only secondary evidence shows dosage sensitivity; clinical interpretation is that dosage sensitivity is "uncertain."
2 represents "Emerging evidence," meaning that the evidence suggests fairly strongly that the gene is dosage sensitive, but that there is insufficient evidence to prove it.  The clinical interpretation is that dosage sensitivity is "Uncertain, likely pathogenic."
3 represents "Sufficient evidence," meaning that the evidence is sufficient to prove that the gene is dosage sensitive.  Clinical interpretation is "Pathogenic."

Source:

Riggs ER et al., Towards an evidence-based process for the clinical interpretation of copy number variation. Clin Genet. 81(5): 403–412.


Where can I find histograms and tables of prevalence of mutations in cancer?

Perhaps you mean COSMIC? The EBI Gene Expression Atlas also has pretty charts, but now mutations.


Which organs need to have fluid compartments in order to develop properly?

Organs consist of different tissues and cells. To function properly each cell needs intracellular fluid. All cellular processes (energy metabolism, signal transduction) occur in aqueous environment, otherwise the required chemical reactions could not take place. Extracellular fluids provide nutrients to the cells and also information from other cells or organs. It can be divided in three categories:

Interstitial compartment: between tissue cells; provides nutrients and helps the cells to communicate within a tissue or organ.
Intravascular compartment: content of blood vessels; transports nutrients, information and immune cells within the body e.g. from one organ to another.
Transcellular compartment: all spaces in the body where only a small amount of fluid is present, normally between organs.

So all organs need these fluid compartments to function properly. The only organ where this is different is the skeleton. But the bone building cells (Osteoblasts) also need extra and intracellular fluid to build a scaffold of collagen. Only after that, they can fill up the interstitial space with hydroxylapatite.
The kidneys clean up the blood and excrete the waste via the urine which occurs in aqueous environment. The intestinal tract absorbs nutrients which are solved in water. Hence, saliva and gastric juice are produced when you ate something.

So every organ needs fluid compartment to do its job. So does the whole organism to make sure all organs are working together (via blood circulation and nervous system).


Is there any evolutionary advantage of selection of L-amino acid over D-amino acid?

The current thinking amongst biophysicists is that if we all woke up tomorrow to find that someone had edited the book of life so as to exchange all of the L-'s and D-'s (and made similar mirroring changes to all of the molecules that any protein interacts with), everything would be exactly the same.

Milton, et al. (Science, 1992) lent supporting empirical evidence to this view by carrying out the total chemical synthesis of a D-enzyme, D-HIV-1 protease. They showed that the L- and D- versions of the enzyme had identical and reciprocal activity, meaning that L-enzyme cut the L-substrate well and the D-substrate poorly, and vice-versa for the D-enzyme:

They also showed that the structures the L-enzyme and D-enzyme were mirror images of one another:

The preference for L- forms over D- emerged sometime early in evolutionary history, and there's a lot of speculation as to how the preference arose (it could have been cosmic rays!), but the evidence is thin.


It's not true that all bacteria hate oxygen. Actually, there are some obligately aerobic bacteria that need oxygen to carry out cellular respiration. A notorious example of this type of bacteria is Mycobacterium tuberculosis, a pathogenic species that infects lungs and cause tuberculosis. Because it's obligately aerobic, in the classic case of tuberculosis, Mycobacterium tuberculosis growths are always found in the well-aerated upper lobes of the lungs where the oxygen requirement is satisfied.

Reference:
1. Levinson, W. (2010). Review of Medical Microbiology and Immunology (11th ed.). McGraw-Hill. pp. 150–157. ISBN 978-0-07-174268-9.


Understanding transplant rejection - how does the cellular, adaptive, response get underway

There's a really good paper on this, Moreau et al., worth reading through entirely. The only caveat is it was published in 2013, so as a rapidly evolving field such as immunology we might have more insight now. However, the general concepts remain the same.

The lymphocyte compartment that we generate in our own bodies is modulated so that it isn't autoreactive. In other words, for every antigen a T cell should expect to actually encounter in vivo, the ones that attack and kill self cells are made to undergo apoptosis, the special case of course being autoimmunity, which is a set of diseases.

An organ transplant is what's known as a so-called allograft. The allo- prefix implies that the origin is the same species, but from different individuals. So how do people differ at the molecular level? Well for one, we inherit and develop slight differences to such things as protein sequences, carbohydrate chain moieties, and certain receptor combinations. So, your lymphocyte compartment may be non-autoreactive, but it could be alloreactive because those aren't your signals.

The other thing transplants do is cause damage and inflammation that result in the presence of these patterns that the innate immune system respond to called PAMPs and DAMPs, or molecular patterns associated with pathogens and tissue damage. They also bring along donor immune cells like antigen-presenting cells, resident lymphocytes, granulocytes, etc. It's also a functioning tissue, and so just like any of your own cells, a liver cell is expressing class-I HLA loaded with alloantigens. This can have two effects: graft-versus-host, so you have donor immune cells attacking the recipient, and the rejection which is where your recipient immune cells attack the transplant.

Your immune cells attack the transplant predicated on direct and indirect recognition, and the fact that all that inflammation already has the immune system up in arms. So your lymphocytes recognize an alloantigen on the donor antigen-presenting cell is an example of direct recognition. This can occur in the transplant, and also in the recipient lymph nodes as donor APCs can traffic there on signals in the lymph. Recipient APCs can also pick up on alloantigens from donor cells and active the adaptive immune response classically, which would be an indirect recognition.

The blanket treatment for this seems to be immunosuppressive therapy.


(Updated question) Problem with Fold-change mean compared to absolute data (in qPCR)

Sample 1. 4096 / 1024 = 4x more B
Sample 2. 16384 / 1024 = 16x more B
The average amount more B = (16 + 4) / 2 = 10x more B

That is not the right way to go about. You are calculating average expression of B in both samples. It does not mean there is 10x more B. There is just 4x more B in Sample-2 relative to Sample-1.
Gene-A does not change its expression between samples and can be used as a reference gene.
If you calculate by threshold cycle the fold change $ = 2^{8-6} = 4x$
See this post too.
The average is calculated between replicates, not between different experimental conditions.
Sometimes the average of two experimental samples is calculated — this is typically done in a MA-plot analysis which is done to filter out genes which show very high fold changes just because of their overall low expression (1:4 vs 100:300).
Answer to your Edit
You should not take the average (arithmetic mean) of Ct. They don't scale linearly with expression (and so is the converse).
For any non-linear function $f(x)$:
$$f(x+y) \ne f(x)+f(y)$$
$$f\left(\frac{x+y}{2}\right) \ne \frac{f(x)+f(y)}{2}$$
Furthermore, for a convex function:
$$f(E[x]) \le  E[f(x)] $$
$$ Jensen's\ inequality $$
where $E[x]$ is expected value of $x$
$a^x$ is a convex function with respect to $x$ ($a$ is any real number > 1). So you can apply Jensen's inequality to Ct values and expression.


The function of heart is just to pump blood and nothing else. Though, it is a vital organ, its functions are limited. The device that you are talking about is a battery powered mechanical pump that performs the same function as heart.

Liver, however has a more complex function. One of its function is to synthesize and secrete certain molecules. A small artificial device cannot do that (you would need a bioreactor !!!).

We still haven't developed and artificial cell. Perhaps a consortium of bacteria can do some of the liver's functions but to culture them in right proportions and implant them without the risk of infection or their elimination is almost impossible as of now. You can clearly see that there are too many steps to be optimized.


Lehninger Principles of Biochemistry by Nelson and Cox is quite popular and covers everything you listed in great detail except for immunology.

I don't really have a recommendation for an immunology book; I think pretty well any of them will cover immunoglobulins (they're pretty integral). My university uses Kuby Immunology by Kindt et al. Molecular Biology of the Cell by Alberts et al. has a couple chapters (some 115 pages) on the subject. As a bonus, it's an amazing reference for cell biology (which you'll need, at least someday, if you're pursuing biochemistry).


It is because the two genes overlap:

CLCN6 is on the plus strand and MTHFR is on the minus strand. The SNP is annotated to both because it falls in a region of the genome claimed by both genes.


How to identify the age of a "living" person?

The most accurate method known so far may be Horvath's methylation dating algorithm, which uses 353 CpG sites (Genome Biology research article, Nature news article).

From the Nature article, this method was validated with at least one population.

  [After the publication in Genome Biology] Marco Boks at the University Medical Centre Utrecht in the Netherlands applied [the algorithm] to blood samples collected from 96 Dutch veterans of the war in Afghanistan aged between 18 and 53. The correlation between predicted and actual ages was 99.7%, with a median error measured in months.

However, I did not read the original research article and it seems that the dating method works poorly on cancer patients.


Which is the correct term haploid daughter cells or haploid parent cells?

"Parent" and "daughter" terminology is indeed relative. Any parent cell has been a daughter at some point. However, in the case of the zygote there is no "parent" strictly speaking since it is the result of a fusion between two cells, that you may call "daughter cells" only if you are referring to the previous meiosis event.

In this particular case, there is no cell division, so no "daughter" is formed, so no point in calling the haploid cells from M2 "parents" either.


Does the brain and the body use the same energy source (glucose/ATP)?

You can grab any university level text on human physiology and you will find that the brain is a unique organ for cellular respiration. The brain is only capable of using two metabolic subtrates: glucose for oxidative phosphorylation (producing ATP) and ketone bodies.

Exercise does indeed divert blood flow toward the muscles. After all, they are undergoing higher levels of respiration and need nourishment. Your body will always balance muscular needs and the needs of the brain and the rest of the body. Similarly, digesting food has a similar response, although this is more involved. Eating food has a autonomic reflex to increase blood flow to the stomach and digestive tract to facilitate the processing and distribution of nutrients.


Understanding Research Paper Differences

This study enrolled 144 CLL (chronic lymphocytic leukemia) patients ("total patient group"). They further grouped these patients into 3 groups according to the treatment they were receiving.

When they refer to "general population" they are referring to norm scores:

  For each patient, an individual norm score was
  derived from age- and gender-matched scores of the general population on the EQ-5D [28] and EORTC QLQ-C30
  [29]. These two studies, as reported in Refs. [28] and [29],
  used a panel consisting of more than 2000 Dutch households, representative of the Dutch-speaking non-institutionalised population in the Netherlands.

So these scores are not part of the current study, but they are estimates from a survey of the wider population rather than patients who have CLL (you can assume they do not have CLL). "Total population" doesn't mean "all CLL", it means "all Dutch-speaking non-institutionalized people".


The Worm Atlas you cited is NOT just a "model." The neuronal cell coordinates were determined from an actual 3-D reconstruction of a worm based on serial thin section electron micrographs.  The serial sections were manually digitized to permit annotation and analysis using computer graphics. The annotation (over a period of years) established the synaptic connectivity, published by John White et al. in 1986 in the Proceedings of the Royal Society of London.


I'm able to create rumbling in my ears at will. Unlike the poster of the video, I don't need to yawn to do so; I can do it without my face appearing to move. I actually discovered this alongside another ability of mine when I was little: the ability to create warmth flowing from the base of my neck outwards into the rest of my body. After some research I figured out that the warmth I'm able to create is actually part of voluntary piloerection (its use for warmth is mentioned here), while the ability to create a rumbling sound is simply the contraction of the tensor tympani, a muscle in the ear. Voluntary control over either one of these things is supposed to be rare, but I've found claims of several other people online who can do both (example1, example2).
Anyways, Wikipedia gives a brief explanation of how the ear rumbling works, which also specifically mentions "yawning deeply" as a trigger:

Contracting muscles produce vibration and sound. Slow twitch fibers produce 10 to 30 contractions per second (equivalent to 10 to 30 Hz sound frequency). Fast twitch fibers produce 30 to 70 contractions per second (equivalent to 30 to 70 Hz sound frequency). The vibration can be witnessed and felt by highly tensing one's muscles, as when making a firm fist. The sound can be heard by pressing a highly tensed muscle against the ear, again a firm fist is a good example. The sound is usually described as a rumbling sound.
Some individuals can voluntarily produce this rumbling sound by contracting the tensor tympani muscle of the middle ear. The rumbling sound can also be heard when the neck or jaw muscles are highly tensed as when yawning deeply. This phenomenon has been known since (at least) 1884.

It also seems like this type of noise can happen with conditions such as Tonic Tensor Tympani Syndrome.
The tensor tympani connects directly to the handle of the malleus, so I'd assume that's why it can be heard by the person doing it. Apparently this also causes the eardrum to move. This means it's classified as objective tinnitus.
Here are some relevant studies I found:

Voluntary contraction of the tensor tympani muscle
and its audiometric effects
Voluntary Eardrum Movement : A Marker for Tensor Tympani Contraction? (paywall)
Tonic contractions of the tensor tympani muscle: a key to some
non-specific middle ear symptoms? Hypothesis and data from
temporal bone experiments (paywall)


Is the 'fluttering feeling' when under stress neurological or physical?

If you want to find out about the the relationship of this response to romance in particular, there's a pretty comprehensive research paper called Love is more than just a kiss: a neurobiological perspective on love and affection[1] which reviews a lot of the work done in this area. This is pretty good as it discusses all the different stages including breakup.

Essentially, there seems to be a lot factors at play which elicits various responses through different stages of love.

In terms of anxiety and stress, initially, there's a large increase in levels of cortisol[2] and a marked drop in serotonin. Depletion of serotonin is found in many psychiatric conditions such as depression, anxiety and panic disorder. There's even been evidence that these levels at early stages of love are similar to those suffering with OCD. Obviously, the 'symptoms' of early love are quite similar to these conditions so it's hypothesised that this, at least in part contributes to those feelings.[1]. It was found that these levels are back to normal in 12-24 months.

The elevated levels of cortisol contribute to the feelings of stress but this hormone has also been shown to promote attachment.[2].

There are also changes in activity of the amygdala. Responsible for regulating a lot of emotions such as fear and sexual drive, the amygdala can activate autonomic nervous system responses through the mechanisms which Kevin described.

There are a bunch of other things at play here including dopamine, oxytocin, vasopressin, nerve growth factor (NGF), testosterone, increased activity in the hypothalamic-pituitary-axis (HPA) and variations in activity in other areas of the brain.

Again, that first reference gives a pretty comprehensive overview of the mechanisms involved.

To answer the actual question about the fluttering feeling, as Kevin mentioned, it's hypothesised that this is caused by reduced peristalsis in the intestines as a result of sympathetic stimulation. I don't have an academic reference for this but there are plenty of non-academic sources that talk about it (a quick Google of butterflies in stomach and physiology will probably show them).

A lot of the mechanisms noted above can contribute to, sensitise for or cause sympathetic activation. For example, panic attacks and anxiety, mentioned earlier with the serotonin relationship, can cause the same feeling.

Boer, et al. Love is more than just a kiss: a neurobiological perspective on love and affection. Neuroscience. 2012. 201:114-124.
Marazziti, et al. Hormonal changes when falling in love.
Psychoneuroendocrinology. 2004. 29(7):931-936.
Guyton and Hall. Medical Physiology. 11th ed. Elsevier Saunders.


In a typical model ecosystem, what might the percentage of plants be to top predators and everything inbetween?

The percentage of biomass at each stage will vary tremendously, based on the following factors:

1: Relative turnover rate of the biomass. When biomass turnover is very high (for example in plankton and whales), it is possible for whale biomass to exceed that of the plankton, even through the whales feed on plankton. Therefore, it is better to use a pyramid of energy, where the total energy flux through a specific trophic level is used. See the article here for more detail.

  Just as with the inverted pyramid of numbers, in some rare exceptions, there could be an inverted pyramid of biomass, where the biomass of the lower trophic level is less than the biomass of the next higher trophic level. The oceans are such an exception because at any point in time the total amount of biomass in microscopic algae is small. Thus a pyramid of biomass for the oceans can appear inverted (see image part b). You should now ask "how can that be?" If the amount of energy in biomass at one level sets the limit of energy in biomass at the next level, as was the case with the hares and foxes, how can you have less energy at the lower trophic level? This is a good question, and can be answered by considering, as we discussed in the last lecture, the all important aspect of "time". Even though the biomass may be small, the RATE at which new biomass is produced may be very large. Thus over time it is the amount of new biomass that is produced, from whatever the standing stock of biomass might be, that is important for the next trophic level.

2: Biomass conversation rate in each trophic stage. For example, the article on entomophagy cites a number of papers that insects convert vegetation to biomass approximately 10 times more efficiently than cattle. A population of humans that fed on cattle would have a different biomass (and energy) pyramid than a population of humans that fed on locusts, for example.


The placement in terms of location on the scalp determines what region of the brain is sampled. The electrode density determines how many locations are sampled. The spatial resolution of an EEG has been reported to be 7 mm (Im et al., 2006), meaning the variability in determined source and verified source (via fMRI in the study cited) is approximately 7 mm. Hence, increasing the density below 7 mm may not be too helpful. The 10-20 system utilizes an inter-electrode distance of 60 - 65 mm (American Clinical Neurophysiology, 2006), indicating it may make sense to use more electrodes when high resolution is needed. Note, however, that MRI and MEG have better spatial resolution than EEG and are methods of choice when you wish to do accurate source localization. EEG has excellent properties in the temporal domain, and a combination of MEG/EEG has great characteristics in both spatial and temporal domains.
Standardized EEG montages indeed promote uniformity so that different studies can be compared more efficiently.
Scrubbing with electrode paste primarily reduces impedance (increases conductivity). Hair and the skin don't conduct well and by applying a conductive paste impedances are substantially reduced. Mostly the technicians also scrape a little bit to ensure even better conductance by removing the fatty top layer of the skin. Also important is that differences in electrode impedances negatively impact recordings (American Clinical Neurophysiology, 2006). Impedance matching is hence necessary and using paste aids this purpose. So yes, conductive paste is essential.

Reference
- Im et al., J Neurosci Methods (2007); 161(1): 142–54


Why is it beneficial for bacteria to conjugate? (Horisontal gene transfer)

I am going to try answer it. Bacteria in general has different survival tactics. In general for bacteria the best way how to surviva is as much copies as it cans. So imagine situation, when bacteria is surround with others bacteria. Then the race will bega. All bacteria wants to survive with same tactic as i mentioned. Thats mean the best way how to archived this goal is make your replication fast.

So when you take plasmid with resitantion to antibiotics its advantige to have those, but when you actually is not exhibit to that antibiotic it slow down your chance to survive (because it slows down your replication, cell division)


For fish, does a bony skeleton have any advantages over a cartilage skeleton?

As a fish morphologist, here's my best attempt. I really like the first reference I listed at the bottom, too.

1) Ancestral Condition:: The cartilaginous skeleton of chondrichthyes (sharks, skates, rays, chimaeras) is almost certainly a derived feature--a synapomorphy-- defining the clade. There are a few lines of evidence for this. First, the cartilage in a shark skeleton is a very specialized form of calcified cartilage,  unique to the group. Second, in other gnathostome and pre-gnathostome ancestors (Osteostracans,  other armored jawless fishes) had big bony head shields. The groups most closely associated with sharks (Placoderms, paraphyletic acanthodians) has both bone and cartilage in their skeletons. Basically I guess my point is that, while cartilaginous skeletons were ancestral for gnathostomes, that cartilage was very different from chondrichthyan cartilage, and bone turned up in many stem fishes before chondrichthyan cartilage. So the ancestor for sharks and bony fishes probably had both cartilage and bone but not the specialized calcified cartilage of sharks

2) Bone as a Plesiomorphic (ancestral feature), but not the entire skeleton: If we take what I've said above, it certainly suggests that your point 3 is in the right direction w.r.t. split between chondrichthyes and osteichthyes. The chondrichthyan skeleton is light...But the osteichthyes definitely took endochondral bone and ran with it--which brings us back to your original question: why did they replace their entire skeleton with bone? Why is always a tricky question in evolution, but we can speculate:

3) Potential adaptive value of a bony skeleton:

bone is better at transmitting muscle force than cartilage, so in that sense, you are correct
when fish were coming into prominence and diversifying, there were a lot of big, terrifying, predatory arthropods. Many early fishes have big bony armor plates-- which may have served to project them from their chitonous predators
More evidence for that -- when big scary predators went extinct, fishes began to pare down their bony armor (most teleosts have highly reduced skeletons).

Without a time machine we can't be certain of these things, but I'm pretty sure what I've laid out is fairly close to the common consensus.

Relevant lit:

https://academic.oup.com/nsr/article/1/4/490/1512529
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237026/


How the pattern of fertilization path is determined before the cell division to form the blastocyst? Is it individually specific?

First of all, the more commonly used term is "copulation path," and I don't ether is used as a formal biological term, but rather in models for the public.  The term that is used in literature is "pronuclear fusion" for the process as a whole, and I don't know of a more technical term for the path itself.  Your inability to find information may have been linked to terms used.

Anyway, the copulation path doesn't have as much variability as the penetration path, which is what determines the copulation path.  The copulation path tends to be a relatively straight line between the two pronucleoli, dictated by and pushed along the cytoskeleton (Lian et al, 2014).  It is worth noting that it is often not the shortest straight line (think of the number of lines between a smaller sphere and a larger one), but still a relatively straight line.  People tend to care about this, because what ever the copulation path, it sets the axis of division, which can effect in vitro fertilization techniques, particularly in plants.

Getting at what I think you are trying to ask, the penetration path is variable because it is an oscillatory phenomenon.  You actually have to move back in the fertilization process to the sperm impact angle (Hedrih et al, 2015 is the coolest model I've seen of this) to see how this can change.

To understand oscillatory phenomenon in general, you need to understand that a lot of the processes in biology are driven by the chaotic (used in the formal since) vibrating or shaking of molecules and fluid microcurrents.  This means that we can not know (regardless of how sensitive we measure) the conditions specific enough to create the specific path.  These things are not tied to genes or to the person in general (perhaps exuding of mutations/disorders that effect the morphology of sperm or egg).  Rather it is specific to any single fertilization reaction simple because of chance/chaos.


In a 2011 Nature review they provide a figure for the life cycle of the Dengue virus,

Source: Immunity to dengue virus: a tale of original antigenic sin and tropical cytokine storms

The Dengue virus is a positive-sense ssRNA virus. This means the ssRNA that enters the host may immediately be translated. The viral ssRNA does not integrate with the host genome!


How predictably will RNA polymerase not transcribe repetitive sequences?

I don't think repetitive sequences are intrinsically problematic to an E coli. Bacteria also deal with things like polyadenylation. Basically, you have nothing to lose from trying -- E coli is one of the more robust expression platforms, and it's difficult to predict whether the sequence will fold into some tertiary structure (which can easily impede translation.)

So I think the predictability should be set at the baseline for E coli RNA polymerase error rate, which is about $10^{-5}$.


TRANSFAC Matrix.dat retrieve count matrix using BA or CC field

So databases like TRANSFAC are of somewhat... variable quality. Those matrices maybe have been derived from a program that just doesn't output a count matrix, but instead outputs a frequency matrix directly. What I would do, and what i have seen people do in published papers, is just multiply the matrix by 100 and round down. It's a kludge, but you'd better be quality checking the matrices somehow anyway, otherwise you're going to get 90% crap.


In general, a grown up man will have a voice with a lower pitch than when he was an adolescent (Cleveland Clinic). The pitch height basically depends on the length of the vocal cords. According to Wikipedia:

  Adult male voices are usually lower-pitched and have larger folds. The
  male vocal folds...are between 17 mm and 25 mm in length. The female
  vocal folds are between 12.5 mm and 17.5 mm in length.

So, the shorter the cords, the higher the pitch. There are other anatomical structures in the throat, mouth and nose that may contribute to more adolescent-like voice. To know what exactly is the cause in a particular man, an examination by an ear, nose and throat (ENT) specialist would be probably required. Additionally, a voice specialist could have a good insight even without physical examination.

There can be reasons associated with self-image that make one to consciously or subconsciously insist in speaking with a voice unusual for his age. Sometimes you can see this in singing competitions, when a young man introduces himself with a child-like voice but then sings as a grown-up man.


Do smaller intelligent animals have a higher neuron density to account for their seeming intelligence? Otherwise, what?

It also may be the case that we are implying intelligence in some cases.
The responses these animals show may have been evolutionarily selected as it best for their survival. However, to us the benefits of these responses may not be directly visible. For example, sheep herding dogs may have a high degree of spatial and numerical capabilities since humans bred them for these traits.


Here's an illustrated example in neurons:

ATP, of course, is generated by aerobic respiration. The critical biochemical reaction in the brain that is halted due to lack of ATP (and therefore O2) is the glutmaine synthetase reaction, which is very important for the metabolism and excretion of nitrogenous wastes:

The body uses this reaction to dump excess ammonia (which is a metabolic waste product) on glutamate to make glutamine. The glutamine is then transported via the circulatory system to the kidney, where the terminal amino group is hydrolyzed by glutaminase, and the free ammonium ion is excreted in the urine.

Therefore, as you'd expect, under hypoxic conditions in the brain, excess ammonia builds up which is very toxic to the cells. Neurons are also highly metabolically active, which means they generate more waste products. A buildup of nitrogenous waste products in the cell (and bloodstream) can be potentially fatal due to it's effects on pH (screws up enzymes and a whole slew of biochemical reactions).

In addition, the buildup of ammonia will cause glutamate dehydrogenase to convert ammonia + aKG to glutamate, which depletes the brain of alpha-ketoglutarate (key intermediate in TCA cycle). This basically creates a logjam in the central metabolic cycle which further depletes the cell of energy.

This is just one example of many. Of course, there are many, many other critical metabolic processes that require ATP (i.e. the Na+/K+ ATPase pump that regulates neuronal firing and osmotic pressure), but nitrogen metabolism was the first that came to mind :)


Is the glomerular filtration rate, per kidney or for both?

The definition of GFR given in Wikipedia -

  Glomerular filtration rate (GFR) is the volume of fluid filtered from the renal (kidney) glomerular capillaries into the Bowman's capsule per unit time.

Since it is difficult to measure the volume entering into each Bowman's capsule, as a proxy, we measure the clearance of a solute that we know isn't going to be absorbed or secreted. For that particular solute,

GFR = (Urine concentration x Urine flow)/ Plasma concentration

The GFR you obtain here is the sum total of volume of all the fluid filtered from all the renal (kidney) glomerular capillaries into all of the Bowman's capsule per unit time.

Obviously, a single Bowman's capsule can't receive 120ml every minute, it is microscopic!!

So yes, the GFR or eGFR we use in clinical practice is the sum total of the function of both the kidneys. In fact, before transplantation, although the left kidney is preferred from the donor (since it is easier for surgery having a longer renal vein), it is more ethical to estimate individual GFR for each kidney and preserving the better functioning kidney. And yes, the total GFR drops after donating a kidney, but the body has sufficient reserve to manage.

If you still have a tough time figuring that out, think of them as many separate taps opened to fill a bucket. One tap for each glomerulus. The net rate of flow is the sum of flow rate in all the taps. The kidney has million such taps! And the taps are being clogged one at a time in chronic kidney disease - decreasing the GFR. And in a transplant, half the taps are suddenly shut down in the donor! But since this is a healthy kidney, the donor adapts and slowly reaches ~70% of original GFR.


Has DNA communication/interaction at a distance been empirically demonstrated?

No — typical DNA extraction will not preserve information about the biochemical state of the cell.

During the process of DNA extraction, proteins are removed and DNA from a population of cells gets precipitated. Then you dissolve the DNA. In this process native conformational state cannot be preserved.

However there are techniques (see this post) that can capture long distance molecular interactions of DNA (which reflects a conformational state). To summarize in a line, these techniques "lock" the DNA in its conformation and downstream steps are carefully done so as prevent loss of information.

Stress is just a kind of biochemical response. This technique can be applied to study long range DNA-DNA interactions for different conditions (for e.g. Developmental stages).

Stress can cause RNA in the cell to aggregate; however once you do the extraction you won't be able to know if it was aggregated in the cell before extraction.

An Analogy: Sugar can be anhydrous powder or can be crystalline. But once you dissolve the sugar in water, there is no way to know in what form it existed before dissolution.

Certain processes (epigentic mechanisms) can lead to methylation (sometimes hydroxymethylation) of DNA (at cytosine; Bacteria also have adenine methylation). These modifications can be detected in the extracted DNA by different methods; one of the common techniques employed for this is bisulphite-sequencing.

Final word: all these claims about molecules having telepathic memory is pseudoscience. There is no evidence whatsoever for such proposed phenomena.


What species of butterfly/moth is this please?

Mint moth. We can only see the forewings on this photo. Single gold spot is the giveaway.


Why did the Brain develop in the front in most organisms?

TL;DR Visual and auditory systems are crucial for survival, especially in higher animals. Also, visual/auditory systems have great number of cells. For processing to be effective, it should be performed closer to data acquisition (eyes).

First of all, for example, in mouse or human, central nervous system includes brain and spinal cord. Since spinal cord is extremely important at regulating different physiological processes as well as in performing complicated motor tasks, it would be unjust to not think about CNS as a whole.

If you talk only about brain part of CNS, it makes sense to locate important processing pathways near sensitive organs for two reasons. First, it saves material on running long axons from many sensory cells. Secondly, longer axons deliver information slower. If there is a sense that is important for survival, than information in that modality must be delivered and processes as quick as possible.

In comments to the question @anongoodnurse mentioned that "butterflies 'taste' with their feet". I would argue that a) taste in butterflies is not vital for immediate survival and b) number of taste buds is very limited, whereas retinal cells are count up to more than thousand per eye.

But what about humans? We also able to "taste with our feet", e.g. feel temperature. For survival it is crucial to be able to escape hot surface as fast as we can. And we do, thanks to a direct reflex arc going from sensory cells to spinal cord and motor neurons. Which brings back point about CNS as a whole system. Crucial information and immediate decisions are made closer to sensitive organs.


Yes. That is definitely a Kermes Oak / quercus Coccifera.

It should start blooming in a week or two, in case you're still in the area by then I recommend checking it out.

It is thriving in that area specifically because it's a dry area, otherwise they tend to be pushed out by Holm Oaks / Quercus ilex.

The combination of the area (see below), habitat (dry hills) and picture (especially the acorn cupule) are pretty conclusive and support your original assumption.


Can someone ID this moth seen in Bellandur, Bangalore?

It's the Indian Lily Moth
(https://en.m.wikipedia.org/wiki/Polytela_gloriosae).


Will ammonia continue to accumulate in an aquarium tank if a strong antibacterial or chlorine is added to the water?

A very large part of the bacteria and fungi will die so very few biological prosesses will continue in the tank if you add chlorine or antibacterial chemicals.

Ammonia will slowly outgass from the water oxygen and CO2 will reach equiriblium in the water as little oxygen is used and little CO2 is produced,it is the same with the other atmospheric gasses.

Life in the tank will simply stop until the toxins are broken down or removed,by toxins i mean chlorine and/or antibacterial chemicals.

Nitrate level will not change as little is produced and little is used,any denitrification will stop too.

denitrification can only happen in an anaerobic environment but denitrfying bacteria too are killed by chlorine and antibacterial chemicals.


What is the secondary structure distribution per AA in the Human proteome?

The question asks why the distribution of coil, alpha-helix and beta-strand is 60:30:10 rather than 33:33:33. The answer is:

  “Why not”

This is because there is no reason whatever to expect that three types of structure (or in the case of coils, lack of structure*) should be present in equal amounts in proteins. It is like expecting that the percentage intron, exon and ‘junk’ DNA should be equal, or that the percentage of fuel reserves stored as glycogen and fat should be the same. Yes, they belong to the same category, but they are sufficiently different in each case for one not to be surprised if they are not required in equal amounts.

To understand this one needs to look a little more carefully at the occurrence of alpha-helix or beta-strand conformation in the three-dimensional structure of proteins. Three points may be emphasized:

Amino acids have particular conformations because they are part of an extended helix or sheet of strands the entirety of which leads to its structural stability — you don’t have a random mixture.
In many cases the helices or sheets are occur in particular combinations to give a family of proteins of similar overall structure. Again, the idea of random mixtures doesn’t enter into the equation.
These overall structures are suited to particular functions, so the abundance of proteins from a particular structural family will be determined by the requirement for antibodies or ion transporters or signal transducing proteins etc., not by some shake of the dice.

Images illustrating two such families are shown below:

(a) shows an ion transport proteins, predominantly alpha-helices, whereas (b) is an immunoglobulin domain with a distinctive pattern of beta strands (as well as some helix). For further examples and information I suggest the EMBL on-line course on protein classification and Berg et al. online, for example Section 7.3.

*Footnote 1: Situations where equal occurences might be expected
It is worth while contrasting the situation with protein secondary structure to some where the prior expectation might well be for equal usage, and the deviation from this could be regarded as bias and an explanation worth asking for:

The different proportion of the 20 amino acids in proteins (although a chemist would not expect equal proportions)
The different usage of synonymous codons of the genetic code in various species and mRNAs
The different usage of the similar molecules with a high phosphoryl group transfer potential: ATP, GTP, UTP and CTP (often loosely termed ‘high-energy’)

*Footnote 2: A coil is not a secondary structure

As is stated in the Wikepedia entry for Protein Secondary Structure:

  The random coil is not a true secondary structure, but is the class of conformations that indicate an absence of regular secondary structure.

It might be mentioned in regard to protein structure that there are smaller three-dimensional motifs that the analysis quoted does not consider. These do not occur in equal proportions either, to nobody's great surprise.


Is it the case that all changes in phenotype during life are not inheritable?

The assertion "You cannot change in life what will be genetically inherited in any possible way" is true, as you cannot (healthily) change the DNA in your germ cells.

However, the assertion "You cannot change in life what will be inherited in any possible way" is wrong, because of epigenetics. Parts of your DNA are marked (in different ways), and this can be inherited and have an effect. E.g. the only causal difference between these two mice is the diet of their mothers:

Image source and a further explanation: Nutrition and the epigenome.


Can some one identify this plant with really sweet smelling flowers?

It's most likely a buddleia of some kind, perhaps Buddliea davidii:

You can see the flower is tubular and has four 'petals' at the end. They also have paired leaves, the underside of which is lighter than the top.

  The flowers are generally rich in nectar and often strongly honey-scented.

I never thought it smelled like honey, but it does have a very pleasant and strong sweet smell.

It is present on four continents.


Which secondary structures of RNA are symmetric?

Each one of those lines has a reference to a paper which will help you to understand the calculation that was performed

Read this from your original post
https://oeis.org/A088518

Overlapping sequences


It is a domestic form of mallard. They are bigger, often white or mostly white. Try to google image domestic mallard and you will see the phenotypic variety that domestication has created.

Note the irregular and not symmetrical shape of the "hat" and read the description below from the biggest research center on birds of the world.

Extracted from:
http://www.birds.cornell.edu/crows/domducks.htm

  (...)lots of white is often involved, including all-white breeds like the popular Pekin Duck (...) Usually these white spots are not symmetrical across both sides, and that asymmetry should tip you off to think domestic influence.


They are both right.

Animal cells do have vacuoles, but they are smaller, larger in number (plant cells usually have just one or a few large vacuoles) AND serve a somewhat different purpose than those of plants.

A vacuole is basically a membrane-covered compartment (vesicle) filled with molecules, that shouldn't, right now, be in the cytoplasm. For plants, this means long-term storage of water and waste products, which cannot be removed from the cell due to the cell wall. For animals it means mostly taking part in exocytosis and endocytosis - they are much more dynamic structures.

And about some half-professional sources, here is a bit from Molecular Biology of the cell which in fact calls plant vacuoles "a kind of specialized lysosome".


As you noticed this is definitely tree from Platanus order.

The London plane which is Platanus acerifolia, which is more casual is actually a hybrid of two platanus. Those two names are Platanus occidentalis and Platanus orientalis.

Frankly, I think the one of what are you looking for is that Platanus orientalis. See it on a picture of seeds taken from Wikipedia.


Do ants within a colony ever fight or come to conflict?

There has been several major transitions (John Maynard Smith and Eors Szathmary) and systematically there is opportunity for conflict to arise…. and it does! There is conflict along genes within a chromosome (example the Psr gene of Nasonia vitripennis, see R. Trivers and A. Burt Genes in conflict), along chromosome within an individual and along individual within a colony.

Ants has been much studies (see E.O. Wilson, L. Keller, M. Chapuisat) and it has been found that there are tons of different reproduction system in those species. There are conflict between queens, between workers and between queen and workers to reproduce. In some species, a colony have several queens, in others, there are several queens fighting early in life for the right of being the unique queen. In some species, workers can fight to take over the queen and take her function. In some species, workers reproduce sometimes even if there is a queen. There is conflict over who will survive depending on how much related one is to the other one. For example, there is conflict over sex-ratio, the queen is as much related to her sons than to her daughters but the workers are more related to their sisters than to their brothers (because of haplo-diploidy, see Robert Trivers).

There are various factors limiting the conflicts: high relatedness (Hamilton, Trivers), Cost of a fight, absence of information, power asymmetries. Ants evolved various strategy. There is a "police" who kill worker's spawn. We might as well consider lineage selection that select for cooperative colonies (note that L. Lehmann and L. Keller argue that group selection and kin selection are the same concept!)

I basically repeated some stuff I read (or learned in class) but I am personally not sure that all that makes sense! I don't know if really the frequency of conflicts is not simply related to the mutation-selection balance. Criticisms are welcome!

UPDATE:

In reaction to your comment:

Conflicts always have to do with reproduction or survival in evolutionary biology. One might make three categories of conflict:

1)Those involving the right of reproducing

2)those involving the probability of dying (I prefer not to be a forager because forager have a very high mortality)

3) Those that concern the survival of kin individuals. The "purpose" (if I might use this agency way of speaking) of any one to to increase its inclusive fitness (Hamilton, but don't read Hamilton, there is lots of easy source of information on kin selection). Therefore, one will rather help its brother to survive rather than his cousin as it is more closely related to its brother. Similarly, beccause of the haplo-diploidy nature of sex determination system in hymenoptera, workers are more closely related to other workers than to the males while the queen is as much closely related to her daughters and sons. Therefore, we would expect a conflict over the sex ratio, queen trying to have a sex-ratio of 1:1 while the workers are trying to have a sex-ratio of 75:25 (if there is only one father).

Hope this helps!

If you want more specific information about sex-ratio in ants, kin selection, group selection please ask it in another post. Note that there is already some discussions one these subjects on Biology.SE.


Why isn't acetyl-coA an entry point for gluconeogenesis?

The problem is that acetyl-CoA enters the TCA cycle by condensing with oxaloacetate in the citrate synthase reaction. Therefore, you need 1 oxaloacetate for each acetyl-CoA added. Now, if the citrate formed goes on to oxaloacetate which is then removed for gluconeogenesis, there is no oxalocatete left for the next citrate synthase reaction. The reactions do not balance. Therefore, an anaplerotic substrate like glutamine or asparate is needed to replenish the lost oxaloacetate.


Humans usually scratch to stop itches. Because scratches are a more high-priority sensation than the itch, the nerves stop transmitting the itch signals to your brain for a while.


Definition of a Katal (unit of enzyme activity)

A katal is indeed a specific amount of enzyme (rather than a reaction rate), but one which is measured with respect to the catalytic activity of the enzyme, rather than with respect to the number of molecules, their weight, or their size.

Roughly speaking, one katal is the amount of of enzyme which can convert 1 mole in 1 second. (Just like one pascal is the amount of pressure which applies one newton of force to an area of one square meter.) Or to rephrase things slightly, just like you can take an object of a particular length and express that length as "X meters" (being the number of meter sticks you can line up next to that length), you can take a given amount of enzyme and express the catalytic activity of that quantity of enzyme as "X katals", being the number of moles the enzyme can convert in one second.

This is not an intrinsic property of the enzyme itself. (It's an "extensive", not an "intensive" property.) The number of katals varies based on how much enzyme you have - if you have twice the amount of enzyme, you have twice the number of katals. (Just like you have twice the number of grams or twice the number of moles.)

As such, you can't talk about "an enzyme with a smaller number of katals of activity". I can understand the confusion, though, given the use of "activity" in the name. A paper the Wikipedia article references talks about the fact that there was some argument for calling the quantity being measured ‘catalytic amount’ rather than ‘catalytic activity’

As to why measuring enzyme amounts in katals versus moles or grams, the argument is similar to why there are separate units for mass (gram) and number (mole). It expresses a feature of the "size" of the enzyme not captured by the other units.


How does exercising/starved muscle import glucose (released by liver)?

GLUT4 is the major glucose transporter in muscle even in exercise. However, during exercise, it is translocated to the cell surface by contraction-triggered, insulin-independent mechanisms, such as AMP-activated protein kinase (AMPK) activation.

For more, you could read this review.

Note:

'No insulin' is too strong a phrase; exercise and fasting are associated with low but detectable insulin levels. The reference range for fasting insulin in healthy individuals is $<174 \ \text{pmol L}^{-1}$ (contrast this with levels upto $1917 \ \text{pmol L}^{-1}$ one hour after glucose ingestion). Exercise studies have shown levels around $60-80 \ \text{pmol L}^{-1}$.


How are the two mating types, a and α, for S. cerevisiae pronounced?

Correct.

Haploid mating types in Saccharomyces cerevisiae are MATa (pronouce a as in day) and MATα (i.e. MAT-alpha).

For convenience you could also refer to the corresponding alleles as MATa or MATalpha (see also here)


There is no problem to transform bacteria with more than one plasmid. The usual methods (either chemical competent cells or electroporation) are working fine, although electroporation might give you better results, as the cells take up more DNA. On the downside you have to make sure that your cells are prepared nicely, otherwise the electroporation cell will produce a short circuit (of course chemically competent cells can be problematic, too).

What you will definitely need are two (or more) different selection markers. The easiest will probably be different antibiotics (something I used in the lab and which works nicely) or other like genes which provide essential substances for the cells. As long as the selection pressure on the cells is held up, both plasmids will stay in the cells, when you take away one of them, the corresponding plasmid will get lost within a few days.

Regarding the efficiency of co-transformations I haven't found any papers. There is however, some data available on factors which influence the effiency of single transformations and I don't see, why these shouldn't be applied for co-transformations as well.

First, there is the size of the plasmid. The bigger the plasmid is, the lower gets the transformation efficiency. The figure from Inoue, 1990 is pretty clear in this point:

So for this reason I would use plasmids as small as possible.

Second, the density at which the growing bacterial culture which is used to prepare the competent cells is harvested has a big influence on the transformation efficiency. Tang and colleagues (1994) found out that growing the cells to a higher density than the classical OD$_{600}$ of 0.6 (which for example Inoue recommends in it paper cited above) is not a very good choice in terms of transformation efficiency. They found an OD$_{600}$ of about 0.94 working much better, see the corresponding figure:

And finally the amount of competing DNA is a big factor. Hanahan, 1983 found out that the transformation efficiency gets lower, the more competing DNA is present:

So I would try to use as little of each DNA to work against this effect.


Can anyone give me the common name of this flower/vine?

I think this is Rosa foetida, the yellow rose. Unfortunately the leafs are not visible very well but the flower, together with the growth, is pretty characteristic. See this image (from here) for comparision:

The German Wikipedia also has a drawing of the plant (from here):


A tiny bit of terminology

Fact

In popular culture, the term fact means "something that is true". I would consider a theory as being the closest concept in science to what is called a fact in the population culture.
In natural sciences, the term fact is rarely used but would have the same meaning than the one in popular culture. The reason we are not often using this concept is that in science (nor in any other field of knowledge) one can never definitely know the truth. We can only have evidence that are congruent with a hypothesis or body of statements. In such case we talk about theory (see below).

Theory

In popular culture, "theory" is used to mean what the natural sciences call a "hypothesis."
In the natural sciences, a theory is a body of thoughts/statements that is very well supported by loads of evidence. In science, a theory is not a hypothesis. For example: Theory of evolution, Theory of general relativity, transition state theory, etc. Note by the way that various definitions of theory are in use (ref.). The below answer respects the definition that I gave above.

The scientific terminology presented above is actually a matter of philosophy and not science. If you need more information about the definitions of "theory", "fact" and other related terms, you may want to ask on Philosophy.SE. Stephen Jay Gould summarized the concepts of theory and facts nicely when saying

  [..] facts and theories are different things, not rungs in a hierarchy of increasing certainty. Facts are the world's data. Theories are structures of ideas that explain and interpret facts.

In the answer below, I am using the scientific terminology.

Your questions

  Is evolution true?

Evolution is what is called a theory in natural science (The Theory of Evolution a.k.a. modern evolutionary synthesis), and it is extremely well-supported. Evolution is NOT a hypothesis. In other words, we have a lot of supporting evidence that living beings have evolved and are evolving.

  Did both humans and chimpanzees evolve from apes?

Humans and chimpanzees are apes (great apes to be more accurate). Both humans and chimpanzees evolved (and are still evolving) from a common ancestor who already was a great ape. We have a lot of evidence to support this common ancestry.

What does the theory of evolution say?

Understanding Evolution (by UC Berkeley) is a short and introductory course to evolutionary biology. Of course, there exist other good sources of information online such as Evolution and the tree of life by Khan Academy.

We have a number of posts providing book recommendations for

General biology (Books for beginners and Introductory biology text for an outsider)
Intro to evolutionary biology (Text Book Recommendation: Organic Evolution and Introductory books about evolution)
Intro to evolutionary genetics (Books on population or evolutionary genetics?)

You will also find a lot of introductory posts on biology.SE such as for examples:

Why do some bad traits evolve, and good ones don't?
Is there a biological mechanism for evolution encoded into our DNA?
Does it make sense to classify all humans in a single species?
Why is a heritability coefficient not an index of how “genetic” something is?
How could humans have interbred with Neanderthals if we're a different species?
If dinosaurs could have feathers, would they still be reptiles?
Why does evolution not make our life longer?
Why don't mammals have more than 4 limbs?
How to define “evolution”?
How did some humans evolve to be white?
Who are humans' closest relatives, after primates?
Did cats evolve from monkeys ? or vice versa?
Why do the ancestors of birds still exist?
How does Natural Selection shape Genetic Variation?

What are the evidence?

Demonstrable and repeatable examples of evolution lists sources that list evidence. There are probably thousands of pieces of evidence listed in total, all explained in lay terms with links to the original article. Of course, this is just a small sample of the evidence we have.

The post Is there any biological evidence that is not suggestive of or seems to disprove evolution? might be of interest too.

Thanks to @CortAmmon's comment for correcting a very poorly phrased sentence.


Why do many people seem to prefer unhealthy compared to healthy foods?

It's a very simple answer. "Unhealthy" foods, for example potato chips, sugary drinks, and other fatty, cheesy or sugary edible items, have only been around a few hundred (at most) years. In prehistoric times (before agriculture, when the primary source of food was hunting and gathering), when food was scarce, fatty and sugary foods would be of great importance. They would supply the body with large quantities of energy (a gramme of fat gives about 9 calories, a gramme of carbs gives around 4 calories). Since we survived mostly on fruits, vegetables, meat, and whatever roots we could find, something as energy rich as, say, a serving of deep fried cheese covered bacon would have sustained us for days. So eating anything with high calorific value, like a fat rich tuber would release 'feel-good' chemicals, like dopamine and serotonin, among others, which make us feel happy (dopamine is also released in response to hugs and accomplishing goals, serotonin is released, in very large quantities, during nicotine consumption).
Our body these days just isn't used to our relatively sedentary lifestyle with  guaranteed food. Our body still hoards fat like it did during our time as hunter-gatherers, and our body still secretes dopamine everytime we dig into a sumptuous serving of cake.
A couple of good sources:
http://www.ncbi.nlm.nih.gov/pubmed/8697046

Serotonin-releasing brain neurons are unique in that the amount of neurotransmitter they release is normally controlled by food intake: Carbohydrate consumption--acting via insulin secretion and the "plasma tryptophan ratio"--increases serotonin release; protein intake lacks this effect. This ability of neurons to couple neuronal signaling properties to food consumption is a link in the feedback mechanism that normally keeps carbohydrate and protein intakes more or less constant. However, serotonin release is also involved in such functions as sleep onset, pain sensitivity, blood pressure regulation, and control of the mood. Hence many patients learn to overeat carbohydrates (particularly snack foods, like potato chips or pastries, which are rich in carbohydrates and fats) to make themselves feel better. This tendency to use certain foods as though they were drugs is a frequent cause of weight gain, and can also be seen in patients who become fat when exposed to stress, or in women with premenstrual syndrome, or in patients with "winter depression," or in people who are attempting to give up smoking. (Nicotine, like dietary carbohydrates, increases brain serotonin secretion; nicotine withdrawal has the opposite effect.)

http://www.scientificamerican.com/article/addicted-to-fat-eating/

Like many pleasurable behaviors—including sex and drug use—eating can trigger the release of dopamine, a feel-good neurotransmitter in the brain. This internal chemical reward, in turn, increases the likelihood that the associated action will eventually become habitual through positive reinforcement conditioning.

http://www.ncbi.nlm.nih.gov/pubmed/8697045

There is an intimate relationship between nutritional intake (eating) and serotonin activity. ...
Traditionally, serotonin has been linked to the macronutrient carbohydrate via the intermediary step of plasma amino acid ratios.

TL;DR:
You would have starved if you didn't eat fatty foods back before we had food so readily available, so your body automatically stocks up in case you ever run out.
Watch this video for more information:
Why our brains love junk food


Where to find the corrected BLOSUM matrices?

Okay, I emailed Dr. Mark Styczynsk (one of the authors) to ask about a link to the matrix. Here are the links he gave me:

http://web.mit.edu/bamel/blosum/revised_blosum.c

http://web.mit.edu/bamel/blosum/original_blosum.c

http://web.mit.edu/bamel/blosum/RBLOSUM64 (isentropic with BLOSUM62)

http://web.mit.edu/bamel/blosum/RBLOSUM62 (not isentropic, but it's 62)

The first link is to the c code to generate the corrected BLOSUM. According to Mark, just replacing the original c file in the original BLOSUM tarball with the revised c file can generate the corrected matrix for any of the BLOSUMs (30, 50, 92). Haven't yet tried that myself.